Multi-Year Prediction of Wheat Yield as Influenced by Changing Agro-Climatic Indices in Kapilvastu Using Dssat Crop Model

Abstract

Central Terai in Nepal is the major production domain of wheat; however, wheat yields have been majorly affected by anomalies of agro-climatic indices like fluctuating maximum and minimum temperatures, solar radiation and rainfall. NASA Power data over 33 years records (1985-2018) were purposively download and compared with the ground station measured data for the study of study by using four years of weather data (1986, 1996, 2006 and 2016) randomly selected years for the multi-year prediction of agroclimatic

scenarios on yields of wheat in Kapilvastu district, of Central Terai, Nepal. The relationship between the DHM recorded weather data and the NASA power data was found fairly valid and safe to see the long-term climate change impacts. At Kapilvastu the annual average and maximum temperatures were found to be decreasing by 0.017˚C and 0.046˚C per year, respectively, whereas the minimum temperature was increasing by 0.011˚C. Similarly, the total precipitation was increased by 28.63mm per year and solar radiation was decreasing by 0.035 MJm -2 per year. The trend analysis on grain yields of wheat were correlated over the historical records of maximum temperature, minimum temperature, rainfall and solar radiations. A positive correlation was found with minimum temperature and rainfall. However, the yield was found to be negatively correlated with the maximum temperature and solar radiations. Cropping Systems model CERES-Wheat embedded in Decision Support System for Agro-technology Transform (DSSAT) ver 4.7 model was used to study the multi-year prediction of wheat yield over the changing agro-climatic scenarios after following IPCC (2007) scenario using environmental modification section of the DSSAT ver 4.7 models. The data sets to run the CSM-CERES- Wheat models have been taken from the well predicted and validated crop model with WK-1204 cultivar of wheat which is popularly grown in Terai and hills condition of sandy-clay loam soil, resembling the production domain of the project sites. The simulation results using DSSAT model over the 33 years of weather data were found to be very closely agreeing with the observed data of the wheat yield recorded from the Ministry of Agriculture and Livestock Development in Nepal. The trend analysis, regression and correlation studies and from sensitivity analysis using DSSAT, all have resulted the uniform relationship between agroclimatic indices and wheat yields. The different climate change scenarios as advocated by

IPCC (2007) for 2020, 2050, and 2080 were studied to simulate the yield performance of

WK-1204 cultivar of wheat. Increased in temperature by 1˚C will increase the wheat yield

and furthermore increased

in temperature decreased the yield under the present levels of agronomic management options. The result showed that the wheat yields for few years can only be sustained by using the present crop varieties and urged for the development of climate change ready crop varieties to feed the increasingly growing population.

Keywords: Agro-climatic indices, DSSAT 4.7 crop model, Multi-year prediction, Wheat yield

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