Using a multiobjective approach to retrieve information on surface properties used in a SVAT model

J. Demarty, C. Ottlé, I. Braud, A. Olioso, J. P. Frangi, L. A. Bastidas, Hoshin Vijai Gupta

Research output: Contribution to journalArticle

46 Citations (Scopus)

Abstract

The reliability of model predictions used in meteorology, agronomy or hydrology is partly linked to an adequate representation of the water and energy balances which are described in so-called SVAT (Soil Vegetation Atmosphere Transfer) models. These models require the specification of many surface properties which can generally be obtained from laboratory or field experiments, using time consuming techniques, or can be derived from textural information. The required accuracy of the surface properties depends on the model complexity and their misspecification can affect model performance. At various time and spatial resolutions, remote sensing provides information related to surface parameters in SVAT models or state variables simulated by SVAT models. In this context, the Simple Soil-Plant-Atmosphere Transfer-Remote Sensing (SiSPAT-RS) model was developed for remote sensing data assimilation objectives. This new version of the physically based SiSPAT model simulates the main surface processes (energy fluxes, soil water content profiles, temperatures) and remote sensing data in the visible, infrared and thermal infrared spectral domains. As a preliminary step before data assimilation in the model, the objectives of this study were (1) to apply a multiobjective approach for retrieving quantitative information about the surface properties from different surface measurements and (2) to determine the potential of the SiSPAT-RS model to be applied with 'little' a priori information about input parameters. To reach these goals, the ability of the Multiobjective Generalized Sensitivity Analysis (MOGSA) algorithm to determine and quantify the most influential input parameters of the SiSPAT-RS model on several simulated output variables, was investigated. The results revealed the main influential input parameters according to different contrasted environmental conditions, and contributed to the reduction of their a priori uncertainty range. A procedure for specifying surface properties from MOGSA results was tested on the thermal and hydraulic soil parameters, and evaluated through the SiSPAT-RS model performance. Although slightly lower than a reference simulation, the performance were satisfactory and suggested that complex SVAT models can be driven with little a priori information on soil properties, as in a future context of remote sensing data assimilation. Measurement acquired on a winter wheat field of the ReSeDA (Remote Sensing Data Assimilation) experiment were used in this study.

Original languageEnglish (US)
Pages (from-to)214-236
Number of pages23
JournalJournal of Hydrology
Volume287
Issue number1-4
DOIs
StatePublished - Feb 25 2004

Fingerprint

Soil Vegetation Atmosphere Transfer models
remote sensing
atmosphere
vegetation
soil
data assimilation
heat
process energy
sensitivity analysis
agronomy
water balance
temperature profiles
hydrology
energy balance
winter wheat
soil water content
soil properties
fluid mechanics
uncertainty

Keywords

  • Multiobjective generalized sensitivity analysis algorithm
  • Multiobjective sensitivity analysis
  • Remote sensing data assimilation
  • ReSeDA experiment
  • Simple soil-plant-atmosphere transfer-remote sensing model
  • Soil vegetation atmosphere transfer models

ASJC Scopus subject areas

  • Soil Science
  • Earth-Surface Processes

Cite this

Using a multiobjective approach to retrieve information on surface properties used in a SVAT model. / Demarty, J.; Ottlé, C.; Braud, I.; Olioso, A.; Frangi, J. P.; Bastidas, L. A.; Gupta, Hoshin Vijai.

In: Journal of Hydrology, Vol. 287, No. 1-4, 25.02.2004, p. 214-236.

Research output: Contribution to journalArticle

Demarty, J. ; Ottlé, C. ; Braud, I. ; Olioso, A. ; Frangi, J. P. ; Bastidas, L. A. ; Gupta, Hoshin Vijai. / Using a multiobjective approach to retrieve information on surface properties used in a SVAT model. In: Journal of Hydrology. 2004 ; Vol. 287, No. 1-4. pp. 214-236.
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