Arid Zone Research ›› 2024, Vol. 41 ›› Issue (11): 1831-1841.doi: 10.13866/j.azr.2024.11.04

• Land and Water Resources • Previous Articles     Next Articles

Impacts of landscape patterns on surface water quality in the Liyuan River Basin

WANG Yu1,2(), LI Neng’an1, LUO Tianfeng3(), ZHANG Ying4, YUAN Xingpeng1, TIAN Miao1, XIN Yaling1, HU Feiyan1   

  1. 1. School of Energy and Power Engineering, Lanzhou University of Technology, Lanzhou 730050, Gansu, China
    2. Key Laboratory of Biomass Energy and Solar Energy Complementary Energy Supply System of Gansu Province, Lanzhou 730050, Gansu, China
    3. Water Conservancy Project Construction Cost and Fee Management Center, Gansu Provincial Water Conservancy Department, Lanzhou 730046, Gansu, China
    4. Gansu Provincial Water Environment Monitoring Centre, Lanzhou 730000, Gansu, China
  • Received:2024-08-07 Revised:2024-09-11 Online:2024-11-15 Published:2024-11-29
  • Contact: LUO Tianfeng E-mail:wangyu-mike@163.com;ltf871@163.com

Abstract:

Studying the degree and mechanism of landscape pattern’s influence on inland river water quality is of great significance for the water environment protection of inland river basins in arid areas. This study was based on the Liyuan River in Linze County. We studied landscape pattern data and measured water quality, using redundancy and correlation analyses to investigate the relationship between landscape patterns and water quality in different buffer zones. The water bodies in the study area generally met the Class II water quality standard, except for the average value of the chemical oxygen demand (CODCr) concentration, which fell into Class III. Additionally, the average dissolved oxygen (DO), total phosphorus (TP), permanganate index (CODMn), and ammonia nitrogen (NH3-N) concentration values met the Class II water quality standard. The buffer zone’s landscape composition was dominated by arable land, and construction land was the second largest type. Analyzing the landscape index revealed that the strength of human activities was not evenly distributed in the buffer zone, and the degree of human interference was the greatest in the 100 m buffer zone. The human interference degree in the 100 m buffer zone was the greatest. The proportion of cultivated land was significantly and positively correlated with DO, TP, electrical conductivity (EC), dissolved solids (TDS), and salinity, while constructed land was significantly and positively correlated with TP and NH3-N. The largest patch index (LPI) and contagion index (CONTAG) were positively correlated with the water quality indicators, whereas patch density (PD), edge density (ED), landscape shape index (LSI), and Shannon’s diversity index (SHDI) were negatively correlated. Redundancy analysis indicated that the explanatory rate of the changes in the water quality indicators by the composition of the landscape and landscape indices was the highest in the 300 m buffer zone. The analysis indicated that the explanatory rate of landscape composition and index on water quality index changes were the highest in the 300 m buffer zone, and the 300 m buffer zone was determined to be the optimal buffer scale for landscape pattern’s influence on the water quality index. Therefore, optimizing the landscape structure within the 300 m buffer zone to enhance the retention and adsorption capacity of pollutants can improve the water quality of the Liyuan River.

Key words: correlation analysis, landscape pattern, water quality, Liyuan River