Evaluation of surface water quality in Heilongjiang Province, China: Based on different quantities of water quality indicators

被引:10
作者
Wei, Qi [1 ,2 ]
Wei, Qi [1 ,2 ]
Li, Siying [3 ]
Xu, Junzeng [1 ,2 ]
Yang, Zihan [3 ]
Liu, Zhenyang [1 ]
Chen, Peng [1 ]
Liu, Yuzhou [1 ]
Ding, Yimin [4 ]
Tan, Junyi [5 ]
Li, Jiuying [6 ]
机构
[1] Hohai Univ, Coll Agr Sci & Engn, Nanjing 210098, Peoples R China
[2] Hohai Univ, Jiangsu Prov Engn Res Ctr Agr Soil Water Efficient, Carbon Sequestrat & Emiss Reduct, Nanjing 210098, Peoples R China
[3] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Peoples R China
[4] Ningxia Univ, Sch Civil Engn & Water Conservancy, Yinchuan 750021, Peoples R China
[5] Jiangsu Environm Engn Technol Co Ltd, Nanjing 210036, Jiangsu, Peoples R China
[6] Heilongjiang Irrigat Drainage & Water Saving Techn, Harbin 150040, Peoples R China
关键词
Surface water quality grade; Improved Nemerow index method; Multiple regression model; Water quality grade calculation; Heilongjiang Province; PHYSICOCHEMICAL PARAMETERS; COMPREHENSIVE EVALUATION; EVALUATION MODEL; INDEX; OPTIMIZATION;
D O I
10.1016/j.ecolind.2023.110472
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Accurately evaluating surface water quality grade (WQG) is of great significance in improving the efficiency of regional water quality management. Based on seven main surface water quality indicators (including dissolved oxygen (DO), chemical oxygen demand (COD), permanganate index (CODMn), ammonia nitrogen (NH4+-N), fluoride (FL), total phosphorus (TP) and total nitrogen (TN)) data from 910 measuring points in Heilongjiang Province from May to August 2017, an improved Nemerow index method (IN method) based on combined weighting was constructed, and the WQG was evaluated. On this basis, the multiple linear or non-linear regression models (MLR or MNR) under different quantities of water quality indicators were established, and the prediction results were evaluated. Results show that: 1) WQG in Heilongjiang Province above grade III accounts for more than 92.6%, evaluated by the IN method; 2) The accuracy of WQG evaluated by MLR based on different quantities of water quality indicators are maintained at 77%-90% and decreases with the increase of the number of water quality indicators (N), which may be related to the selected combination of water quality indicators and key water pollutants. The accuracy is improved by 3.9%-17.4% for MNR as compared to MLR, and especially the accuracy can reach as high as 95.6% when N is 5; 3) Compare to the MLR, the MNR is less affected by the data fluctuation characteristics, and performs best when N is 5 under both the great and small data fluctuations, with an accuracy of 85% and 90%, respectively. 4) TN (0.72), NH4+-N (0.41), and CODMn (0.33) are significantly related to the WQG. COD is a key parameter affecting the stability and uncertainty of MLR and MNR. These results provide a simple and reliable method for accurately evaluating the surface WQG, which have important guiding significance for decision-makers and researchers in water environment protection and agricultural water fertilizer management in Heilongjiang Province.
引用
收藏
页数:11
相关论文
共 60 条
[1]  
Bhardwaj S.K., 2019, J SOIL WATER CONSERV, V18, P275
[2]   Surface water quality assessment by environmetric methods [J].
Boyacioglu, Huelya ;
Boyacioglu, Hayal .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 2007, 131 (1-3) :371-376
[3]   Comparative analysis of water quality and toxicity assessment methods for urban highway runoff [J].
Chen, Rui-Hong ;
Li, Fei-Peng ;
Zhang, Hai-Ping ;
Jiang, Yue ;
Mao, Ling-Chen ;
Wu, Ling-Ling ;
Chen, Ling .
SCIENCE OF THE TOTAL ENVIRONMENT, 2016, 553 :519-523
[4]   Analysis of Water Environment Quality Changes and Influencing Factors during the "Thirteenth Five-Year Plan" Period in Heilongjiang Province [J].
Chen, Wei ;
Bai, Yu ;
Li, Bo ;
Feng, Chengcheng ;
Zhou, Mi .
WATER, 2022, 14 (15)
[5]   Crop pattern optimization for the coordination between economy and environment considering hydrological uncertainty [J].
Chen, Yingshan ;
Zhou, Yan ;
Fang, Shiqi ;
Li, Mo ;
Wang, Yijia ;
Cao, Kaihua .
SCIENCE OF THE TOTAL ENVIRONMENT, 2022, 809
[6]   Development of a water quality assessment model: a water quality assessment model based on watershed characteristics by non-linear regression [J].
Cho, Yongdeok .
WATER SCIENCE AND TECHNOLOGY-WATER SUPPLY, 2015, 15 (02) :236-247
[7]  
Chu HB, 2013, J AGR SCI TECH-IRAN, V15, P343
[8]   Effects of Water Quality and Post-Harvest Handling on Microbiological Contamination of Lettuce at Urban and Peri-Urban Locations of Ouagadougou, Burkina Faso [J].
Dao, Juliane ;
Stenchly, Kathrin ;
Traore, Oumar ;
Amoah, Philip ;
Buerkert, Andreas .
FOODS, 2018, 7 (12)
[9]   Evaluation of water quality in the Chillan River (Central Chile) using physicochemical parameters and a modified Water Quality Index [J].
Debels, P ;
Figueroa, R ;
Urrutia, R ;
Barra, R ;
Niell, X .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 2005, 110 (1-3) :301-322
[10]   A Revised Method of Surface Water Quality Evaluation Based on Background Values and Its Application to Samples Collected in Heilongjiang Province, China [J].
Duan, Maoqing ;
Du, Xia ;
Peng, Wenqi ;
Zhang, Shijie ;
Yan, Linqing .
WATER, 2019, 11 (05)