Management optimization of nonpoint source pollution considering the risk of exceeding criteria under uncertainty

Management of nonpoint source (NPS) pollution is highly important inwatershedwater environmental and ecological security. However, themany complexities and uncertainties that exist in the processes of export andmanagement 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 ofwatershed 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 Reservoirwatershed in South China. Results showed that the preference of decision makers regarding land use adjustment plays a decisive role in determiningmodel 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 theNPS nitrogen and phosphorus pollution loads and REC in each subbasin. Themodel, 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. (C) 2020 Elsevier B.V. All rights reserved.

Automated summary

A developed IMPMMP model effectively deals with system uncertainties and complexities in NPS pollution management, considering the risk of exceeding criteria in NPS pollution management systems. Results showed that decision maker preferences regarding land use adjustment are crucial, with optimized NPS pollution loads primarily from different land uses and human population.