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Estimation of Soil Erosion for Himalayan Micro-watershed using GIS Technique
Iqbal Hafiz Ganai
(2010-324-D)
Division of Soil Science
Faculty of Post-graduate Studies
Sher-e-Kashmir University of Agricultural Sciences and
Technology of Kashmir
2014
Estimation of Soil Erosion for Himalayan Micro-watershed using GIS Technique
Iqbal Hafiz Ganai
(2010-324-D)
Thesis
Submitted to
The Faculty of Post-graduate Studies Sher-e-Kashmir University of Agricultural Sciences &
Technology of Kashmir in partial fulfillment of req uirement for the award of the degree of
Doctor of Philosophy in Agriculture (Soil Science)
2014
Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir
Division of Soil Science, Shalimar Campus, Srinagar-190025
Certificate – I This is to certify that the thesis entitled, “Estimation of Soil Erosion for Himalayan Micro-watershed using GIS Technique” submitted in partial fulfillment of the requirements for the award of the degree of Doctor of Philosophy in Agriculture (Soil Science), to the Faculty of Post-graduate Studies, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir is a record of bonafide research work carried out by Mr. Iqbal Hafiz Ganai (Regd. No. 2010-324-D) under my supervision and guidance. No part of the thesis has been submitted for any other degree or diploma. It is further certified that information received during the course of investigation has duly been acknowledged.
(Dr. Mushtaq Ahmad Wani)
Chairman Advisory Committee
Endorsed Prof. & Head, Division of Soil Science.
Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir
Division of Soil Science, Shalimar Campus, Srinagar-190025
Certificate – II We, the members of the Advisory Committee of Mr. Iqbal Hafiz Ganai (Regd. No. 2010-324-D), a candidate for the degree of Doctor of Philosophy in Agriculture (Soil Science) have gone through the manuscript of the thesis entitled, “Estimation of Soil Erosion for Himalayan Micro-watershed using GIS Technique” and recommend that it may be submitted by the student in partial fulfillment of the requirements for the award of the degree.
Advisory Committee
Chairman Dr. Mushtaq Ahmad Wani Associate Professor-cum-Senior Scientist,
Division of Soil Science, SKUAST-Kashmir
Members
Dr. M. Auyoub Bhat
Assistant Professor-cum-Junior Scientist, Division of Soil Science,
SKUAST-Kashmir
Dr. K. N. Singh Prof. & Head,
Division of Agronomy, SKUAST-Kashmir
Dr. Showket Maqbool
Assistant Professor-cum-Junior Scientist Division of Agri. Statistics
SKUAST-Kashmir Dean PG Nominee
Dr. M. H. Wani
Professor, Rajiv Gandhi Chair, SKUAST-Kashmir
Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir,
Shalimar Campus, Srinagar-190025
Certificate – III This is to certify that the thesis entitled, “Estimation of Soil Erosion for Himalayan Micro-watershed using GIS Technique” submitted by Mr. Iqbal Hafiz Ganai (Regd. No. 2010-324-D) to the Faculty of Post-graduate Studies, Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir in partial fulfillment of the requirements for the award of the degree of Doctor of Philosophy in Agriculture (Soil Science) was examined and approved by the Advisory Committee and External Examiner on …………………….. Chairman External Examiner Advisory Committee Prof. & Head Division of Soil Science Director Resident Instruction-cum-Dean Post-graduate Studies, SKUAST-Kashmir
Sher-e-Kashmir
University of Agricultural Sciences and Technology of Kashmir Division of Soil Science, Shalimar-190025
Name of the student : Iqbal Hafiz Ganai Registration No. : 2010-324-D Major Subject : Soil Science Minor Subject : Agronomy Major Advisor : Dr. Mushtaq Ahmad Wani
Associate Professor-cum-Senior Scientist Division of Soil Science SKUAST-K, Shalimar
Title of the Thesis : Estimation of Soil Erosion for Himalayan Micro-watershed using GIS Technique
ABSTRACT
Land degradation in the form of soil erosion is worldwide phenomenon leading to nutrient loss and is a major constraint to farming activities and sustainable agricultural development. Thus estimation of soil loss and identification of critical areas for implementation of best management practice is central to success of soil conservation programme. In this study Geographical Information System (GIS) has been integrated with universal soil loss equation (USLE) for the assessment of soil loss at micro-watershed level in the Nilser sub-catchment, Ningle catchment of Jhelum basin in J&K State. The main advantage of GIS methodology is in providing quick information on the estimated value of soil loss for any part of investigated area. The rainfall erositivity R-factor of USLE was found as 334. Soil erodibility K-factor varied from 0.30-0.60 and LS factor ranging from 0-247.82. The C-factor values were computed from existing cropping patterns in the micro-watershed and support practices P-factors were assigned by studying land slope. Average soil loss was calculated to be highest in scrubs and open forest areas associated with moderate steep to steep sloping. The majority area of the micro-watershed is subjected to very low to moderate erosion risk due to low LS factor value and high organic carbon content of soils. The study predicted that 86.9% area has very low, 11.86% area has low to moderate and 1.16% area has moderately high to very high risk of soil erosion in the micro-watershed. In order to assess and investigate soil quality status of study area, a total of twenty nine (29) surface soil samples and six profile samples were taken and examined and analyzed for some morphological and physico-
chemical properties. The morphological characteristics indicated that the colour of the soils had, by and large, similar trend with 10 YR as common hue and have granular to sub-angular blocky surface and sub-angular to angular blocky sub-surface structure. The analysis revealed that soils varied in their texture from loam/silt clay loam at upper zone to silt clay loam/ clay loam at mid and lower zone, also gradual variation in texture was noted with increase in the depth of soil profiles. The pH of micro-watershed was slightly acidic to neutral with normal electrical conductivity and medium organic carbon status. Exchangeable cations were in the order Ca2+>Mg2+>K+>Na+ in all the soil profiles studies. All the macronutrients were found in sufficient range and among macronutrients K was higher in lower zone soils. The results showed that erosion in the study area has a quantifiable effect on most of the chemical and physical properties in the upper, middle and lower zone of the micro-watershed. Land capability classification showed that majority of soils belong to class , II, III and IV lands with limitation of erosion, drainage and fertility. Key words: GIS, USLE, K-factor, LS factor, C-factor, land capability, micro-watershed Signature of Student Signature of Major Advisor Dated: Dated:
ACKNOWLEDGEMENTACKNOWLEDGEMENTACKNOWLEDGEMENTACKNOWLEDGEMENT
All praises to Almighty ALLAH whose blessings helped me in accomplishing the present course programme and billions of peace and blessings of ALLAH be upon HAZRAT MUHAMMAD (PBUH). A formal presentation of mere words is scarcely indicative of my feelings of venerable gratitude and indebtedness of my Major advisor Dr. Mushtaq Ahmad Wani, Associate Professor, Division of Soil Science, SKUAST-Kashmir for his highly invigoratative, imaginative, inspiring and enthusiastic guidance, wise counseling, meticulous suggestions, enduring encouragement, constructive criticism and for developing in me the spirit of an independent research worker. I express my sincere gratitude to Dr. M. Auyoub Bhat, Assistant Professor, Division of Soil Science, for contributing so extensively to my little learning over these years.
I sincerely thank my other Advisory Committee members (Prof. K. N. Singh, Dr. Showket Maqbool and Prof. M. H. Wani) for rendering all kind of help, whenever I needed it. Their sense of involvement during the entire duration of this Ph. D programme is commendable and unforgettable.
I could not fail to mention my deep gratitude to Prof. Tahir Ali, Prof. & Head, Division of Soil Science, who in spite of not being member of Advisory Committee for his consistent encouragement, proficient suggestions and guidance which helped sustain my efforts and interest in the present research activity and unrelenting help. I feel deeply grateful to each of my many inspiring teachers, Dr. Javaid Ahmad Wani and Dr. N. A. Kirmani for all the many lessons that have served me so well in accomplishing this job. I was immensely benefitted by their constructive criticism, words of wisdom and other suggestions distilled from their experience. I may not be genuinely able to express my gratefulness to the other scientific staff from Division of Soil Science, especially Dr. M. A. Dar and Dr. M. A. Malik for their help from time to time. I especially want to thank Mr. Mohammad Rafiq Mir (Brother) of Division Vegetable Science and each staff member and labours of the Division of Soil Science who remained important part of this struggle and deserve equal credit for successful completion of my Ph.D programme. I express my special gratitude to Mr. M. Ismail, Mr. M. Yousuf, Mr. Ali. Mohammad, Mr. Gh. Hassan, Mr. Shabir Ahmad, Mr. Tariq Ahmad, Mr. M. A. Nadaf, Mr. Khazir Mohammad and Mr. Manzoor Ahmad Division of Soil Science for having remained associated with my Ph.D programme both in the on farm and off farm activities. Their sense of caring during all these years is simply unimaginable.
I want to thank all my friends and well wishers; Dr. Talit Majid, Dr. Aflaq Hamid, Dr. Mir Shams-ud-din, Dr. Wasim Ali, Mr. Mumtaz Ahmad, Mr. Mehraj-u-din and many others for their constant encouragement during the entire course of this programme.
I especially want to thank to ARIS, SKUAST-Kashmir for their consistent support and encouragement during the entire course of study. Wherever I have offended people by not succeeding in thanking them individually or collectively, I apologize, but shall always remain indebted to those unmentioned names within or outside this university. On a very personal note, I acknowledge with love my gratitude to my brothers, sisters and all other relatives who on various occasions missed my love and affection during the course of my study. I owe more than I can say to my parents who gave me life and love, good wishes and sustained support. They have always been a source of endless love and a force to lean back upon in all the times- great and difficult, good and bad. No one has worked harder with me in this programme than my better half who is always there for me, whatever be the circumstances.
Dated: Dated: Dated: Dated: ( ( ( (Iqbal Hafiz GanaiIqbal Hafiz GanaiIqbal Hafiz GanaiIqbal Hafiz Ganai))))
CCOONNTTEENNTTSS
CChhaapptteerr PPaarr tt iiccuullaarr ss PPaaggee NNoo..
11 II NNTTRROODDUUCCTTII OONN 0011 22 RREEVVII EEWW OOFF LL II TTEERRAATTUURREE
22..11 SSooii ll eerroossiioonn aanndd ssooii ll lloossss 22..22 SSooii ll lloossss aasssseessssmmeenntt uussiinngg UUSSLLEE 22..33 AAppppll iiccaattiioonn ooff GGIISS ffoorr eessttiimmaattiioonn ooff ssooii ll eerroossiioonn 22..44 IInntteeggrraattiioonn ooff GGIISS aanndd UUSSLLEE iinn aasssseessssmmeenntt ooff ssooii ll lloossss 22..55 PPhhyyssiiccoo--cchheemmiiccaall cchhaarraacctteerriissttiiccss ooff ssooii llss 22..66 AAvvaaii llaabbllee nnuuttrriieennttss 22..77 SSooii ll ssuurrvveeyy ffoorr llaanndd eevvaalluuaattiioonn
0066 0066 0088 1100 1122 1144 2222 3300
33 MM AATTEERRII AALL SS AANNDD MM EETTHHOODDSS 33..11 GGeenneerraall ddeessccrriippttiioonn ooff tthhee ssttuuddyy aarreeaa 33..22 RReeccoonnnnaaiissssaannccee ssuurrvveeyy 33..33 SSeelleeccttiioonn ooff ssaammppllee ff iieellddss 33..44 SSooii ll eerroossiioonn ddaattaa aaccqquuiissii ttiioonn 33..55 SSooii ll qquuaall ii ttyy aasssseessssmmeenntt 33..66 GGeenneerraattiioonn ooff MMaappss 33..77 LLaanndd EEvvaalluuaattiioonn
3344 3344 3388 3388 3399 4433 4455 4466
44 EEXXPPEERRII MM EENNTTAALL FFII NNDDII NNGGSS 44..11 PPhhyyssiiccoo--cchheemmiiccaall cchhaarraacctteerriissttiiccss ooff ssuurrffaaccee ssooii llss 44..22 FFeerrttii ll ii ttyy ssttaattuuss ooff tthhee ssuurrffaaccee ssooii ll ss 44..33 CChhaarraacctteerriizzaattiioonn ooff mmiiccrroo--wwaatteerrsshheedd ssooii llss 44..44 SSooii ll lloossss eessttiimmaattiioonn uussiinngg GGIISS aanndd UUSSLLEE tteecchhnniiqquuee aanndd ssooii ll
eerroossiioonn mmaappppiinngg 44..55 LLaanndd eevvaalluuaattiioonn // LLaanndd ccaappaabbii ll ii ttyy ccllaassssii ff iiccaattiioonn
4477 4477 5566 6611 7799
9933
55 DDII SSCCUUSSSSII OONN 55..11 PPhhyyssiiccoo--cchheemmiiccaall cchhaarraacctteerriisseerrss ooff mmiiccrroo wwaatteerrsshheedd 55..22 SSooii ll ffeerrttii ll ii ttyy ssttaattuuss ooff mmiiccrroo--wwaatteerrsshheedd ssooii ll 55..33 CChhaarraacctteerriizzaattiioonn ooff mmiiccrroo--wwaatteerrsshheedd ssooii ll 55..44 SSooii ll lloossss eessttiimmaattiioonn uussiinngg GGIIss aanndd UUSSLLEE tteecchhnniiqquuee 55..55 LLaanndd ccaappaabbii ll ii ttyy ccllaassssii ff iiccaattiioonn
9955 9955 9977 9999 110055 110088
66 SSUUMM MM AARRYY AANNDD CCOONNCCLL UUSSII OONN 66..11 PPhhyyssiiccoo--cchheemmiiccaall cchhaarraacctteerriissttiiccss ooff mmiiccrroo--wwaatteerrsshheedd ssooii llss 66..22 FFeerrttii ll ii ttyy ssttaattuuss ooff mmiiccrroo--wwaatteerrsshheedd ssooii llss.. 66..33 CChhaarraacctteerriizzaattiioonn ooff mmiiccrroo--wwaatteerrsshheedd ssooii llss 66..44 SSooii ll lloossss eessttiimmaattiioonn uussiinngg GGIISS aanndd UUSSLLEE tteecchhnniiqquuee 66..55 LLaanndd ccaappaabbii ll ii ttyy ccllaassssii ff iiccaattiioonn
110099 109 110 111 112 113
LL II TTEERRAATTUURREE CCII TTEEDD II --XXXXII VV AAPPPPEENNDDII CCEESS
LL II SSTT OOFF TTAABBLL EESS
TTaabbllee NNoo.. PPaarr tt iiccuullaarr ss PPaaggee NNoo..
11 PPaarrttiiccllee ssiizzee ddiissttrriibbuuttiioonn ooff ssuurrffaaccee ssooii llss ooff NNaallaahh KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd
4488
22 PPhhyyssiiccoo--cchheemmiiccaall pprrooppeerrttiieess ooff ssuurrffaaccee ssooii llss ooff NNaallaahh KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd
5533
33 FFeerrttii ll ii ttyy ssttaattuuss ooff KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd ssooii llss 5588 44 SSooii ll ssii ttee ddeessccrriippttiioonn 6622 55 MMoorrpphhoollooggiiccaall cchhaarraacctteerriissttiiccss ooff ssooii ll pprrooff ii lleess ooff NNaallaahh
KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd 6655
66 PPaarrttiiccllee ssiizzee ddiissttrriibbuuttiioonn iinn ssooii ll pprrooff ii lleess ooff NNaallaahh KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd
7722
77 PPhhyyssiiccoo--cchheemmiiccaall pprrooppeerrttiieess ooff ssooii ll pprrooff ii lleess ooff KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd
7755
88 AAvvaaii llaabbllee mmaaccrroonnuuttrriieenntt ccoonncceennttrraattiioonn iinn ssooii ll pprrooff ii lleess
ooff KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd
8800
99 AAvvaaii llaabbllee MMiiccrroo--NNuuttrriieenntt ccoonncceennttrraattiioonn iinn ssooii ll pprrooff ii lleess ooff KKhhuurrssii mmiiccrroo--wwaatteerrsshheedd
8833
1100 SSttrruuccttuurraall aanndd ppeerrmmeeaabbii ll ii ttyy ccooddeess 8899 1111 CC aanndd PP wwaass ccaallccuullaatteedd bbyy uussiinngg LLUULLCC ooff tthhee aarreeaa aanndd
CC aanndd PP ttaabblleess 9911
1122 SSooii ll lloossss aasssseessssmmeenntt 9922 1133 LLaanndd ccaappaabbii ll ii ttyy ccllaassssii ff iiccaattiioonn ooff NNaall llaahh KKhhuurrssii mmiiccrroo--
wwaatteerrsshheedd 9944
LL II SSTT OOFF FFII GGUURREESS
FFiigguurr ee NNoo.. PPaarr tt iiccuullaarr ss AAff tteerr ppaaggee NNoo.. 11 Location Map of Khursi micro-watershed,
district Baramulla, Jammu & Kashmir 3344
11aa Location and extent of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
3344
22 Rainfall curve of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
3355
33aa Sand content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
5500
33bb Silt content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
5500
33cc Clay content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
5500
44aa Soil reaction (pH) of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
5555
44bb EC of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
5555
44cc Organic carbon content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
5555
44dd Calcium carbonate content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
5555
55aa Available nitrogen content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
55bb Available phosphorous content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
55cc Available potassium content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
55dd Available sulphur content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
55ee Available zinc content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
55ff Available copper content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
55gg Available iron content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
55hh Available Manganese content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
6600
66aa Rainfall erosivity factor of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
8866
66bb Soil erodibility factor of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
8877
66cc Slope map of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
8888
66dd Topographic factor of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
8888
66ee Cover and management factor of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
9911
66ff Conservation practice factor of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
9911
66gg Drainage pattern of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
9911
77 Soil erosion risk map of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
9922
88 Land use/Land cover map of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
110055
Chapter-1
INTRODUCTION
Soil is a component of the lithosphere and biosphere system. It is a vital
natural resource supporting life systems and helps in socio-economic development.
Since land degradation is directly proportional to the population as such per capita
cultivable land has declined from 0.32 ha in 1950's through 0.14 by the turn of the
century and less than 0.1 ha by 2020. The challenge, therefore, is not only to increase
productivity on sustainable basis, but also to preserve and maintain soil resource
bases for the posterity. The ability of the land to produce is limited and the limits to
produce are set by soil, climate and landform conditions which are further
characterized by intrinsic characteristics that include agro-ecological settings, use and
management (FAO, 1993a). Therefore, comprehensive account of our land resource
ascertaining its potential and problems towards optimizing land use on sustainable
basis is necessary.
Soil erosion is a complex dynamic process by which productive surface soils
are detached, transported and accumulated in a distant place resulting in exposure of
subsurface soil and sedimentation in reservoirs. It is estimated that out of the total
geographical area of 329 M. ha of India, about 167 M. ha is affected by serious water
and wind erosion. This includes 127 M. ha affected by soil erosion and 40 M. ha
degraded through gully and ravines, shifting cultivation, water logging, salinity and
alkalinity, shifting of river courses and desertification (Das, 1985). Narayan and Babu
(1983) have estimated that in India about 5334 Mt (16.4 t ha-1) of soil is detached
annually, about 29% is carried away by the rivers into the sea and10% is deposited in
reservoirs resulting in the considerable loss of the storage capacity.
1
The entire Himalayan region is afflicted with a serious problem of soil erosion
an drivers, flowing through this region, transport a heavy load of sediment. The
Himalayan and Tibetan regions cover only about 5% of the Earth's land surface, but
supply about 25% of the dissolved load to the world oceans (Raymo and Ruddiman,
1992). In the Himalayan Mountains, as a consequence of loss of forest cover coupled
with the influence of the monsoon pattern of rainfall, the fragile catchments have
become prone to low water retention and high soil loss associated with runoff
(Valdiya, 1985; Rawat and Rawat, 1994). A large-scale deforestation that occurred in
the lower range, known as Shivalik range of Himalayas, exposed the soil on the land
surfaces directly to the rains, during the 1960s. This unprotected soil was readily
removed from the land surface by the combined action of rain (Kothyari, 1996). Most
parts of the Himalayas which represent the foothills of the Himalayas in the northern
and eastern Indian states are comprised of sandstone, shale and conglomerates with
the characteristics of fluvial deposits and with deep soils. These formations are
geologically weak, unstable and hence highly prone to erosion. Accelerated erosion
has occurred in this region, due to intensive deforestation, large-scale road
construction, mining and cultivation on steep slopes. Garde and Kothyari (1987)
reported that the soil erosion rate in the Northern Himalayan region is high (2000 to
2500 t km-2 yr-1).
Universal Soil Loss Equation (USLE) is the most popular empirically based
model used globally for erosion prediction and control. Scientifically, the main
attributor to land degradation is soil erosion by runoff water. Of the world's land
degradation problems, soil erosion is the first order category. Soil erosion by water is
a major problem in mountainous areas with steep slopes. Inappropriate land use in
these areas is likely to accelerate water erosion entailing soil loss and land fertility
decline (Hurni et al., 1996; Liniger and Thomas,1998). Suspension from the eroded
material damages the water quality in downstream areas and its subsequent
2
sedimentation decreases the carrying capacity of water bodies. Therefore, controlling
erosion is crucial to sustain agricultural yields and to reduce environmental damage.
Spatial and quantitative information on soil erosion on a regional scale contributes to
conservation planning, erosion control and management of the environment.
Identification of erosion prone areas and quantitative estimation of soil loss rates with
sufficient accuracy are of extreme importance for designing and implementing
appropriate erosion control or soil and water conservation practices (Shi et al., 2004).
Equally, erosion and sedimentation research and a proper understanding of the
physical processes are important in order to enhance understanding of landform
development across temporal and spatial scales (Slattery et al., 2002; Wainwright et
al., 2003).
Geographic Information System (GIS), a technology designed to store,
manipulate, and display spatial and non-spatial data, has become an important tool in
the spatial analysis of factors such as topography, soil, land-use/land cover, etc. GIS
provides a digital representation of the catchment, which can be used in hydrologic
modeling. The land surface slope, land-use and soil characteristics can be extracted
using this technique. Remote sensing and GIS techniques have become valuable tools
specially when assessing erosion at larger scales due to the amount of data needed
and the greater area coverage. For this reason use of these techniques have been
widely adopted and currently there are several studies that show the potential of
remote sensing techniques integrated with GIS in soil erosion mapping (Pilesjo,1992;
Mettemicht and Fermont,1998).
In the recent past, concept of watershed based holistic development has
emerged as one of the potential approaches in rain-fed areas, which can lead to higher
productivity and sustainability in agricultural production. Different measures are
adopted and executed carefully in each of topo-sequences according to their
capability. The sustainable development of a region need not only protection and
3
reclamation of natural resources particularly soil and land, but also a scientific basis
for the management in harmony with environment. These resources should be
managed in a sustainable manner so that the changes proposed to meet the needs of
development are brought out without diminishing the potential for their future use
(Kanwar, 1994). While studying the characterization and soil resource mapping of
Moolbari watershed, Shimla, Walia et.al. (2010) reported that the soils are rich in
organic matter and are slightly to strongly acidic in reaction. The distribution of soils
in the watershed is related to physiography, land use/land cover, slope and aspect.
Soil erosion has long been a serious problem in Kashmir valley especially in
highlands like other Himalayan regions. The high potential soil erosion by water is
observed in the sloping Kerawas and hilly tracts of the Liddar valley basin where the
rate of soil loss has been estimated as 10.5 tons ha-1 yr-1 to 34.5 tons ha-1 yr-1 (Shakeel
and Kanth, 2009). The high degree of potential erosivity in Kashmir valley has lead
to the net nutrient depletion and severe soil health loss. However, detailed
information about the amount of soil loss and its severity on agricultural land and soil
health, soil quality and soil fertility status of any specific area in Kashmir valley has
not been studied and documented. As such detailed area specific study could help in
imagine the severity of the soil erosion problem of the larger segment in the region.
Keeping these considerations in view, an investigation was undertaken in
Nilser (N2) sub-catchment under Ningle catchment (1EN). The Ningle catchment of
District Baramulla falls within the latitude and longitude of 34° 9' to 34° 13' N and
74° 22' to 74° 27'E, respectively. The catchment has two sub-catchments viz.
Khilanmarg (N1) and Nilser (N2). Nilser (N2) sub-catchment has two watersheds viz.,
N2a and N2b. Micro-watershed Khursi Nalla (N2a2) falls under watershed N2a having
almost all land uses was selected to undertake study with the following objectives:
4
� Integration of GIS (Geographical Information System) and USLE (Universal
Soil Loss Equation) for quantifying the magnitude of soil loss.
� To study the effect of soil erosion on soil quality.
� To assess the land evaluation of the study area
5
Chapter-2
REVIEW OF LITERATURE
Review of literature to present investigation entitled, “Estimation of Soil
erosion for Himalayan Micro-Watershed using GIS Technique” has been broadly
discussed under following headings:
2.1 Soil erosion and soil loss
2.2 Soil loss assessment using USLE
2.3 Application of GIS for estimation of soil erosion
2.4 Integration of GIS and USLE in assessment of soil loss
2.5 Physico-chemical characteristics of soils
2.6 Available nutrients
2.7 Soil survey for land evaluation
2.1 Soil erosion and soil loss
Accelerated soil erosion is a man induced process that causes serious damages
to agriculture wherever it is not effectively controlled (Toy et al., 2002). Accelerated
soil erosion has adverse economic and environmental impacts (Lal, 1998). The
normal rate of erosion under natural vegetation is, however, in approximate
equilibrium with the rate of soil formation (Troeh et al., 1999). Problems arise when
the natural process of soil erosion is accelerated due to human interventions that
result in deviations from the equilibrium. Among the different human activities that
accelerate soil erosion processes, agriculture is the most important and most soil
erosion occurs on cultivated lands (Hudson, 1996).
