H010-0014
Remote sensing and modeling of water availability in Afghanistan from snow dominated highlands to arid lowlands

Monday, 7 December 2020
Poster
Md Shahriar Pervez1, Amy McNally2, Kimberly Slinski3, Jossy P Jacob3, Augusto Getirana3, Michael E Budde4, James Rowland5 and Harikishan Jayanthi6, (1)USGS Earth Resources Observation and Science (EROS) Center Sioux Falls, Sioux Falls, SD, United States, (2)US Agency for International Development, Falls Church, United States, (3)NASA Goddard Space Flight Center, Greenbelt, MD, United States, (4)Earth Resources Observation Systems Sioux Falls, Sioux Falls, SD, United States, (5)U.S. Geological Survey, Sioux Falls, SD, United States, (6)ASRC Federal Data Solutions /USGS EROS, Sioux Falls, SD, United States
Abstract:
Hydrologic regimes of Afghanistan depend on seasonal storage of water as snow. Winter snow accumulation over high mountains in the central and far northeastern parts of the country melts in spring and summer and provides perennial flow to most of the rivers across the country. Runoff generated from snowmelt is the primary source of water in these rivers which provide most of the consumptive water for the people of Afghanistan. Irrigation is by far the largest water use and accounts for approximately 80% of the food supply. Additionally, the country’s water resources are unequally distributed. The northern basins of Amu Darya cover only 37% of the territory but contain 60% of the flow, whereas the Helmand basin, with concentration of some of the largest irrigated lands, covers 49% of the territory but holds only 11% of the flow. We use CHIRPS data to monitor the progression of the winter wet season. While the precipitation was average to above average during the 2019-2020 wet season, the accumulation of water equivalent in the snowpack was impeded due to above average temperatures. We use the daily soil moisture and snow water equivalent (SWE) estimated from land surface models using remote sensing inputs in the framework of Famine Early Warning Systems Network Land Data Assimilation System (FLDAS) to monitor snow water storage. Analysis of SWE confirmed an earlier than normal start and finish of snowmelt across many basins. While CHIRPS and FLDAS provide critical information on water availability, a comprehensive monitoring requires information about the dynamics of streamflow across the county, especially in assessing the water availability in the downstream arid lands. We estimate streamflow at each basin outlet by utilizing the HyMAP routing algorithm. The daily streamflow will be generated from 1982 using GDAS rainfall and other meteorological data. We will generate benchmark flow exceedance probabilities information as a guide in identifying flood risk. We will also investigate streamflow forecasting by utilizing blended CHIRPS and Global Ensemble Forecast System precipitation. We expect that incorporation of these streamflow estimates will better represent the water balance and provide an improved understanding of prevailing water availability with beneficial early warning for flooding risks across Afghanistan.