Simulation and prediction of soil loss using the RMMF and CA-Markov models in the Upper Tana River basin, Kenya

Abstract

Soil loss is one of the major environmental concerns with significant negative implications on top soil loss, land degradation, waterbody sedimentation and agricultural productivity. These losses arise from the complex interaction of climatic, biophysical, and anthropogenic factors. This study aimed at assessing and predicting soil loss using the Revised Morgan-Morgan Finney (RMMF) model and CA-Markov chain analysis in the Upper Tana basin. The datasets used included: rainfall intensity, mean daily rainfall, total annual rainfall, land use land cover, canopy height, soil moisture content, soil bulk density, canopy cover fraction, fraction of rainfall not intercepted by canopy, ground cover fraction, root depth, soil surface cohesion, soil detachability factor, evapotranspiration and the digital elevation model. The GIS-based RMMF model was used to simulate soil losses for the years 2002, 2012 and 2022 while the CA-Markov was used for predicting soil loss for the year 2030. The findings revealed that total soil loss exhibited a decreasing trend between 2002 and 2012 from 30159416.72 t/ha to 28762653.24 t/ha and later increased in 2022 which showcased the highest recorded level of 43527091.89 t/ha with a mean of 14.838±32.55 t/ha, 14.400±32.11 t/ha and 21.063±29.87 t/ha respectively. By 2030, the very low soil loss is expected to have a higher coverage of 60.14% followed by the low at 36.77%, the moderate at 0.31%, the high at 0.12% and the very high class at 2.67% of the total area. The study concluded that the anthropogenic, biophysical and climatic factors each play a key role in soil loss.