基于最大熵原理的区域农业干旱度概率分布模型

Probability distribution model of regional agricultural drought degree based on the maximum entropy principle

提出了构建综合考虑自然因素与农作物生长周期之间量化关系的干旱度评价指标,并基于最大熵原理建立了项目区干旱度分布密度函数,避免了以往构建概率分布的随意性,实现了对区域农业干旱度进行量化评价的目的。首先根据作物在非充分灌溉条件下的减产率,建立了干旱程度的量化评价指标,然后通过蒙特卡罗法生成了长系列降雨资料,并计算历年干旱度指标,最后利用最大熵原理,构建了农业干旱度分布的概率分布密度函数。以河南省濮阳市渠村灌区为对象进行了实例计算。结果表明,该模型概念清晰,计算简便实用,结果符合实际,是一种较好的评估方法。

The evaluation index of drought degree, which comprehensively considering the quantitative rela- tionship between the crop growing period and natural factors, is presented in this paper. The distribution density function of drought degree has been established based on the maximum-entropy principle. It can avoid the randomness of probability distribution previous constructed and has realized purpose of quantita- tive evaluation of agricultural drought degree. Firstly, the quantitative evaluation index of drought degree was established according to the yield reduction rate of deficit irrigation conditions. Secondly, a long series rainfall data were generated by Monte-Carlo method and the past years index of drought degree were calcu- lated. Finally, the density function of probability distribution of agricultural drought degree distribution was constructed by using maximum entropy principle. As an example, the calculation results of the distribution of drought degree of agriculture in Qucun irrigation area were presented. The results show that the model provides a better evaluation method with clear concept, simple and practical approach, and reasonable outcomes.