Improved modeling of groundwater recharge in agricultural watersheds using a combination of crop model and remote sensing

For improved water management and effi ciency of use in agriculture, studies dealing with coupled crop-surface water-groundwater models are needed. Such integrated models of crop and hydrology can provide accurate quantifi cation of spatio-temporal variations of water balance parameters such as soil moisture store, evapotranspiration and recharge in a catchment. Performance of a coupled crop-hydrology model would depend on the availability of a calibrated crop model for various irrigated/rainfed crops and also on an accurate knowledge of soil hydraulic parameters in the catchment at relevant scale. Moreover, such a coupled model should be designed so as to enable the use/assimilation of recent satellite remote sensing products (optical and microwave) in order to model the processes at catchment scales. In this study we present a framework to couple a crop model with a groundwater model for applications to irrigated groundwater agricultural systems. We discuss the calibration of the STICS crop model and present a methodology to estimate the soil hydraulic parameters by inversion of crop model using both ground and satellite based data. Using this methodology we demonstrate the feasibility of estimation of potential recharge due to spatially varying soil/crop matrix.

[1]  Laurent Barbiero,et al.  Using a structural approach to identify relationships between soil and erosion in a semi-humid forested area, South India , 2007 .

[2]  Chong-Yu Xu,et al.  Suitability of the TRMM satellite rainfalls in driving a distributed hydrological model for water balance computations in Xinjiang catchment, Poyang lake basin , 2012 .

[3]  Sat Kumar Tomer,et al.  Parameter estimation of a two-horizon soil profile by combining crop canopy and surface soil moisture observations using GLUE , 2012 .

[4]  Aljosja Hooijer,et al.  Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia , 2011 .

[5]  G. Salvucci,et al.  Equilibrium analysis of groundwater–vadose zone interactions and the resulting spatial distribution of hydrologic fluxes across a Canadian Prairie , 1999 .

[6]  R. Maxwell,et al.  Integrated surface-groundwater flow modeling: A free-surface overland flow boundary condition in a parallel groundwater flow model , 2006 .

[7]  M. Canty,et al.  Hydraulic parameter estimation by remotely-sensed top soil moisture observations with the particle filter , 2011 .

[8]  Véronique Beaujouan,et al.  Modelling the effect of the spatial distribution of agricultural practices on nitrogen fluxes in rural catchments , 2001 .

[9]  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.

[10]  T. Skaggs,et al.  A root zone modelling approach to estimating groundwater recharge from irrigated areas , 2009 .

[11]  Samuel Buis,et al.  Soil properties estimation by inversion of a crop model and observations on crops improves the prediction of agro-environmental variables , 2010 .

[12]  Reed M. Maxwell,et al.  Development of a Coupled Land Surface and Groundwater Model , 2005 .

[13]  Eric Justes,et al.  A package of parameter estimation methods and implementation for the STICS crop-soil model , 2011, Environ. Model. Softw..

[14]  Michael T. Coe,et al.  Testing the performance of a dynamic global ecosystem model: Water balance, carbon balance, and vegetation structure , 2000 .

[15]  B. Scanlon,et al.  Choosing appropriate techniques for quantifying groundwater recharge , 2002 .

[16]  Daniel Hillel,et al.  Groundwater recharge in arid regions: Review and critique of estimation methods , 1988 .

[17]  Changhui Peng,et al.  From static biogeographical model to dynamic global vegetation model: a global perspective on modelling vegetation dynamics , 2000 .

[18]  I. C. Prentice,et al.  An integrated biosphere model of land surface processes , 1996 .

[19]  Stephan J. Maas,et al.  Using Satellite Data to Improve Model Estimates of Crop Yield , 1988 .

[20]  I. Simmers,et al.  Groundwater recharge: an overview of processes and challenges , 2002 .

[21]  H. McNairn,et al.  The Potential of RADARSAT-2 for Crop Mapping and Assessing Crop Condition , 2000 .

[22]  P. Bartlein,et al.  Simulating the climatic effects on vegetation: approaches, issues and challenges , 2008 .

[23]  Yang Hong,et al.  Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins , 2012, IEEE Geoscience and Remote Sensing Letters.

[24]  Jirka Šimůnek,et al.  Evaluating Interactions between Groundwater and Vadose Zone Using the HYDRUS‐Based Flow Package for MODFLOW , 2008 .

[25]  Michele Vurro,et al.  A GIS tool for hydrogeological water balance evaluation on a regional scale in semi-arid environments , 2005, Comput. Geosci..

[26]  Tom Addiscott,et al.  Critical Evaluation of Models and Their Parameters , 1995 .

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

[28]  S. Paloscia.  An empirical approach to estimating leaf area index from multifrequency SAR data , 1998 .

