Assimilation of NASA MODIS Flood Mapping Product into Operational Flash Flood Warning Systems
Abstract
Regional operational systems that support forecasters for the real-time warning of flash flood events have been implemented worldwide in the last decade. These systems provide hydrological and meteorological agencies the tools to make possible timely alerts and warnings for flash floods in small basins (area of order of 100 km2). The output of the model consists of indices that estimate the amount of rain of a certain duration that is needed over a given small basin in order to cause minor flooding (bankfull flow) at its outlet. These indices are adjusted and used with local available data and nowcast products by forecasters and enable the generation of prompt flash flood warnings and alerts. Soil moisture is the principal state variable in estimating the rainfall-runoff relationship in a given catchment. Antecedent soil moisture conditions directly impact the ability of additional precipitation to infiltrate, rather than becoming surface runoff. In the operational systems the focus is on the water balance over the flash-flood prone small watersheds. Backwater catchment inundation from swollen rivers or regional groundwater inputs is not significant over the spatial and temporal scales for the majority of the upland flash flood prone basins, and as such, these effects are not considered. However, some lowland areas and flat terrain near large rivers experience standing water long after local precipitation has ceased as a result of phenomena outside of local forcing. The NASA Office of Applied Science is producing an experimental product from the MODIS instrument on the Terra and Aqua satellites that detects standing water, beyond reference water, at a daily time interval and with a 250m resolution. This presentation discusses the potential utility of this product to adjust the soil water estimates of the operational systems for flash flood prone basins in low lying areas to improve local flash flood warnings. Given that a portion of the catchment area is inundated, the total volume of the upper soil water content of the catchment can be expressed with respect to the proportion of inundated area, and with respect to the modeled soil saturation fraction and its error. These relations are used to derive an error estimate for the modeled soil saturation fraction; whereby, the soil saturation fraction model state can be updated given the availability of observed inundation. At its limit, the difference between modeled soil saturation fraction estimates and unity, representing full inundation, for those basin-days experiencing full inundation was found to be nearly normally distributed. In order to represent uncertainty in error estimates, conditional sampling was used to generate an ensemble of model error estimates for a given range of modeled upper soil water. Those error estimates were used in the context of Monte Carlo ensemble forecasting of soil water and flash flood potential. Numerical experiments with six months of data (July 2012 - December 2012) showed that MODIS inundation data, when assimilated to correct soil moisture estimates, increased the likelihood that bankfull flow would occur, over non-assimilated modeling, at catchment outlets for approximately 44% of basin-days during the study time period. For these basins this is a significant reduction of the bias that leads forecasters to underestimate local flash flood threat.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2013
- Bibcode:
- 2013AGUFMIN14A..06P
- Keywords:
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- 1855 HYDROLOGY Remote sensing;
- 1804 HYDROLOGY Catchment;
- 1910 INFORMATICS Data assimilation;
- integration and fusion;
- 4337 NATURAL HAZARDS Remote sensing and disasters