Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 807, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2021.151726
Keywords
Source-sink theory; Landscape contrast index; NPS pollution risk; land use pattern; Environmental impact
Categories
Funding
- National Science Fund for Distinguished Young Scholars [52125901]
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In this study, a multi-factor NPS risk assessment model NSPRI based on the source-sink landscape theory was proposed and applied in Muzhuhe River Basin, Shandong, China. The results showed that the method could effectively assess spatial and temporal variations in the risks from nitrogen and phosphorus losses, providing scientific support for NPS pollution control from the perspective of source-sink landscape theory.
In watershed management, it is of great importance to evaluate the risks of nonpoint source (NPS) pollution. In this study, the Nonpoint Source Pollution Risk Index (NSPRI), a multi-factor NPS risk assessment model that was based on the source-sink landscape theory, was proposed and applied in Muzhuhe River Basin, Shandong, China to (1) highlight spatial and temporal variations in the risks from nitrogen and phosphorus losses, and (2) identify how the basin characteristics influenced the risk of nutrient loss. According to the analysis on land use change, the study area is featured with high proportions of forest and agricultural land uses; the area of urban and industrial land had increased considerably from 2000 and 2018. Based on the division of the calculated risk indices on subbasin scale, the area with extremely high risks has decreased from 56,442 ha to 43,922 ha. The average and coefficient of variation (CV) values of NSPRI in the river basin have dropped from 1.3 to 1.1, and from 78.2% to 48.9%, respectively. The distribution of NSPRI suggested an increase in spatial clustering and improvements in the ecological balance. Correlation analysis of the Soil and Water Assessment Tool (SWAT) model (R-2 > 0.68, ENS > 0.59) and NSPRI indicated the applicability of the method used (r > 0.84, p < 0.01). Analysis on the impact of metrics of land use composition, landscape, and environmental settings on NSPRI indicated that the water quality was more significantly correlated with land use composition, landscape pattern and vegetation cover than with flow path distance, soil erodibility, and rainfall erosivity. Moreover, results of redundancy analysis revealed that nutrient loss risk was better explained by land use compositions than by landscape configuration. The assessment method provided scientific support for NPS pollution control from the perspective of source-sink landscape theory.
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