11 analysis of topographic transects -...

11 ANALYSIS OF TOPOGRAPHIC TRANSECTS

RESULTS AND DISCUSSION

229

In this part of the research, a detailed study focuses on the influence of climate

change on land degradation, land productivity and crop suitability along two

topographic transects in Seville, and one transect in El-Fayoum. Land component

boundaries often coincide with transitions in environmental land properties such

as soil, climate and biology (Zama et al., 2014).

11.1 SEVILLE

11.1.1 LOCATION AND SOIL INFORMATION

Seville province is located in the southwest of Andalusia, and it is the capital of

Andalusia. Seville is located between latitudes 36° 40´ and 38° 05´ N and

longitudes 6° 50´ and 4° 60´ W. To represent the variability in elevation, lithology

and soil type in this region, two soil transects (TA and TB) were considered (more

or less S-N and W-E), including 63 representative points at regular 4 km intervals.

These points were subsequently represented by 41 soil profiles from the soil

database SDBm-Seville, and 63 points of climatic data (Figure 11-1). The landforms

are characterized by less than 3.5% surface slopes with an elevation varying from

0 m to 1122 masl above sea level. Soil transect TA included 31 points; 25 soil

profiles have been chosen to represent a high variation in soil types. Soil transect

TB has 32 points and 16 soil profiles to represents the variation of this transect

(Table 11-1). Figure 11-1 shows the position of transects points and their

elevation.

Figure 11-1. Location of Seville within Spain, and the digital elevation model with the

studied soil transects.

CHAPTER 11

230

Table 11-1. Transect (T), representative soil profiles (SDBm code), horizons, depth (cm),

effective depth (cm), transect points (TP), soil type (USDA, 2010) and present land use of

TA and TB transects points. Both transects start in one common point, so TA01 and TB01

are identical.

T Code Horizons Depth TP Eff. depth Soil type Land use

TA SE0103 Ap-B2g-C1g-C2g 0-10-37-56 TA01 100 Typic Halaquept Grassland

SE0117 Ap-IIC1-IIC2-IVC3 0-20-45-70-111 TA02-

TA05

> 150 Aquic Xerofluvent Wheat and

cotton

SE0602 Ap1-Ap2-C1-C2 0-20-32-52-80 TA06-

TA07

> 150 Typic Halaquept Rice

SE1021 Ap1-Ap2-C1-C2-C3 0-20-30-52-64- TA08 > 150 Typic Fluvaquent Rice

SE1066 Ap-A3g-Bg-gD 0-10-20-65-170 TA09 > 150 Typic Haploxeralf Olive

SE1062 Ap11-Ap12-A3-B-CD-IIg2D 0-5-10-30-70-80- TA10-

TA11

> 150 Typic Hapludalfs Olive

SE1065 Ap-Ap2g-g11-g12-g21-g22-

Cgca

0-10-25-42-58-85-

160-

TA12 > 150 Typic Xerofluvent Olive

SE0710 Ap-B-C 0-20-55-110 TA13 > 150 Typic Haploxeralf Olive

SE1002 Ap-B1-C1ca-C2ca 0-20-45-65- TA14 > 150 Typic Calcixerolls Olive

SE1013 Ap-Ap2-IIB1g-IIB2g-IIICca 0-25-45-90-130- TA15 > 150 Aquic Haploxeralf Settlements

SE0412 Ap-Ap2-B2-B3ca-Cca 0-20-30-45-90- TA16 > 150 Typic Dystrudepts Agriculture

SE0993 Ap-AB-B1-BC-BCca 0-30-50-100-150- TA17 > 150 Chromic Dystruderts Agriculture

SE1010 Ap1-Ap2-B1-IIB2g-IIB22g-

IICca-IIIC

0-20-38-60-95-115-

165-

TA18 50-100 Aquic Haploxeralf Vine

SE1009 A1-A2-B1-IIB21g-IIB22g-

IIIBg-IVC

0-12-32-42-100-135-

165-

TA19 > 150 Aquic Haploxeralf Olive

SE1000 Ap-B11-B12-Cca 0-25-70-85- TA20 > 150 Vertic Calcixeroll Irrigation crops

SE0016 Ap-B1-C1ca-C2ca-IICca 0-20-45-70-100- TA21 100-150 Chromic Dystruderts Olive

SE0313 Ap-AC-C 0-30-100- TA22 > 150 EnticDystruderts Wheat

SE0309 A-R 0-20- TA23 0-25 Lithic Xerorthents Grassland

SE0635 Ap-B11-B12-C 0-20-60-110 TA24-

TA25

> 150 Typic Haploxeralfs Cotton

SE0404 Ap-B2t-BC1-BC2-R 0-10-40-70-100- TA26 > 150 Typic Haploxeralfs Forest

SE0052 A1-B2t-BC1-BC2-R 0-10-40-70-100- TA27 100 Typic Haploxeralfs Forest

SE0930 AO-A1-B-C (-5)-1-40-60- TA28 100 Typic Xerorthents Forest

SE0072 A1-AB-B2t-BC-C 0-10-30-120-150- TA29 > 150 Typic Rhodoxeralf Olive

SE0401 A1-A2-AB-B1-B2t-B3-C 0-8-15-30-55-220-

250-

TA30 > 150 Typic Palexerult Cork oak

SE0082 A1-A2-AB-B1-B2t1-B2t2 0-8-15-30-55-110- TA31 > 150 Typic Palexerult Cork oak

TB SE0103 Ap-B2g-C1g-C2g 0-10-37-56- TB01-

TB02

100 Typic Halaquept Grassland

SE1082 Ap-Bg1-Bg2-Cg 0-10-20-70-80 TB03 > 150 Chromic

Haploxererts

Sugar beet

SE0107 Ap-C 0-20- TB04-

TB05

50 Typic Xerorthents Forest cropping

SE0109 A1-Csa 0-25- TB06 50 Halic Haploxererts Grassland

SE0104 Ap1-Ap2-B1-B2-Bca-C 0-15-40-65-100-110- TB07-

TB09

> 150 Typic Haploxererts Cotton, maize

SE0818 Ap-A/C-Ca/C 0-20-35- TB10 100 Chromic

Haploxererts

Olive

SE0854 Ap1-Ap2-Ap3/C 0-10-50- TB11-

TB12

> 150 Typic Xerorthent Olive

SE0815 Ap-Ca/C-C 0-20-60- TB13 100 Typic Xerorthent Olive

SE0821 Ap-Ca/C-C 0-20-80- TB14,

TB15

50 Typic Xerorthents Olive

SE0836 Ap-B1-B2-Ca/C 0-10-30-60- TB16-

TB18

> 150 Typic Xerorthents Olive

SE0856 Ap1-Ap2/C 0-30- TB19 > 150 Typic Haploxerepts Olive

SE0855 Ap-Ca/C 0-60- TB20 > 150 Calcic Haploxerepts Olive

SE0886 Ap-Ap (B1)-B2-B2ca-Cca 0-12-42-75-90- TB21-

TB22

> 150 Typic Xerorthent Olive

SE0229 Ap-C1-C2 0-20-80- TB23-

TB25

> 150 Vertic Xerofluvent Wheat

SE0142 Ap-B-Cca 0-20-50- TB26-

TB28

> 150 Calcic Haploxerepts Agriculture

crops

SE0140 Ap-B2-B3 ca-Cca 0-20-40-70- TB29-

TB30

> 150 Calcic Haploxerepts Olive

SE0101 Ap-AC-C 0-25-35- TB31-

TB32

25 Entic Haploxeroll Olive


231

Figure 11-2. Elevation and impression of soil profiles along the studied topographic

transects TA and TB.

It is useful to study soils along transects to understand the correlation between

elevation, and physical, chemical, and mineralogical soil properties, and to assess

their suitability for crop development, taking into account the climate parameters

and the projected climatic changes.

11.1.2 CLIMATE INFORMATION

The climatic data of Seville province indicate that the total precipitation ranges

from 413 to 538 mm/year; the lowest monthly average temperature is 5°C in

January, and the warmest month is July at 35°C. Climate change scenarios have

been calculated according to the global climate model (CNRMCM3) by extracting

spatial climate data (monthly) under IPCC scenario A1B for the current period

(average data from 1960-2000), 2040, 2070 and 2100. Along the 63 studied

points, there is a high spatial variation in the climatic parameters, such as

temperature and precipitation, where the highest annual precipitation value

(990mm) is located in TA31 and the lowest precipitation in TB08 with an annual

precipitation of 403 mm. The monthly climatic parameters of the three

representative climatic points (TA01/TB01, TA31, and TB32) in the two transects

have been presented graphically

CHAPTER 11

232

Figure 11-3. CDBm outputs for the starting point (TA01 = TB01) of the topographic

transects and the final point of both transects (TA31 and TB32). Tm: temperature mean

in °C, P: precipitation in mm, ET0: reference evapotranspiration in mm, ARi: aridity index

expressed as the number of months per year in which the reference evapotranspiration

exceeds the precipitation.

for different climate change scenarios: the current situation, and projections for

2040, 2070, and 2100 (Figure 11-3).

