Spatial Distribution of Non-point Source Pollution Ｒisk Based on PNPI and SWAT Model

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Spatial Distribution of Non-point Source Pollution Ｒisk Based on PNPI and SWAT Model

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[1]ZHENG Jiake,GAN ong,ZUO Qiting,et al.Spatial Distribution of Non-point Source Pollution Ｒisk Based on PNPI and SWAT Model[J].Journal of Zhengzhou University (Engineering Science),2023,44(03):22-29.[doi:10.13705/j.issn.1671-6833.2023.03.014]

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Journal of Zhengzhou University (Engineering Science)[ISSN 1671-6833/CN 41-1339/T] Volume: 44卷 Number of periods: 2023 03 Page number: 22-29 Column: Public date: 2023-04-30

Title:: Spatial Distribution of Non-point Source Pollution Ｒisk Based on PNPI and SWAT Model

Author(s):: ZHENG Jiake; GAN Ｒong; ZUO Qiting; YANG Feng; 1.School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou 450001, China; 2.Henan Key Laboratory of Groundwater Pollution Prevention and Rehabilitation, Zhengzhou University,Zhengzhou 450001, China; 3.Zhengzhou Key Laboratory of Water Resources and Water Environment, Zhengzhou University, Zhengzhou 450001, China; 4.Construction Management Company for Chushandian Reservoir of Project of Henan Pro-vince, Xinyang 464043, China

Keywords:: nitrogen and phosphorus pollution; potential non-point source pollution index model; output coefficient method; SWAT model; Yiluo River Basin

CLC:: X52

DOI:: 10.13705/j.issn.1671-6833.2023.03.014

Abstract:: In order to clarify the spatial distribution characteristics of non-point source nitrogen (N) and phosphorus (P) nutrient pollution risk in the watershed, the key non-point source pollution source areas in the watershed were identified. This study took the Yiluo River Basin as an example. The output coefficient method was used to quantify the N and P pollution loads generated by different land use types, residents′ lives and livestock breeding in the watershed. With the improved potential non-point pollution indicator (PNPI) model and SWAT (soil and water assessment tool) model, the spatial distribution characteristics of N and P pollution risk were described, and the key source areas of N and P pollution were identified. Pearson correlation coefficient method was used to calculate the correlation between the simulation results of the two models, and the reliability of the simulation results of the improved PNPI model was evaluated. The results showed that in 2020, the spatial distribution of N and P non-point source pollution risks in the Yiluo River Basin was similar. It showed the spatial distribution characteristics of lower pollution risks in the upper reaches of the Yi River and Luo River tributaries, and higher pollution risks in the middle and lower reaches. N and P very low, low, medium, high and extremely high risk areas accounted for 48.85%, 14.61%, 9.68%, 14.64%, 12.22% and 55.48%, 8.76%, 11.14%, 13.25%, 11.38% of the total area of Yiluo River, respectively. The output of land use was the main source of N and P pollution in the basin, with the load of 20 643.62 t/a and 3 033.31 t/a, respectively. Among different land use types, the output of N and P pollution from arable land was the most, which were 13 000.07 t/a and 1 956.44 t/a, respectively; the output of grassland produced the least N pollution, with a pollution load of 1 322.99 t/a. The P pollution of residential land was the least, and the pollution load was 113.61 t/a. The Pearson correlation coefficients between the N and P pollution loads simulated by the improved PNPI model and the SWAT model reached 0.6, indicating that the improved PNPI model was suitable for the study area.

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Last Update: 2023-05-08