[29]  Samuel Buis,et al.  Global sensitivity analysis measures the quality of parameter estimation: The case of soil parameters and a crop model , 2010, Environ. Model. Softw..

[30]  K. R. Rushton,et al.  Groundwater Hydrology: Conceptual and Computational Models , 2003 .

[31]  Murari R. R. Varma,et al.  Water balance modelling in a tropical watershed under deciduous forest (Mule Hole, India): Regolith matric storage buffers the groundwater recharge process , 2010 .

[32]  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 .

[33]  A. J. Stern,et al.  Crop Yield Assessment from Remote Sensing , 2003 .

[34]  Henry Lin.  Chapter 1 – Hydropedology: Addressing Fundamentals and Building Bridges to Understand Complex Pedologic and Hydrologic Interactions , 2012 .

[35]  Simonetta Paloscia,et al.  The relationship between the backscattering coefficient and the biomass of narrow and broad leaf crops , 2001, IEEE Trans. Geosci. Remote. Sens..

[36]  Zeng Qingcun,et al.  A land surface model (IAP94) for climate studies part I: Formulation and validation in off-line experiments , 1997 .

[37]  M. C. Mastin,et al.  Recharge from precipitation in three small glacial-till-mantled catchments in the Puget Sound Lowland, Washington , 1997 .

[38]  J. Maréchal,et al.  Modelling the chemical weathering fluxes at the watershed scale in the Tropics (Mule Hole, South India): Relative contribution of the smectite/kaolinite assemblage versus primary minerals , 2010 .

[39]  J. R. Ritchie,et al.  Description and performance of CERES-Wheat: a user-oriented wheat yield model , 1985 .

[40]  Juan M. Lopez-Sanchez,et al.  Potentials of polarimetric SAR interferometry for agriculture monitoring , 2009 .

[41]  Stephan J. Maas,et al.  Use of remotely-sensed information in agricultural crop growth models , 1988 .

[42]  Muddu Sekhar,et al.  Regolith mass balance inferred from combined mineralogical, geochemical and geophysical studies: Mule Hole gneissic watershed, South India , 2009 .

[43]  G. Gee,et al.  Vadose-zone techniques for estimating groundwater recharge in arid and semiarid regions , 1994 .

[44]  Søren Hansen,et al.  NPo-research, A10: DAISY: Soil Plant Atmosphere System Model , 1990 .

[45]  I. C. Prentice,et al.  Evaluation of the terrestrial carbon cycle, future plant geography and climate‐carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs) , 2008 .

[46]  V. Arora.  MODELING VEGETATION AS A DYNAMIC COMPONENT IN SOIL‐VEGETATION‐ATMOSPHERE TRANSFER SCHEMES AND HYDROLOGICAL MODELS , 2002 .

[47]  John R. Williams,et al.  The EPIC crop growth model , 1989 .

[48]  Elfatih A. B. Eltahir,et al.  Representation of Water Table Dynamics in a Land Surface Scheme. Part I: Model Development , 2005 .

[49]  Keith Beven,et al.  The future of distributed models: model calibration and uncertainty prediction. , 1992 .

[50]  Henry Lin,et al.  Chapter 1 – Hydropedology: Addressing Fundamentals and Building Bridges to Understand Complex Pedologic and Hydrologic Interactions , 2012 .

[51]  F.W.T. Penning de Vries,et al.  Evaluation of simulation models in agriculture and biology: Conclusions of a workshop , 1977 .

[52]  B. Bonan,et al.  A Land Surface Model (LSM Version 1.0) for Ecological, Hydrological, and Atmospheric Studies: Technical Description and User's Guide , 1996 .

[53]  Xiaoyan Zhao,et al.  Interpreting RADARSAT-2 Quad-Polarization SAR Signatures From Rice Paddy Based on Experiments , 2012, IEEE Geoscience and Remote Sensing Letters.

[54]  Mekonnen Gebremichael,et al.  Evaluation of satellite rainfall products through hydrologic simulation in a fully distributed hydrologic model , 2011 .

[55]  Philippe Lagacherie,et al.  Digital Soil Mapping: A State of the Art , 2008 .

[56]  Muddu Sekhar,et al.  Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling , 2009 .

[57]  John R. Porter,et al.  A winter wheat crop simulation model without water or nutrient limitations , 1984, The Journal of Agricultural Science.

[58]  Heather McNairn,et al.  The sensitivity of RADARSAT-2 quad-polarization SAR data to crop LAI , 2009, Optical Engineering + Applications.

[59]  I. C. Prentice,et al.  Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model , 2003 .

[60]  Richard C. Carter,et al.  A single layer soil water balance model for estimating deep drainage (potential recharge): An application to cropped land in semi-arid North-east Nigeria , 2007 .

[61]  Bruno Mary,et al.  Conceptual basis, formalisations and parameterization of the STICS crop model , 2009 .