Developing and evaluating national soil moisture percentile maps
2020
Zhao, Chen | Quiring, Steven M. | Yuan, Shanshui | McRoberts, Douglas Brent | Zhang, Ning | Leasor, Zachary
Soil moisture is an integral part of the climate system. There are numerous monitoring networks operated by state and federal agencies that provide real‐time soil moisture measurements in the United States. These measurements have value for a variety of applications, such as operational drought monitoring. This paper describes the methods that are used to collect and quality control soil moisture measurements from multiple networks, to convert volumetric water content to soil moisture percentiles, and to interpolate these data to a national 4‐km grid in the contiguous United States. The accuracy of three interpolation methods (inverse distance weighting [IDW], ordinary kriging [OK], and regression kriging [RK]) is evaluated, and we conclude that RK provides the most accurate approach for producing national soil moisture percentile maps. At 5 cm, the 12‐yr mean absolute error (MAE) for RK of the soil moisture percentiles is 0.17, followed by OK (0.19) and IDW (0.27). At 20 cm, the MAEs for RK, OK, and IDW are 0.18, 0.19 and 0.26, respectively. Two case studies, the 2011 drought and the 2015 summer floods in Oklahoma and West Texas, were used to demonstrate the utility of these soil moisture percentile maps.
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