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Volumn 495, Issue , 2013, Pages 38-51

Comparative evaluation of numerical model and artificial neural network for simulating groundwater flow in Kathajodi-Surua Inter-basin of Odisha, India

Author keywords

Artificial neural network; Deltaic aquifer system; Groundwater flow modeling; Kathajodi Surua Inter basin; MODFLOW

Indexed keywords

ALLUVIAL AQUIFER SYSTEMS; ARTIFICIAL NEURAL NETWORK MODELS; COMPARATIVE EVALUATIONS; DELTAIC AQUIFER SYSTEMS; GROUNDWATER FLOW MODELING; KATHAJODI-SURUA INTER-BASIN; MODFLOW; ROOT MEAN SQUARED ERRORS;

EID: 84878372332     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2013.04.041     Document Type: Article
Times cited : (119)

References (51)
  • 1
    • 80052027629 scopus 로고    scopus 로고
    • A wavelet neural network conjunction model for groundwater level forecasting
    • Adamowski J., Chan H.F. A wavelet neural network conjunction model for groundwater level forecasting. J. Hydrol. 2011, 407:28-40.
    • (2011) J. Hydrol. , vol.407 , pp. 28-40
    • Adamowski, J.1    Chan, H.F.2
  • 2
    • 0347135828 scopus 로고    scopus 로고
    • The journey from safe yield to sustainability
    • Alley W.M., Leake S.A. The journey from safe yield to sustainability. Ground Water 2004, 42(1):12-16.
    • (2004) Ground Water , vol.42 , Issue.1 , pp. 12-16
    • Alley, W.M.1    Leake, S.A.2
  • 3
    • 79151468931 scopus 로고    scopus 로고
    • Groundwater modeling of Saq Aquifer Buraydah Al Qassim for better water management strategies
    • Al-Salamah I.S., Ghazaw Y.M., Ghumman A.R. Groundwater modeling of Saq Aquifer Buraydah Al Qassim for better water management strategies. Environ. Monit. Assess. 2011, 173(1-4):851-860.
    • (2011) Environ. Monit. Assess. , vol.173 , Issue.1-4 , pp. 851-860
    • Al-Salamah, I.S.1    Ghazaw, Y.M.2    Ghumman, A.R.3
  • 5
    • 0034174280 scopus 로고    scopus 로고
    • Artificial neural networks in hydrology - I: Preliminary concepts
    • ASCE
    • ASCE Artificial neural networks in hydrology - I: Preliminary concepts. J. Hydrol. Eng. ASCE 2000, 5(2):115-123.
    • (2000) J. Hydrol. Eng. ASCE , vol.5 , Issue.2 , pp. 115-123
  • 6
    • 79551472362 scopus 로고    scopus 로고
    • Artificial neural network model as a potential alternative for groundwater salinity forecasting
    • Banerjee P., Singh V.S., Chattopadhyay K., Chandra P.C., Singh B. Artificial neural network model as a potential alternative for groundwater salinity forecasting. J. Hydrol. 2011, 398:212-220.
    • (2011) J. Hydrol. , vol.398 , pp. 212-220
    • Banerjee, P.1    Singh, V.S.2    Chattopadhyay, K.3    Chandra, P.C.4    Singh, B.5
  • 8
    • 0033911352 scopus 로고    scopus 로고
    • Integrated water management: emerging issues and challenges
    • Bouwer H. Integrated water management: emerging issues and challenges. Agric. Water Manag. 2000, 45:217-228.
    • (2000) Agric. Water Manag. , vol.45 , pp. 217-228
    • Bouwer, H.1
  • 9
    • 3242807004 scopus 로고    scopus 로고
    • Ground Water Resource Estimation Methodology - 1997
    • CGWB, Report of the Ground Water Resource Estimation Committee, Central Ground Water Board (CGWB), Ministry of Water Resources, Government of India, New Delhi, India
    • CGWB, 1997. Ground Water Resource Estimation Methodology - 1997. Report of the Ground Water Resource Estimation Committee, Central Ground Water Board (CGWB), Ministry of Water Resources, Government of India, New Delhi, India, 107 pp.
    • (1997) , pp. 107
  • 10
    • 84878365759 scopus 로고    scopus 로고
    • CGWB, Dynamic Groundwater Resources of India (as on March, 2004). Central Ground Water Board (CGWB), Ministry of Water Resources, New Delhi, India.
    • CGWB, 2006. Dynamic Groundwater Resources of India (as on March, 2004). Central Ground Water Board (CGWB), Ministry of Water Resources, New Delhi, India.