6
While studying the degradation status of Jammu and Kashmir soils,
Mahapatra et al. (2000) observed that the soil degradation problems are mainly due to
water erosion, wind erosion and partially due to flooding and water logging. About
31 per cent of the area of the state is under various forms of degradation and 57 per
cent is unfit for agriculture due to rock out crops, ice caps and glaciers. The rest area
of 12 per cent constitutes arable land, stable under natural conditions.
Nyle and Ray (2002) reiterated that soil erosion by water is fundamentally a
three-step process involving the detachment, transportation of the detached particles
downhill by floating, rolling, dragging, and splashing and deposition of the
transported particles at some place lower in elevation. The water erosion process
consists of discrete stages from rain drop impact to the formation of gully erosion.
Each stage has its own processes and characteristics. Controlling or preventing water
erosion requires an understanding of each step in the erosion process (Sharyn and
Clerk, 2006)
The lowest soil loss is estimated on flat plains (< 2% slope) about 1.59 tons
ha-1 yr-1, which is less than the minimum tolerable soil loss (2 tons ha-1 yr-1) for the
country. However, the highest soil loss is from steep slopes (30-50%) which is 35.43
tons ha-1 yr-1, about twice the maximum tolerable soil loss (18 tons ha-1 yr-1). The
average soil loss rate at watershed level is 9.63 tons ha-1 yr-1 about half of the
maximum tolerable soil loss. The implication is the contribution of the implemented
SWC measures in decreasing the rate of soil erosion is encourageable as compared to
the results related to high soil loss estimated in the past studies i.e., before massive
SWC implementation (Brhane and Makonen, 2009).
Five soil series have low rates of soil loss, i.e. Tebok, Lating, Bungor, Kekura
and Gong Chenak series, having an average soil loss of 0.65, 0.10, 1.61, 4.23 and
0.53 tons ha-1 yr-1, respectively. Two soil series have moderate rates of soil erosion
namely Serdang and Prang series (average of 47.41 and 41.10 tons ha-1 yr-1,
7
respectively). Two soil series with moderately high rates of soil loss are Kuala Brang
and Rasau soil (average of 57.16 and 57.93 tons ha-1 yr-1, respectively). Malacca
Series has high rate of soil loss, ranges from 21.44 to 348.7 or average of 130.26 tons
ha-1 yr-1. Kedah soil series has very high soil loss, ranges from 79.99 to 319.75 or
average of 180.49 tons ha-1 yr-1. This high erosion rate is expected to generate higher
sedimentation rate into the Tasik Chini water body, elevating the lake fills and
eventually forming an extinct lake (Mir et al., 2010).
Shakeel and Kant (2009) assessed erosion hazards of liddar river basin in
Kashmir Himalayas reported that about 56 per cent of the study area is subjected to
high potential soil loss. In sloping kerawas and hilly tracts, high degree of potential
erosivity with an estimated soil loss as 10.5 to ha-1 yr-1 to 34.5 tons ha-1 yr-1 was
observed. Low to moderate potential erosion varying between 1.54 tons ha-1 yr-1 to
10.5 tons ha-1 yr-1was observed in flat topped kerawas and alpine pastures.
2.2 Soil loss assessment using USLE
The factors that most influence soil erosion are linked to topography,
vegetation type, soil properties and land use/cover. Average annual soil losses were
calculated by multiplying five factors: R; the erosivity factor, K; the soil erodibility
factor; LS, the topographic factor; C, the crop management factor and P; the
conservation support practice. The annual soil loss predictions range between 0 and
61tons ha-1. Average soil loss was highest (26 tons ha-1 yr-1) in agriculture area and
lowest soil loss rate was found in forest area (0.99 tons ha-1 yr-1).
For horticulture and plantation the soil loss rates were 1.47 and 5.39 tons ha-1
yr-1, respectively. For pasture, fallow and scrub the soil loss rates were 25.47, 28.39
and 35.76 tons ha-1 yr-1, respectively (Shiekh et al., 2011) The rainfall erosivity R-
factor of USLE was found as 293.96 and the soil erodibility K- factor varies from
0.325 - 0.476. Slopes in the catchment varied between 0 and 83% having LS factor
8
values ranging from 0 - 6.7. The C factor values were computed from existing
cropping patterns in the catchment and support practice factors were assigned by
studying land slope. Average annual soil erosion at micro-watershed level in Konar
basin having 961.4 km2 areas was estimated as 1.68 tons ha-1 yr-1. Further, micro-
watershed priorities have been fixed on the basis of soil erosion risk to implement
management practices in micro-watersheds which will reduce soil erosion in Konar
basin (Shinde et al., 2010).
The process of soil erosion is determined and influenced by a combination of
different factors. Wischmeier and Smith (1978) developed a soil loss equation
(Universal Soil Loss Equation) containing six main factors. Each factor is influenced
by a number of other factors. The equation is one of the best-known and most
comprehensive models in terms of data, for predicting soil erosion. The USLE is a
long-term model, i.e. it predicts long-term mean values for erosion. It is not intended
for application to individual events. It allows assessing soil loss from agricultural
fields in specific conditions. The USLE according to Wischmeier and Smith (1978) is
formulated as follows:
A = f (R, K, L, S, C, P)
Where;
A = computed annual soil loss in tons ha-1 yr-1.
R = Rainfall erosion factors (rainfall erosivity), to account for the erosive
power of rain, related to the amount and intensity of rainfall over the year. It is
expressed joules m-2.
K = Soil erodibility factor to account for the soil loss rates in tons ha-1 per
erosion index units for a given soil as measured on a unit plot, defined as a plot
22.1m long on a 9% slope under a continuous bare cultivated fallow. It ranges from
9
less than 0.1 for the least erodible soils to approaching 1.0 in the worst possible case
Expressed in tons m-2.
LS = A combined factor to account for the effects the length and steepness of
the slope, LS = 1.0 on a 9% slope, 22.1m long
C = A combined factor to account for the effects of vegetation cover and
management techniques. These reduces the rate of soil loss, so in the worst case,
where the soil is bare and no management is being applied C=0.1. In the ideal case,
where there is no loss occurring, C would be zero.
P = Physical protection factor, to account for the effects of soil conservation
measures. In this context “conservation defined as structures or vegetation barriers
spaced at intervals on a slope, as distinct from continuous mulches or improved
cultural techniques, which recover under the management techniques.
2.3 Application of GIS for estimation of soil erosion
Samad and Abdul Patah (1997) conducted study on soil erosion and
hydrological regime in the Bakum Dam catchment area, Sarawak using remote
sensing and geographical information system (GIS). During this study, the current
and potential erosion risk maps of the study area were generated useful for planning
the land clearing activities at Bakum and estimating the seventy of soil sedimentation
in the dam area.
Dwivedi et al. (1997) conducted studies on the nature, extent and magnitude
of soil erosion in India using land sat MSS, TM and IRS-IA LISS II data. Three
categories of eroded lands, namely nil to slight, moderate, and severe to very severe
were identified.
Jain et al. (2001) used GIS technique for estimation of soil erosion in a
Himalayan watershed. In this study, authors concluded that GIS platform gives output
10
maps that can be understood better and hence can be used as an ideal tool for
developing land use management strategies to reduce soil loss.
Jain and Goel (2002) while working on catchment properties responsible for
soil erosion in Ukai Reservior located on the river Tapi Gujarat, India used GIS
system to evaluate topography and morphology related indices. An integrated effect
of all the parameters was evaluated to find different areas vulnerable to soil erosion.
Sharma and Sharma (2003) reported that the information obtained through
remote sensing and GIS technique helps in better understanding of geographical
location, distribution of quality land in the watershed’s and prioritization of critical
areas for the soil and water conservation treatments.
Yang et al. (2003) used a GIS based RUSLE model to study the global soil
erosion potential for viewing the present situation analyzing changes over the past
century and projecting future trends with reference to global changes in land use and
climate. The current soil erosion potential was estimated to be about 0.38 mm year-1
for the globe, with Southeast Asia found to be most seriously affected region in the
world. The authors concluded that nearly 60% of present soil erosion is induced by
human activity with developments of cropland further increasing the percentage by
about 17%.
Deshmukh et al. (2007) reported that GIS technique was found useful for
discritization of the catchment into small square grids and extracting spatial
information of the catchment, which was used for deriving model input parameters.
The authors concluded that GIS platform gives output maps that can be understood
better.
Yuskel et al. (2008) used remote sensing and GIS technology for erosion risk
mapping of Kartalkaya Dam watershed in Kahramanmaras, Turkey based on the
methodology implemented in coordination of information on Environment
11
(CORINE) model. The result indicated that 33.82%, 35.44% and 30.74% of the study
area were under low, moderate and high actual erosion risks, respectively. It was
concluded that CORWE model integrated with RS and GIS technologies has great
potential for producing accurate and inexpensive erosion risk map in Turkey.
Meiaraj and Sundararajan (2009) while studying soil erosion of Alanthurai
watershed of Tamil Nadu represented the estimated soil loss values pictorially using
Arc view 3.2a version of GIS software. From the thematic map it was concluded by
the authors that around 25% of the land areas along the watershed are subjected to
high and very high erosion.
Saravanan et al. (2010) conducted study on soil erosion maping of Katteri
watershed using USLE and GIS. During this study, authors confirms that remote
sensing and GIS provide promising tools for evaluating and mapping soil erosion risk
in Katteri watershed.
Kumar and Kushwaha (2013) implemented RUSLE-3D model in GIS for
predicting soil loss and illustrated the use of GIS technology in quantitative spatial
modeling of soil erosion to predict soil loss potential and to identify area of high
erosion risk for soil conservation measures in the Shivalik sub-watershed.
2.4 Integration of GIS and USLE in assessment of soil loss
The USLE has been used / integrated with Geographical Information System
(GIS) to estimate soil erosion because GIS helps users manipulate and analyse the
spatial data easily, and it also helps users identify to spatial locations vulnerable to
soil erosion (Yitayew et al., 1999; Ouyang and Barthalic, 2001; Lufafa et al., 2002).
Jain et al. (2001) used GIS technique for estimation of soil erosion in a
Himalayan watershed. In the study, two different soil erosion models, i.e., the
Morgan model and USLE model, were used to estimate soil erosion. Parameters
12
required for both models were generated using remote sensing and ancillary data in
GIS mode. The soil erosion estimated by Morgan model was within limits reported
for this region and soil erosion estimated by USLE gave a higher rate.
Deshmukh et al. (2007) integrated GIS with modified USLE for the
prediction of storm sediment yield from the Banha catchment of upper damodar
valley in Jharkhand state. Using modified USLE, the sediment yield for each
discretized grid cell of the catchment was computed. GIS technique was found useful
for discretization of the catchment into small square grids. GIS platform gives output
maps that can be better understood.
Meiaraj and Sundararajan (2009) while studying the soil erosion status of
Alanthurai watershed in Tamil Nadu by using USLE and GIS found that the forest
covered western parts and the vegetation covered, lesser land slopy eastern region are
subjected to low erosion.
Yadav and Sidhu (2010) while addressing the soil erosion in Himachal
Pradesh through USLE and GIS divided annual soil loss into seven erosion losses and
thus final soil erosion map was generated and area under each class was determined.
It was concluded by authors that more than 10% area experienced extremely severe
erosion (780 t ha-1 yr-1), while 28.41%, 9%, 7.40% and 5.74% of total geographical
area experienced slight (5-10 t ha-1 yr-1), moderate (10-15 t ha-1 yr-1), severe (20-40 t
ha-1 yr-1) and very severe (40-80 t ha-1 yr-1) erosion respectively.
Saravanan et al. (2010) while studying soil erosion assessing and mapping of
Katteri watershed using USLE and GIS reported that GIS was used for determination
of the soil loss from the catchment and surface erosion in the individual cell was
determined using USLE model, which is cost and time effective analysis.
Deka et al. (2011) during their study to assess soil loss and to map the
erosional soil loss in Ghiladhari watershed of the northern Brahmaputra valley by
13
using USLE and ARC/INFO GIS reported that 37.44%, 18.96%, 6.14%, 20.295,
8.12% and 9.05% of watershed areas were under slight erosion, moderately slight
erosion, moderate erosion, moderately erosion, severe erosion and very severe
erosion respectively.
Kumar and Kushwaha (2013) conducted studies on the modeling soil erosion
risk based on RUSLE-3D using GIS in a shivalik sub-watershed. The study
demonstrated that RUSLE-3D model with GIS serves robust and vital tool in
identifying spatial distribution of soil erosion risk area in the watershed for soil
conservation planning. The study predicted that 15% area have moderate to
moderately high and 26% area has high to very high risk of soil erosion in the sub-
watershed.
2.5 Physico-chemical characteristics of soils
2.5.1 Particle size distribution
The texture of the soil cannot be easily altered, it is considered as the basic
property of a soil. The mineral particles of a soil are separated into various groups on
the basis of their size, which are referred to as soil separates. Sand fractions have low
water holding capacity with low organic matter level but possess high infiltration and
drainage having their effect on aeration. Comparatively to clay fractions which have
high nutrient storage capacity and high water holding capacity. While as silt fraction
has medium properties. Thus their proportions will highly influence various
properties of soil.
The dominant soil texture of Kashmir soils ranges from clay loam to silt loam
(Handoo, 1983). The texture of apple orchard soils in Himachal Pradesh was reported
in the range of sandy loam to clay loam (Sharma and Bhandari, 1992). Mushki (1994)
reported that texture of apple orchard soils of Kashmir valley ranged from silt loam to
clay loam, while Peer (1994) observed texture of soils of Kashmir as loam to clay
14
loam. Najar (2002) reported that texture of high altitudes Karewa and valley basin of
Kashmir valley were found medium to moderately find and moderately fine to fine
texture with translocation of clay and its subsequent deposition on lower horizon.
Mahapatra et al. (2000) observed that sub humid soils of Kashmir region vary
greatly in texture from loamy Skeletal (mostly on steep slopes) to silt clay loam and
clay loam (in plains and karewas). The texture of Pattan Karewa of district Baramulla
ranged from loam to clay loam with silt showing decreasing trend and clay increasing
trend with depth (Kirmani, 2004).
2.5.2 Soil reaction (pH)
The pH of the soil being mostly outstanding characteristic of the soil
influences the nutrient availability, microbial activity and other soil physical
properties. Verma et al. (1990) observed that pH in the surface soils of Kashmir
valley was 5.6-6.0 with a slight increase in sub-horizons in Duksum and Yus
location. The pH varied from 6.5-6.7 in the apple orchard soils of Kashmir (Mushki,
1994). Wallia and Rao (1996) reported tendency of pH to increase with depth. Soil
reaction of apple growing area of Kashmir valley was slightly acidic to slightly
alkaline and there was gradual increase in pH with depth (Najar, 2002; Ahmed,
2003). Kirmani (2004) observed slightly acidic to alkaline pH in Pattan Karewa soil
of district Baramulla with lower pH in surface horizons.
2.5.3 Electrical conductivity
Electrical conductivity in surface and surface layers of apple orchard soils of
Kashmir ranged from 0.15-0.39 d Sm-1 and 0.10-0.43 d Sm-1, respectively (Mushki,
1994). While studying almond orchard soils of Kashmir, Mir (1994) reported that the
electrical conductivity of surface soils varied from 0.14-0.35 whereas in subsurface
soils it varied from 0.1-0.36 d Sm-1.
15
While characterizing the orchard soils of Kashmir, Najar (2002) observed that
the electrical conductivity values of surface soils ranged from 0.12 to 0.32, 0.18 to
0.46 and 0.10 to 0.42 with the mean value of 0.22, 0.31 and 0.24 d Sm-1 in the high
altitudes, Karewa and valley basin soils, respectively and did show significant
relationship with altitude. Kirmani (2001) while characterizing lacustrine soils of
Kashmir valley reported that electrical conductivity values ranges from 0.02 to 0.8 d
Sm-1 in surface soils, while as it ranged from 0.02 to 0.2 d Sm-1 in sub-surface
horizon.
2.5.4 Organic carbon
The organic carbon content varied from 0.54 – 4.83 per cent in Kashmir
valley soils with high content in surface horizons (Handoo, 1983). Mushki (1994)
reported that organic carbon content in apple orchard soils of Kashmir ranged from
0.90 – 3.18 and 0.15 – 2.16 per cent in surface and sub-surface layers, respectively.
According to Farida (1997), the organic carbon content of some bench mark
soils of Kashmir at different altitudes varied from 0.63 to 1.27 per cent.
Khadem and Mermat (2003) observed a varied organic carbon content in the
Argids of Iran. The organic carbon content ranged from 0.50 to 11.7 g kg-1 of soils
which showed a decreasing trend, with depth of the pedon. The organic carbon
content showed a definite relationship with the slope and altitude of the area, besides
the type of vegetation (Sharma et al., 2004). According to Patil and Prasand (2004),
organic carbon varied from 33 to 2 g kg-1 with depth, being higher in surface and sub-
surface horizons. Also topography, slope and type of vegetation showed a definite
relationship. Singh et al. (2006) observed that organic carbon was higher in surface
layers as compared to sub-surface layers. Najar et al. (2009) while studying the effect
of aspect and slope on some apple orchards, soils of valley, observed higher content
of organic carbon in northern facing pedons as compared to southern facing pedons.
16
The organic carbon content in saffron growing soils of Kashmir was found
higher in northern aspect pedons than the southern facing pedons. Also it decreased
with the increase in soil depth in both the aspects (Bhat, 2010). The organic carbon
content of Dara Micro-watershed in Kashmir varied from 1.01 to 2.93 per cent with
higher contents observed in locations facing northern aspect than the locations facing
southern aspect (Anjum, 2012).
2.5.5 Calcium carbonate
Subbaiah and Manickhem (1992) observed that CaCO3 content varies from
0.5 to 48.2 per cent and increase with depth. Also soils derived from lime charged
granite-gneiss, lime-charged shale’s show higher CaCO3 content, while as soils
derived from granite shows least CaCO3 content.
Wani (1994) reported 1.00 to 5.50 per cent calcium carbonate in Karewa soils
of Kashmir. The calcium carbonate content varied from 0.20 to 0.40, 1.40 to 1.90 and
0.5 to 0.80 per cent in high altitude, Karewa and valley basin soils of Kashmir,
respectively (Farida, 1997).
Singh et al. (2000) reported that upland soils have no free calcium carbonate
while it ranged from 2.8 to 8.2 per cent in low land soils of Soan basin (Bihar).
Ahmad (2003) reported the increasing trend of calcium carbonate with the
increasing depth of soil. Kirmani (2004) reported 0 to 1.40 per cent CaCO3 in surface
and 0 to 17.80 per cent CaCO3 in subsurface horizon of the pedons in lacustrine belt
of Kashmir valley.
The CaCO3 was not found in the surface horizons of my profile studied.
However, as compared to surface horizons, traces to 7 per cent was observed in
subsurface horizons (Bhat, 2010). The CaCO3 content varied from 0.0 to 1.1 per cent,
0.0 to 1.7 per cent and 0.0 to 0.57 per cent in high, mid and low altitudes,
17
respectively. Subsurface horizons showed higher content of CaCO3 as compared to
surface horizons (Anjum, 2012).
2.5.6 Cation exchange capacity
The CEC value did not follow any definite trend with depth (Kaishta et al.,
1990; Verma et al., 1990; Sahu and Patnaik, 1990; Nirmalayabala and Sahu, 1993).
The increase in CEC values with increase in altitude have been reported by
Singh and Ahuja (1990). Verma et al. (1990) in a study of the soils under forests of
Kashmir valley found that CEC values under different profiles at different slopes
ranged from 2.90 to 28.20 cmolc kg-1 at 0-15 cm depth. Farida (1997) observed that
CEC estimates ranges from 14.00 to 18.20 cmolc kg-1 in some karewa soils of
Kashmir valley. Rao et al. (1997) found CEC varying from 0.71 to 0.99 cmolc kg-1 in
some soils of Himachal Pradesh.
Najar (2002) reported that CEC of surface and subsurface Karewa soils of
Kashmir valley ranged from 14.20 to 23.4 cmolc kg-1 and 13.60 to 26.80 cmolc kg-1
respectively. Ahmad (2003) during his study in orchard soils of Barmulla district,
observed CEC between 16.6 and 20.8 cmolc kg-1 and 18.98 and 20.52 cmolc kg-1 in
surface and subsurface soils, respectively.
The CEC of 11.20 to 14.10 cmolc kg-1 was found in Charar-e-Sharief
watershed which corresponds to the clay content in the respective horizons (Wani, et
al., 2009). Anjum (2012) reported that CEC of Dara micro-watershed soils of
Kashmir valley ranged from 11.52 to 18.23 cmolc kg-1 and observed slight variation
in CEC with altitude.
2.5.7 Bulk density
Gupta and Verma (1975) reported that the sand stone profiles of Kdhampur
district has higher bulk density due to dominance of sand fractions. Besides low bulk
18
density was attributed to high content of organic matter, heavy soil texture and
presence of CaCO3 in soils developed from blue clay and lime stone.
According to Unger and Mallale (1980), bulk density of the tillage layer is
normally lower in ploughed soils than unploughed soils. However with increase in
the amount of residues, bulk density decreases. Sambyal and Sharma (1986) in their
study of lower Himalayas eroded forest soils found that bulk density ranged from
1.36 to 1.54 g cc-1 with highest value for entisols. They also found that bulk density
varied from 1.08 to 1.74 g cc-1 at 170 to 650 m altitude. The bulk density was
negatively correlated with organic carbon. Sharma et al. (1993) while doing
characterization of Soan river valley soils of lower shiwaliks in Himachal Pradesh
reported higher values of bulk density which were in line with the findings of
Sambyal and Sharma (1986) and were attributed to low organic carbon content and
more proportion of coarse fractions.
Alvaro Pires et al. (1997) used the concept of relative bulk density as a
measure of the effect of management of soil compactness for comparing the soil with
different inherent characteristics (texture and organic matter). It was found that bulk
density was related with clay and organic matter. The bulk density for the highest
organic matter content valued from 0.82 to 1.71 g cc-1. Sharma et al. (1997) while
studying two command areas of Assam reported that bulk density increases with clay
content. The increase in bulk density was also reported by Verma et al. (1990) for
chaur land soils of North Bihar.
The bulk density of alluvial soils of Kashmir valley ranged from 1.21 to 1.67
g cc-1. Khan (2003), Mir (1999) while studying the erodibility of the soils of Pohru
watershed under different land uses and slopes observed that the values of bulk
density are in the increasing order of forest < pasture < arable land use soils. The
higher bulk density in soil of Shikohpur watershed of Gurgaon district, Haryana was
19
due to their course texture and in some cases the presence of calcium carbonate and
low organic matter content (Sittanggang et al., 2006).
2.5.8 Exchangeable bases
2.5.8.1 Exchangeable calcium
The exchangeable calcium in some saffron growing soils of Kashmir ranged
from 12.5 to 17.1 and 13.7 to 18.0 cmolc kg-1 with mean values of 14.8 and 15.9
cmolc kg-1 soil in surface and subsurface layers, respectively (Wani, 1994). Mushki
(1994) found that exchangeable calcium in apple orchard soils of Kashmir ranged
from 6.20 to 16.80 and 5.60 to 18.0 cmolc kg-1 soil in surface and subsurface layers,
respectively. Peer (1994) observed that exchangeable calcium was a dominant cation
varying from 12.96 to 15.10 cmolc kg-1 in the soils of Kashmir. Sidhu et al. (1999)
observed exchangeable calcium varied from 2.3 to 3.6 cmolc kg-1 and did not
exhibited any trend with the increase in soil depth.
Average calcium content was 6.85 and 8.4 cmolc kg-1 in surface and
subsurface layers, respectively (Kirmani, 2004). Wani et al. (2009) observed higher
amounts of calcium ions occupying exchangeable sites in micro-watershed of Tasri-
shrief in Budgam district of Kashmir valley. Anjum (2012) while working on Dara
micro-watershed soils of Kashmir reported that exchangeable calcium varied from
7.0 to 9.25 cmolc kg-1 and 5.11 to 10.41 cmolc kg-1 soil in high and low altitude soils.
2.5.8.2 Exchangeable magnesium
Mushki (1994) found that in high altitude, Karewa and valley basin soils of
Kashmir, the exchangeable Mg content varied from 0.80 to 9.20, 5.0 to 10.0 and 1.80
to 5.01 cmolc kg-1 soil, respectively. Wani (1994) reported that the exchangeable
magnesium in saffron growing soils of Kashmir ranged from 1.5 to 2.8 and 1.2 to 3.0
cmolc kg-1 soil in surface and sub-surface layers, respectively. Sidhu et al. (1999)
20
found that two contents of exchangeable magnesium in some soils of Jammu ranged
between 0.4 to 2.0 cmolc kg-1 soil. Ahmad (2003) during his study in apple orchard
soils of district Baramulla reported that the available magnesium content ranged from
140.2 to 178.8 ppm in surface soils and 126 to 188.6 ppm in subsurface soils.
Kirmani (2004) reported that the exchangeable magnesium was found in the range of
1.58 to 2.5 cmolc kg-1 soil and 1.86 to 2.85 cmolc kg-1 soil in surface and subsurface
of lacustrine deposits of Kashmir valley, respectively. Bhat (2010) while studying the
saffron growing soils of Pulwama district of Kashmir valley revealed that the
exchangeable magnesium in surface horizon of north and south facing pedons ranged
from 1.23 to 2.13 and 1.90 to 2.48 cmolc kg-1 soil, respectively. In high, mid and low
altitude soils of Dara micro-watershed of Kashmir valley, exchangeable magnesium
ranged from 1.04 to 2.01, 0.67 to 1.9 and 1.41 to 1.98 cmolc kg-1, respectively
(Anjum, 2012).
