Combining Remote Sensing and in-Situ Data to Estimate Soil Moisture Across Mixed Land Cover Types.

Soil moisture is an essential variable which affects climatic, hydrological, agricultural, and ecological systems. Due to the impact of soil moisture on important earth processes, in-situ soil monitoring networks are becoming more prevalent. However, the majority of soil moisture monitoring networks consider only one land cover type, usually grasslands, which limits the use of these data for applications in other cover types. The Oklahoma Mesonet has monitored soil moisture at over 100 grassland sites for nearly two decades, but large areas of forest (12 million acres, or 28% of the state), cropland (~8 million acres, or 18%), and other vegetation types in the state have gone largely unmonitored (McPherson et al., 2007; National Agricultural Statistics Service; Oklahoma Forestry Service). While the current long-term soil moisture record is useful for a number of applications in many research areas, a major limitation of the current data is that it has been collected exclusively in grassland ecosystems and does not reflect soil moisture conditions under other vegetation types. However, remote sensing by satellites has led to the availability of high-resolution vegetation indices (VI) data, and these data, along with in-situ meteorological data from the Mesonet, may be incorporated into a simple water balance model to effectively estimate root-zone soil moisture at sites throughout Oklahoma regardless of vegetation type. These generalized soil moisture estimates could provide new, much needed information relevant to a number of disciplines, including hydrology, water resource planning, climatology, and agriculture.