Soil Water Retention Characteristics (SWRC) models have been widely used in many applications. Presently, there are many models in the literature and many more still being developed so much so that it is confusing whi...Soil Water Retention Characteristics (SWRC) models have been widely used in many applications. Presently, there are many models in the literature and many more still being developed so much so that it is confusing which model to prefer. The current choice of the appropriate model to use has not been well guided by any incisive research on the predictive performance of these models. Consequently, SWRC model applications have been largely moved by convenience. This study used a global dataset to evaluate 12 commonly used SWRC models. The measured data onto which the models were evaluated was grouped into different soil depths and different regions of the world. The evaluation used correlation, Nash-Sutcliffe efficiency, and residual standard error statistics to choose the best overall performing model and models for each category. It gives an indication of the type of SWRC models to use in different regions of the world and depths of sampling. The suitability of the models to regions showed that the Fredlund and Xing model had the best performance in subsoils in Africa;Omuto in Southern Asia;and van Genuchten in subsoils of the other regions. It is recommended that many more models be tested using the procedures in this study so that benchmarks can be established on SWRC model selection suitable for various regions.展开更多
Groundwater prospecting in Kenya has been haphazard and expensive due to lack of information on the appropriate areas for hydrogeological exploration and drilling of boreholes. Drilling in areas without prior knowledg...Groundwater prospecting in Kenya has been haphazard and expensive due to lack of information on the appropriate areas for hydrogeological exploration and drilling of boreholes. Drilling in areas without prior knowledge about their groundwater potential has been leading to the drilling of numerous dry boreholes. In this study, we explored the use of Geographic Information System as a pre-analysis tool to identify zones with groundwater potential for Garissa Country. Factors that contributed to groundwater occurrence were identified as landcover, soil type and rock formation. The groundwater potential zones were generated by analysing thematic data of the three factors and integrating the musing Weighted Index Overlay Analysis (WIOA) method. The groundwater potential zones were validated by comparing the predicted potentials with actual yields of existing boreholes drilled within those areas. Results indicate that, whereas the model correctly predicted areas with low or no groundwater potential, it performed sparingly well when predicting areas with good groundwater potential. The study conclusively identified areas where groundwater prospecting should not be attempted and other alternative methods of surface water provision should be explored.展开更多
The purpose of the study was to develop pedotransfer functions for determining saturated hydraulic conductivity (Ks). Pedotransfer functions (PTFs) for predicting soil physical properties used in determining saturated...The purpose of the study was to develop pedotransfer functions for determining saturated hydraulic conductivity (Ks). Pedotransfer functions (PTFs) for predicting soil physical properties used in determining saturated hydraulic conductivity, based on moisture retention characteristics, were developed. The van Genuchten moisture retention equation was fitted to measured moisture retention properties obtained from International Soil Reference and Information Centre (ISRIC) soils data base in order to determine parameters in the equation i.e. saturated soil moisture content (θs), residual soil moisture (θr), air entry parameter (α) and the pore size distribution parameter (n). 457 samples drawn from the data base were used to be the maximum possible sample size that contained the measured soils characteristics data required. Using statistical regression, mathematical relationships were developed between moisture retention parameters (response variables) and appropriately selected transformed basic soil properties (predictor variables). The developed PTFs were evaluated for accuracy and reliability. It was found that pedotransfer functions developed for θs produced the best performance in reliability compared to the remaining parameters yielding a correlation coefficient value of coefficient of determination (R2 = 0.76), RMSE = 2.09, NSE = 0.75 and RSR = 0.5 indicating good performance. Relatively poorest performance was obtained from the pedotransfer function developed for α which yielded a correlation coefficient, R2= 0.06, RMSE = 0.85 and a NSE of 0.02 reflecting the best possible equation derived for the parameter for use in predicting hydraulic conductivity. Out of the pedotransfer functions developed for each of the moisture retention parameters, the best performing PTF was identified for each parameter. The accuracy of the pedotransfer functions assessed based on R2 were for θs (R2 = 0.80), θr (R2 = 0.42), α (R2 = 0.04) and for n (R2 = 0.30), when the variables were expressed directly in terms of the selected transformations of the basic soil properties.展开更多
Modeling stream flow forms a basis upon which policy makers, watershed planners and managers make ap- propriate decisions consistent with sustainable management of land and water resources in the watershed. The aim of...Modeling stream flow forms a basis upon which policy makers, watershed planners and managers make ap- propriate decisions consistent with sustainable management of land and water resources in the watershed. The aim of this research is to provide a preliminary assessment of the performance of a complex watershed model in predicting stream flow on the Naro Moru river catchment in Ewaso Ng’iro river basin, Kenya. The research involved model input data preparation, model set up and test running, sensitivity analysis and cali- bration of the Soil Water Assessment Tool (SWAT) model. Preliminary evaluation of the model performance involved the use of known quantitative evaluation statistics that included correlation coefficient, Nash Sut- cliffe efficiency (NSE), Deviation Volume (Dv) and a graphical technique for comparing observed and simu- lated flows. Initial model runs yielded poor daily flow simulations compared to monthly simulations. Poor daily simulation was attributed to differences in the timing of observed and simulated hydrographs. The model was calibrated for a three year period followed by a three year validation period based on monthly flows. Calibration results indicated an acceptable, but modest, agreement between observed and simulated monthly stream flows with a correlation coefficient (r) of about 0.7, NSE = 5%, and Dv= 61.7%. After vali- dation, the model performance was satisfactory with the coefficient of determination (R2 ≈ 0.6), Nash-Sut- cliffe efficiency (NSE) of 0.51 and a deviation volume (Dv) value of 24.7%. The modest model performance was associated with input data deficiencies and model limitations. Even then, the results indicate that the model can possibly be adapted to the local conditions in the catchment for which it is being applied but with improvements involving better parameter calibration techniques, and collection of better quality data. Such a study may be used to predict the effect of climate change on river flows as well as the effect of land use changes on the hydrologic response of a catchment.展开更多
文摘Soil Water Retention Characteristics (SWRC) models have been widely used in many applications. Presently, there are many models in the literature and many more still being developed so much so that it is confusing which model to prefer. The current choice of the appropriate model to use has not been well guided by any incisive research on the predictive performance of these models. Consequently, SWRC model applications have been largely moved by convenience. This study used a global dataset to evaluate 12 commonly used SWRC models. The measured data onto which the models were evaluated was grouped into different soil depths and different regions of the world. The evaluation used correlation, Nash-Sutcliffe efficiency, and residual standard error statistics to choose the best overall performing model and models for each category. It gives an indication of the type of SWRC models to use in different regions of the world and depths of sampling. The suitability of the models to regions showed that the Fredlund and Xing model had the best performance in subsoils in Africa;Omuto in Southern Asia;and van Genuchten in subsoils of the other regions. It is recommended that many more models be tested using the procedures in this study so that benchmarks can be established on SWRC model selection suitable for various regions.
