印度Theni地区降雨变率和概率分析

YMER Digital Pub Date : 2022-08-19 DOI:10.37896/ymer21.08/67
C. Dharani
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引用次数: 0

摘要

基于概率分析的作物计划有助于提高产量。利用每周和每月的降雨量数据,通过对40年期间(1982-2021年)的概率分析,在Theni地区开展了一项作物规划研究。年平均降雨量为1100.2 mm,分布在90个阴雨天。概率研究表明,连续8周(38 ~ 45周),每周可获得20mm的降雨量,有利于播种和种植。另一方面,10月的月平均降雨量最大(191.8 mm),其次是11月(147.9 mm)。该地区种植的主要作物是水稻、甘蔗和香蕉,但由于它们的生长周期更短,产量更高,因此应该用玉米、豆类、豇豆、高粱、ragi和小小米来代替。关键词:降雨,马尔可夫链分析,初始概率和条件概率,作物规划
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of rainfall variability and probability in Theni District, India
Crop planning based probability analysis aids in increasing production. A crop planning research was conducted in the Theni district by examining probability analysis over a 40-year period (1982-2021) using weekly and monthly rainfall data. The mean annual rainfall in the Theni district was 1100.2 mm spread over 90 rainy days. The probability study revealed that obtaining 20mm rainfall per week received for 8 weeks (38 to 45th week), which is beneficial for sowing and planting. On the other side, October had the greatest mean monthly rainfall (191.8 mm), followed by November (147.9 mm). The main crops farmed in this area are rice, sugarcane, and bananas, but they should be replaced with maize, pulses, cowpea, sorghum, ragi, and minor millets since they can grow in a shorter time period and yield higher. Key words: Rainfall, Markov chain analysis, initial and conditional probability and crop planning
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