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Environmental science and pollution research international
Mar, 2022;29 (12): 18103-18115.

Evaluation of water quality and its driving forces in the Shaying River Basin with the grey relational analysis based on combination weighting.

Jie Tao, Xin-Hao Sun, Yang Cao, Min-Hua Ling
Author Information
  1. Jie Tao: School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou, 450001, China.
  2. Xin-Hao Sun: School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou, 450001, China.
  3. Yang Cao: School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou, 450001, China.
  4. Min-Hua Ling: School of Water Conservancy Engineering, Zhengzhou University, Zhengzhou, 450001, China. qwe2818358@163.com. ORCID
PMID: 34677767 DOI: 10.1007/s11356-021-16939-z

Abstract

The water quality of the Shaying River Basin and even the entire Huai River Basin has been widely concerned. Based on the water quality data acquired in flood and non-flood seasons from 2012 to 2016, the Shaying River Basin was selected as the research object. First, the principal component analysis method was used to identify the main pollution indices. Then, grey relational analysis combined with an analytic hierarchy process and entropy weight method was used to evaluate the water quality of the upper, middle, and lower reaches of the Shaying River Basin, while the single factor evaluation method was used for comparative analysis. Finally, the driving forces of water quality were analyzed and discussed from natural and human aspects. The results show that the main pollutants in the Shaying River Basin are total nitrogen, total phosphorus, and ammonium nitrogen. While the basin is seriously polluted by nitrogen and phosphorus, the spatial and temporal distribution of the pollution varies, although the overall trend toward improving water quality conditions is significant. The midstream region had the poorest water quality, which fluctuated between Classes III and V. The downstream region had generally good water quality, which could be ranked as Class III most of the time. And the upstream region had the best water quality with well-developed ecological conditions; all the water samples were ranked as Class I or II. The water quality improves significantly during the flood season when compared with that in the non-flood season. Seasonal climate variation, non-point source pollution emissions, the release of water from sluices and dams, and water resource management activities are the main reasons for the variations in water quality across the Shaying River Basin.

Keywords

Combination weighting Driving forces Grey relational analysis Shaying River Basin Water quality evaluation

