Next Article in Journal
A Time Series Model Comparison for Monitoring and Forecasting Water Quality Variables
Next Article in Special Issue
Mitigating Spatial Discontinuity of Multi-Radar QPE Based on GPM/KuPR
Previous Article in Journal
Seasonal and Basinal Influences on the Formation and Transport of Dissolved Trace Metal Forms in a Mining-Impacted Riverine Environment
Previous Article in Special Issue
Analysing the Potential of OpenStreetMap Data to Improve the Accuracy of SRTM 30 DEM on Derived Basin Delineation, Slope, and Drainage Networks
Article Menu

Export Article

Open AccessArticle
Hydrology 2018, 5(3), 36;

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

Center for Ocean-Land-Atmosphere Studies, George Mason University, 4400 University Drive, Mail Stop 6C5, Fairfax, VA 22030, USA
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)
Full-Text   |   PDF [4788 KB, uploaded 25 July 2018]   |  


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

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Dirmeyer, P.A.; Norton, H.E. Indications of Surface and Sub-Surface Hydrologic Properties from SMAP Soil Moisture Retrievals. Hydrology 2018, 5, 36.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics



[Return to top]
Hydrology EISSN 2306-5338 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top