Prediction and optimization of regional land-use patterns considering nonpoint-source pollution control under conditions of uncertainty

• Published in: Journal of environmental management Vol. 306; p. 114432
• Main Authors: Rong, Qiangqiang, Zeng, Jingni, Su, Meirong, Yue, Wencong, Cai, Yanpeng
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 15-03-2022
• Subjects: China; Environmental Monitoring; Export coefficient model; Fuzzy parameter programming; Interval linear programming; Land-use management; Models, Theoretical; Nitrogen - analysis; Non-Point Source Pollution; Phosphorus - analysis; Rivers; System dynamics; Uncertainty; Water Pollutants, Chemical - analysis; China; Fuzzy parameter programming; System dynamics; Interval linear programming; Export coefficient model; Land-use management
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2022.114432

Socioeconomic development, leading to significant changes in land-use patterns, has further influenced the output of regional nonpoint-source (NPS) pollution. Multiple uncertainties exist in the processes of land-use changes and NPS pollution export. These uncertainties can deeply affect the management of regional land-use patterns and control of NPS pollution. In this research, an integrated land-use prediction and optimization (ILUPO) model based on system dynamics, export coefficient, interval linear programming, and fuzzy parameter programming models was proposed. The ILUPO model can provide future land-use patterns and NPS pollution loads, and also help optimize the patterns under multiple pollution reduction scenarios. Interval and fuzzy uncertainties in the processes of land-use changes and NPS pollution output can be effectively addressed. The developed model was applied to a water source area in the central part of northern Guangdong Province in South China. For the prediction period 2020–2030 under the high-speed development scenario, results show that cropland area would decrease, while grassland and waterbody areas would increase. In contrast, these three types of land-use would show opposite variation trends under the low-speed development scenario. Construction land area would decrease, while forestland area would increase under both the low-speed and high-speed development scenarios. Variation of the predicted land-use patterns would lead to an increase of total nitrogen loads under each of the scenario, while the total phosphorus loads would show relatively complex variation trends. Regional land-use patterns should be further optimized to mitigate NPS pollution. However, the pollution loads in the study area cannot be reduced by >5% through land-use adjustment. Because cropland would still be the critical source of NPS pollution after optimization, strictly controlling the areas of cropland would be important for the management of such pollution in the research area. In addition, certain areas of grassland and waterbody would need to be converted into cropland and construction land to balance the economic benefit of the system and NPS pollution control. Multiple results obtained from the model under different scenarios of pollution reduction targets and α-cut levels can provide decision-making supports for the local policy makers. The developed ILUPO model can yield insights useful for the planning and adjustment of regional land-use patterns while considering NPS pollution control under conditions of uncertainty.
•An integrated model is proposed for land-use prediction and optimization.•System dynamics of land-use patterns affected by multiple factors can be reflected.•Uncertainties in land-use change and NPS pollution export processes can be addressed.•Optimal land-use patterns can be obtained to support land-use decision-making.