气候变化领域集成服务门户

Incorporating the structure and connectivity of the river network to seasonal variations and different land use patterns can help improve the understanding the complex relationship between water quality and environmental factors. The present study first employed the grey relational analysis (GRA) to examine any existing correlations between the water quality and the structure and connectivity of river networks in the Southern Jiangsu Plain in Eastern China. All grey relational degree results were greater than the distinguishing coefficient (rho - 05), and their average value was 07551. The average grey relational degrees of the water quality parameters varied between 0.7389 and 0.7744, and those of the characteristic indicators of the river network ranged from 0.6874 to 0.8850. Seasonal variations and different land use patterns were then employed to further analyze these relationships. The average grey relational degrees in the urban, rural, and fringe regions were calculated to be 0.7231, 0.7530, and 0.7124 during the flood season, respectively, and 0.7331, 0.7432, and 0.7052 during the non-flood season. The results suggest strong correlations between the water quality and the structure and connectivity of the river network. The preponderance of the urban land weakened the original correlations more than that of the cultivated land, while the seasonal interactions of the cultivated and urban lands presented opposite. The GRA can be employed as an effective supplement for numerical modeling and statistical analysis of the incomplete data. In addition, the structure and connectivity of the river network should be taken in account to improve water quality. (C) 2019 Elsevier B.V. All rights reserved.