As is shown in the Appendix, climate station TB32 has the lowest ET0 values, which

reach 1066, 1122, 921 and 1009 mm under the different climatic scenarios

(current, 2040, 2070, and 2100, respectively). On the other hand, TB03 has the

highest values with 1248, 1314, 1091, and 1296. The ARi has the lowest values in

TA31 with 6 (current, 2040 and 2070) and 7 (2100). The transect point TB11 has

the lowest values for HUi: 0.49, 0.39, 0.47 and 0.34 (under current, 2040, 2070,

2100 scenarios, respectively), TA31, on the other hand, shows the highest values

(1.15, 0.93, 1.17, and 0.91 under different scenarios respectively).


233

Annual climate indices related to land degradation have been calculated for all

points on the transects for the current climate (1961-2000) and for projections for

the future (2040, 2070, and 2100) (Appendix). Those calculated indexes include

precipitation concentration index (PCi); modified Fournier index (MFi); and Arkley

index (AKi). Although the amount of precipitation will decrease in the future, the

PCi will increase, especially in the 2100 climate scenario. The lowest MFi values

can be found in TB08 (with 50, 39, 37 and 42 under the climatic scenarios

‘current’, 2040, 2070, 2100, respectively), while the highest values are reported

for TA31 (with 147, 104, 107 and 125 under the different climatic scenarios

respectively). In the case of AKi, again, TB08 has the lowest values with 139.9,

78.3, 70.3 and 74.9; and again TA31 has the highest values (with 689.3, 500.7,

488.2 and 439.4, again corresponding to the different climate scenarios).

Figure 11-4. Development of reference evapotranspiration (A: ET0), humidity index (B:

HUi), aridity index (C: ARi), precipitation concentration index (D: PCi), modified Fournier

index (E: MFi), and Arkley index (F: AKi) over time in the projections for 2040, 2070 and

2100 for three selected points on the Seville transects.

CHAPTER 11

234

As illustrated in Figure 11-4, ET0 increases in the 2040 scenario, then decreases in

2070, followed by another increase in the 2100 scenario. HUi, on the other hand,

will first decrease in the 2040 scenario, then increases in 2070, and will decrease

again in 2100. There is not much variation in ARi between the different scenarios.

In addition, climatic indexes that are related to land degradation, such as PCi, MFi

and AKi, have been calculated by using CDBm. As shown in Figure 11-4, PCi will

increase especially under the 2100 future climatic scenario in comparison to the

current situation therefore, even though the total quantity of precipitation will

decrease in the future, precipitation is thought to be more concentrated in time.

On the other hand, AKi values will decrease under al future climatic scenarios. The

highest value of MFi is in the current situation and the lowest is predicted for

2070.

11.2 EL-FAYOUM

In the area of El-Fayoum, one topographic transect was considered (SE-NW),

including 10 representative soil profiles at regular 3.3 km intervals. Climate data

of the El-Fayoum weather station were collected and soil degradation risks under

wheat, sunflower, and olive crops under different management scenarios were

studied.

The transect from the south to the north of the province was extracted using Arc-

GIS 10.2 software. Morphological description and laboratory analyses of ten soil

profiles have been selected from an existing collection of 46 profiles. These ten

profiles were selected based on their proximity to the transect, but were originally

prepared by Haroun (2004), Ali (2005), and Hamdi (2007). A number of eight sub

transect represent the different topography, therefore, from these sites, soil types

were identified, and the sites were characterized in detail regarding soil and

topography, for example slope gradient, slope direction, and surface elevation.

Figure 11-5. The toposequence and soil profiles change from southeast (A) to

northwest (B) of El-Fayoum Province The toposequence changes from the

southeast (A) to the northwest (B) of El-Fayoum province. To illustrate this

topography, a transect was delineated from the highest elevation point (A) at

+26m above sea level where the Nile water enters into El-Fayoum province, to the

lowest elevation point (B) at -45m, close to the Qarun Lake, with an intermediate

point (AB) at +11m. These three points have been chosen to check the profiles

from the collection by doing our own soil profiles. Transect length is 33 km, and

the slope downward is about 2 m/km,


235

Figure 11-5. The toposequence and soil profiles change from southeast (A) to northwest

(B) of El-Fayoum Province.

which has been divided into eight sub-transects. This entire transect gives a good

illustration of the changing topography in El-Fayoum province, as it represents the

change in surface elevation, landscape, lithology, relief, land forms, soil units, soil

texture class, and water table depth.

It was found that the water table decreased from 150 cm below the land surface

in point A, to 90 cm in point AB, and to a distance between 25 to 0 cm below the

surface at point B, as shown in Figure 11-5. It was especially noted that in sub-

transect number 8, closest to the lake, farmers were prompted to use land for fish

farms, as soil depth of 0-25 cm led to the emergence of problems with salinity

(e.g. Baoshan 2010; Cui et al. 2008, and Sung-Ho, 2002). The urban areas were

distributed throughout all sub-transects. Soil salinity ranges from 1.68 dS/m in site

1 (water table at 150 cm, and elevation +24 m) to 54.17 dS/m in site 8 (located at

the lowest water table depth and elevation of -45m). The relationship between

CHAPTER 11

236

soil salinity and proximity of the water table to the surface is highly significant,

consistent with the view of (Rengasamy, 2006).

11.3 SOIL CONTAMINATION AND EROSION RISK

11.3.1 SEVILLE

The Pantanal and Rizal models have been applied to the different climate

scenarios (current, 2040, 2070, and 2100), and the analysis showed that the soil

degradation risk does not change under different climate change scenarios. The

risks of soil contamination and erosion have been studied in each point of the

transect TA and TB, under three vegetation type (wheat, sunflower and olive), and

under different climate scenarios (current, 2040, 2070 and 2100). The results of

the risk assessment for those three crops and four types of contaminants are

shown in Table x. Under wheat cultivation, the management vulnerability of

contamination is V4i, V4j, V4e, and V3e for phosphorus, nitrogen, heavy metals,

and pesticides, respectively. Under sunflower cultivation, the management

vulnerability classes were V1, V3, V2, and V1 under different contaminants type

respectively. In the case of olive cultivation, the management risk classes were

V2e, V4e, V2e, and V2e under different contaminants respectively.

The wind management erosion risk has the same classification (V4u) for all three

type of vegetation. In the case of the water erosivity the crops do affect the

classification: V3o in the case of wheat, V3 for sunflower, and V4z for olive.

The attainable and actual vulnerability classes depend on the point along the

transect, and on the vegetation type. Table 11-2, Table 11-3, and Table 11-4 in the

Appendix present the attainable and field vulnerability to contaminants and

erosion for each point along the two transects, and for each of the three crops.

The application of Pantanal and Rizal models have been applied under the

different climate scenarios (current-2040-2070 and 2100), the analysis showed

that soil degradation risk does not vary under different climate change scenarios.

Soil properties, climate, and elevation are the main factors that determine the

vulnerability class for erosion and contamination risk. Elevation was positively

correlated with soil moisture, mean annual precipitation, soil organic matter,

labile C and mineralizable N, microbial activities, extractable ammonium, and

denitrification potential. In contrast, bulk density, pH and soil temperature

showed a negative correlation to elevation consistent with the view of (Griffiths,

et al. 2009).


237

Table 11-2. Transect (T), transect point (TP), attainable and field vulnerability of

contamination (P: phosphorus, N: nitrogen, H: heavy metals, and X: pesticides) and

attainable and field water and wind erosion risks under wheat cultivation in each

transect point of Seville.

