This video is public domain and can be downloaded at: http://svs.gsfc.nasa.gov/goto?11091
In July 2010, monsoon rains put one fifth of Pakistan under water. In December 2010 and January 2011, Tropical Cyclone Tasha and a wet year combined to drown Queensland, Australia. And in the United States this May, flooding on the Mississippi River has displaced thousands of people. Over months or a few short hours, extreme rain can interact with the right combination of topography, land use and climate to trigger deadly and costly floods.
To better understand and predict floods scientists have developed hydrological models based on how much rainfall occurs and where the water will likely go once it hits the ground. They use several satellite precipitation datasets within these models to provide near real-time estimates of when and where areas may flood. While the majority of flood models currently focus on local or regional scales — taking into account one drainage basin or watershed — some recent research has shifted to estimating areas of potential flooding on a global scale. The International Flood Network (IFNet) converts precipitation data from TRMM into rainfall maps as part of their Global Flood Alert System. While still in its trial version, IFNet determines flood risk based on a minimum precipitation threshold and in the future will alert communities of potential flooding in their region. Another global flood monitoring system integrates TRMM rainfall into a hydrologic model to estimate potential flooding conditions in near real-time, considering stream flow, water routing and existing river networks.
TRMM's flood monitoring map from March 11, 2011. The colored areas indicate locations with a low to high potential for flooding given the preceding rainfall conditions and flood modeling.
Go to the TRMM Flood and Landslide Monitoring page.
Organizations Which Use PMM Data for Flood Applications
The GFMS is a NASA-funded experimental system using real-time TRMM Multi-satellite Precipitation Analysis (TMPA) 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.
In spring 2009, the state of Iowa established (and funded) the new Iowa Flood Center (IFC). This effort was spearheaded by several Iowa senators and representatives, with much behind-the-scenes work by IIHR research engineers Larry Weber and Witold Krajewski. A total of $1,300,000 was appropriated for the center in its first year (FY2010).
The IFC is now actively engaged in flood projects in several Iowa communities and employs several graduate and undergraduate students participating in flood-related research. IFC researchers have designed a cost-efficient sensor network to better monitor stream flow in the state; have developed a library of flood-inundation maps for several Iowa communities; and are working on a large project to develop new floodplain map for 85 of Iowa’s 99 counties.
On Wednesday afternoon, June 12, a severe storm outbreak developed and moved across central and eastern Iowa, and then western Illinois, spawning huge thunderstorms and several tornadoes. NASA's Polarimetric (NPOL) precipitation radar, currently deployed in Iowa as part of the Iowa Flood Studies field campaign for the Global Precipitation Measurement mission, rapidly scanned these storms as they moved across the state.
Ground data now being collected in northeastern Iowa by the Iowa Flood Studies (IFloodS) experiment will evaluate how well NASA's Global Precipitation Measurement mission satellite rainfall data can be used for flood forecasting. With rainfall estimates in hand, the science teams input them into flood prediction computer models and then evaluate how the rain estimates and their uncertainties affect the outcome of the flood forecast.