Crop Planning of the Warangal District of Telangana State using Probability Distribution of 40 Years Rainfall Data

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Abstract

Rain is a major component of the water cycle that deposits most of the fresh water on the earth. The determination of the frequency of occurrence of extreme hydrological events is a prerequisite for planning and execution of many water resource projects. A comprehensive statistical analysis on annual, monthly and seasonal rainfall for Warangal District, Telangana was performed using rainfall data for 40 years (1962-2001). The current investigation was conducted with the ultimate aim of determining the type of Probability distribution that best fits the rainfall data of that particular area. The plotting position and probabilistic methods of probability distribution functions were used for analysis of rainfall data. Rainfall magnitude were evaluated for different return periods. As well as the rainfall pattern of that area has been studied with help of standard deviation and co-efficient of variation. The difference in results obtained from the methods of plotting position were found to be insignificant. Chi-square test was used to measure the Goodness of fit for the seasonal and monthly rainfall. Gumbel’s (Extreme value type-I) method and Normal method was found to be the best method of distribution for the rainfall data of this region. A detailed study was conducted on the crop planning of this region. Rainfall amount is decreasing gradually due to urbanization, global climatic change and hence a decrease in crop productivity. Despite the growth in percentage of gross-irrigated area over Rain-fed farming, Farmers are still rainfall dependent. Crop planning is done with the average effective rainfall of Warangal. Economic analysis is carried out for the crops cultivated in this region and farmers get 23% increase in their yield according to the rates available in Warangal market.

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APA

Deepa*, D., Sasireka*, K., & Avala, A. (2019). Crop Planning of the Warangal District of Telangana State using Probability Distribution of 40 Years Rainfall Data. International Journal of Recent Technology and Engineering (IJRTE), 8(4), 8539–8546. https://doi.org/10.35940/ijrte.d4236.118419

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