T TP Attainable vulnnerability Field vulnerability Attainable

erosion risk

Field erosion risk

P N H X P N H X Water Wind Water Wind

TA TA01 V2 V1 V1 V3o V2-/e V1-/e V1-/e V3o/e V2k V9e V4(k/o) V4(e/-)

TA02 V2 V1 V1 V3o V2-/e V1-/e V1-/e V3o/e V5k V10e V7(k/o) V5(e/-)

TA03 V4r V3r V3r V4ogr V5r/i V5r/j V5r/e V5ogr/e V9tr V5 V9(tr/o) V9(-/u)

TA04 V2 V1 V1 V3o V4-/i V3-/j V3-/e V4o/e V3r V8e V5(r/o) V10(e/u)

TA05 V2 V2d V1 V3o V4-/i V4d/j V3-/e V4o/e V5r V10e V7(r/o) V10(e/u)

TA06 V3r V2r V3r V4r V5r/i V4r/j V5r/e V5r/e V7tr V9e V8(tr/o) V10(e/u)


TA08 V2 V2 V2 V3o V4-/i V4-/j V4-/e V4o/e V1 V10e V2(-/o) V10(e/u)

TA09 V3r V2r V3d V4r V5r/i V4r/j V5d/e V5r/e V1 V8e V2(-/o) V10(e/u)

TA10 V1 V1 V1 V1 V3-/i V3-/j V3-/e V2-/e V4r V8e V6(r/o) V10(e/u)

TA11 V4r V2r V3r V4or V5r/i V4r/j V5r/e V5or/e V3r V9e V5(r/o) V10(e/u)

TA12 V4r V3dr V3r V2r V5r/i V5dr/j V5r/e V4r/e V7tr V8e V8(tr/o) V10(e/u)


TA14 V4r V2r V3d V2r V5r/i V4r/j V5d/e V4r/e V6r V3 V8(r/o) V7(-/u)

TA15 V4r V3r V3r V4ogr V5r/i V5r/j V5r/e V5ogr/e V8t V8e V8(t/o) V10(e/u)

TA16 V3r V2r V3d V4r V5r/i V4r/j V5d/e V5r/e V3r V8e V5(r/o) V10(e/u)

TA17 V4 V3r V4r V4r V5-/i V5r/j V5r/e V5r/e V8 V9e V8(-/o) V10(e/u)

TA18 V4 V3c V4cr V3o V5-/i V5c/j V5cr/e V4o/e V7 V9e V8(-/o) V10(e/u)

TA19 V4 V2 V2 V2 V5-/i V4-/j V4-/e V4-/e V4r V5 V6(r/o) V9(-/u)

TA20 V3r V2r V3r V4r V5r/i V4r/j V5r/e V5r/e V7tr V8e V8(tr/o) V10(e/u)



TA23 V4 V3dr V4r V4ogr V5-/i V5dr/j V5r/e V5ogr/e V9tr V9e V9(tr/o) V10(e/u)

TA24 V4r V3dr V3r V4org V5r/i V5dr/j V5r/e V5org/e V2 V10e V4(-/o) V10(e/u)

TA25 V3r V2r V3r V4or V5r/i V4r/j V5r/e V5or/e V10tk V10e V9(tk/o) V10(e/u)


TA27 V4r V3dr V3r V4org V5r/i V5dr/j V5r/e V5org/e V6kr V9e V8(kr/o) V10(e/u)

TA28 V1 V1 V1 V2 V3-/i V3-/j V3-/e V4-/e V3 V8e V5(-/o) V10(e/u)

TA29 V4r V2r V3r V4or V5r/i V4r/j V5r/e V5or/e V8 V8e V8(-/o) V10(e/u)

TA30 V3r V2r V3d V4r V5r/i V4r/j V5d/e V5r/e V5 V8e V7(-/o) V10(e/u)


TB TB01 V2 V1 V1 V3o V2-/e V1-/e V1-/e V3o/e V2k V9e V4(k/o) V4(e/-)

TB02 V2 V2d V1 V4og V4-/i V4d/j V3-/e V5og/e V2 V7 V4(-/o) V10(-/u)

TB03 V4 V3dr V4r V3r V5-/i V5dr/j V5r/e V4r/e V7tr V8e V8(tr/o) V10(e/u)

TB04 V2 V3 V3 V2 V4-/i V5-/j V5-/e V4-/e V3r V3 V5(r/o) V7(-/u)

TB05 V3r V2r V3d V4r V5r/i V4r/j V5d/e V5r/e V4r V5 V6(r/o) V9(-/u)

TB06 V4 V4cr V4cr V4ogr V5-/i V5cr/j V5cr/e V5ogr/e V3r V10e V5(r/o) V10(e/u)

TB07 V4 V3r V3r V4or V5-/i V5r/j V5r/e V5or/e V8 V10e V8(-/o) V10(e/u)

TB08 V2 V1 V1 V2 V4-/i V3-/j V3-/e V4-/e V3r V6e V5(r/o) V9(e/u)

TB09 V1 V2 V1 V1 V3-/i V4-/j V3-/e V2-/e V6kr V3 V8(kr/o) V7(-/u)

TB10 V2 V3c V3c V2 V4-/i V5c/j V5c/e V4-/e V4 V10e V6(-/o) V10(e/u)

TB11 V3r V2r V3r V4or V5r/i V4r/j V5r/e V5or/e V7 V5 V8(-/o) V9(-/u)

TB12 V3r V2r V3d V4or V5r/i V4r/j V5d/e V5or/e V5 V8e V7(-/o) V10(e/u)

TB13 V3r V2r V3r V4r V5r/i V4r/j V5r/e V5r/e V9tr V8e V9(tr/o) V10(e/u)

TB14 V3r V2r V3d V4r V5r/i V4r/j V5d/e V5r/e V6t V8e V8(t/o) V10(e/u)

TB15 V4rl V4ld V4rl V4lor V5rl/i V5ld/j V5rl/e V5lor/e V6r V3 V8(r/o) V7(-/u)

TB16 V4r V3r V3r V3r V5r/i V5r/j V5r/e V4r/e V7tr V8e V8(tr/o) V10(e/u)

TB17 V2 V2 V2 V3o V4-/i V4-/j V4-/e V4o/e V8t V7 V8(t/o) V10(-/u)

TB18 V3r V2r V3d V3r V5r/i V4r/j V5d/e V4r/e V5 V8e V7(-/o) V10(e/u)


TB20 V4 V3r V3r V4r V5-/i V5r/j V5r/e V5r/e V7tr V9e V8(tr/o) V10(e/u)

TB21 V4r V2r V3r V4or V5r/i V4r/j V5r/e V5or/e V6r V10e V8(r/o) V10(e/u)

TB22 V4r V2r V3r V3ogr V5r/i V4r/j V5r/e V4ogr/e V6r V7 V8(r/o) V10(-/u)


TB24 V1 V1 V1 V3o V3-/i V3-/j V3-/e V4o/e V4r V8e V6(r/o) V10(e/u)

TB25 V3 V2 V2 V3o V5-/i V4-/j V4-/e V4o/e V6r V9e V8(r/o) V10(e/u)

TB26 V3r V2r V3d V4r V5r/i V4r/j V5d/e V5r/e V4r V8e V6(r/o) V10(e/u)

TB27 V3r V2r V3d V4r V5r/i V4r/j V5d/e V5r/e V6r V8e V8(r/o) V10(e/u)

TB28 V2 V1 V2 V3o V4-/i V3-/j V4-/e V4o/e V6kr V6 V8(kr/o) V9(-/u)

TB29 V4 V3dr V3r V4rg V5-/i V5dr/j V5r/e V5rg/e V6r V8e V8(r/o) V10(e/u)

TB30 V3r V2r V3r V4or V5r/i V4r/j V5r/e V5or/e V8 V8e V8(-/o) V10(e/u)

TB31 V4 V2r V3r V4or V5-/i V4r/j V5r/e V5or/e V5r V10e V7(r/o) V10(e/u)

TB32 V3 V2 V2 V3o V5-/i V4-/j V4-/e V4o/e V1 V9e V2(-/o) V10(e/u)

CHAPTER 11

238



attainable and field water and wind erosion risks under sunflower cultivation in each

transect point of Seville.


erosion risk

Field erosion risk


TA TA01 V2 V1 V1 V3o V1-/- V3-/j V1-/- V2o/- V2k V9e V4(k/-) V10(e/u)

TA02 V2 V1 V1 V3o V1-/- V3-/j V1-/- V2o/- V5k V10e V7(k/-) V10(e/u)






TA08 V1 V1 V1 V2 V1-/- V3-/j V1-/- V1-/- V3k V9e V5(k/-) V10(e/u)



TA11 V2 V2 V2 V2 V1-/- V4-/j V2-/- V1-/- V1 V9e V2(-/-) V10(e/u)

TA12 V2 V2 V2 V2 V1-/- V4-/- V2-/- V1-/- V1 V9e V2(-/-) V10(e/u)

TA13 V2 V2 V1 V3o V1-/- V4-/- V1-/- V2o/- V1 V9e V2(-/-) V10(e/u)



TA16 V4 V2 V2 V2 V2-/- V4-/- V2-/- V1-/- V2k V8e V4(k/-) V10(e/u)

TA17 V1 V1 V1 V2 V1-/- V2-/- V1-/- V1-/- V2k V8e V4(k/-) V10(e/u)

TA18 V4 V3cd V3cr V4og V2-/- V4cd/- V3cr/- V2og/- V2k V10e V4(k/-) V10(e/u)


TA20 V2 V1 V1 V3o V1-/- V2-/- V1-/- V2o/- V2k V10e V4(k/-) V10(e/u)

