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

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.

[1]  W. Verhoef,et al.  PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .

[2]  Peter Droogers,et al.  Calibration of a distributed hydrological model based on satellite evapotranspiration , 2008 .

[3]  S. Birkinshaw,et al.  Nitrogen transformation component for SHETRAN catchment nitrate transport modelling , 2000 .

[4]  Pamela L. Nagler.  The role of remote sensing observations and models in hydrology: the science of evapotranspiration† , 2011 .

[5]  Keith Beven,et al.  Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology , 2001 .

[6]  Elizabeth Pattey,et al.  Using Leaf Area Index, retrieved from optical imagery, in the STICS crop model for predicting yield and biomass of field crops , 2012 .

[7]  J. Maréchal,et al.  Projected impacts of climate change on farmers' extraction of groundwater from crystalline aquifers in South India , 2014, Scientific reports.

[8]  Martin Volk,et al.  Towards the implementation of the European Water Framework Directive?: Lessons learned from water quality simulations in an agricultural watershed , 2009 .

[9]  Vahid Naeimi,et al.  Temporal variation of soil moisture over the Wuding River basin assessed with an eco-hydrological model, in-situ observations and remote sensing , 2008 .

[10]  Heejun Chang,et al.  The effects of climate change and urbanization on the runoff of the Rock Creek basin in the Portland metropolitan area, Oregon, USA , 2009 .

[11]  F. Laurent,et al.  Simulation de l'effet de changements de pratiques agricoles sur la qualité des eaux avec le modèle SWAT , 2008 .

[12]  Saleh Taghvaeian,et al.  Water balance of irrigated areas: a remote sensing approach , 2011 .

[13]  M. Claverie,et al.  Validation of coarse spatial resolution LAI and FAPAR time series over cropland in southwest France , 2013 .

[14]  P. Durand.  Simulating nitrogen budgets in complex farming systems using INCA: calibration and scenario analyses for the Kervidy catchment (W. France) , 2004 .

[15]  E. Justes,et al.  Simulating the long term impact of nitrate mitigation scenarios in a pilot study basin , 2013 .

[16]  E. J. Wilson,et al.  A semi-distributed ntegrated itrogen model for multiple source assessment in tchments (INCA): Part I — model structure and process equations , 1998 .

[17]  Sylvain Ferrant,et al.  Assessing water availability in a semi-arid watershed of southern India using a semi-distributed model , 2012 .

[18]  J. Nash,et al.  River flow forecasting through conceptual models part I — A discussion of principles☆ , 1970 .

[19]  Kellie B. Vaché,et al.  Current concepts in nitrogen dynamics for mesoscale catchments , 2008 .

[20]  Gérard Dedieu,et al.  A multi-temporal method for cloud detection, applied to FORMOSAT-2, VENµS, LANDSAT and SENTINEL-2 images , 2010 .

[21]  Weimin Ju,et al.  Distributed hydrological model for mapping evapotranspiration using remote sensing inputs , 2005 .

[22]  Steven T. Bednarz,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART II: MODEL APPLICATION 1 , 1998 .

[23]  Gilbert T. Bernhardt,et al.  A comprehensive surface-groundwater flow model , 1993 .

[24]  F. Baret,et al.  GAI estimates of row crops from downward looking digital photos taken perpendicular to rows at 57.5° zenith angle: Theoretical considerations based on 3D architecture models and application to wheat crops , 2010 .

[25]  J. Germon,et al.  NEMIS, a predictive model of denitrification on the field scale , 2000 .

[26]  J. Refsgaard,et al.  Large scale modelling of groundwater contamination from nitrate leaching , 1999 .

[27]  Ralf Ludwig,et al.  Editorial Remote sensing in hydrological sciences , 2009 .

[28]  Ernst-Walter Reiche.  Modelling water and nitrogen dynamics on catchment scale , 1994 .

[29]  E. J. Wilson,et al.  A semi-distributed integrated flow and nitrogen model for multiple source assessment in catchments (INCA): Part II — application to large river basins in south Wales and eastern England , 1998 .

[30]  H. Sinoquet,et al.  An overview of the crop model STICS , 2003 .

[31]  Luca Brocca,et al.  Assimilation of Surface- and Root-Zone ASCAT Soil Moisture Products Into Rainfall–Runoff Modeling , 2012, IEEE Transactions on Geoscience and Remote Sensing.

[32]  Véronique Beaujouan,et al.  A hydrological model dedicated to topography‐based simulation of nitrogen transfer and transformation: rationale and application to the geomorphology– denitrification relationship , 2002 .

[33]  Benoît Duchemin,et al.  A simple algorithm for yield estimates: Evaluation for semi-arid irrigated winter wheat monitored with green leaf area index , 2008, Environ. Model. Softw..

