Estimating Hydraulic Conductivity Fields in Composite Fan Delta Using Vertical Electrical Sounding
Hydraulic conductivity (K) is crucial for groundwater studies and is conventionally obtained through pumping tests, which are costly due to well installation, resulting in a limited amount of data. Recent studies have addressed this limitation by estimating K through the integration of a pumping-tes...
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description | Hydraulic conductivity (K) is crucial for groundwater studies and is conventionally obtained through pumping tests, which are costly due to well installation, resulting in a limited amount of data. Recent studies have addressed this limitation by estimating K through the integration of a pumping-test K and electrical resistivity measurements. While this approach is suitable for local areas, it cannot readily be applied to determine K fields for the composite fan delta. This study proposes and demonstrates an advanced method to estimate the K’s spatial distribution of a composite fan delta. The proposed method included data classification, linear regression, and kriging interpolation. Data classification was conducted using a physical-based zonation method. The K and formation factor (F) data pairs were classified into several groups. Linear regression was used to develop K-F mapping for each group. The regression results showed a good correlation between K and F in each group. These K-F mappings were verified by additional pumping tests. These results indicate that estimation errors were between 7 m/day and 58 m/day, and the correlation coefficient of each data group was greater than 0.8. Based on these regression equations and ordinary kriging method, the detailed K spatial distribution of the study area was derived. According to these results, the proposed method is efficient and economical to delineate K’s spatial features for regional groundwater systems and can benefit groundwater-related studies. |
doi_str_mv | 10.3390/w10111620 |
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Recent studies have addressed this limitation by estimating K through the integration of a pumping-test K and electrical resistivity measurements. While this approach is suitable for local areas, it cannot readily be applied to determine K fields for the composite fan delta. This study proposes and demonstrates an advanced method to estimate the K’s spatial distribution of a composite fan delta. The proposed method included data classification, linear regression, and kriging interpolation. Data classification was conducted using a physical-based zonation method. The K and formation factor (F) data pairs were classified into several groups. Linear regression was used to develop K-F mapping for each group. The regression results showed a good correlation between K and F in each group. These K-F mappings were verified by additional pumping tests. These results indicate that estimation errors were between 7 m/day and 58 m/day, and the correlation coefficient of each data group was greater than 0.8. Based on these regression equations and ordinary kriging method, the detailed K spatial distribution of the study area was derived. According to these results, the proposed method is efficient and economical to delineate K’s spatial features for regional groundwater systems and can benefit groundwater-related studies.</description><identifier>ISSN: 2073-4441</identifier><identifier>EISSN: 2073-4441</identifier><identifier>DOI: 10.3390/w10111620</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Aquifers ; Classification ; Correlation coefficient ; Correlation coefficients ; Electrical resistivity ; Geology ; Groundwater ; Groundwater studies ; Hydraulics ; Hydrogeology ; Kriging interpolation ; Pumping ; Pumping tests ; Regional development ; Rivers ; Sediments ; Spatial distribution ; Water, Underground ; Zonation</subject><ispartof>Water (Basel), 2018-11, Vol.10 (11), p.1620</ispartof><rights>COPYRIGHT 2018 MDPI AG</rights><rights>2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-b40ef3cecb899722558598a5c6da149c9179e38153e8c75813133e8ec10759b23</citedby><cites>FETCH-LOGICAL-c331t-b40ef3cecb899722558598a5c6da149c9179e38153e8c75813133e8ec10759b23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><creatorcontrib>Chen, You-Cheng</creatorcontrib><creatorcontrib>Tsai, Jui-Pin</creatorcontrib><creatorcontrib>Chang, Liang-Cheng</creatorcontrib><creatorcontrib>Chang, Ping-Yu</creatorcontrib><creatorcontrib>Lin, Helen</creatorcontrib><title>Estimating Hydraulic Conductivity Fields in Composite Fan Delta Using Vertical Electrical Sounding</title><title>Water (Basel)</title><description>Hydraulic conductivity (K) is crucial for groundwater studies and is conventionally obtained through pumping tests, which are costly due to well installation, resulting in a limited amount of data. Recent studies have addressed this limitation by estimating K through the integration of a pumping-test K and electrical resistivity measurements. While this approach is suitable for local areas, it cannot readily be applied to determine K fields for the composite fan delta. This study proposes and demonstrates an advanced method to estimate the K’s spatial distribution of a composite fan delta. The proposed method included data classification, linear regression, and kriging interpolation. Data classification was conducted using a physical-based zonation method. The K and formation factor (F) data pairs were classified into several groups. Linear regression was used to develop K-F mapping for each group. The regression results showed a good correlation between K and F in each group. These K-F mappings were verified by additional pumping tests. These results indicate that estimation errors were between 7 m/day and 58 m/day, and the correlation coefficient of each data group was greater than 0.8. Based on these regression equations and ordinary kriging method, the detailed K spatial distribution of the study area was derived. According to these results, the proposed method is efficient and economical to delineate K’s spatial features for regional groundwater systems and can benefit groundwater-related studies.