Jérôme Demarty

Contribution of Thermal Infrared Remote Sensing Data in Multiobjective Calibration of a Dual-Source SVAT Model

Abstract This study fits within the overall research on the usage of space remote sensing data to constrain land surface models (LSMs) (also called SVAT models for soil–vegetation–atmosphere transfer). The goal of this paper is to analyze the potential of using thermal infrared (TIR) remote sensing data for LSM calibration. LSMs are characterized by a large number of parameters and initial conditions that have to be specified. This model calibration is generally performed at a local scale by minimization between measurements and time series difference. Recent studies have shed light on the use of multiobjective approaches for performing calibration and for analyzing the model’s sensitivity to input parameters. Such an approach has been implemented in the SEtHyS LSM (for “Suivi de l’Etat Hydrique des Sols,” the French acronym for soil moisture monitoring) with the objective of assessing the information contributed by having knowledge of the remote sensing surface brightness temperature. For this purpose, t...

Modeling Surface Runoff and Water Fluxes over Contrasted Soils in the Pastoral Sahel: Evaluation of the ALMIP2 Land Surface Models over the Gourma Region in Mali

AbstractLand surface processes play an important role in the West African monsoon variability. In addition, the evolution of hydrological systems in this region, and particularly the increase of surface water and runoff coefficients observed since the 1950s, has had a strong impact on water resources and on the occurrence of floods events. This study addresses results from phase 2 of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project (ALMIP2), carried out to evaluate the capability of different state-of-the-art land surface models to reproduce surface processes at the mesoscale. Evaluation of runoff and water fluxes over the Mali site is carried out through comparison with runoff estimations over endorheic watersheds as well as evapotranspiration (ET) measurements. Three remote-sensing-based ET products [ALEXI, MODIS, and Global Land Evaporation Amsterdam Model (GLEAM)] are also analyzed. It is found that, over deep sandy soils, surface runoff is generally ove...

Comparison of measured and SISPAT-RS simulated brightness temperatures and reflectances at field scale during ReSeDA experiment

The Simple Soil-Plant-Atmosphere Transfer - Remote Sensing (SiSPAT-RS) model was developed to simulate soil-vegetation-atmosphere energy and water transfers as well as remote sensing measurements at field scale, in the visible and thermal infrared domains. This model has been validated on the Alpilles-ReSeDA (Remote Sensing Data Assimilation) experimental database gathering micrometeorological data and remote sensing observations. Sensitivity and uncertainty studies were performed with the SVAT model and the radiative transfer models using stochastic technics like Monte Carlos methods. The results permit us to quantify the model uncertainties linked to parameters and initial conditions uncertainties, such information which is essential to carry on assimilation studies. Here, we present the results concerning the sensitivity analysis and the results of the calibration on an experimental agricultural field of ReSeDA experiment.