[34]  P. Béziat,et al.  Carbon balance of a three crop succession over two cropland sites in South West France , 2009 .

[35]  Raghavan Srinivasan,et al.  Nonpoint Source (NPS) Pollution Modeling Using Models Integrated with Geographic Information Systems (GIS) , 1993 .

[36]  Vincent Rivalland,et al.  Crops’ water use efficiencies in temperate climate: Comparison of stand, ecosystem and agronomical approaches , 2013 .

[37]  Martin Claverie.  Estimation spatialisée de la biomasse et des besoins en eau des cultures à l'aide de données satellitales à hautes résolutions spatiale et temporelle : application aux agrosystèmes du sud-ouest de la France , 2012 .

[38]  Jeng-Shing Chern,et al.  Lesson learned from FORMOSAT-2 mission operations , 2006 .

[39]  C. Laplanche,et al.  Continuous measurement of nitrate concentration in a highly event‐responsive agricultural catchment in south‐west of France: is the gain of information useful? , 2013 .

[40]  M Benoit,et al.  Agriculture and groundwater nitrate contamination in the Seine basin. The STICS-MODCOU modelling chain. , 2007, The Science of the total environment.

[41]  Luca Brocca,et al.  Antecedent Wetness Conditions based on ERS scatterometer data in support to rainfall-runoff modeling , 2009 .

[42]  T. Meyers,et al.  Measuring Biosphere‐Atmosphere Exchanges of Biologically Related Gases with Micrometeorological Methods , 1988 .

[43]  I. Burns,et al.  A MODEL FOR PREDICTING THE REDISTRIBUTION OF SALTS APPLIED TO FALLOW SOILS AFTER EXCESS RAINFALL OR EVAPORATION , 1974 .

[44]  E. Cowling,et al.  The Nitrogen Cascade , 2003 .

[45]  Tommy Dalgaard,et al.  A model for simulating the timelines of field operations at a European scale for use in complex dynamic models , 2012 .

[46]  T. W. Horst.  The Footprint for Estimation of Atmosphere-Surface Exchange Fluxes by Profile Techniques , 1999 .

[47]  Andrew Hursthouse,et al.  Development and application of a catchment scale diffuse nitrate modelling tool , 2005 .

[48]  W. Bastiaanssen,et al.  Spatial Quantification of Groundwater Abstraction in the Irrigated Indus Basin , 2014, Ground water.

[49]  Paul Bordenave,et al.  Modelling denitrification at the catchment scale. , 2009, The Science of the total environment.

[50]  Keith Beven.  Distributed hydrological modelling: applications of the TOPMODEL concept. , 1997 .

[51]  Gérard Dedieu,et al.  Estimation of leaf area and clumping indexes of crops with hemispherical photographs , 2008 .

[52]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .

[53]  S. Recous,et al.  STICS : a generic model for the simulation of crops and their water and nitrogen balances. I. Theory, and parameterization applied to wheat and corn , 1998 .

[54]  Rebecca J. Lunn,et al.  DEVELOPMENT AND APPLICATION OF A NITROGEN MODELLING SYSTEM FOR LARGE CATCHMENTS , 1996 .

[55]  N. Bosch.  The influence of impoundments on riverine nutrient transport: An evaluation using the Soil and Water Assessment Tool , 2008 .

[56]  Pierre Moreau,et al.  An approach for global sensitivity analysis of a complex environmental model to spatial inputs and parameters: A case study of an agro-hydrological model , 2013, Environ. Model. Softw..

[57]  O. Hagolle,et al.  LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION: Part 1: Principles of the algorithm , 2007 .

[58]  W. G. Knisel,et al.  GLEAMS: Groundwater Loading Effects of Agricultural Management Systems , 1987 .

[59]  Gérard Dedieu,et al.  Correction of aerosol effects on multi-temporal images acquired with constant viewing angles: Application to Formosat-2 images , 2008 .

[60]  Pierre Moreau.  Modélisation intégrée des systèmes agricoles et de la dynamique de l'azote dans les bassins versants : de la conception du modèle au test de scénarios , 2012 .

[61]  Giovanni Laguardia,et al.  On the comparison between the LISFLOOD modelled and the ERS/SCAT derived soil moisture estimates , 2008 .

[62]  Eric Justes,et al.  STICS: a generic model for simulating crops and their water and nitrogen balances. II. Model validation for wheat and maize , 2002 .

[63]  Anju Gaur,et al.  Integrating remote sensing and a process-based hydrological model to evaluate water use and productivity in a south Indian catchment , 2008 .

[64]  Eric Justes,et al.  Understanding nitrogen transfer dynamics in a small agricultural catchment: Comparison of a distributed (TNT2) and a semi distributed (SWAT) modeling approaches , 2011 .