Scale Effects of Landscape Patterns on Nitrogen and Phosphorus Pollution in Yanshan River Basin, Guilin, China

Author:

Fang Zhongjie1,Fang Rongjie123,Xu Baoli123ORCID,Xue Pengwei1,Zou Chuanlin1,Huang Jianhua1,Xu Qinxue123,Dai Junfeng23

Affiliation:

1. School of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China

2. Guangxi Key Laboratory of Environmental Pollution Control Theory and Technology, Guilin 541004, China

3. Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Areas, Guilin 541004, China

Abstract

Changes in land use and landscape patterns significantly influence watershed water quality by affecting non-point source (NPS) pollution processes. Understanding the characteristics of water quality and the relationships between landscape patterns and water quality is crucial to informing land-use planning aimed at ensuring water security. In this study, we employed landscape index methods, correlation analysis, and redundancy analysis based on monitored water quality data and land-use types relative to the Yanshan River Basin, Guilin, China. The results show the following features: (1) Water quality in the small watershed exceeded the values of class III during the study period, and total nitrogen (TN) was the main pollutant, with a pollution load ratio reaching 67.9%. (2) Water quality was significantly impacted by the landscape patterns of the small watershed river. The monitored concentrations of TN, ammonia nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), and total phosphorus (TP) were negatively correlated with the proportion of forest area, and the concentrations of NH4+-N and TP were positively correlated with the proportions of building, orchard, and cultivated land areas. Moreover, the influences of landscape patterns during the wet seasons on water quality were stronger than those during the dry seasons. (3) The total interpretation rates of the landscape indices for the water quality indices in the dry and wet seasons were 96.7% and 94.4%, respectively. Moreover, the largest patch and aggregation indices of the building area were the most effective variables in explaining the water quality indices, with contribution rates of 30.8% and 23.2% in the dry seasons and 34.3% and 23.8% in the wet seasons, respectively. By analyzing these relationships, in this study, we obtained insights into how different landscape patterns contribute to variations in water quality. The findings contribute to sustainable land-use planning strategies that aim to mitigate the impacts of land-use changes on water resources.

Funder

Natural Science Foundation of Guangxi, China

Science and Technology Major Project of Guangxi, China

Foundation of Key Laboratory of Guangxi

Guilin University of Technology Foundation

Publisher

MDPI AG

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