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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.
In January 2015, the Shire River in Malawi, and Zambezi River in Mozambique were under tight scrutiny. Weeks of torrential rains led these and other rivers to burst their banks displacing 390,000 people across the region. In southern Malawi 220,000 acres of farmland were turned into a lake, cutting off roads and stranding thousands of people on patches of high ground. The flood was devastating for the country, but within 72 hours of it being declared an emergency the United Nations World Food Programme (WFP) was on the ground distributing food to residents.
Rain, snow, hail, ice, and every mix in between make up the precipitation that touches everyone on our planet. But precipitation doesn't fall equally in all places around the world, as seen in NASA's new animation that captures every shower, snowstorm and tropical cyclone over a six-day period in August 2014. The time lapse was created from data captured by the Global Precipitation Measurement (GPM) satellite mission, now just over a year old, which scientists are using to better understand freshwater resources, natural disasters, crop health and more.
On October 6, 2014 (0215 UTC) the Global Precipitation Measurement (GPM) mission's Core Observatory flew over Typhoon Phanfone as it made landfall over Tokyo, Japan. At this point, Typhoon Phanfone is category 3 with maximum sustained winds at 127 miles per hour (mph) and gusts reaching 155 mph. Phanfone caused landslides and flooding throughout Japan.
One of the world's longest migrations of zebras occurs in the African nation of Botswana, but predicting when and where zebras will move has not been possible until now. Using NASA rain and vegetation data, researchers can track when and where arid lands begin to green, and for the first time anticipate if zebras will make the trek or, if the animals find poor conditions en route, understand why they will turn back.
"We had an extremely busy campaign," said Witek Krajewski, director of the Iowa Flood Center in Iowa City that partnered with NASA's GPM mission to run the Iowa Flood Studies (IFloodS) experiment from May 1 to June 15. The effort included scientists from 10 research institutions. IFloodS was a ground validation field campaign designed to provide ground truth and interpret satellite measurements.