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Hydrology 2018, 5(3), 36; https://doi.org/10.3390/hydrology5030036

Indications of Surface and Sub-Surface Hydrologic Properties from SMAP Soil Moisture Retrievals

1
Center for Ocean-Land-Atmosphere Studies, George Mason University, 4400 University Drive, Mail Stop 6C5, Fairfax, VA 22030, USA
2
I.M. Systems Group Inc., NOAA/NCEP/EMC, NOAA Center for Weather and Climate Prediction, 5830 University Research Court, College Park, MD 20740, USA
*
Author to whom correspondence should be addressed.
Received: 30 June 2018 / Revised: 22 July 2018 / Accepted: 23 July 2018 / Published: 25 July 2018
(This article belongs to the Special Issue Remote Sensing in Hydrological Modelling)
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Abstract

Variability and covariability of land properties (soil, vegetation and subsurface geology) and remotely sensed soil moisture over the southeast and south-central U.S. are assessed. The goal is to determine whether satellite soil moisture memory contains information regarding land properties, especially the distribution karst formations below the active soil column that have a bearing on land-atmosphere feedbacks. Local (within a few tens of km) statistics of land states and soil moisture are considered to minimize the impact of climatic variations, and the local statistics are then correlated across the domain to illuminate significant relationships. There is a clear correspondence between soil moisture memory and many land properties including karst distribution. This has implications for distributed land surface modeling, which has not considered preferential water flows through geologic formations. All correspondences are found to be strongest during spring and fall, and weak during summer, when atmospheric moisture demand appears to dominate soil moisture variability. While there are significant relationships between remotely-sensed soil moisture variability and land properties, it will be a challenge to use satellite data for terrestrial parameter estimation as there is often a great deal of correlation among soil, vegetation and karst property distributions. View Full-Text
Keywords: soil moisture; remote sensing; karst; soil properties; vegetation properties soil moisture; remote sensing; karst; soil properties; vegetation properties
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Dirmeyer, P.A.; Norton, H.E. Indications of Surface and Sub-Surface Hydrologic Properties from SMAP Soil Moisture Retrievals. Hydrology 2018, 5, 36.

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