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Wheat is the major cereal crop of winter season in the Indo-gangetic plains of India. The study is aimed to analyze impact of climate change on wheat varieties viz. K-9107 and HD-2733, under two different agroclimatic zones using simulation model InfoCrop. Model was calibrated and validated for Patna and Ranchi centres. Sensitivity analysis indicated declining yield trend with increase in temperature. Wheat yields simulated for future climate change scenario HADCM3 A2 for different time periods viz. 2020, 2050 and 2080. Simulated wheat yield showed decline from 3 to 38 percent for Patna and 3 to 28 percent for Ranchi. Due to higher temperature in future scenario the days to anthesis, days to maturity and grain number showed decline for both the locations.

Long term weather data is requisite to drive physically based hydrological and crop growth models to assess climate change impacts. However, lack of sufficient historical weather data many a times restrict use of these models. Realization of above facts has resulted in development of a range of weather generators such as WGEN, CLIGEN, ClimGen and LARS-WG. Any generator must be tested to ensure that the data that it produces is satisfactory for the purposes for which it is to be used. The aim of this paper is to test a commonly used weather generator, LARSWG (version 4.0) at three sites at Bihar. Statistical test were conducted, including t-test and Ftest, to compare the differences between generated weather data versus 30 years observed weather data. In recent years the weather generators have also been employed to construct climate change scenarios for impact assessment. The results showed that the generated weather series was similar to the observed data for its distribution of monthly precipitation and its variances, monthly means and variance of minimum and maximum air temperatures.