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

Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa

Evapotranspiration (ET) accounts for a substantial amount of the water use in river basins particular in the tropics and arid regions. However, accurate estimation still remains a challenge especially in large spatially heterogeneous and data scarce areas including the Upper Pangani River Basin in Eastern Africa. Using multitemporal Moderate‐resolution Imaging Spectroradiometer (MODIS) and Surface Energy Balance Algorithm of Land (SEBAL) model, 138 images were analyzed at 250 m, 8 day scales to estimate actual ET for 16 land use types for the period 2008–2010. A good agreement was attained for the SEBAL results from various validations. For open water evaporation, the estimated ET for Nyumba ya Mungu (NyM) reservoir showed a good correlations (R = 0.95; R2 = 0.91; Mean Absolute Error (MAE) and Root Means Square Error (RMSE) of less than 5%) to pan evaporation using an optimized pan coefficient of 0.81. An absolute relative error of 2% was also achieved from the mean annual water balance estimates of the reservoir. The estimated ET for various agricultural land uses indicated a consistent pattern with the seasonal variability of the crop coefficient (Kc) based on Penman‐Monteith equation. In addition, ET estimates for the mountainous areas has been significantly suppressed at the higher elevations (above 2300 m a.s.l.), which is consistent with the decrease in potential evaporation. The calculated surface outflow (Qs) through a water balance analysis resulted in a bias of 12% to the observed discharge at the outlet of the river basin. The bias was within 13% uncertainty range at 95% confidence interval for Qs. SEBAL ET estimates were also compared with global ET from MODIS 16 algorithm (R = 0.74; R2 = 0.32; RMSE of 34% and MAE of 28%) and comparatively significant in variance at 95% confidence level. The interseasonal and intraseasonal ET fluxes derived have shown the level of water use for various land use types under different climate conditions. The evaporative water use in the river basin accounted for 94% to the annual precipitation for the period of study. The results have a potential for use in hydrological analysis and water accounting

Baseline review and ecosystem services assessment of the Tana River Basin, Kenya

The ‘WISE-UP to climate’ project aims to demonstrate the value of natural infrastructure as a ‘nature-based solution’ for climate change adaptation and sustainable development. Within the Tana River Basin, both natural and built infrastructure provide livelihood benefits for people. Understanding the interrelationships between the two types of infrastructure is a prerequisite for sustainable water resources development and management. This is particularly true as pressures on water resources intensify and the impacts of climate change increase. This report provides an overview of the biophysical characteristics, ecosystem services and links to livelihoods within the basin

Mapping evapotranspiration trends using MODIS and SEBAL model in a data scarce and heterogeneous landscape in Eastern Africa

Evapotranspiration (ET) accounts for a substantial amount of the water use in river basins particular in the tropics and arid regions. However, accurate estimation still remains a challenge especially in large spatially heterogeneous and data scarce areas including the Upper Pangani River Basin in Eastern Africa. Using multitemporal Moderate-resolution Imaging Spectroradiometer (MODIS) and Surface Energy Balance Algorithm of Land (SEBAL) model, 138 images were analyzed at 250 m, 8 day scales to estimate actual ET for 16 land use types for the period 2008–2010. A good agreement was attained for the SEBAL results from various validations. For open water evaporation, the estimated ET for Nyumba ya Mungu (NyM) reservoir showed a good correlations (R?=?0.95; R2?=?0.91; Mean Absolute Error (MAE) and Root Means Square Error (RMSE) of less than 5%) to pan evaporation using an optimized pan coefficient of 0.81. An absolute relative error of 2% was also achieved from the mean annual water balance estimates of the reservoir. The estimated ET for various agricultural land uses indicated a consistent pattern with the seasonal variability of the crop coefficient (Kc) based on Penman-Monteith equation. In addition, ET estimates for the mountainous areas has been significantly suppressed at the higher elevations (above 2300 m a.s.l.), which is consistent with the decrease in potential evaporation. The calculated surface outflow (Qs) through a water balance analysis resulted in a bias of 12% to the observed discharge at the outlet of the river basin. The bias was within 13% uncertainty range at 95% confidence interval for Qs. SEBAL ET estimates were also compared with global ET from MODIS 16 algorithm (R?=?0.74; R2?=?0.32; RMSE of 34% and MAE of 28%) and comparatively significant in variance at 95% confidence level. The interseasonal and intraseasonal ET fluxes derived have shown the level of water use for various land use types under different climate conditions. The evaporative water use in the river basin accounted for 94% to the annual precipitation for the period of study. The results have a potential for use in hydrological analysis and water accounting.Water ManagementCivil Engineering and Geoscience