Browsing by Author "Klik, Andreas"

Now showing 1 - 2 of 2

Predicting daily streamflow in ungauged rural catchments: the case of Masinga catchment, Kenya
(Taylor&Francis, 2007) Mutua, Benedict Mwavu; Klik, Andreas
Access to daily streamflow data at the catchment scale, is a central component of many aspects of water resources and water quality management. However, the majority of river reaches in many catchments in Kenya are ungauged or poorly gauged, and in some cases existing measurement networks are declining. Long-term continuous monitoring is not being done due to high costs of equipment maintenance. Therefore, there is a need for an alternative tool such as a catchment-scale hydrological model that is capable of predicting the daily streamflow. An approach is presented of predicting daily streamflow using a physically-based catchment-scale model, the geospatial Stream Flow Model (SFM). The SFM was developed using the “C” programming language and the user interface was developed using the Avenue script of the ArcView software. The SFM simulates the dynamics of runoff processes by utilizing remotely sensed and widely available global or local data sets. The model was applied in the Masinga catchment, Kenya, and the results gave a model performance coefficient of 0.74 based on the Nash-Sutcliffe statistical criterion.
Predictings sediment loading into Masinga reservoir and its storage capacity reduction
(2005-09-07) Mutua, Benedict M.; Klik, Andreas; Loiskandl, Willibald
It is estimated that the annual loss in storage capacity of the world’s reservoirs due to sedimentation is around 0.5 – 1.0%. For many reservoirs, however, annual depletion rates are much higher and can go up to 4% or 5%, such that they lose the majority of their capacity after only 25 – 30 years. The Masinga reservoir, one of the main reservoirs in Kenya, designed for hydropower generation, public water supply and irrigation is faced with severe sedimentation. The designed sediment load into this reservoir in 1981 was estimated to be 3.0 x 106 m3 per year (about 1% per annum reservoir reduction). By 2000, annual sediment loading had increased to over 11.0 x 106 m3 , nearly four times, thus reducing the designed capacity by more than 15%. As land degradation has become more evident with increasing land use change within Masinga catchment over the years, the operation and life span of Masinga reservoir is thus under imminent danger from erosion and sedimentation. There is need therefore to quantify spatially soil erosion and sediment yield reaching the reservoir with a view to reducing the sediment delivery. In this paper, a comprehensive procedure to predict spatial sediment yield and overall mean annual sediment volume delivered to Masinga reservoir is presented. Geographical Information System (GIS) technology as a tool to support soil erosion and sediment models is employed. Simulations of different land use and management scenarios are performed and their corresponding sediment yields estimated. Predictions show annual sediment loading into the reservoir of about 14.0 x 106 m3 for land use practices in 2003. By simulating the best feasible management practices (BMPs), the achieved results show that the sediment volume reaching the reservoir could be reduced to about 6.0 x 106 m3 per year.