TA21 V2 V1 V1 V3o V1-/- V2-/- V1-/- V2o/- V2k V10e V4(k/-) V10(e/u)








TA29 V4 V3r V3r V4r V2-/- V4r/- V3r/- V2r/- V6k V5e V8(k/-) V9(e/u)

TA30 V4 V3c V4cr V3o V2-/- V4c/- V4cr/- V2o/- V3 V7e V5(-/-) V10(e/u)

TA31 V4 V3c V4cr V4o V2-/- V4c/- V4cr/- V2o/- V3 V5e V5(-/-) V9(e/u)

TB TB01 V2 V1 V1 V3o V1-/- V3-/j V1-/- V2o/- V2k V9e V4(k/-) V10(e/u)

TB02 V2 V1 V1 V3o V1-/- V2-/- V1-/- V2o/- V2k V9e V4(k/-) V10(e/u)

TB03 V2 V1 V1 V3o V1-/- V2-/- V1-/- V2o/- V2k V9e V4(k/-) V10(e/u)

TB04 V2 V1 V1 V3o V1-/- V2-/- V1-/- V2o/- V1 V9e V2(-/-) V10(e/u)


TB06 V1 V1 V1 V2 V1-/- V2-/- V1-/- V2o/- V1 V9e V2(-/-) V10(e/u)

TB07 V1 V1 V1 V2 V1-/- V2-/- V1-/- V1-/- V2k V8e V4(k/-) V10(e/u)



TB10 V1 V1 V1 V1 V1-/- V2-/- V1-/- V1-/- V1 V8e V2(-/-) V10(e/u)

TB11 V3r V2r V3d V4r V2r/- V4r/- V3d/- V2r/- V1 V8e V2(-/-) V10(e/u)

TB12 V3r V2r V3d V4r V2r/- V4r/- V3d/- V2r/- V2 V8e V4(-/-) V10(e/u)

TB13 V4r V3r V3r V4or V2r/- V4r/- V3r/- V2or/- V6 V10e V8(-/-) V10(e/u)





TB18 V1 V1 V1 V2 V1-/- V2-/- V1-/- V1-/- V1 V8e V2(-/-) V10(e/u)



TB21 V3r V2r V3r V4r V2r/- V4r/- V3r/- V2r/- V2k V8e V4(k/-) V10(e/u)


TB23 V4r V2r V3r V4or V2r/- V4r/- V3r/- V2or/- V7t V9e V8(t/-) V10(e/u)








TB31 V4r V2r V3r V4or V2r/- V4r/- V3r/- V2or/- V5t V9e V7(t/-) V10(e/u)



239



attainable and field water and wind erosion risks under olive cultivation in each transect

point of Seville.


erosion risk

Field erosion risk


TA TA01 V2 V1 V1 V3o V2-/e V3-/e V1-/e V3o/e V2k V9e V6(k/z) V10(e/u)

TA02 V2 V1 V1 V3o V2-/e V3-/e V1-/e V3o/e V5k V10e V9(k/z) V10(e/u)






TA08 V1 V1 V1 V2 V1-/e V3-/e V1-/e V2-/e V3k V9e V7(k/z) V10(e/u)



TA11 V2 V2 V2 V2 V2-/e V4-/e V2-/e V2-/e V1 V9e V3(-/z) V10(e/u)


TA13 V2 V2 V1 V3o V2-/e V4-/e V1-/e V3o/e V1 V9e V3(-/z) V10(e/u)





TA18 V4 V3cd V3cr V4og V4-/e V5cd/e V3cr/e V4og/e V2k V10e V6(k/z) V10(e/u)










TA28 V3 V3r V3r V4r V4-/e V5r/e V3r/e V4r/e V6k V5e V9(k/z) V9(e/u)

TA29 V4 V3r V3r V4r V4-/e V5r/e V3r/e V4r/e V6k V5e V9(k/z) V9(e/u)

TA30 V4 V2c V3cr V3o V4-/e V4c/e V3cr/e V3o/e V2 V10e V6(-/z) V10(e/u)

TA31 V4 V2c V4cr V4o V4-/e V4c/e V4cr/e V4o/e V2 V9e V6(-/z) V10(e/u)

TB TB01 V2 V1 V1 V3o V2-/e V3-/e V1-/e V3o/e V2k V9e V6(k/z) V10(e/u)

TB02 V2 V1 V1 V3o V2-/e V3-/e V1-/e V3o/e V2k V9e V6(k/z) V10(e/u)

TB03 V2 V1 V1 V3o V2-/e V3-/e V1-/e V3o/e V2k V9e V6(k/z) V10(e/u)

TB04 V2 V1 V1 V3o V2-/e V3-/e V1-/e V3o/e V1 V9e V3(-/z) V10(e/u)


TB06 V1 V1 V1 V2 V1-/e V3-/e V1-/e V2-/e V2k V8e V6(k/z) V10(e/u)




TB10 V1 V1 V1 V1 V1-/e V3-/e V1-/e V1-/e V1 V8e V3(-/z) V10(e/u)

TB11 V3r V2r V3d V4r V3r/e V4r/e V3d/e V4r/e V1 V8e V3(-/z) V10(e/u)

TB12 V3r V2r V3d V4r V3r/e V4r/e V3d/e V4r/e V2 V8e V6(-/z) V10(e/u)

TB13 V4r V3r V3r V4or V4r/e V5r/e V3r/e V4or/e V6 V10e V9(-/z) V10(e/u)





TB18 V1 V1 V1 V2 V1-/e V3-/e V1-/e V2-/e V1 V8e V3(-/z) V10(e/u)



TB21 V3r V2r V3r V4r V3r/e V4r/e V3r/e V4r/e V2k V8e V6(k/z) V10(e/u)


TB23 V4r V2r V3r V4or V4r/e V4r/e V3r/e V4or/e V7t V9e V10(t/z) V10(e/u)








TB31 V4r V2r V3r V4or V4r/e V4r/e V3r/e V4or/e V5t V9e V9(t/z) V10(e/u)


CHAPTER 11

240

11.3.2 EL-FAYOUM

In the El-Fayoum transect, the risks of soil contamination and erosion have been

studied in each point of the transect TC, under three vegetation types (again

wheat, sunflower and olive), and under different irrigation scenarios. As is shown

in Table 11-5 and Table 11-6 shows the vulnerabilities to contamination and

erosion are the same for all points along the transect, and vary depending on the

crop type and the irrigation scenario.

As shown in Table 11-7, Table 11-8, and Table 11-9, the attainable risks of erosion

and contamination does not change under the different scenarios of irrigation

management and also no changes under wheat, sunflower and olive cultivations.

The crop that has more risk of contamination is wheat compared with sunflower

and olive. Scenario 4 has lowest contamination and water erosion risks, and in

contrast, scenario 1 has the highest risk of contamination and water erosion

compared with other scenarios. Extreme wind erosion is found under scenario 4,

so the surrounding areas of El-Fayoum depression are vulnerable to wind erosion.

The erosion risk increased under olive and sunflower cultivations and decreased

under wheat crop.

Table 11-5. Management vulnerability to contamination under the cultivation of

different crops, in each soil transect point of El-Fayoum, under different management

scenarios. All points along the transect are grouped, as they do not differ in their

vulnerability classification.

Scenario TP Wheat Sunflower Olive

P N H X P N H X P N H X

1 TC01 -TC10 V4i V4j V4q V4t V4i V4j V4q V4t V4e V4j V4q V4t

2 TC01 -TC10 V4i V2 V4q V3 V4i V4j V4q V2 V3 V4j V4q V3

3 TC01 -TC10 V3 V2 V4q V2 V3 V2 V4q V2 V2 V2 V2 V1

4 TC01 -TC10 V2e V2e V2e V2e V2e V2e V2e V2e V2e V2e V2e V2e

Table 11-6. Management vulnerability to erosion under the cultivation of different

crops, in each soil transect points (TP) of El-Fayoum, under different management

scenarios. All points along the transect are grouped, as they do not differ in their

vulnerability classification.

Scenario TP Wheat Sunflower Olive

1 TC01 -TC10 V2 V4u V4u

2 TC01 -TC10 V1 V2 V3

3 TC01 -TC10 V1 V2 V3

4 TC01 -TC10 V4c V4u V4u


241

Table 11-7. Attainable and field vulnerability to contamination, attainable wind erosion

risnk (AWER) and field wind erosion risk (FWER) under wheat cultivation, in each

transect point (TP) of El-Fayoum, under different management scenarios.

