Comprehensive Evaluation and Distribution Prediction of River Water Quality in One Typical Resource-Depleted City, Central China

Abstract

Access to clean and equitable water is vital to human survival and an essential component of a sustainable society. Using 59 monitoring sections, the water quality of 32 rivers in 12 river systems within two river basins in one resource-depleted city (Jiaozuo) was examined in four seasons to better comprehend the extent of river pollution, and the distribution prediction of main indexes was conducted. In total, 92% of the monitoring sections met the national standards. Overall, 12.5%, 62.5%, and 25% of samples met water quality standards III, IV, and V, respectively. The concentrations of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) ranged from 0.527 to 7.078, 0.001 to 1.789, and 0.53 to 799.25 mg/L, respectively. The Yellow River Basin has higher annual mean concentrations of total carbon (TC), TN, and total organic carbon (TOC) than the Haihe River Basin. The highest and lowest concentrations of specific water quality indices varied across seasons and rivers. Dashilao and Rongyou Rivers have the best water quality, while Dasha, Xin, and Mang Rivers have the worst. TN, TP, and NH4+-N concentrations in the Laomang River midstream were greater than those upstream and downstream. Statistically, significant positive associations were found between NH4+-N and TC, TOC, and COD (p < 0.025), where NH4+-N and COD influenced water quality the most. A significant positive relationship between COD and TP (p < 0.01) was observed. Overall, water quality values were highest in the summer and lowest in winter. The distribution prediction revealed TN, TP, NH4+-N, and COD showed significant regional differences. Household sewage, industrial sewage discharge, and agricultural contamination were all the possible significant contributors to declining water quality. These findings could provide a scientific reference for river water resource management in resource-depleted cities.