References

  1. Alcayaga H, Palma S, Caamaño D, Mao L, Soto-Alvarez M (2019) Detecting and quantifying hydromorphology changes in a Chilean river after 50 years of dam operation. J S Am Earth Sci 93:253–266. https://doi.org/10.1016/j.jsames.2019.04.018
  2. Annys S, Ghebreyohannes T, Nyssen J (2020) Impact of hydropower dam operation and management on downstream hydrogeomorphology in semi-arid environments (Tekeze, Northern Ethiopia). Water 12(8):2237. https://doi.org/10.3390/w12082237 [DOI: 10.3390/w12082237]
  3. Anugrah DR, Sobriyah S, Handayani D (2017) Performance evaluation of Dimoro irrigation area based on Rating Scale Methods. Int J Sci Applied Sci 2(1):79–87. https://doi.org/10.20961/ijsascs.v2i1.16684
  4. Araujo JC, Dias FF (2021) Multicriterial method of AHP analysis for the identification of coastal vulnerability regarding the rise of sea level: case study in Ilha Grande Bay, Rio de Janeiro, Brazil. Nat Hazards 107:53–72. https://doi.org/10.1007/S11069-021-04573-4 [DOI: 10.1007/S11069-021-04573-4]
  5. Chen H, Zuo QT, Dou M, Ma JX (2014) Comprehensive experimental research on impacts of dam operation on water environment of polluted river. Acta Sci Circum 34:763–771
  6. Chong KL, Lai SH (2021) Review on dam and reservoir optimal operation for irrigation and hydropower energy generation utilizing meta-heuristic algorithms. IEEE Access 9:19488–19505 [DOI: 10.1109/ACCESS.2021.3054424]
  7. Deng JM (2021) Water quality level index (WLI) and its application in water quality assessment and early warning in coastal areas of southern Guangxi. Yangtze River 52:18–24
  8. Deniz GE, Oncel CH, Galip S (2021) Determination of water quality assessment in wells of the Göksu Plains using multivariate statistical techniques. Environ Forensics 22(1–2):172–188. https://doi.org/10.1080/15275922.2020.1834025 [DOI: 10.1080/15275922.2020.1834025]
  9. Ding TT, Du SL, Huang ZY, Wang ZJ, Zhang J, Zhang YH, Liu SS, He LS (2021) Water quality criteria and ecological risk assessment for ammonia in the Shaying River Basin, China. Ecotoxicol Environ Saf. https://doi.org/10.1016/J.ECOENV.2021.112141
  10. Fan GC, Zhong DH, Yan FG, Yue P (2016) A hybrid fuzzy evaluation method for curtain grouting efficiency assessment based on an AHP method extended by D numbers. Expert Sys Appl 44:289–303. https://doi.org/10.1016/j.eswa.2015.09.006 [DOI: 10.1016/j.eswa.2015.09.006]
  11. Frediani JP, Medeiros MMM, de Castro RL, Walter C, Da PAR (2020) A modeling assessment of large-scale hydrologic alteration in South American pantanal due to upstream dam operation. Front Environ Sci. https://doi.org/10.3389/FENVS.2020.567450
  12. Gao HJ, Zheng LJ, Ji XY, Song YH, Han L, Lv CJ (2017) Study on comprehensive evaluation methods for surface water of typical cities. Environ Monit China 33:55–60
  13. Getirana A, Jung HC, Van Den Hoek J, Ndehedehe CE (2020) Hydropower dam operation strongly controls Lake Victoria’s freshwater storage variability. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2020.138343
  14. Guo J, Wang CM, Huang DZ, Li LQ, Lian H (2019) Pollution characterization and water quality assessment of Dongting Lake. Environ Chemistry 38:152–160
  15. Han SX, Wang LH, Zhao CS (2017) Applicability and modifications of the Nemerow index method in evaluating environmental quality. Journal of Agro-Environment Science 36:2153–2160
  16. Hao SN, Dong F (2019) Changing characteristics of the water quality along the Niyang River based on multivariate analysis method. Journal of Irrigation and Drainage 38:109–114
  17. He B, He J, Wang L, Zhang X, Bi E (2019) Effect of hydrogeological conditions and surface loads on shallow groundwater nitrate pollution in the Shaying River Basin: based on least squares surface fitting model. Water Res 163:114880. https://doi.org/10.1016/j.watres.2019.114880
  18. Ivana K, Dušanka C, Đorđe O, Maja N, Djuradj M, Dragan S, Mirjana V, Snežana R (2021) Water quality and macrophytes in the Danube river: artificial neural network modelling. Ecol Indic. https://doi.org/10.1016/J.ECOLIND.2020.107076
  19. Jiang QQ, Fang Q, Zhang GC (2015) Assessment of geohazards risk based on new combined weight method. Journal of Natural Disasters 24:28–36
  20. Lang QL, Wang W, Gao CL (2020) Stability evaluation of deep foundation pit of metro based on grey correlation analysis with combined weights. Journal of Jilin University (Earth Science Edition) 50:1823–1832
  21. Li DF, Zuo QT (2012) Study on mechanism of water quality and quantity of heavy pollution river by dam regulating. Water Resources and Power 30:26–29
  22. Li DF, Zuo QT (2014) Effect simulation and regulation strategy of dam on heavily of polluted rivers. Yellow River 36:87–90
  23. Li X, Xiao GR, Cai SH (2019) Evaluation of water environmental sensitivity based on fuzzy analytic hierarchy process combined with web text. Journal of Geo-Information Science 21:1832–1844
  24. Li HM, Hou LL, Xu P (2020) Application of various water quality index methods in water quality evaluation of Xiajiang Reservoir. Yangtze River 51:32–36
  25. Liang X, Ju WH, Sun BW, Hu Z, Gao XP, Zhang J, Zhao JY (2021) Water quantity regulation of regional water network based on optimal selection of key gate dam. South-to-North Water Transfers and Water Science & Technology:1–13
  26. Liu X, Xue Y, Ji YP, Xu BD, Ren YP (2015) An assessment of water quality in the Yellow River estuary and its adjacent waters based on principal component analysis. China Environ Sci 35:3187–3192
  27. Liu Y, Ji ZY, Liu SJ, Ye CB, Liu SJ, Li L (2020) Application and comparison of three methods in water quality evaluation of plateau lakes. J Oceanol Limnol 2:166–174
  28. Luo J, Chen C, Xie J (2015) Multi-objective immune algorithm with preference-based selection for reservoir flood control operation. Water Resour Manag 29(5):1447–1466. https://doi.org/10.1007/s11269-014-0886-6 [DOI: 10.1007/s11269-014-0886-6]
  29. Ma Y, Wang J (2015) Study on improved grey relational analysis method and its application in water quality evaluation of lake-type wetland. Water Saving Irrigation 4:70–73
  30. Maryam I, Mahmudul HM, Fernando BL, Kent M, Zoran K (2021) A novel machine learning application: water quality resilience prediction model. Sci Total Environ. https://doi.org/10.1016/j.scitotenv.2020.144459