Scenario TP Attainable vulnerability Field vulnerability AWER FWER

P N H X P N H X

1 TC01 V1 V1 V1 V1 V3-/i V3-/j V3-/q V3-/t V6 V5(-/-)

TC02 V1 V1 V1 V3g V3-/i V3-/j V3-/q V5g/t V8e V6(e/-)


TC04 V1 V1 V1 V2 V3-/i V3-/j V3-/q V4-/t V8e V6(e/-)


TC06 V2 V1 V1 V3o V4-/i V3-/j V3-/q V5o/e V9e V7(e/-)





2 TC01 V1 V1 V1 V1 V3-/i V1-/- V3-/q V2-/- V6e V3(e/-)

TC02 V1 V1 V1 V3g V3-/i V1-/- V3-/q V4g/- V8e V4(e/-)


TC04 V1 V1 V1 V2 V3-/i V1-/- V3-/q V4-/- V8e V4(e/-)


TC06 V2 V1 V1 V3o V4-/i V1-/- V3-/q V4o/- V9e V4(e/-)




TC10 V1 V1 V1 V1 V3-/i V1-/- V3-/q V2-/- V6 V3(-/-)

3 TC01 V1 V1 V1 V1 V2-/- V1-/- V3-/q V1-/- V6e V3(e/-)

TC02 V1 V1 V1 V3g V2-/- V1-/- V3-/q V3g/- V8e V4(e/-)


TC04 V1 V1 V1 V2 V2-/- V1-/- V3-/q V2-/- V8e V4(e/-)


TC06 V2 V1 V1 V3o V4-/- V1-/- V3-/q V3o/- V9e V4(e/-)





4 TC01 V1 V1 V1 V1 V1-/e V1-/e V1-/e V1-/e V6e V9(e/c)

TC02 V1 V1 V1 V3g V1-/e V1-/e V1-/e V3g/e V8e V10(e/c)


TC04 V1 V1 V1 V2 V1-/e V1-/e V1-/e V2-/e V8e V10(e/c)

TC05 V1 V1 V1 V1 V1-/e V1-/e V1-/e V1-/e V6 V9(-/c)

TC06 V2 V1 V1 V3o V2-/e V1-/e V1-/e V3o/e V9e V10(e/c)





CHAPTER 11

242


risnk (AWER) and field wind erosion risk (FWER) under sunflower cultivation, in each

transect point (TP) of El-Fayoum, under different management scenarios.


P N H X P N H X

1 TC01 V1 V1 V1 V1 V3-/i V3-/j V3-/q V3-/t V6e V6(-/z)

TC02 V1 V1 V1 V3g V3-/i V3-/j V3-/q V5g/t V8e V6(k/z)


TC04 V1 V1 V1 V2 V3-/i V3-/j V3-/q V4-/t V8e V6(k/z)


TC06 V2 V1 V1 V3o V4-/i V3-/j V3-/q V5o/t V9e V6(-/z)




2 TC10 V1 V1 V1 V1 V3-/i V3-/j V3-/q V3-/t V6e V6(k/z)

TC01 V1 V1 V1 V1 V3-/i V3-/j V3-/q V1-/- V6e V1(-/-)

TC02 V1 V1 V1 V3g V1-/- V2-/- V1-/- V2g/- V8e V4(k/-)

TC03 V1 V1 V1 V3g V3-/i V3-/j V3-/q V3g/- V8e V1(k/-)

TC04 V1 V1 V1 V2 V3-/i V3-/j V3-/q V2-/- V8e V1(k/-)


TC06 V2 V1 V1 V3o V4-/i V3-/j V3-/q V3o/- V9e V1(-/-)


TC08 V1 V1 V1 V3g V3-/i V3-/j V3-/q V3g/- V8e V1(k/-)


3 TC10 V1 V1 V1 V1 V3-/i V3-/j V3-/q V1-/- V6 V1(k/-)

TC01 V1 V1 V1 V1 V2-/- V1-/- V3-/q V1-/- V6e V1(-/-)

TC02 V1 V1 V1 V3g V2-/- V1-/- V3-/q V3g/- V8e V1(k/-)


TC04 V1 V1 V1 V2 V2-/- V1-/- V3-/q V2-/- V8e V1(k/-)


TC06 V2 V1 V1 V3o V1-/- V2-/- V1-/- V2o/- V9e V4(-/-)




4 TC10 V1 V1 V1 V1 V2-/- V1-/- V3-/q V1-/- V6e V1(k/-)

TC01 V1 V1 V1 V1 V1-/e V1-/e V1-/e V1-/e V6e V1(-/-)

TC02 V1 V1 V1 V3g V1-/e V1-/e V1-/e V3g/e V8e V1(k/-)


TC04 V1 V1 V1 V2 V1-/e V1-/e V1-/e V2-/e V8e V1(k/-)


TC06 V2 V1 V1 V3o V2-/e V1-/e V1-/e V3o/e V9e V4(-/-)




TC10 V1 V1 V1 V1 V1-/e V1-/e V1-/e V1-/e V6e V9(e/u)


243


risnk (AWER) and field wind erosion risk (FWER) under olive cultivation, in each transect

point (TP) of El-Fayoum, under different management scenarios.


P N H X P N H X

1 TC01 V1 V1 V1 V1 V3-/e V3-/j V3-/q V3-/t V6e V6(-/z)

TC02 V1 V1 V1 V3g V3-/e V3-/j V3-/q V5g/t V8e V6(k/z)


TC04 V1 V1 V1 V2 V3-/e V3-/j V3-/q V4-/t V8e V6(k/z)


TC06 V2 V1 V1 V3o V4-/e V3-/j V3-/q V5o/t V9e V6(-/z)




2 TC10 V1 V1 V1 V1 V3-/e V3-/j V3-/q V3-/t V6e V6(k/z)

TC01 V1 V1 V1 V1 V2-/- V3-/j V3-/q V2-/- V6e V2(-/-)

TC02 V1 V1 V1 V3g V2-/- V3-/j V3-/q V4g/- V8e V2(k/-)


TC04 V1 V1 V1 V2 V2-/- V3-/j V3-/q V4-/- V8e V2(k/-)


TC06 V2 V1 V1 V3o V4-/- V3-/j V3-/q V4o/- V9e V2(-/-)

TC07 V3r V2r V3d V4r V3r/e V4r/e V3d/e V4r/e V8e V6(-/z)



3 TC10 V1 V1 V1 V1 V2-/- V3-/j V3-/q V2-/- V6 V2(k/-)

TC01 V1 V1 V1 V1 V1-/- V1-/- V1-/- V1-/- V6e V1(-/-)



TC04 V1 V1 V1 V2 V1-/- V1-/- V1-/- V1-/- V8e V1(k/-)

TC05 V1 V1 V1 V1 V1-/- V1-/- V1-/- V1-/- V6e V1(k/-)

TC06 V2 V1 V1 V3o V2-/- V1-/- V1-/- V2o/- V9e V1(-/-)

TC07 V1 V1 V1 V1 V1-/- V1-/- V1-/- V1-/- V6e V1(k/-)


TC09 V1 V1 V1 V2 V1-/- V1-/- V1-/- V1-/- V8e V1(k/-)

4 TC10 V1 V1 V1 V1 V1-/- V1-/- V1-/- V1-/- V6e V1(k/-)

TC01 V1 V1 V1 V1 V1-/e V1-/e V1-/e V1-/e V6e V1(-/-)





TC06 V2 V1 V1 V3o V2-/e V1-/e V1-/e V3o/e V9e V1(-/-)





11.4 BIOCLIMATIC LIMITATION, AND LAND CAPABILITY

11.4.1 SEVILLE

The Terraza model was run for each point of transects TA and TB (63 points), to

study the response of wheat and sunflower productivity to climate change in

different climatic locations and different climate projections (current, 2040, 2070

and 2100). In both studied transects, climate change will have a negative impact

on water availability and crop yield. Climate change will affect sunflower

CHAPTER 11

244

cultivation more than wheat, especially in the projected scenario for 2100. The

transect points that experience the highest impact of climate change are TA15,

TA18, TA23, TB16, and TB32, where lower water availability will result in a higher

water deficit and more severe yield reduction compared to the other transects

point (Figure 11-6). The vulnerability of agriculture to changing environmental

conditions may be the most dangerous short-term consequence of climate

change; therefore, predictions on the effect of the geography on changes will be

useful to implement mitigation strategies (Beck, 2013).

Kitchen et al. (2003) demonstrate that multiple factors can affect yield, and the

relationship between yield, topography and soil properties can be nonlinear in

nature and many potential interactions between variables exist. Rabe (2007)

found a strong multivariate relationship between the topographic derivatives and

three years of yield data, using the slope map as the partitioning factor for zone

management (i.e. 2002 wheat yield r2=0.94; 2003 pea yield r

2=0.79; 2005 wheat

yield r2=0.91). The traditional soil survey was not as effective for zone

management (i.e. 2002 to 2005 yield r2 from 0.35 to 0.62). Relationships between

yield and topography are known to vary substantially from year to year. Boundary

line analysis combined with nonparametric spline regression was found to be a

useful diagnostic tool to identify yield potential and to describe complexly shaped

relationships between yield and topography (Huang et al., 2008). Several

researchers have studied the effects of topography and precipitation on yield

variability for major crops, such as maize, soybean and wheat (e.g. Jiang and

Thelen 2004; Si and Farrell 2004).

