Modelling irrigated maize with a combination of coupled-model simulation and uncertainty analysis, in the northwest of China

The hydrologic model HYDRUS-1-D and the crop growth model WOFOST are coupled to efficiently manage water resources in agriculture and improve the prediction of crop production. The results of the coupled model are validated by experimental studies of irrigated-maize done in the middle reaches of northwest China's Heihe River, a semi-arid to arid region. Good agreement is achieved between the simulated evapotranspiration, soil moisture and crop production and their respective field measurements made under current maize irrigation and fertilization. Based on the calibrated model, the scenario analysis reveals that the most optimal amount of irrigation is 500–600 mm in this region. However, for regions without detailed observation, the results of the numerical simulation can be unreliable for irrigation decision making owing to the shortage of calibrated model boundary conditions and parameters. So, we develop a method of combining model ensemble simulations and uncertainty/sensitivity analysis to speculate the probability of crop production. In our studies, the uncertainty analysis is used to reveal the risk of facing a loss of crop production as irrigation decreases. The global sensitivity analysis is used to test the coupled model and further quantitatively analyse the impact of the uncertainty of coupled model parameters and environmental scenarios on crop production. This method can be used for estimation in regions with no or reduced data availability.

[1]  J. Monteith,et al.  Principles of Environmental Physics , 2014 .

[2]  Bin Jia,et al.  Application of the SWAP model to simulate water-salt transport under deficit irrigation with saline water , 2011, Math. Comput. Model..

[3]  Juana Paul Moiwo,et al.  Estimation of irrigation requirement for sustainable water resources reallocation in North China , 2010 .

[4]  Qiang Yu,et al.  Modelling the effects of climate variability and water management on crop water productivity and water balance in the North China Plain , 2010 .

[5]  Gerrit Hoogenboom,et al.  Irrigation strategies to improve the water use efficiency of wheat-maize double cropping systems in North China Plain , 2010 .

[6]  Garey A. Fox,et al.  Influence of flow concentration on parameter importance and prediction uncertainty of pesticide trapping by vegetative filter strips , 2010 .

[7]  Rafael Muñoz-Carpena,et al.  Parameter importance and uncertainty in predicting runoff pesticide reduction with filter strips. , 2010, Journal of environmental quality.

[8]  Xu Ziwei,et al.  A Study on the Data Processing and Quality Assessment of the Eddy Covariance System , 2008 .

[9]  David B. Goldston.  Hazy reasoning behind clean air , 2008, Nature.

[10]  Erik Stokstad.  Dueling Visions for a Hungry World , 2008, Science.

[11]  Joop G Kroes,et al.  SWAP Version 3.2. Theory description and user manual , 2008 .

[12]  Rafael Muñoz-Carpena,et al.  Development, Testing, and Sensitivity and Uncertainty Analyses of a Transport and Reaction Simulation Engine (TaRSE) for Spatially Distributed Modeling of Phosphorus in South Florida Peat Marsh Wetlands , 2008 .

[13]  J. Monteith.  Evaporation and surface temperature , 2007 .

[14]  V. Lakshmi.  Useless Arithmetic: Why Environmental Scientists Can't Predict the Future , 2007 .

[15]  Keith Smettem,et al.  Welcome address for the new ‘Ecohydrology’ Journal , 2007 .

[16]  S. Gayler,et al.  The impact of crop growth sub-model choice on simulated water and nitrogen balances , 2006, Nutrient Cycling in Agroecosystems.

[17]  P. de Willigen,et al.  Nitrogen turnover in the soil-crop system; comparison of fourteen simulation models , 1991, Fertilizer research.

[18]  Stefano Tarantola,et al.  Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models , 2004 .

[19]  S. Patil,et al.  Effect of cultural practices on soil properties, moisture conservation and grain yield of winter sorghum (Sorghum bicolar L. Moench) in semi-arid tropics of India , 2004 .

[20]  M. Anwar,et al.  Water-use efficiency and the effect of water deficits on crop growth and yield of Kabuli chickpea (Cicer arietinum L.) in a cool-temperate subhumid climate , 2003, The Journal of Agricultural Science.

[21]  Tammo S. Steenhuis,et al.  A soil‐water‐balance approach to quantify groundwater recharge from irrigated cropland in the North China Plain , 2003 .

[22]  David G. Vaughan,et al.  The Skeptical Environmentalist: Measuring the Real State of the World , 2003, Antarctic Science.

[23]  L. R. Ahuja,et al.  Crop–Soil Simulation Models , 2003, Journal of Environmental Quality.

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

[25]  J. Eitzingera,et al.  Comparison of CERES, WOFOST and SWAP models in simulating soil water content during growing season under different soil conditions , 2003 .

[26]  Senthold Asseng,et al.  An overview of APSIM, a model designed for farming systems simulation , 2003 .

[27]  James W. Jones,et al.  The DSSAT cropping system model , 2003 .