2.5.8.3 Exchangeable potassium
In forests soils of Kashmir valley, exchangeable potassium of 0.28 to 1.33
cmolc kg-1 in different horizons was found (Verma et al., 1990). Exchangeable
potassium in the range of 0.0 to 0.5 cmolc kg-1 in different soil pedons of north west
Himalayan region of Himachal Pradesh was observed by Singh et al. (1991).
According to Dandroo (2001) the soils of lower Munda watershed showed
overall range of 0.32 to 0.75 cmolc kg-1 with average value of 0.62 cmolc kg-1.
Kirmani (2004) reported that exchangeable potassium ranged from 0.44 to 0.96 and
0.29 to 1.04 cmolc kg-1 in the surface and sub-surface horizons respectively, of
lacustrine deposits in the Kashmir valley. Najar (2002) reported the average value of
exchangeable potassium as 0.53 cmolc kg-1 in surface soils and 0.46 cmolc kg-1 in
subsurface soils of orchards of Karewa soils of valley. Bhat (2010) revealed that
exchangeable potassium varied from 0.74 to 0.92, 0.76 to 0.95, 0.74 to 0.95, 0.78 to
21
0.92 cmolc kg-1 soil with a mean values of 0.81, 0.89, 0.83, 0.83 cmolc kg-1 soils, in
soils drawn from northern, southern, near level and slopping area, respectively.
2.5.8.4 Base saturation
Gangopadhyay et al. (1998) reported high base saturation ranging from 20 to
88 per cent in rice growing soils of Assam. Kirmani (2004) while characterizing
some karewa soils of Kashmir valley reported that the base saturation varied from
73.5 to 81.1 per cent and 72.1 to 78.7 per cent with the mean of 77.75 and 75.88 per
cent in the surface and sub-surface horizons, respectively. As reported by Tripathi et
al. (2006), the base saturation varied from 58.6 to 66.3 and 56.6 to 74.3 per cent in
surface and subsurface soils, respectively, of Kair-Nagali micro-watershed in North-
west Himalayas.
Base saturation varied from 88 to 95 per cent, higher value of base saturation
was due to predominance of calcite (Wani et al., 2009). Similar findings were
reported by Singh et al. (1991).
The base saturation in high, mid and low altitude soils of Dar micro-
watershed showed an irregular trend with a range of 76.87 to 94.74, 50.12 to 90.37
and 69.87 to 92.11 per cent, respectively (Anjum, 2012).
2.6 Available nutrients
2.6.1 Available macro-nutrients
2.6.1.1 Nitrogen
The available nitrogen in the soil represents the fraction of the total N
available to plants. Verma et al. (1990) found that available N ranged from 36.0 to
205.0 ppm with a mean value of 118.0 ppm in some alluvial soils of Kashmir. The
available nitrogen content of some apple orchard soils of valley varied from 56.0 to
22
140.0 and 22.5 to 117.60 ppm in surface and subsurface horizons, respectively
(Mushki, 1994).
Ganai et al. (1995) noticed that available N content in cherry orchard soils
was in the range of 83.0 to 107.0 and 77.0 to 95.0 ppm in surface and subsurface
soils, respectively. The available nitrogen content of some land forms of Uttar
Pradesh ranged from 95.0 to 159.0 mg kg-1 soil in surface and 51.0 to 159.0 mg kg-1
soil in subsurface horizons (Walia et al., 1996). Dar (1996) while working on cherry
orchard soils of Kashmir noticed the available N content in surface soils ranged from
131.6 to 193.2 ppm, whereas, in subsurface soils it varied from 61.6 to 137.2 ppm.
Khan et al. (1997) reported that available N in some benchmark soils of
Bangladesh varied between 30.0 to 202.0 mg kg-1 soil. Farida (1997) revealed that
surface nitrogen varied from 125.00 to 196.00 ppm and subsurface from 42.00 to
120.00 ppm while studying the wheat soils in Kashmir observed that nitrogen content
was in medium range.
Ganai (2001) reported available nitrogen content in the range of 124.54 to
336.63 kg ha-1 with a mean value of 238.82 kg ha-1 in saffron growing soils of Jammu
and Kashmir.
The available nitrogen content of some orchard soils of Kashmir showed
decreasing trend with depth and ranged from 126.0 to 162.80 ppm (high altitude),
82.0 to 142.1 ppm (karewa) and 182.0 to 150.0 ppm (valley basin) in surface soils
and 50.0 to 98.0 ppm (high altitude), 46.0 to 118.2 ppm (karewa) and 30.10 to 93.0
ppm (valley basin) in subsurface soils (Najar, 2002). Sharma et al. (2008) reported
that available nitrogen in surface soil samples of Amritsar district of Punjab varied
the range of 63 to 170 kg ha-1 with a mean value of 117 kg ha-1.
23
The available nitrogen content of cherry orchard soils ranged between 188.1
top 407.6 kg ha-1 with highest content in surface soils than in subsurface soils (Teli,
2011).
The available nitrogen content in high, mid and low altitudes of Dara micro-
watershed ranged from 121.11 to 348.72, 72.32 to 510.22 and 72.43 to 37.32 kg ha-1,
respectively and decreased with depth (Anjum, 2012).
2.6.1.2 Phosphorus
The available phosphorus in the soil represents a fraction of the total
phosphorus which is susceptible to absorption by plants during their growth. Gupta
(1974) observed that available phosphorus in soils of Jammu and Kashmir varied
from 9.15 to 30.0 ppm. The available P content in surface soils of apple orchards of
Himachal Pradesh varied from 10.5 to 40.5 ppm as reported by Sharma and Bhandari
(1992). Mushki (1994) observed that available phosphorus in some apple orchard
soils of Kashmir ranged from 10.0 to 20.0 and 9.0 to 26.0 ppm in the surface and
subsurface layers, respectively. Mir (1994) while studying almond orchard soils of
Kashmir observed that the available Phosphorus content in surface and subsurface
soil layers ranged from 5.11 to 13.33 and 2.59 to 15.16 ppm, respectively.
Khan et al. (1997) reported that available phosphorus was high in the surface
and decreased downwards in the soil profiles. Antoo (2000) while studying the
command area soils of Zangir found that phosphorus content ranged from 12.90 to
16.70 ppm. According to Najar (2002) the available phosphorus content in apple
growing soils of Kashmir varied from 12.0 to 27.5, 12.0 to 19.10 and 15.0 to 21.50
ppm in high altitude, karewa and valley basin, respectively. The available phosphorus
content of forest soils of Kashmir ranged medium to high (Amarjit, 2004).
Dwivedi et al. (2005) reported that available phosphorus ranged from 2.35 to
25.66 and 2.5 to 137.4 kg ha-1 in the surface soils of leh and kargil districts of Jammu
24
and Kashmir, respectively. Sharma et al. (2008) noticed a range of 9.38 to 84.9 kg
ha-1 averaging to 37.3 kg ha-1 for available phosphorus in the Amritsar, Punjab.
While characterizing and classifying soil resources of Dara micro-watershed,
Anjum (2012) reported that available phosphorus content varied between 12.34 to
23.58, 7.33 to 25.56 and 9.53 to 27.22 4 kg ha-1 in high, mid and low altitudes,
respectively and no particular trend was observed with depth in profile samples.
2.6.1.3 Potassium
The available potassium in soil is generally the sum of water soluble and
exchangeable potassium. Mandal et al. (1990) noticed a range of available potassium
of 47.2 and 289.8 ppm in some forest soils of eastern Himalayas. According to Mir
(1994) the available potassium in some orchard soils of Kashmir varied from 108.44
to 207.75 and 67.32 to 151.84 ppm in surface and subsurface soils, respectively and
observed a decreasing trend in available K content with increase in depth.
Dar (1996) observed that available potassium content in the cherry orchard
soils of Kashmir ranged between 135.0 to 205.0 ppm in surface and from 80.0 to
170.0 in subsurface soils. Awasthi et al. (1998) noticed that available potassium
content in apple orchard soils of Himachal Pradesh ranged from 143.0 to 191.5 ppm.
Aijaz (1999) reported that available potassium varied from 135 to 145, 145 to
180 and 135 to 180 ppm in low, mid and upland soils of South Kashmir, respectively.
The available potassium ranged from 11 to 496 and 103 to 861 mg kg-1 in soil surface
sample of Leh and Kargil districts, respectively of Ladakh region (Dwivedi et al.,
2005).
Wani (2005) while working on the potassium dynamics of some soils of
Kashmir valley reported that available potassium varied from 0.17 to 0.435, 0.141 to
0.179 and 0.120 to 0.230 cmolc kg-1 in high, mid and low altitude soils, respectively.
25
Wani et al. (2007) reported that the soils of Zanigir command area of north Kashmir
were medium in available potassium, ranging from 134-158 mg kg-1.
Nazir and Wani (2009) observed that the plant available potassium in some
soils of Kashmir valley varied from 0.10 to 0.37 cmolc kg-1 soil. Anjum (2012)
reported that available potassium content of soils of Dara micro-watershed varied
from 140.63 to 280.32 kg ha-1, 155.4 to 326.23 kg ha-1 and 183.65 to 320.42 kg ha-1
in high, mid and low altitudes, respectively, and in general its content increased with
depth.
2.6.1.4 Sulphur
In apple orchard soils of Kinnour district of Himachal Pradesh,
available sulphur varied from 6.0 to 45.0 ppm (Singh and Bhandari, 1992). The
sulphate S ranged from 7.2 to 29.4 ppm with a mean value of 14.9 ppm in subsurface
layers of apple orchards in Himachal Pradesh (Sharma and Bhandari, 1992). Tripathi
and Singh (1992) reported a range of 5.5 to 21.2 ppm of available S and a decreasing
trend along with soil depth. Kher and Singh (1993) found that available S content in
the north Kashmir soils ranged between 4.0 to 15 ppm with a mean value of 10.0
ppm. Ganjoo (1994) observed that the sulphate S in mid-hill soils of Jammu region
ranged from 2.80 to 7.10 ppm with a mean value of 4.67 ppm. Agarwal and Singh
(1995) found that the available S content ranged from 0.3 to 75 mg kg-1 soil in the
surface soils while studying low land and upland soils of Bihar Antoo (2000) reported
that available S ranged from 9.20 to 11.10 ppm in soils of Zangeer block district
Baramulla (Kashmir). Wani (2001) found that in surface soils of apple orchards of
north Kashmir, the available S varied from 11.0 to 11.2, 9.5 to 11.0 and 8.6 to 9.7
with mean values of 11.04, 10.34 and 9.12 ppm in high altitude, karewa and low belt,
respectively. Najar (2002), while studying the apple growing soils of Kashmir
reported that available S in high altitude, karewa and valley basin varied between
26
9.90 to 12.10, 9.60 to 11.40 and 9.30 to 11.30 ppm, respectively. Available S content
showed decreasing trend with depth and ranged from 20.16 to 25.68 in sweet cherry
orchard soils of Kashmir (Teli, 2011).
2.6.2 Micronutrients cation distribution
2.6.2.1 Available Zinc
Bhandari and Randhawa (1985) found in orchard soils of Simla that DTPA
extractable Zn content varied from 0.18 to 7.80 ppm and also observed a decreasing
trend with depth of soil. The DTPA extractable zinc in high altitude soils ranged from
0.35 to 0.65 mg kg-1 and was higher than that of Karewa and valley basin soils of
Kashmir (Jalali et al., 1989). Mushki (1994) while studying the nutrient status of
Kashmir soils noticed that the content of zinc ranged between 0.51 to 1.20 ppm.
According to Dar (1996) DTPA-extractable zinc in cherry orchard soils of district
srinagar varied from 0.33-1.82 ppm.
Ganai et al. (2000) reported that DTPA-extractable zinc in some saffron
growing soils of Kashmir was in the range of 0.35 to 1.14 mg kg-1 soil. Sarkar (2000)
observed highest content of DTPA-extractable Cu, Fe, Mn, Zn contents in surface
soil layers and also observed decreasing tendency with increase in soil depth.
Rakshanda (2005) reported that DTPA extractable Zinc varied from 0.37 to 1.20,
0.40 to 0.70 and 0.58 to 0.98 mg kg-1 in the soils of high altitude, karewa and valley
basin, respectively. Anjum (2012) noticed that DTPA extractable zinc content ranged
from 0.24 to 2.34 ppm and in general surface horizons had more DTPA-zinc than
underlying horizons.
2.6.2.2 Available Copper
The DTPA-extractable Cu ranged from 0.07 to 0.33 ppm in some benchmark
soils of Kashmir (Jalali, 1989). Wani (1994) while working with Karewa soils of
27
Kashmir found that DTPA-extractable copper decreased with profile depth and its
content ranged from 0.07 to 0.38 mg kg-1 soil with mean value of 0.20 mg kg-1 in
surface horizon. The DTPA-Cu varied from 0.09 to 0.70 and 0.11 to 0.92 mg kg-1 soil
of Spiti and Kinnaur areas of Himachal Pradesh (Parmar et al., 1999). The available
copper in surface soils of apple orchards varied from 0.82 to 1.27 ppm and in
subsurface soil it ranged from 0.52 to 1.23 ppm, also with the increase in depth a
decrease in copper content was observed (Baba, 2003). Ahmad (2003) reported that
available copper in surface soils varied from 0.82 to 1.27 ppm with mean value of
1.04 ppm whereas in subsurface soils it ranged from 0.52 to 1.23 ppm with mean
value of 0.82 ppm in orchard soils. Rao et al. (2008) reported that DTPA-extractable
copper was found in the range of 0.2 to 1.04 mg kg-1 soil with mean value of 0.58 mg
kg-1 soil in surface soils.
2.6.2.3 Available Iron
The available iron content varied from 9.0 to 84.0 and 2.2 to 62.5 pm with
mean values of 42.0 and 21.3 ppm in surface and subsurface soils of apple orchards
in Himachal Pradesh, respectively (Bhandari and Randhawa, 1985). Jalali et al.
(1989) observed that available iron generally decreased with depth and was higher in
high altitudes and valley basin soils than in karewa soils and the range was 24-124, 6-
116 and 3-21 ppm, respectively. The available Fe content in surface soils of Kashmir
varied from 8.0 to 72.0 ppm with the mean value of 23.0 ppm, whereas in subsurface
soils it varied from 6.0 to 37.0 ppm with mean value of 16.0 ppm (Wani, 1994). Dar
(1996) while working on nutrient status of cherry orchard soils of district Srinagar
found that DTPA-extractable iron in these orchards ranged from 9.9-57.4 ppm.
Ahmad (2003) reported that DTPA-extractable Fe in orchard soils of
Baramulla varied in the range of 42.8 to 58.33 mg kg-1 soil with an average value of
47.79 mg kg-1 soil in surface soils. Available iron was found in higher range in both
28
surface and sub-surface horizons and showed decreasing trend with increasing depth
(Kirmani, 2004). The DTPA-extractable iron in vertisols of Maharashtra was found to
very in the range of 7.85 to 13.99 mg kg-1 soil (Dhale and Prasad, 2009). Anjum
(2012) while characterizing Dara micro-watershed soils of Kashmir observed that
DTPA-extractable iron varied from 32.42 to 50.21 ppm, 30.32 to 66.13 and 33.21 to
46.03 ppm in high, mid and low altitude soils, respectively.
2.6.2.4 Available Manganese
Chadha and Pareek (1993) observed that available manganese in apple
orchards of Himachal Pradesh ranged from 30.1 to 42.8 ppm with a mean value of
36.4 ppm. The DTPA-extractable manganese in apple orchard soils of Kashmir
varied from 19.30 to 28.9 ppm (Mushki, 1994). Dar (1996) noticed that DTPA-
extractable manganese varied from 10.7 to 61.0 ppm in some cherry orchard soils of
Kashmir.
Mamgain et al. (1998) observed that the DTPA-extractable manganese ranged
between 13.5 to 26.9 mg kg-1 in Himachal Pradesh soil. Najar (2002) reported that
available manganese content in apple orchards in Karewa soils varied from 29.0 to
64.0 ppm with the mean value of 44.16 ppm and 7.0 to 48.0 ppm with mean value of
24.66 ppm in the surface and subsurface soils, respectively. Gradual decrease in
manganese content with the increase in soil depth was observed by Kirmani (2004).
Sheikh (2006) while working on Kashmir soils reported that manganese content of
low, medium and high altitude soils had a mean values of 15.33, 25.67 and 17.66
ppm, respectively. The available manganese content in high, mid and low altitude
soils ranged from 38.01 to 48.21 ppm, 28.66 to 49.21 ppm and 33.21 to 46.03 ppm in
Dara micro-watershed of Kashmir, respectively (Anjum, 2012).
29
2.7 Soil survey for land evaluation/land use planning
The results obtained after land evaluation studies of Vidarbha region revealed
that soils fall into capability classes of II, III, IV and VI and were found to be
moderately suitable for cotton, sorghum and pigeon pea (Gabhane et al., 2006)
The tasks of soil survey are description, classification and mapping of soils.
Most countries have organizations charged with the responsibility of carrying out
such studies. The objective of soil survey as defined by Simonson (1952) and Bertelli
(1962) is to characterize, classify soils and to show distribution of soils of an area on
maps so as to i) describe their characteristics particularly with reference to economic
crops, grasses and trees ii) to report on actual use of soil, their adaptation to various
crops and relative productiveness of several soil types iii) to provide reliable
information on which some sort of land management or land treatment programmes.
A soil map with its memoir forms a tool from which the user can inform himself
about the soil conditions at any site without having to go there. An important general
concept in soil resource inventory is that of site specificity (Forbes et al., 1983).
Objective and purpose of soil survey should specify the evaluation level of soil
survey. Land use objectives for which soil resource inventories are used differ widely
in both kind and level of generalization (Cline, 1981). Soil surveys have several
objectives. It should be designed carefully so as to encompass immediate needs and
future purpose as well (Swindale, 1977). Soil Survey Staff (1951) distinguished
detailed basic soil survey, reconnaissance soil survey and exploratory soil surveys
based on the extent of effort made in the field to draw soil boundaries. Kind of
surveys will be according to the purpose or objective of the survey and the level of
information required for making decisions on land use planning. Murthy et al. (1977)
recommended detailed soil surveys using base maps of 1:15,000 or larger scales and
reconnaissance soil surveys using base maps of 1:50,000 giving procedures to map
the soils in our country. In the detailed soil surveys, legend should give phases of
30
different soil classes (soil series) complexes and miscellaneous land types and in
reconnaissance soil surveys, association of soil series or soil classes, their phases or
land types which will be delineated through the process of verification in the field
through observations traverse and correlation. Davidson (1980) observed that in soil
survey, the intensity of sampling is related to the scale of the map to be published, the
objective of the survey, the complexity of the area and the financial and labour
resource of the survey organization. Dent and Young (1981) stated that the
fundamental purpose of land evaluation is to predict the consequences of change.
Prediction is needed on the suitability of the land for different forms of production of
their benefits, and the consequences of such changes upon the environment. They
further stated that as with soil surveys the detailed purposes of land evaluation vary
with the physical, economical and social context, with the scale and intensity of the
study and with the aims of the user. Rourke (1981) stated that with the exception of
the series, all the mapping units in the legend used in detailed soil surveys are not
taxonomic classification. The legend design, or the kinds of mapping units for any
given kind of soil survey is determined by i) the nature and complexity of the soil
pattern ii) the field procedures used to examine the soil and to plot their boundaries
and iii) the purpose of soil survey. The National Bureau of Soil Survey and Land Use
Planning (NBSS and LUP Staff, 1984), in the Memorandum on Soil Correlation
(unpublished) has given map scale and legend relationship to be followed in detailed
and reconnaissance soil surveys in the country. Examples of mapping units and
description that indicate the purity of delineation are also described. Most important
and specific objectives of soil surveys are to interpret the soil properties and
characteristics for various uses (Butler, 1980). This refers to the technical
classification of soils. Soils differing in slope, stoniness, depth and salinity are
applied with a genetic group of limited variation, such classification is very useful
(Papadakis, 1969). The most recent evaluation procedure has been introduced since
31
the mid-seventies by FAO. It is a crop specific suitability system that is based on the
comparison of plant growth and production requirements with prevailing
environmental conditions. Five phases can hereby be distinguished 1) identification
of the land utilization type 2) definition of its growth requirements 3) compilation of
basic climatic, soils and physiological data of the study area 4) matching of those
field data with the crop requirements and 5) determination of the suitability classes on
the basis of the nature and degree of crop growth constraints (Varade et al., 1994).
Morphology, physical and chemical characteristics and land use plans of basaltic trap
representing different landforms in Pratapgarh region of Southern Rajasthan were
studied. The soils at elevated topography were shallow to moderately shallow, clayey
to loamy skeletal and yellowish brown, while at lower topography were deep to very
deep, fine to fine loamy and grayish. The influence of topography had a marked
influence on properties like pH, CaCO3, clay content, vertic properties, cation
exchange capacity and exchangeable cations upto pedon 4, thereafter they were
subdued by local ephaemerals (Sharma et al., 1996). Deshmukh and Bapat (1993)
reported that soils from six different physiographic units were described and their
production potential, coefficient of improvement and nature of improvement
calculated. The study was carried out in an area between 22045' and 23045' N and
77020' and 70040' E in Raisan district, Madhya Pradesh, India. The six soils were; P1
– Pathari (Lithic Ustorthent) on hills, P2 – Piplai (Typic Ustochrept) on plateau, P3 –
Samter (Vertic Ustochrept) in valley, P4-Chickold (Typic Ustochrept) in basin, P5-
Padri (Entic Chromustert) on piedmont alluvial plain and P6 (Typic Ustochrept) on a
dissected flooded plain. Soils P1, P2 and P3 were limited by depth, P4, P5 and P6 by
organic matter, P3, P4 and P5 by texture/structure, P1 and P2 by moisture storage and
P1 and P6 by slope. Soil characteristics and the taxonomy of the shrink-swell soils in
the semi-arid tropical region of India are discussed. A new sub-group of Vertisols,
with a mollic epipedon, is proposed for extensive shrink-swelled soils in Maharashtra
32
(Rajeev Srivastav and Jagdish Prasad, 1992). The present land evaluation
methodology has historically grown from former systems which have gradually been
improved and updated. The main concern hereby is to come to an accurate and
objective assessment system based on clear definitions and sound assumptions
(Shivaprasad et al., 1998). Interpretations of soil surveys carried out in Borai sub-
catchments, Bilaspur district, Madhya Pradesh, under Mahanadi catchment have been
discussed with regard to the land capability, soil and land irrigability and paddy soil
classification. The total area of 22,050 ha was grouped into 15 land capability units
such as II-1, II-2, IIw-1, IIe-1, IIe-2, IIe-1-2, IIIs-1, IIIes-1, Ive-1, Ives-1, Vie-1,
Vies-1-2 and VIIes-1, with a brief description of each unit. The nature and extent of
limitations for each group are discussed (Biswas, 1977). Diwakar and Singh (1994)
reported that the fine textured soils of sedimentary and old alluvial origin are
characterized by uniform colour (brown to very dark grey), mottles of various shades
and intensities, neutral slightly alkaline reaction, low organic carbon and high clay
content and high CEC and SiO2 content. These have developed on varied types of
parent materials at different physiographic levels under basic environment and
impeded drainage. Four typical pedons representing major landforms of Kiar-Nagali
micro-watershed, developed from sedimentary rocks, comprising feeromagnesian
shale and dolomites/dolomitic limestone and occurring at different elevations under
varying land uses were studied by Tripathi et al. (2006) for their morphological
characteristics and physico-chemical properties and suitability for locally preferred
crops. As per Storie’s Index the soil productivity potential of the micro-watershed
area varies from non-agricultural to good. Nagali-I soils were found to be unfit for
cultivation. Nagali-II and Kundla soils had good productivity potential. The land
capability classes ranged from II to VIII. The agricultural land belongs to class II and
III. The lands had limitations of slope and texture.
33
Chapter-3
MATERIALS AND METHODS
The particulars relating to the general description of the area, geographical
setting of the study area viz., geology, climate, natural vegetation, land use, drainage,
altitude, topography, slope, depth, collection and preparation of soil samples and soil
loss and soil quality assessment methods adopted in the investigation are briefly
presented in this chapter under the following headings:
3.1 General description of the study area
3.2 Reconnaissance survey
3.3 Selection of sample fields
3.4 Soil erosion data acquisition
3.5 Soil quality assessment
3.6 Generation of Maps
3.7 Land Evaluation
3.1 General description of the study area
3.1.1 Location and Extent
The selected Nallah Khurshi micro-watershed belongs to Wagoora Block of
Baramulla district (Fig-1). The Nallah Khurshi micro-watershed is located between
34o9’4.9”N and 34o14’3.9”N latitude and 74o22’27.1”E and 74o27’31.6”E longitude.
The average elevation of the micro-watershed is 1700 m above mean sea level (MSL)
with following associated information.
34
Figure 1: Location Map of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
Figure 1a: Location and extent of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
Particulars : Characteristics
Agro-Climatic Zone : Mid to high altitude temperate zone
Agro-Ecological Zone : Temperate, growing periods 150-210 days
Approachable Roads : Baramulla-Baba Reshi
Pothkah-Chandoosa and
Kreeri-Kalantra, Road
Total Geographical Area : 3179.00 ha
Elevation : Max. 2011 m amsl
Min. 1604 m amsl
3.1.2 Geology
The study area covers the Nallah-Khurshi micro-watershed area. The
predominant minerals noticed in the study area are lignite and lime stone and besides
these minerals slate stone also occur.