文摘Groundwater prospecting in Kenya has been haphazard and expensive due to lack of information on the appropriate areas for hydrogeological exploration and drilling of boreholes. Drilling in areas without prior knowledge about their groundwater potential has been leading to the drilling of numerous dry boreholes. In this study, we explored the use of Geographic Information System as a pre-analysis tool to identify zones with groundwater potential for Garissa Country. Factors that contributed to groundwater occurrence were identified as landcover, soil type and rock formation. The groundwater potential zones were generated by analysing thematic data of the three factors and integrating the musing Weighted Index Overlay Analysis (WIOA) method. The groundwater potential zones were validated by comparing the predicted potentials with actual yields of existing boreholes drilled within those areas. Results indicate that, whereas the model correctly predicted areas with low or no groundwater potential, it performed sparingly well when predicting areas with good groundwater potential. The study conclusively identified areas where groundwater prospecting should not be attempted and other alternative methods of surface water provision should be explored.
文摘The purpose of the study was to develop pedotransfer functions for determining saturated hydraulic conductivity (Ks). Pedotransfer functions (PTFs) for predicting soil physical properties used in determining saturated hydraulic conductivity, based on moisture retention characteristics, were developed. The van Genuchten moisture retention equation was fitted to measured moisture retention properties obtained from International Soil Reference and Information Centre (ISRIC) soils data base in order to determine parameters in the equation i.e. saturated soil moisture content (θs), residual soil moisture (θr), air entry parameter (α) and the pore size distribution parameter (n). 457 samples drawn from the data base were used to be the maximum possible sample size that contained the measured soils characteristics data required. Using statistical regression, mathematical relationships were developed between moisture retention parameters (response variables) and appropriately selected transformed basic soil properties (predictor variables). The developed PTFs were evaluated for accuracy and reliability. It was found that pedotransfer functions developed for θs produced the best performance in reliability compared to the remaining parameters yielding a correlation coefficient value of coefficient of determination (R2 = 0.76), RMSE = 2.09, NSE = 0.75 and RSR = 0.5 indicating good performance. Relatively poorest performance was obtained from the pedotransfer function developed for α which yielded a correlation coefficient, R2= 0.06, RMSE = 0.85 and a NSE of 0.02 reflecting the best possible equation derived for the parameter for use in predicting hydraulic conductivity. Out of the pedotransfer functions developed for each of the moisture retention parameters, the best performing PTF was identified for each parameter. The accuracy of the pedotransfer functions assessed based on R2 were for θs (R2 = 0.80), θr (R2 = 0.42), α (R2 = 0.04) and for n (R2 = 0.30), when the variables were expressed directly in terms of the selected transformations of the basic soil properties.
文摘Modeling stream flow forms a basis upon which policy makers, watershed planners and managers make ap- propriate decisions consistent with sustainable management of land and water resources in the watershed. The aim of this research is to provide a preliminary assessment of the performance of a complex watershed model in predicting stream flow on the Naro Moru river catchment in Ewaso Ng’iro river basin, Kenya. The research involved model input data preparation, model set up and test running, sensitivity analysis and cali- bration of the Soil Water Assessment Tool (SWAT) model. Preliminary evaluation of the model performance involved the use of known quantitative evaluation statistics that included correlation coefficient, Nash Sut- cliffe efficiency (NSE), Deviation Volume (Dv) and a graphical technique for comparing observed and simu- lated flows. Initial model runs yielded poor daily flow simulations compared to monthly simulations. Poor daily simulation was attributed to differences in the timing of observed and simulated hydrographs. The model was calibrated for a three year period followed by a three year validation period based on monthly flows. Calibration results indicated an acceptable, but modest, agreement between observed and simulated monthly stream flows with a correlation coefficient (r) of about 0.7, NSE = 5%, and Dv= 61.7%. After vali- dation, the model performance was satisfactory with the coefficient of determination (R2 ≈ 0.6), Nash-Sut- cliffe efficiency (NSE) of 0.51 and a deviation volume (Dv) value of 24.7%. The modest model performance was associated with input data deficiencies and model limitations. Even then, the results indicate that the model can possibly be adapted to the local conditions in the catchment for which it is being applied but with improvements involving better parameter calibration techniques, and collection of better quality data. Such a study may be used to predict the effect of climate change on river flows as well as the effect of land use changes on the hydrologic response of a catchment.
