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- W4220809218 abstract "Quantifying spatio-temporal variations of non-point source pollution (NSP) risk induced by land-use change provides insights into effective control of NSP through land-use optimization. However, there is a lack of efficient tools for assessing the variations of NSP risk under various land-use change scenarios. In this study, a framework, which couples the modified potential non-point pollution indicator (PNPI) model with the future land-use simulation (FLUS) model, was developed and applied for assessing the spatio-temporal variations of NSP risk caused by both historical and possible future land-use change in a rapidly urbanized basin (i.e., the upper Beiyun River basin, Beijing) during 1980–2030. The PNPI model is tested with monitored water quality data with an accuracy ratio of 0.75, and the FLUS model can accurately simulate land-use change in the basin (Kappa coefficient = 0.74). Due to rapid urbanization, the area of extremely high-risk zones of NSP went up, even though the area of farmlands decreased, and the area of green spaces increased during 1980–2020. The spatio-temporal variations of NSP risk are different in 2020–2030 under different land-use change scenarios. The ecological security scenario will slow down the growth rate of NSP risk, however, the total area of the extremely high-risk and high-risk zones will increase by 40.17 km2 in 2030 under the rapid urbanization scenario. Coupling the modified PNPI model with the FLUS model provides an efficient tool set to support future land-use planning for NSP control and to assess spatio-temporal variations of NSP risk caused by both historical and future land-use change in data-limited regions." @default.
- W4220809218 created "2022-04-03" @default.
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- W4220809218 date "2022-04-01" @default.
- W4220809218 modified "2023-10-08" @default.
- W4220809218 title "A framework to assess spatio-temporal variations of potential non-point source pollution risk for future land-use planning" @default.
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- W4220809218 doi "https://doi.org/10.1016/j.ecolind.2022.108751" @default.
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