The Cervanta model was run for each point of transect TA and TB to predict the

land capability; results indicate that the land capability classes varied from good

land capability classes (S2l) to the marginal classes (Ntl and Nlb). The bioclimatic

limitation appears to be an important limiting factor, especially in climate scenario

2100. The soil profiles with shallow profile depths, such as E0309 (TA23) and

SE0101 (TB31) have been classified as marginal land capability class Nl and Ntl,

respectively.


245

Figure 11-6. Water surplus, water deficit and yield reduction under projected climate

change scenarios (Current-2040-2070-2100) under wheat crop and sunflower crops for

transect TA and TB.

CHAPTER 11

246

Table 11-10. Land capability for wheat and sunflower crops, for the soil profiles along

the transects, and under projected climate scenarios (current, 2040, 2070 and 2100).

Limitation factors; t: topography (slope type and slope gradient), l: soil (useful depth,

texture, stoniness/rockiness, drainage, and salinity), r: erosion risk (soil erodibility,

slope, vegetation cover, and rainfall erosivity), b: bioclimatic limitation.

Transect SDBm code Wheat Sunflower

Current 2040 20070 21000 Current 2040 2070 2100 TA01 SE0103 S3l S3l S3l S3l S3l S3l S3lb S3l

TA02 to TA07 SE0117, SE0602 S3l S3l S3l S3l S3l S3l S3l S3l

TA08 SE1021 S3l S3l S3l S3l S3l S3l S3lb S3l

TA09,TA10 SE1066, SE1062 S2lrb S2lr S2lr S2lr S2lrb S2lrb S2lrb S2lrb

TA11 SE1062 S2trb S2tr S2tr S2tr S2trb S2trb S2trb S2trb

TA12, TA13 SE1065, SE0710 S2rb S2r S2r S2r S2rb S2rb S2rb S2rb

TA14 SE1002 S2rb S2r S2r S2r S2rb S2r S2rb S2r

TA15 SE1013 S2lb S2l S2l S2l S3b S3b S3b S3b

TA16 SE0412 S2lrb S2lr S2lr S2lr S2lrb S2lrb S2lrb S2lrb

TA17 SE0993 S3l S3l S3l S3l S3l S3l S3l S3l

TA18 SE1010 S3l S3l S3l S3l S3lb S3lb S3lb S3lb

TA19 SE1009 S3l S3l S3l S3l S3l S3l S3l S3l

TA20, TA21 SE1000, SE0016 S2rb S2rb S2r S2r S2rb S2rb S2rb S2rb

TA22 SE0313 S3b S2trb S2tr S2tr S3b S2trb S2tr S2tr

TA23 SE0309 Nl Nl Nl Nl Nl Nl Nlb Nlb

TA24 to TA27 SE0635, SE0404,

SE0052

S3b S3b S2rb S2rb S3b S3b S2rb S2rb

TA28, TA29 SE0930, SE0072 S3lb S3lb S3lb S3l S3lb S3lb S3lb S3l

TA30 SE0401 S3lrb S3lrb S3lrb S3lr S3lrb S3lrb S3lrb S3lr

TA31 SE0082 S3b S3b S3b S3r S3b S3b S3b S3r

TB01 to TB03 SE0103, SE1082 S3l S3l S3l S3l S3l S3l S3lb S3l

TB04 SE0107 S2lrb S2lr S2lr S2lr S3b S3b S3b S3b

TB05 SE0107 S2lr S2lr S2lr S2lr S3b S3b S3b S3b

TB06 SE0109 S2l S2l S2l S2l S3b S3b S3b S3b

TB07 to TB09 SE0104 S3l S3l S3l S3l S3l S3l S3l S3l

TB10 SE0818 S2lrb S2lr S2lr S2lr S2lrb S2lrb S3b S3b

TB11 SE0854 S2lrb S2lrb S2lr S2lr S2lrb S2lrb S3b S3b

TB12 SE0854 S2lrb S2lrb S2lr S2lr S2lrb S2lrb S2lrb S2lrb

TB13 SE0815 S2tlrb S2tlrb S2tlr S2tlr S2tlrb S2tlrb S2tlrb S2tlrb

TB14 SE0821 S2lrb S2lrb S2lr S2lr S2lrb S2lrb S2lrb S2lrb

TB15 SE0821 S2lrb S2lrb S2lrb S2lr S2lrb S2lrb S3b S2lrb

TB16 SE0836 S2lrb S2lrb S2lrb S2lr S3b S3b S3b S3b

TB17, TB18 SE0836 S2lrb S2lrb S2lrb S2lrb S2lrb S2lrb S2lrb S2lrb

TB19, TB20 SE0856, SE0855 S2lrb S2lrb S2lrb S2lr S2lrb S2lrb S2lrb S2lr

TB21, TB22 SE0886 S2lrb S2lrb S2lr S2lr S2lrb S2lrb S2lrb S2lrb

TB23 SE0229 S3t S3t S3t S3t S3t S3t S3tb S3t

TB24, TB25 SE0229 S3r S3r S3r S3r S3r S3r S3r S3r

TB26 SE0142 S3r S3r S3r S3r S3r S3r S3r S3r

TB27, TB28 SE0142 S2lrb S2lrb S2lr S2lr S2lrb S2lrb S2lrb S2lrb

TB29, TB30 SE0140 S3r S3r S3r S3r S3r S3r S3r S3r

TB31 SE0101 Ntl Ntl Ntl Ntl Ntl Ntl Ntl Ntl

TB32 SE0101 Nl Nl Nl Nl Nl Nl Nl Nl


247

Table 11-11. Land capability for wheat and sunflower crops, for the soil profiles along

the transect, under the different irrigation scenarios. Limitation factors: l: soil (useful

depth, texture, stoniness/rockiness, drainage, salinity), r: erosion risk (soil erodibility,

slope, vegetation cover, and rainfall erosivity), b: bioclimatic limitation.

Transect point SDBm code Scenarios 1, 2 Scenario 3 Scenario 4

TC01 FA-H21 S2l S2l Nb





TC06 FA-A07 S3l S3l Nb



TC09 FA-A16 Nl Nlb Nlb

TC10 FA-H08 Nl Nlb Nlb

11.4.2 EL-FAYOUM

The calculation of the bioclimatic limitation depends mainly on the climate data

and the amount of useful water for each soil type. El-Fayoum has only one climate

station and just six soil types. Land capability changes along the transect, where

the starting points of the transect have a good land capability class (S2l), the

intermediate part has a moderate class (S3l), and the final part of the transect has

a marginal class (Nl). This classification only applies to irrigation scenarios 1, 2,

and 3, because a loss of irrigation water input will result in the entire transect

being classified as marginal soil (scenario 4). The land capability results did not

vary (between sunflower and wheat) as much as the output results for Andalusia.

11.5 CROP SUITABILITY

Agricultural land suitability analysis to help to improve soils by addressing

limitations can be an adaptation strategy to climate change. The study aims to

investigate the influence of topography and the variability of soil factors on crop

suitability for 12 annual, semiannual, and perennial Mediterranean crops, along

the transects in Seville and El-Fayoum. The Almagra model was used to assess the

soil suitability. The model application results are grouped into five soil suitability

classes: S1(optimum), S2 (high), S3 (moderate), S4 (marginal), and S5 (not

suitable). The agricultural uses that are being considered are the following

traditional crops: wheat (T), corn (M), melon (Me), potato (P), soybean (S), cotton

CHAPTER 11

248

(A), sunflower (G), and sugar beet (R) as annuals; alfalfa (Af) as semiannual; and

peach (Mc), citrus fruits (C), and olive (O) as perennials. Crop suitability is affected

by complex interactions between different factors, such as topography, soil

properties, and management practices (Jaynes et al., 2003; Kravchenko et al.,

2005).

11.5.1 SEVILLE

In the suitability classes of the Almagra model, the main limiting factors in the soil

category are the subclasses depth (p), texture (t), drainage (d), calcium carbonate

content (c), salinity (s), sodium saturation (a), and profile’s degree of development

(g). Table 11-2 shows how the Almagra model classifies some of the soil profiles of

the Seville transects.

