Weather Variability Impacting the Productivity of RICE, Wheat and Sugarcane in North WEST India.

Weather condition of a given location remains practically constant but the microscopic observations show a considerable variation in day to day occurrences. Such variations often encouraged the insect pest and disease attack on the crops and in return adversely affecting their productivity. In view of this the study was undertaken for the Haridwar district of Uttarakhand on rice, wheat and sugarcane crops employing model studies (DSSAT & Regression) and comparing the predicted yield with actually reported yield during 2000-2016. Daily weather data for the period 2000- 2016 was collected from the Agromet Observatory of the, Indian Institute of Technology Roorkee. Daily weather data of rainfall, maximum temperature, minimum temperature, maximum humidity and maximum humidity was also converted into weekly. Area (A), production (P) and Yield (Y) of rice, wheat and sugarcane for the period 2000-2016 of Haridwar district for the period 2000-2016 was collected from the Directorate of Agriculture Uttarakhand. Step wise regression and DSSAT models were used to analyze the sensitivity of weather variation on productivity during their growing season. Step wise regression model revealed that that the rice, wheat and sugarcane productivity was favorably affected by rainfall and maximum humidity, rainfall and minimum temperature as well as the rainfall and minimum humidity respectively. Yield of these crops modeled using DSSAT have shown annual variability but were statistically insignificant.