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Groundwater is a vital resource for domestic, agricultural, and industrial activities, as well as for ecosystem services. Despite this, the resource is under significant threat, due to increasing contamination from anthropogenic activities. Therefore, to ensure its reliability for present and future use, effective management of groundwater is important not only in terms of quantity (i.e. abstraction) but also quality. This can be achieved by identifying areas that are more vulnerable to contamination and by implementing protective measures. To identify the risk and delineate areas that are more exposed to pollution, various groundwater vulnerability assessment techniques have been developed across the globe. This paper presents an overview of some of the commonly used groundwater vulnerability assessment models in terms of their unique features and their application. Special emphasis is placed on statistical methods and overlay-index techniques. The assessment of the literature shows that statistical methods are limited in application to the assessment of groundwater vulnerability to pollution because they rely heavily on the availability of sufficient and quality data. However, in areas where extensive monitoring data are available, these methods estimate groundwater vulnerability more realistically in quantitative terms. Many works of research indicate that index-overlay methods are used extensively and frequently in groundwater vulnerability assessments. Due to the qualitative nature of these models, however, they are still subject to modification. This study offers an overview of a selection of relevant groundwater vulnerability assessment techniques under a specific set of hydro-climatic and hydrogeological conditions.
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186--198
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Bibliogr. 127 poz., rys., tab.
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autor
- University of Johannesburg, Faculty of Engineering and the Built Environment, Department of Civil Engineering Sciences, PO Box 524, Auckland Park, 2006 Johannesburg, South Africa
autor
- University of Johannesburg, Faculty of Engineering and the Built Environment, Department of Civil Engineering Sciences, PO Box 524, Auckland Park, 2006 Johannesburg, South Africa
Bibliografia
- ABDULLAHI U.S. 2009. Evaluation of models for assessing groundwater vulnerability to pollution in Nigeria. Bayero Journal of Pure Applied Sciences. Vol. 2(2) p. 138–142. DOI 10.4314/bajopas.v2i2.63801.
- AL-AMOUSH H., HAMMOURI N.A., ZUNIC F., SALAMEH E. 2010. Intrinsic vulnerability assessment for the alluvial aquifer in the northern part of Jordan valley. Water Resources Management. Vol. 24 p. 3461–3485. DOI 10.1007/s11269-010-9615-y.
- ALLER L., BENNET T., LEHER J.H., PETTY R.J., HACKETT G. 1987. DRASTIC: A standardized system for evaluating ground water pollution potential using hydrogeological settings. (EPA600/2-87-035). Ada, OK. US EPA pp. 622.
- AN Y., LU W. 2018. Assessment of groundwater quality and groundwater vulnerability in the northern Ordos Cretaceous Basin, China. Arabian Journal of Geosciences. Vol. 11, 118. DOI 10.1007/s12517-018-3449-y.
- ANANE M., ABIDI B., LACHAAL F., LIMAM A., JELLALI S. 2013. GIS-based DRASTIC, Pesticide DRASTIC and the Susceptibility Index (SI): comparative study for evaluation of pollution potential in the Nabeul-Hammamet shallow aquifer, Tunisia. Hydrogeology Journal. Vol. 21 p. 715–731. DOI 10.1007/s10040-013-0952-9.
- ARTHUR J.D., WOOD H.A.R., BAKER A.E., CICHON J.R., RAINES G.L. 2007. Development and implementation of a Bayesian-based aquifer vulnerability assessment in Florida. Natural Resources Research. Vol. 16 p. 93–107. DOI 10.1007/s11053-007-9038-5.
- AYDI A. 2018. Evaluation of groundwater vulnerability to pollution using a GIS-based multi-criteria decision analysis. Groundwater for Sustainable Development. Vol. 7 p. 204–211. DOI 10.1016/j.gsd.2018.06.003.
- AYDI W., SAIDI S., CHALBAOUI M., CHAIBI S., BEN DHIA H. 2012. Evaluation of the groundwater vulnerability to pollution using an intrinsic and a specific method in a GIS environment: Application to the Plain of Sidi Bouzid (Central Tunisia). Arabian Journal for Science and Engineering. Vol. 38 p. 1815–1831. DOI 10.1007/s13369-012-0417-9.
- BABIKER I.S., MOHAMED M.A., HIYAMA T., KATO K. 2005. A GIS-based DRASTIC model for assessing aquifer vulnerability in Kakami-gahara Heights, Gifu Prefecture, central Japan. Science of The Total Environment. Vol. 345(1–3) p. 127–140. DOI 10.1016/j.scitotenv.2004.11.005.
- BAGHAPOUR M.A., FADAEI NOBANDEGANI A., TALEBBEYDOKHTI N., BAGHER-ZADEH S., NADIRI A.A., GHAREKHANI M., CHITSAZAN N. 2016. Optimization of DRASTIC method by artificial neural network, nitrate vulnerability index, and composite DRASTIC models to assess groundwater vulnerability for unconfined aquifer of Shiraz Plain, Iran. Journal of Environmental Health Science and Engineering. Vol. 14, 13. DOI 10.1186/s40201-016-0254-y.
