Global Flood Monitoring System (GFMS)

University of Maryland

Real-time quasi-global hydrological calculations at 1/8th degree and 1 km resolution

Contact: Dr. Huan Wu huanwu@umd.edu


GENERAL DESCRIPTION: The GFMS is a NASA-funded experimental system using real-time TRMM Multi-satellite Precipitation Analysis (TMPA) and Global Precipitation Measurement (GPM) Integrated Multi-Satellite Retrievals for GPM (IMERG) precipitation information as input to a quasi-global (50°N - 50°S) hydrological runoff and routing model running on a 1/8th degree latitude/longitude grid. Flood detection/intensity estimates are based on 13 years of retrospective model runs with TMPA input, with flood thresholds derived for each grid location using surface water storage statistics (95th percentile plus parameters related to basin hydrologic characteristics). Streamflow,surface water storage,inundation variables are also calculated at 1km resolution.In addition, the latest maps of instantaneous precipitation and totals from the last day, three days and seven days are displayed.

HOW TO USE SYSTEM: Starting with the 1/8th degree resolution maps, users can "zoom in" to regional areas, change which parameter to view, time sequence the maps over the last few days or months, and select a latitude/longitude location and plot time sequences of data at a point. Once sufficiently "zoomed in"(~10° latitude window is recommended) on the 1/8th degree maps, one can select from the 1 km resolution parameters (streamflow, water storage,inundation map) for a high resolution view of the regional basin. Time sequences at this high resolution of the map can be viewed and time series at a point can also be plotted by clicking the mouse at the location (it is encouraged to zoom-in enough to locate correctly the interested point).

SHORT-TERM (4-5 DAYS)FLOOD FORECASTING(at 1/8th deg.): The loading page shows the latest flood simulations using satellite information. One can click ">> Next time step" below each panel or input a future time (into 4-5 days) to view the flood forecasts using the hydrological model based on NWP (i.e.GEOS-5) precipitation.

MORE ABOUT THE HYDROLOGICAL MODEL AND OUTPUTS: The flood model is based on the University of Washington Variable Infiltration Capacity (VIC) land surface model (Liang et al., 1994) coupled with the University of Maryland Dominant River Tracing Routing (DRTR) model (Wu et al., 2013,).The VIC/DRTR coupled model is named as the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model. The flood detection algorithm is described in Wu et al. (2012). The real-time TMPA precipitation data product (Huffman et al., 2010) is obtained from the NASA Goddard TRMM/GPM Precipitation Processing System (PPS).The new GFMS with the DRIVE model has been evaluated based on 15-yr (1998~2012) retrospective simulation against more than 1,000 gauge streamflow observations and more than 2,000 reported flood events across the globe(Wu et al., 2013). The PDF file of the paper is available here. A summary of the flood system, examples of results and validation results is also included in a set of slides from a recent conference talk.
      The surface water storage (i.e. the routed runoff) is the the depth [mm] of the surface water above dry ground. At 1/8th degree resolution, the flood intensity value is the calculated water depth [mm] above the flood threshold. Calculations of streamflow [m3/s] are also shown as well as streamflow values above a flood threshold determined from retrospective model runs at 1/8th degree resolution. The surface water storage map (at 1km res.) shows the spatial distribution of natural surface water, including all surface water constrained in river channels and overflowing to surrounding floodplains. The inundation map at every 3-hour time step is derived based on the surface water storage at the same time step by masking out the normal (or referential) water coverage from it. The referential water coverage is defined from historic hydrological simulation, i.e. we use 95th percentile value map of the surface storage as the referential water coverage. Two thresholds are applied to further define the referential water map and inundation, i.e. the referential water has to be larger than 3 mm and an inundation occurs only when the surface water storage is larger than 10 mm. The calculations are for natural systems and do not include the changes in topography caused by man-made constructions (e.g. dams, levees ). All the calculations are updated every three hours.

DATA AVAILABILITY: Flood Detection/Intensity at 1/8th degree resolution are available from here

References

Huffman, G.J., R.F. Adler, D.T. Bolvin, E.J. Nelkin, 2010: The TRMM Multi-satellite Precipitation Analysis (TMPA). Chapter 1 in Satellite Applications for Surface Hydrology, F. Hossain and M. Gebremichael, Eds. Springer Verlag, ISBN: 978-90-481-2914-0, 3-22.

Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for GSMs, J. Geophys. Res., 99(D7), 14,415-14,428.

Wu, H., R. F. Adler, Y. Tian, G. J. Huffman, H. Li, and J. Wang (2014), Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model, Water Resour. Res., 50, 2693.2717, doi:10.1002/2013WR014710.

Wu H., R. F. Adler, Y. Hong, Y. Tian, and F. Policelli (2012), Evaluation of Global Flood Detection Using Satellite-Based Rainfall and a Hydrologic Model. J. Hydrometeor, 13, 1268.1284.

Wu H., J. S. Kimball, H. Li, M. Huang, L. R. Leung, R. F. Adler (2012), A new global river network database for macroscale hydrologic modeling, Water Resour. Res., 48, W09701, doi:10.1029/2012WR012313.

Wu, H., J. S. Kimball, N. Mantua, and J. Stanford (2011), Automated upscaling of river networks for macroscale hydrological modeling, Water Resour. Res., 47, W03517, doi:10.1029/2009WR008871.