In the TA transect, the low calcium carbonate content becomes a limiting factor in

the soil profiles of SE0165 (pH 6.1), SE1066 (pH 6.5), SE0404 (pH 5.5), SE0401 (pH

5.4). In these cases, the acidity of the soil stems from the parent material of acidic

igneous rocks. On the other hand, the excessive contents of calcium carbonate

appeared to be an limiting factor in the transect TB, especially in the profile

locations SE0818 and SE0815, where the basic soils had been formed from basic

igneous rocks and the pH values were 7.6 and 7.7, respectively. The soil profiles

that were located at lower elevations often have salinity problems, a heavy

texture, high values of Exchangeable Sodium Percentage, very poor drainage, and

shallow soil depth, and incipient development of soil profiles make these locations

marginal, or not suitable, soils for the 12 Mediterranean crops. The results of the

soil suitability evaluation ranged from S1 to S5p and S5s; the final part of transect

TA has a S4t subclass due to the high content of gravel and the resulting coarse

texture. Transect TB was classified as an S5p subclass due to the shallow useful

depth.


249

Table 11-12. How the Almagra model calculates the final classifications: Each soil profile

is classified on a scale from 1 (best) to 5 (worst) for each subclass, depending on the

specific requirements of each crop. The final classification is determined by the worst

subclasses, which is indicated by their letter.

SDBm

code

Soil factors/

classification

Crops

T M Me P S A G R Af Mc C O

SE0103 Useful depth (p) 1 1 1 1 1 1 1 1 1 1 1 1

Texture (t) 2 2 2 2 2 2 2 2 2 4 4 4

Drainage (d) 3 2 2 2 3 2 2 3 3 4 4 4

Carbonate (c) 1 2 2 2 1 2 1 1 1 2 2 1

Salinity (s) 4 4 4 4 4 3 4 3 3 5 5 3

Sodium sat (a) 1 1 1 1 1 2 1 2 1 1 1 1

Profile dev (g) 1 1 1 1 1 1 1 1 1 2 2 1

Classification S4

s

S4

s

S4

s

S

4

S4

s

S3

s

S4

s

S3

ds

S3

ds

S5

s

S5

s

S4

td SE0082 Useful depth (p) 1 1 1 1 1 1 1 1 1 1 1 1

Texture (t) 4 4 4 4 4 4 4 4 4 3 3 3

Drainage (d) 1 1 1 1 1 1 1 1 1 1 1 1

Carbonate (c) 3 2 2 2 3 2 3 3 3 2 2 3

Salinity (s) 1 1 1 1 1 1 1 1 1 1 1 1

Sodium sat (a) 1 1 1 1 1 2 1 2 1 1 1 1

Profile dev (g) 2 2 2 2 2 3 2 3 2 3 3 2

Classification S4

t

S4

t

S4

t

S

4t

S4

t

S4

t

S4

t

S4

t

S4

t

S3

tg

S3

tg

S3

tc SE0101 Useful depth (p) 5 5 5 5 5 5 5 5 5 5 5 5

Texture (t) 1 1 2 2 1 2 1 1 1 2 2 3

Drainage (d) 1 1 1 1 1 1 1 1 1 1 1 1

Carbonate (c) 2 3 3 3 2 3 2 2 2 3 3 2

Salinity (s) 1 1 1 1 1 1 1 1 1 1 1 1

Sodium sat (a) 1 1 1 1 1 2 1 2 1 1 1 1

Profile dev (g) 1 1 1 1 1 1 1 1 1 1 1 1

Classification S5

p

S5

p

S5

p

S

5

S5

p

S5

p

S5

p

S5

p

S5

p

S5

p

S5

p

S5

p

The Almagra model has been applied to the current situation and under an

improvement scenario, in this scenario, the suitability is determined in case some

of the limiting soil factors (d, c, s, and a) are improved. Table 11-13 shows the

results of the soil suitability evaluation for the twelve Mediterranean crops under

the current situation of soil factors. Table 11-14 the soil suitability for a

hypothetical situation in which the soil factors drainage, calcium carbonate

content, salinity, and sodium saturation would have been improved. In this

hypothetical scenario, the highest improvement on suitability is for perennial

crops in the TA transect.

CHAPTER 11

250

Figure 11-7. The results of the soil suitability evaluation in the current situation and the

improvement scenario, for each point of transect TA and TB and for twelve

Mediterranean crops. Lower values on the y-axis represent better suitabilities.

0

5

10

15

20 Wheat

0

5

10

15

20 Corn

0

5

10

15

20 Melon

0

5

10

15

20 Potato

0

5

10

15

20 Soybean

0

5

10

15

20 Cotton

0

5

10

15

20 Sunflower

0

5

10

15

20 Suger beet

0

5

10

15

20 Peach

0

5

10

15

20 Citrus

1 2 3 4 5 6 7 8 9

10

11

12

13

14

15

16

1718

1920

2122

23

24

25

26

27

28

29

30

31

0

5

10

15

20 Olive

0

5

10

15

20 Alfalfa

Wheat

Corn

Melon

Potato

Soybean

Cotton

Sunflower

Suger beet

Alfalfa

Peach

Citrus

1 2 3 4 5 6 7 8 91011121314151617181920212223242526272829303132

Olive

Annuals crops

Semiannual crops

Perennials crops

Transect points

Soil limitations

TA TB

Improvement of soil limitationsCurrent situation Improvment scenario


251

Table 11-13. Results of the soil suitability evaluation of the best agricultural lands from

the transects, according to the Almagra qualitative model (De la Rosa et al. 1992). The

crops are: wheat (T), corn (M), melon (Me), potato (P), soybean (S), cotton (A),

sunflower (G), sugar beet (R), alfalfa (Af), peach (Mc), citrus fruits (C), and olive (O). Soil

limitation factors range from S1 (optimum) to S5 (not suitable), the most limiting factors

are indicated with a letter: p: useful depth, t: texture, d: drainage, c: calcium carbonate

content, s: salinity, a: sodium saturation, g: profile development.

