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Towards Global Hydrological Drought Monitoring Using Remotely Sensed Reservoir Surface Area
Author(s) -
Zhao Gang,
Gao Huilin
Publication year - 2019
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2019gl085345
Subject(s) - environmental science , surface runoff , hydrology (agriculture) , streamflow , surface water , groundwater , scale (ratio) , water storage , water resources , geology , drainage basin , geography , ecology , geotechnical engineering , cartography , geomorphology , environmental engineering , inlet , biology
Hydrological drought quantification using surface water information has been lacking at a large scale due to limited in situ data. We introduce a framework for monitoring hydrological droughts using a global, long‐term, monthly, remotely sensed reservoir surface area dataset. At regional scales, a new index—the reservoir area drought index (RADI)—is defined as the monthly normalized reservoir area time series. RADI was validated using an in situ reservoir storage based index (average R 2 = 0.83). RADI not only helps to characterize drought propagation from meteorological and agricultural droughts to hydrological droughts but also fills the information gap between streamflow/runoff based and groundwater based drought indices. The surface area dataset was further used to characterize the recovery rate (and to estimate the recovery time) at the individual reservoir scale during droughts. This across‐scale drought monitoring framework can help mitigate drought impacts and increase water use efficiency among multi‐reservoir systems.