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Remote Sens. 2016, 8(2), 154; doi:10.3390/rs8020154

Extracting Soil Water Holding Capacity Parameters of a Distributed Agro-Hydrological Model from High Resolution Optical Satellite Observations Series

1
Centre d’Etudes Spatiales de la BIOsphère (CESBIO), Université Toulouse III Paul Sabatier, 18 Avenue Edouard Belin, 31401 Toulouse, France
2
Centre National d’Etudes Spatiales (CNES), CESBIO, 31401 Toulouse, France
3
IUT “A” Paul Sabatier, site d’Auch, 24 rue d’Embaquès, 32000 Auch, France
4
INRA—UMR1069 Sol Agro et hydrosystème Spatialisation (SAS), 35000 Rennes, France
5
Agrocampus Ouest, UMR1069, SAS, 35000 Rennes, France
6
Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
7
NASA, Goddard Space Flight Center, Greenbelt, MD 20771, USA
8
CNRS, CESBIO, 31401 Toulouse, France
9
Laboratoire Ecologie Fonctionnelle et Environnement (EcoLab), Université de Toulouse, UPS, INPT, Avenue de l’Agrobiopole, BP 32607 Auzeville-Tolosane, 31326 Castanet-Tolosan Cedex, France
10
CNRS-Ecolab, ENSAT, Avenue de l’Agrobiopole, 31326 Castanet-Tolosan Cedex, France
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Academic Editors: Mutlu Ozdogan, Yoshio Inoue and Prasad S. Thenkabail
Received: 12 October 2015 / Revised: 21 January 2016 / Accepted: 25 January 2016 / Published: 17 February 2016
(This article belongs to the Special Issue Remote Sensing in Precision Agriculture)
View Full-Text   |   Download PDF [6414 KB, uploaded 17 February 2016]   |  

Abstract

Sentinel-2 (S2) earth observation satellite mission, launched in 2015, is foreseen to promote within-field decisions in Precision Agriculture (PA) for both: (1) optimizing crop production; and (2) regulating environmental impacts. In this second scope, a set of Leaf Area Index (LAI) derived from S2 type time-series (2006–2010, using Formosat-2 satellite) is used to spatially constrain the within-field crop growth and the related nitrogen contamination of surface water simulated at a small experimental catchment scale with the distributed agro-hydrological model Topography Nitrogen Transfer and Transformation (TNT2). The Soil Water Holding Capacity (SWHC), represented by two parameters, soil depth and retention porosity, is used to fit the yearly maximum of LAI (LAX) at each pixel of the satellite image. Possible combinations of soil parameters, defining 154 realistic SWHC found on the study site are used to force spatially homogeneous SWHC. LAX simulated at the pixel level for the 154 SWHC, for each of the five years of the study period, are recorded and hereafter referred to as synthetic LAX. Optimal SWHCyear_I,pixel_j, corresponding to minimal difference between observed and synthetic LAXyear_I,pixel_j, is selected for each pixel, independent of the value at neighboring pixels. Each re-estimated soil maps are used to re-simulate LAXyear_I. Results show that simulated and synthetic LAXyear_I,allpixels obtained from SWHCyear_I,allpixels are close and accurately fit the observed LAXyear_I,allpixels (RMSE = 0.05 m2/m2 to 0.2 and R2 = 0.99 to 0.94), except for the year 2008 (RMSE = 0.8 m2/m2 and R2 = 0.8). These results show that optimal SWHC can be derived from remote sensing series for one year. Unique SWHC solutions for each pixel that limit the LAX error for the five years to less than 0.2 m2/m2 are found for only 10% of the pixels. Selection of unique soil parameters using multi-year LAX and neighborhood solution is expected to deliver more robust soil parameters solutions and need to be assessed further. The use of optical remote sensing series is then a promising calibration step to represent crop growth within crop field at catchment level. Nevertheless, this study discusses the model and data improvements that are needed to get realistic spatial representation of agro-hydrological processes simulated within catchments. View Full-Text
Keywords: nitrate contamination; nitrogen excess; agro-hydrological model; spatial calibration; soil water holding capacity; leaf area index; Formosat-2 time series; Sentinel-2 type time series nitrate contamination; nitrogen excess; agro-hydrological model; spatial calibration; soil water holding capacity; leaf area index; Formosat-2 time series; Sentinel-2 type time series
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ferrant, S.; Bustillo, V.; Burel, E.; Salmon-Monviola, J.; Claverie, M.; Jarosz, N.; Yin, T.; Rivalland, V.; Dedieu, G.; Demarez, V.; Ceschia, E.; Probst, A.; Al-Bitar, A.; Kerr, Y.; Probst, J.-L.; Durand, P.; Gascoin, S. Extracting Soil Water Holding Capacity Parameters of a Distributed Agro-Hydrological Model from High Resolution Optical Satellite Observations Series. Remote Sens. 2016, 8, 154.

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