Soil hydraulic parameters and surface soil moisture of a tilled bare soil plot inversely derived from l-band brightness temperatures

Handle URI:
http://hdl.handle.net/10754/563172
Title:
Soil hydraulic parameters and surface soil moisture of a tilled bare soil plot inversely derived from l-band brightness temperatures
Authors:
Dimitrov, Marin; Vanderborght, Jan P.; Kostov, K. G.; Jadoon, Khan; Weihermüller, Lutz; Jackson, Thomas J.; Bindlish, Rajat; Pachepsky, Ya A.; Schwank, Mike; Vereecken, Harry
Abstract:
We coupled a radiative transfer model and a soil hydrologic model (HYDRUS 1D) with an optimization routine to derive soil hydraulic parameters, surface roughness, and soil moisture of a tilled bare soil plot using measured brightness temperatures at 1.4 GHz (L-band), rainfall, and potential soil evaporation. The robustness of the approach was evaluated using five 28-d data sets representing different meteorological conditions. We considered two soil hydraulic property models: the unimodal Mualem-van Genuchten and the bimodal model of Durner. Microwave radiative transfer was modeled by three different approaches: the Fresnel equation with depth-averaged dielectric permittivity of either 2-or 5-cm-thick surface layers and a coherent radiative transfer model (CRTM) that accounts for vertical gradients in dielectric permittivity. Brightness temperatures simulated by the CRTM and the 2-cm-layer Fresnel model fitted well to the measured ones. L-band brightness temperatures are therefore related to the dielectric permittivity and soil moisture in a 2-cm-thick surface layer. The surface roughness parameter that was derived from brightness temperatures using inverse modeling was similar to direct estimates from laser profiler measurements. The laboratory-derived water retention curve was bimodal and could be retrieved consistently for the different periods from brightness temperatures using inverse modeling. A unimodal soil hydraulic property function underestimated the hydraulic conductivity near saturation. Surface soil moisture contents simulated using retrieved soil hydraulic parameters were compared with in situ measurements. Depth-specific calibration relations were essential to derive soil moisture from near-surface installed sensors. © Soil Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA.
KAUST Department:
Water Desalination and Reuse Research Center (WDRC); Water Desalination and Reuse Research Center
Publisher:
Soil Science Society of America
Journal:
Vadose Zone Journal
Issue Date:
2014
DOI:
10.2136/vzj2013.04.0075
Type:
Article
ISSN:
15391663
Sponsors:
This study is a part of the research unit FOR 1083 MUSIS (Multi-Scale Interfaces in Unsaturated Soil) funded by the German Research Foundation (DFG). We thank Prof. Dr. P.-S. Lammers and Dr. Lutz Damerow (Institute of Agriculture Engineering) for providing the laser profiler. We thank the team of H. Jagdfeld (Central Institute of Technology, Research Centre Julich) for the development of the holding construction of the radiometer; the team of A. Egmen and D. Schnabel (technician workshop of IBG, Research Centre Julich) for building the holding construction of the radiometer. We thank C. Steenpass, Dr. U. Rosenbaum, and Dr. F. Jonard for support during the development of the inversion approach. We thank the technician staff of the Agrosphere Institute, especially R. Harms and F. Engels, for technical support during the measurements; A. Langen for laboratory measurements of the soil hydraulic properties, and N. Hermes for the logging software for the radiometer data. M. Dimitrov thanks Dr. S. Huisman, Dr. A. Graf, Dr. J. Bikowski, Dr. I. Mladenova and Dr. Th. Holmes for all of the consultations and the model improvement. The USDA is an equal opportunity provider and employer.
Appears in Collections:
Articles; Water Desalination and Reuse Research Center (WDRC)

