Hydrological and water resources investigations of the Mereb-Gash river basin in Eritrea

Abstract

Introduction. Adaptation and mitigation of climate change and its consequences through effective water resources management, among others, is essential for achieving sustainable development goals. The construction of water infrastructure facilities and the maintenance of existing ones which can be done with up-to-date hydrological information are required. Therefore, this study aims at obtaining unique information and choosing effective tools for stream flow simulations in Mereb-Gash river basin. Materials and methods. To this end, physically-based semi-distributed and conceptual models are investigated using climate reanalysis datasets and geomorphologic catchment characteristics. Prior to feeding model forcing variables, their statistical and spatial patterns, methods of potential evapotranspiration estimations, and basin drought conditions are studied. Two or more approaches have been employed for each of these tasks. Results. GIUH-Nash model has the potential to produce acceptable values in most cases irrespective of sources and resolutions of digital elevation models, but it is found to be sensitive to the type of algorithms selected for stream network generations. The continuous simulation models reveal considerable overestimation of most of the precipitation in the reanalysis datasets, which in turn has a significant effect on other variables, such as potential evapotranspiration and thereby leading to a substantial discrepancy between simulated and observed. Conclusions. Despite the fact that reanalysis dataset has a great advantage over ground-based observations in terms of their simplicity and accessibility, the research results have shown the need for a critical attitude to both sources of initial data. To minimize the uncertainties of mathematical models and thereby to improve modeling capabilities, there is no qualitative alternative to restoring existing as well as new ground-based observation stations.