Identifying and Classifying Pollution Hotspots to Guide Watershed Management in a Large Multiuse Watershed

Fangli Su, David Kaplan, Lifeng Li, Haifu Li, Fei Song and Haisheng Liu
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Fangli Su: College of Water Conversation, Shenyang Agricultural University, No. 120 Dongling Road, Shenyang 110866, China
David Kaplan: Engineering School of Sustainable Infrastructure and Environment, Department of Environmental Engineering Sciences, University of Florida, 6 Phelps Lab, Gainesville, FL 32611-6350, USA
Lifeng Li: College of Water Conversation, Shenyang Agricultural University, No. 120 Dongling Road, Shenyang 110866, China
Haifu Li: College of Water Conversation, Shenyang Agricultural University, No. 120 Dongling Road, Shenyang 110866, China
Fei Song: College of Water Conversation, Shenyang Agricultural University, No. 120 Dongling Road, Shenyang 110866, China
Haisheng Liu: College of Water Conversation, Shenyang Agricultural University, No. 120 Dongling Road, Shenyang 110866, China

IJERPH, 2017, vol. 14, issue 3, 1-14

Abstract: In many locations around the globe, large reservoir sustainability is threatened by land use change and direct pollution loading from the upstream watershed. However, the size and complexity of upstream basins makes the planning and implementation of watershed-scale pollution management a challenge. In this study, we established an evaluation system based on 17 factors, representing the potential point and non-point source pollutants and the environmental carrying capacity which are likely to affect the water quality in the Dahuofang Reservoir and watershed in northeastern China. We used entropy methods to rank 118 subwatersheds by their potential pollution threat and clustered subwatersheds according to the potential pollution type. Combining ranking and clustering analyses allowed us to suggest specific areas for prioritized watershed management (in particular, two subwatersheds with the greatest pollution potential) and to recommend the conservation of current practices in other less vulnerable locations (91 small watersheds with low pollution potential). Finally, we identified the factors most likely to influence the water quality of each of the 118 subwatersheds and suggested adaptive control measures for each location. These results provide a scientific basis for improving the watershed management and sustainability of the Dahuofang reservoir and a framework for identifying threats and prioritizing the management of watersheds of large reservoirs around the world.

Keywords: classification; water quality; watershed management; cluster analysis; Dahuofang reservoir; point source pollution; non-point source pollution (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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