Regional groundwater productivity potential mapping using a geographic information system (GIS) based artificial neural network model;Cartographie régionale du potentiel de productivité des aquifères à partir d'un système d'information géographique base sur un modèle de réseau de neurones artificiels

Hydrogeology Journal

Volumn 20, Issue 8, 2012, Pages 1511-1527

  Lee, Saro ^a   Song, Kyo Young ^a   Kim, Yongsung ^b   Park, Inhye ^c  

^a Korea Institute of Geosceince and Mineral Resources   (South Korea)

^b GeoGreen22 Co Ltd   (South Korea)

^c University of Seoul   (South Korea)

Author keywords

Back propagation training; Geographic information systems; Groundwater development; Hydrogeological factor; Korea

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; GIS; GROUNDWATER FLOW; HYDROGEOLOGY; MAPPING;

NORTH KYONGSANG; POHANG; SOUTH KOREA;

EID: 84870653357     PISSN: 14312174     EISSN: 14350157     Source Type: Journal    
DOI: 10.1007/s10040-012-0894-7     Document Type: Article

References (55)

1. Adinarayana J, Krishna NR (1996) Integration of multi-seasonal remotely-sensed images for improved landuse classification of a hilly watershed using geographical information systems. Int J Remote Sens 17: 1679-1688.
2. Atkinson PM, Tatnall ARL (1997) Neural networks in remote sensing. Int J Remote Sens 18: 699-709.
3. Chenini I, Mammou AB (2010) Groundwater recharge study in arid region: an approach using GIS techniques and numerical modeling. Comput Geosci 36: 801-817.
4. Corsini A, Cervi F, Ronchetti F (2009) Weight of evidence and artificial neural networks for potential groundwater spring mapping: an application to the Mt. Modino area (Northern Apennines, Italy). Geomorphology 111: 79-87.
5. Dar IA, Sankar K, Dar MA (2010) Remote sensing technology and geographic information system modeling: an integrated approach towards the mapping of groundwater potential zones in Hardrock terrain, Mamundiyar basin. J Hydrol 394: 285-295.
6. Engman ET, Gurney RJ (1991) Remote sensing in hydrology. Chapman and Hall, London.
7. Garrett JH (1994) Where and why artificial neural networks are applicable in civil engineering. J Comput Civil Eng 8(2): 129-130.
8. Gleick PH (1993) Water in crisis: a guide to the world's fresh water resources. Oxford University Press, New York.
9. Hardcastle KC (1995) Photolineament factor: a new computer-aided method for remotely sensing the degree to which bedrock is fractured. Photogramm Eng Rem S 61: 739-747.
10. Hines JW (1997) Fuzzy and neural approaches in engineering. Wiley, New York.
11. Hwang JH, Kim DH, Cho DL, Song KY (1996) Explanatory note of the Andong sheet. Korea Institute of Geoscience and Mineral Resources, Daejeon, Korea.
12. Israil M, Al-hadithi M, Singhal DC (2006) Application of resistivity survey and geographical information system (GIS) analysis for hydrogeological zoning of a piedmont area, Himalayan foothill region, India. Hydrogeol J 14: 753-759.
13. Jaiswal RK, Mukherjee S, Krishnamurthy J, Saxena R (2003) Role of remote sensing and GIS techniques for generation of groundwater prospect zones towards rural development: an approach. Int J Remote Sens 24: 993-1008.
14. Jasmin I, Mallikarjuna P (2011) Review: satellite-based remote sensing and geographic information systems and their application in the assessment of groundwater potential, with particular reference to India. Hydrogeol J. doi: 10. 1007/s10040-011-0712-7.
15. Jha MK, Peiffer S (2006) Applications of remote sensing and GIS technologies in groundwater hydrology: past, present and future. Bayreuth University Press, Bayreuth, Germany.
16. Jha MK, Chowdhury A, Chowdary VM, Peiffer S (2007) Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints. Water Resour Manag 21: 427-467.
17. Kane WF, Peters DC, Speirer RA (1996) Remote sensing in investigation of engineered underground structures. J Geotech Eng 122: 674-681.
18. Kenny JF, Barber NL, Hutson SS, Linsey KS, Lovelace JK, Maupin MA (2009) Estimated use of water in the United States in 2005. US Geol Surv Circ 1344, 52 pp.
19. Kiesel J, Fohrer N, Schmalz B, White MJ (2010) Incorporating landscape depressions and tile drainages of a northern German lowland catchment into a semi-distributed model. Hydrol Process 24: 1472-1486.
20. Kim DH, Hwang JH, Park KH, Song KY (1998) Explanatory note of the Busan sheet. Korea Institute of Geoscience and Mineral Resources, Daejeon, Korea.
21. Kim NW, Lee JW, Lee J, Lee JE (2010) SWAT application to estimate design runoff curve number for South Korean conditions. Hydrol Process 24: 2156-2170.
22. Koike K, Nagano S, Kawaba K (1998) Construction and analysis of interpreted fracture planes through combination of satellite-image derived lineaments and digital elevation model data. Comput Geosci 24: 573-583.
23. Korea Institute of Geoscience and Mineral Resource (1964) Geological map, 1: 50, 000. KIGMR, Daejeon, Korea.
