Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness Temperatures
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 eva...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | Vadose Zone Journal |
| Online Access: | https://doi.org/10.2136/vzj2013.04.0075 |
| _version_ | 1797771585724088320 |
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| author | M. Dimitrov J. Vanderborght K. G. Kostov K. Z. Jadoon L. Weihermüller T. J. Jackson R. Bindlish Y. Pachepsky M. Schwank H. Vereecken |
| author_facet | M. Dimitrov J. Vanderborght K. G. Kostov K. Z. Jadoon L. Weihermüller T. J. Jackson R. Bindlish Y. Pachepsky M. Schwank H. Vereecken |
| author_sort | M. Dimitrov |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-12T21:38:42Z |
| format | Article |
| id | doaj.art-ae5cb032723942cdaac1bc6979b9ecc1 |
| institution | Directory Open Access Journal |
| issn | 1539-1663 |
| language | English |
| last_indexed | 2024-03-12T21:38:42Z |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Vadose Zone Journal |
| spelling | doaj.art-ae5cb032723942cdaac1bc6979b9ecc12023-07-27T05:56:47ZengWileyVadose Zone Journal1539-16632014-01-0113111810.2136/vzj2013.04.0075Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness TemperaturesM. Dimitrov0J. Vanderborght1K. G. Kostov2K. Z. Jadoon3L. Weihermüller4T. J. Jackson5R. Bindlish6Y. Pachepsky7M. Schwank8H. Vereecken9Research Centre JülichInstitute of Bio‐ and Geosciences: Agrosphere (IBG 3)Jülich52425GermanyResearch Centre JülichInstitute of Bio‐ and Geosciences: Agrosphere (IBG 3)Jülich52425GermanyBulgarian Academy of SciencesInstitute of ElectronicsSofia1784BulgariaResearch Centre JülichInstitute of Bio‐ and Geosciences: Agrosphere (IBG 3)Jülich52425GermanyResearch Centre JülichInstitute of Bio‐ and Geosciences: Agrosphere (IBG 3)Jülich52425GermanyUSDA‐ARSHydrology and Remote Sensing Lab.BeltsvilleMD20705‐2350USDA‐ARSHydrology and Remote Sensing Lab.BeltsvilleMD20705‐2350USDA‐ARSEnvironmental Microbial and Food Safety Lab.BeltsvilleMD20705‐2350Swiss Federal Institute WSLMountain Hydrology and TorrentsZürcherstrasse 1118903BirmensdorfSwitzerlandResearch Centre JülichInstitute of Bio‐ and Geosciences: Agrosphere (IBG 3)Jülich52425GermanyWe 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.https://doi.org/10.2136/vzj2013.04.0075 |
| spellingShingle | M. Dimitrov J. Vanderborght K. G. Kostov K. Z. Jadoon L. Weihermüller T. J. Jackson R. Bindlish Y. Pachepsky M. Schwank H. Vereecken Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness Temperatures Vadose Zone Journal |
| title | Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness Temperatures |
| title_full | Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness Temperatures |
| title_fullStr | Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness Temperatures |
| title_full_unstemmed | Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness Temperatures |
| title_short | Soil Hydraulic Parameters and Surface Soil Moisture of a Tilled Bare Soil Plot Inversely Derived from L‐Band Brightness Temperatures |
| title_sort | soil hydraulic parameters and surface soil moisture of a tilled bare soil plot inversely derived from l band brightness temperatures |
| url | https://doi.org/10.2136/vzj2013.04.0075 |
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