Agricultural Water Management ( IF 6.7 ) Pub Date : 2022-06-22 , DOI: 10.1016/j.agwat.2022.107780 Youzhi Wang, Xinwei Guo, Fan Zhang, Huijuan Yin, Ping Guo, Wenge Zhang, Qiangkun Li
water-agricultural-ecology nexus system has spatial heterogeneous characteristics owing to heterogeneities of soil, crop, and weather types. Such complexes aggravate the difficulties in agricultural water, land, and fertilizer resources optimization. To address the above problems, this paper developed the spatially-distributed ANN-multi-objective multi-preference fuzzy credibility constrained programming (distributed ANN-MOMPFCCP) for optimizing water, land, and fertilizer resources. It incorporates the multi-objective programming (MOP), multi-preferences credibility constrained programming (MPFCCP) with the distributed ANN model, and has obvious advantages in improving the calculation efficiency of the traditional spatially-distributed crop simulation-optimization model. Besides, it can address uncertainties of the crop simulation model by introducing stochastic programming. It builds connections between food yields and agricultural ecological effects by introducing negative and positive ecological benefits in study system. Through proposed model, optimal distributed schemes considering spatial heterogeneous net economic and ecological benefit, and associated integrated risks can be generated. Optimal results show that water shortage risk occupied about 20 % of total risks, economic and ecological loss occupied about 20~20.2 % and 20~21 % of total economic and ecological benefits, respectively. Considering uncertainties of crop simulation model was a high effective way to improve robustness of simulation model. The model could offer insight alternatives for regional managers in measuring distributed agricultural-ecological benefit as well as making tradeoff among economic, ecological benefits and risks. Moreover, this approach can help manage multi-type resources under uncertainties, and provide multiple groups of Pareto solutions for managers, so that managers could select best management practices based on respective risk attitudes, and preferences.
中文翻译:
不确定性和风险下水-农业-生态关系管理的空间分布ANN优化方法
由于土壤、作物和天气类型的异质性,水-农业-生态关系系统具有空间异质性特征。此类复合物加剧了农业用水、土地和肥料的困难资源优化。针对上述问题,本文开发了空间分布式ANN-多目标多偏好模糊可信约束规划(distributed ANN-MOMPFCCP),用于优化水、土地和肥料资源。它将多目标规划(MOP)、多偏好可信约束规划(MPFCCP)与分布式人工神经网络模型相结合,在提高传统空间分布作物模拟优化模型的计算效率方面具有明显优势。此外,它可以解决作物模拟模型的不确定性通过引入随机规划。它通过在研究系统中引入消极和积极的生态效益来建立粮食产量和农业生态效应之间的联系。通过所提出的模型,可以生成考虑空间异构净经济和生态效益以及相关综合风险的最优分布式方案。优化结果表明,水资源短缺风险占总风险的20%左右,经济和生态损失分别占经济和生态总效益的20~20.2%和20~21%。考虑作物模拟模型的不确定性是提高模拟模型鲁棒性的有效途径。该模型可以为区域管理人员在衡量分布式农业生态效益以及制定经济、生态效益和风险之间的权衡。此外,这种方法可以帮助管理不确定性下的多类型资源,并为管理者提供多组帕累托解,使管理者可以根据各自的风险态度和偏好选择最佳管理实践。