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Verifying optimality of rainfed agriculture using a stochastic model for drought occurrence

机译:使用干旱随机模型验证雨养农业的最优性

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It may be paradoxical but subsistence rainfed agriculture is the predominant source of food in Sub-Saharan Africa where the production uncertainty is associated with the stochastic nature of rainfall. This paper attempts to comprehend the rationale of this situation by a mathematical approach. Considering the level of drought severity as the zero-reverting Ornstein-Uhlenbeck process, optimality of rainfed agriculture is investigated in the context of stochastic control theory. Occurrence of drought terminating growth of crops is modelled with the concept of first exit time. A stochastic control problem allowing for virtual cost of irrigation, water stress to crops, and benefits of farming is formulated with irrigation effort as the control variable. The Hamilton-Jacobi-Bellman equation governing the optimal control is studied to identify the set of cost functions optimizing rainfed agriculture in an inverse problem approach. Data and information were collected in the coastal savanna agro-ecological zone of Ghana, to identify model parameters, formulate the stochastic control problem, solve the inverse problem, and then verify optimality of rainfed agriculture. The results indicated that rainfed agriculture is not optimal when the crop is more tolerant to water stress.
机译:这可能是自相矛盾的,但自给自足的雨养农业是撒哈拉以南非洲的主要食物来源,那里的生产不确定性与降雨的随机性有关。本文试图通过一种数学方法来理解这种情况的基本原理。考虑到干旱严重程度为零回复的Ornstein-Uhlenbeck过程,在随机控制理论的背景下研究了雨养农业的最优性。用首次退出时间的概念对干旱终止作物生长的发生进行了建模。随机控制问题考虑了灌溉的虚拟成本,对作物的水分胁迫以及耕作的好处,并以灌溉努力作为控制变量。研究了控制最优控制的汉密尔顿-雅各比-贝尔曼方程,以逆问题方法确定优化雨养农业的成本函数集。在加纳沿海热带稀树草原农业生态区收集数据和信息,以识别模型参数,制定随机控制问题,解决逆问题,然后验证雨养农业的最优性。结果表明,当农作物对水分胁迫的耐受性更高时,雨养农业并不是最佳选择。

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