3.1.3 Climate
The climate of the study is cool temperature with annual precipitation of
about 900 mm. The maximum precipitation is received in the form of snow during
winter. Sub-zero temperatures are recorded from November to January. The rainfall
data (Appendices III) is collected by the Indian Meteorological Station from Gulmarg
station.
3.1.3.1 Rainfall
The rainfall data between year 2000 to year 2012 shows that annual rainfall
varies from 750 mm to 950 mm. The rainfall generally breaks in the middle of March
through May. April and May month’s account for the major share of rainfall. The
monsoon showers breaks in the study area. The highest and lowest rainfall occurred
in the year 2000 and 2003 with annual rainfall of 855 mm and 451 mm, respectively.
35
Figure 2: Rainfall curve of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
3.1.3.2 Temperature
Comparison of temperature data within the time frame considered in this
study i.e., between -5OC to 35OC, shows that summer is extremely hot with July and
August as the hottest months and winter extremely cool with sub-zero temperatures
recorded from November to January. The mean maximum temperatures reaches to
24.5oC in the month of July and mean minimum temperature reaches minus 2.0oC in
the month of January.
SMCS (Soil Moisture Control Section) of micro-watershed area falls under
udic moisture regime with mesic temperature regime.
3.1.4 Natural vegetation
Scattered vegetation constitutes of natural local grasses and naturally grown
hedges/shrubs with predominance of Cynodon dactylon, Dactylis glomerata,
Trifolium pretense are found in the study area. The commonly observed tree species
in the study area are Accacia species, Willow (Salix alba), Popular (Populus alba),
Kiker (Rubinia pseudo-acacia), Chinar (Plantanus orientalis) Walnut, Plum, Pear,
Apricot, Mulberries. These tree species, observed throughout the micro-watershed,
are mostly scattered in the cultivated landscape. There are about 34 ha of community
land grazing and pasture lands scattered in all villages of study area. Due to open
grazing practices in the selected villages, land remains poorly grassed. The
precipitation results in loss of top soil due to erosion and generally these lands are
deteriorated and degredaded.
36
3.1.5 Land use
The total land area of Nallah-Khurshi micro-watershed is 3179.00 ha, of
which 500.00 ha are considered suitable for agriculture. Due to moderately steep
slopes and lack of assured irrigation facilities, limited area of micro-watershed is
under paddy crop. Being predominantly rainfed, maize and wheat (fodder) are
cultivated in the major area of arable lands of the study area.
The micro-watershed receives less than normal rainfall during spring (Kharif)
and few showers are also experienced in Rabi season which are helpful in growing
pulses, oilseeds and forages during the season. Some parts of valley basin of micro-
watershed area were found to be under vegetable cultivation viz., Tomato, Onion,
Knol khol etc. Few parts of micro-watershed are covered by apple orchards (mostly
newly established). Cultivation of maize, M.P Cherry grass etc in orchards is the
common practice in the area. Other horticultural crops Pear, Apricot, Plum are also
grown. Despite the area of land allocated for diverse crop cultivation, yield is
substantially low in most cases because of the soil fertility loss due to erosion and
irregularity of rainfall.
3.1.6 Drainage
Due to moderate slopes to moderately steep slopes surface drainage is good
with sparse/scattered vegetation, the water courses are dry for a greater part of the
year and there is no water lodging.
3.1.7 Altitude
Altitudinally, the Nallah-Khurshi micro-watershed ranges from 1604 to 2011
meter above seas level (masl), but most of the study area falls under 1700 masl.
Based on the variation in altitude, the study area was categorized into uplands,
midlands and lowlands.
37
3.1.8 Topography and slope
The micro-watershed is situated in the North-Southern aspect of the
Himalayan range. The configuration confirms in general to uniform steep slopes. The
steepness of slope ceases towards the lower reaches, entire micro-watershed is
covered with medium to deep gullies. In some parts of micro-watershed, soil and
water conservation structures were constructed by farmers themselves with the
financial and technical assistance provided by the Department of Agriculture.
3.2 Reconnaissance survey
A preliminary field survey has been conducted to get a general view on the
physical condition of the area such as the vegetation cover, land use type, and
topography of the study area. A topographic map, having a scale of 1:50,000 was
used to delineate the catchment boundary (Fig.1). This was followed by a systematic
semi-detailed survey and description of the altitude, cropping history, slope gradient,
management practices, soil attributes (i.e., depth, colour etc), and other factors (table-
4).
3.3 Selection of sample fields
Based on the relative topographic position and the slope conditions, the study
area was classified into three different zones: upper zone, middle zone and lower
zone. Afterwards, sample sites were selected from these zones using homogeneity
criteria of management and cropping history, slope characteristics and conservation
practices (table-4). The altitude and geographical positions in degrees and UTM were
taken using GPS (Global Position System). See table-4 for detailed characteristics of
the sample fields. The cultivated fields selected in the upper zone were in the slope
38
range of 25-35%; in the middle and lower zone were in the slope range of 10-25%
and 0-10% respectively.
3.4 Soil erosion data acquisition
3.4.1. Estimation of soil loss using USLE
Soil loss assessment for the cultivated lands at Nallah Khursi micro-watershed
is based on the Universal Soil Loss Equation (USLE) (Wischmeire and Smith 1978).
According to the USLE, soil loss is the function of six different factors as shown in
the following equation. The preparations of data for input to the equation are
discussed here under:
A= R*K*LS*C*P
Where;
A= Computed annual soil loss rate (tons ha-1 year-1)
R= Rainfall erosivity factor
K= Soil erodibility factor
L= Slope length factor
S= Slope gradient factor
C= Cover types factor
P= Land management and conservation practice factors
3.4.2 Determining USLE factor values
The USLE developed by Wischmeier and Smith (1978) is an erosion model
for prediction of long-term average annual soil loss from specified area in specified
cover and management conditions. The equation predicts losses from sheet and rill
39
erosion only. It computes soil loss for a site as a product of six factors. Soil loss (A)
in tons per hectare per year (t ha-1 yr-1) is computed by the equation:
A=R x K x L x S x C x P
The six factors of universal soil loss equations were computed by standard
methods/equations defined below:
Rainfall Erosivity Factor (R)
Rainfall erosivity (R) is the rainfall factor in Mega Joules-millimeter (MJ-
mm) per hectare-hour-year (ha-hr-yr). It is calculated as the product of storm energy
times the maximum 30 minute storm intensity and summed up for all storms in a
year. The KE of a storm in metric unit is calculated by equation developed by
Wischmeier and Mannering (1969).
In India, rainfall data from 45 stations having self-recording rain gauges were
collected (Ram Babuet al., 1978) and R-factor was calculated. Linear relationships
were established between average annual erosion index (YA) and average annual
rainfall (XA) and seasonal erosion index (YS) and average seasonal rainfall (XS). The
equation developed were as given below:
YA= 79 + 0.363 XA (r = 0.83)
YS = 50 + 0.389 XS (r = 0.88)
The data were collected from Gulmarg station of the state and annual and
seasonal R-values were determined by the above two equations. Based on the R
values of these locations, iso-erodent map of the state was prepared and R-factor of
each grid was taken from this map.
40
Soil Erodibility Factor (K)
Soil erodibility factor is a measure of inherent erodibility of a given soil under
the standard condition of the unit USLE plot, maintained in continuous fallow and
tilled condition. It is measured in unit (t-ha-hr/ha-MJ-mm). It was calculated from
soil erodibility monograph developed by Wischmeier and Smith (1978), by entering
the values of soil texture, organic matter, soil structure and permeability. It can also
be calculated by the equation given below:
100K = 2.1 x 10-4 M1.14 (12-a) + 3.25 (b-2) + 2.5 (c-3)
Where,
M = particle size parameter (per cent silt + % very fine sand) (100-% clay)
a= % organic matter
b= soil structure code (very fine granular, I; fine granular, 2; medium or
coarse granular, 3; blocky, platy, or massive, 4)
c= profile permeability class (rapid, I; moderate to rapid, 2; moderate, 3; slow
to moderate, 4; slow, 5; very slow, 6)
The values were taken from the 586 grids soil data collected by NBSS & LUP
during soil resource mapping of the state.
Topographic Factor (LS)
Slope strength (L) factor is the ratio of soil loss from the field slope length to
that from standard plot (22.13 m) length under identical conditions and slope
steepness (S) factor is the ratio of soil loss from the area with specified cover and
management to that from a 9% slope under otherwise identical conditions. Combined
values of LS factor for different lengths and degrees of slope have been compiled
(Renardet al., 1994) and these were used to obtain LS value for different grids.
41
Cover and Management Factor (C)
Crop cover and management factor (C) is ratio of soil loss from an area with
specified cover and management to that from an identical area in tilled continuous
fallow. It is combined effect of cover, cropping sequence, productivity level, length
of growing season, tillage practices, residue management and the expected time
distribution of erosive rainstorms with respect to seeding and harvesting date in the
locality. The major crop of the region around grid was assigned the value. The values
for different crops have been compiled by Singh et al. (1981) and Wischmeier and
Smith (1978).
Conservation Practice Factor (P)
Supporting conservation practice factor P is the ratio of soil loss with a
specified supporting practice to the corresponding loss with up and down cultivation.
The specified practices include contour cultivation, contour bunding, strip cropping,
terracing and values of these factors have been worked out by different workers and
compiled by Singh et al. (1981) and Wischmeier and Smith (1978).
Generation of Map
The information of 29 grid locations in the study area were collected from the
soil resource data of the state for computation of K, LS, C and P factors. Value of R
factor were calculated for each grid point form the rainfall erosivity map of the state
generated by GIS technique from annual and seasonal rainfall data. The latitude,
longitude and annual soil loss values for all grid points were marked on the map of
study area and soil erosion map was generated using GIS (ARC INFO Ver. 10.1)
technique. Annual soil loss was divided into seven erosion classes on the basis of
range agreed upon at the national level to keep uniformity in the interpretation of data
and, thus, final soil erosion map was generated and area under each class was
determined.
42
3.5 Soil quality assessment
3.5.1 Soil sampling
In order to assess and investigate soil fertility status through the analysis of
some physical and chemical soil properties, soil samples were taken from the study
area. The sample collection targeted on homogeneity criteria of management and
cropping history, slope characteristics and conservation practices of the cultivated
fields (Appendix II). The exact sample location was recorded using GPS (Appendix
II). Twenty nine soil samples were taken from cultivated fields at the upper, middle
and lower zones of the micro-watershed, respectively, at a depth of 0-20cm in case of
field crops and six pit samples, two each at the upper, middle and lower zones, in
case of orchards.
3.5.2 Soil laboratory analyses
Standard laboratory procedures were followed in the analysis of the selected
physicochemical properties considered in the study. The soil samples were air dried,
mixed well and passed through a 2 mm sieve for analysis of selected soil chemical
and physical properties. The procedures adopted for the analysis are as follows:
3.5.2.1 Mechanical analysis
The mechanical composition of soil was determined by international pipette
method as described by Piper (1966).
3.5.2.2 Soil reaction (pH)
The soil pH was determined in 1:2.5 soil: water suspension using glass
electrode pH meter as described by Jackson (1973).
43
3.5.2.3 Electric conductivity
Electrical conductivity was determined using the same soil suspension used
for pH determination (Jackson, 1973).
3.5.2.4 Organic carbon
The Walkley and Black (1934) as modified by Walkley (1935) wet digestion
method was used to determine soil organic carbon content.
3.5.2.5 Calcium carbonate
The free calcium carbonate content of the soil was determined by Rapid
titration method as described by Piper (1966).
3.5.2.6 Bulk density
Soil bulk density of surface samples was determined by the weighing bottle
method and for determining bulk density of profile samples, core sampling method
was adopted.
3.5.2.7 Cation exchange capacity
Cation exchange capacity was analyzed using ammonium acetate method
(Champan, 1965).
3.5.2.8 Exchangeable cations
The exchangeable cations viz., sodium, potassium, calcium and magnesium
were extracted with neutral ammonium acetate. Sodium and potassium were
determined by flame photo-metrically while as, calcium and magnesium were
determined by atomic absorption spectroscopy using atomic absorption
spectrophotometer.
3.5.2.9 Base saturation percentage
It is calculated by using the formula below:-
44
Sum of the exchangeable bases [cmolc kg-1]
CEC [ cmolc kg-1] x 100
3.5.2.10 Available N, P, K and S
Available nitrogen was analyzed using the Kjeldahl digestion, distillation and
titration method as described by Black (1965). Available phosphorus of soil samples
was determined by following method as described by Jackson (1967). Available
potassium was extracted with neutral normal ammonium acetate (pH 7.0) and the
content of potassium in the solution was estimated by Flame photometer (Jackson,
1967). Available sulphur was extracted from the soil using 0.15 per cent calcium
chloride solution and sulphur in solution was determined by turbidometry as outlined
by Black (1965b) using spectrophotometer (Spectronic 20-D) at 420 mm.
3.5.2.11 Micronutrient cation analysis (DTPA-extractable)
The method of Lindsay and Norvel (1978) was used for the estimation of
micro-nutreint cations. Ten grams of soil were shaken for 2 hours with 20 ml of
extracting solution consisting of 0.005 M DTPA (Di-ethylene tri-amine penta-acetic
acid), 0.01 M CaCl2 and 0.1 M TEA (Tri-ethanol amine) buffered at 7.3, the filtrate
was analyzed for zinc, copper, manganese and iron by using atomic absorption
spectrophotometer, after standardizing the instrument with proper standards.
3.6 Generation of Maps
In the present study, two software viz., Image Processing ERDAS (Earth
Resources Data Analysis System) and ARCGIS-10.1 were used for the preparation of
the required database and for analysis of the data for fertility maps. ARCGIS is a tool
used for spatial analysis, tabular databases and conventional GIS characteristics.
ERDAS IMAGINE was mainly used for image processing purpose.
45
3.7 Land Evaluation
The soil survey data was interpreted for land capability classification .The
land capability is mainly based on the inherent soil characteristics, external land
features and environmental factors. The land capability classes and sub classes were
arrived at as per the guidelines in Soil Survey Manual (AISLUS, 1971). The criteria
used for land capability classification are presented in Appendix-I.
46
Chapter-4
EXPERIMENTAL FINDINGS
The result pertaining to the present investigation entitled, “Estimation of soil
erosion for Himalayan micro-watershed using GIS technique” are presented in
this chapter under the following headings:
4.1 Physico-chemical characteristics of surface soils
4.2 Fertility status of the surface soils
4.3 Characterization of micro-watershed soils
4.4 Soil loss estimation using GIS and USLE technique and soil erosion mapping
4.5 Land evaluation / Land capability classification
4.1 Physico-chemical characteristics of surface soils
Soil samples from 29 different sites located in three physiographic zones of
micro-watershed were collected and their results are presented as under:
4.1.1 Particle size distribution
Perusal of date presented in table 1 revealed that upper zone had overall
surface texture of loam to silt loam with a mean values of 3.69 per cent coarse sand,
23.85 per cent find sand, 47.65 per cent silt and 24.33 per cent for clay content. While
as, middle zone had a textural variation from silt loam, sandy clay loam, silty clay
loam to clay loam, with mean values ranged from 3.69 per cent for coarse sand, 23.24
per cent fine sand, 41.27 per cent silt and 31.37 per cent clay. Similarly lower zone
had mean values of 2.41 per cent for coarse sand, 18.62 per cent for fine sand, 43.90
per cent for silt and 34.59 per cent for clay content with silt clay loam to clay loam
surface texture. In general there was gradual increase in clay content with decrease in
altitude. The thematic maps of sand, silt and clay are shown in figures 3a, 3b and 3c.
47
Table 1 : Particle size distribution of surface soils of Nalah Khursi micro-watershed
Zone (m amsl)
Location Elevation (m amsl)
Latitude/ Longitude
Coarse sand (%)
Fine sand (%)
Silt (%)
Clay (%)
Textural Class
Katyawalay 1913 34o11’2.5”N 74o22’47.2”E
3.10 19.70 54.20 22.30 Silt loam
Larey 1910 34o10’35.3”N 74o23’1.6”E
3.10 20.10 53.30 23.50 Silt loam
Gohan 2011 34o10’17.7”N 74o22’27.1”E
3.90 25.30 48.60 21.80 Loam
Larey 1941 34o10’21.9”N 74o22’39.6”E
4.80 26.70 43.90 24.30 Loam
Larey 1959 34o9’52.1”N 74o22’29.0”E
4.50 29.10 41.80 23.30 Loam
Pachhar 1951 34o9’27.6”N 74o22’32.2”E
3.70 25.90 48.10 21.70 Loam
Fakirbagh 1949 34o9’12.6”N 74o22’28.0”E
4.10 28.30 43.00 24.20 Loam
Chandoosa 1910 34o9’4.9”N 74o23’20.9”E
2.30 19.80 51.10 26.10 Silt loam
Chandoosa 1910 34o9’4.9”N 74o23’20.9”E
1.90 20.30 53.10 24.20 Silt loam
Masjid Angan 1939 34o9’33.1”N 74o23’16.4”E
4.10 27.10 44.90 23.10 Loam
Upper Zone (1900-2011)
Vulraman 1920 34o10’2.9”N 74o23’41.8”E
5.10 20.10 42.10 33.10 Silt clay loam
Mean 3.69 23.85 47.65 24.33 --
Contd........
48
Zone (m amsl)
Location Elevation (m amsl)
Latitude/ Longitude
Coarse sand (%)
Fine sand (%)
Silt (%)
Clay (%)
Textural Class
Katawalay 1899 34o10’40.4”N
74o23’11.4”E
2.40 19.30 52.80 24.10 Silt loam
Vulraman 1854 34o10’21.1”N
74o24’23.7”E
5.10 20.10 42.10 33.10 Silt clay loam
Wirnar 1793 34o10’4.8”N
74o24’22.1”E
1.50 18.10 43.70 35.30 Silt clay loam
Wirnar 1796 34o10’6.5”N
74o24’24.5”E
1.50 18.10 43.70 35.30 Silt clay loam
Hudpora 1765 34o10’41.3:N
74o24’30.1”E
6.10 25.40 36.10 32.20 Clay loam
Fresdubh 1756 34o10’37.6”N
74o24’8.8”E
5.30 27.10 35.70 33.10 Clay loam
TakiWagura 1714 34o10’51.0”N
74o24’44.6”E
2.10 16.60 48.70 32.30 Silt clay loam
KhaiTangan 1721 34o11’6.5”N
74o24’15.5”E
6.70 48.30 21.10 23.10 Sandy clay
loam
Middle
Zone
(1700-1900)
Ramzanpora 1700 34o11’12.5”N
74o24’21.8”E
2.50 16.20 47.50 33.80 Silt clay loam
Mean 3.69 23.24 41.27 31.37 --
Contd........
49
Zone (m amsl)
Location Elevation (m amsl)
Latitude/ Longitude
Coarse sand (%)
Fine sand (%)
Silt (%)
Clay (%)
Textural Class
Potkhah 1604 34o143.9”N
74o27’31.6”E
1.20 17.40 45.50 34.90 Silt clay loam
Nowpora Jagir 1620 34o13’1.9”N
74o27’0.0”E
1.10 16.30 47.30 35.20 Silt clay loam
Muqam 1644 34o13’29.7”N
74o24’34.0”E
1.80 17.30 45.10 35.60 Silt clay loam
Muqam 1609 34o13’41.1”N
74o27’18.4”E
2.10 16.80 47.10 33.80 Silt clay loam
Khursi 1664 34o11’57.0”N
74o25’22.4”E
2.10 23.10 37.30 37.10 Clay loam
Chack 1682 34o11’30.1”N
74o24’48.7”E
1.30 18.20 45.30 34.40 Silt clay loam
Nichbattan 1667 34o11’39.3”N
74o24’57.0”E
3.10 16.30 47.30 32.10 Silt clay loam
Mirangund 1660 34o12’24.4”N
74o26’11.3”E
5.80 26.10 34.90 33.30 Clay loam
Lower Zone
(1600-1700)
Singpora 1695 34o12’35.8”N
74o25’36.2”E
3.20 16.10 45.30 34.90 Silt clay loam
Mean 2.41 18.62 43.90 34.59 --
50
Figure 3a: Sand content of the soils of Khursi micro-watershed, district
Baramulla, Jammu & Kashmir
Figure 3b: Silt content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
Figure 3c: Clay content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
4.1.2 Soil reaction
The pH varied from 6.43 to 7.57, 6.08 to 7.12 and 6.43 to 7.80 in the higher,
middle and lower zone surface soils with the mean values of 6.93, 6.65 and 7.35,
respectively (Table 2). Surface soil pH was found to be higher in lower zone. The
soils were slightly acidic to slightly alkaline in reaction.
4.1.3 Electrical conductivity (EC)
The electrical conductivity of surface soils (Table 2) ranged from 0.18 to
0.78, 0.20 to 0.38 and 0.23 to 0.39 with mean values of 0.34, 0.30, 0.30 d Sm-1 in the
upper, middle and lower zones, respectively. No regular trend was found in electrical
conductivity while moving from higher locations to lower ones.
4.1.4 Organic carbon
The organic carbon content of surface soils varied from 0.64 to 1.57, 0.91 to
2.01 and 0.71 to 1.78 with mean values of 1.17, 1.29 and 1.08 per cent in the upper
zone, middle zone and lower zone, respectively (Table 2). The content of organic
carbon varied in three zones, although not considerably, with higher mean values
recorded in middle and upper zones of watershed.
4.1.5 Calcium carbonate
The calcium carbonate in the surface soils was negligible or absent with the
mean values of 0.11, 0.00 and 0.33 per cent in upper, middle and lower zones,
respectively (Table 2). The relatively higher content of calcium carbonate was
observed in the Karewa soils.
4.1.6 Cation exchange capacity
The cation exchange capacity, being an important parameter, reflects the
nutrient availability of soils. The cation exchange capacity ranged from 11.11 to
51
15.18, 12.43 to 19.81 and 15.21 to 20.31 cmolc kg-1 in the surface soils of upper,
middle and lower zones, with the mean values of 12.90, 17.00 and 17.91 cmolc kg-1,
respectively. An overall increase in CEC was noticed while moving from upper zone
locations to lower zone locations.
4.1.7 Bulk density
The data presented in table 2 revealed that bulk density of surface soils varied
from 1.23 to 1.39, 1.23 to 1.38 and 1.24 to 1.39 g cm3 in the upper, middle and lower
zone with the mean values of 1.33, 1.28 and 1.32 gcm3, respectively. In the values of
bulk density, no distinct variation could be seen between the zones.
The thematic maps of pH, EC, OC and CaCO3 are presented in the figure 4a,
4b, 4c and 4d.
52
Table 2: Physico-chemical properties of surface soils of Nalah Khursi micro-watershed
Zone (m amsl) Location
Elevation (m amsl)
Latitude/ Longitude
pH (1:2.5)
EC (d Sm-1)
OC (%)
CaCO3 (%)
CEC (cmolc
kg-1 soil)
Bulk density (g cm-3)
Katyawalay 1913 34o11’2.5”N 74o22’47.2”E
7.55 0.43 0.88 0.63 11.30 1.32
Larey 1910 34o10’35.3”N 74o23’1.6”E
6.80 0.26 1.43 0.00 12.61 1.31
Gohan 2011 34o10’17.7”N 74o22’27.1”E
6.83 0.26 1.42 0.00 11.11 1.36
Larey 1941 34o10’21.9”N 74o22’39.6”E
7.36 0.32 0.78 0.18 12.33 1.39
Larey 1959 34o9’52.1”N 74o22’29.0”E
6.60 0.28 1.47 0.00 14.78 1.38
Pachhar 1951 34o9’27.6”N 74o22’32.2”E
6.51 0.27 1.01 0.00 12.78 1.33
Fakirbagh 1949 34o9’12.6”N 74o22’28.0”E
6.52 0.18 1.03 0.00 12.81 1.36
Chandoosa 1910 34o9’4.9”N
74o23’20.9”E 6.43 0.19 1.54 0.00 13.43 1.24
Chandoosa 1910 34o9’4.9”N
74o23’20.9”E 6.61 0.33 1.57 0.00 12.94 1.23
Masjid Angan 1939 34o9’33.1”N 74o23’16.4”E
7.43 0.78 0.64 0.38 12.63 1.36
Upper Zone (1900-2011)
Vulraman 1920 34o10’2.9”N 74o23’41.8”E
7.57 0.42 1.12 0.00 15.18 1.35
Mean 6.93 0.34 1.17 0.11 12.90 1.33
Contd........
53
Zone (m amsl) Location
Elevation (m amsl)
Latitude/ Longitude
pH (1:2.5)
EC (d Sm-1)
OC (%)
CaCO3 (%)
CEC (cmolc
kg-1 soil)
Bulk density (g cm-3)
Katawalay 1899 34o10’40.4”N
74o23’11.4”E
6.69 0.20 1.54 0.00 12.43 1.25
Vulraman 1854 34o10’21.1”N
74o24’23.7”E
6.08 0.38 1.12 0.00 16.31 1.37
Wirnar 1793 34o10’4.8”N
74o24’22.1”E
7.08 0.35 1.13 0.00 18.30 1.25
Wirnar 1796 34o10’6.5”N
74o24’24.5”E
6.24 0.27 2.01 0.00 16.91 1.23
Hudpora 1765 34o10’41.3:N
74o24’30.1”E
6.51 0.22 1.06 0.00 17.82 1.29
Fresdubh 1756 34o10’37.6”N
74o24’8.8”E
6.43 0.30 1.22 0.00 18.91 1.27
TakiWagura 1714 34o10’51.0”N
74o24’44.6”E
6.93 0.36 1.31 0.00 19.22 1.24
KhaiTangan 1721 34o11’6.5”N
74o24’15.5”E
6.77 0.28 1.33 0.00 13.31 1.38
Middle Zone
(1700-1900)
Ramzanpora 1700 34o11’12.5”N
74o24’21.8”E
7.12 0.33 0.91 0.00 19.81 1.26
Mean 6.65 0.30 1.29 0.00 17.00 1.28
Contd........
