Estimation of Potential Soil Erosion for River Perkerra Catchment in Kenya

Abstract

River Perkerra catchment with an area of 1207 km 2 is drained by River Perkerra, which is one of the rivers flowing into Lake Baringo whose drainage area is 6820 km 2 . The lake is in a semi-arid area of Kenya. Its depth has reduced from 8 m in 1972 to 2.5 m in 2003 due to siltation resulting from high erosion rates in the catchment. The entire catchment is characterised by very steep slopes on the hillsides and gentle slopes in the middle and lower reaches where the surface is bare with very little undergrowth. Interventions to control soil erosion in this fragile ecosystem have been limited partly because of lack of data on erosion and its spatial distribution. In the present study, Universal Soil Loss Equation (USLE) was used in conjunction with GIS Arc/Info and Integrated Land and Water Information Systems (ILWIS) to estimate potential soil loss from River Perkerra catchment. Various physical parameters of the equation were derived by analysing spatial data and processing Landsat TM satellite imagery of the catchment. The estimated potential soil erosion from the catchment was 1.73 million tonnes/year while the sediment yield at the catchment outlet was found to be 1.47 million tonnes/year. The sediment delivery ratio derived using an empirical equation was 0.83. This figure indicates that a higher proportion of sediments generated in the catchment is delivered at the outlet. The use of GIS enabled the results of erosion potential to be mapped back onto the catchment. This is useful in identifying priority areas that require urgent management interventions in controlling soil erosion.

Modelling soil erosion at European scale: towards harmonization and reproducibility

“…R d1 , region A 3 in Table 1c) proposed by de Santos Loureiro and de Azevedo Coutinho (2001) received wide acceptance (Onyando et al, 2005;Taveira-Pinto et al, 2009;Ranzi et al, 2012). The relationship has been tested in Italy (Diodato, 2004b) where it provided estimates more stable than the ones provided by other widely used empirical equations (in the limited validation set, the estimates of R d1 did not show rank reversals when compared to the measured erosivity).…”

Soil erodibility and its estimation for agricultural soils in China

“…Lu et al (2004) in Central and South America, Kim et al (2005), Onyando et al (2005) in Africa, and Vezina et al (2006) in Asia, to cite just a few. For most of these large-scale applications of USLE/RUSLE for erosion risk assessment and conservation planning, the nomograph-based method has been extensively applied to estimate K values with little or no independent field validation.…”

Recent limnological changes and their implication on fisheries in Lake Baringo, Kenya

“…Lake Baringo waters remain fresh despite lack of surface outlet, shallow depth and high net evaporation that characterizes the rift floor. Recent hydrogeological evidence confirms the original assumption (Beadle, 1932) that some lake water is lost by underground seepage through the fractured lake floor (Onyando et al, 2005). Dunkley et al (1993) .…”

“…Furthermore, established macrophytic communities in the two zones contribute to accumulation of silt by acting as traps for the incoming materials. The type of local geology, topography and meteorology (Onyando et al, 2005) coupled with anthropological activities, especially overgrazing and deforestation expose the Lake Baringo catchment to high erosion. The resulting sediments and suspended solids in turn influence the lake's depth and substratum.…”