- BAGHERZADEH S., KALANTARI N., NOBANDEGANI A.F., DERAKHSHAN Z., CONTI G.O., FERRANTE M., MALEKAHMADI R. 2018. Groundwater vulnerability assessment in karstic aquifers using COP method. Environmental Science and Pollution Research. Vol. 25 p. 18960–18979. DOI 10.1007/s11356-018-1911-8.
- BARBULESCU A.J.W. 2020. Assessing groundwater vulnerability: DRASTIC and DRASTIC-Like Methods: A review. Water. Vol. 12(5) pp. 1356. DOI 10.3390/w12051356.
- BARZEGAR R., MOGHADDAM A.A., DEO R., FIJANI E., TZIRITIS E. 2018. Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms. Science of The Total Environment. Vol. 621 p. 697–712. DOI 10.1016/j.scitotenv.2017.11.185.
- BOUFEKANE A., SAIGHI O. 2018. Application of groundwater vulnerability overlay and index methods to the Jijel Plain Area (Algeria). Ground Water. Vol. 56(1) p. 143–156. DOI 10.1111/gwat.12582.
- BOY-ROURA M., NOLAN B.T., MENCIÓ A., MAS-PLA J. 2013. Regression model for aquifer vulnerability assessment of nitrate pollution in the Osona region (NE Spain). Journal of Hydrology. Vol. 505 p. 150–162. DOI 10.1016/j.jhydrol.2013.09.048.
- BREIMAN L. 2001. Random forests. Machine learning. Vol. 45 p. 5–32. DOI 10.1023/A:1010933404324.
- BRINDHA K., ELANGO L. 2015. Cross comparison of five popular groundwater pollution vulnerability index approaches. Journal of Hydrology. Vol. 524 p. 597–613. DOI 10.1016/j.jhydrol.2015.03.003.
- BUSICO G., KAZAKIS N., COLOMBANI N., MASTROCICCO M., VOUDOURIS K., TEDESCO D. 2017. A modified SINTACS method for groundwater vulnerability and pollution risk assessment in highly anthropized regions based on NO3– and SO42– concentrations. Science of The Total Environment. Vol. 609 p. 1512–1523. DOI 10.1016/j.scitotenv.2017.07.257.
- BUTLER A.P., WHEATER H., MATHIAS S., LI X. 2010. Groundwater vulnerability and protection. In: Groundwater modelling in arid and semi-arid areas. Eds. H. Wheater, S. Mathias, X. Li. Cambridge. Cambridge University Press p. 75–86.
- CANION A., MCCLOUD L., DOBBERFUHL D. 2019. Predictive modeling of elevated groundwater nitrate in a karstic spring-contributing area using random forests and regression-kriging. Environmental Earth Sciences. Vol. 78 p. 271–271. DOI 10.1007/s12665-019-8277-1.
- CHANDOUL I.R., BOUAZIZ S., DHIA H.B. 2014. Groundwater vulnerability assessment using GIS-based DRASTIC models in shallow aquifer of Gabes North (South East Tunisia). Arabian Journal of Geosciences. Vol. 8 p. 7619–7629. DOI 10.1007/s12517-014-1702-6.
- CHEN H.H., DRULINER A.D. 1988. Agricultural chemical contamination of ground water in six areas of the High Plains aquifer, Nebraska. Geological survey-water supply paper (USA).
- CHEN J., LI M., WANG W. 2012. Statistical uncertainty estimation using random forests and its application to drought forecast. Mathematical Problems in Engineering. Vol. 2012, 915053 p. 1–12. DOI 10.1155/2012/915053.
- CHEN J., WU H., QIAN H., LI X. 2018. Challenges and prospects of sustainable groundwater management in an agricultural plain along the Silk Road Economic Belt, north-west China. International Journal of Water Resources Development. Vol. 34(3) p. 354–368. DOI 10.1080/07900627.2016.1238348.
- CIVITA M. 1994. Le carte della vulnerabilità degli acquiferi all’inquinamento: Teoria & pratica [The maps of groundwater vulnerability to pollution: Theory and practice]. Quaderni e Tecniche di Protezione Ambientale. No. 31. Bologna. Pitagora. ISBN 978-8837106881 pp. 344.
- CIVITA M., DE MAIO M. 2004. Assessing and mapping groundwater vulnerability to contamination: The Italian combined approach. Geofísica Internacional. Vol. 43(4) p. 513–532.
- COSTA C.W., LORANDI R., LOLLO J.A., SANTOS V.S. 2019. Potential for aquifer contamination of anthropogenic activity in the recharge area of the Guarani Aquifer System, southeast of Brazil. Groundwater for Sustainable Development. Vol. 8 p. 10–23. DOI 10.1016/j.gsd.2018.08.007.
- DENNY S.C., ALLEN D.M., JOURNEAY J.M. 2006. DRASTIC-Fm: A modified vulnerability mapping method for structurally controlled aquifers in the southern Gulf Islands, British Columbia, Canada. Hydrogeology Journal. Vol. 15 p. 483–493. DOI 10.1007/s10040-006-0102-8.
