# Presentation: 420667

## Remotely-Sensed Estimates of Soil Moisture 

**to Infer Soil Texture and Hydraulic Properties **

- Near-surface soil moisture is a critical component of land-surface energy and water balance models, but accurate soil moisture prediction requires soil texture and hydraulic property information, which is poorly characterized over most of the globe.

- Physically meaningful soil texture information can be retrieved from a few but appropriately-timed soil moisture measurements from microwave remote sensing.

**Figure 1**

- Optimized vs. Measured Soil Textures

**Figure 2**

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## Name: Christa Peters-Lidard, NASA/GSFC 

**E-mail: **Christa.D.Peters-Lidard@nasa.gov
**Phone: **301-614-5811
**References:**
- Santanello, J.A., Jr., C. D. Peters-Lidard, M. Garcia, D. Mocko, M. Tischler, MS. Moran, and D.P. Thoma, 2007.  Using Remotely-Sensed Estimates of Soil Moisture to Infer Soil Texture and Hydraulic Properties across a Semi-arid Watershed, In Press, Remote Sensing of the Environment.
- Peters-Lidard, Christa D., David M. Mocko, Joseph A. Santanello, Jr., Michael A. Tischler, M. Susan Moran, Matthew Garcia, and Y. Wu, 2007. The role of precipitation uncertainty for soil property estimation using soil moisture retrievals in a semi-arid environment. Submitted to Water Resources Research.
- Garcia, M., C.D. Peters-Lidard, and D.C. Goodrich, 2007.  Spatial interpolation of precipitation in a dense gauge network for monsoon storm events in the southwestern US.  Submitted to Water Resources Research.
**Data Sources:  **This is a joint effort composed of multiple agencies including the USDA-Agricultural Research Service (watershed, remote-sensing data), NASA-GSFC (land-surface modeling within the Land Information System (LIS; http://lis.gsfc.nasa.gov), coupled with Parameter Estimation (PEST)) and US Army Corps of Engineers-Engineering Research and Development Center (financial support, operational testing, user interface development),
- Near-surface (0-5cm) soil moisture observations (Figure 1) derived from successive aircraft flights using NASA’s L-Band Push-Broom Microwave Radiometer (PBMR; a precursor to the Hydros/SMAP mission) were acquired during the Monsoon ‘90 experiment in SE Arizona, and used to calibrate soil hydraulic properties in the Noah land-surface model executed within LIS at a very high horizontal spatial resolution of 40 meters.
**Technical Description of Image:**
***Figure 1:  ***Simulated (top), PBMR-observed (middle), and difference (bottom) 0-5 cm soil moisture using a) default (USDA SSURGO) soils and b) soil properties calibrated using LIS/Noah+PEST on DOY 214.  The soil moisture bias and RMS error are greatly reduced after the soil property calibration. Limited remote microwave retrievals of near-surface soil moisture can be used to calibrate the soil texture and hydraulic properties using this combined observation, modeling and parameter estimation approach. (Fig. 1).  [Santanello et al., 2007]
***Figure 2:***  Percentages of sand, silt, and clay estimated using this approach at the eight sites compared with in-situ soil measurements from Schmugge et al. (1994).  The LIS/Noah+PEST system correctly estimates highly-sandy soils in this semi-arid watershed. Soil texture estimated using this approach corresponds well with in situ observations of sand, silt, and clay at various sites across the watershed. By estimating within a continuous range of soil properties such as sand, silt, and clay percentages rather than applying disconitnuous soil texture classes, the physical accuracy and consistency of the estimated soil properties is assured and can be more easily assessed against in situ measurements.
**Scientific significance: **Soil texture and hydraulic properties are required for accurate prediction of soil moisture, and are poorly known over many areas of the globe.  This work is the first to demonstrate how remotely sensed soil moisture combined with a physical model may be combined to infer these critical parameters.
**Relevance for future science and relationship to Decadal Survey: **Soil moisture is a critical control on water and energy cycles, as well as weather, climate, hydrological and agricultural prediction.  Soil texture and hydraulic properties are required for accurate prediction of soil moisture.  Soil moisture observations from the SMAP mission, to be launched in the 2010-2013 timeframe, combined with precipitation observations from the GPM mission, to be launched in 2013, will provide the necessary data products to infer soil textures world wide using the techniques presented in this work.

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