Abstract
Abstract. Soil moisture governs the surface fluxes of mass and energy and is a major influence on floods and drought. Existing techniques measure soil moisture either at a point or over a large area many kilometers across. To bridge these two scales we used the cosmic-ray rover, an instrument similar to the recently developed COSMOS probe, but bigger and mobile. This paper explores the challenges and opportunities for mapping soil moisture over large areas using the cosmic-ray rover. In 2012, soil moisture was mapped 22 times in a 25 km × 40 km survey area of the Tucson Basin at an average of 1.7 km2 resolution, i.e., a survey area extent comparable to that of a pixel for the Soil Moisture and Ocean Salinity (SMOS) satellite mission. The soil moisture distribution is dominated by climatic variations, notably by the North American monsoon, that results in a systematic increase in the standard deviation, observed up to 0.022 m3 m−3, as a function of the mean, between 0.06 m3 m−3 and 0.14 m3 m−3. Two techniques are explored to use the cosmic-ray rover data for hydrologic applications: (1) interpolation of the 22 surveys into a daily soil moisture product by defining an approach to utilize and quantify the observed temporal stability producing an average correlation coefficient of 0.82 for the soil moisture distributions that were surveyed, and (2) estimation of soil moisture profiles by combining surface moisture from satellite microwave sensors (SMOS) with deeper measurements from the cosmic-ray rover. The interpolated soil moisture and soil moisture profiles allow for basin-wide mass balance calculation of evapotranspiration, which amounted to 241 mm in 2012. Generating soil moisture maps with a cosmic-ray rover at this intermediate scale may help in the calibration and validation of satellite soil moisture data products and may also aid in various large-scale hydrologic studies.
Highlights
Quantifying area-average soil moisture at the mesoscale (2– 1000 km) is difficult because of the footprint or support volume (Western and Bloschl, 1999; Robinson et al, 2008) of current measurement methods
The surveys were conducted each month throughout the year, but once a week during the monsoon season (July–September) in order to capture the increased soil moisture dynamics associated with the increased precipitation in this season
We attempt to link these patterns to daily observations in order to predict the behavior between surveys. This time-interpolation involves major assumptions, increasing the level of uncertainty of these results beyond errors implicit in the data. We think it worthwhile to provide these exploratory results for the purpose of demonstrating potential applications of the cosmic-ray rover; they are likely to improve when using alternative techniques to quantify the evolution of the daily soil moisture distribution with time
Summary
Quantifying area-average soil moisture at the mesoscale (2– 1000 km) is difficult because of the footprint or support volume (Western and Bloschl, 1999; Robinson et al, 2008) of current measurement methods. In situ point measurements have very small support volumes (e.g., Robinson et al, 2008) that are likely not representative of the surrounding area (Zreda et al, 2012). There is a gap in observational methods for measuring soil moisture at intermediate scales between point measurements and satellites pixels. This has stimulated research into area-average soil moisture monitoring using GPS surface feedbacks (Larson et al, 2008), distributed sensor networks (Bogena et al, 2010), and cosmicray neutron monitoring (Zreda et al, 2008, 2012). Distributed sensor networks may have a relatively small footprint if they are installed over a small area and, if they are widely spaced, they act as point measurements, not necessarily representative of a study area
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