- DEVIC G., DJORDJEVIC D., SAKAN S. 2014. Natural and anthropogenic factors affecting the groundwater quality in Serbia. Science of The Total Environment. Vol. 468–469 p. 933–942. DOI 10.1016/j.scitotenv.2013.09.011.
- DIXON B. 2005. Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis. Journal of Hydrology. Vol. 309 p. 17–38. DOI 10.1016/j.jhydrol.2004.11.010.
- DOERFLIGER N., JEANNIN P.Y., ZWAHLEN F. 1999. Water vulnerability assessment in karst environments: a new method of defining protection areas using a multi-attribute approach and GIS tools (EPIK method). Environmental Geology. Vol. 39 p. 165–176. DOI 10.1007/s002540050446.
- EL HIMER H., FAKIR Y., STIGTER T. Y., LEPAGE M., EL MANDOUR A., RIBEIRO L. 2013. Assessment of groundwater vulnerability to pollution of a wetland watershed: The case study of the Oualidia-Sidi Moussa wetland, Morocco. Aquatic Ecosystem Health, Management. Vol. 16(2) p. 205–215. DOI 10.1080/14634988.2013.788427.
- FAWAGREH K., GABER M. M., ELYAN E. 2014. Random forests: from early developments to recent advancements. Systems Science & Control Engineering. Vol. 2(1) p. 602–609. DOI 10.1080/21642583.2014.956265.
- FIELD C. B., BARROS V. R., CHANGE I. P. O. C., WORKING G., 2014. Climate change 2014: impacts, adaptation, and vulnerability: Working Group II contribution to the fifth assessment report of the Intergovernmental Panel on Climate Change. New York. Cambridge University Press. ISBN 978-1-107-64165-5 pp. 1132.
- FOCAZIO M.J., REILLY T.E., RUPERT M.G., H ELSEL D.R. 2002. Assessing groundwater vulnerability to contamination: providing scientifically defensible information for decision makers. Reston, Virginia. U.S. Dept. of the Interior, USGS. DOI 10.3133/cir1224.
- FOSTER S.S.D. 1987. Fundamental concepts in aquifer vulnerability, pollution risk and protection strategy. International Conference, 1987, Noordwijk Aan Zee, the Netherlands Vulnerability of Soil and Groundwater to Pollutants The Hague, Netherlands Organization for Applied Scientific Research. Hage. Netherlands Organization for Applied Scientific Research p. 69–86.
- FRAGA C.M., FERNANDES L.F.S., PACHECO F.A.L., REIS C., MOURA J.P. 2013. Exploratory assessment of groundwater vulnerability to pollution in the Sordo River Basin, Northeast of Portugal. Rem: Revista Escola de Minas. Vol. 66 p. 49–58. DOI 10.1590/S0370-44672013000100007.
- GHANEM M., AHMAD W., KEILAN Y., SAWAFTAH F. 2017. Groundwater vulnerability mapping assessment of central West Bank catchments using PI method. Environmental Earth Sciences. Vol. 76, 347. DOI 10.1007/s12665-017-6681-y.
- GHAZAVI R., EBRAHIMI Z. 2015. Assessing groundwater vulnerability to contamination in an arid environment using DRASTIC and GOD models. International Journal of Environmental Science and Technology. Vol. 12 p. 2909–2918. DOI 10.1007/s13762-015-0813-2.
- GOLDSCHEIDER N. 2002. Hydrogeology and vulnerability of karst systems: examples from the Northern Alps and the Swabian Alb. PhD Thesis, University of Karlsruhe (TH), Faculty for Bio-and Geosciences. Karlsruhe pp. 236.
- GOLDSCHEIDER N. 2005. Karst groundwater vulnerability mapping: application of a new method in the Swabian Alb, Germany. Hydrogeology Journal. Vol. 13 p. 555–564. DOI 10.1007/s10040-003-0291-3.
- GOLDSCHEIDER N., KLUTE M., STURM S., HÖTZL H. 2000. The PI method - a GIS-based approach to mapping groundwater vulnerability with special consideration of karst aquifers. Journal of Applied Geology. Vol. 46 p. 157–166.
- GREENE E.A., LAMOTTE A.E., CULLINAN K.A. 2005. Ground-water vulnerability to nitrate contamination at multiple thresholds in the mid-Atlantic region using spatial probability models. US Department of the Interior, USGS pp. 24. DOI 10.3133/sir20045118.
- GÜLER C., KURT M.A., KORKUT R.N. 2013. Assessment of groundwater vulnerability to nonpoint source pollution in a Mediterranean coastal zone (Mersin, Turkey) under conflicting land use practices. Ocean & Coastal Management. Vol. 71 p. 141–152. DOI 10.1016/j.ocecoaman.2012.10.010.
- GURDAK J.J., QI S.L. 2012. Vulnerability of recently recharged ground-water in principal [corrected] aquifers of the United States to nitrate contamination. Environmental Science & Technology. Vol. 46 p. 6004–6012. DOI 10.1021/es300688b.
