Managing Basin Interdependencies in a Heterogeneous, Highly Utilized and Data Scarce River Basin in Semi-Arid Africa: The case of the Pangani River Basin, Eastern Africa

For integrated water resources management both blue and green water resources in a river basin and their spatial and temporal distribution have to be considered. This is because green and blue water uses are interdependent. In sub-Saharan Africa, the upper landscapes are often dominated by rainfed and supplementary irrigated agriculture that rely on green water resources. Downstream, most blue water uses are confined to the river channels, mainly for hydropower and the environment. Over time and due to population growth and increased demands for food and energy, water use of both green and blue water has increased. This book provides a quantitative assessment of green-blue water use and their interactions. The book makes a novel contribution by developing a hydrological model that can quantify not only green but also blue water use by many smallholder farmers scattered throughout the landscape. The book provides an innovative framework for mapping ecological productivity where gross returns from water consumed in agricultural and natural vegetation are quantified. The book provides a multi-objective optimization analysis involving green and blue water users, including the environment. The book also assesses the uncertainty levels of using remote sensing data in water resource management at river basin scale.Dissertation submitted in fulfilment of the requirements of the Board for Doctorates of Delft University of Technology and of the Academic Board of the UNESCO-IHE Institute for Water Education.Water Resource

Modelling stream flow and quantifying blue water using modified STREAM model in the Upper Pangani River Basin, Eastern Africa

Effective management of all water uses in a river basin requires spatially distributed information of evaporative water use and the link towards the river flows. Physically based spatially distributed models are often used to generate this kind of information. These models require enormous amounts of data, if not sufficient would result in equifinality. In addition, hydrological models often focus on natural processes and fail to account for water usage. This study presents a spatially distributed hydrological model that has been developed for a heterogeneous, highly utilized and data scarce river basin in Eastern Africa. Using an innovative approach, remote sensing derived evapotranspiration and soil moisture variables for three years were incorporated as input data in the model conceptualization of the STREAM model (Spatial Tools for River basin Environmental Analysis and Management). To cater for the extensive irrigation water application, an additional blue water component was incorporated in the STREAM model to quantify irrigation water use (ETb(I)). To enhance model parameter identification and calibration, three hydrological landscapes (wetlands, hill-slope and snowmelt) were identified using field data. The model was calibrated against discharge data from five gauging stations and showed considerably good performance especially in the simulation of low flows where the Nash–Sutcliffe Efficiency of the natural logarithm (Eln) of discharge were greater than 0.6 in both calibration and validation periods. At the outlet, the Eln coefficient was even higher (0.90). During low flows, ETb(I) consumed nearly 50% of the river flow in the river basin. ETb(I) model result was comparable to the field based net irrigation estimates with less than 20% difference. These results show the great potential of developing spatially distributed models that can account for supplementary water use. Such information is important for water resources planning and management in heavily utilized catchment areas. Model flexibility offers the opportunity for continuous model improvement when more data become available.Water ManagementCivil Engineering and Geoscience

Modelling stream flow and quantifying blue water using a modified STREAM model for a heterogeneous, highly utilized and data-scarce river basin in Africa

Integrated water resources management is a combination of managing blue and green water resources. Often the main focus is on the blue water resources, as information on spatially distributed evaporative water use is not as readily available as the link to river flows. Physically based, spatially distributed models are often used to generate this kind of information. These models require enormous amounts of data, which can result in equifinality, making them less suitable for scenario analyses. Furthermore, hydrological models often focus on natural processes and fail to account for anthropogenic influences. This study presents a spatially distributed hydrological model that has been developed for a heterogeneous, highly utilized and data-scarce river basin in eastern Africa. Using an innovative approach, remote-sensing-derived evapotranspiration and soil moisture variables for 3 years were incorporated as input data into the Spatial Tools for River basin Environmental Analysis and Management (STREAM) model. To cater for the extensive irrigation water application, an additional blue water component (Qb) was incorporated in the STREAM model to quantify irrigation water use. To enhance model parameter identification and calibration, three hydrological landscapes (wetlands, hillslope and snowmelt) were identified using field data. The model was calibrated against discharge data from five gauging stations and showed good performance, especially in the simulation of low flows, where the Nash–Sutcliffe Efficiency of the natural logarithm (Ens_ln) of discharge were greater than 0.6 in both calibration and validation periods. At the outlet, the Ens_ln coefficient was even higher (0.90). During low flows, Qb consumed nearly 50% of the river flow in the basin. The Qb model result for irrigation was comparable to the field-based net irrigation estimates, with less than 20% difference. These results show the great potential of developing spatially distributed models that can account for supplementary water use. Such information is important for water resources planning and management in heavily utilized catchment areas. Model flexibility offers the opportunity for continuous model improvement when more data become available.Water ManagementCivil Engineering and Geoscience