24. Korean Ministry for Food, Agriculture, Forestry and Fisheries (1985-2005) Rural groundwater survey report. KMFAFF, Seoul.
25. Korean Ministry of Land, Transport and Maritime Affairs (1995) National groundwater monitoring network construction report. KMLMA, Seoul.
26. Korean Ministry of Land, Transport and Maritime Affairs (1998) National groundwater monitoring network construction report. KMLMA, Seoul.
27. Korean Ministry of Land, Transport and Maritime Affairs (2001) National groundwater monitoring network construction report. KMLMA, Seoul.
28. Korean Ministry of Land, Transport and Maritime Affairs (2003) Report of groundwater in Pohang area. KMLMA, Seoul.
29. Korean Ministry of Land, Transport and Maritime Affairs (2006) National groundwater monitoring network construction report. KMLMA, Seoul.
30. Korean Ministry of Land, Transport and Maritime Affairs (2009) National groundwater monitoring network construction report. KMLMA, Seoul.
31. Kumar MG, Bali R, Agarwal AK (2009) Integration of remote sensing and electrical sounding data for hydrogeological exploration: a case study of Bakhar watershed, India. Hydrolog Sci J 54: 949-960.
32. Lee S, Dan NT (2005) Probabilistic landslide susceptibility mapping in the Lai Chau province of Vietnam: focus on the relationship between tectonic fractures and landslides. Environ Geol 48: 778-787.
33. Lee S, Kim YS, Oh HJ (2012) Application of a weights-of-evidence method and GIS to regional groundwater productivity potential mapping. J Environ Manage 96: 91-105.
34. Livingstone DJ, Manallack DT, Tetko IV (1997) Data modelling with neural networks: advantages and limitations. J Comput Aid Mol Des 11: 135-142.
35. Madrucci V, Taioli F, de Araújo CC (2008) Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, São Paulo State, Brazil. J Hydrol 357: 153-173.
36. Murthy KSR (2000) Ground water potential in a semi-arid region of Andhra Pradesh: a geographical information system approach. Int J Remote Sens 21: 1867-1884.
37. Murthy KSR, Mamo AG (2009) Multi-criteria decision evaluation in groundwater zones identification in Moyale-Teltele subbasin, South Ethiopia. Int J Remote Sens 30: 2729-2740.
38. National Academy of Agricultural Science (1977) Detailed soil map, 1: 25, 000. NAAS, Seoul.
39. National Geographic Information Institute (1997) Digital topographic map, 1: 5, 000. NGII, Seoul.
40. O'Leary DW, Friedman JD, Pohn HA (1976) Lineament, linear, lineation; some proposed new standards for old terms. Geol Soc Am Bull 87: 1463-1469.
41. Oh H-J, Kim Y-S, Choi J-K, Park E, Lee S (2011) GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea. J Hydrol 399: 158-172.
42. Paola JD, Schowengerdt RA (1995) A review and analysis of backpropagation neural networks for classification of remotely sensed multi-spectral imagery. Int J Remote Sens 16: 3033-3058.
43. Park YJ, Lee KK, Kim JM (2001) Effects of highly permeable geological discontinuities upon groundwater productivity and well yield. Math Geol 32: 605-618.
44. Pradhan B (2009) Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques. Cent Eur J Geosci 1: 120-129.
45. Ranganai RT, Ebinger CJ (2008) Aeromagnetic and Landsat TM structural interpretation for identifying regional groundwater exploration targets, south-central Zimbabwe Craton. J Appl Geophys 65: 73-83.
46. Sander P, Chesley MM, Minor TB (1996) Groundwater assessment using remote sensing and GIS in a rural groundwater project in Ghana: lessons learned. Hydrogeol J 4: 40-49.
47. Saud MA (2010) Mapping potential areas for groundwater storage in Wadi Aurnah Basin, western Arabian Peninsula, using remote sensing and geographic information system techniques. Hydrogeol J 18: 1481-1495.
48. Singh CK, Shashtri S, Singh A, Mukherjee S (2011) Quantitative modeling of groundwater in Satluj River basin of Rupnagar district of Punjab using remote sensing and geographic information system. Environ Earth Sci 62: 871-881.
49. Solomon S, Quiel F (2006) Groundwater study using remote sensing and geographic information system (GIS) in the central highlands of Eritrea. Hydrogeol J 14: 729-741.
50. Srivastava P, Bhattacharya A (2006) Groundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain. Int J Remote Sens 27: 4599-4620.
51. Todd DK (1980) Groundwater hydrology. Wiley, New York, pp 111-163.
52. Todd DK, Mays LW (2005) Groundwater hydrology. Wiley, New York.
53. Vijay R, Panchbhai N, Gupta A (2007) Spatio-temporal analysis of groundwater recharge and mound dynamics in an unconfined aquifer: a GIS-based approach. Hydrol Process 21: 2760-2764.
54. Yeh HF, Lee CH, Hsu KC, Chang PH (2009) GIS for the assessment of the groundwater recharge potential zone. Environ Geol 58: 185-195.
55. Zhou W (1999) Verification of the nonparametric characteristics of backpropagation neural networks for image classification. IEEE T Geosci Remote 37: 771-779.