Articles | Volume 18, issue 12
Hydrol. Earth Syst. Sci., 18, 5219–5237, 2014
Hydrol. Earth Syst. Sci., 18, 5219–5237, 2014

Research article 16 Dec 2014

Research article | 16 Dec 2014

Agro-hydrology and multi-temporal high-resolution remote sensing: toward an explicit spatial processes calibration

S. Ferrant1,2, S. Gascoin1,3, A. Veloso1,3, J. Salmon-Monviola4,5, M. Claverie6,7, V. Rivalland1,3, G. Dedieu1,2, V. Demarez1, E. Ceschia1, J.-L. Probst8,9, P. Durand4,5, and V. Bustillo1 S. Ferrant et al.
  • 1Université de Toulouse, UPS, Centre d'Etude Spatiale de la BIOsphère (CESBIO), 18 av. Edouard Belin, bpi 2801, 31401 Toulouse, Cedex 9, France
  • 2Centre National d'Etudes Spatiales (CNES), CESBIO, Toulouse, France
  • 3CNRS-CESBIO, Toulouse, France
  • 4INRA – UMR1069 Sol Agro et hydrosystème Spatialisation (SAS), 35000 Rennes, France
  • 5Agrocampus Ouest, UMR1069, SAS, 35000 Rennes, France
  • 6Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
  • 7NASA-Goddard Space Flight Center, Greenbelt, MD 20771, USA
  • 8Université de Toulouse, UPS, INPT, Laboratoire d'Ecologie Fonctionnelle et Environnement (EcoLab), ENSAT, Avenue de l'Agrobiopole, BP 32607 Auzeville-Tolosane, 31326 Castanet-Tolosan Cedex, France
  • 9CNRS, Ecolab, ENSAT, Avenue de l'Agrobiopole, Castanet, France

Abstract. The growing availability of high-resolution satellite image series offers new opportunities in agro-hydrological research and modeling. We investigated the possibilities offered for improving crop-growth dynamic simulation with the distributed agro-hydrological model: topography-based nitrogen transfer and transformation (TNT2). We used a leaf area index (LAI) map series derived from 105 Formosat-2 (F2) images covering the period 2006–2010. The TNT2 model (Beaujouan et al., 2002), calibrated against discharge and in-stream nitrate fluxes for the period 1985–2001, was tested on the 2005–2010 data set (climate, land use, agricultural practices, and discharge and nitrate fluxes at the outlet). Data from the first year (2005) were used to initialize the hydrological model. A priori agricultural practices obtained from an extensive field survey, such as seeding date, crop cultivar, and amount of fertilizer, were used as input variables. Continuous values of LAI as a function of cumulative daily temperature were obtained at the crop-field level by fitting a double logistic equation against discrete satellite-derived LAI. Model predictions of LAI dynamics using the a priori input parameters displayed temporal shifts from those observed LAI profiles that are irregularly distributed in space (between field crops) and time (between years). By resetting the seeding date at the crop-field level, we have developed an optimization method designed to efficiently minimize this temporal shift and better fit the crop growth against both the spatial observations and crop production. This optimization of simulated LAI has a negligible impact on water budgets at the catchment scale (1 mm yr−1 on average) but a noticeable impact on in-stream nitrogen fluxes (around 12%), which is of interest when considering nitrate stream contamination issues and the objectives of TNT2 modeling. This study demonstrates the potential contribution of the forthcoming high spatial and temporal resolution products from the Sentinel-2 satellite mission for improving agro-hydrological modeling by constraining the spatial representation of crop productivity.

Short summary
A set of high spatial and temporal satellite images have been used to spatially calibrate crop growth within an agro-hydrological model dedicated to nitrogen contamination of stream water. This type of spatial calibration greatly improved the simulation of nitrogen plant uptake and better constrained nutrient fluxes in the river. This is an example of the benefit of the forthcoming Sentinel-2 high resolution optical image series that will be acquired every 4/5 days over continental surfaces.