Utilizing Remote Sensing and Climate Predicted Precipitation Patterns to Drive Water Resource Infrastructure Investment Decisions: Marwa, Tanzania

Abstract:

Near the village of Marwa, Tanzania, grazing cattle periodically erode the shoreline of the Pangani River, increasing flooding and spreading water-borne illnesses to the villagers’ primary freshwater source. Surface water capture and storage has been identified as another water source for both livestock and villagers alike. Utilizing only remotely sensed data, we evaluate the potential efficacy of different infrastructure choices and determine their optimal location. As part of the decision-making process, the long-term sustainability of the infrastructure is assessed utilizing climate predicted changes to rainfall to model water availability for years to come. Various publicly available databases, methodologies, and software were used to obtain this goal. NASA’s Earthdata provided the necessary rainfall and surface runoff data to create an environmental profile of the region. Using GIS software, watershed delineation and bluespot identification programs were performed. These located already low-lying, flood-prone areas ideal for a reservoir. Overall, an optimal location was determined for the upslope reservoir. Using surface runoff estimations, soil data, and the delineated watershed, potential threats to the structure were examined and possible solutions were recommended. This research project proves that remotely sensed data alone can provide sufficient insights toward environmental decision-making. In addition, it provides a methodology for planning robust water infrastructure that can withstand precipitation patterns altered by climate change. Altogether, these methods will undoubtedly save time and resources for engineers and help suffering communities receive long-lasting aid promptly and inexpensively.