Top

Environmental Earth Sciences

Published in:

01-04-2022 | Original Article

Assessment of groundwater vulnerability based on the modified DRASTIC model: a case study in Baicheng City, China

Authors: Mingjun Liu, Changlai Xiao, Xiujuan Liang

Published in: Environmental Earth Sciences | Issue 8/2022

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Accurate assessment of groundwater vulnerability objectively reflects an area’s potential for groundwater pollution and provides a reference basis for pollution control and prevention. The main objective of this study was to modify the original DRASTIC model to improve the consistency of groundwater vulnerability assessment results with regard to the actual conditions of the study area. To optimize the assessment objectivity, two additional factors that are influenced by human activities (land use and degree of groundwater extraction) were added to form the DRASTICLE model. Then, based on the correlation between all factors and measured nitrate concentrations, the improved three-scale analytic hierarchy process (AHP) and the weights of evidence (WOE) methods were used to reassign the factor weights of the DRASTICLE model. The area under the receiver operating characteristic (ROC) curve, denoted as AUC, was used to quantitatively evaluate the accuracy of all four models (original DRASTIC model AUC: 0.62). By modifying the factors and weights, the three new models showed better performance, AUC values were 0.64, 0.73 and 0.85 for the DRASTICLE, AHP-DRASTICLE, and WOE-DRASTICLE models, respectively. These results indicate that the modified models could more accurately convey groundwater vulnerability in the study area. The WOE-DRASTICLE model, which had the best performance, was then used to assess groundwater vulnerability in 2000 and 2010 and these were compared to 2018. In 2000, 2010, and 2018, the proportion of areas with very high groundwater vulnerability was 5%, 6%, 8%, respectively. Meanwhile, the proportion of areas with very low vulnerability decreased from 73 to 75%, and then rose to 82%, indicating that the spatial distribution of groundwater vulnerability has changed over time. Findings of this study are expected to provide a new theoretical basis for the Baicheng City municipal government in China to better manage and exploit groundwater resources.

previous article Deformation patterns and failure mechanism of high and steep stratified rock slopes with upper steep and lower gentle style induced by step-by-step excavations

next article Characterizing groundwater salinity patterns in a coastal sand aquifer at Magilligan, Northern Ireland, using geophysical and geotechnical methods

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Available only for authorised users

Abu-Bakr HAE-A (2020) Groundwater vulnerability assessment in different types of aquifers. Agric Water Manag. https://doi.org/10.1016/j.agwat.2020.106275CrossRef

Agterberg FP (1989) Computer programs for mineral exploration. Science 245(4913):76–81. https://doi.org/10.1126/science.245.4913.76CrossRef

Al-Adamat RAN, Foster IDL, Baban SMJ (2003) Groundwater vulnerability and risk mapping for the Basaltic aquifer of the Azraq basin of Jordan using GIS, Remote Sensing and DRASTIC. Appl Geogr 23(4):303–324. https://doi.org/10.1016/j.apgeog.2003.08.007CrossRef

Aller L, Bennett T, Lehr J, Petty R, Hackett G (1987) DRASTIC: standardized system for evaluating groundwater pollution potential using hydrogeologic settings. J Geol Soc India 29

Almasri MN (2008) Assessment of intrinsic vulnerability to contamination for Gaza coastal aquifer, Palestine. J Environ Manag 88(4):577–593. https://doi.org/10.1016/j.jenvman.2007.01.022CrossRef

An Y, Lu W (2018) Assessment of groundwater quality and groundwater vulnerability in the northern Ordos Cretaceous Basin, China. Arab J Geosci. https://doi.org/10.1007/s12517-018-3449-yCrossRef

Antonakos AK, Lambrakis NJ (2007) Development and testing of three hybrid methods for the assessment of aquifer vulnerability to nitrates, based on the drastic model, an example from NE Korinthia, Greece. J Hydrol 333(2–4):288–304. https://doi.org/10.1016/j.jhydrol.2006.08.014CrossRef

Arabameri A, Rezaei K, Cerda A, Lombardo L, Rodrigo-Comino J (2019) GIS-based groundwater potential mapping in Shahroud plain, Iran. A comparison among statistical (bivariate and multivariate), data mining and MCDM approaches. Sci Total Environ 658:160–177. https://doi.org/10.1016/j.scitotenv.2018.12.115CrossRef

Babiker IS, Mohamed MA, Hiyama T, Kato K (2005) A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakamigahara Heights, Gifu Prefecture, central Japan. Sci Total Environ 345(1–3):127–140. https://doi.org/10.1016/j.scitotenv.2004.11.005CrossRef

Bai L, Wang Y, Meng F (2012) Application of DRASTIC and extension theory in the groundwater vulnerability evaluation. Water Environ J 26(3):381–391. https://doi.org/10.1111/j.1747-6593.2011.00298.xCrossRef

Barber C, Bates L, Barron R, Allison H (1998) Comparison of standardised and region-specific methods for assessment of the vulnerability of groundwater to pollution; a case study in an agricultural catchment. Environ Sci. https://doi.org/10.1201/9781482287349-8CrossRef

