A wealth of information about the planet's water is contained in the moisture levels of its soil. As outlined in the SMAP Applications Plan, SMAP findings will have global significance in a range of scientific endeavors with socioeconomic impact.
Weather and Climate Forecasting
Because soil moisture variations affect weather and climate over continental regions, accurate and detailed data about soil moisture can be critical for weather prediction and seasonal climate models. Improved seasonal climate predictions will benefit climate-sensitive socioeconomic activities including water management, agriculture, and monitoring of drought hazards. 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, especially during conditions of water shortage and drought. Yet with no global 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 space-based soil-moisture observations. Related links:
- U.S. Drought Portal (NIDIS)
Floods and Landslides
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 understanding whether precipitation is infiltration or runoff. Soil moisture in mountainous areas is one of the most important determinants of landslides. Hydrologic forecast systems informed by mapped, high-resolution soil moisture fields will open up new capabilities in operational flood forecasting. Related links:
SMAP will provide information on water availability for estimating plant productivity and potential yield in agricultural prediction models. Direct soil-moisture observations will enable significant improvements in operational crop productivity and water-stress information systems.
Famine early-warning systems will directly benefit from improved seasonal soil-moisture forecasts using SMAP data, particularly in sub-Saharan Africa and South Asia. In those regions, hunger remains a major human health factor, and food comes from rain-fed crops in highly monsoonal (seasonal) conditions. Indirect health benefits of SMAP data will include 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. Direct observations of soil moisture will also provide valuable information for the emerging field of landscape epidemiology, which is aimed at identifying and mapping vector habitats and vector population dynamics for diseases such as malaria.