FALL 2011 AGU ALERT- Please join us for a discussion Tuesday, December 6, 2011. AGU Flyer (PDF, 2.71 MB)

In line with recommendations of the NRC Decadal Survey report (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, Space Studies Board, National Academies Press, 2007) SMAP is implementing a strategy that promotes applications research and engages a broad community of users in SMAP applications. The goals of the SMAP applications Program are to:

• Establish a SMAP Applications Working Group
• Promote the use of SMAP products to a community of end-users and decision makers that understand SMAP capabilities and are interested in using SMAP products in their application;
• Facilitate feedback between SMAP user communities through the SMAP Applications Working Group and the SMAP mission and Science Definition Team;
• Provide information on and documentation of collaboration with different classes of users and communities and design communication strategies to reach out to these new communities, including those of precipitation, drought detection, agriculture, ecosystem modeling, among others;

Applications Working Group

The SMAP Applications Working Group coordinates applications activities for the mission. The Working Group has developed a SMAP Applications Plan, and is coordinating the engagement of SMAP Applications Early Adopters.

The Working Group held the 1st SMAP Applications Workshop at the NOAA Science Center, Silver Spring, MD, on September 9-10, 2009. The 2nd SMAP Applications Workshop will be held October 12-13, 2011 at the U.S. Dept. of Agriculture in Washington, DC.

SMAP Applications Areas

SMAP has the potential to enable a diverse range of applications including drought and flood guidance, agricultural productivity estimation, weather forecasting, climate prediction, and human health and security, as listed below. Applications across agencies are a unique feature of SMAP.

Soil moisture variations affect the evolution of weather and climate over continental regions. Initialization of numerical weather prediction and seasonal climate models with accurate soil moisture information enhances their prediction skills and extends their skillful lead-times. Improved seasonal climate predictions will benefit climate-sensitive socioeconomic activities, including water management, agriculture, and fire, flood and drought hazards monitoring.
Related Links:
Goddard Modeling and Assimilation Office (GMAO)
National Centers for Environmental Prediction (NCEP)
European Centre for Medium Range Weather Prediction (ECMWF)
Meteorological Service of Canada (MSC)

Soil moisture strongly affects plant growth and hence agricultural productivity, especially during conditions of water shortage and drought. At present there is no global in situ network for soil moisture monitoring. Global estimates of soil moisture and plant water stress must be derived from models. These model predictions (and hence drought monitoring) can be greatly enhanced through assimilation of space-based soil moisture observations.
Related Links:
U.S. Drought Portal (NIDIS)

Soil moisture is a key variable in water related natural hazards such as floods and landslides. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. The surface soil moisture state is key to partitioning of precipitation into infiltration and runoff. Soil moisture in mountainous areas is one of the most important determinants of landslides. Hydrologic forecast systems initialized with mapped high-resolution soil moisture fields will therefore open up new capabilities in operational flood forecasting.
Related Links:
Dartmouth Flood Observatory
NOAA NWS River Forecast Centers

SMAP will provide information on water availability for estimating plant productivity and potential yield. The availability of direct observations of soil moisture from SMAP will enable significant improvements in operational crop productivity and water stress information systems, by providing realistic soil moisture observations as inputs for agricultural prediction models.

Improved seasonal soil moisture forecasts using SMAP data will directly benefit famine early warning systems particularly in sub-Saharan Africa and South Asia, where hunger remains a major human health factor and the population harvests its food from rain-fed agriculture in highly monsoonal (seasonal) conditions. Indirect benefits will also be realized as SMAP data will enable better weather forecasts that lead to improved predictions of heat stress and virus spreading rates. Better flood forecasts will lead to improved disaster preparation and response. SMAP will also benefit the emerging field of landscape epidemiology (aimed at identifying and mapping vector habitats for human diseases such as malaria) where direct observations of soil moisture can provide valuable information on vector population dynamics.