54
Zone (m amsl) Location
Elevation (m amsl)
Latitude/ Longitude
pH (1:2.5)
EC (d Sm-1)
OC (%)
CaCO3 (%)
CEC (cmolc
kg-1 soil)
Bulk density (g cm-3)
Potkhah 1604 34o14’3.9”N
74o27’31.6”E
7.73 0.30 1.01 0.53 19.11 1.39
NowporaJagir 1620 34o13’1.9”N
74o27’0.0”E
7.23 0.27 0.71 0.30 20.31 1.38
Muqam 1644 34o13’29.7”N
74o24’34.0”E
7.80 0.33 1.00 0.55 17.92 1.33
Muqam 1609 34o13’41.1”N
74o27’18.4”E
6.43 0.24 1.78 0.00 19.12 1.32
Khursi 1664 34o11’57.0”N
74o25’22.4”E
7.76 0.34 0.89 0.50 18.48 1.25
Chack 1682 34o11’30.1”N
74o24’48.7”E
6.70 0.23 1.34 0.00 18.68 1.27
Nichbattan 1667 34o11’39.3”N
74o24’57.0”E
6.93 0.29 1.11 0.00 16.58 1.34
Mirangund 1660 34o12’24.4”N
74o26’11.3”E
7.79 0.39 0.91 0.33 15.21 1.30
Lower Zone
(1600-1700)
Singpora 1695 34o12’35.8”N
74o25’36.2”E
7.80 0.33 1.00 0.75 15.79 1.24
Mean 7.35 0.30 1.08 0.33 17.91 1.32
55
Figure 4a: Soil reaction (pH) of the soils of Khursi micro-watershed,
district Baramulla, Jammu & Kashmir
Figure 4b: EC of the soils of Khursi micro-watershed, district
Baramulla, Jammu & Kashmir
Figure 4c: Organic carbon content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 4d: Calcium carbonate content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
4.2 Fertility status of micro-watershed soils
4.2.1 Available nitrogen
The available nitrogen content in the surface soils of the upper, middle and
lower zones varied from 169.34 to 577.02, 169.34 to 388.86 and 137.98 to 469.34
with the mean values of 317.59, 298.26 and 289.78 kg ha-1, respectively (Table 3).
The mean available nitrogen content variation in the three watershed zones with
higher content noticed in upper zones followed by middle and lower zones.
4.2.2 Available phosphorus
The available phosphorus content in the surface soils of upper, middle and
lower zones varied from 9.97 to 35.91, 10.01 to 21.53 and 9.34 to 32.59 with mean
values stands at 20.76, 15.25 and 17.50 kg ha-1, respectively (Table 3). The mean
available phosphorus content showed variation in three watershed zones with higher
content recorded in upper zone followed by lower and middle zones.
4.2.3 Available potassium
The data present in tables 3 revealed that available potassium content ranged
from 109.26 to 442.88, 103.87 to 258.73 and 109.71 to 426.11with mean values of
245.18, 205.15 and 215.65 kg ha-1 in the surface soils of upper, middle and lower
zones, respectively. Highest mean value for available potassium was noticed in upper
zone followed by lower and middle zones.
4.2.4 Available sulphur
An examination of data presented in tables 3 depicted that available sulphur
content in upper, middle and lower zones ranged from 5.99 to 59.64, 5.67 to 31.29
and 21.11 to 75.21 with mean values of 26.92, 15.33 and 36.29 kg ha-1, respectively.
The content varied considerably from each other in the three zones.
56
4.2.5 Micronutrient cations
4.2.5.1 Zinc
The DTPA extractable zinc of surface soils varied from 0.60 to 3.72, 0.53 to
1.14 and 0.32 to 2.58 with the mean values of 1.52, 0.79 and 0.98 mg kg-1 (Table 3)
in upper, middle and lower zones, respectively. Highest mean value for DTPA
extractable zinc was recorded in upper zones followed by lower and middle zones.
4.2.5.2 Copper
Perusal of data presented in table 3 showed that DTPA extractable copper
varied from 0.18 to 0.48, 0.09 to 0.38 and 0.19 to 1.10 with the mean values of 0.33,
0.29 and 0.50 mg kg-1in the upper, middle and lower zone surface soils, respectively.
The DTPA extractable copper showed distinct variation between the zones.
4.2.5.3 Iron
The contents of available iron varied from 7.45 to 32.30, 6.60 to 23.86 and
3.26 to 39.34 with the mean values of 18.56, 16.33, 16.19 mg kg-1 (table 3) in the
surface soils of upper, middle and lower zones, respectively. The content of iron
showed variation in three zones, with higher content noticed in upper zone followed
by middle and lower zone.
4.2.5.4 Manganese
The data presented in tables 3 indicated that the DTPA extractable manganese
in the surface soils of upper, middle and lower zones varied from 2.08 to 17.69, 7.37
to 35.32 and 3.57 to 11.76 with the mean values of 9.38, 17.26 and 6.04 mg kg-1,
respectively. The contents were higher in middle zone than in upper and lower zone.
The thematic maps of soil nutrient elements are presented in figures 5a, 5b,
5c, 5d, 5e, 5f, 5g and 5h.
57
Table 3: Fertility status of Khursi micro-watershed soils
Average Macro Nutrient (kg ha-1)
Average Micro Nutrient (mg kg-1)
Zone (m amsl)
Location Elevation (m amsl)
Latitude/ Longitude
N P K S Zn Cu Fe Mn
Katyawalay 1913 34o11’2.5”N 74o22’47.2”E 200.70 13.22 130.85 39.48 2.06 0.18 7.45 5.37
Larey 1910 34o10’35.3”N 74o23’1.6”E
357.50 16.74 224.90 22.49 0.84 0.36 16.32 7.51
Gohan 2011 34o10’17.7”N 74o22’27.1”E
482.94 35.91 442.88 11.76 3.72 0.38 27.34 6.40
Larey 1941 34o10’21.9”N 74o22’39.6”E
357.50 32.92 413.28 31.08 1.96 0.40 17.66 3.87
Larey 1959 34o9’52.1”N 74o22’29.0”E
200.70 14.95 193.09 17.36 1.10 0.31 23.32 14.49
Pachhar 1951 34o9’27.6”N 74o22’32.2”E
577.02 19.31 109.26 28.68 1.06 0.26 22.98 15.82
Fakirbagh 1949 34o9’12.6”N 74o22’28.0”E
232.06 11.36 183.23 22.68 0.85 0.48 32.30 16.01
Chandoosa 1910 34o9’4.9”N 74o23’20.9”E
388.86 13.16 172.03 17.08 0.60 0.36 14.67 9.17
Chandoosa 1910 34o9’4.9”N 74o23’20.9”E
200.70 35.45 404.54 39.87 2.50 0.26 26.00 17.69
Masjid Angan 1939 34o9’33.1”N 74o23’16.4”E
169.34 9.97 120.51 59.64 1.01 0.21 8.16 4.72
Upper Zone (1900-2011)
Vulraman 1920 34o10’2.9”N 74o23’41.8”E
326.14 25.42 302.41 5.99 0.97 0.43 7.98 2.08
Mean 317.59 20.76 245.18 26.92 1.52 0.33 18.56 9.38
Contd........
58
Average Macro Nutrient
(kg ha-1)
Average Micro Nutrient
(mg kg-1)
Zone
(m amsl)
Location Elevation
(m amsl)
Latitude/
Longitude
N P K S Zn Cu Fe Mn
Katawalay 1899 34o10’40.4”N 74o23’11.4”E
294.78 14.95 154.56 5.88 0.84 0.21 21.90 14.80
Vulraman 1854 34o10’21.1”N 74o24’23.7”E
232.06 16.45 258.28 5.67 0.56 0.35 23.86 23.50
Wirnar 1793 34o10’4.8”N 74o24’22.1”E
388.86 15.85 184.13 6.37 0.68 0.09 8.96 7.37
Wirnar 1796 34o10’6.5”N 74o24’24.5”E
263.42 11.36 218.18 5.83 0.88 0.36 23.10 35.32
Hudpora 1765 34o10’41.3:N 74o24’30.1”E
294.78 20.33 198.24 22.58 0.84 0.30 20.92 19.76
Fresdubh 1756 34o10’37.6”N 74o24’8.8”E
169.34 16.45 253.79 6.38 1.14 0.38 21.72 20.26
TakiWagura 1714 34o10’51.0”N 74o24’44.6”E
357.50 21.53 258.73 22.88 0.71 0.31 6.60 8.24
KhaiTangan 1721 34o11’6.5”N 74o24’15.5”E
357.50 10.01 103.87 31.08 0.53 0.33 12.89 8.19
Middle Zone (1700-1900)
Ramzanpora 1700 34o11’12.5”N 74o24’21.8”E
326.14 10.32 216.61 31.29 0.96 0.31 7.01 17.92
Mean 298.26 15.25 205.15 15.33 0.79 0.29 16.33 17.26
Contd........
59
Average Macro Nutrient (kg ha-1)
Average Micro Nutrient (mg kg-1)
Altitude (m amsl)
Location Elevation (m amsl)
Latitude/ Longitude
N P K S Zn Cu Fe Mn Potkhah 1604 34o143.9”N
74o27’31.6”E 294.78 9.34 109.71 56.31 0.59 0.69 26.62 3.73
NowporaJagir 1620 34o13’1.9”N 74o27’0.0”E
294.78 11.21 157.47 75.21 2.58 1.10 39.34 5.95
Muqam 1644 34o13’29.7”N 74o24’34.0”E
232.06 13.46 219.30 25.48 1.19 0.26 5.22 6.63
Muqam 1609 34o13’41.1”N 74o27’18.4”E
469.34 28.11 157.92 27.16 1.06 1.02 36.22 9.10
Khursi 1664 34o11’57.0”N 74o25’22.4”E
137.98 13.46 297.02 21.11 0.49 0.30 3.26 3.57
Chack 1682 34o11’30.1”N 74o24’48.7”E
357.50 11.36 181.81 21.84 0.57 0.36 14.18 11.76
Nichbattan 1667 34o11’39.3”N 74o24’57.0”E
357.50 20.03 196.22 39.37 0.32 0.19 8.03 5.27
Mirangund 1660 34o12’24.4”N 74o26’11.3”E
200.70 32.59 426.11 38.98 1.50 0.31 7.45 3.90
Low Altitude (1600-1700)
Singpora 1695 34o12’35.8”N 74o25’36.2”E
263.42 17.94 195.33 21.11 0.49 0.24 5.35 4.47
Mean 289.78 17.50 215.65 36.29 0.98 0.50 16.19 6.04
60
Figure 5a: Available nitrogen content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 5b: Available phosphorous content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 5c: Available potassium content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 5d: Available sulphur content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 5e: Available zinc content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 5f: Available copper content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 5g: Available iron content of the soils of Khursi micro-
watershed, district Baramulla, Jammu & Kashmir
Figure 5h: Available Manganese content of the soils of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
Mn Map
4.3 Characterization of micro-watershed soils
After conducting a general traversing of the study area, six profiles (two each
from upper, middle and lower zones) were selected on the basis of heterogeneity in
apparent soils colour, topography, vegetation etc. The location of the profiles of the
micro-watershed is depicted in Fig-8. The morphological and physio-chemical
characteristics of these profiles were studied and are described here under:
4.3.1 Soil site description
The soil site characteristics were observed following the standard proforma of
soil site description of NBSS and LUP soil bulletin No. 23 (Sehgal, 1994). The
selected profiles varied in elevation, physiography, slope, drainage etc.
The detailed description of the site characteristics of the study area are
presented in table 4. However, the salient features are described below.
The profiles selected varied in elevation from 1620 to 1898 m amsl.
Physiography of study area ranged from side slope at higher zone (P1 and P2) to upper
piedmont plain at middle zone (P3 and P4) and lower piedmont plain at lower zone (P5
and P6). Wide variation in topography was noticed in watershed. It was hilly at
profile P1 and P3, rolling at P2, terraced at P4, P5 and flat at profile P6. The slope class
varied from moderately sloping (10-15%) at profile P1, gently sloping (3-8%) at
profiles P2 and P3 to very gently sloping (1-3%) at profiles P4 and P5, to nearly
levelled at profile P6.
The erosion class varied from moderately eroded at profiles P1 to slightly
eroded at profiles P2, P3, P4 and P5 to un-eroded at profile P6.
61
Table 4: Soil site description
Profile No.
Location Elevation Latitude and
longitude
Physiography Topography Aspect Slope class Erosion Flooding Drainage Vegetation
P1 Katyawalay 1894 34o11’16.5”N
74o23’06.1”E
Side slope Rolling Southern Moderately steeply sloping
Moderately erosion
No Well drained
Coniferous, apple, pear
trees, willow, maize
P2 Chandoosa 1898 34o09’02.5”N
74o23’20.1”E
Upper piedmont plain
Terraced Northern Moderately sloping
Slight erosion
No Imperfect drainage
Cherry, pear, apple trees,
willow, maize
P3 Hudpora 1843 34o10’09.1”N
74o24’30.1”E
Upper piedmont plain
Undulating Southern Moderately sloping
Slight erosion
No Moderately well
drained
Willow, apple, cherry trees,
walnut, wheat, maize
P4 Khaitangan 1803 34o10’49.4”N
74o23’51.1”E
Upper piedmont plain
Hilly Northern Gently sloping Slight erosion
No Moderately well
drained
Apple, cherry, willow, maize,
grasses
P5 Nowpora Jagir 1620 34o12’35.0”N
74o26’57.2”E
Lower piedmont plain
Undulating Northern Gently sloping Slight erosion
No Moderately well
drained
Apple, cherry, pear trees,
maize
P6 Mugam 1622 34o13’57.4”N
74o27’24.2”E
Lower piedmont plain
Terraced Northern Very gently sloping
Nil No Well drained
Apple, cherry, pear trees,
surface natural grasses
62
4.3.2 Morphological characteristics
The detailed description of morphological properties of six (06) representative
soil profiles in three physiographic zones is presented in table 5. However the salient
morphological characteristics are described below:
The diagnostic horizons and depth varied in these profiles as shown in table 5.
The colour of the soils in surface horizons of profiles P1 and P2 is dark brown (10 YR
4/3, 10 YR 3/3) while as, in sub surface horizons of profile P1 colour ranged from
dark brown (10 YR 3/3) to yellowish brown (10 YR 5/4). However, in profile P2
colour of sub-surface horizon ranged from very dark grey (10 YR 3/1) to dark brown
(10 YR 3/3). Surface texture of both profiles P1 and P2 was silt loam. Whileas, sub-
surface texture of profile P1 and P2 ranged from silt loam to silty clay loam and silt
clay loam to clay loam, respectively. The soil structure in surface horizon of both
profiles 1 and 2 was found to be granular with moderate grade. However profile 1 had
coarse surface structure and profile 2 had medium surface structure. In sub-surface
soils of profile 1, soil structure varied from granular to angular blocky with moderate
grade and medium structure. While as, in profile 2, it varied from sub-angular blocky
to angular blocky with moderate to strong grade and medium structure. The wet and
moist consistency in all horizons of profile 1 was found to be slightly sticky and
friable with loose to hard dry consistency. While as, in profile 2, consistency varied
from slightly sticky to sticky, friable to very firm and hard to very hard from surface
to sub-surface. Thin, patchy clay cutans (Argillans) were also observed in both
profiles.
In profile 3 and 4 colour of the soils ranged from very dark grey (10 YR 3/1)
to dark grey brown (10 YR 4/2) and brown (10 YR 5/3) to brownish yellow (10 YR
7/6)/Fiant brownish yellow (10 YR 6/6), from surface to sub-surface horizons,
respectively. Structure and texture of profile 3 ranged from sub-angular blocky,
63
moderate, coarse and clay loam to angular blocky, strong, medium and clay. While
as, consistency varied from sticky, firm and very hard to very sticky, very firm to
very hard from surface to sub-surface. However, in profile 4, structure and texture
ranged from sub-angular blocky, moderate, medium and clay loam to single grain,
structure less, fine and sandy loam from surface to sub-surface. While as, consistency
from sticky, firm, very hard to non-sticky, very friable and loose. Thin, patchy clay
cutans were also observed in sub-surface horizons of profile 3 while as, no such
cutans were seen in profile 4.
In profile 5 and 6 colour of the soils from surface to sub-surface varied from
dark brown (10 YR 3/3) to dark yellowish brown (10 YR 4/4) and yellowish brown
(10 YR 5/4) to brown (10 YR 5/3), respectively. In both profiles surface texture was
silt clay loam and it changed to clay loam in the sub-surfaces. In profile 5 soil
structure was found to be sub-angular blocky with moderate grade and medium
structure in all the horizons, while as in profile 6, it was found as angular blocky to
sub-angular blocky with moderate to strong grade and medium structure. The wet and
moist consistency in both profiles varied from sticky and friable to very sticky and
firm from surface to sub-surface. On the other hand, dry consistency varied from hard
to very hard in profile 5 and slightly hard to hard in profile 6.
In all profiles, roots medium, coarse and fine in size with few, many and
common quantity, were found throughout the depth.
4.3.3 Physico-chemical characteristics
The physico-chemical properties of micro-watershed soils under different
zones are presented in table 6 and 7.
64
Table 5: Morphological characteristics of soil profiles of Nalah Khursi micro-watershed Boundary Structure Consistence Roots Cutans Zone
(m amsl)
Pro
file
No.
Horizon Depth
(cm)
Textural
Class
Matrix colour
Coa
rse
frag
men
ts
Dis
t.
Top
ogra
phy
Siz
e
Gra
de
Typ
e
Dry
Moi
st
Wet
Siz
e
Qty
Ty
Th
Qny
pH
(1:2.5)
B.S
%age
Mottle
colour
Ap 0-15 sil 10YR5/3(D) Brown,
10YR4/3(M) Dark
brown
Nil d s C 2 gr dsh mfr wss m-f-c m - - - 6.74 90.53 Nil
AB 15-43 sil 10YR3/3 Dark
brown Nil d s M 2 gr dsh mfr wss m-f-c c - - - 6.82 78.72 Nil
Bw1 43-82 sil 10YR4/4 Dark
yellowish brown Nil d s M 2 abk dsh mfr wss m-f c - - - 6.98 75.81 Nil
Bw2 82-90 sil 10YR5/4 Yellowish
brown Nil - - M 2 sbk dl mfr wss m-f f - - - 7.21 73.23 Nil
P1
Bw3 90-120 sicl 10YR4/4 Dark
yellowish brown Nil - - M 2 sbk dh mfr wss f-vf f - - - 7.27 71.63 Nil
Ap 0-20 sil
10YR4/2(D) Dark
grey brown,
10YR3/3(M)Dark
brown
Nil d s M 2 gr dh mfr wss m-f-c m - tn - 6.30 83.23 Nil
Bt1 20-45 sicl 10YR4/2 Yellowish
brown Nil g i M 2 abk dh mfi ws m-f-c c - - - 6.39 76.13 Nil
Bt2 45-90 cl 10YR3/1 Very dark
grey Nil c w M 3 sbk dvh mvfi ws f-vt f T tn p 6.42 72.82 Nil
Upper
zone
(>1900)
P2
Bt3 90-120 cl 10YR4/1 Dark grey Nil -- - M 2 abk dvh mvfi ws vt f T tn p 6.81 70.03 Nil
Contd......
65
Boundary Structure Consistence Roots Cutans Zone
(m
amsl)
Pro
file
No.
Horizon Depth
(cm)
Textural
Class
Matrix colour
Coa
rse
frag
men
ts
Dis
t.
Top
ogra
phy
Siz
e
Gra
de
Typ
e
Dry
Moi
st
Wet
Siz
e
Qty
Ty
Th
Qny
pH
(1:2.5)
B. S.
%age
Mottle
colour
Ap 0-19 cl 10YR4/1(D)Dark
grey, 10YR3/1(M)
Very dark grey
Nil c s C 2 sbk dvh mfi ws m-f-c m - - - 6.66 69.88 Nil
Bt1 19-32 c 10YR4/2Dark
grey brown Nil c s M 3 abk dvh mfi wvs m-f-c c T tn p 6.68 54.57 Nil
Bt2 32-88 c 10YR4/1 Dark
grey Nil d w M 3 abk dvh mvfi wvs f-vf f T tn p 6.77 56.07 Nil
P3
Bt3 88-120 c 10YR3/1 Very
dark grey Nil - - M 3 abk dvh mvfi wvs vf f T tn p 7.00 50.01 Nil
Ap 0-12 cl
10YR6/3(D) Pale
brown,
10YR5/3(M)
Brown
Nil c s M 2 sbk dvh mfi ws m-f-c c - - - 6.75 82.66 Nil
Bw 12-28 scl 10YR7/6
Brownish yellow
fg
(10-20%) c s F 1 gr dsh mfr wss m-f f - - - 6.82 85.73 Nil
Bc1 28-65 sl 10YR5/6
Yellowish brown
cg
(20/30%) - - F 0 sg dl mvfr wso mvf f - - p 6.88 91.62 Nil
Middle
zone
(1700-
1900)
P4
Bc2 65-120 sl 10YR6/6 Faint
brownish yellow Nil - - F 0 sg dl mvfr wso - - - - p 7.01 87.30 Nil
Contd......
66
Boundary Structure Consistence Roots Cutans Zone
(m amsl)
Pro
file
No.
Horizon Depth
(cm)
Textural
Class
Matrix colour
Coa
rse
frag
men
ts
Dis
t.
Top
ogra
phy
Siz
e
Gra
de
Typ
e
Dry
Moi
st
Wet
Siz
e
Qty
Ty
Th
Qny
pH
(1:2.5)
B. S.
%age
Mottle
colour
Ap 0-16 sicl 10YR4/3(D)Brown,
10YR3/3(M)Dark
Brown
Nil c s M 2 sbk dh mfr ws m-f-c m - - - 7.37 61.97 Nil
Bw1 16-46 cl 10YR4/2Dark
brown Nil g w M 2 sbk dh mfi ws m-f c - - - 7.41 66.00 Nil
Bw2 46-85 cl 10YR4/4Dark
yellowish brown Nil g i M 2 sbk dh mfi ws m-vf f T tn p 7.51 59.69 Nil
P5
Bw3 85-120 cl 10YR4/4Dark
yellowish brown Nil - - M 2 sbk dvh mvfi wvs f-vf f T tn p 7.47 56.74 Nil
Ap 0-15 sicl 10YR6/3(D)Pale
brown, 10YR5/4(M)
Yellowish brown
Nil c s M 2 sbk dsh mfr ws m-f-c m - - - 7.37 67.87 Nil
Bw1 15-45 cl 10YR5/3Brown Nil g i M 3 abk dh mfi ws m-f c - - - 7.44 63.63 Nil
Bw2 45-80 cl 10YR5/4Yellowish
brown Nil g i M 2 abk dh mfi wvs f-vf f T tn p 7.55 87.14 Nil
Lower
zone
(< 1700)
P6
Bw3 80-120 cl 10YR5/4Brown Nil - - M 2 sbk dh mfi ws vf f T tn p 7.45 66.12 Nil
67
Symbols used in morphological characterization (Table-5) of soils
Texture Structure Consistence Boundary Root Cutans
l=loam
cl=clay loam
sil=silt loam
sicl=silty clay loam
sl=sandy loam
scl=sandy clay loam
c=clay
0=structure less
1=weak
2=moderate
m=medium
c=coarse
f=fine
sbk=sub angular block
abk=angular blocky
gr=granular
sg=single grain
d=dry
m=moist
w=wet
h=hard
sh=slightly hard
fr=friable
vfr=very friable
fi=firm
vfi=very firm
vs=very sticky
s=sticky
ss=slightly sticky
so=non sticky
c=clear
g=gradual
s=smooth
i=irregular
w=wavy
d=diffused
f=few
m=many
c=common
T=argillian
tn=thin
p=patchy
68
4.3.3.1 Particle size distribution
Perusal of data in table 6 revealed that the coarse sand varied from 1.70 to
5.10, 0.90 to 7.40 and 1.00 to 3.00 with the mean values of 3.43, 3.31 and 1.71 per
cent in upper, middle and lower zone soils, respectively. The content of fine sand
ranged from 14.80 to 23.30, 15.80 to 54.8 and 17.00 to 25.00 with mean values of
18.43, 33.06 and 20.60 per cent in upper, middle and lower zone soils, respectively.
The content of fine sand and coarse sand in these soils did not depict any particular
trend in its vertical distribution. The content of silt fraction varied from 33.10 to
55.60, 20.80 to 37.70 and 35.00 to 48.10 with mean values of 47.14, 26.11 and 39.85
per cent in upper, middle and lower zones, respectively. In general, there was a
gradual decrease in silt content in most of the profiles. The content of clay ranged
from 24.30 to 37.80, 19.00 to 58.50 and 33.30 to 39.30 with the corresponding mean
values of 30.28, 36.60 and 37.06 per cent in upper, middle and lower horizon soils,
respectively. In general the clay content was low in the surface than sub-surface
horizons in all the profiles except profile 4.
