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Delineation of management zones and optimization of irrigation scheduling to improve irrigation water productivity and revenue in a farmland of Northwest China
Precision Agriculture ( IF 6.2 ) Pub Date : 2019-10-01 , DOI: 10.1007/s11119-019-09688-0
Shichao Chen , Sufen Wang , Manoj Kumar Shukla , Di Wu , Xiuwei Guo , Donghao Li , Taisheng Du

Precision agriculture has been increasingly practised in recent years. Under precision management, farmland is divided into several management zones to implement different strategies and improve irrigation water productivity and revenues. In this research, six soil properties (silt, sand, soil moisture content, available nitrogen, electrical conductivity and elevation) were selected, and fuzzy c-means clustering was used to delineate management zones. The field was divided into three zones. The differences in the mean of the soil properties among the zones were large and within a zone were small. The coefficient of variation of the properties and yield were also smaller than that before classification. The optimization was carried out by using a genetic algorithm based on the Jensen model. Three objective functions were set as maximum yield, maximum irrigation water productivity (IWP) and maximum revenue, and the weights were kept equal to 1/3. The WHCNS (soil water heat carbon nitrogen simulator) model was used to simulate the maize yield under optimized irrigation schedule for the three management zones and to calculate IWP and revenue. Compared with uniform management, IWP and revenue were increased by 0.6 kg m −3 and $61 ha −1 , respectively. The optimized irrigation schedule can be used as a reference for the actual irrigation management. It can increase the IWP and revenue under the premise of achieving the target yield. The results show that the method can guide precision agricultural production and management in large-scale farmland.

中文翻译:

西北某农田划定管理区和优化灌溉调度以提高灌溉水生产力和收益

近年来,精准农业得到了越来越多的实践。在精准管理下,农田被划分为多个管理区,以实施不同的策略,提高灌溉水的生产力和收入。在本研究中,选择了六种土壤性质(淤泥、沙子、土壤含水量、有效氮、电导率和海拔),并使用模糊 c 均值聚类来划分管理区域。该领域被划分为三个区域。区域间土壤性质均值差异较大,区域内差异较小。性能和产量的变异系数也比分级前小。优化是通过使用基于 Jensen 模型的遗传算法进行的。三个目标函数被设置为最大产量,最大灌溉水生产力(IWP)和最大收益,权重保持等于 1/3。WHCNS(土壤水热碳氮模拟器)模型用于模拟三个管理区优化灌溉计划下的玉米产量,并计算 IWP 和收入。与统一管理相比,IWP 和收入分别增加了 0.6 kg m -3 和 $61 ha -1 。优化后的灌溉计划可作为实际灌溉管理的参考。可以在达到目标产量的前提下增加IWP和收益。结果表明,该方法可以指导规模化农田的精准农业生产和管理。WHCNS(土壤水热碳氮模拟器)模型用于模拟三个管理区优化灌溉计划下的玉米产量,并计算 IWP 和收入。与统一管理相比,IWP 和收入分别增加了 0.6 kg m -3 和 $61 ha -1 。优化后的灌溉计划可作为实际灌溉管理的参考。可以在达到目标产量的前提下增加IWP和收益。结果表明,该方法可以指导规模化农田的精准农业生产和管理。WHCNS(土壤水热碳氮模拟器)模型用于模拟三个管理区优化灌溉计划下的玉米产量,并计算 IWP 和收入。与统一管理相比,IWP 和收入分别增加了 0.6 kg m -3 和 $61 ha -1 。优化后的灌溉计划可作为实际灌溉管理的参考。可以在达到目标产量的前提下增加IWP和收益。结果表明,该方法可以指导规模化农田的精准农业生产和管理。分别。优化后的灌溉计划可作为实际灌溉管理的参考。可以在达到目标产量的前提下增加IWP和收益。结果表明,该方法可以指导规模化农田的精准农业生产和管理。分别。优化后的灌溉计划可作为实际灌溉管理的参考。可以在达到目标产量的前提下增加IWP和收益。结果表明,该方法可以指导规模化农田的精准农业生产和管理。
更新日期:2019-10-01
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