</description><subject>Aquifers</subject><subject>Classification</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Electrical resistivity</subject><subject>Geology</subject><subject>Groundwater</subject><subject>Groundwater studies</subject><subject>Hydraulics</subject><subject>Hydrogeology</subject><subject>Kriging interpolation</subject><subject>Pumping</subject><subject>Pumping tests</subject><subject>Regional development</subject><subject>Rivers</subject><subject>Sediments</subject><subject>Spatial distribution</subject><subject>Water, Underground</subject><subject>Zonation</subject><issn>2073-4441</issn><issn>2073-4441</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpNUE1LAzEQDaJgqT34DwKePGzNx2Y3OZbaWqHgQet1yWZnS8p2U5Os0n9vakWcOczjzXsz8BC6pWTKuSIPX5RQSgtGLtCIkZJneZ7Ty3_4Gk1C2JFUuZJSkBGqFyHavY623-LVsfF66KzBc9c3g4n208YjXlromoBtn-j9wQUbAS91jx-hixpvwsn6Dj5aozu86MBE_wNf3dA3aXmDrlrdBZj8zjHaLBdv81W2fnl6ns_WmeGcxqzOCbTcgKmlUiVjQkihpBamaDTNlVG0VMAlFRykKYWknPIEwVBSClUzPkZ357sH7z4GCLHaucH36WXFhGSKk4IXSTU9q7a6g8r2rYtem9QN7K1xPbQ28bNSUSZZmYIbo_uzwXgXgoe2OviUmD9WlFSn2Ku_2Pk3PwRzEA</recordid><startdate>20181109</startdate><enddate>20181109</enddate><creator>Chen, You-Cheng</creator><creator>Tsai, Jui-Pin</creator><creator>Chang, Liang-Cheng</creator><creator>Chang, Ping-Yu</creator><creator>Lin, Helen</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope></search><sort><creationdate>20181109</creationdate><title>Estimating Hydraulic Conductivity Fields in Composite Fan Delta Using Vertical Electrical Sounding</title><author>Chen, You-Cheng ; Tsai, Jui-Pin ; Chang, Liang-Cheng ; Chang, Ping-Yu ; Lin, Helen</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-b40ef3cecb899722558598a5c6da149c9179e38153e8c75813133e8ec10759b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Aquifers</topic><topic>Classification</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Electrical resistivity</topic><topic>Geology</topic><topic>Groundwater</topic><topic>Groundwater studies</topic><topic>Hydraulics</topic><topic>Hydrogeology</topic><topic>Kriging interpolation</topic><topic>Pumping</topic><topic>Pumping tests</topic><topic>Regional development</topic><topic>Rivers</topic><topic>Sediments</topic><topic>Spatial distribution</topic><topic>Water, Underground</topic><topic>Zonation</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, You-Cheng</creatorcontrib><creatorcontrib>Tsai, Jui-Pin</creatorcontrib><creatorcontrib>Chang, Liang-Cheng</creatorcontrib><creatorcontrib>Chang, Ping-Yu</creatorcontrib><creatorcontrib>Lin, Helen</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><jtitle>Water (Basel)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, You-Cheng</au><au>Tsai, Jui-Pin</au><au>Chang, Liang-Cheng</au><au>Chang, Ping-Yu</au><au>Lin, Helen</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimating Hydraulic Conductivity Fields in Composite Fan Delta Using Vertical Electrical Sounding</atitle><jtitle>Water (Basel)</jtitle><date>2018-11-09</date><risdate>2018</risdate><volume>10</volume><issue>11</issue><spage>1620</spage><pages>1620-</pages><issn>2073-4441</issn><eissn>2073-4441</eissn><abstract>Hydraulic conductivity (K) is crucial for groundwater studies and is conventionally obtained through pumping tests, which are costly due to well installation, resulting in a limited amount of data. Recent studies have addressed this limitation by estimating K through the integration of a pumping-test K and electrical resistivity measurements. While this approach is suitable for local areas, it cannot readily be applied to determine K fields for the composite fan delta. This study proposes and demonstrates an advanced method to estimate the K’s spatial distribution of a composite fan delta. The proposed method included data classification, linear regression, and kriging interpolation. Data classification was conducted using a physical-based zonation method. The K and formation factor (F) data pairs were classified into several groups. Linear regression was used to develop K-F mapping for each group. The regression results showed a good correlation between K and F in each group. These K-F mappings were verified by additional pumping tests. These results indicate that estimation errors were between 7 m/day and 58 m/day, and the correlation coefficient of each data group was greater than 0.8. Based on these regression equations and ordinary kriging method, the detailed K spatial distribution of the study area was derived. According to these results, the proposed method is efficient and economical to delineate K’s spatial features for regional groundwater systems and can benefit groundwater-related studies.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/w10111620</doi><oa>free_for_read</oa></addata></record> |
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subjects | Aquifers Classification Correlation coefficient Correlation coefficients Electrical resistivity Geology Groundwater Groundwater studies Hydraulics Hydrogeology Kriging interpolation Pumping Pumping tests Regional development Rivers Sediments Spatial distribution Water, Underground Zonation |
title | Estimating Hydraulic Conductivity Fields in Composite Fan Delta Using Vertical Electrical Sounding |
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