期刊
HYDROLOGY RESEARCH
卷 52, 期 6, 页码 1184-1199出版社
IWA PUBLISHING
DOI: 10.2166/nh.2021.010
关键词
critical source areas; driving factors; export coefficient method; nonpoint source pollution; source factors; SWAT
资金
- China National Natural Science Foundation [41430318,41572222,41602262,41702261]
- National Key R&D Program of China [2016YFC0801800]
- Beijing Natural Science Foundation [8162036]
- Fundamental Research Funds for the Central Universities [2010YD02]
- Innovation Research Team Program of Ministry of Education [IRT1085]
- State Key Laboratory of Coal Resources and Safe Mining
The study identified CSAs in watersheds for NPS pollution management by integrating SWAT model and ECM method to quantify S factors. It found that using multi-factors with different weights was more accurate for CSA identification, providing a sound basis for future decision-making.
Identification of critical source areas (CSAs) is pivotal for the management of nonpoint source (NPS) pollution of watersheds. Most studies focus on source (S) factors and ignore the driving (D) factors of such pollution. The Soil and Water Assessment Tool (SWAT) model and the export coefficient method (ECM) were incorporated to quantify the S factors of ammonia nitrogen (NH4-N) and total phosphorus (TP) as NPS pollution. Specifically, S factors coupled with D factors, including precipitation, slope, soil and land use, were regarded as multi-factors. Moreover, the analytical hierarchy process (AHP) method was adopted to determine the respective weights of multi-factors after overlaying the factor maps to identify the CSAs. These CSAs accounted for 23.86% of the total area, and generated 54.94% of NH4-N and 42.59% of the TP loads. In contrast with single and multi-factors, we found that using multi-factors having differing weights was more accurate for identifying CSAs. Our study results indicate this approach is reasonable for CSAs' identification in watersheds, and it can provide insights into different pollution sources and migration, thus providing a sounder basis for future decision-making.
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