Using MODAWEC to generate daily weather data for the EPIC model

Although the EPIC model has been widely used in agricultural and environmental studies, applications of this model may be limited in the regions where daily weather data are not available. In this paper, a stand-alone MODAWEC model was developed to generate daily precipitation and maximum and minimum temperature from monthly precipitation, maximum and minimum temperature, and wet days. A case study shows that the crop yields and evapotranspiration (ET) simulated with the generated daily weather data compare very well with those simulated with the measured daily weather data with low normalized mean square errors (0.008-0.017 for crop yields and 0.003-0.004 for ET). The MODAWEC model can extend the application of the EPIC model to the regions where daily data are not available or not complete. In addition, the generated daily weather data can possibly be used by other environmental models. Associated with MODAWEC, the EPIC model can play a greater role in assessing the impacts of global climate change on future food production and water use.

[1]  Roberta A. Brown,et al.  Sensitivity of crop yield and water use to change in a range of climatic factors and CO2 concentrations: a simulation study applying EPIC to the central USA , 1997 .

[2]  John R. Williams,et al.  EPIC-erosion/productivity impact calculator: 1. Model documentation. , 1990 .

[3]  V. Singh,et al.  The EPIC model. , 1995 .

[4]  R. L. Elliott,et al.  Economic and environmental impacts of water quality protection policies: 1. Framework for regional analysis , 1993 .

[5]  A. Saltelli,et al.  An alternative way to compute Fourier amplitude sensitivity test (FAST) , 1998 .

[6]  Richard F. Gunst,et al.  Applied Regression Analysis , 1999, Technometrics.

[7]  Jimmy R. Williams,et al.  An Approach for Estimating Soil Carbon Using the National Nutrient Loss Database , 2004, Environmental management.

[8]  John R. Williams,et al.  A modeling approach to determining the relationship between erosion and soil productivity [EPIC, Erosion-Productivity Impact Calculator, mathematical models] , 1984 .

[9]  C. Harpham,et al.  A daily weather generator for use in climate change studies , 2007, Environ. Model. Softw..

[10]  John R. Williams,et al.  Predicting Daily Mean Soil Temperatures in the EPIC Simulation Model , 1994 .

[11]  C. Kling,et al.  Multiple Benefits of Carbon-Friendly Agricultural Practices: Empirical Assessment of Conservation Tillage , 2004, Environmental management.

[12]  Joe T. Ritchie,et al.  Model for predicting evaporation from a row crop with incomplete cover , 1972 .

[13]  R. L. Elliott,et al.  Modification OF Epic TO SIMULATE PESTICIDE ACTIVITIES: EPIC-PST , 1991 .

[14]  Volker Schwieger.  Variance-based Sensitivity Analysis for Model Evaluation in Engineering Surveys , 2004 .

[15]  Steffen Fritz,et al.  A spatially explicit assessment of current and future hotspots of hunger in Sub-Saharan Africa in the context of global change , 2008 .

[16]  C. Willmott.  Some Comments on the Evaluation of Model Performance , 1982 .

[17]  Junguo Liu,et al.  A GIS-based tool for modelling large-scale crop-water relations , 2009, Environ. Model. Softw..

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

[19]  C. W. Richardson,et al.  The Weather Factor: Incorporating Weather Variance Into Computer Simulation , 1992, Weed Technology.

[20]  Gerrit Hoogenboom,et al.  Weather analogue: A tool for real-time prediction of daily weather data realizations based on a modified k-nearest neighbor approach , 2008, Environ. Model. Softw..

[21]  V. Singh,et al.  Computer Models of Watershed Hydrology , 1995 .

[22]  M. Nolin,et al.  Crop yield, soil temperature and sensitivity of EPIC under central-eastern Canadian conditions , 1998 .

[23]  Hong Yang,et al.  Modeling the role of irrigation in winter wheat yield, crop water productivity, and production in China , 2007, Irrigation Science.

[24]  Irving M. Klotz,et al.  Symposia of the Society for Experimental Biology , 1952, The Yale Journal of Biology and Medicine.

[25]  R. Shibasaki,et al.  Global estimation of crop productivity and the impacts of global warming by GIS and EPIC integration , 2003 .

[26]  George H. Hargreaves,et al.  Reference Crop Evapotranspiration from Temperature , 1985 .

[27]  I. Sobol,et al.  About the use of rank transformation in sensitivity analysis of model output , 1995 .

[28]  Samar J. Bhuyan,et al.  Soil loss predictions with three erosion simulation models , 2002, Environ. Model. Softw..

[29]  D E Radcliffe,et al.  Phosphorus losses from grasslands fertilized with broiler litter: EPIC simulations. , 2001, Journal of environmental quality.

[30]  Michele Rinaldi,et al.  Application of EPIC model for irrigation scheduling of sunflower in Southern Italy , 2001 .

[31]  R. L. Elliott,et al.  Economic and environmental impacts of water quality protection policies: 2. Application to the Central High Plains , 1993 .

[32]  Jimmy R. Williams,et al.  GEPIC - modelling wheat yield and crop water productivity with high resolution on a global scale , 2007 .

[33]  Stefano Tarantola,et al.  A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output , 1999, Technometrics.

[34]  Z. Şen,et al.  First-order Markov chain approach to wind speed modelling , 2001 .

[35]  Donald L. Phillips,et al.  Sensitivity of the US corn belt to climate change and elevated CO2: II. Soil erosion and organic carbon , 1996 .

[36]  C. Fortuin,et al.  Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory , 1973 .

[37]  J. Monteith.  Climate and the efficiency of crop production in Britain , 1977 .

[38]  Donald L. Phillips,et al.  Sensitivity of the US corn belt to climate change and elevated CO2: I. Corn and soybean yields , 1996 .

[39]  William E. Easterling,et al.  Improving the validation of model-simulated crop yield response to climate change: an application to the EPIC model , 1996 .

[40]  John R. Williams,et al.  SENSITIVITY AND UNCERTAINTY ANALYSES OF CROP YIELDS AND SOIL ORGANIC CARBON SIMULATED WITH EPIC , 2005 .

[41]  K. N. Potter,et al.  EVALUATION OF EPIC'S WIND EROSION SUBMODEL USING DATA FROM SOUTHERN ALBERTA , 1998 .

[42]  William E. Easterling,et al.  Simulations of crop response to climate change: effects with present technology and no adjustments (the dumb farmer scenario) , 1992 .

[43]  K. K. Tanji,et al.  Crop nitrogen utilization and soil nitrate loss in a lettuce field , 2004, Fertilizer research.

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

[45]  Junguo Liu,et al.  DROPS FOR CROPS: MODELLING CROP WATER PRODUCTIVITY ON A GLOBAL SCALE , 2008 .

[46]  T. D. Mitchell,et al.  A comprehensive set of high-resolution grids of monthly climate for Europe and the globe: the observed record (1901-2000) and 16 scenarios (2001-2100). , 2004 .

[47]  R. Shibasaki,et al.  National spatial crop yield simulation using GIS-based crop production model , 2001 .

[48]  M. Cabelguenne,et al.  Strategies for Limited Irrigations of Maize in Southwestern France – A Modeling Approach , 1995 .

[49]  C. W. Richardson.  Stochastic simulation of daily precipitation, temperature, and solar radiation , 1981 .