4.3.3.2 Soil reaction
Perusal of the data in table 7 revealed that pH varied from 6.30 to 7.27, 6.66
to 7.01 and 7.37 to 7.55 with mean values of 6.77, 6.82 and 7.45 in upper, middle and
lower zone soils, respectively. The pH of soils showed overall increase in depth. The
soils were slightly acidic to slightly alkaline in reaction.
Soil pH was relatively higher in lower zone as depicted by its overall mean
i.e., 7.45.
4.3.3.3 Electrical conductivity
The electrical conductivity of upper, middle and lower zones varied from
0.18 to 0.27, 0.19 to 0.27 and 0.20 to 0.35 with mean values of 0.22, 0.22 and 0.25 d
69
Sm-1, respectively. The electrical conductivity did not exhibit any specific trend with
soil depth. No regular trend was found in electrical conductivity while moving from
higher location to lower ones.
4.3.3.4 Organic carbon
The data in table 7 revealed that the organic carbon content in upper, middle
and lower zone soils varied from 0.69 to 1.27, 0.26 to 1.33 and 0.34 to 0.67 with
mean values of 0.98, 0.76, and 0.47 per cent, respectively. The organic carbon
showed decreasing trend with respect to depth in all zones. Also organic carbon
content varied with altitude with higher content recorded in upper zone.
4.3.3.5 Calcium carbonate
The perusal of data presented in tables 7 revealed that the calcium carbonate
was absent or less in all the three zones. In upper and lower horizons the calcium
carbonate varied from 0.0 to 0.15 and 0.0 to 0.18 with mean values of 0.03 and 0.02
per cent, respectively. However, it was absent in middle zone profiles.
4.3.3.6 Cation exchange capacity
The cation exchange capacity ranged from 13.20 to 17.37, 9.18 to 21.86 and
17.31 to 19.91 in upper, middle and lower zone soils with mean values of 15.56,
15.82 and 18.51 cmolckg-1, respectively (Table 7). CEC first increased then decreased
in profiles P1, P2, P4 and P6, whereas in profiles P3 and P5 it showed increasing trend
with respect to depth. Also the mean values for cation exchange capacity was
considerably higher in lower horizon soils.
4.3.3.7 Exchangeable cations
As per the data presented in table 7, exchangeable calcium was the dominant
cation followed by magnesium and potassium. Average calcium content was 9.20,
70
7.70 and 8.70 cmolc kg-1 with the range values of 8.55 to 10.12, 6.13 to 9.13 and 7.86
to 9.21 cmolc kg-1 in upper, middle and lower zone soils, respectively.
The average magnesium content was 2.01, 2.17 and 2.56 cmolc kg-1 with
range values of 1.78 to 2.53, 1.18 to 2.81 and 1.94 to 3.20 cmolc kg-1 in upper, middle
and lower zone soils, respectively.
The exchangeable potassium ranged from 0.51 to 0.81, 0.50 to 0.76 and 0.44
to 0.61 cmolc kg-1 with mean values of 0.68, 0.65 and 0.51 cmolc kg-1 in upper,
middle and lower zones, respectively. The exchangeable cations did not depict any
definite trend in their vertical distribution.
4.3.3.8 Base saturation
The base saturation showed decreasing vertical trend with a range of 70.03 to
90.53 per cent, with mean value of 76.90 per cent in case of upper zone soils. In
middle and lower zones base saturation showed an irregular vertical trend with the
range values of 50.01 to 91.62 percent and mean of 71.66 percent, and 56.74 to 67.87
percent and mean of 63.65 percent, respectively. Base saturation was relatively higher
in upper zones followed by middle and lower zones.
71
Table 6: Particle size distribution in soil profiles of Nalah Khursi micro-watershed
Zone
(m amsl)
Location
(Profile No.)
Horizon Depth
(cm)
Coarse
sand (%)
Fine sand
(%)
Silt
(%)
Clay
(%)
Textural Class
Ap 0-15 3.80 16.10 55.60 24.30 Siltyloam
AB 15-43 5.10 14.80 52.30 27.80 Silt loam
Bw1 43-82 4.60 15.70 52.20 26.20 Silt loam
Bw2 82-90 3.40 16.10 51.60 27.90 Silt loam
Katianwalay
P1
Bw3 90-120 2.00 17.90 47.90 31.20 Silty clay loam
Ap 0-20 1.80 20.80 49.10 27.30 Silt loam
Bt1 20-45 1.70 18.30 46.30 35.20 Silty clay loam
Bt2 45-90 4.70 22.90 33.10 37.80 Clay loam
Upper Zone
(1900-2011)
Chandoosa
P2
Bt3 90-120 3.80 23.30 36.20 34.80 Clay loam
Mean 3.43 18.43 47.14 30.28 --
Contd........
72
Zone
(m amsl)
Location
(Profile No.)
Horizon Depth
(cm)
Coarse sand
(%)
Fine sand
(%)
Silt
(%)
Clay
(%)
Textural
Class
Ap 0-19 7.40 26.30 30.20 35.10 Clay loam
Bt1 19-32 3.20 22.40 28.10 45.10 Clay
Bt2 32-88 1.20 17.30 25.30 55.20 Clay
Hudpora
P3
Bt3 88-120 0.90 15.80 23.40 58.50 Clay
Ap 0-12 1.90 31.10 37.70 29.30 Clay loam
Bw 12-28 3.20 44.30 21.10 31.30 Sandy clay
loam
BC1 28-65 4.70 54.80 20.80 19.30 Sandy loam
Middle zone
(1700-1900) Khaitangan
P4
BC2 65-120 4.00 52.50 22.30 19.00 Sandy loam
Mean 3.31 33.06 26.11 36.60
Contd........
73
Zone
(m amsl)
Location
(Profile No.)
Horizon Depth
(cm)
Coarse
sand (%)
Fine sand
(%)
Silt
(%)
Clay
(%)
Textural Class
Ap 0-16 1.20 17.00 48.10 33.60 Silty clay loam
Bw1 16-46 1.40 24.10 37.20 36.80 Clay loam
Bw2 46-85 1.10 25.0 35.80 37.70 Clay loam
Nowpora
Jagir
P5
Bw3 85-120 1.70 23.30 35.00 38.80 Clay loam
Ap 0-15 1.00 18.10 47.10 33.30 Silty clay loam
Bw1 15-45 3.00 19.80 37.40 38.90 Clay loam
Bw2 45-80 2.10 19.30 38.50 39.30 Clay loam
Lower zone
(1600-1700)
Muqam
P6
Bw3 80-120 2.20 18.20 39.70 38.10 Clay loam
Mean 1.71 20.60 39.85 37.06 --
74
Table 7: Physico-chemical properties of soil profiles of Khursi micro-watershed
Exchangeable cations
(cmolc kg-1 soil) Zone
(m amsl) Location
(Profile No.) Depth
(cm)
pH
(1:2.5)
EC
(d Sm-1)
OC
(%)
CaCO3
(%)
CEC
(cmolc kg-1 soil)
Ca2+ Mg2+ K+ Na+
Base saturation
(%)
0-15 6.74 0.22 1.27 0.00 13.20 9.21 2.03 0.71 Tr 90.53
15-43 6.82 0.23 1.10 0.00 14.57 8.93 1.89 0.65 Tr 78.72
43-82 6.98 0.21 0.96 0.00 14.50 8.55 1.81 0.63 Tr 75.81
82-90 7.21 0.25 0.82 0.12 15.73 9.10 1.78 0.64 Tr 73.23
Katianwalay
P1
90-120 7.27 0.27 0.82 0.15 16.11 9.25 1.78 0.51 Tr 71.63
0-20 6.30 0.20 1.17 0.00 14.73 9.27 2.31 0.68 Tr 83.23
20-45 6.39 0.18 1.03 0.00 16.89 10.12 1.99 0.75 Tr 76.13
45-90 6.42 0.24 0.95 0.00 17.37 9.31 2.53 0.81 Tr 72.82
Upper zone
(1900-2011 )
Chandoosa
P2
90-120 6.81 0.21 0.69 0.00 16.90 9.10 1.98 0.76 Tr 70.03
Mean 6.77 0.22 0.98 0.03 15.56 9.20 2.01 0.68 -- 76.90
Contd........
75
Exchangeable cations
(cmolc kg-1 soil) Zone
(m amsl)
Location (Profile No.)
Depth
(cm)
pH
(1:2.5)
EC
(d Sm-1)
OC
(%)
CaCO3
(%)
CEC
(cmolc
kg-1 soil) Ca2+ Mg2+ K+ Na+
Base saturation
(%)
0-19 6.66 0.19 1.33 0.00 18.10 9.13 2.81 0.71 Tr 69.88
19-32 6.68 0.20 1.32 0.00 21.11 8.31 2.53 0.68 Tr 54.57
32-88 6.77 0.27 1.01 0.00 21.85 8.42 1.98 0.76 Tr 51.07
Hudpora
P3
88-120 7.00 0.25 0.96 0.00 21.86 8.27 1.96 0.70 Tr 50.01
0-12 6.75 0.20 0.51 0.00 12.23 7.11 2.49 0.51 Tr 82.66
12-28 6.82 0.20 0.37 0.00 12.90 7.98 2.58 0.50 Tr 85.73
28-65 6.88 0.22 0.28 0.00 9.31 6.13 1.80 0.68 Tr 91.62
Middle zone
(1700-1900)
Khaitangan
P4
65-120 7.01 0.20 0.26 0.00 9.18 6.22 1.18 0.65 Tr 87.73
Mean 6.82 0.22 0.76 0.00 15.82 7.70 2.17 0.65 -- 71.66
Contd........
76
Exchangeable cations
(cmolc kg-1 soil) Zone
(m amsl)
Location
(Profile No.)
Depth
(cm)
pH
(1:2.5)
EC
(d Sm-1)
OC
(%)
CaCO3
(%)
CEC
(cmolc
kg-1 soil) Ca2+ Mg2+ K+ Na+
Base
saturation
(%)
0-16 7.37 0.29 0.67 0.18 17.83 7.86 2.71 0.48 Tr 61.97
16-46 7.41 0.22 0.52 0.00 19.12 8.91 3.10 0.61 Tr 66.00
46-85 7.51 0.24 0.41 0.00 19.85 9.19 2.21 0.45 Tr 59.69
Nowpora
Jagir
P5
85-120 7.47 0.20 0.40 0.00 19.91 8.91 1.94 0.44 Tr 56.74
0-15 7.37 0.35 0.57 0.00 17.31 8.03 3.20 0.52 Tr 67.87
15-45 7.44 0.30 0.50 0.00 17.82 8.31 2.50 0.53 Tr 63.63
45-80 7.55 0.22 0.37 0.00 18.29 9.14 2.68 0.46 Tr 67.14
Lower zone
(1600-1700)
Muqam
P6
80-120 7.45 0.20 0.34 0.00 17.91 9.21 2.11 0.56 Tr 66.12
Mean 7.45 0.25 0.47 0.02 18.51 8.70 2.56 0.51 63.65
77
4.3.4 Available nutrient content
4.3.4.1 Available macro-nutrient content
Perusal of data presented in table 8 revealed that available nitrogen,
phosphorus, potassium and sulphur in upper horizon soil profiles varied from 145.31
to 294.78, 9.71 to 24.51, 61.90 to 72.93 and 7.21 to 17.63 kg ha-1 with mean values of
223.01, 15.89, 68.07 and 11.07 kg ha-1, respectively.
In middle zone available nitrogen, phosphorus, potassium and sulphur
contents ranged from 117.27 to 294.78, 9.71 to 24.77, 71.90 to 80.28 and 7.51 to
18.27 kg ha-1 with mean values of 220.72, 14.21, 75.76 and 11.33 kg ha-1,
respectively.
In lower zone range values of available nitrogen, phosphorus, potassium and
sulphur were 134.31 to 263.42, 6.12 to 17.72, 71.00 to 88.27 and 5.31 to 16.65 kg
ha-1 with mean values of 195.11, 10.32, 78.77 and 10.65 kg ha-1, respectively. In
general a decreasing trend with the depth was observed in all the three zones in case
of nitrogen, phosphorus and sulphur contents, a reverse trend was observed for
potassium content in almost all zones.
4.3.4.2 Available micro-nutrient content
The data present in table 9 revealed that in upper zone soil profiles, zinc and
copper varied from 0.21 to 0.97 and 0.23 to 0.36 mg kg-1 with mean values of 0.57
and 0.30 mg kg-1, respectively. Similarly iron and manganese content of upper zone
profiles had a range of 11.69 to 35.48 and 13.81to 18.38 mg kg-1with mean values of
24.68 and 16.26 mg kg-1.
In middle zone soils zinc, copper, iron and manganese contents varied from
0.43 to 0.89, 0.20 to 0.46, 12.31 to 19.45 and 12.23 to 16.93 mg kg-1 with mean
values of 0.62, 0.29, 14.84 and 15.20 mg kg-1, respectively.
78
The data revealed that zinc, copper, iron and manganese content of lower zone
soils had a range of 0.13 to 0.90, 0.17 to 0.73, 8.34 to 31.32 and 9.31 to 16.96 mg
kg-1 with mean values of 0.39, 0.33, 15.32 and 13.03 mg kg-1, respectively
It is evident from the data presented in table 9 that in general micro-nutrients
zinc, copper, iron and manganese contents decreased with the increase in soil depth.
4.4 Soil loss estimation using GIS and USLE technique and soil erosion
mapping
Geographical information system (GIS) has been integrated with Universal
Soil Loss Equation (USLE) for the assessment of soil loss in Nallah Khursi micro-
watershed. Soil erosion mapping of the study area was modelled within study area,
integrating the USLE with GIS.
4.4.1 Universal soil loss equation (USLE)
The USLE model calculates potential average soil loss (A) as follows:
A = R x K x LS x C x P
Where,
A = Average soil loss per unit area (t ha-1 yr-1)
R = Rainfall erosivity factor (mt ha-1 cm-1)
K = Soil erodibility factor (t ha-1 per unit R)
LS = Topographic (Length – Slope) factor (dimensionless)
C = Land cover or prevention practice factor (dimensionless)
P = Land management and conservation practice factor (dimensionless)
79
Table 8: Available macronutrient concentration in soil profiles of Khursi micro-watershed
Available Macro-nutrients (kg ha-1) Zone
(m amsl)
Location
(Profile No.)
Depth
(cm) N P K S
0-15 294.78 22.03 65.71 17.63
15-43 263.42 16.27 69.82 12.67
43-82 235.53 14.71 68.53 10.31
82-90 203.10 13.83 71.89 08.73
Katianwalay
P1
90-120 178.06 13.39 72.93 05.84
0-20 263.42 24.51 61.90 16.29
20-45 232.06 17.32 68.35 12.37
45-90 191.42 11.25 67.80 08.54
Upper zone
(1900-2011 )
Chandoosa
P2
90-120 145.31 09.71 65.73 07.21
Mean 223.01 15.89 68.07 11.07
Contd........
80
Available Macro-nutrients (kg ha-1) Zone
(m amsl)
Location
(Profile No.)
Depth
(cm) N P K S
0-19 294.78 17.72 74.81 18.27
19-32 263.78 13.01 76.74 14.52
32-88 215.42 09.82 78.34 09.23
Hudpora
P3
88-120 178.31 09.71 80.28 08.13
0-12 294.78 24.77 71.90 15.25
12-28 232.06 15.42 79.83 10.21
28-65 169.34 13.15 72.20 07.54
Middle zone
(1700-1900)
Khaitangan
P4
65-120 117.27 10.05 72.01 07.51
Mean 220.72 14.21 75.76 11.33
Contd........
81
Available Macro-nutrients (kg ha-1) Zone (m amsl) Location (profile No.)
Depth
(cm) N P K S
0-16 263.42 16.24 72.57 16.65
16-46 230.42 12.13 76.38 12.32
46-85 137.98 06.50 85.79 08.23
Nowpora Jagir
P5
85-120 134.31 06.37 88.27 09.03
0-15 232.06 17.72 71.00 15.65
15-45 200.70 11.00 79.88 11.12
45-80 190.70 06.50 77.68 06.89
Lower zone
(1600-1700)
Muqam
P6
80-120 171.30 06.12 78.56 05.31
Mean 195.11 10.32 78.77 10.65
82
Table 9: Available Micro-Nutrient concentration in soil profiles of Khursi micro-watershed
Available Micro-nutrients (mg kg -1) Zone (m amsl)
Location (Profile No.)
Depth (cm) Zn Cu Fe Mn
0-15 0.97 0.34 35.48 18.38
15-43 0.82 0.33 29.22 18.05
43-82 0.71 0.33 24.31 16.72
82-90 0.53 0.31 18.27 13.81
Katianwalay
P1
90-120 0.30 0.30 11.69 14.60
0-20 0.95 0.36 33.98 18.38
20-45 0.37 0.28 31.00 16.25
45-90 0.23 0.26 18.87 14.81
Upper zone
(1900-2011)
Chandoosa
P2
90-120 0.21 0.23 19.30 15.31
Mean 0.57 0.30 24.68 16.26
Contd........
83
Available Micro-nutrients (mg kg -1) Zone
(m amsl)
Location
(Profile No.)
Depth
(cm) Zn Cu Fe Mn
0-19 0.89 0.46 19.45 16.45
19-32 0.82 0.38 18.24 15.16
32-88 0.73 0.27 13.43 14.74
Hudpora
P3
88-120 0.43 0.25 13.53 13.32
0-12 0.59 0.29 14.05 16.93
12-28 0.53 0.25 13.92 16.84
28-65 0.51 0.25 13.78 15.93
Middle zone
(1700-1900)
Khaitangan
P4
65-120 0.43 0.20 12.31 12.23
Mean 0.62 0.29 14.84 15.20
Contd........
84
Available Micro-nutrients (mg kg -1) Zone
(m amsl)
Location
(Profile No.)
Depth
(cm) Zn Cu Fe Mn
0-16 0.90 0.73 31.32 16.96
16-46 0.37 0.38 22.29 14.47
46-85 0.21 0.24 08.34 14.27
Nowpora Jagir
P5
85-120 0.19 0.21 10.11 12.25
0-15 0.79 0.45 20.54 13.25
15-45 0.31 0.24 10.75 12.34
45-80 0.19 0.19 09.18 11.41
Lower zone
(1600-1700)
Muqam
P6
80-120 0.13 0.17 10.01 09.31
Mean 0.39 0.33 15.32 13.03
85
4.4.2 Generated digital input maps
The contour map of the study area was digitized using the GIS system and
toposheet (1:50,000). The DEM was used to delineate catchment boundary and to
calculate slope and LS factor.
4.4.3 Computation of input parameters of USLE
For computing erosion loss from study area, various parameters of USLE
were estimated. For the present investigation, value of K for each discretized zone
was assigned on the basis of field and laboratory data. The C and P values were
assigned on the basis of land use information and associated support practice
information.
4.4.3.1 Rainfall erosivity (R) factor
The rainfall erosivity indicates the soil loss potential of a given storm event.
The annual erosivity was indicated by summing rainfall erosivity of individual
erosive storms of the year or season (Wishmeier and Smith, 1978). It requires long-
term data of rainfall amounts and intensities, which is not available for most of the
area and hence, relationship between rainfall erosivity index and annual rainfall was
developed with the data available from various meteorological observations in India
(Singh et al., 1981). The linear annual relationship to erosion index was as follows:
Y = 79 + 0.383 (r)
Where,
Y = Average annual erosion index (mt ha-1 cm-1)
r = Average annual rainfall in mm
Nearest metrological station for the micro-watershed is located at Indian
Meteorological Station, Gulmarg which received average annual rainfall of 668.15
86
Figure 6a: Rainfall erosivity factor of Khursi micro-watershed, district
Baramulla, Jammu & Kashmir
mm per year for the period of 2001-2011 (Fig-2 and 6a). The rainfall erosivity index
was estimated to be 334.9 mt ha-1 cm-1 using equation. This value was used to
estimate average annual soil loss from the micro-watershed.
4.4.3.2 Soil erodibility (K) factor
Soil erodibility is an important index to evaluate the soil susceptibility to
erosion. It reflects the combined effect of soil properties of texture, stability of
structure, permeability and organic matter. The soil erodibility factor was calculated
using field and laboratory estimated data of texture, organic matter content, structure
and permeability of surface soil samples following monographs given by Wishmeier
and Smith (1978).
The K- index of surface soils of each soil type, associated with the mapping
units was computed using following equation:
K = [2.8 x 10-7 M1.14 (12-a) + 4.3 x 10-3 x (b-2) x 3.3 x 10-3 (c-3)]
Where,
K = soil erodibility factor (t ha-1)
M = particle size parameter (% salt + % very fine sand) x (100-% clay)
a = organic matter content (%)
b = structural code
c = permeability class
The structural codes and permeability classes are given in table-10
The soils in the micro-watershed were characterized and soil erodibility of
surface soils (Fig-6b) were computed for each mapping units based on salient
characteristics, soil map units were grouped into five major physiographic soil units
87
Figure 6b: Soil erodibility factor of Khursi micro-watershed, district
Baramulla, Jammu & Kashmir
(Fig 11). The soil erodibility factor of these five physiographic units ranged from
0.30-0.35, 0.35-0.40, 0.40-0.45, 0.45-0.50 and 0.50-0.60.
4.4.3.3 Spatial distributed slope length (L) and Steepness (S) factor
Contour lines of 20 m interval from SOI toposheets were digitized and
interpelated to generate digital elevation model (DEM) of micro-watershed with grid
cell size of 30 m in ARCGIS-10.1. DEM was processed to generate slope gradient
and LS factor maps of study area. The slope was classified into nine steepness classes
(Wishmeier and Smith, 1978) of erosion hazards of nearly level (0-1%), very gentle
sloping (1-3%), gentle sloping (3-5%), moderately sloping (5-10%), strongly sloping
(10-15%), moderately steep to steep sloping (15-25%), steep sloping (25.33), very
steep (33-50%), and extremely steep sloping (> 50%) slope classes.
Spatial pattern of slope map (Fig-6c) revealed 18.12% area is under nearly
level to gentle sloping and 69.05 % area in moderately sloping to moderately steep
sloping classes, whereas11.83 % area belongs to steep sloping to extremely steep
slope classes. The LS factor (Fig-6d) accounts for the effect of slope length and
gradient on soil erosion. Steep sloping area had higher steepness factor (S) and lowest
slope length (L) factor.
4.4.3.4 Cropping management factor (c)
The values of the cover and management practices have been estimated based
on the criteria given by Wishmeier and Smith (1978). As per this method values of c
are correlated with land use, canopy and cover conditions and specific values of c for
different land use are used. The overall values of c factor ranges from 0.04-1.00. The
maximum values of c (1.00) estimated for 15.3% covering 93.62 ha area of micro-
watershed, whereas the minimum value of c i.e., 0.04 was estimated for 16.0%
covering an area of 97.87 ha. The distribution of c factor for study catchment is
shown in fig 6e. The c values for each soil scape are given in table 11.
88
Figure 6c: Slope map of Khursi micro-watershed, district Baramulla,
Jammu & Kashmir
Figure 6d: Topographic factor of Khursi micro-watershed, district
Baramulla, Jammu & Kashmir
Table 10: Structural and permeability codes
Sites Texture Structure
Code
Permeability
Code 1 Siltloam 5 3
2 Siltloam 5 3
3 Siltloam 5 3
4 Loam 4 3
5 Loam 4 3
6 Loam 4 3
7 Loam 4 3
8 Loam 4 3
9 Siltloam 5 3
10 Siltloam 5 3
11 Loam 4 3
12 clayloam 2 4
13 clayloam 2 4
14 Siltyclayloam 3 5
15 Siltyclayloam 3 5
16 Clayloam 2 4
17 Clayloam 2 4
18 Siltyclayloam 3 5
19 Siltyclayloam 3 5
20 Siltyclayloam 3 5
21 Siltyclayloam 3 5
22 Clayloam 2 4
23 Siltyclayloam 3 5
24 Siltyclayloam 3 5
25 Siltyclayloam 3 5
26 Sandy clayloam 4 4
27 Siltyclayloam 3 5
28 Clayloam 2 4
29 Siltyclayloam 3 5
89
4.4.3.5 Erosion control practices factor (p)
The supporting practice factor of P were obtained as per guidelines given by
Wishmeier and Smith (1978) for the micro-watershed area. Majority of the micro-
watershed area (53.20 %) has the P-value of 0.4 -0.5 and no specific soil conservation
measure have been adopted as shown in fig 6f. The derived P values for catchment
ranged from 0.2 to 1.0 (Table 11).
4.4.4 Assessment of soil loss and generation of erosion map
Quantification of soil loss in the micro-watershed has been done with the
computation of various USLE factors. The values of annual soil loss in the state have
been categorized into six different erosion risk classes (Table 12). Spatial distribution
of soil loss in the study area into different erosion classes is generated using GIS
techniques in the form of soil erosion map (Fig-7). Maps of values of USLE
parameters viz., K, L, S, C and P were multiplied using Raster Calculator of ARCGIS
10.1 software to obtain a composite map of factor’s KLSCP. The area calculated
from the map under different erosion classes is given in table 12.
About 86.90 % (2762.18 ha) of TGA of the micro-watershed produces annual
soil less than 5 t ha-1 yr-1. Slight erosion (5-10 t ha-1 yr-1) occurs in 300.99 ha,
constituting 9.47 % area of micro-watershed. Moderate erosion (10-15 t ha-1 yr-1) is
experienced in 2.39 % area.