  31. Ni J, Yu BY, Gu LH, Li JB (2018) Math-model of flood control and anti-pollution scheduling for mid-reach of Huaihe River during flood and non-flood seasons. Water Resources and Hydropower Engineering 49:136–143
  32. Ning ZR, Li HB (2020) Assessment and analysis of water quality in Ningxia section of the Yellow River based on comprehensive water quality identification index. Journal of Irrigation and Drainage 39:56–61
  33. Qi MX, Wang HP, Chen J (2017) Decomposition of Phragmites australis and Typha angustifolia and their effects on the water quality in winter and spring. Journal of Lake Sciences 29:420–429 [DOI: 10.18307/2017.0218]
  34. Rai SP, Sharma N, Lohani AK (2014) Risk assessment for transboundary rivers using fuzzy synthetic evaluation technique. J Hydrol 519:1551–1559. https://doi.org/10.1016/j.jhydrol.2014.08.060 [DOI: 10.1016/j.jhydrol.2014.08.060]
  35. Saha P, Paul B (2021) Identification of potential strategic sites for city planning based on water quality through GIS-AHP-integrated model. Environ Sci Pollut Res 28:23073–23086. https://doi.org/10.1007/S11356-020-12292-9 [DOI: 10.1007/S11356-020-12292-9]
  36. Samira S, Hossein S, Mohammad M, Parisa F, Hassan A (2020) Spatio-temporal variation of WQI, scaling and corrosion indices, and principal component analysis in rural areas of Marand. Groundw Sustain Dev, Iran, p 11. https://doi.org/10.1016/j.gsd.2020.100480
  37. Shi WW, Zhou JL, Zeng YY, Sun Y (2021) Multiple groundwater quality evalution of Urumqi-Changji-Shihezi city agglomeration in Xinjiang. J Arid Land Res Environ 35:109–116
  38. Sutadian AD, Muttil N, Yilmaz AG, Perera BJC (2017) Using the analytic hierarchy process to identify parameter weights for developing a water quality index. Ecolog Indic 75:220–233. https://doi.org/10.1016/j.ecolind.2016.12.043 [DOI: 10.1016/j.ecolind.2016.12.043]
  39. Wang H, Yao J, Li Y (2016) An analysis of water environment factors and an evaluation of water quantity of Liangzi Lake. J Geosci Environ Prot 4(7):44–51. https://doi.org/10.4236/gep.2016.47006
  40. Wang GL, Qiang Z, Cao C, Chen Y, Hao JY (2021a) Assessment of susceptibility to karst collapse based on geodetector and analytic hierarchy process: an example of Zhongliangshan area in Chongqing. Carsologica Sinica:1–10
  41. Wang R, Yang FX, Qu GM (2021b) Prediction model of agricultural non-point source water pollution based on grey correlation method. Nat Environ Pollut Technol 20(2):633–641. https://doi.org/10.46488/NEPT.2021.V20I02.021
  42. Wang XW, Liu ZQ, Qiong GQ, Li Y, Li KP, Zhang CY (2021c) Spatial-temporal distribution characteristics of water quality and analysis of pollution sources in Huangzhou River Basin of Guizhou Province. Environ Eng:1–10
  43. Wei GL, Yang ZF, Cui BS, Li B, Chen H, Bai JH, Dong SK (2009) Impact of dam construction on water quality and water self-purification capacity of the Lancang River China. Water Resour Manag 23(9):1763–1780. https://doi.org/10.1007/s11269-008-9351-8
  44. Won KJ, Won LH, Seok LY, Hyun CJ (2020) A study on the water quality relationship between continuous dam discharge and downstream in North Han River. J Korean Soc Water Environ 36(2):89–97
  45. Wu YJ, Ling R, Zhou JX, Zhang MX, Gao W (2021) Prediction of water quality based on artificial neural network. J Phys Conf Ser. https://doi.org/10.1088/1742-6596/1738/1/012066
  46. Xie JQ, You JJ, Jiang JY (2020) Function evaluation of shallow groundwater based on level difference maximization. Water Resour Prot:1–9
  47. Xing XR, Ma XS, Tian W, Wu ZX (2011) Two robust statistic techniques in proficiency testing by interlaboratory comparisons. Environ Monit China 27:4–8
  48. Yang Q, Tang QH, Zhang YY (2019) Spatiotemporal changes of water quality in Huai River Basin (Henan Section) and its correlation with land use patterns. Res Environ Sci 32:1519–1530
  49. Yang RJ, Wang YZ, Li XH, Zang Y, Sun MY (2021) Water quality evaluation and spatio-temporal variation characteristics of Guanting Reservoir. Water Resour Prot:1–10
  50. Yılmaz B, Özçelik C (2018) Evaluation of water quality monitoring networks using principal component analysis: a case of Gediz River Basin. Celal Bayar Üniversitesi Fen Bilimleri Dergisi 1:65–75 [DOI: 10.18466/cbayarfbe.356774]
  51. Yu WJ, Jia C, Di ST, Li K, Yuan H (2019) Groundwater quality assessment based on comprehensive weight and improved matter-element extension evaluation model. Journal of Jilin University (Earth Science Edition) 49:539–547
  52. Zhang YY, Xia J, Chen JF, Meng DJ (2010) Study on optimal dam operation of water quantity and quality based on a distributed SWAT model. Journal of Hydroelectric Engineering 29:159–164
  53. Zhang Q, Feng M, Hao X (2018) Application of Nemerow index method and integrated water quality index method in water quality assessment of Zhangze reservoir. IOP Conf Ser Earth Environ Sci. https://doi.org/10.1088/1755-1315/128/1/012160
  54. Zhang Q, Li GQ, Zhu Ge YS, Yu X, Tan HW, Qiang Du (2019) Application of improved fuzzy comprehensive method to water quality assessment in Erhai. Journal of China Institute of Water Resources and Hydropower Research 17:226–232
  55. Zheng BQ, Dou M, Huang LB, Zhao GJ (2012) Analysis of sluice operation impact on diversification in water quality. Environ Sci Technol 35:14–18
  56. Zhou M, Ma Z (2017) Improved comprehensive water quality identification index method and its application. Water Power 43:1–4
  57. Zhou J, Guan WS, Fu LT (2020) Water quality assessment and pollution source analysis of Xi’an River based on multivariate statistics. Water Resources Protection 36:79–84
  58. Zuo QT, Li DF (2013a) Research on regulation for pollution-control of dams on heavily polluted river base on the model of simulation and optimization. J Hydraul Eng 44:979–986
  59. Zuo QT, Li DF (2013b) Study on limited water level for pollution control of sluice and dam on heavily polluted river. Water Resources and Hydropower Engineering 44:22–26
  60. Zuo QT, Luo ZL, Shi YQ, Gan R, Liu J, Chen H (2016) Main parameters and physiographic characteristics of Shayinghe River Basin. Water Resources and Hydropower Engineering 47:66–72

