Abstract
Monitoring of improper soil erosion empowered by water is constantly adding more risk to the natural resource mitigation scenarios, especially in developing countries. The demographical pattern and the rate of growth, in addition to the impairments of the rainfall pattern, are consequently disposed to adverse environmental disturbances. The current research goal is to evaluate soil erosion triggered by water in the coastal area of Kenya on the district level, and also in protected areas. The Revised Universal Soil Loss Equation (RUSLE) model was exercised to estimate the soil loss in the designated study area. RUSLE input parameters were functionally realized in terms of rainfall and runoff erosivity factor (R), soil erodibility factor (K), slope length and gradient factor (LS), land cover management factor (C) and slope factor (P). The realization of RUSLE input parameters was carried out using different dataset sources, including meteorological data, soil/geology maps, the Digital Elevation Model (DEM) and processing of satellite imagery. Out of 26 districts in coastal area, eight districts were projected to have mean annual soil loss rates of >10 t.ha(-1).y(-1): Kololenli (19.709 t.ha(-1).y(-1)), Kubo (14.36 t.ha(-1).y(-1)), Matuga (19.32 t.ha(-1).y(-1)), Changamwe (26.7 t.ha(-1).y(-1)), Kisauni (16.23 t.ha(-1).y(-1)), Likoni (27.9 t.ha(-1).y(-1)), Mwatate (15.9 t.ha(-1).y(-1)) and Wundanyi (26.51 t.ha(-1).y(-1)). Out of 34 protected areas at the coastal areas, only four were projected to have high soil loss estimation rates >10 t.ha(-1).y(-1): Taita Hills (11.12 t.ha(-1).y(-1)), Gonja (18.52 t.ha(-1).y(-1)), Mailuganji (13.75.74 t.ha(-1).y(-1)), and Shimba Hills (15.06 t.ha(-1).y(-1)). In order to mitigate soil erosion in Kenya's coastal areas, it is crucial to regulate the anthropogenic disturbances embedded mainly in deforestation of the timberlands, in addition to the natural deforestation process caused by the wildfires.