- HAQUE E., REZA S., AHMED R. 2018. Assessing the vulnerability of groundwater due to open pit coal mining using DRASTIC model: A case study of Phulbari Coal Mine, Bangladesh. Geosciences Journal. Vol. 22 p. 359–371. DOI 10.1007/s12303-017-0054-0.
- HÖLTING B., HAERTLÉ T., HOHBERGER K.-H., NACHTIGALL K. H., VILLINGER E., WEINZIERL W., WROBEL J.-P. 1995. Konzept zur Ermittlung der Schutzfunktion der Grundwasserüberdeckung. Empfehlungen für die Erstellung von hydrogeologischen Gutachten zur Bemessung und Gliederung von Trinkwasserschutzgebieten – Schutzgebiete für Grundwasser. [Concept for determining the protective function of the groundwater cover. Recommendations for the preparation of hydrogeological reports on the dimensioning and structuring of drinking water protection areas – protection areas for groundwater]. Geologisches Jahrbuch. Reihe C. Band C 63. Hannover. ISBN 978-3-510-96195-5 pp. 65.
- HOWARD K.W.F. 2014. Sustainable cities and the groundwater governance challenge. Environmental Earth Sciences. Vol. 73 p. 2543–2554. DOI 10.1007/s12665-014-3370-y.
- HUANG L., ZENG G., LIANG J., HUA S., YUAN Y., LI X., DONG H., LIU J., NIE S., LIU J. 2017. Combined Impacts of Land Use and Climate Change in the Modeling of Future Groundwater Vulnerability. Journal of Hydrologic Engineering. Vol. 22 p. 05017007–05017007. DOI 10.1061/(asce)he.1943-5584.0001493.
- IQBAL J., GORAI A.K., KATPATAL Y.B., PATHAK G. 2014a. Development of GIS-based fuzzy pattern recognition model (modified DRASTIC model) for groundwater vulnerability to pollution assessment. International Journal of Environmental Science and Technology. Vol. 12 p. 3161–3174. DOI 10.1007/s13762-014-0693-x.
- IQBAL J., PATHAK G., GORAI A.K. 2014b. Development of hierarchical fuzzy model for groundwater vulnerability to pollution assessment. Arabian Journal of Geosciences. Vol. 8 p. 2713–2728. DOI 10.1007/s12517-014-1417-8.
- JAFARI S.M., NIKOO M.R. 2019. Developing a fuzzy optimization model for groundwater risk assessment based on improved DRASTIC method. Environmental Earth Sciences. Vol. 78 p. 109–109. DOI 10.1007/s12665-019-8090-x.
- JANG C.-S., CHEN S.-K. 2015. Integrating indicator-based geostatistical estimation and aquifer vulnerability of nitrate-N for establishing groundwater protection zones. Journal of Hydrology. Vol. 523 p. 441–451. DOI 10.1016/j.jhydrol.2015.01.077.
- JANG W.S., ENGEL B., HARBOR J., THELLER L. 2017. Aquifer vulnerability assessment for sustainable groundwater management using DRASTIC. Water. Vol. 9(10), 792. DOI 10.3390/w9100792.
- JAUNAT J., GAREL E., HUNEAU F., EROSTATE M., SANTONI S., ROBERT S., FOX D., PASQUALINI V. 2019. Combinations of geoenvironmental data underline coastal aquifer anthropogenic nitrate legacy through groundwater vulnerability mapping methods. Science of The Total Environonment. Vol. 658 p. 1390–1403. DOI 10.1016/j.scitotenv.2018.12.249.
- JAVADI S., KAVEHKAR N., MOHAMMADI K., KHODADADI A., KAHAWITA R. 2011. Calibrating DRASTIC using field measurements, sensitivity analysis and statistical methods to assess groundwater vulnerability. Water International. Vol. 36 p. 719–732. DOI 10.1080/02508060.2011.610921.
- JESIYA N. P., GOPINATH G. 2019. A Customized FuzzyAHP - GIS based DRASTIC-L model for intrinsic groundwater vulnerability assessment of urban and peri urban phreatic aquifer clusters. Groundwater for Sustainable Development. Vol. 8 p. 654–666. DOI 10.1016/j.gsd.2019.03.005.
- JIANG Y., WU Y., GROVES C., YUAN D., KAMBESIS P. 2009. Natural and anthropogenic factors affecting the groundwater quality in the Nandong karst underground river system in Yunan, China. Journal of Contaminant Hydrology. Vol. 109 p. 49–61. DOI 10.1016/j.jconhyd.2009.08.001.
- KHATRI N., TYAGI S. 2014. Influences of natural and anthropogenic factors on surface and groundwater quality in rural and urban areas. Frontiers in Life Science. Vol. 8 p. 23–39. DOI 10.1080/21553769.2014.933716.
- KHOSRAVI K., SARTAJ M., TSAI F.T., SINGH V.P., KAZAKIS N., MELESSE A.M., PRAKASH I., TIEN BUI D., PHAM B.T. 2018. A comparison study of DRASTIC methods with various objective methods for groundwater vulnerability assessment. Science of The Total Environment. Vol. 642 p. 1032–1049. DOI 10.1016/j.scitotenv.2018.06.130.
