Erosion assessment for large basins using remote sensing and GISAuthor: Byman, H Hamududu | 1998 | MSc | International Institute for Aerospace Survey and Earth Sciences, Netherlands The erosion assessment of Naivasha Basin has been carried out using the Terrain Mapping Units approach. This methodology combines the effect of rainfall, land cover and (TMU) soils, topography on the erosion process. The study aimed to assess the erosion processes occurring in the area that result from the hydrological behavior of the catchment. Rainfall analysis was done within the basin to determine the spatial and temporal distribution of the rainfall. The results showed that the area experience varying amounts of rainfall both in space and time due to orographic effects. The central part (bottom of the Rift Valley) receives the lowest (yearly average 600-mm) amount of rainfall while the mountain ranges on both sides receive an appreciable amount of rainfall (average 1200 mm). In addition to this due to the topography of the area (rain shadow effect), the rainfall pattern differed from area to area. The average yearly rainfall ranges from 480 mm to 1300 mm. The rainfall pattern in the year is bi-moda]. one peak in between April and June and the second one in October and November. The high erosive storm occurs mostly in April, May and November.The land cover is influenced by rainfall pattern of the area. At high altitudes (>2100 masl) where there is high rainfall the land cover is mainly dense forest, while at lower altitudes, bottom of the rift valley ½2000 masl), the land cover is mainly scrub land and occasionally bare soil This is clearly seen on the satellite image where forest appears black and the bare soil and scrubland appear almost white gray. The rest of the area is under heavy agricultural activities, which changes from season to season. The image interpretation was done and supervised classification carried out in ILWIS package. Six land cover classes were identified; Forest, Scrub, Bare soil, Agricultural crop, Lava flow, and Water.The three data layers were prepared as described in the following sections. With relational modelling, 2-dimensional tables were prepared for each pair of data layers. The last 2-dimensional table was a result of the other two 2-dimensional tables used. The 2-dimensional table was used to reclassify the maps into an erosion map by the assigned values or ratings. These ratings were assigned based on the knowledge from the field. The result was an erosion map with rainfall and TMU data, and cover factor. The sediment concentrations and the annual sediment yields were also analyzed. The sediment concentrations were highest during the first storms. The concentrations were also found to be high in the long rainy season, followed by the dry period, were the least in the short rainy season (October and November). Only two rivers had enough sediment concentration data for analysis. These are Malewa and Turasha rivers. Rating curves for the seasonal sediment concentrations were calculated and the amount of sediment yield for the entire basin was estimated from these curves. The sediment data was also used for estimating the sediment yield from some TMUs in which drainage was well defined.
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