About 1.24% of TGA of micro-watershed is suffering from severe form of
erosion (> 15 t ha-1 yr-1). Annual soil loss is 15-20, 20-40, > 40 t ha-1 yr-1 occurs in
0.60, 0.48 and 0.16% of TGA of the micro-watershed, respectively. The areas are
scattered in patches in almost all the upper and middle zones. Katiawalay, Larey,
Masjid Angan and Vulraman villages have small areas under moderately high and
high erosion classes. Very high erosion is also experienced in the entire upper zone.
90
Table 11: C and P was calculated by using LULC of the area and C
and P tables
S. No. Land use/land cover C P
1. Agriculture land-1 0.5 0.5
2. Agriculture land-2 0.3 0.4
3. Orchard 0.1 0.5
4. Very dense forest 0.004 1.0
5. Dense forest 0.008 1.0
6. Moderately dense forest 0.08 1.0
7. Open forest 0.4 1.0
8. Dense scrub 0.05 1.0
9. Forest blank 0.8 1.0
10. Forest plantation 0.02 0.8
11. Wasteland with scrub 0.6 1.0
12. Wasteland without scrub 1.0 1.0
13. Built up (settlement) -- --
14. Mixed built-up land 0.5 0.3
15. Water bodies (river/ pond) -- --
16. Total -- --
91
Figure 6e: Cover and management factor of Khursi micro-watershed,
district Baramulla, Jammu & Kashmir
Figure 6f: Conservation practice factor of Khursi micro-watershed,
district Baramulla, Jammu & Kashmir
Figure 6g: Drainage pattern of Khursi micro-watershed, district
Baramulla, Jammu & Kashmir
Table 12: Soil loss assessment
Erosion risk classes t ha-1 yr -1 Area (ha) % of TGA
Very low 0-5 2762.18 86.90
Low 05-10 300.99 9.47
Moderate 10-15 75.97 2.39
Moderately high 15-20 19.07 0.60
High 20-40 15.25 0.48
Very high >40 5.08 0.16
92
Figure 7: Soil erosion risk map of Khursi micro-watershed, district
Baramulla, Jammu & Kashmir
4.5 Land evaluation / Land capability classification
Land capability classification is the hypothetical grouping of soils mainly
based on the inherent soil characteristics external land features and environmental
factors that limit the use of the land. It is thus grouping of the lands according to their
potentialities and limitations for sustained use. LCC is an interpretative grouping
made primarily for agriculture/horticultural, forestry, pasture and recreational
purpose.
The land capability classification of selected micro-watershed was worked out
and is presented in table 13. The perusal of data revealed that the micro-watershed
area represented by upper zone were classified into two sub-classes viz., IVe (P1) due
to limitation in erosion and IIItw (P2) due to moderate limitation in topography,
drainage and fertility. The middle zone profile P3 was placed under sub-class IIIt due
to moderate limitation in topography and fertility. The profile P4 of middle zone and
profile P5 and P6 were classified into IIs land capability sub class due to slight
limitation in physical conditions and poor fertility status of soil. The total per cent
area under different capability classes viz., II, III, IV were 47, 32 and 21 per cent
respectively.
93
Table 13: Land capability classification of Nallah Khursi micro-watershed
Topography Wetness (w) Physical conditions (s) Fertility Location Altitude
(m masl) Slope
(%)
Erosion Flooding Drainage Surface
texture
Surface
coarse
frag.
(%)
Surface
stoniness
(%)
Sub
surface
coarse
frag.
(%)
Soil
depth
(cm)
CEC
(cmolc
kg-1)
B.S
(%)
O.C
(%)
Salinity
EC
(d Sm-1)
Gypsum
(%)
Capability
class
Katianwalay 1894 IV III I I II II II II II II II I I - IV e
Chandoosa 1898 III II I III II II II II II II III I I - III tw
Hudpora 1843 III II I II II II II II II I III I I - III t
Khaitangan 1803 II II I II II I I I II II II III I - II s
Nowpora Jagir 1620 II II I II II I I I II I III III I - II s
Muqam 1622 I I I II II I I I II I III III I - II s
94
Chapter- 5
DISCUSSION
The salient findings of the present investigation are discussed in light of the
relevant literature under the following heads:
5.1 Physico-chemical characterisers of micro watershed
5.2 Soil fertility status of micro-watershed soil
5.3 Characterization of micro-watershed soil
5.4 Soil loss estimation using GIS and USLE technique
5.5 Land capability classification
5.1 Physico-chemical characteristics of micro-watershed
5.1.1 Particle size distribution in surface soil of micro-watershed
The data regarding the particle size distribution detailed in Table 1 indicate
that soils in three physiographic zones of micro-watershed varied in mechanical
makeup. The surface texture of upper zone soil was coarser than middle zone and
lower zone soils which could be attributed to the removal of finer solid fractions due
to erosion from higher elevations and their consequent deposition in lower less
sloppy areas. Similar observations were made by Gana et al. (2000), Tripathi et al.
(2006), Sarade and Prasad (2008), and Anjum (2012).
5.1.2 Soil reaction
The soil studied exhibited almost slightly acidie to slightly alkaline pH
ranging between 6.08 to 7.80 with the lower values observed in upper and middle
zone soil and higher values observed in lower zone soils (Table 2). This variation in
pH of the soil from three physiographic zones could be attributed to the variation in
95
organic matter content and erosion impacts. Similar reports were made by Lahiri and
Chakarvarti (1989), Mandal et al. (1990), Najar (2002) and Philor (2011).
5.1.3 Electrical conductivity
The electrical conductivity was within normal limits in the surface soil of
watershed with the mean values of 0.34, 0.30 and 0.30 d Sm-1 in upper, middle and
lower zones respectively. Dar (1996), Najar (2002) and Anjum (2012) also observed
similar results.
5.1.4 Organic carbon
Organic carbon was found in medium to higher range. The soils varied
conspicuously in the organic carbon content in all the three zones. The higher
contents of organic carbon were observed in upper and middle zone soils and lower
values observed in lower zone soils (Table 2). The higher content of organic carbon
in upper and middle zone soils could be attributed to low rate of mineralization
because of lower temperature. These results were in conformity with those Mushki
(1994), Dar (1996), Minhas et al. (1997) Najar et al. (2009).
5.1.5 Calcium carbonate
The calcium carbonate was absent from the top plough layer from which
samples were drawn except at certain location in upper and lower zones of watershed.
The results confirm the findings of Dar (1996), Syed (2003), Bhat (2010) and Anjum
(2012).
5.1.6 Cation exchange capacity
The cation exchange capacity of middle and lower zone soils varied very
slightly on the other hand, the higher zone soils had the lowest cation exchange
capacity among all the zones. This could be attributed to the higher content of clay in
96
middle and lower zones. Similar results were reported by Benerjee et al. (1996),
Verma et al. (1990) and Najar (2002).
5.1.7 Bulk density
Comparing middle zone with upper and lower zones, although their bulk
density was not distinctly different, the upper zone and lower zone had a slightly
higher mean bulk densities. The higher values of bulk density in upper zone could be
explained by the relatively low organic matter in the upper zone than middle zone,
which in turn could be due to higher erosion rates (Gatechew, 2009). It can also be
attributed to low day and high sand content (Dandroo, 2010).
Surface soils of lower zone under paddy land use system recorded increase in
bulk density and this might be due to collapse of non-capillary pores during puddling
operation. This is in agreement with the studies of Dey and Sehgal (1997) and
Rudramurthy et al. (2007).
5.2 Fertility status of micro-watershed soils
5.2.1 Available macronutrient concentration
5.2.1.1 Available of nitrogen
The nitrogen availability of surface soil in all the three zones was found to be
medium in status with higher content recorded in upper and middle zones. This
variation in available nitrogen content in three zones might be attributed to the
climatic and altitudal condition favourable for the accumulation of higher organic
matter content. Similar results were noticed by Dar (1996), Mushki 91994), Wani
(1994) and Najar (2002).
As the organic matter and the available nitrogen content showed strong
association, the total nitrogen content of the soils is affected among others by the
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reduction of soil organic matter content due to top soil less by erosion (Gateehew,
2009).
5.2.1.2 Available Phosphorus
The available phosphorus content showed variation in three watershed zones
with higher contents recorded in upper zone soil. The data depicted that available
phosphorus of the soils of the study area with exception of some localities, was less
than 9-22 kg ha-1 qualifying for the low to medium range. The low to medium
contents of available phosphorus observed in the soils of study area are in agreement
with the results reported by Rao et al. (2008), Bhat (2010) and Anjum (2012) and
could be attributed to the impacts of fixation and erosion phosphorus is normally
strongly bonded to soil particles and is therefore easily transported down slope during
erosion.
5.2.1.3 Available Potassium
In the present study, the soil were generally medium to high in available
potassium content which could be due to presence of higher clay content and illitic
nature of clays. The content of available potassium varied distinctly in all the three
physiographic zones with higher quantities recorded in higher zone soil. The results
are in conformity with the findings of Mushki (1997), Farida (1997), Wani (1994),
Najar (2002) and Anjum (2012). The relatively higher quantities of available
potassium in lower zone than middle zone is perhaps due to the accumulation of finer
soil particles (clay particles) in the lower zone.
5.2.1.4 Available sulphur
The sulphur availability was found to vary between low to medium in surface
samples of micro-watershed. These findings are in agreement with earlier works of
Sharma and Bhandari (1992), Mir (1994), Awasthi (1998 a) and Teli (2011).
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5.2.2 Available micronutrient concentration
5.2.2.1 Available Zinc
In the present study, the soil were generally medium to high in available zinc
content with higher quantities found in upper zone soil. This could be attributed to the
larger content of organic matter. The results were in conformity with those of
Chinchmalatpura et al. (2000), Dandroo (2001), Najar (2002) and Anjum (2012)
5.2.2.2 Available Copper
It was found in lower range in watershed soils. The content of available
copper did not exhibit any distinct variation between the zones. The results are in
conformity with Ghose and Kundu (2004) and Panwar and Pal (2010)
5.2.2.3 Available Iron
Available iron was found in sufficient range in all the three physiographic
zones which could be attributed to the higher quantities of organic matter and
favourable pH. Similar observations were made by Mushki (1994), Najar (2002) and
Anjum (2012).
5.2.2.4 Available Manganese
It was found in low to medium range in watershed soil. Ghose and Kundu
(2004) reported similar findings. Lower values of manganese could be attributed to
the erosion impacts.
5.3 Characterization of micro-watershed soils
5.3.1 Morphological characteristics
Six profiles were exposed for detailed study two each at the representative
locations in the three physiographic zones of micro-watershed. Their morphological
and physico-chemical properties are discussed as under.
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The data revealed that almost whole of the soils of watershed were
characterized by 10 YR as the common hue of soil matrix for the surface as well as
sub-surface horizons. The dark colour in the surface horizons can be attributed to
high organic matter content and down the profile dark colour can be attributed to clay
illuvation. The various shades like dark brown, very dark brown, yellowish brown
and dark yellowish brown in the surface and subsurface horizons of the profiles
indicate that these soils had well drainage conditions. The various shades of grey
colour in the studied profiles could be attributed to the coagulation of iron and / or
calcium with humus components (Dhir 1967, Gupta 1992).
The surface textural class of study area was silt loam in upper zones, clay
loam in middle zones and silt clay loam in lower zones. The surface texture of upper
zone was coarser as compared to mid and lower zones, which might be due to
elevation and slope gradient resulting in the translocation or removal of finer particles
of soil by eluviation, surface erosion due to rainfall. Similar observations have been
reported by Mandal et al. (1990), Kumar et al. (2002) and Najar (2002).
Translocation of clay from the surface horizons deposition in the lower
horizons was observed in almost all profiles as also reported by Najar (2002).
The moderate granular structure in surface horizons of higher zone (P1 and P2
profiles) is attributed to high organic matter content as also reported by Sehgal et al.
(1985) and Minhas et al. (1997) under such situations. The prevalence of angular/
Sub angular blocky structures in all the horizons of most of the middle and lower
zones profiles (P2, P4 and P6) and in subsurface horizons of upper zone profiles (P1
and P2) exhibit structural development. But, the sub surface horizon of profile P4 had
the single grain structure.
The consistency of the studied pedons varied widely. In the surface horizons
of upper zone soil it was slightly hard and hard when dry and firm/slightly sticky
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when moist/wet. On the other hand in middle and lower zone soils it was very hard
/hard/slightly hard when dry, firm/frisk when moist and sticky when wet. In the sub
surface horizons of upper zone, it varied from loose to very hard when dry, friable to
very firm when moist and slightly sticky to sticky when wet, whereas in middle and
lower zone sub surface horizons consistency was loose to very hard when dry, friable
to very firm when moist and non-sticky to very sticky when wet.
5.3.2 Physico-chemical characteristics and nutrient concentration in
soil profiles
5.3.2.1 Particle size distribution
In general, fine sand and silt decreased with depth, whiles as clay content
increased with depth except in profile P4. The increase in clay content with depth may
be attributed to the illuviation and translocation of clay in the B horizons occurring
during soil development. Similar observations were made by Farida (1997), Najar
(2002), Sharma et al. (2004) and Kirmani (2004).
The clay content was found to be higher in lower horizon soils, which could
be attributed to the removal of finer fractions from upper slopes due to erosion and
their subsequent deposition in relatively levelled areas of lower zones. Similar results
were observed by Dandroo (2001) and Thangasamy et al. (2005).
5.3.3.2 Soil reaction
The soils of the study area exhibited slightly acidic to neutral pH with a mean
of 6.77, 6.82 and 7.45 in upper, middle and lower zone soils, respectively. This
variation in pH of the soils from three physiographic zones could be attributed to the
variation in organic matter content. Similar reports were made by Minhas and Bora
(1982), and Mandal et al. (1990). The increase in pH with the increase in soil depth
could be ascribed to leaching of bases from surface horizons and its deposition at the
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lower horizons. Verma et al. (1990), Wani (1994), Najar (2002) and Kirmani (2004)
have also reported increase in soil pH with the soil depth.
5.3.3.3 Electrical conductivity
The electrical conductivity of the soils was found within normal range both in
surface and sub-surface horizons of profiles in all the three physiographic zones.
Similar results were observed by Wani (1994), Bhargana (2002) and Kirmani (2004).
5.3.3.4 Organic carbon
The soil varied in organic carbon content in all the three zones. The higher
content was observed in upper zone followed by middle and lower zone. The higher
content of organic carbon in upper zone soil could be due to low rate of
mineralization because of lower temperature. These results were in conformity with
those of Minhas et al. (1997) and Najar (2002).
The organic carbon was found higher in surface horizon compared to sub-
surface horizons i.e., in general organic carbon content decreased with the increase in
soil depth irrespective of physiography. This might be as a result of incorporation of
crop residues and fallen leaves. These findings are in accordance with those of Lahari
and Chakarvarti (1982), Najar (2002).
5.3.3.5 Calcium carbonate
The calcium carbonate content was absent or very low in all the three zones.
The presence of calcium carbonate in some locations might be due to the leaching of
soluble salts (Kher and Singh, 1993).
5.3.3.6 Cation exchange capacity
The cation exchange capacity showed slight reaction with altitude. The cation
exchange capacity of upper zone were low as compared to middle and lower zone
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soils. This variation might be due to the clay content being positively correlated with
cation exchange capacity (Sharma and Kumar, 2003). The increasing trend of cation
exchange capacity with increase in depth could be due to gradual increase in the clay
content in lower horizons. These results were in agreement with those of Sahu et al.
(1990) and Ahmad (2003).
5.3.3.7 Exchangeable cation
The exchangeable bases/cations in all the profiles irrespective of
physiography were in the order of Ca2+>Mg2+>K+>Na+ on the exchangeable
complexes. From the data it was clear that Mg2+ was present in low amount than Ca2+
because of its higher mobility and low values of exchangeable monovalents (K+ and
Na+) compared to divalents was due to preferential leaching of monovalents (Das and
Rey, 1979). In general, exchangeable cations did not exhibit any definite pattern in
their vertical distribution. These results were in accordance with those of Verma et al.
(1990), Mushki (1994) and Najar (2002).
5.3.3.8 Base saturation
The mean values of base saturation in upper, middle and lower horizon soils
were 76.90, 71.66 and 63.65 percent, respectively. The data showed that base
saturation was relatively higher in upper zone soil followed by middle and lower zone
soil. This might be due to the presence of higher amount of exchangeable cation
which followed the similar trend. Similar results were reported by Reddy and Shiva
Prasad (1999) and Kirmani (2004).
5.3.3.9 Available nutrient concentration
5.3.3.9.1 Available macronutrient concentration
The available nitrogen content increased with the increase in altitude. Major
portion of nitrogen pool is contributed by organic matter. The variation in available
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nitrogen content is attributed to the variation in organic matter/carbon content in
different zones. Similar observations were recorded by Mushki (1994) and Najar
(2002). Also the decreasing trend with the profile depth was observed in all the three
physiographic units due to decrease in organic matter with increase in soil depth. The
results are in close conformity with the findings of Talib and Verma (1990), Singh et
al. (2000) and Anjum (2012).
The available phosphorus content varied significantly in all these
physiographic zone, with higher contents recorded in upper and middle zone soil. The
available phosphorus exhibited a decreasing trend with increase in the soil depth.
These results were in agreement with those of Talib (1984) Khan et al. (1997) and
Najar (2002). The soil in general were medium to high in available Phosphorus
content which could be attributed to favourable soil reaction and formation of
organophosphate complexes and coating of iron and aluminium particles by human as
also justified in research work of Gupta et al. (1990) and Farida (1997).
The available potassium content exhibited slight variation with altitude. The
highest content of available potassium with a mean value of 78-77 kg ha-1 was
recorded in low attitude soils which might be attributed to the high clay percentage in
low altitude soil compared to high or mid altitude soil. Also an increase in the
available potassium with depth was observed due to obvious reason. Similar findings
were reported earlier by Gupta et al (1988), Najar (2002) and Anjum (2012).
The findings revealed that the available sulphur content is medium to low in
statue in all the three physiographic zones. The surface soil registered maximum
value of available content and an increase in the available sulphur with soil depth was
observed. The findings are in agreement with earlier works of Kher and Singh (1993),
Antoo (2000) and Teli (2011).
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5.3.3.9.2 Available micronutrient concentration
The mean values of Zn and cu content in soil profiles of upper, middle and
lower zone soils were 0.57 and 0.30 ppm, 0.62 and 0.29 ppm and 0.39 and 0.33 ppm
respectively. The decrease in content of both Zn and Cu was noted with increase in
soil depth which may be attributed to their positive correlation with organic carbon.
Similar findings were observed by Ganai (1999), Bhandari (1992), Wani (1994),
Sarkar et al. (2000) and Anjum (2012).
Fe and Mn had mean values of 24.68 and 16.26 ppm, 14.84 and 15.20 ppm
and 15.32 and 13.03 ppm in upper, middle and lower zone profiles, respectively. The
surface soil layer contains higher content of DTPA Fe and Mn which decreased with
increase in soil depth, which can be ascribed to low pH and high organic carbon
content in surface soils. Sharma and Bhandari (1992), Wani (1994), Dar (19960 and
Teli (2011) noted similar results.
5.4 Soil loss extraction using GIs and USLE technique
USLE parameters were derived using field and laboratory estimated data and
integrated in GIS environment to compute average soil loss and to find soil erosion
risk area in the micro-watershed. The distribution of land use/land cover, soil types
and terrain characteristics and their influence on soil erosion potential are discussed
as follows.
5.4.1 Land use/Land cover (LULC)
The land use/land cover (Fig-8) were regrouped for assigning c and p factor
values. Agriculture land covered 8% area grouped as Agriculture land-1 and 27%
area grouped as Agriculture land-2. An area of 18% was noticed under orchards and
5% area under Agriculture plantation. Forest-evergreen-open and forest scrub was
30% and 1% respectively. 4%, 5% and 2% area was under settlement, wasteland with
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Figure 8: Land use/Land cover map of Khursi micro-watershed, district Baramulla, Jammu & Kashmir
scrubs and wastelands without scrubs. vegetation cover (c) values of various LULC
varied from 0.004 to 1.0 (table 11).Highest C value was assigned to wasteland
without scrubs where as lowest C value was assigned to very dense forest cover. The
findings are in accordance with the Yadav and Sidhu (2010) and Kumar and
Kushwaha (2013).
Based on conservation practices followed in various land use/land cover types
p factor values were assigned. Forest cover in the watershed falls under reserved
Forest Category. As such no mechanical or biological measures are adopted in forest
area but it enjoys the protection from human interference. Thus, a conservation
practice factor value of 1.0 was assigned to forest land and lands with scrub without
scrub. Based on field management practices such as field bunds, tree plantation along
field boundary, P factor values were assigned. These values were assigned according
to guidelines given by Wishmeir and Smith (1978), Singh et al. (1981) and Narian et
al. (1994).
5.4.2 Soil erodibility (K) factor
Soil erodibility is an important index to evaluate the soil susceptibility to
erosion. It reflects the combined effect of soil properties of texture, stability of
structure, permeability and organic matter. Soil erodibility increases as the soil
texture becomes finer. Fine loamy soils (silt loam) have higher proportion of silt and
very fine sand, making them more susceptible to erosion. Organic matter in the soil
influences the aggregation of soil particles into stable soil structure. Soils with less
than 3.5% organic matter are considered to be erodible (Evan 1980). Higher values of
soil erodibility indicate its higher susceptibility to erosion. The soils in the watershed
were characterized and soil erodibility of surface soils were computed for each soil
mapping unit.
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Soils in steep hilly areas were characterized as excursively drained,
moderately deep silt loam to sandy loam texture, 20-30% sand separates in the
surface layer and their soil erodibility factor varies from 0.50 to 0.60. Soils in
moderately sloping areas were well drained, deep, silt loam to loam in texture and
contain 20-25% sand separates in the surface layer and their soil erodibility factors
ranged from 0.45 to 0.50. Piedmont plain soils were characterized by silt loam to silt
clay loam in texture in the surface layer and their erodibility factor ranged from 0.40-
0.45. Soils of alluvial plain lying below piedmont plain were characterized as sandy
clay loam to clay loam texture and their erodibility values ranged from 0.30-0.35.
Soil of alluvial plain and flood plain were more erodible due to fine texture and low
organic matter. These findings are in accordance with the findings of Kumar and
Kushwaha (2013).
5.4.3 Terrain slope and LS factor
The highest slope length (L) factor value was observed where overland flow
tends to accumulate in the area of concave topography and the lowest in area in area
of convex topography such as ridge, where flow diverges (Hoyos, 2005). However,
area with higher slope had high LS values. A comparison of LS factor with slope
gradient map revealed a distinct impact of steepness on LS factor. Spatial analysis of
LS factor map of the watershed indicated that 38% area occurred mainly is piedmont
plain with <5 LS value. It shows that topographic factor is largely controlling erosion
processes in various land forms of the micro-watershed. These results are also
justified by the findings of Deka et al. (2011) and Kumar and Kushwaha (2013).
5.4.4 Assessment of soil loss
Topographic and the vegetation cover factors are the most important factors
affecting soil loss in mountainous watershed (King et al., 2005; Zohu et al., 2008).
Open forests having very poor vegetation cover increases surface runoff and results
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higher soil erosion (Sidle et al., 2004). Moderately dense forests and open forests in
micro-watershed were predicted to have higher soil erosion rate than land with scrub
and without scrub (fallow land). This could be attributed to topographic factor. Very
high risk erosion areas in the micro-watershed were found to be associated with
moderate steep to steep sloping areas having scrub and open forest cover. Higher and
moderately soil erosion rate in the some areas of micro-watershed is attributed to
higher topographic and soil erodibility factors. These findings are supported by the
observations of Kumar and Khushwan (2013).
5.5 Land capability classification
The micro-watershed soils because of their site, morphological, physico-
chemical and other characteristics in respect to slope, erosion, depth, drainage etc.,
are placed in three capability classes viz., II, III and IV covering 47, 32 and 21
percent of total micro-watershed area, respectively. The subclasses identified were
IIs, IIIt, IIItw and IVe.
Class II soils (P4, P5, P6) are good cultivable lands with slight limitations and
need simple management practices.
Class III soil were moderately good cultivable land with moderate limitations
of fertility and topography (P2, P3,) and drainage (P2). Hence application of organic
manures and crop rotation with legumes can be followed in these soils. Drainage and
slope problems can be overcomed by adopting careful management practices.
Class IV soil (P1) are fairly good cultivable lands with major limitation of
erosion. So intensive soil conservation and management practices and choice of
appropriate crops may be required.
These findings are in conformity with the results of NBSS and LUP (No. 26)
and Walia and Chamuah (1990, 1994) in Kashmir and Assam, respectively.
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Chapter-6
SUMMARY AND CONCLUSION
The investigation entitled “Estimation of Soil erosion for Himalayan
Micro-Watershed using GIS Technique” was undertaken to assess extent of soil
erosion and to study the effect of soil erosion on soil quality. In this study soil
erosion was estimated using universal soil loss equation (USLE) and Geographic
Information system (GIS). The annual soil loss values estimated from the USLE were
represented pictorially using Are GIS software. In order to assess and investigate soil
quality and soil fertility status 29 surface soil samples and 6 profile samples
representing three physiographic zones viz., upper zone, middle zone and lower zone
were collected/exposed and studied. The morphological properties of soil were
described in the field and later soils were characterized in laboratory for their
physico-chemical properties. Land capability classification off micro-watershed soils
was worked out. Arc GIS was used for the preparation of the required database and
for analysis of the data for fertility maps. The findings of the investigation are
summarized under following headings.
