West Africa is one of the poorest regions in the world and highly vulnerable to extreme hydrological events due to the lack of reliable monitoring and forecast systems. For the first time, we demonstrate that initial hydrological conditions informed by satellite-based terrestrial water storage (TWS) estimates improve seasonal streamflow forecasts. TWS variability detected by the Gravity Recovery and Climate Experiment (GRACE) satellites is assimilated into a land surface model during 2003–2016 and used to initialize 6-month hindcasts (i.e., forecasts of past events) during West Africa's wet seasons. We find that GRACE data assimilation (DA) generally increases groundwater and soil moisture storage in the region, resulting in increased evapotranspiration and reduced total runoff. Total runoff is particularly lower at the headwaters of the Niger River, positively impacting streamflow simulations and hindcast initializations. Compared to simulations without GRACE-DA, hindcasts are notably improved at locations draining from large basin areas, in particular, over the Niger River basin, which is consistent with GRACE's coarse spatial resolution. The long memory of groundwater and deep soil moisture, two main TWS components updated by GRACE-DA, is reflected in prolonged improvements in the streamflow hindcasts. Model accuracy at Niamey, Niger, the most populated city where streamflow observations are available, improved up to 33% during the flood season. These new findings directly contribute to ongoing developments in food security, flood potential forecast, and water-related disaster warning systems for Africa.
|Journal||Water Resources Research|
|Publication status||Published - 2020 Feb 1|
Bibliographical noteFunding Information:
This study was funded by NASA's Applied Sciences Programs—SERVIR and Water Resources. The MERRA-2 meteorological data set is distributed by the Goddard Earth Sciences (GES) Data and Information Services Center (DISC; https://earthdata.nasa.gov/about/daacs/daac-ges-disc). CHIRPS rainfall estimates are made available by the Climate Hazards Center at UC Santa Barbara through https://www.chc.ucsb.edu/data/chirps/ website. Streamflow data are collected by different national water services, assembled by the Comité permanent Inter état de Lutte contre la Sécheresse au Sahel (CILSS) and available under request. GRACE land data are processed by the Center for Space Research (CSR) and available online (https://grace.jpl.nasa.gov/).
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All Science Journal Classification (ASJC) codes
- Water Science and Technology