Soil moisture plays an important role in weather and hydrological forecasts as well as agriculture and water management. Using a suite of hydrological instruments, we have analyzed soil moisture data from various sources in the Walnut Gulch Experimental Watershed in Southern Arizona. Instruments used here include rain gages, point soil moisture measurement such as Time Domain Reflectometry (TDR) and capacitance probes, and COsmic-ray Soil Moisture Observing System (COSMOS) probes with a foot print of around 700 m in diameter and a depth of 15-70 cm depending on soil moisture. COSMOS probes infer soil moisture from neutron counts, because neutrons penetrating the surface are highly moderated by the presence of hydrogen but are insensitive to soil chemistry. Benefits of such probes include a bridged spatial gap between point and large-scale remote sensing in these measurements.

In this presentation, we will show the spatiotemporal distributions of soil moisture inferred from these measurements during the 2010 North American Monsoon period. Because there are more rain gauge sites than point soil moisture measurement sites, we have also developed a simple water balance model to compute soil moisture based on precipitation. Coefficients in this simple model are calibrated by comparing the computed soil moisture with point soil moisture measurements at co-located sites. Finally, a soil moisture vertical weighting scheme is created from TDR measurements for comparison with COSMOS data, which has implications in Soil Water Equivalent (SWE) and vertical distribution of soil moisture.