6.1 Physico-chemical characteristics of micro-watershed soils
6.2 Fertility status of micro-watershed soils.
6.3 Characterization of micro-watershed soils
6.4 Soil loss estimation using GIS and USLE technique
6.5 Land capability classification
6.1 Physico-chemical characteristics of micro-watershed soils
The mechanical analysis of surface samples revealed that the surface texture
of upper zone soils were coarser due to removal of fixer soil fractions from upper
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zone areas. While as middle and lower zone soils had finer texture varying from silt
loam to clay loam. The pH of surface soil samples drawn from upper zone was
slightly acidic compared to the soil samples drawn from mid and lower zones. The
overall electrical conductivity of micro-watershed was within normal range with
slightly higher values in upper zone. Organic carbon content of surface soil samples
was high in upper and middle zones compared to lower zone. Calcium carbonate was
almost absent from surface samples except at few areas in upper and lower zones.
Cation exchange capacity in surface soil had a mean values of 12.90, 17.00 and 17.91
cmolc kg-1 in upper, middle and lower zones, respectively and followed the
distribution pattern of clay and organic matter content. Mean bulk densities of upper
zone and lower zone soil samples were slightly higher than middle zone soil samples.
6.2 Fertility status of micro-watershed soils.
6.2.1 Available macronutrients.
The available nitrogen in surface soil samples was medium in status with
higher content in upper and middle zone soil samples. The available phosphorus
content in surface samples was found low to medium in range due to fixation and
erosion impacts. The available potassium valued distinctly in three physiographic
zones with relatively higher quantities in lower zone soils than middle zone soils. The
available potassium in surface samples was medium to high in status. The available
sulphur in surface soil samples was found to vary between low to medium in status.
6.2.2. Available micronutrients.
Available zinc and manganese were medium to high and low to medium in
micro-watershed surface soils, respectively. Available copper and iron were low and
medium in status, respectively. Copper was major constraint among micro nutrients.
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6.3 Characterization of micro-watershed soils
6.3.1 Morphological properties of soil profiles
The colour of the studied soils had by and larger similar trend with 10 YR as
common hue on all the profiles which revealed that soils are well drained. In general
sub-surface horizon color was darker than surface horizons. The texture of soils
varied from sandy loam/sandy clay loam/ loam/ silt clay loam/ silt loam/ clay loam to
clay. The texture of lower physiographic zone was finer than upper physiographic
mainly due to lateral movement of finer fractions from higher to lower zones. The
soils in general have moderate granular to sub-angular blocky structure in the surface
and moderate to strong sub-angular blocky to angular blocky in the sub-surface
horizons which showed moderate to strong profile development.
There was a large variation in consistence in different soil profiles ranging
from hard to loose when dry, very friable to vary firm when moist and non-sticky non
plastic to very sticky very plastic when wet depending upon the clay and organic
matter content.
6.3.2 Physico-chemical properties and nutrient concentration in soil profiles
The physico-chemical properties confirmed the texture variation in all the
profiles of upper, middle and lower zones. Also clay content increased down the
profiles, indicated clay illuviation. The pH varied from being slightly acidic to neutral
and increased down the profile. Electrical conductivity was in the normal range. The
highest value of organic carbon was recorded in upper zone soils followed by middle
and lower zone soils. Also organic carbon content decreased with depth. In general
the calcium carbonate content was almost absent except at few places. Cation
exchange capacity was greatly influenced by clay and organic matter content with
higher values down the profiles due to clay illuviation. Ca2+ was dominant cation
111
followed by Mg2+ and K+ in all soil profiles. Base saturation of study area was greater
than 50 per cent in almost all profiles.
The available nitrogen concentration in surface horizons was higher and
showed gradual decrease with depth, preferably due to decrease in organic carbon.
Higher values of nitrogen were observed in the profiles of upper zone due to higher
organic carbon present as influenced by vegetative cover. The available phosphorus
content was comparably higher in upper and middle zones while as available
potassium content was high in lower zone soils due to increase in clay percentage in
lower zone. Increase in potassium content was observed with depth due to obvious
reason. DTPA extractable micronutrient was observed higher in surface horizons and
decreased with depth especially Zn and Cu, which may be attributed to positive
association with organic carbon.
6.4 Soil loss estimation using GIS and USLE technique
The study illustrated integration of USLE and GIS technology in quantifying
soil erosion and soil loss potential and to identify areas of high erosion risk for soil
conservation measure. Assessed average annual rate of soil loss was classified into
six erosion risk classes to assess erosion severity. 86.9 % area was classified as very
low, 9.47% as low and 2.39% as moderate risk of soil erosion in the micro-
watershed. Nearly 0.60%, 0.48% and 0.08% area in micro-watershed were assessed
under moderately high, high and very high risk of soil erosion. Very high and high
erosion risk areas in micro-watershed area were found to be associated with moderate
steep and steep sloping areas having scrub and open forest cover. The majority area
of the micro-watershed is subjected to very low to moderate erosion risk due to low
LS factor value and high organic carbon content of soils.
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6.5 Land capability classification
Land capability classification was carried out for the study area based on the
inherent soil characteristics, external land features and environmental factors. Over
all three capability classes viz., II, III and IV were recognized in the micro-watershed.
The sub classes in the land capability map namely IIs, IIIt, IIItw and IVe have been
differentiated.
Conclusion
The research programme is concluded with the following points.
• The integration of GIS technology with USLE made possible to assess the
land erosion process and the estimation of soil erosion rate in the area. Study
demonstrated that integration of USLE with GIS serves as robust and vital
tool in identifying spatial distribution of soil erosion risk area in the
watershed.
• The majority study area is subjected to very low to moderate erosion and can
be managed by adopting soil conservation measures. High and very high soil
erosion is a serious problem in some areas of micro-watershed area
particularly in the upper zone.
• The study reveals that erosion in the study area has a quantifiable effect on the
soil quality parameters. The loss of nutrients from upper and middle zones to
lower zone have resulted in depletion of fertility status of upper and middle
zones in this regard, the major decline was observed. cation exchange
capacity and available potassium due to the removal of clay fractions from
higher elevations.
• Soils of micro-watershed were drained to moderately well drained and have
granular to sub- angular blocky structure in most of the profiles. The surface
soils of upper zone soils were coarser due to removal of finer fractions. pH of
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the soils are slightly acidic to neutral, electrical conductivity is within normal
range and calcium carbonate was mostly absent. The soils are found low to
high in organic carbon, medium in available nitrogen, low to medium in
available phosphorus and medium to high in available potassium. Available
micronutrients were positively associated with organic carbon.
• The surface soils varied in texture from loam/ silt loam/ silt clay loam to clay
loam
• The micro-watershed was classified into three capability classes viz., II, III
and IV. The sub classes namely IIs, IIIt, IIItw and IVe have been
differentiated.
Recommendations
Based on the results of the study, the following recommendations are forwarded:
� Soil and water conservation measures should be practised in the study area
with a full consensus and participation of the farmers
� Land management practices such as agro-forestry, composting, soil fertility
management and erosion prevention measures (terracing/contour bunding)
should be practiced.
� Repair/renovation of already existing terraces and repairing of field
boundaries.
� When recommending changes in farming practices, a new approach to the
farmer is needed. Since reducing soil erosion is likely to be a less important
objective for the farmer than securing immediate food needs, recommended
changes should be shown to provide tangible results.
� Construction of mechanical conservation structures should be followed up by
other inputs, such as fertilizer, improved seeds, and other farming factors.
114
� Fencing of pastures should be done in order to avoid overgrazing. This would
make grazing lands more productive by their judicious utilization through
proper management.
� Proper utilization of areas poor in nutrients and inclusion of leguminous crops
in rotation with addition of enough organic matter.
� Further studies should be made to get more information about the soil fertility
status of the cultivated land and other related impacts on the dwellers of study
catchment.
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Appendix-I Land capability classification-quantification of the criteria Characteristics Class I Class II Class III Class IV Class V Class VI Class VII Class VIII TOPOGRAPHY Slope (%) 0-1 1-3 3-8 8-15 Upto 3 15-35 35-50 >50 Erosion nil Slight Moderate Severe Nil Severe v.severe WETNESS (w) Flooding Nil (F 0) Nil (F 0)
(F 0/F 1) Nil to slight
(F 1/F 2) Slight to moderate
(F3)
Mod. to severe (F0/F3)
Nil to severe severe(F0/F4)
Nil to very --
Drainage (1) Well Mod. Well Imperfect Poor V. poor Excessive Excessive Excessive Permeability moderate Mod. rapid Rapid, slow v. rapid,
very slow -- -- -- --
Infiltration rate (cm/hr) 2-3.5 1-2.0 3.0-5.0
0.5-1.0 5.0-10.0
<0.5 >10.0
2.0
PHYSICAL SOIL CONDITIONS (s) Surface texture Loam Sil & cl
Sicl Sl & c Scl S,c(m) Ls-cl Ls, s, c Ls, s, c(m)
Surface Stoniness (%) <1 1-3 3-5 5-8 8-15 15-40 40-75 >75 Subsurface coarse fragments (%)
<15 <15 15-35 35-50 50-75 50-75 50-75 >75
Soil depth (cm) >150 150-100 100-50 50-25 --- 25-10 25-10 <10 Profile development Cambic/
Argillic hor. A-(B)-C
A-B-C Stratified A-C;
A-B-C
Salic(Z)/ Calcic(K) hor. A-Bz-C/A-Bk-C
Az-C, A-Bz-C
Gypsic(y) hor. A-Cy
A-C (Stony) A-C
(bouldry)
FERTILITY (f) CEC (Cmol(p) kg-1) 40-16 16-12 16-12 -- -- -- -- -- Base saturation (%) 80+ 80+ 80-50 50-35 50-35 35-15 <15 -- O.C. (0-15 cm) (%) >1.0 0.75-1.0 0.5-0.75 <0.5 <0.5 -- -- -- Salinity EC (dS m-1) <1.0 1-2 2-4 4-8 8-15 15-35 35-50 >50 Gypsum (%) 0.3-2.0 2-5 5-10 10-15 15-25 >25 -- --
Appendix-II
Zone Location Elevation (m)
Latitude and longitude
Mean slope gradient (%)
Soil colour
Soil depth (cm)
Crop cover Management practices
Katyawalay 1913 34o11’2.5”N 74o22’47.2”E
41.50 Brown 120 Maize, apple orchard
Ploughing on contours
Larey 1910 34o10’35.3”N 74o23’1.6”E
27.50 Brown 120 Maize, pulses, apple orchard
Ploughing on contours
Gohan 2011 34o10’17.7”N 74o22’27.1”E
27.50 Brown 90 Maize Ploughing on contours
Larey 1941 34o10’21.9”N 74o22’39.6”E
41.50 Brown 100 Maize, pulses, apple orchard
Ploughing on contours
Larey 1959 34o9’52.1”N 74o22’29.0”E
58.00 Brown 90 Maize, apple, pear orchard
Ploughing on contours
Pachhar 1951 34o9’27.6”N 74o22’32.2”E
41.50 Brown 90 Maize, apple orchard
Ploughing on contours
Fakirbagh 1949 34o9’12.6”N 74o22’28.0”E
27.50 Grey brown
90 Maize Ploughing on contours
Chandoosa 1910 34o9’4.9”N 74o23’20.9”E
17.50 Grey brown
120 Maize, apple orchard
Ploughing up and down
Chandoosa 1910 34o9’4.9”N 74o23’20.9”E
17.50 Grey brown
120 Maize apple orchard
Ploughing on contours
Masjid Angan
1939 34o9’33.1”N 74o23’16.4”E
27.50 Brown 110 Maize apple orchard
Ploughing on contours
Upper zone (> 1900)
Vulraman 1920 34o10’2.9”N 74o23’41.8”E
17.50 Brown 110 Maize Ploughing on contours
Zone Location Elevation (m)
Latitude and longitude
Mean slope gradient (%)
Soil colour
Soil depth (cm)
Crop cover Management practices
Katyawalay 1899 34o10’40.4”N
74o23’11.4”E
20.00 Brown 120 Pulses Ploughing on contours
Vulraman 1854 34o10’21.1”N
74o24’23.7”E
12.50 Brown 110 Maize, apple orchard (newly)
Ploughing on contours
Wirnar 1793 34o10’4.8”N
74o24’22.1”E
12.50 Grey brown
110 Maize, apple orchard
Ploughing on contours
Wirnar 1796 34o10’6.5”N
74o24’24.5”E
20.00 Dark brown
120 Maize, walnut
Ploughing on contours
Hudpora 1765 34o10’41.3:N
74o24’30.1”E
20.00 Dark grey 120 Maize, apple orchard (newly)
Ploughing on contours
Fresdubh 1756 34o10’37.6”N
74o24’8.8”E
7.50 Brown 120 Maize, apple orchard
Ploughing on contours
Taki Wagura 1714 34o10’51.0”N
74o24’44.6”E
12.50 Brown 120 Pulses, vegetables,
apple orchards
Ploughing on contours
Khai Tangan 1721 34o11’6.5”N
74o24’15.5”E
4.00 Pale brown
120 Maize Ploughing up and down
Middle zone (1700-1900)
Ramzanpora 1700 34o11’12.5”N
74o24’21.8”E
4.00 Pale brown
120 Maize, apple orchards
Ploughing up and down
Zone Location Elevation
(m) Latitude and
longitude Mean slope
gradient (%) Soil
colour Soil depth
(cm) Crop cover Management
practices Potkhah 1604 34o143.9”N
74o27’31.6”E
0.50 Grey brown
120 Paddy
Nowpora Jagir
1620 34o13’1.9”N
74o27’0.0”E
2.00 Brown 120 Paddy
Muqam 1644 34o13’29.7”N
74o24’34.0”E
7.50 Pale brown
120 Maize, apple orchard
Ploughing on contours
Muqam 1609 34o13’41.1”N
74o27’18.4”E
1.50 Grey brown
120 Paddy
Khursi 1664 34o11’57.0”N
74o25’22.4”E
1.70 Pale brown
120 Maize, apple orchard
Chack 1682 34o11’30.1”N
74o24’48.7”E
7.50 Brown 120 M. P. cherry, maize, apple orchard
Ploughing on contours
Nichbattan 1667 34o11’39.3”N
74o24’57.0”E
12.50 Brown 120 Maize Ploughing on contours
Mirangund 1660 34o12’24.4”N
74o26’11.3”E
4.00 Brown 120 Vegetable, apple orchard
Ploughing up and down
Lower zone (< 1700)
Singpora 1695 34o12’35.8”N
74o25’36.2”E
2.00 Brown 120 Scrap land
Appendix-III Monthly rainfall (mm) data of the study area
Months Year
January February March April May June July August September October November December
Annual RF
(mm/Year)
2000 26.3 41.3 43.7 122.9 83.8 24.9 55.8 55.6 48.2 152.5 102.7 98.1 855.8
2001 57.9 69.7 81.6 93.7 38.7 22.8 89.4 58.7 67.3 93.4 28.6 39.4 761.2
2002 37.3 71.2 37.4 24.8 62.4 33.4 80 75.9 21.3 101.9 102.2 127.6 775.4
2003 32.8 19.3 19.4 19.4 43.1 43.7 67.6 0 22.7 36.5 88.1 59 451.6
2004 69.4 30.5 33.4 77.9 48.7 29.1 63.2 125.3 12.7 108.6 55.8 21.4 676
2005 19 43.5 55.1 30.1 22.1 57.6 43 42.75 66.3 55.9 37.8 29.7 502.85
2006 19.6 28.4 40.7 43.4 84.5 8.9 57.5 73.2 62.9 101 90.9 58.1 669.1
2007 68.5 66.8 32.7 3.7 146 136.7 110.4 31.5 34.3 93 50.3 32.9 806.2
2008 70.6 22.6 83.8 34.3 110.1 70.7 77.6 91.4 48.6 56.6 80.6 23.9 770.8
2009 36.8 60.1 22.2 30.1 31.2 55.35 120.9 65.7 9.3 42.4 95.8 78.5 648.35
2010 46.3 82 33 15.9 51.1 43.7 22.9 172.5 58.5 44.6 36.5 22.2 629.2
2011 52.70 78.90 37.88 70.87 63.40 59.20 33.20 134.76 60.77 68.76 70.38 43.75 774.57
2012 34.88 76.9 32.11 23.65 46.76 41.67 43.88 145.91 76.65 57.42 45.7 34.75 757.46
Indian Meteorological Department, Gulmarg Station
Appendix-IV Morphological characteristics of soil profiles
Profile No : P1 Location : Katyawalay Physiography : Side slope Natural vegetation : Coniferous, Cherry, Apple, Pear, Willow, Maize Slope : 10-15% Erosion : E2 Drainage : Well drained
Horizon Depth (cm) Description
Ap 0-15 10 YR 5/3 (D), Brown: 10 YR 4/3 (m), Dark brown, silt loam, coarse, moderate, granular, slightly hard (dry), friable (moist), slight sticky and slightly plastic (wet), diffused and smooth boundary, pH:6.74, effervescence nill, coarse to find many roots
AB 15-43 10 YR 3/3, Dark brown, silt loam, medium, moderate, granular, slightly hard (dry), friable (moist), slightly sticky and slightly plastic (wet), diffused and smooth boundary, pH:6.82, effervescence nill, coarse to fine common roots
Bw1 43-82 10 YR 4/4 Dark yellowish brown, silt loam, medium, moderate, angular blocky, slightly hard (dry), friable (moist), slightly sticky and slightly plastic (wet), diffused and smooth boundary, pH:6.98, effervescence nill, fine to medium common roots
Bw2 82-90 10 YR 5/4 Yellowish brown, silt loam, medium, moderate, sub-angular blocky, loose (dry), friable (moist), slightly sticky and slightly plastic (wet), pH:7.21, effervescence nill, medium to fine few roots.
Bw3 90-120 10 YR 4/4 Dark yellowish brown, silty clay loam, medium, moderate, sub-angular blocky, hard (dry) friable (moist), slightly sticky and slightly plastic (wet),pH:7.27, effervescence nill, fine to very fine few roots.
Classification: Fine loamy, mixed, mesic, family of Eutrudepts
Profile No : P2 Location : Chandoosa Physiography : Upper piedmont plain Natural vegetation : Apple, Pear, Cherry, Maize, Willow Slope : 3-8% Erosion : E1 Drainage : Imperfect drainage Horizon Depth (cm) Description
Ap 0-20 10 YR 4/2 (D) Dark grey brown: 10 YR 3/3 (M) Dark brown, silt loam, medium, moderate, granular, hard (dry), friable (moist), slightly sticky and slightly plastic (wet), thin clay cutans, diffused and smooth boundary, pH:6.30, effervescence nill, coarse to fine many roots.
Bt1 20-45 10 YR 4/2 Yellowish brown, silt clay loam, medium, moderate, angular blocky, hard (dry), firm (moist), sticky and plastic (wet), diffused and irregular boundary, pH:6.39, ffervescence nill, coarse to fine common roots.
Bt2 45-90 10 YR 3/1 Very dark grey, clay loam, medium, strong, sub angular blocky, very hard (dry) very firm (moist), sticky and plastic (wet), clear and wavy boundary, clay cutans thin and patchy, pH:6.42, effervescence nill, very fine to fine few roots.
Bt3 90-120 10 YR 4/1 Dark grey, clay loam, medium, moderate, angular blocky, very hard (dry), very firm (moist), sticky and plastic (wet), clay cutans thin and patchy, pH:6.81, effervescence nill, very fine few roots.
Classification: Fine, mixed, mesic, family of Typic hapludalfs
Profile No : P3 Location : Hudpora Physiography : Upper piedmont plain Natural vegetation : Pear, Cherry, Walnut, Maize, Wheat Slope : 3-8% Erosion : E1 Drainage : Moderately well drained Horizon Depth (cm) Description
Ap 0-19 10 YR 4/1 (D), Dark grey: 10 YR 3/1 (M), Very dark grey, clay loam, coarse, moderate, sub-angular blocky, very hard (dry), firm (moist), sticky and plastic (wet), clear and smooth boundary, pH:6.66, effervescence nill, coarse to fine many roots.
Bt1 19-32 10 YR 4/2 Dark grey brown, clay, medium, strong, angular blocky, very hard (dry), firm (moist), very sticky and plastic (wet), clear and smooth boundary, clay cutans thin and patchy, pH:6.68, effervescence nill, coarse to fine common roots.
Bt2 32-88 10 YR 4/1 Dark grey, clay, medium strong, angular blocky, very hard (dry), very firm (moist), very sticky and plastic (wet), diffused and wavy boundary, clay cutans thin and patchy, pH:6.77, effervescence nill, fine to very fine few roots.
Bt3 88-120 10 YR 3/1 Very dark grey, clay, medium, strong, angular blocky, very hard (dry), very firm (moist), very sticky and plastic (wet), thin and patchy clay cutans, pH:7.00, effervescence nill, very fine few roots
Classification: Fine, mixed, mesic, family of Typic hapludalfs
Profile No : P4 Location : Khaitangan Physiography : Upper piedmont plains Natural vegetation : Apple, Cherry, Willow, Maize, Grasses Slope : 1-3% Erosion : E1 Drainage : Moderately well drained Horizon Depth (cm) Description
Ap 0-12 10 YR 6/3 (D), Pale brown: 10 YR 5/3 (M) Brown, clay loam, medium, moderate, sub-angular blocky, very hard (dry), firm (moist), sticky and plastic (wet), clear and smooth boundary, pH:6.75, effervescence nill, coarse to fine common roots.
Bw 12-28 10 YR 7/6 Brownish yellow, sandy clay loam, fine, weak, granular, slightly hard (dry), friable (moist), slightly sticky and slightly plastic (wet), clear and smooth boundary, pH:6.82, coarse fragments 10-20%, effervescence nill, medium to fine few roots.
Bc1 28-65 10 YR 5/6 Yellowish brown, sandy loam, fine, structure less, single grain, loose (dry), very friable (moist), non-sticky and non-plastic (wet), patchy clay cutans, pH:6.88, coarse fragments 2-3%, effervescence nill, medium to very fine few roots.
Bc2 65-120 10 YR 6/6 Faint brownish yellow, sandy loam, fine structure less, single grain, loose (dry), very friable (moist), non-sticky and non-plastic (wet), patchy clay cutans, pH:7.01, effervescence nill.
Classification: Coarse loamy, mixed, mesic, family of Typic Eutrudepts
Profile No : P5 Location : Nowpore Jagir Physiography : Lower piedmont plains Natural vegetation : Apple, Pear, Cherry, Maize Slope : 1-3% Erosion : E1 Drainage : Moderately well drained Horizon Depth (cm) Description
Ap 0-16 10 YR 4/3 (D), Brown: 10 YR 3/3 (M) Dark brown, silt clay loam, medium, moderate, sub-angular blocky, hard (dry), friable (moist), sticky and plastic (wet), clear and smooth boundary, pH:7.37, effervescence nill, coarse to fine many roots.
Bw1 16-46 10 YR 4/2 Dark brown, clay loam, medium, moderate, sub-angular blocky, hard (dry), firm (moist), sticky and plastic (wet), gradual and wavy boundary, pH:7.41, effervescence nill, medium to fine common roots.
Bw2 46-85 10 YR 4/4 Dark yellowish brown, clay loam, medium, moderate, sub-angular blocky, hard (dry), firm (moist), sticky and plastic (wet), gradual and irregular boundary, thin and patchy clay cutans, pH:7.51, effervescence nill, medium to very fine few roots.
Bw3 85-120 10 YR 4/4 Dark yellowish brown, clay loam, medium, moderate, sub-angular blocky, very hard (dry), very firm (moist), very sticky and plastic (wet), thin and patchy clay cutans, pH:7.47, effervescence nill, fine to very fine few roots.
Classification: Fine, mixed, mesic, family of Typic Eutrudepts
Profile No : P6 Location : Muqam Physiography : Lower piedmont plains Natural vegetation : Apple, Pear, Cherry, Surface natural grasses Slope : 0-1% Erosion : E0 Drainage : Well drained Horizon Depth (cm) Description
Ap 0-15 10 YR 6/3 (D) Pale brown: 10 Y/R 5/4 (M) Yellowish brown, silt clay loam, medium, moderate, sub-angular blocky, slightly hard (dry), friable (moist), sticky and plastic (wet), clear and smooth boundary, pH:7.37, effervescence nill, coarse to fine many roots
Bw1 15-45 10 YR 5/3 Brown, clay loam, medium, strong, angular blocky, hard (dry), firm (moist), sticky and plastic (wet), gradual and irregular boundary, pH:7.44, effervescence nill, medium to fine common roots.
Bw2 45-80 10 YR 5/4 Yellowish brown, clay loam, medium, moderate, angular blocky, hard (dry), firm (moist), very sticky and plastic (wet), gradual and irregular boundary, thin and patchy clay cutans, pH:7.55, effervescence nill, fine to very fine few roots.
Bw3 80-120 10 YR 5/4 Brown, clay loam, medium, moderate, sub-angular blocky, hard (dry), firm (moist), sticky and plastic (wet), thin and patchy clay cutans, pH:7.45, effervescence nill, very fine few roots.
Classification: Fine loamy, mixed, mesic, family of Dystric Eutrudepts
Certificate
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This is to certify that all the modifications/corrections as suggested
by External Examiner(s) during evaluation and viva-voce examination in
the manuscript entitled, “Estimation of Soil Erosion for Himalayan
Micro-watershed using GIS Technique” submitted by Mr. Iqbal Hafiz
Ganai (Regd. No. 2010-324-D) have been taken care of before final
binding of the same.
DDrr .. MM uusshhttaaqq AAhhmmaadd WWaannii MM aajj oorr AAddvviissoorr