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September 14, 2016

Droughts are one of the costliest natural disasters and globally affect a large number of people and their livelihoods every year. A new NASA satellite shows the promise of using the satellite’s soil moisture data for drought monitoring.

Droughts are among the costliest natural disasters and affect millions of people and their livelihoods every year globally. In the U.S., droughts cause financial damage of $6 to $8 billion per year on average. In order to minimize losses due to droughts and to manage the impact of water scarcities, it is essential to develop scientifically-based drought monitoring tools and early warning systems.

To help understand and plan for droughts, some experts recommend a shift in focus in water resources management from “blue water” (surface and  groundwater) to “green water” (soil moisture or the water retained in soils) especially in arid and semi-arid regions where drought is a common phenomenon. However, our understanding of green water/soil moisture changes across landscapes and throughout time has been limited. Soil moisture may be measured by a variety of methods, but unfortunately there is no comprehensive, national network of soil moisture monitoring instruments that can provide seamless information on soil moisture status across the nation.

To help strengthen our understanding of soil moisture and drought, NASA launched the Soil Moisture Active Passive (SMAP) satellite in January 2015 to take global measurements of soil moisture in the top 5 cm of soil. One of the key objectives of this satellite mission is to improve current flood prediction and drought monitoring capability.

A new study, led by the USGS Earth Resources Observation and Science (EROS) Center and the DOI North Central Climate Science Center, recently published in Rangelands journal, validates the soil moisture data being collected by SMAP over rangelands of the U.S. high plains. Researchers obtained nine months of SMAP soil moisture observations from the National Snow and Ice Data Center and compared the data with on-the-ground observations and computer models in order to validate its accuracy. They found a high level of agreement between the observations, models, and satellite data.

The researchers also evaluated the SMAP data to understand its use for drought monitoring in the rangeland watersheds of Texas and Oklahoma by comparing it  to three “agro-hydrologic” variables of interest for drought monitoring: precipitation, land surface temperature, and evapotranspiration.

This study shows the promise of using the SMAP satellite’s soil moisture data to produce useful products for drought monitoring purposes. It must be stressed, however, that this study used only nine months (April–Dec 2015) of beta quality (early adopter) data with preliminary algorithms. Hence, more evaluation over longer time periods and spatial extents is necessary to fully understand the full benefits and limitations of using SMAP soil moisture data for drought monitoring in diverse ecosystems.

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