Full metadata record

DC FieldValue Language
dc.contributor.authorDimitrov, Marinen
dc.contributor.authorVanderborght, Jan P.en
dc.contributor.authorKostov, K. G.en
dc.contributor.authorJadoon, Khanen
dc.contributor.authorWeihermüller, Lutzen
dc.contributor.authorJackson, Thomas J.en
dc.contributor.authorBindlish, Rajaten
dc.contributor.authorPachepsky, Ya A.en
dc.contributor.authorSchwank, Mikeen
dc.contributor.authorVereecken, Harryen
dc.date.accessioned2015-08-03T11:37:26Zen
dc.date.available2015-08-03T11:37:26Zen
dc.date.issued2014en
dc.identifier.issn15391663en
dc.identifier.doi10.2136/vzj2013.04.0075en
dc.identifier.urihttp://hdl.handle.net/10754/563172en
dc.description.abstractWe coupled a radiative transfer model and a soil hydrologic model (HYDRUS 1D) with an optimization routine to derive soil hydraulic parameters, surface roughness, and soil moisture of a tilled bare soil plot using measured brightness temperatures at 1.4 GHz (L-band), rainfall, and potential soil evaporation. The robustness of the approach was evaluated using five 28-d data sets representing different meteorological conditions. We considered two soil hydraulic property models: the unimodal Mualem-van Genuchten and the bimodal model of Durner. Microwave radiative transfer was modeled by three different approaches: the Fresnel equation with depth-averaged dielectric permittivity of either 2-or 5-cm-thick surface layers and a coherent radiative transfer model (CRTM) that accounts for vertical gradients in dielectric permittivity. Brightness temperatures simulated by the CRTM and the 2-cm-layer Fresnel model fitted well to the measured ones. L-band brightness temperatures are therefore related to the dielectric permittivity and soil moisture in a 2-cm-thick surface layer. The surface roughness parameter that was derived from brightness temperatures using inverse modeling was similar to direct estimates from laser profiler measurements. The laboratory-derived water retention curve was bimodal and could be retrieved consistently for the different periods from brightness temperatures using inverse modeling. A unimodal soil hydraulic property function underestimated the hydraulic conductivity near saturation. Surface soil moisture contents simulated using retrieved soil hydraulic parameters were compared with in situ measurements. Depth-specific calibration relations were essential to derive soil moisture from near-surface installed sensors. © Soil Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA.en
dc.description.sponsorshipThis study is a part of the research unit FOR 1083 MUSIS (Multi-Scale Interfaces in Unsaturated Soil) funded by the German Research Foundation (DFG). We thank Prof. Dr. P.-S. Lammers and Dr. Lutz Damerow (Institute of Agriculture Engineering) for providing the laser profiler. We thank the team of H. Jagdfeld (Central Institute of Technology, Research Centre Julich) for the development of the holding construction of the radiometer; the team of A. Egmen and D. Schnabel (technician workshop of IBG, Research Centre Julich) for building the holding construction of the radiometer. We thank C. Steenpass, Dr. U. Rosenbaum, and Dr. F. Jonard for support during the development of the inversion approach. We thank the technician staff of the Agrosphere Institute, especially R. Harms and F. Engels, for technical support during the measurements; A. Langen for laboratory measurements of the soil hydraulic properties, and N. Hermes for the logging software for the radiometer data. M. Dimitrov thanks Dr. S. Huisman, Dr. A. Graf, Dr. J. Bikowski, Dr. I. Mladenova and Dr. Th. Holmes for all of the consultations and the model improvement. The USDA is an equal opportunity provider and employer.en
dc.publisherSoil Science Society of Americaen
dc.titleSoil hydraulic parameters and surface soil moisture of a tilled bare soil plot inversely derived from l-band brightness temperaturesen
dc.typeArticleen
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)en
dc.contributor.departmentWater Desalination and Reuse Research Centeren
dc.identifier.journalVadose Zone Journalen
dc.contributor.institutionResearch Centre Jülich, Institute of Bio and Geosciences: Agrosphere (IBG 3), Jülich 52425, Germanyen
dc.contributor.institutionBulgarian Academy of Sciences, Institute of Electronics, Sofia 1784, Bulgariaen
dc.contributor.institutionUSDA-ARS, Hydrology and Remote Sensing Lab, Beltsville, MD 20705-2350, United Statesen
dc.contributor.institutionUSDA-ARS, Environmental Microbial and Food Safety Lab, Beltsville, MD 20705-2350, United Statesen
dc.contributor.institutionSwiss Federal Institute WSL, Mountain Hydrology and Torrents, Zürcherstrasse 111, 8903 Birmensdorf, Switzerlanden
dc.contributor.institutionGamma Remote Sensing AG, Worbstrasse 225, 3073 Gümligen, Switzerlanden
kaust.authorJadoon, Khanen
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