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.
The monsoon is a seasonal rain and wind pattern that occurs over South Asia (among other places). Through NASA satellites and models we can see the monsoon patterns like never before. Monsoon rains provide important reservoirs of water that sustain human activities like agriculture and supports the natural environment through replenishment of aquifers. However, too much rainfall routinely causes disasters in the region, including flooding of the major rivers and landslides in areas of steep topography.
A series of winter storms brought more than 20 inches of rainfall to the Midwest and southeastern United States in December 2015. Massive flooding followed throughout both the regions. An animation of rainfall data from those storms was created at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The animation shows the accumulation of rainfall from December's three major storm systems that took place on Dec. 1 through 3, Dec. 13 through 16, and Dec. 21 through 31. The observations are from NASA's Global Precipitation Measurement (GPM) mission. Red colors indicate accumulate...
It was rain that wouldn't quit. A weather system fueled by warm moisture streaming in from the Atlantic Ocean on Oct. 3 and 4 relentlessly dumped between one and two feet of rain across most of South Carolina. The result was rivers topping their banks and dams bursting. Catastrophic flooding followed across most of the state, which has left residents in some areas without power or clean drinking water.
The United States has seen a tale of two extremes this year, with drenching rains in the eastern half of the country and persistent drought in the west. A new visualization of rainfall data collected from space shows the stark contrast between east and west for the first half of 2015. The precipitation data shown here, from Jan. 1 through July 16, is from the joint NASA-Japan Aerospace Exploration Agency's Global Precipitation Measurement mission. Accumulated rain totals are shown in different colors: 0 to 1 inch is light blue, up to 12 inches is green, up to 20 inches is yellow,...
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.