[28]  M. Donatelli,et al.  Modelling cropping systems¿highlights of the symposium and preface to the special issues , 2002 .

[29]  Robin Matthews,et al.  Crop-Soil Simulation Models: Applications in Developing Countries , 2002 .

[30]  A. Saltelli,et al.  Making best use of model evaluations to compute sensitivity indices , 2002 .

[31]  A. Gupta,et al.  Application of GIS and crop growth models in estimating water productivity , 2002 .

[32]  Jeroen P. van der Sluijs,et al.  A way out of the credibility crisis of models used in integrated environmental assessment , 2002 .

[33]  Joost Wolf,et al.  Comparison of two soya bean simulation models under climate change : I Model calibration and sensitivity analyses , 2002 .

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

[35]  A. Shepherd,et al.  Simulation of the effect of water shortage on the yields of winter wheat in North-East England , 2002 .

[36]  I. Rodríguez‐Iturbe,et al.  Intensive or extensive use of soil moisture: Plant strategies to cope with stochastic water availability , 2001 .

[37]  Brian Keating,et al.  Approaches to modular model development , 2001 .

[38]  Liwang Ma,et al.  Modeling Carbon and Nitrogen Dynamics for Soil Management , 2001 .

[39]  H.F.M. ten Berge,et al.  ORYZA2000 : modeling lowland rice , 2001 .

[40]  R. I. Veld,et al.  Willingly and knowingly : the roles of knowledge about nature and the environment in policy processes , 2000 .

[41]  S. I. Bhuiyan,et al.  Increasing water-use efficiency in rice production: farm-level perspectives , 1999 .

[42]  W. James Shuttleworth,et al.  Measurement and modelling evaporation for irrigated crops in north‐west Mexico , 1998 .

[43]  M. Schaap,et al.  Neural network analysis for hierarchical prediction of soil hydraulic properties , 1998 .

[44]  C. A. van Diepen,et al.  User's guide for the WOFOST 7.1 crop growth simulation model and WOFOST Control Center 1.5. , 1998 .

[45]  Radhika Vidanage De Silva,et al.  World water demand and supply, 1990 to 2025: scenarios and issues , 1998 .

[46]  G. Hoogenboom,et al.  Understanding Options for Agricultural Production , 1998, Systems Approaches for Sustainable Agricultural Development.

[47]  M. J. Kropff,et al.  Applications of Systems Approaches at the Field Level , 1997, Systems Approaches for Sustainable Agricultural Development.

[48]  David Molden,et al.  Accounting for water use and productivity , 1997 .

[49]  M. Schaap,et al.  Modeling water retention curves of sandy soils using neural networks , 1996 .

[50]  Bernd Diekkrüger,et al.  Validity of agroecosystem models a comparison of results of different models applied to the same data set , 1995 .

[51]  Michael D. McKay,et al.  Evaluating Prediction Uncertainty , 1995 .

[52]  Larry O. Pochop,et al.  Evaporation, Evapotranspiration and Climatic Data , 1994 .

[53]  E. Priesack,et al.  Expert-N - A Building Block System of Nitrogen Models as Resource for Advice, Research, Water Management and Policy , 1993 .

[54]  Ilya M. Sobol,et al.  Sensitivity Estimates for Nonlinear Mathematical Models , 1993 .

[55]  C. A. Diepen,et al.  Crop-specific simulation parameters for yield forecasting across the European Community , 1993 .

[56]  H. Raman,et al.  Decision Support System for Crop Planning during Droughts , 1992 .

[57]  J. Goudriaan,et al.  Simulation of crop growth for potential and water - limited production situations : as applied to spring wheat , 1992 .

[58]  Max D. Morris,et al.  Factorial sampling plans for preliminary computational experiments , 1991 .

[59]  Guna N. Paudyal,et al.  Irrigation planning by multilevel optimization , 1990 .

[60]  H. van Keulen,et al.  Modelling of agricultural production: Weather, soils, and crops , 1986 .

[61]  G. Hornberger,et al.  Approach to the preliminary analysis of environmental systems , 1981 .

[62]  Van Genuchten,et al.  A closed-form equation for predicting the hydraulic conductivity of unsaturated soils , 1980 .

[63]  Warren J. Busscher,et al.  Simulation of Field Water Use and Crop Yield , 1980 .

[64]  K. H. Hartge,et al.  Feddes, R. A., Kowalik, P. I. und Zaradny, H.: simulation of field water use and crop yield. Pudoc (Centre for agricultural publishing and documentation) Wageningen, Niederlande, 195 Seiten, 13 Abbildungen, Paperback. Preis: hfl 30,– , 1980 .

[65]  G. Campbell,et al.  An Introduction to Environmental Biophysics , 1977 .

[66]  Y. Mualem,et al.  Hysteretical models for prediction of the hydraulic conductivity of unsaturated porous media , 1976 .

[67]  J. Monteith.  Evaporation and environment. , 1965, Symposia of the Society for Experimental Biology.