Grants

  1. 51709238/innovative research group project of the national natural science foundation of china

MeSH Term

China
Environmental Monitoring
Humans
Phosphorus
Rivers
Water Pollutants, Chemical
Water Pollution
Water Quality

Chemicals

Water Pollutants, Chemical
Phosphorus
Journal Article

Word Cloud

Created with Highcharts 10.0.0waterqualityRiverBasinShayinganalysismethodusedmainpollutionrelationalforcesnitrogenregionfloodnon-floodgreyevaluationdrivingtotalphosphorusconditionsIIIrankedClassseasonweightingevenentireHuaiwidelyconcernedBaseddataacquiredseasons20122016selectedresearchobjectFirstprincipalcomponentidentifyindicescombinedanalytichierarchyprocessentropyweightevaluateuppermiddlelowerreachessinglefactorcomparativeFinallyanalyzeddiscussednaturalhumanaspectsresultsshowpollutantsammoniumbasinseriouslypollutedspatialtemporaldistributionvariesalthoughoveralltrendtowardimprovingsignificantmidstreampoorestfluctuatedClassesVdownstreamgenerallygoodtimeupstreambestwell-developedecologicalsamplesIIimprovessignificantlycomparedSeasonalclimatevariationnon-pointsourceemissionsreleasesluicesdamsresourcemanagementactivitiesreasonsvariationsacrossEvaluationbasedcombinationCombinationDrivingGreyWater

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