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SOIL DEGRADATION RISK FACTORS

Based on the surveillance protocol conducted in the River Nyando basin, and the spectral screening tests developed for soil fertility condition and soil erosion, we were able to analyze the relationships between land use and soil degradation and identify tentative risk factors associated with soil degradation. Prospective studies are required to verify these risk factors.

Land Cover Type

On average, over the basin, soil physical degradation (i.e. sheet and rill, gully, hardsetting) was strongly associated with sparse vegetation, whereas forest and wetlands were protective of soil degradation.

Vegetation cover

Land Degradation Surveillance
Further analysis confirmed that soil physical degradation was strongly associated with herbaceous ground cover, and was greater on steeper slopes and shallower soils (<50cm depth). There was no causal association between soil degradation and woody cover when herbaceous cover was considered. Low soil carbon and available phosphorus levels were associated with soil physical degradation.
These results show that the critical factor for managing soil degradation is the amount of herbaceous ground cover!

Likelihood of observing soil physical degradation in the Nyando basin under different vegetation cover types


A graphical model showing conditional relationships between soil physical degradation and herbaceous ground cover

 

SOIL FERTILITY, SOIL EROSION AND AGRICULTURE

Soil erosion, in turn, appears to be the over-riding risk factor for soil fertility change in the Nyando basin, whereas agriculture has little impact on soil fertility once erosion is controlled for in the analysis. Eroded soils have lost about half of their capacity to retain nutrient cations and half of their carbon content relative to stable soils.
Relationship between spectral indices of soil fertility and soil erosion showing the absence of any interaction with agriculture (Figure above and Table below)

Variable Estimate SE t
Cut G/A -1.904 0.160 -11.92
Cut A/P 1.805 0.148 12.18
Γs 0.809 0.074 10.99
Agriculture 0.096 0.215 0.45
Γs Agriculture 0.152 0.100 1.52
Γs2 -0.065 0.009 -7.04
Γs2 Agriculture 0.032 0.037 0.87
 The spectral library approach provides a coherent framework for linking soil information with remote sensing information for improved spatial prediction of soil functional capacity. Remote sensing of soil properties directly from space platforms is hampered by problems such as atmospheric interference, shade and shadow effects, mixtures of materials within pixels, and variation in soil moisture content. Studies on the effect of soil moisture content on calibrations between soil functional attributes and soil reflectance would help to evaluate the potential of reflectance spectroscopy in the field. Future studies should explore approaches that combine soil spectral libraries, and other geo-referenced information, such as from digital terrain models and field observations, with information from multi- and hyper-spectral remote sensing imagery (e.g. Shepherd and Walsh, 2002.)