Barzegar R, Moghaddam AA, Baghban H (2015) A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer, Iran. Stoch Environ Res Risk Assess 30(3):883–899. https://doi.org/10.1007/s00477-015-1088-3CrossRef

Barzegar R, Moghaddam AA, Deo R, Fijani E, Tziritis E (2018) Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms. Sci Total Environ 621:697–712. https://doi.org/10.1016/j.scitotenv.2017.11.185CrossRef

Bojórquez-Tapia LA, Cruz-Bello GM, Luna-González L, Juárez L, Ortiz-Pérez MA (2009) V-DRASTIC: Using visualization to engage policymakers in groundwater vulnerability assessment. J Hydrol 373(1–2):242–255. https://doi.org/10.1016/j.jhydrol.2009.05.005CrossRef

Bonfanti M, Ducci D, Masetti M, Sellerino M, Stevenazzi S (2016) Using statistical analyses for improving rating methods for groundwater vulnerability in contamination maps. Environ Earth Sci. https://doi.org/10.1007/s12665-016-5793-0CrossRef

Brindha K, Elango L (2015) Cross comparison of five popular groundwater pollution vulnerability index approaches. J Hydrol 524:597–613. https://doi.org/10.1016/j.jhydrol.2015.03.003CrossRef

Feng X (2019) Study on the protection scheme of groundwater resources in Baicheng City (master), Jilin University, Available from Cnki

Ferreira JPL, Oliveira MM (2004) Groundwater vulnerability assessment in Portugal. Geofísica Internacional 43(4):541–550

Ghazavi R, Ebrahimi Z (2015) Assessing groundwater vulnerability to contamination in an arid environment using DRASTIC and GOD models. Int J Environ Sci Technol 12(9):2909–2918. https://doi.org/10.1007/s13762-015-0813-2CrossRef

Gogu RC, Dassargues A (2000) Current trends and future challenges in groundwater vulnerability assessment using overlay and index methods. Environ Geol 39(6):549–559. https://doi.org/10.1007/s002540050466CrossRef

Hong HY, Ilia I, Tsangaratos P, Chen W, Xu C (2017) A hybrid fuzzy weight of evidence method in landslide susceptibility analysis on the Wuyuan area, China. Geomorphology 290:1–16. https://doi.org/10.1016/j.geomorph.2017.04.002CrossRef

Huan H, Wang J, Teng Y (2012) Assessment and validation of groundwater vulnerability to nitrate based on a modified DRASTIC model: a case study in Jilin City of northeast China. Sci Total Environ 440:14–23. https://doi.org/10.1016/j.scitotenv.2012.08.037CrossRef

Huan H, Wang JS, Zhai YZ, Xi BD, Li J, Li MX (2016) Quantitative evaluation of specific vulnerability to nitrate for groundwater resource protection based on process-based simulation model. Sci Total Environ 550:768–784. https://doi.org/10.1016/j.scitotenv.2016.01.144CrossRef

Jhariya DC (2019) Assessment of groundwater pollution vulnerability using GIS-based DRASTIC model and its validation using nitrate concentration in Tandula Watershed, Chhattisgarh. J Geol Soc India 93(5):567–573. https://doi.org/10.1007/s12594-019-1218-5CrossRef

Kazakis N, Voudouris KS (2015) Groundwater vulnerability and pollution risk assessment of porous aquifers to nitrate: Modifying the DRASTIC method using quantitative parameters. J Hydrol 525:13–25. https://doi.org/10.1016/j.jhydrol.2015.03.035CrossRef

Khan R, Jhariya DC (2019) Assessment of groundwater pollution vulnerability using GIS based modified DRASTIC model in Raipur city, Chhattisgarh. J Geol Soc India 93(3):293–304. https://doi.org/10.1007/s12594-019-1177-xCrossRef

Khosravi K, Sartaj M, Tsai FT, Singh VP, Kazakis N, Melesse AM, Prakash I, Tien Bui D, Pham BT (2018) A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment. Sci Total Environ 642:1032–1049. https://doi.org/10.1016/j.scitotenv.2018.06.130CrossRef

Mukherjee I, Singh UK (2020) Delineation of groundwater potential zones in a drought-prone semi-arid region of east India using GIS and analytical hierarchical process techniques. CATENA. https://doi.org/10.1016/j.catena.2020.104681CrossRef

O’Brien RM (2007) A caution regarding rules of thumb for variance inflation factors. Qual Quant 41(5):673–690. https://doi.org/10.1007/s11135-006-9018-6CrossRef

Omotola OO, Oladapo MI, Akintorinwa OJ (2020) Modeling assessment of groundwater vulnerability to contamination risk in a typical basement terrain case of vulnerability techniques application comparison study. Model Earth Syst Environ 6(3):1253–1280. https://doi.org/10.1007/s40808-020-00720-1CrossRef

