Land use as an important indicator for water quality prediction in a region under rapid urbanization. (February 2023)

• Record Type: Journal Article
• Authors: Yao, Siyang; Chen, Cheng; He, Mengnan; Cui, Zhen; Mo, Kangle; Pang, Ruonan; Chen, Qiuwen
• Is Part Of: Ecological indicators. Volume 146(2023)
• Publication Date: 2023-02
• Subjects: Land use and land cover -- Rapid urbanization area -- River water quality -- Prediction -- Cellular automata-markov model; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2022.109768
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Land use is an effective indicator for water quality in rapidly urbanized areas. Multiple linear regression and CA–Markov models were combined to predict water quality. The land use-based prediction model performed fairly well for total nitrogen. Abstract: Land use and land cover (LULC) have significant impacts on river water quality, particularly in regions subjected to rapid urbanization. However, it is unclear whether LULC (LULC type and pattern index) can be used as an effective indicator to predict water quality over the rapid urbanization regions. Here, we investigated the spatiotemporal changes of LULC and their impacts on the water quality of a river flowing through a rapidly developed area in China. Then, a cellular automata-Markov model was established to predict the LULC, which was used as a key indicator to predict future water quality by a multiple linear regression model. The results showed that construction land experienced rapid growth between 2000 and 2010 taking over arable land to a great extent, and the number of patch (NP) showed a significant downward trend during 2000–2010. The biochemical oxygen demand in five days (BOD5 ), total nitrogen (TN), and total phosphorus (TP) exhibited significantly positive correlations with construction land, while dissolved oxygen (DO) showed a significantly negative correlation with construction land. The DO exhibited a significantly positive correlation with the number of patch (NP), but TN and TP showed significantly negative correlations with NP. The water quality prediction model based on LULC performed well, especially TN prediction has a coefficient of determination of 0.691 and a mean relative error of 12.14%. The prediction of water quality in 2030 indicated that TN will not increase further, but TP will exhibit a remarkable increase in Zhenjiang city if the current development trend continues and no extra pollution control measures are taken.