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Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part II: integration of remote sensing and hydrologic modeling

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Abstract
In most hydrologic modeling studies, the hypothesis is made that an improvement in the modeled soil moisture leads to an improvement in the modeled surface energy balance. The objective of this paper is to assess whether this hypothesis is true. The study was performed over the winter wheat fields in the AgriSAR 2006 domain. Remotely sensed soil moisture values and latent heat fluxes were used, in combination with in situ observations. First, the land cover and saturated subsurface flow parameters were estimated using the in situ observations. A spatially distributed model simulation was then performed, for which the Brooks–Corey parameters were derived from a soil texture map, and of which the results were validated using the remote sensing data. The remotely sensed soil moisture values were then used to optimize the Brooks–Corey parameters. As expected, a better performance with respect to the soil moisture estimation was obtained. However, this did not improve the latent heat flux estimates. This can be explained by the consumption of water from the deeper soil layers by the vegetation. The overall conclusion is that, under conditions where evapotranspiration is limited by energy and not by the soil moisture content, surface soil moisture values alone are not sufficient for the optimization of hydrologic model results. More data sets are needed for this purpose.
Keywords
parameter estimation., inverse problems, soil moisture, hydrology, numerical models, Mathematical programming, ATMOSPHERE TRANSFER SCHEME, SOIL-MOISTURE RETRIEVAL, BALANCE PROCESSES, MULTIOBJECTIVE CALIBRATION, PARAMETER-ESTIMATION, FLUX ESTIMATION, VARIABLE WATER, VEGETATION, ASSIMILATION, TEMPERATURE

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Citation

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Chicago
De Lathauwer, Els, Wim Timmermans, Giuseppe Satalino, Francesco Mattia, Alexander Loew, Juan-Carlos Jiménez-Muñoz, Victoria Hidalgo, José Antonio Sobrino, and Valentijn Pauwels. 2011. “Estimation of the Spatially Distributed Surface Energy Budget for AgriSAR 2006, Part II: Integration of Remote Sensing and Hydrologic Modeling.” Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4 (2): 482–493.
APA
De Lathauwer, E., Timmermans, W., Satalino, G., Mattia, F., Loew, A., Jiménez-Muñoz, J.-C., Hidalgo, V., et al. (2011). Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part II: integration of remote sensing and hydrologic modeling. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 4(2), 482–493. Presented at the 5th International workshop on Multi-Temporal Imagery Analysis.
Vancouver
1.
De Lathauwer E, Timmermans W, Satalino G, Mattia F, Loew A, Jiménez-Muñoz J-C, et al. Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part II: integration of remote sensing and hydrologic modeling. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. 2011;4(2):482–93.
MLA
De Lathauwer, Els, Wim Timmermans, Giuseppe Satalino, et al. “Estimation of the Spatially Distributed Surface Energy Budget for AgriSAR 2006, Part II: Integration of Remote Sensing and Hydrologic Modeling.” IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 4.2 (2011): 482–493. Print.
@article{1229077,
  abstract     = {In most hydrologic modeling studies, the hypothesis is made that an improvement in the modeled soil moisture leads to an improvement in the modeled surface energy balance. The objective of this paper is to assess whether this hypothesis is true. The study was performed over the winter wheat fields in the AgriSAR 2006 domain. Remotely sensed soil moisture values and latent heat fluxes were used, in combination with in situ observations. First, the land cover and saturated subsurface flow parameters were estimated using the in situ observations. A spatially distributed model simulation was then performed, for which the Brooks--Corey parameters were derived from a soil texture map, and of which the results were validated using the remote sensing data. The remotely sensed soil moisture values were then used to optimize the Brooks--Corey parameters. As expected, a better performance with respect to the soil moisture estimation was obtained. However, this did not improve the latent heat flux estimates. This can be explained by the consumption of water from the deeper soil layers by the vegetation. The overall conclusion is that, under conditions where evapotranspiration is limited by energy and not by the soil moisture content, surface soil moisture values alone are not sufficient for the optimization of hydrologic model results. More data sets are needed for this purpose.},
  author       = {De Lathauwer, Els and Timmermans, Wim and Satalino, Giuseppe and Mattia, Francesco and Loew, Alexander and Jim{\'e}nez-Mu{\~n}oz, Juan-Carlos and Hidalgo, Victoria and Sobrino, Jos{\'e} Antonio and Pauwels, Valentijn},
  issn         = {1939-1404},
  journal      = {IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING},
  keyword      = {parameter estimation.,inverse problems,soil moisture,hydrology,numerical models,Mathematical programming,ATMOSPHERE TRANSFER SCHEME,SOIL-MOISTURE RETRIEVAL,BALANCE PROCESSES,MULTIOBJECTIVE CALIBRATION,PARAMETER-ESTIMATION,FLUX ESTIMATION,VARIABLE WATER,VEGETATION,ASSIMILATION,TEMPERATURE},
  language     = {eng},
  location     = {Storrs, CT, USA},
  number       = {2},
  pages        = {482--493},
  title        = {Estimation of the spatially distributed surface energy budget for AgriSAR 2006, part II: integration of remote sensing and hydrologic modeling},
  url          = {http://dx.doi.org/10.1109/JSTARS.2010.2094997},
  volume       = {4},
  year         = {2011},
}

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