Towards a South Asia Land Data Assimilation System: first results for transboundary basins

Benjamin F Zaitchik1, Debjani Ghatak2, David L Toll3, Nancy D Searby4, Ashutosh S Limaye5, Christa D Peters-Lidard6, Birendra Bajracharya7, Basanta Raj Shrestha8, Charles Iceland9, Kapil Narula10, Sylvia Lee11, Bessma Mourad11 and Bradley Doorn12, (1)Johns Hopkins University, Department of Earth and Planetary Sciences, Baltimore, United States, (2)Johns Hopkins University, Baltimore, MD, United States, (3)NASA GSFC, Greenbelt, MD, United States, (4)NASA Headquarters, Washington, United States, (5)NASA Marshall Space Flight Center, Huntsville, AL, United States, (6)NASA GSFC, Greenbelt, United States, (7)International Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal, (8)ICIMOD, Kathmandu, Nepal, (9)World Resources Institute, Washington, DC, United States, (10)Confederation of Indian Industry, New Delhi, India, (11)Skoll Global Threats Fund, San Francisco, CA, United States, (12)NASA Headquarters, Applied Sciences Program, Water Resources & Agriculture, Washington, United States
Abstract:
South Asia faces a remarkably complex and diverse set of hydrologic stresses, including melting glaciers, variable snowpack, intensively utilized transboundary rivers, rapid groundwater depletion due to irrigation, flood and drought hazard, and rapidly changing land use/cover and climate conditions. The management and prediction challenges posed by these conditions are compounded by the sparseness of in situ monitoring sites, particularly in headwaters regions, and a lack of open sharing of hydrometeorological data across national boundaries. As a result, uncertainties in availability in a situation of rising demands are leading to increasing competing and exploitive use of a limited resource, being experienced at various scales. An open water information system for decision support is an absolute necessity. In order to provide an open and spatially complete water information system for decision support across the region, we are implementing a customized Land Data Assimilation System (LDAS) designed to provide best-available estimates of hydrologic states and fluxes across South Asia, both retrospectively and in near-real time. The LDAS merges advanced land surface models with satellite-derived and in situ observations. In the case of South Asia, multiple satellite-derived hydrological fields are relevant to complete water balance analysis, including precipitation from multiple sources (e.g., TRMM, CHIRPS, GPM), water storage anomalies from GRACE, thermal infrared evapotranspiration estimates, and snowpack characteristics from visible and microwave sensors. Each of these observation types can either be ingested to South Asia LDAS or used as an independent observation for comparison. Here we present the first results of this South Asian Land Data Assimilation System, with a focus on complete water balance analysis for selected river basins in South Asia.