Research Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan 523808, China.
Research Center for Eco-environmental Engineering, Dongguan University of Technology, Dongguan 523808, China.
Sci Total Environ. 2021 Mar 1;758:143659. doi: 10.1016/j.scitotenv.2020.143659. Epub 2020 Nov 20.
Management of nonpoint source (NPS) pollution is highly important in watershed water environmental and ecological security. However, the many complexities and uncertainties that exist in the processes of export and management of NPS pollution exert substantial influences on the reliability of multiple management practices. This study developed an inexact multiobjective possibilistic mean-variance mixed-integer programming (IMPMMP) model for NPS pollution management through optimization of watershed land use pattern and livestock production structure. By coupling interval parameter programming, mixed-integer programming, multiobjective programming, and an export coefficient model within a general possibilistic mean-variance model framework, the IMPMMP model deals effectively with system uncertainties and complexities. Moreover, the risk of exceeding criteria (REC) in NPS pollution management systems can be considered. The proposed IMPMMP model was applied to a real-world case study in the Xinfengjiang Reservoir watershed in South China. Results showed that the preference of decision makers regarding land use adjustment plays a decisive role in determining model feasibility. The area provided for each land use type that could be adjusted has to reach a certain threshold to achieve the goals of reduced pollution load and REC control. The NPS pollution loads after optimization would be exported primarily from different land uses and the human population. Compared with NPS nitrogen pollution management, it is more difficult to reduce the NPS phosphorus load and to manage the corresponding REC through adjustment of the land use pattern and livestock production structure. Moreover, it is difficult to simultaneously reduce the NPS nitrogen and phosphorus pollution loads and REC in each subbasin. The model, which can provide policy makers with a series of schemes for optimization of land use pattern and livestock production structure, has satisfactory applicability and could be used for watershed NPS pollution management.
非点源(NPS)污染管理在流域水环境保护和生态安全中非常重要。然而,NPS 污染输出和管理过程中存在的许多复杂性和不确定性对多种管理实践的可靠性产生了重大影响。本研究通过优化流域土地利用格局和畜牧业生产结构,开发了一种用于 NPS 污染管理的不精确多目标可能性均值-方差混合整数规划(IMPMMP)模型。通过在一般可能性均值-方差模型框架内耦合区间参数规划、混合整数规划、多目标规划和排放系数模型,该 IMPMMP 模型有效地处理了系统不确定性和复杂性。此外,可以考虑 NPS 污染管理系统中超过标准的风险(REC)。将所提出的 IMPMMP 模型应用于中国南方新丰江水库流域的实际案例研究。结果表明,决策者对土地利用调整的偏好对确定模型可行性起着决定性作用。可调整的每种土地利用类型的面积必须达到一定的阈值,才能实现减少污染负荷和 REC 控制的目标。优化后的 NPS 污染负荷主要从不同的土地利用和人口中输出。与 NPS 氮污染管理相比,通过调整土地利用格局和畜牧业生产结构来减少 NPS 磷负荷和管理相应的 REC 更为困难。此外,在每个子流域中同时减少 NPS 氮和磷污染负荷和 REC 是困难的。该模型可以为决策者提供一系列优化土地利用格局和畜牧业生产结构的方案,具有令人满意的适用性,可用于流域 NPS 污染管理。