- KIHUMBA A.M., VANCLOOSTER M., LONGO J.N. 2017. Assessing ground-water vulnerability in the Kinshasa region, DR Congo, using a calibrated DRASTIC model. Journal of African Earth Sciences. Vol. 126 p. 13–22. DOI 10.1016/j.jafrearsci.2016.11.025.
- KNOLL L., BREUER L., BACH M. 2019. Large scale prediction of groundwater nitrate concentrations from spatial data using machine learning. Science of The Total Environment. Vol. 668 p. 1317–1327. DOI 10.1016/j.scitotenv.2019.03.045.
- KOZŁOWSKI M., SOJKA M. 2019. Applying a modified DRASTIC Model to assess groundwater vulnerability to pollution: A case study in Central Poland. Polish Journal of Environmental Studies. Vol. 28 (3) p. 1223–1231. DOI 10.15244/pjoes/84772.
- KUMAR P., BANSOD B.K.S., DEBNATH S.K., THAKUR P.K., GHANSHYAM C. 2015. Index-based groundwater vulnerability mapping models using hydrogeological settings: A critical evaluation. Environmental Impact Assessment Review. Vol. 51 p. 38–49. DOI 10.1016/j.eiar.2015.02.001.
- LI B., YANG G., WAN R., DAI X., ZHANG Y. 2016. Comparison of random forests and other statistical methods for the prediction of lake water level: a case study of the Poyang Lake in China. Hydrology Research. Vol. 47 p. 69–83. DOI 10.2166/nh.2016.264.
- LIANG J., LI Z., YANG Q., LEI X., KANG A., L I S. 2019. Specific vulnerability assessment of nitrate in shallow groundwater with an improved DRSTIC-LE model. Ecotoxicology and Environmental Safety. Vol. 174 p. 649–657. DOI 10.1016/j.ecoenv.2019.03.024.
- LIGGETT J.E., TALWAR S. 2009. Groundwater vulnerability assessments and integrated water resource management. Streamline Watershed Management Bulletin. Vol. 13(1) pp. 18–29.
- LUOMA S., OKKONEN J., KORKKA-NIEMI K. 2016. Comparison of the AVI, modified SINTACS and GALDIT vulnerability methods under future climate-change scenarios for a shallow low-lying coastal aquifer in southern Finland. Hydrogeology Journal. Vol. 25 p. 203–222. DOI 10.1007/s10040-016-1471-2.
- MACHIWAL D., JHA M. K., SINGH V. P., MOHAN C. 2018. Assessment and mapping of groundwater vulnerability to pollution: Current status and challenges. Earth-Science Reviews. Vol. 185 p. 901–927. DOI 10.1016/j.earscirev.2018.08.009.
- MAIR A., EL-KADI A. I. 2013. Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA. Journal of Contaminant Hydrology. Vol. 153 p. 1–23. DOI 10.1016/j.jconhyd.2013.07.004.
- MASETTI M., POLI S., STERLACCHINI S. 2007. The use of the weights-of-evidence modeling technique to estimate the vulnerability of groundwater to nitrate contamination. Natural Resources Research. Vol. 16 p. 109–119. DOI 10.1007/s11053-007-9045-6.
- MASETTI M., STERLACCHINI S., BALLABIO C., SORICHETTA A., POLI S. 2009. Influence of threshold value in the use of statistical methods for groundwater vulnerability assessment. Science of The Total Environment. Vol. 407 p. 3836–3846. DOI 10.1016/j.scito-tenv.2009.01.055.
- MESSIER K.P., WHEELER D.C., FLORY A.R., JONES R.R., PATEL D., NOLAN B. T., WARD M.H. 2019. Modeling groundwater nitrate exposure in private wells of North Carolina for the agricultural health study. Science of The Total Environment. Vol. 655 p. 512–519. DOI 10.1016/j.scitotenv.2018.11.022.
- MISI A., GUMINDOGA W., HOKO Z. 2018. An assessment of groundwater potential and vulnerability in the Upper Manyame Sub-Catch-ment of Zimbabwe. Physics and Chemistry of the Earth. Parts A/B/C. Vol. 105 p. 72–83. DOI 10.1016/j.pce.2018.03.003.
- MOORE P., JOHN S. 1990. SEEPAGE: A system for early evaluation of the pollution potential of agricultural groundwater environments. Geology Technical Note. No. 5. Chester, PA, USA. USDA, SCS, Northeast Technical Center.
- MUHAMMETOGLU A., YARDIMCI A. 2006. A fuzzy logic approach to assess groundwater pollution levels below agricultural fields. Environmental Monitoring and Assessment. Vol. 118 p. 337–354. DOI 10.1007/s10661-006-1497-3.
- MUHAMMETOĞLU H., MUHAMMETOĞLU A., SOYUPAK S. 2002. Vulnerability of groundwater to pollution from agricultural diffuse sources: A case study. Water Science and Technology. Vol. 45 p. 1–7. DOI 10.2166/wst.2002.0191.
- MUSEKIWA C., MAJOLA K. 2013. Groundwater vulnerability map for South Africa. South African Journal of Geomatics. Vol. 2(2) p. 152–162.
