Sensitivity analysis and calibration of the Modified Universal Soil Loss Equation (MUSLE) for the upper Malewa Catchment, Kenya.

Simulation models are widely used for studying physical processes such as surface runoff, sediment transport and sediment yield in catchments. Most models need case-specific empirical data for parameterization before being applied especially in regions other than the ones they have been developed. Sensitivity analysis is usually performed to determine the most influential factors of a model so that they can be prioritized for optimization. In this way uncertainties in model outputs can be reduced considerably. This study evaluates the commonly used modified universal soil loss equation (MUSLE) model used for sediment yield simulation for the case of the upper Malewa catchment in Kenya. The conceptual factors of the model are assessed relative to the hydrological factors in the model. Also, the sensitivity of the model to the choice of the objective function in calibration is tested. The Sobol' sensitivity analysis method was used for evaluating the degree of sensitivity of the conceptual and hydrological factors for sediment yield simulations using the MUSLE model. Nash-Sutcliffe Efficiency (NSE) and the modified Nash-Sutcliffe Efficiency (NSEm) are used to test the sensitivity of the model to the choice of the objective function and robustness of model performance with sediment data measured from upper Malewa catchment, Kenya. The results indicate that the conceptual factors are the most sensitive factors of the MUSLE model contributing about 66% of the variability in the output sediment yield. Increased variability of sediment yield output was also observed. This was attributed to interactions of input factors. For the upper Malewa catchment calibration of the MUSLE model indicates that the use of NSEm as an objective function provides stable results, which indicates that the model can satisfactorily be applied for sediment yield simulations

Sensitivity analysis and calibration of the Modified Universal Soil Loss Equation (MUSLE) for the upper Malewa Catchment, Kenya

Simulation models are widely used for studying physical processes such as surface runoff, sediment transport and sediment yield in catchments. Most models need case-specific empirical data for parameterization before being applied especially in regions other than the ones they have been developed. Sensitivity analysis is usually performed to determine the most influential factors of a model so that they can be prioritized for optimization. In this way uncertainties in model outputs can be reduced considerably. This study evaluates the commonly used modified universal soil loss equation (MUSLE) model used for sediment yield simulation for the case of the upper Malewa catchment in Kenya. The conceptual factors of the model are assessed relative to the hydrological factors in the model. Also, the sensitivity of the model to the choice of the objective function in calibration is tested. The Sobol' sensitivity analysis method was used for evaluating the degree of sensitivity of the conceptual and hydrological factors for sediment yield simulations using the MUSLE model. Nash-Sutcliffe Efficiency (NSE) and the modified Nash-Sutcliffe Efficiency (NSEm) are used to test the sensitivity of the model to the choice of the objective function and robustness of model performance with sediment data measured from upper Malewa catchment, Kenya. The results indicate that the conceptual factors are the most sensitive factors of the MUSLE model contributing about 66% of the variability in the output sediment yield. Increased variability of sediment yield output was also observed. This was attributed to interactions of input factors. For the upper Malewa catchment calibration of the MUSLE model indicates that the use of NSEm as an objective function provides stable results, which indicates that the model can satisfactorily be applied for sediment yield simulations

Coupling socio-economic factors and eco-hydrological processes using a cascade-modeling approach

Most hydrological studies do not account for the socio-economic influences on eco-hydrological processes. However, socio-economic developments often change the water balance substantially and are highly relevant in understanding changes in hydrological responses. In this study a multi-disciplinary approach was used to study the cascading impacts of socio-economic drivers of land use and land cover (LULC) changes on the eco-hydrological regime of the Lake Naivasha Basin. The basin has recently experienced substantial LULC changes exacerbated by socio-economic drivers. The simplified cascade models provided insights for an improved understanding of the socio-ecohydrological system. Results show that the upstream population has transformed LULC such that runoff during the period 1986–2010 was 32% higher than during the period 1961–1985. Cut-flower export volumes and downstream population growth explain 71% of the water abstracted from Lake Naivasha. The influence of upstream population on LULC and upstream hydrological processes explained 59% and 30% of the variance in lake storage volumes and sediment yield respectively. The downstream LULC changes had significant impact on large wild herbivore mammal species on the fringe zone of the lake. This study shows that, in cases where observed socio-economic developments are substantial, the use of a cascade-modeling approach, that couple socio-economic factors to eco-hydrological processes, can greatly improve our understanding of the eco-hydrological processes of a catchment

Coupling socio-economic factors and eco-hydrological processes using a cascade-modeling approach

Most hydrological studies do not account for the socio-economic influences on eco-hydrological processes. However, socio-economic developments often change the water balance substantially and are highly relevant in understanding changes in hydrological responses. In this study a multi-disciplinary approach was used to study the cascading impacts of socio-economic drivers of land use and land cover (LULC) changes on the eco-hydrological regime of the Lake Naivasha Basin. The basin has recently experienced substantial LULC changes exacerbated by socio-economic drivers. The simplified cascade models provided insights for an improved understanding of the socio-ecohydrological system. Results show that the upstream population has transformed LULC such that runoff during the period 1986–2010 was 32% higher than during the period 1961–1985. Cut-flower export volumes and downstream population growth explain 71% of the water abstracted from Lake Naivasha. The influence of upstream population on LULC and upstream hydrological processes explained 59% and 30% of the variance in lake storage volumes and sediment yield respectively. The downstream LULC changes had significant impact on large wild herbivore mammal species on the fringe zone of the lake. This study shows that, in cases where observed socio-economic developments are substantial, the use of a cascade-modeling approach, that couple socio-economic factors to eco-hydrological processes, can greatly improve our understanding of the eco-hydrological processes of a catchment

Land use and land cover changes on a tropical lake basin : the socioeconomic drivers and cascading impacts on hydrology and ecological system : powerpoint

Lake Naivasha experiences frequent lake level fluctuations despite being on the decline in the last three decades. The main possible cause has been postulated to be increased abstraction around the lake. However, land use land cover changes (LULC) in the basin may be impacting on the level fluctuations and decline. The LULC interfere with runoff, evapotranspiration, and infiltration conditions of a catchment. The frequent lake levels fluctuations resulting from LULC impact significantly on riparian vegetation productivity and species composition. In addition, it has impact on the aquatic ecosystem water quality especially in terms of turbidity. Lake Naivasha basin has experienced significant LULC transformations predominantly caused by socio-economic drivers. Implications of past, present and future patterns of socio-economic drivers of LULC is vital to the understanding of social, ecological and limnological functioning of the basin. These factors are proposed to impact on the entire hydrological regime of the lake. In this study we present first results of the Earth Observation Integrated Assessment (EOIA) project for the governance of Lake Naivasha basin using Interdisciplinary approach that applies GIS and RS towards the understanding of the dynamics of Lake Naivasha ecosystem