Will urban expansion lead to an increase in future water pollution loads?—a preliminary investigation of the Haihe River Basin in northeastern China
2014
Dong, Yang | Liu, Yi | Chen, Jining
Urban expansion is a major driving force changing regional hydrology and nonpoint source pollution. The Haihe River Basin, the political, economic, and cultural center of northeastern China, has undergone rapid urbanization in recent decades. To investigate the consequences of future urban sprawl on nonpoint source water pollutant emissions in the river basin, the urban sprawl in 2030 was estimated, and the annual runoff and nonpoint source pollution in the Haihe River basin were simulated. The Integrated Model of Non-Point Sources Pollution Processes (IMPULSE) was used to simulate the effects of urban sprawl on nonpoint source pollution emissions. The outcomes indicated that the urban expansion through 2030 increased the nonpoint source total nitrogen (TN), total phosphorous (TP), and chemical oxygen demand (COD) emissions by 8.08, 0.14, and 149.57 kg/km², respectively. Compared to 2008, the total nonpoint emissions rose by 15.33, 0.57, and 12.39 %, respectively. Twelve percent of the 25 cities in the basin would increase by more than 50 % in nonpoint source TN and COD emissions in 2030. In particular, the nonpoint source TN emissions in Xinxiang, Jiaozuo, and Puyang would rise by 73.31, 67.25, and 58.61 %, and the nonpoint source COD emissions in these cities would rise by 74.02, 51.99, and 53.27 %, respectively. The point source pollution emissions in 2008 and 2030 were also estimated to explore the effects of urban sprawl on total water pollution loads. Urban sprawl through 2030 would bring significant structural changes of total TN, TP, and COD emissions for each city in the area. The results of this study could provide insights into the effects of urbanization in the study area and the methods could help to recognize the role that future urban sprawl plays in the total water pollution loads in the water quality management process.
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