Browsing by Author "Klik, A."

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Estimating spatial sediment delivery ratio on a large rural catchment
(2006-05-20) Mutua, Benedict M.; Klik, A.
Soil erosion and sediment yield from catchments are key limitations to achieving sustainable land use and maintaining water quality in streams, lakes and other water bodies. Controlling sediment loading requires the knowledge of the soil erosion and sedimentation. However, sediment yield is usually not available as a direct measurement but estimated by using a sediment delivery ratio (SDR). An accurate prediction of SDR is important in controlling sediments for sustainable natural resources development and environmental protection. There is no precise procedure to estimate SDR, although the USDA has published a handbook in which the SDR is related to drainage area. This paper presents a new approach for estimating spatial sediment delivery ratio (SDR) for large rural catchments. The SDR is predicted using a Hillslope Sediment Distributed Delivery (HSDD) model in conjunction with a physically distributed hydrological model in a GIS environment. The new approach was developed and tested on Masinga catchment, a rural large catchment in Kenya. The hydrological model was validated using predicted and observed daily stream flows and a performance criterion based on Nash Sutcliffe coefficient of model efficiency was used. The developed model is not only conceptually easy and well suited to the local data needs but also requires less parameters, which offer less uncertainty in its application while meeting the intended purpose.
Modelling soil erosion and sediment yield at a catchment scale: the case of Masinga catchment, Kenya
(John Wiley & Sons, Ltd., 2006-08-07) Mutua, Benedict M.; Klik, A.; Loiskandl, w.
Development of improved soil erosion and sediment yield prediction technology is required to provide catchment stakeholders with the tools they need to evaluate the impact of various management strategies on soil loss and sediment yield in order to plan for the optimal use of the land. In this paper, a newly developed approach is presented to predict the sources of sediment reaching the stream network within Masinga, a large‐scale rural catchment in Kenya. The study applies the revised universal soil loss equation (RUSLE) and a developed hillslope sediment delivery distributed (HSDD) model embedded in a geographical information system (GIS). The HSDD model estimates the sediment delivery ratio (SDR) on a cell‐by‐cell basis using the concept of runoff travel time as a function of catchment characteristics. The model performance was verified by comparing predicted and measured plot runoff and sediment yield. The results show a fairly good relationship between predicted and measured sediment yield (R2=0·82). The predicted results show that the developed modelling approach can be used as a major tool to estimate spatial soil erosion and sediment yield at a catchment scale. Copyright © 2006 John Wiley & Sons, Ltd.
Soil erosion management at a large catchment scale using the RUSLE-GIS: the case of Masinga catchment, Kenya
(WIT Press, 2004-08-23) Mutua, Benedict M.; Klik, A.
Kenya is one country suffering heavily from land degradation due to increasing anthropogenic pressure on its natural resources. As is common to many tropical countries, Kenya suffers from a lack of financial resources to research, monitor and model sources and outcomes of environmental degradation for large catchment domains. In order to evaluate viable management options, soil erosion modelling at the catchment scale needs to be undertaken. This paper presents a comprehensive methodology that integrates an erosion model, the Revised Universal Soil Loss Equation (RUSLE) with a Geographic Information System (GIS) for estimating soil erosion at Masinga catchment, which is a typical rural catchment in Kenya. The objective of the study was to map the spatial mean annual soil erosion for the Masinga catchment and identify the risk erosion areas. Current land use/cover and management practices and selected, feasible, future management practices were evaluated to determine their effects on average annual soil loss. The results can be used to advice the catchment stakeholders in prioritising the areas of immediate erosion mitigation. The integrated approach allows for relatively easy, fast, and cost-effective estimation of spatially distributed soil erosion and sediment delivery. It thus provides a useful and efficient tool for predicting long-term soil erosion potential and assessing erosion impacts of various cropping systems and conservation support practices.