Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation

Author:

Zhu Kangwen12ORCID,Zhang Yan1,Tian Xiaosong13ORCID,Guan Dongjie1,Zhang Sheng2ORCID,He Yong1,Zhou Lilei1ORCID

Affiliation:

1. School of Smart City, Chongqing Jiaotong University, Chongqing 400074, China

2. Chongqing Academy of Eco-Environmental Sciences, Chongqing 401147, China

3. School of Resources and Safety Engineering, Chongqing Vocational Institute of Engineering, Chongqing 402260, China

Abstract

Analysis of the relationship between future land use change and agricultural non-point source pollution (ANPSP) evolution is vital to promoting sustainable regional development. By simulating future land use types, we can identify and analyze the evolution trend of ANPSP. This study takes Chongqing as a case study to establish an integrated solution based on the PLUS model, output coefficient model, and GIS technology. The solution can simulate data, identify trends, and identify key control areas under future development scenarios. The results show that the PLUS model can simulate land use types at the provincial scale with high accuracy, with a Kappa coefficient of around 0.9. The land use type changes show that urban expansion has occupied a large amount of cultivated land. From 2000 to 2020, the proportion of high-load areas with TN pollution load levels was 4.93%, 5.02%, and 4.73%, respectively. Under the two scenarios in 2030–2050, the number of high-load areas decreased, and the average load level decreased from west to east. Sensitivity analysis found that risk changes are more sensitive to the increase in fertilizer application. When the TN and TP output coefficients are increased, the number of towns with increased levels is greater than those with decreased levels when the output coefficients are decreased. Sensitivity analysis can better identify key pollution control areas. The areas sensitive to changes in farmers’ behavior are mainly the Hechuan District, Nanchuan District, Qijiang District, Jiangjin District, and Bishan District. This study provides data and decision-making support for rural green development and water environment improvement.

Funder

Chongqing Municipal Bureau of Science and Technology

National Natural Science Foundation of China Youth Science Fund Project

Chongqing Municipal Education Commission

Innovation Center for Green Intelligent Environmental Protection Technology and Equipment Technology in Chongqing

Chongqing Key Laboratory of Spatial and Temporal Information in Mountainous Cities

Publisher

MDPI AG

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