基于SWAT模型的浑太河流域非点源氮磷污染负荷分布模拟研究
SWAT-Based Modeling of Spatiotemporal Variations in Non-Point Source Nitrogen and Phosphorus Loads in the Huntai River Basin
DOI: 10.12677/aep.2025.1511168, PDF,   
作者: 欧阳婉盈:辽宁师范大学地理科学学院,辽宁 大连
关键词: 氮磷SWAT非点源浑太河Nitrogen and Phosphorus SWAT Model Non-Point Source Pollution Huntai River Basin
摘要: 非点源与城市污水排放的复合输入显著加剧流域富营养化风险。以浑太河流域为例,应用SWAT模型模拟分析流域非点源氮磷污染的时空分布特征。研究结果表明:(1) SWAT模型在率定期、验证期的R2Ens均大于0.7,说明模型在研究区具有较高适用性;(2) 时间分布:2010~2022年间TN和TP总体负荷呈下降趋势,年内变化表现为“汛期高、非汛期低”的特征。(3) 空间分布:TN和TP的高值区主要分布在上中游及库区周边,下游地区负荷相对较低。进一步分析表明,土地利用变化对氮磷输出具有显著影响:耕地和建设用地是流域氮磷输出的主要“源区”,而林地、草地与水域则发挥“汇区”功能,有效削减非点源污染。本研究揭示了浑太河流域非点源氮、磷污染的时空格局及其驱动机制,可为流域水环境管理提供科学依据。
Abstract: The combined input of non-point sources and urban sewage discharge significantly exacerbates the risk of eutrophication in river basins. Taking the Huntai River Basin as an example, the SWAT model was applied to simulate and analyze the temporal and spatial distribution characteristics of non-point source nitrogen and phosphorus pollution in the basin. The research results indicate that: (1) The R2 and Ens values of the SWAT model during the calibration and validation periods are both greater than 0.7, suggesting that the model has high applicability in the study area. (2) Temporal distribution: From 2010 to 2022, the overall loads of total nitrogen (TN) and total phosphorus (TP) showed a downward trend, and the intra-annual variation was characterized by “high during the flood season and low during the non-flood season”. (3) Spatial distribution: The high-value areas of TN and TP are mainly distributed in the upper and middle reaches and around the reservoir area, while the loads in the downstream area are relatively low. Further analysis shows that land-use changes have a significant impact on nitrogen and phosphorus output: cultivated land and construction land are the main “source areas” of nitrogen and phosphorus output in the basin, while forest land, grassland, and water areas function as “sink areas”, effectively reducing non-point source pollution. This study reveals the temporal and spatial patterns and driving mechanisms of non-point source nitrogen and phosphorus pollution in the Huntai River Basin, providing a scientific basis for water environment management in the basin.
文章引用:欧阳婉盈. 基于SWAT模型的浑太河流域非点源氮磷污染负荷分布模拟研究[J]. 环境保护前沿, 2025, 15(11): 1541-1552. https://doi.org/10.12677/aep.2025.1511168

参考文献

[1] 解鑫, 尤佳艺, 李文攀, 等. 2011-2021年全国地表水环境质量评价与变化分析[J]. 中国环境监测, 2023, 39(4): 23-32.
[2] 第二次全国污染源普查公报[J]. 环境保护, 2020, 48(18): 8-10.
[3] 涂小强, 傅春. 非点源污染研究发展演化与前沿分析[J]. 人民长江, 2021, 52(4): 47-54.