Pacheco FA, Pires LM, Santos RM, Sanches Fernandes LF (2015) Factor weighting in DRASTIC modeling. Sci Total Environ 505:474–486. https://doi.org/10.1016/j.scitotenv.2014.09.092CrossRef

Perrin J, Cartannaz C, Noury G, Vanoudheusden E (2015) A multicriteria approach to karst subsidence hazard mapping supported by weights-of-evidence analysis. Eng Geol 197:296–305. https://doi.org/10.1016/j.enggeo.2015.09.001CrossRef

Rezaei F, Safavi HR, Ahmadi A (2013) Groundwater vulnerability assessment using fuzzy logic: a case study in the zayandehrood aquifers, Iran. Environ Manag 51(1):267–277. https://doi.org/10.1007/s00267-012-9960-0CrossRef

Saaty T, Kearns K (1985) The analytic hierarchy process. Anal Plan. https://doi.org/10.1016/B978-0-08-032599-6.50008-8CrossRef

Sahoo M, Sahoo S, Dhar A, Pradhan B (2016) Effectiveness evaluation of objective and subjective weighting methods for aquifer vulnerability assessment in urban context. J Hydrol 541:1303–1315. https://doi.org/10.1016/j.jhydrol.2016.08.035CrossRef

Sener E, Davraz A (2012) Assessment of groundwater vulnerability based on a modified DRASTIC model, GIS and an analytic hierarchy process (AHP) method: the case of Egirdir Lake basin (Isparta, Turkey). Hydrogeol J 21(3):701–714. https://doi.org/10.1007/s10040-012-0947-yCrossRef

Shrestha S, Semkuyu DJ, Pandey VP (2016) Assessment of groundwater vulnerability and risk to pollution in Kathmandu Valley, Nepal. Sci Total Environ 556:23–35. https://doi.org/10.1016/j.scitotenv.2016.03.021CrossRef

Thirumalaivasan D, Karmegam M, Venugopal K (2003) AHP-DRASTIC: software for specific aquifer vulnerability assessment using DRASTIC model and GIS. Environ Model Softw 18(7):645–656. https://doi.org/10.1016/s1364-8152(03)00051-3CrossRef

Victorine Neh A, Ako Ako A, Richard Ayuk A, Hosono T (2015) DRASTIC-GIS model for assessing vulnerability to pollution of the phreatic aquiferous formations in Douala-Cameroon. J Afr Earth Sc 102:180–190. https://doi.org/10.1016/j.jafrearsci.2014.11.001CrossRef

Voutchkova DD, Schullehner J, Rasmussen P, Hansen B (2021) A high-resolution nitrate vulnerability assessment of sandy aquifers (DRASTIC-N). J Environ Manag 277:111330. https://doi.org/10.1016/j.jenvman.2020.111330CrossRef

Wang JL, Yang YS (2008) An approach to catchment-scale groundwater nitrate risk assessment from diffuse agricultural sources: a case study in the Upper Bann, Northern Ireland. Hydrol Process 22(21):4274–4286. https://doi.org/10.1002/hyp.7036CrossRef

Wu X, Li B, Ma C (2018) Assessment of groundwater vulnerability by applying the modified DRASTIC model in Beihai City, China. Environ Sci Pollut Res Int 25(13):12713–12727. https://doi.org/10.1007/s11356-018-1449-9CrossRef

Zhang ZJ, Zuo RG, Xiong YH (2016) A comparative study of fuzzy weights of evidence and random forests for mapping mineral prospectivity for skarn-type Fe deposits in the southwestern Fujian metallogenic belt, China. Sci China Earth Sci 59(3):556–572. https://doi.org/10.1007/s11430-015-5178-3CrossRef

Zuo J (1988) The indirect method of judgment matrix in analytic hierarchy process. Syst Eng (06): 56–63. CNKI:SUN:GCXT.0.1988-06-013

Title: Assessment of groundwater vulnerability based on the modified DRASTIC model: a case study in Baicheng City, China
Authors: Mingjun Liu
Changlai Xiao
Xiujuan Liang
Publication date: 01-04-2022
Publisher: Springer Berlin Heidelberg
Published in: Environmental Earth Sciences / Issue 8/2022
Print ISSN: 1866-6280
Electronic ISSN: 1866-6299
DOI: https://doi.org/10.1007/s12665-022-10350-8

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Other articles of this Issue 8/2022

Characterizing groundwater salinity patterns in a coastal sand aquifer at Magilligan, Northern Ireland, using geophysical and geotechnical methods

Modelling unsaturated flow in porous media using an improved iterative scheme

Height of overlying strata failure zone under different hydrogeological units

Mobility of organotin pesticides: azocyclotin and cyhexatin in clayey and sandy soils from the Northern Paraná state—Brazil

An assessment of the factors that drive changes in the distribution and area of cultivated land in the Yellow River Delta, China

Geostatistical analysis of hydrogeological data of the Baraka gold zone, prefecture of Siguiri, Republic of Guinea