- NADIRI A. A., SEDGHI Z., KHATIBI R., GHAREKHANI M. 2017. Mapping vulnerability of multiple aquifers using multiple models and fuzzy logic to objectively derive model structures. Science of The Total Environment. Vol. 593–594 p. 75–90. DOI 10.1016/j.scitotenv.2017.03.109.
- NADIRI A. A., SEDGHI Z., KHATIBI R., SADEGHFAM S. 2018. Mapping specific vulnerability of multiple confined and unconfined aquifers by using artificial intelligence to learn from multiple DRASTIC frameworks. Journal of Environmental Management. Vol. 227 p. 415–428. DOI 10.1016/j.jenvman.2018.08.019.
- NANOU E.-A., ZAGANA E. 2018. Groundwater vulnerability to pollution map for karst aquifer protection (Ziria Karst System, Southern Greece). Geosciences. Vol. 8(4) p. 125. DOI 10.3390/geos-ciences8040125.
- NRC 1993. Groundwater vulnerability assessment: Predicting relative contamination potential under conditions of uncertainty. Washington. National Research Council. ISBN 9780309047999 pp. 224.
- NAVULUR K.C.S., ENGEL B.A. 1998. Groundwater vulnerability assessment to non-point source nitrate pollution on a regional scale using GIS. Transactions of the ASAE. Vol. 41 p. 1671–1678. DOI 10.13031/2013.17343.
- OKE S.A. 2015. Evaluation of the vulnerability of selected aquifer systems in the Eastern Dahomey basin, South Western Nigeria. PhD Thesis. University of the Free State pp. 228.
- OKE S.A. 2017. An overview of aquifer vulnerability. In: Aquifers: Properties, roles and research. Ed. H. Bailey. New York. Nova Science Publishers p. 1–56.
- ONI T.E., OMOSUYI G.O., AKINLALU A.A. 2019. Groundwater vulnerability assessment using hydrogeologic and geoelectric layer susceptibility indexing at Igbara Oke, Southwestern Nigeria. NRIAG Journal of Astronomy and Geophysics. Vol. 6(2) p. 452–458. DOI 10.1016/j.nrjag.2017.04.009.
- OROJI B. 2018. Groundwater vulnerability assessment using GIS-based DRASTIC and GOD in the Asadabad plain. Journal of Materials and Environmental Science. Vol. 9 p. 1809–1816. DOI 10.26872/jmes.2018.9.6.201.
- PAVLIS M., CUMMINS E., MCDONNELL K. 2010. Groundwater vulnerability assessment of plant protection products: A review. Human and Ecological Risk Assessment: An International Journal. Vol. 16(3) p. 621–650. DOI 10.1080/10807031003788881.
- PIGA F.G., TÃO N.G.R., RUGGIERO M.H., MARQUEZOLA D.D.S., BOINA W.L.D.O., COSTA C.W., LOLLO J.A.D., LORANDI R., MELANDA E.A., MOSCHINI L.E. 2017. Multi-criteria potential groundwater contamination and human activities: Araras watershed, Brazil. RBRH. Vol. 22. DOI 10.1590/2318-0331.0217170052.
- POLEMIO M., CASARANO D., LIMONI P.P. 2009. Karstic aquifer vulnerability assessment methods and results at a test site (Apulia, southern Italy). Natural Hazards and Earth System Sciences. Vol. 9 p. 1461–1470. DOI 10.5194/nhess-9-1461-2009.
- REZAEI F., SAFAVI H. R., AHMADI A. 2013. Groundwater vulnerability assessment using fuzzy logic: a case study in the Zayandehrood aquifers, Iran. Environmental Management. Vol. 51 p. 267–277. DOI 10.1007/s00267-012-9960-0.
- RIBEIRO L. 2000. IS: um novo índice de susceptibilidade de aquíferos á contaminação agrícola [SI: a new index of aquifersusceptibility to agricultural pollution]. Internal report, ER-SHA/CVRM. Lisbon, Portugal. Instituto Superior Técnico pp. 12.
- RIBEIRO L., PINDO J.C., DOMINGUEZ-GRANDA L. 2017. Assessment of groundwater vulnerability in the Daule aquifer, Ecuador, using he susceptibility index method. Science of The Total Environment. Vol. 574 p. 1674–1683. DOI 10.1016/j.scitotenv.2016.09.004.
- RODRIGUEZ-GALIANO V., MENDES M. P., GARCIA-SOLDADO M. J., CHICA-OLMO M., RIBEIRO L. 2014. Predictive modeling of groundwater nitrate pollution using Random Forest and multisource variables related to intrinsic and specific vulnerability: a case study in an agricultural setting (Southern Spain). Science of The Total Environment. Vol. 476–477 p. 189–206. DOI 10.1016/j.scito-tenv.2014.01.001.
- SAHA D., ALAM F. 2014. Groundwater vulnerability assessment using DRASTIC and Pesticide DRASTIC models in intense agriculture area of the Gangetic plains, India. Environmental Monitoring and Assessment. Vol. 186 p. 8741–8763. DOI 10.1007/s10661-014-4041-x.
