Analyzing Spatial Groundwater Salinity Using Multivariate Analysis and Multiple Linear Regression Models

Kristin Ina Binna, R. Yanidar, S. M. P. Marendra, Herika Muhammad Taki, A. D. Astuti
{"title":"Analyzing Spatial Groundwater Salinity Using Multivariate Analysis and Multiple Linear Regression Models","authors":"Kristin Ina Binna, R. Yanidar, S. M. P. Marendra, Herika Muhammad Taki, A. D. Astuti","doi":"10.23969/jcbeem.v8i1.12708","DOIUrl":null,"url":null,"abstract":"The increase in the amount of groundwater withdrawal will inevitably pose a threat of seawater intrusion. The purpose of this research was to identify the distribution of shallow groundwater salinity in North Jakarta, West Jakarta and Central Jakarta and to develop a regional model of shallow groundwater salinity distribution. The data used in this study was that of the groundwater quality monitoring, obtained from the Regional Environment Status Book (SLHD), published by The Environment office of Greater Jakarta released in 2022, involving a total of 121 sample points in North Jakarta, West Jakarta, and Central Jakarta. The primary data was taken at 6 (six) sampling locations for model validation purposes. The study began with data grouping, using the Hierarchical Cluster Analysis (HCA) method. The results of identifying the highest distribution of salinity are in cluster 3 (three). A model was subsequently developed, after removing the outliers, with multiple linear analysis methods using the variable the distance from the coastline (X1), well depth (X2) and hardness (X3), to determine the influence of EC, TDS and salinity distribution in shallow groundwater. The results obtained are as follows; EC Models: YEC3 = -1.879+ (1.19.X1) + (5.08.X3). TDS models: YTDS3 = -2.211.30 + (0.81.X1) + (101.41.X2) + (4.07.X3). Salinity models: Ysalinity3 = -0.07+ (6.75×10-5.X1) + (2.4×10-4.X3). Model verification results for R2EC3 = 0.70; R2TDS3 = 0.92; R2salinity3 = 0.88. Validation results produce 21.14% for EC, 8.21% for TDS, and 22.87% for Salinity. This needs further research by increasing the number of primary samples.","PeriodicalId":236852,"journal":{"name":"Journal of Community Based Environmental Engineering and Management","volume":"103 10","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Community Based Environmental Engineering and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23969/jcbeem.v8i1.12708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The increase in the amount of groundwater withdrawal will inevitably pose a threat of seawater intrusion. The purpose of this research was to identify the distribution of shallow groundwater salinity in North Jakarta, West Jakarta and Central Jakarta and to develop a regional model of shallow groundwater salinity distribution. The data used in this study was that of the groundwater quality monitoring, obtained from the Regional Environment Status Book (SLHD), published by The Environment office of Greater Jakarta released in 2022, involving a total of 121 sample points in North Jakarta, West Jakarta, and Central Jakarta. The primary data was taken at 6 (six) sampling locations for model validation purposes. The study began with data grouping, using the Hierarchical Cluster Analysis (HCA) method. The results of identifying the highest distribution of salinity are in cluster 3 (three). A model was subsequently developed, after removing the outliers, with multiple linear analysis methods using the variable the distance from the coastline (X1), well depth (X2) and hardness (X3), to determine the influence of EC, TDS and salinity distribution in shallow groundwater. The results obtained are as follows; EC Models: YEC3 = -1.879+ (1.19.X1) + (5.08.X3). TDS models: YTDS3 = -2.211.30 + (0.81.X1) + (101.41.X2) + (4.07.X3). Salinity models: Ysalinity3 = -0.07+ (6.75×10-5.X1) + (2.4×10-4.X3). Model verification results for R2EC3 = 0.70; R2TDS3 = 0.92; R2salinity3 = 0.88. Validation results produce 21.14% for EC, 8.21% for TDS, and 22.87% for Salinity. This needs further research by increasing the number of primary samples.
利用多元分析和多元线性回归模型分析空间地下水盐度
地下水开采量的增加将不可避免地带来海水入侵的威胁。本研究的目的是确定雅加达北部、雅加达西部和雅加达中部浅层地下水盐度的分布情况,并建立浅层地下水盐度分布的区域模型。本研究使用的数据来自地下水质量监测数据,这些数据来自大雅加达地区环境办公室于 2022 年发布的《地区环境状况手册》(SLHD),涉及雅加达北部、雅加达西部和雅加达中部共 121 个采样点。主要数据取自 6 个采样点,用于模型验证。研究首先使用层次聚类分析(HCA)方法对数据进行分组。结果发现盐度分布最密集的是第 3 组(3)。在剔除异常值后,使用多重线性分析方法,利用与海岸线的距离(X1)、水井深度(X2)和硬度(X3)变量,建立了一个模型,以确定 EC、TDS 和盐度分布对浅层地下水的影响。得出的结果如下: EC 模型YEC3 = -1.879+ (1.19.X1) + (5.08.X3).TDS 模型:YTDS3 = -2.211.30 + (0.81.x1) + (101.41.x2) + (4.07.x3)。盐度模型:Ysalinity3 = -0.07+ (6.75×10-5.X1) + (2.4×10-4.X3)。模型验证结果为 R2EC3 = 0.70;R2TDS3 = 0.92;R2salinity3 = 0.88。验证结果表明,EC 值为 21.14%,TDS 值为 8.21%,盐度值为 22.87%。这需要通过增加原始样本的数量来进一步研究。
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