Evaluation of WGEN for generating long term weather data for crop simulations.

Abstract We evaluated the ability of the WGEN model to generate long term weather series in situations where the actual historic weather data record is only 3–10 years long. The series generated were used to simulate yield of irrigated and rainfed chickpea. To do this, four 100-year samples of weather data were generated for Tabriz, Iran. The WGEN parameters used to generate data were obtained from daily actual weather data of 3 (W3), 5 (W5), 7 (W7), and 10 (W10) recent years. The actual and generated weather series were each used as input to a chickpea crop model under irrigated and rainfed conditions at three planting dates. Results showed that the generated data are very similar to the actual data used for parameter estimation for all base periods tested. In comparison of the generated data and the historic data the means and the distributions of weather data variables differed significantly. However, with increasing the number of years used for parameter estimation of WGEN from 3 to 10, percent of significant differences were 38, 26, 17 and 13% for W3–W10, respectively. When generated weather data were evaluated as input to a chickpea crop model, simulated yields obtained using generated data were significantly different from that obtained using actual data in 50 and 8% of cases under irrigated and rainfed conditions, respectively. To generate data similar to long term historic data, a longer base period (>10 years) would be required for parameter estimation. However, when it is required that the generated data represent recent history rather than a long term period, the WGEN can be used as a reliable source of weather data even if it’s required parameters are obtained from only 3–10 years of actual historical weather data.

[1]  James W. Jones,et al.  Decision support system for agrotechnology transfer: DSSAT v3 , 1998 .

[2]  W. Bruening,et al.  Planting date and soybean yield: evaluation of environmental effects with a crop simulation model: SOYGRO☆ , 1992 .

[3]  P. K. Aggarwal.  Agro-ecological zoning using crop growth simulation models: characterization of wheat environments of India , 1993 .

[4]  W. G. Knisel,et al.  CREAMS: a field scale model for Chemicals, Runoff, and Erosion from Agricultural Management Systems [USA] , 1980 .

[5]  C. W. Richardson.  Weather simulation for crop management models , 1985 .

[6]  Holger Meinke,et al.  A Peanut Simulation Model: II. Assessing Regional Production Potential , 1995 .

[7]  T. Sinclair.  Water and nitrogen limitations in soybean grain production I. Model development , 1986 .

[8]  G. O'Leary,et al.  A simulation study of wheat crop response to water supply, nitrogen nutrition, stubble retention, and tillage , 1998 .

[9]  H. Meinke,et al.  A sunflower simulation model: II. Simulating production risks in a variable sub-tropical environment , 1993 .

[10]  Paul Teng,et al.  Systems approaches for agricultural development , 1993, Systems Approaches for Sustainable Agricultural Development.

[11]  R. Braddock,et al.  Stochastic weather modelling: a phenomenological approach , 1990 .

[12]  James W. Jones,et al.  WeatherMan: a utility for managing and generating daily weather data , 1994 .

[13]  B. Habekotté.  Options for increasing seed yield of winter oilseed rape (Brassica napus L.): a simulation study , 1997 .

[14]  K. Boote,et al.  A peanut simulation model. I: Model development and testing , 1995 .

[15]  Iwan Supit,et al.  A simple method for generating daily rainfall data , 1986 .

[16]  G. Larsen,et al.  Stochastic Simulation of Daily Climatic Data for Agronomic Models1 , 1982 .

[17]  J. Amir,et al.  A model of water limitation on spring wheat growth and yield , 1991 .

[18]  D. Bachelet,et al.  Simulating the impact of climate change on rice production in Asia and evaluating options for adaptation , 1997 .

[19]  R. C. Muchow,et al.  Assessing climatic risk to sorghum production in water-limited subtropical environments II. Effects of planting date, soil water at planting, and cultivar phenology , 1994 .

[20]  M. Saxena,et al.  Adaptation of Chickpea in the West Asia and North Africa Region , 1996 .

[21]  H. Meinke,et al.  Evaluation of radiation and temperature data generators in the Australian tropics and sub-tropics using crop simulation models , 1995 .

[22]  James W. Jones,et al.  POTENTIAL USES AND LIMITATIONS OF CROP MODELS , 1996 .

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

[24]  J. Doorenbos,et al.  Guidelines for predicting crop water requirements , 1977 .

[25]  L. S. Rathore,et al.  Vulnerability of rice and wheat yields in NW India to future changes in climate , 1998 .

[26]  G. Campbell,et al.  On the relationship between incoming solar radiation and daily maximum and minimum temperature , 1984 .

[27]  A. Soltani,et al.  A simple model for chickpea growth and yield , 1999 .