[4] Du, X., Li, X., Zhang, W. and Wang, H. (2014) Variations in Source Apportionments of Nutrient Load among Seasons and Hydrological Years in a Semi-Arid Watershed: GWLF Model Results. Environmental Science and Pollution Research, 21, 6506-6515. [Google Scholar] [CrossRef] [PubMed]
[5] Wang, K., Wang, P., Zhang, R. and Lin, Z. (2020) Determination of Spatiotemporal Characteristics of Agricultural Non-Point Source Pollution of River Basins Using the Dynamic Time Warping Distance. Journal of Hydrology, 583, Article ID: 124303. [Google Scholar] [CrossRef
[6] Shen, Z., Liao, Q., Hong, Q. and Gong, Y. (2012) An Overview of Research on Agricultural Non-Point Source Pollution Modelling in China. Separation and Purification Technology, 84, 104-111. [Google Scholar] [CrossRef
[7] Romagnoli, M., Portapila, M., Rigalli, A., Maydana, G., Burgués, M. and García, C.M. (2017) Assessment of the SWAT Model to Simulate a Watershed with Limited Available Data in the Pampas Region, Argentina. Science of the Total Environment, 596, 437-450. [Google Scholar] [CrossRef] [PubMed]
[8] Busteed, P.R., Storm, D.E., White, M.J. and Stoodley, S.H. (2009) Using SWAT to Target Critical Source Sediment and Phosphorus Areas in the Wister Lake Basin, Usa. American Journal of Environmental Sciences, 5, 156-163. [Google Scholar] [CrossRef
[9] Huang, Y., Huang, J., Ervinia, A., Duan, S. and Kaushal, S.S. (2021) Land Use and Climate Variability Amplifies Watershed Nitrogen Exports in Coastal China. Ocean & Coastal Management, 207, Article ID: 104428. [Google Scholar] [CrossRef
[10] Li, Q., Zhang, J., Zhang, J., Gao, H., Chen, W., Huang, J., et al. (2023) Spatial and Temporal Distribution Characteristics and Prediction Analysis of Nitrogen and Phosphorus Surface Source Pollution in Shandong Province under the Climate and Land Use Changes. Frontiers in Ecology and Evolution, 11, Article 1231394. [Google Scholar] [CrossRef
[11] Bihon, Y.T., Lohani, T.K., Ayalew, A.T., Neka, B.G., Mohammed, A.K., Geremew, G.B., et al. (2024) Performance Evaluation of Various Hydrological Models with Respect to Hydrological Responses under Climate Change Scenario: A Review. Cogent Engineering, 11, Article ID: 2360007. [Google Scholar] [CrossRef
[12] Moriasi, D.N., Gitau, M.W., Pai, N., et al. (2015) Hydrologic and Water Quality Models: Performance Measures and Evaluation Criteria. Transactions of the ASABE, 58, 1763-1785
[13] Wu, L., Long, T., Liu, X. and Guo, J. (2012) Impacts of Climate and Land-Use Changes on the Migration of Non-Point Source Nitrogen and Phosphorus during Rainfall-Runoff in the Jialing River Watershed, China. Journal of Hydrology, 475, 26-41. [Google Scholar] [CrossRef
[14] 马东, 杜志勇, 吴娟, 等. 强降雨下农田径流中溶解态氮磷的输出特征——以崂山水库流域为例[J]. 中国环境科学, 2012, 32(7): 1228-1233.
[15] Withers, P.J.A. and Jarvie, H.P. (2008) Delivery and Cycling of Phosphorus in Rivers: A Review. Science of the Total Environment, 400, 379-395. [Google Scholar] [CrossRef] [PubMed]
[16] Yuan, X., Krom, M.D., Zhang, M. and Chen, N. (2021) Human Disturbance on Phosphorus Sources, Processes and Riverine Export in a Subtropical Watershed. Science of the Total Environment, 769, Article ID: 144658. [Google Scholar] [CrossRef] [PubMed]
[17] Lowrance, R., Todd, R., Fail, J., Hendrickson, O., Leonard, R. and Asmussen, L. (1984) Riparian Forests as Nutrient Filters in Agricultural Watersheds. BioScience, 34, 374-377. [Google Scholar] [CrossRef
[18] Camargos, C., Julich, S., Houska, T., Bach, M. and Breuer, L. (2018) Effects of Input Data Content on the Uncertainty of Simulating Water Resources. Water, 10, Article 621. [Google Scholar] [CrossRef
[19] Tan, M.L. and Yang, X. (2020) Effect of Rainfall Station Density, Distribution and Missing Values on SWAT Outputs in Tropical Region. Journal of Hydrology, 584, Article ID: 124660. [Google Scholar] [CrossRef
[20] Shen, Z.Y., Chen, L. and Chen, T. (2012) Analysis of Parameter Uncertainty in Hydrological and Sediment Modeling Using GLUE Method: A Case Study of SWAT Model Applied to Three Gorges Reservoir Region, China. Hydrology and Earth System Sciences, 16, 121-132. [Google Scholar] [CrossRef
[21] Wang, M., Chen, L., Wu, L., Zhang, L., Xie, H. and Shen, Z. (2022) Review of Nonpoint Source Pollution Models: Current Status and Future Direction. Water, 14, Article 3217. [Google Scholar] [CrossRef