Spatial assessment of soil degradation and its impact on SOC under different land covers – experience from Tajikistan

STAP soil organic carbon for global benefits workshop, 10-12 September 2012, Nairobi, Kenya

Bettina Wolfgramm, Centre for Development and Environment (CDE), University of Bern, Switzerland; Research Fellow, University of Central Asia

Tajikistan: semi-arid, mountainous area

MODIS 7 June 2011

• Grazing land (never cultivated) (47%) • Permanently cultivated (12%)

• Annual cropland • Tree and shrub cropping • Mixed systems: traditional and recently

emerging systems • Temporarily cultivated (35%)

Land cover / land use

Wolfgramm et al. 2007. Spatial assessment of erosion and its impact on soil fertility in the Tajik foothills. EARSeL eProceedings 6 (1):12-25.

Study area Loess hills of central Tajikistan

Imagery Landsat ETM+ (August 2000 / May 2001), DEM from Russian topographic maps

Reference data / validation data

Field protocol, soil spectral and chemical data

Model Statistical model: Classification and regression tree (CART)

User accuracy Land cover and soil maps ~70%, hot/bright spot map ~55%

Participation none

1) Mapping soil condition

waveband [nm]

soil

spec

tral

ref

lect

ance

[%]

A soil spectral library for prediction of SOC

2 test areas (10x10 km) 15 clusters per test area 13 sampling sites per cluster 400 field observations 1500 soil samples (0-20/20-50 cm) 250 samples selected for soil chemical analysis

Raster data

Field observations

Classification tree model (CART)

Point extraction and extrapolation

The land cover classification tree model

Classification system: Aquatic areas (rivers, streams) Settlement area Annual cropland Perennial crops Tree and shrub cropping Grazing low cover Grazing medium cover Grazing high cover

Raster variables

Terminal node

OSAVI: optimized soil-adjusted vegetation index FVC: fractional vegetation cover

N1a N1b

N2

N3

N4

N5 N6 N7

N8

N9a N9b

N9c

N10 N11 N12

N13

N14

N15

N16

N17 N18

N19

The link between LULC and soil condition (175 survey points)

flat (<14%)

Low VI in May

orchards (on terraces)

LUCs Aquatic areas Settlement area Annual cropland Perennial crops Tree and shrub cropping Grazing low cover Grazing medium cover Grazing high cover

bright degrading

stable hot

The hot/bright spot map

0%

25%

50%

75%

100%

Study area Faizabadtest area

Varzob testarea

Excluded areaBright spotStable areaDegrading areasHot spot

Hot spots: Areas in need for conservation measures • Grazing areas: low cover, steep slopes • Annual cropland: cropland on hill slopes,

cultivated or fallow

Bright spots: Opportunities for SLM • Grazing land: high cover all year • Tree and shrub cropping / mixed systems • Cropland annual: cropland on valley

floors and plateaus

2) Comparative case studies and SLM scenario modeling

Study area Local level: 5 villages Imagery High resolution imagery Quickbird

Reference data field data and existing USLE parameter definitions

Model (R)USLE for relative soil loss pred.

User accuracy soil loss validation through a Cs137 tracer study on-going

Participation Scenario definition based on inter-views with farmers of plots with SLM

Bühlmann et al. 2010. Geographic information system–based decision support for soil conservation planning in Tajikistan. Journal of Soil and Water Conservation 65 (3): 151-159.

Knowledge on Technologies Calibration data

What technology where? Cost – impact - efficiency

Combining data from 3 levels

Scenario modeling

Evaluation of SW conservation practices

Soil conservation scenario modeling

Soil conservation propositions

Soil conservation scenario: soil loss < 20 t/ha

Material flow analysis for a systemic biomass assessment

2000

Jun

1000

Apr Aug Oct Dec Feb Apr

Dashed line: Only straw used as feedSolid line: Straw and other residues used as feed

0

1000

2000

3000

Dec Feb Apr Jun Aug Oct Dec Feb Apr

Wheat Straw:

0

1000

2000

Jun Aug Oct Dec Feb Apr Jun Aug

Large FarmsMedium FarmsSmall Farms

0

1000

2000

Jun Aug Oct Dec Feb Apr Jun Aug

Field Stock

Household storage

Field Stock

Household storage

Dec Feb0

Wheat Straw:

Wheat Grain:

Wheat Grain:

kg dm

kg dm

kg dm

kg dm

Conclusions

• Identify where land needs preservation, mitigation, and rehabilitation

• SLM pays of if we account for multiple benefits for rural households and communities (on- and off-site benefits)

• Soil spectral libraries for efficient, low cost soil property prediction, especially for reference sites

• Comparative case studies to monitor SLM benefits and CC effects

• Access to appropriate satellite imagery is still a major challenge

Odina Nekushoev, farmer

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