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Modeling Soil Moisture Profiles in Irrigated Fields by the Principle of Maximum Entropy

机译:利用最大熵原理模拟灌溉田土壤水分剖面

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Vertical soil moisture profiles based on the principle of maximum entropy (POME) were validated using field and model data and applied to guide an irrigation cycle over a maize field in north central Alabama (USA). The results demonstrate that a simple two-constraint entropy model under the assumption of a uniform initial soil moisture distribution can simulate most soil moisture profiles that occur in the particular soil and climate regime that prevails in the study area. The results of the irrigation simulation demonstrated that the POME model produced a very efficient irrigation strategy with minimal losses (about 1.9% of total applied water). However, the results for finely-textured (silty clay) soils were problematic in that some plant stress did develop due to insufficient applied water. Soil moisture states in these soils fell to around 31% of available moisture content, but only on the last day of the drying side of the irrigation cycle. Overall, the POME approach showed promise as a general strategy to guide irrigation in humid environments, such as the Southeastern United States.
机译:利用田间和模型数据验证了基于最大熵原理(POME)的垂直土壤水分剖面,并将其用于指导美国阿拉巴马州中北部玉米田的灌溉周期。结果表明,在假设初始土壤水分分布均匀的情况下,简单的两约束熵模型可以模拟研究区域中普遍存在的特定土壤和气候条件下的大多数土壤水分剖面。灌溉模拟的结果表明,POME模型产生了一种非常有效的灌溉策略,损失最小(约占总应用水的1.9%)。但是,对于质地细密的(粉质粘土)土壤,结果是有问题的,因为施加的水分不足,确实会引起一些植物胁迫。这些土壤中的土壤水分状态降至可用水分含量的31%左右,但仅限于灌溉周期干燥期的最后一天。总体而言,POME方法显示出有望作为指导潮湿环境(例如美国东南部)灌溉的总体策略。

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