SDBm

code

Crops


TA soil transect SE0103 S4s S4s S4s S4s S4s S3s S4s S3ds S3ds S5s S5s S4td

SE0117 S3d S2tdc S2dc S2dc S3d S2dca S2td S3d S3d S4d S4d S4d

SE0602 S4d S3d S3d S3d S4d S3d S3d S4d S4d S5d S5d S5d

SE1021 S1 S2c S2tc S2tc S1 S2tca S1 S2a S1 S2tdc S2tdc S3t

SE1066 S3c S2tc S2tc S2tc S3c S2tc S3c S3c S3c S4t S4t S4t

SE1062 S4t S4t S4t S4t S4t S4t S4t S4t S4t S5t S5t S5t

SE1065 S3c S2c S2c S2c S3c S2c S3c S3c S3c S2tcg S2tcg S3tc

SE0710 S2tc S3c S3c S3c S2tc S3c S2tc S2tca S2tc S3c S3c S2c

SE1002 S2c S1 S2t S2t S2c S2ta S2c S2ca S2c S2tg S2tg S3t

SE1013 S3tdc S3t S3t S3t S3tdc S3t S3tc S3tdc S3tdc S4d S4d S4d


SE0993 S3dc S2tdc S2tdc S2tdc S3dc S2tdc S3c S3dc S3dc S4td S4td S4td

SE1010 S4t S4t S4t S4t S4t S4t S4t S4t S4t S4d S4d S4d

SE1009 S4t S4t S4t S4t S4t S4t S4t S4t S4t S4d S4d S4d

SE1000 S3c S2tc S2tc S2tc S3c S2tca S3c S3c S3c S4t S4t S4t

SE0016 S2t S2tc S2tc S2tc S2t S2tca S2t S2ta S2t S4t S4t S4t

SE0313 S3c S2tc S2tc S2tc S3c S2ts S3c S3c S3c S4t S4t S4t

SE0309 S5p S5p S5p S5p S5p S5p S5p S5p S5p S5p S5p S5p

SE0635 S3c S2c S2tc S2tc S3c S2tca S3c S3c S3c S2tdc S2tdc S3tc

SE0404 S3c S2tcg S2cg S2cg S3c S3g S3c S3c S3c S3g S3g S3c

SE0052 S3c S2cg S2tcg S2tcg S3c S3g S3c S3c S3c S3g S3g S3tc

SE0930 S3tc S3t S2tc S2tc S3tc S2tca S3tc S3tc S3tc S2tcg S2tcg S3c

SE0072 S4d S3td S3d S3d S4d S3d S3tdc S4d S4d S5d S5d S5d

SE0401 S4t S4t S4t S4t S4t S4t S4t S4t S4t S3tg S3tg S3tc

SE0082 S4t S4t S4t S4t S4t S4t S4t S4t S4t S3tg S3tg S3tc

TB soil transect

SE0103 S4s S4s S4s S4s S4s S3s S4s S3ds S3ds S5s S5s S5s

SE1082 S4d S3d S3d S3d S4d S3d S3d S4d S4d S5d S5d S5d

SE0107 S3t S3t S3t S3t S3t S3t S3t S3t S3t S2ptc S2ptc S2t

SE0109 S3d S2tdc S2tdcs S2tdcs S3d S2tdca S2tds S3d S3d S4td S4td S4td

SE0104 S3d S2tdc S2tdc S2tdc S3d S2tdca S2td S3d S3d S4td S4td S4td

SE0818 S3c S3c S3c S4c S3c S3c S3c S3c S3c S4tc S4tc S4t

SE0854 S2c S3c S3c S3c S2c S3c S2c S2c S2c S3c S3c S3t

SE0815 S3c S3c S3c S4c S3c S3c S3c S3c S3c S4c S4c S3c

SE0821 S2tc S2t S2p S1 S2ptc S2pa S2ptc S2ptca S2ptc S3p S3p S3p


SE0856 S3d S2dc S2tdc S2tdc S3d S2tdc S2d S3d S3d S4d S4d S4d

SE0855 S3d S2dc S2tdc S2tdc S3d S2tdca S2d S3d S3d S4d S4d S4d

SE0886 S3d S2tdc S2tdc S2tdc S3d S2tdc S2td S3d S3d S4td S4td S4td

SE0229 S2t S2tc S3t S3t S2t S3t S2t S2t S2t S3t S3t S4t

SE0142 S1 S2c S2tc S2tc S1 S2tca S1 S2a S1 S2tdcg S2tdcg S3t

SE0140 S1 S2c S2tc S2tc S1 S2tca S1 S1 S1 S2tcg S2tcg S3t


CHAPTER 11

252

Table 11-14. The results of the soil suitability evaluation in the improved scenario,

according to the application of the Almagra model to the studied transects. The crops

are: wheat (T), corn (M), melon (Me), potato (P), soybean (S), cotton (A), sunflower (G),

sugar beet (R), alfalfa (Af), peach (Mc), citrus fruits (C), and olive (O). Soil limitation

factors range from S1 (optimum) to S5 (not suitable), the most limiting factors are

indicated with a letter: p: useful depth, t: texture, d: drainage, c: calcium carbonate

content, s: salinity, a: sodium saturation, g: profile development.

SDBm

code

Crops


TA soil transect SE0103 S3d S2tdc S2tdc S2tdc S3d S2tdc S2td S2ta S2t S4td S4td S4t

SE0117 S2t S2t S1 S1 S2t S1 S2t S2tg S2t S2c S2c S1

SE0602 S2t S2tc S2tcs S2tcs S2ts S2ts S2ts S2ta S2ts S4t S4t S4t

SE1021 S1 S1 S2t S2t S1 S2t S1 S1 S1 S2t S2t S3t

SE1066 S2t S2t S2t S2t S2t S2t S2t S2ta S2t S4t S4t S4t


SE1065 S1 S1 S1 S1 S1 S1 S1 S1 S1 S2tg S2tg S3t

SE0710 S2c S2t S1 S1 S1 S2a S2c S2c S2c S1 S1 S1

SE1002 S1 S1 S2t S2t S1 S2t S1 S1 S1 S2tg S2tg S3t

SE1013 S3t S3t S3t S3t S3t S3t S3t S3t S3t S2tcg S2tcg S3c


SE0993 S2t S2t S2t S2t S2t S2t S2td S2ta S2t S4t S4t S4t

SE1010 S4t S4t S4t S4t S4t S4t S4t S4t S4t S3t S3t S3c

SE1009 S4t S4t S4t S4t S4t S4t S4t S4t S4t S3t S3t S3c





SE0635 S3c S2c S2t S2t S1 S2t S1 S1 S1 S2t S2t S2t

SE0404 S2tg S2tg S2g S2g S2tg S2ca S2tg S2ta S2tg S3g S3g S2g

SE0052 S2g S2g S2tg S2tg S2g S3g S2g S2a S2g S3g S3g S3t

SE0930 S3t S3t S2t S2t S3t S2t S3t S3t S3t S2tg S2tg S2t

SE0072 S3tc S3td S2tcg S2tcg S3tc S2tca S3t S3tcg S3tc S3g S3g S3c



TB soil transect

SE0103 S3d S2tdc S2tdc S2tdc S3d S2tdca S2td S2ta S2t S4td S4td S4td

SE1082 S2tc S2t S2t S2t S2tc S2ta S2tc S2tc S2tc S4d S4d S4d

SE0107 S3t S3t S3t S3t S3t S3t S3t S3t S3t S2pt S2pt S2t

SE0109 S2t S2t S2t S2t S2ts S2t S2t S2ta S2t S4t S4t S4t


SE0818 S2t S2t S2t S2t S2t S2ta S2t S2t S2t S4t S4t S4t

SE0854 S2t S2t S1 S1 S2t S0 S2t S2ta S2t S1 S1 S1

SE0815 S2t S2t S1 S1 S2t S1 S2t S2ta S2t S1 S1 S1

SE0821 S2t S2t S2p S1 S2pt S2p S2pt S2pt S2pt S3p S3p S3p


SE0856 S1 S1 S2t S2t S1 S2t S1 S2a S1 S2tc S2tc S3t

SE0855 S1 S1 S1 S1 S1 S2t S1 S2a S1 S2tc S2tc S3t

SE0886 S1 S2t S2t S2t S2t S2t S2t S2ta S2t S4t S4t S4t






253

The low levels of calcium carbonate content become a limiting factor in some

parts of TA, in contrast, the excessive concentrations of calcium carbonate

appeared to be a limiting factor to crop suitability in some parts of the TB

transect, while soil salinity is the main limiting factor in the lowlands of both

transects. Decreasing the severity of some soil limiting factors (in the improved

scenario) leads to an increase in the soil suitability for the twelve crops along of

TA and TB transects. The only parts that did not receive an improved classification

were the parts where the shallow soil depth and very coarse texture are the

limiting factors, as improvement of these factors is not feasible, and therefore

these factors were not included in the scenario.

11.5.2 EL-FAYOUM

The Almagra model has also been applied to each soil profile along the El-Fayoum

transect to assess the soil suitability. In the starting points of the transect TC01 (F-

H21) and TC02 (F-H25), the suitably had a good class (S2) with different soil

limitation factors for eleven crops, only for olive cultivation, the soil had a

moderate suitability class (S3t), in these locations, the main limitation for olive

cultivation is the soil texture. From TC03 to TC07, the moderate and high classes

dominate for the majority of crops. In TC09 (F-A16) and TC10 (F-H08), the soil

suitability has been classified as a not suitable class (S5) because of the high

salinity. The results from the model suggest that the main soil factors that limit

soil suitability are soil texture, drainage, and soil salinity. The excessive content of

calcium carbonate appeared to be a limiting factor to crop suitability, especially in

TC01 and TC02.

Table 11-15. Soil suitability evaluation results from application of the Almagra model to

transect points (TP) and soil profiles (SP) in El-Fayoum. The crops are: wheat (T), corn

(M), melon (Me), potato (P), soybean (S), cotton (A), sunflower (G), sugar beet (R),

alfalfa (Af), peach (Mc), citrus fruits (C), and olive (O). Soil limitation factors range from

S1 (optimum) to S5 (not suitable), the most limiting factors are indicated with a letter: p:

useful depth, t: texture, d: drainage, c: calcium carbonate content, s: salinity, a: sodium

saturation, g: profile development.

TP SP T M Me P S A G R Af Mc C O

TC01 F-H21 S2ca S2a S2csa S2csa S2csa S2t S2csa S2c S2csa S2tdcag S2tdcag S3t

TC02 F-H25 S2ca S2a S2csa S2csa S2csa S2t S2csa S2c S2csa S2tdcag S2tdcag S3t

TC03 F-H22 S3d S2tda S2tdsa S2tdsa S3d S2td S2tdcsa S3d S3d S4td S4td S4td



TC06 F-A07 S3d S2tda S2tdsa S2tdsa S3d S2td S2tdcsa S3d S3d S4td S4td S4td

TC07 F-H14 S3d S3a S2tdsa S2tdsa S3d S2td S2tdcsa S3d S3d S4td S4td S4td

TC08 F-H13 S4ds S4sa S4s S4s S4ds S3dsa S4s S4d S4d S5d S5d S5d

TC09 F-A16 S5s S5s S5s S5s S5s S5s S5s S5s S5s S5tds S5tds S5tds

TC10 F-H08 S5s S5s S5s S5s S5s S5s S5s S5s S5s S5ds S5ds S5ds

Rainfall-induced erosion processes in

Huelva, Andalusia.

Terracing agricultural systems in small

parts of El-Fayoum depression.

11 analysis of topographic transects -...

Documents