- SAHOO G.B., RAY C., MEHNERT E., KEEFER D.A. 2006. Application of artificial neural networks to assess pesticide contamination in shallow groundwater. Science of The Total Environment. Vol. 367 p. 234–251. DOI 10.1016/j.scitotenv.2005.12.011.
- SAHOO G.B., RAY C., WADE H.F. 2005. Pesticide prediction in ground water in North Carolina domestic wells using artificial neural networks. Ecological Modelling. Vol. 183(1) p. 29–46. DOI 10.1016/j.ecolmodel.2004.07.021.
- SAHOO M., SAHOO S., DHAR A., PRADHAN B. 2016a. Effectiveness evaluation of objective and subjective weighting methods for aquifer vulnerability assessment in urban context. Journal of Hydrology. Vol. 541 p. 1303–1315. DOI 10.1016/j.jhydrol.2016.08.035.
- SAHOO S., DHAR A., KAR A., CHAKRABORTY D. 2016b. Index-based groundwater vulnerability mapping using quantitative parameters. Environmental Earth Sciences. Vol. 75 p. 522–522. DOI 10.1007/s12665-016-5395-x.
- SANTOS M.G.D., PEREIRA S.Y. 2011. Método AVI (Aquifer Vulnerability Index) para a classificação da vulnerabilidade das águas subterrâneas na região de Campos dos Goytacazes, Rio de Janeiro [AVI (Aquifer Vulnerability Index) method for the classification of groundwater vulnerability in the Campos dos Goytacazes region, Rio de Janeiro]. Engenharia Sanitaria e Ambiental. Vol. 16 p. 281–290. DOI 10.1590/S1413-41522011000300011.
- SHRESTHA S., KAFLE R., PANDEY V. P. 2017. Evaluation of index-overlay methods for groundwater vulnerability and risk assessment in Kathmandu Valley, Nepal. Science of The Total Environment. Vol. 575 p. 779–790. DOI 10.1016/j.scitotenv.2016.09.141.
- SORICHETTA A., BALLABIO C., MASETTI M., ROBINSON G.R. J R ., STERLACCHINI S. 2013. A comparison of data-driven groundwater vulnerability assessment methods. Ground Water. Vol. 51(6) p. 866–879. DOI 10.1111/gwat.12012.
- SORICHETTA A., MASETTI M., BALLABIO C., STERLACCHINI S., BERETTA G.P. 2011. Reliability of groundwater vulnerability maps obtained through statistical methods. Journal of Environmental Management. Vol. 92 p. 1215–1224. DOI 10.1016/j.jenvman.2010.12.009.
- STACKELBERG P.E., BARBASH J.E., GILLIOM R.J., STONE W.W., WOLOCK D.M. 2012. Regression models for estimating concentrations of atrazine plus deethylatrazine in shallow groundwater in agricultural areas of the United States. Journal of Environmental Quality. Vol. 41(2) p. 479–494. DOI 10.2134/jeq2011.0200.
- STEICHEN J., KOELLIKER J., GROSH D., HEIMAN A., YEAROUT R., ROBBINS V. 1988. Contamination of farmstead wells by pesticides, volatile organics, and inorganic chemicals in Kansas. Groundwater Monitoring & Remediation. Vol. 8(2) p. 153–160. DOI 10.1111/j.1745-6592.1988.tb01092.x
- STEMPVOORT D.V., EWERT L., WASSENAAR L. 1993. Aquifer vulnerability index: A GIS-compatible method for groundwater vulnerability mapping. Canadian Water Resources Journal. Vol. 181 p. 25–37. DOI 10.4296/cwrj1801025.
- STEVENAZZI S., BONFANTI M., MASETTI M., NGHIEM S.V., SORICHETTA A. 2017. A versatile method for groundwater vulnerability projections in future scenarios. Journal of Environmental Management. Vol. 187 p. 365–374. DOI 10.1016/j.jenvman.2016.10.057.
- STIGTER T.Y., RIBEIRO L., DILL A.M.M.C. 2005. Evaluation of an intrinsic and a specific vulnerability assessment method in comparison with groundwater salinisation and nitrate contamination levels in two agricultural regions in the south of Portugal. Hydrogeology Journal. Vol. 14 p. 79–99. DOI 10.1007/s10040-004-0396-3.
- STRICKLAND J. 2017. Logistic regression inside and out. Lulu Press, Inc. ISBN 978-1-365-81915-5 pp. 310.
- TESORIERO A.J., GRONBERG J.A., JUCKEM P.F., MILLER M.P., AUSTIN B.P. 2017. Predicting redox-sensitive contaminant concentrations in groundwater using random forest classification. Water Resources Research. Vol. 53(8) p. 7316–7331. DOI 10.1002/2016wr020197.
- TESORIERO A.J., VOSS F.D. 1997. Predicting the probability of elevated nitrate concentrations in the Puget Sound Basin: Implications for aquifer susceptibility and vulnerability. Ground Water. Vol. 35(8) p. 1029–1039. DOI 10.1111/j.1745-6584.1997.tb00175.x.
