Hydrological Balance for Sustainable Water Resources Management: Case Studies from the EWA-BELT Project

The sustainable management of water resources is critical in addressing the challenges of climate change, population growth, and agricultural demands. Under the framework of the EWA-BELT project, the Thornthwaite-Mather model was performed to estimate the water balance in selected watersheds in the following countries: Ghana, Tanzania, Burkina Faso, and Kenya. This widely used model provides a framework for understanding how precipitation, evapotranspiration, and water storage in the soil interact over time within a defined geographic area. It helps assess whether a region is experiencing conditions of surplus, deficit, or equilibrium
regarding its water resources from a geomorphological point of view. Data regarding land use, soil, geological conditions, GIS etc. (derived from the literature review and internet platforms), and available meteorological data (precipitation and temperature)
were coupled to calculate the water balance in the examined basins. The prevailing conditions between the investigated East and West African countries are different. East African countries show lower temperature and higher precipitation. Also, geological formations are more permeable in East African case studies. The key findings are as follows: all case studies show water surplus. That means that on an intra-annual scale, at the end of the year, soil moisture reaches its maximum capacity, and an amount of water is stored in the aquifers and becomes runoff. East African countries (Kenya and Tanzania) case studies revealed a greater potential for water resources exploitation. In the case studies of these two countries, precipitation heights and infiltration percentages are higher, while evapotranspiration rates are relatively low compared to those of Ghana and Burkina Faso. This means that larger amounts of water resources could be used to cover demands for anthropogenic activities, mainly for irrigation purposes. The model's output can inform water resource management decisions, agricultural planning, and climate change impact studies. It is particularly useful in regions where water resources are critical and must be managed with an understanding of seasonal and inter-annual variability.