The Relationship between Surface Water Quality and Watershed Characteristics

Amir Mohammadi, M. Vafakhah, M. Javadi
{"title":"The Relationship between Surface Water Quality and Watershed Characteristics","authors":"Amir Mohammadi, M. Vafakhah, M. Javadi","doi":"10.32732/JCEC.2019.8.3.107","DOIUrl":null,"url":null,"abstract":"The healthy water resources are necessary and essential prerequisite for environmental protection and economic development, political, social and cultural rights of Iran. In this research, water quality parameters i.e. total dissolved solids (TDS), sodium absorption rate (SAR), electrical conductivity (EC), Na+, Cl-, CO32-, K+, Mg2+, Ca2+, pH, HCO3- and SO42- during 2010-2011 were obtained from Iranian Water Resources Research Institute in water quality measurement stations on Mazandaran province, Iran. Then, the most important catchment characteristics (area, mean slope, mean height, base flow index, annual rainfall, land cover, and geology) were determined on water quality parameters using stepwise regression via backwards method in the 63 selected rivers. The results showed that sodium absorption rate (SAR), total dissolved solids (TDS), electrical conductivity (EC), Na+ and Cl- parameters are strongly linked to geology characteristics, while K+, Mg2+ and Ca2+ cations is linked to rainfall and geology characteristics. pH and HCO3- are related to area, rainfall, land cover and geology characteristics, CO32- is related to area, rainfall, rangeland area and geology characteristics and SO42- is related to area, rainfall, range and bar land area and geology characteristics. Adaptive Neuro-Fuzzy Inference System (ANFIS) was used for modeling the selected catchment characteristics and water quality parameters. The ANFIS models have a high Nash–Sutcliffe model efficiency coefficient (NSE)  and low root mean squares error (RMSE) to estimate water quality parameters.","PeriodicalId":243788,"journal":{"name":"Journal of Civil Engineering and Construction","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Civil Engineering and Construction","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32732/JCEC.2019.8.3.107","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The healthy water resources are necessary and essential prerequisite for environmental protection and economic development, political, social and cultural rights of Iran. In this research, water quality parameters i.e. total dissolved solids (TDS), sodium absorption rate (SAR), electrical conductivity (EC), Na+, Cl-, CO32-, K+, Mg2+, Ca2+, pH, HCO3- and SO42- during 2010-2011 were obtained from Iranian Water Resources Research Institute in water quality measurement stations on Mazandaran province, Iran. Then, the most important catchment characteristics (area, mean slope, mean height, base flow index, annual rainfall, land cover, and geology) were determined on water quality parameters using stepwise regression via backwards method in the 63 selected rivers. The results showed that sodium absorption rate (SAR), total dissolved solids (TDS), electrical conductivity (EC), Na+ and Cl- parameters are strongly linked to geology characteristics, while K+, Mg2+ and Ca2+ cations is linked to rainfall and geology characteristics. pH and HCO3- are related to area, rainfall, land cover and geology characteristics, CO32- is related to area, rainfall, rangeland area and geology characteristics and SO42- is related to area, rainfall, range and bar land area and geology characteristics. Adaptive Neuro-Fuzzy Inference System (ANFIS) was used for modeling the selected catchment characteristics and water quality parameters. The ANFIS models have a high Nash–Sutcliffe model efficiency coefficient (NSE)  and low root mean squares error (RMSE) to estimate water quality parameters.
地表水水质与流域特征的关系
健康的水资源是伊朗环境保护和经济发展以及政治、社会和文化权利的必要先决条件。本研究利用伊朗水资源研究所2010-2011年在伊朗Mazandaran省水质测量站采集的水质参数,即总溶解固形物(TDS)、钠吸收率(SAR)、电导率(EC)、Na+、Cl-、CO32-、K+、Mg2+、Ca2+、pH、HCO3-和SO42-。在此基础上,对63条河流的水质参数进行逐步回归,确定了流域最重要的流域特征(面积、平均坡度、平均高度、基流指数、年降雨量、土地覆盖和地质)。结果表明,钠吸收率(SAR)、总溶解固形物(TDS)、电导率(EC)、Na+和Cl-等参数与地质特征密切相关,而K+、Mg2+和Ca2+等阳离子则与降雨和地质特征密切相关。pH和HCO3-与面积、降雨、土地覆盖和地质特征有关,CO32-与面积、降雨、牧场面积和地质特征有关,SO42-与面积、降雨、牧场和沙洲面积和地质特征有关。采用自适应神经模糊推理系统(ANFIS)对选定的流域特征和水质参数进行建模。ANFIS模型对水质参数的估计具有较高的Nash-Sutcliffe模型效率系数(NSE)和较低的均方根误差(RMSE)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信