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Updated: Sep 7, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
A holistic framework of water quality evaluation using water quality index (WQI) in the Yihe River (China)
Jiahui Qi1, Liyuan Yang2, Enfeng Liu3
1School of Water Conservancy and Environment, University of Jinan, Jinan, 250022, China.
Abstract:
The Yihe River is an important river in Shandong Province, China. It is a catchment river for the South-to-North Water Diversion Project (SNWDP-ER), providing a variety of benefits and ecosystem services, such as flood and drought regulation, fishery and aquaculture, drinking water sources, and biodiversity conservation. In order to objectively reflect the status and changing trend of water environmental quality of the Yihe River, reduce the cost of detection, and improve the efficiency of water quality evaluation, samples were collected at 8 sampling sites in the 220 km main stream of the Yihe River from 2009 to 2019. The spatiotemporal variations of 10 water quality indicators were analyzed, including pH, water temperature (WT), dissolved oxygen (DO), 5-day biochemical oxygen demand (BOD5), chemical oxygen demand (COD), total phosphorus (TP), ammonia nitrogen (NH3-N), nitrate (NO3-N), fluoride (F-), and sulphate (SO42-). The water quality index (WQI) was used to evaluate the spatiotemporal water quality changes, and the minimum WQI (WQImin) model consisting of five key indicators, i.e., NH3-N, BOD5, DO, SO42-, and WT, was built by using stepwise multiple linear regression analysis. The results indicated that the water quality indicators in the Yihe River showed significant spatiotemporal variations. With the exception of the COD and TP, the other water quality indicators conformed to the Class I or II standards of China, indicating that the water quality of the Yihe River was better than most natural water bodies. Seasonally, the WQI was better in the autumn and higher in the upstream area compared to the downstream. The water quality remained at the "good" level. The weighted WQImin model performed well in evaluating water quality, with coefficient of determination (R2), mean square error (MSE), and percentage error (PE) values of 0.903, 3.05, and 1.70%, respectively.
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