- TWARAKAVI N.K., KALUARACHCHI J.J. 2005. Aquifer vulnerability assessment to heavy metals using ordinal logistic regression. Ground Water. Vol. 43(2) p. 200–214. DOI 10.1111/j.1745-6584.2005.0001.x.
- TYRALIS H., PAPACHARALAMPOUS G., LANGOUSIS A. 2019. A brief review of random forests for water scientists and practitioners and their recent history in water resources. Water. Vol. 11(2), 910. DOI 10.3390/w11050910.
- UHAN J., VIŽINTIN G., PEZDIČ J. 2010. Groundwater nitrate vulnerability assessment in alluvial aquifer using process-based models and weights-of-evidence method: Lower Savinja Valley case study (Slovenia). Environmental Earth Sciences. Vol. 64 p. 97–105. DOI 10.1007/s12665-010-0821-y.
- VAN BEYNEN P. E., NIEDZIELSKI M. A., BIALKOWSKA-JELINSKA E., ALSHARIF K., M ATUSICK J. 2012. Comparative study of specific groundwater vulnerability of a karst aquifer in central Florida. Applied Geography. Vol. 32(2) p. 868–877. DOI 10.1016/j.apgeog.2011.09.005.
- VELASQUEZ M., HESTER P. T. 2013. An analysis of multi-criteria decision making methods. International Journal of Operations Research. Vol. 10(2) p. 56–66.
- VIAS J.M., ANDREO B., PERLES M.J., CARRASCO F. 2004. A comparative study of four schemes for groundwater vulnerability mapping in a diffuse flow carbonate aquifer under Mediterranean climatic conditions. Environmental Geology. Vol. 47(4) p. 586–595. DOI 10.1007/s00254-004-1185-y.
- VIAS J.M., ANDREO B., PERLES M.J., CARRASCO F., VADILLO I., JIMÉNEZ P. 2002. Preliminary proposal of a method for vulnerability mapping in carbonate aquifers. In: Proceedings of the 2nd Nerja Cave Geological Symposium Karst and Environment. Nerja, Spain, 15–17.10.2002 p. 20–23.
- VÍAS J.M., ANDREO B., PERLES M.J., CARRASCO F., VADILLO I., JIMÉNEZ P. 2006. Proposed method for groundwater vulnerability mapping in carbonate (karstic) aquifers: The COP method. Hydrogeology Journal. Vol. 14(4) p. 912–925. DOI 10.1007/s10040-006-0023-6.
- WACHNIEW P., ZUREK A. J., STUMPP C., GEMITZI A., GARGINI A., FILIPPINI M., ROZANSKI K., MEEKS J., KVÆRNER J., WITCZAK S. 2016. Toward operational methods for the assessment of intrinsic groundwater vulnerability: A review. Critical Reviews in Environmental Science and Technology. Vol. 46(8) p. 827–884. DOI 10.1080/10643389.2016.1160816.
- WANG J. L., YANG Y. S. 2008. An approach to catchment-scale groundwater nitrate risk assessment from diffuse agricultural sources: a case study in the Upper Bann, Northern Ireland. Hydrological Processes. Vol. 22 p. 4274–4286. DOI 10.1002/hyp.7036.
- WHEELER D. C., NOLAN B. T., FLORY A. R., DELLAVALLE C. T., WARD M. H. 2015. Modeling groundwater nitrate concentrations in private wells in Iowa. Science of The Total Environment. Vol. 536 p. 481–488. DOI 10.1016/j.scitotenv.2015.07.080.
- WORRALL F., BESIEN T. 2005. The vulnerability of groundwater to pesticide contamination estimated directly from observations of presence or absence in wells. Journal of Hydrology. Vol. 303(1–4) p. 92–107. DOI 10.1016/j.jhydrol.2004.08.019.
- WU X., LI B., MA C. 2018. Assessment of groundwater vulnerability by applying the modified DRASTIC model in Beihai City, China. Environmental Science and Pollution Research. Vol. 25(13) p. 12713–12727. DOI 10.1007/s11356-018-1449-9.
- YANG Y.S., WANG L. 2010. Catchment-scale vulnerability assessment of groundwater pollution from diffuse sources using the DRASTIC method: a case study. Hydrological Sciences Journal/Journal des Sciences Hydrologiques. Vol. 55 p. 1206–1216. DOI 10.1080/02626667.2010.508872.
- YESILNACAR M.I., SAHINKAYA E., NAZ M., OZKAYA B. 2007. Neural network prediction of nitrate in groundwater of Harran Plain, Turkey. Environmental Geology. Vol. 56 p. 19–25. DOI 10.1007/s00254-007-1136-5.
- ZHOU J., LI G., LIU F., WANG Y., GUO X. 2009. DRAV model and its application in assessing groundwater vulnerability in arid area: a case study of pore phreatic water in Tarim Basin, Xinjiang, Northwest China. Environmental Earth Sciences. Vol. 60 p. 1055–1063. DOI 10.1007/s12665-009-0250-y.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-3265e217-f73a-4c55-840a-c33bfc60002e