Inland water bodies are critical to human development and biodiversity, but they are under a confluence of anthropogenic and climate pressures. The Hamun lakes on the border of Afghanistan and Iran, fed by an endorheic transboundary basin of Helmand River, embody the challenges facing inland water bodies. The Hamun lakes started shrinking in 2000 and have shifted from a perennial to an intermittent hydrologic regime in the recent decade. This resulted in socioenvironmental catastrophes including shortage of drinking water, loss of croplands and livestock, dust/sand storms, and out-migration from the region. To assess the causes of drying of the Hamun Lakes, I propose to use various satellite and climate data from 1984-2019 to capture changes in land use, water resources, and climate forcings within the region. In the absence of in-situ observations, I propose to compile a reliable climate dataset by evaluating available remotely sensed and reanalysis data using signal-to-noise ratio metrics to derive an ensemble weighted-average. A drought analysis based on drought indices will ensue to shed light on how climate stressors may have contributed to drying of the lakes. I also propose to document historical agricultural activity, and changes in surface water bodies using a combination of Landsat and MODIS multispectral products. Finally, I propose to model the Hamun Lakes’ dynamic using different network architecture of a Long-Short Term Memory model. The inputs of the model will consist of both climatic and land use data and I will develop different scenarios to disentangle the effects of anthropogenic and climatic stressors on the surface area of the Hamun Lakes.