HydroXtreme-MaP: A Global Real-time Hydrological Modeling System for Flood and Drought Monitoring and Prediction

Nowadays, flooding and drought are increasing in frequency and severity around the world. Detecting, Monitoring and predicting the flooding and drought at global scales pose the big challenges and opportunities for the hydrologist. We developed a Global Hydrological Flood and Drought Mapping and Prediction System (HydroXtreme-MaP) driven by near real-time 3-hour TRMM Multi-satellite Prediction Analysis (TMPA) precipitation, via the Coupled Routing and Excess STorage (CREST) distributed hydrological model (Wang et al. 2011) to provide modeling streamflow, actual ET, soil moisture and other state variables to detect, monitor and predict flooding and drought at 1/8th degree resolution, displayed on http://eos.ou.edu. On too-much-water side, this system detects storm-triggered floods and on too-little-water side, it maps precipitation-based meteorological drought (SPI), streamflow-based Hydrological Drought (SRI), and plant-available-soil moisture-based Agricultural Drought (Soil Moisture) (SMI). This HydroXtreme-MaP (GFD-Maps) system directly addresses the first objective of Global Earth Observation System of Systems (GEOSS): Enabling the use of Earth observations and predictive models for timely disaster decision making to benefit society. The HydroXtreme-MaP is validated in several basins in the U.S. and China and other continents in terms of flooding and drought detection capability.