|STILLMAN, S. - University Of Arizona|
|NINNEMAN, J. - University Of Alaska|
|ZENG, X. - University Of Arizona|
|FRANZ, T. - University Of Arizona|
|Scott, Russell - Russ|
|SHUTTLEWORTH, W.J. - University Of Arizona|
|CUMMINS, K. - University Of Arizona|
Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/28/2014
Publication Date: 8/1/2014
Publication URL: https://handle.nal.usda.gov/10113/6472392
Citation: Stillman, S., Ninneman, J., Zeng, X., Franz, T., Scott, R.L., Shuttleworth, W., Cummins, K. 2014. Summer soil moisture spatiotemporal variability in southeastern Arizona. Journal of Hydrometeorology. 15:1473-1485. https://doi.org/10.1175/JHM-D-13-0173.1.
Interpretive Summary: Knowing the amount of moisture in the soil is important for many different applications including meteorology, agriculture, and water management. Routine measurements of soil moisture are uncommon and, even when available, are generally not available over a wide area of interest such as a field or watershed. The purpose of this study was to take advantage of the unique long-term, spatially-distributed, soil moisture and precipitation dataset that has been collected over the past decade over the USDA-ARS Walnut Gulch Experimental Watershed to develop a method to determine soil moisture using more commonly available precipitation data alone. This model is then used to effectively increase the amount of soil moisture observations from the 13 to 17 normally available in any given year to the 37 to 88 available precipitation measurement sites and extend the time period of measurements from 10 (2002-2011) to 56 (1956-2011) years. The daily soil moisture over the watershed has a large spatial range following a summer thunderstorm and a small range during dry drought-like periods. Spatially and seasonally averaged soil moisture can be estimated nearly as well with the 13-17 soil moisture measurement sites as with samples at all rain gauge locations; however, estimates of daily spatial variability can be significantly hindered using fewer samples. The new longer-term and higher-resolution soil moisture dataset can be useful for new experimental applications such as hydrological modeling, soil moisture-sensing satellite calibrations, and plant growth models.
Technical Abstract: Soil moisture is important for many applications, but its measurements are lacking globally and even regionally. The Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona has measured nearsurface 5-cm soil moisture with 19 in situ probes since 2002 within its 150km2 area. Using various criteria to identify erroneous data, it is found that in any given period from 1 July to 30 September from 2002 to 2011, 13– 17 of these probes were producing reasonable data, and this is sufficient to estimate area-averaged seasonal soil moisture. A soil water balance model is then developed using rainfall as its only input to spatially extrapolate soil moisture estimates to the 88 rain gauges located within the watershed and to extend the measurement period to 56 years. The model is calibrated from 2002 to 2011 so that the daily in situ and modeled soil moisture time series have a high average correlation of 0.89 and a root-mean-square deviation of 0.032m3m23. By interpolating modeled soil moisture from the 88 rain gauges to a 100-m gridded domain over WGEW, it is found that spatial variability often increases when 88 (rather than 13–17) estimates are taken. While no trend in the spatial average surface soil moisture is found, large variability in the spatial average soil moisture from 1 July to 30 September is observed from year to year, ranging from 0.05 to 0.09m3m23. In addition to spatiotemporal analysis of WGEW, this gridded soil moisture product from 1956 to 2011 can be used for validation of satellite-based and reanalysis products and land surface models.