    • (2006)
  • 11
    • 0344984214 scopus 로고    scopus 로고
    • Artificial neural network approach for predicting transient water levels in a multilayered groundwater system under variable state, pumping, and climate conditions
    • Coppola E., Szidarovszky F., Poulton M., Charles E. Artificial neural network approach for predicting transient water levels in a multilayered groundwater system under variable state, pumping, and climate conditions. J. Hydrol. Eng. ASCE 2003, 8(6):348-360.
    • (2003) J. Hydrol. Eng. ASCE , vol.8 , Issue.6 , pp. 348-360
    • Coppola, E.1    Szidarovszky, F.2    Poulton, M.3    Charles, E.4
  • 12
    • 15944365544 scopus 로고    scopus 로고
    • A neural network approach for predicting aquifer water level elevations
    • Coppola E.A., Rana A.J., Poulton M.M., Szidarovszky F., Uhl V.W. A neural network approach for predicting aquifer water level elevations. Ground Water 2005, 43(2):231-241.
    • (2005) Ground Water , vol.43 , Issue.2 , pp. 231-241
    • Coppola, E.A.1    Rana, A.J.2    Poulton, M.M.3    Szidarovszky, F.4    Uhl, V.W.5
  • 13
    • 0034993945 scopus 로고    scopus 로고
    • Artificial neural network modeling of water table depth fluctuations
    • Coulibaly P., Anctil F., Aravena R., Bobee B. Artificial neural network modeling of water table depth fluctuations. Water Resour. Res. 2001, 37(4):885-896.
    • (2001) Water Resour. Res. , vol.37 , Issue.4 , pp. 885-896
    • Coulibaly, P.1    Anctil, F.2    Aravena, R.3    Bobee, B.4
  • 14
    • 20344369583 scopus 로고    scopus 로고
    • Groundwater level forecasting using artificial neural network
    • Daliakopoulos I.N., Coulibaly P., Tsanis I.K. Groundwater level forecasting using artificial neural network. J. Hydrol. 2005, 309:229-240.
    • (2005) J. Hydrol. , vol.309 , pp. 229-240
    • Daliakopoulos, I.N.1    Coulibaly, P.2    Tsanis, I.K.3
  • 15
    • 53649110289 scopus 로고    scopus 로고
    • Methods and technologies to improve efficiency of water use
    • Evans R.G., Sadler E.J.( Methods and technologies to improve efficiency of water use. Water Resour. Res. 2008, 44:W00E04. 10.1029/2007WR006200.
    • (2008) Water Resour. Res. , vol.44
    • Evans, R.G.1    Sadler, E.J.2
  • 16
    • 79952738166 scopus 로고    scopus 로고
    • Combined use of groundwater modeling and potential zone analysis for management of groundwater
    • Gaur S., Chahar B.R., Graillot D. Combined use of groundwater modeling and potential zone analysis for management of groundwater. Int. J. Appl. Earth Obs. Geoinf. 2011, 13:127-139.
    • (2011) Int. J. Appl. Earth Obs. Geoinf. , vol.13 , pp. 127-139
    • Gaur, S.1    Chahar, B.R.2    Graillot, D.3
  • 17
    • 78149414476 scopus 로고    scopus 로고
    • Prediction of water table depth in western region, Orissa using BPNN and RBFN neural networks
    • Ghose D.K., Panda S.N., Swain P.C. Prediction of water table depth in western region, Orissa using BPNN and RBFN neural networks. J. Hydrol. 2010, 394:296-304.
    • (2010) J. Hydrol. , vol.394 , pp. 296-304
    • Ghose, D.K.1    Panda, S.N.2    Swain, P.C.3
  • 18
    • 0347192726 scopus 로고    scopus 로고
    • Sustainable Groundwater Development
    • Special Publication No. 193, Geological Society, London, UK
    • Hiscock, K.M., Rivett, M.O., Davison, R.M. (Eds.), 2002. Sustainable Groundwater Development. Special Publication No. 193, Geological Society, London, UK.
    • (2002)
    • Hiscock, K.M.1    Rivett, M.O.2    Davison, R.M.3
  • 19
    • 42149163573 scopus 로고    scopus 로고
    • Modeling groundwater levels in an urban coastal aquifer using artificial neural networks
    • Krishna B., Rao Y.R.S., Vijaya T. Modeling groundwater levels in an urban coastal aquifer using artificial neural networks. Hydrol. Process. 2008, 22:1180-1188.
    • (2008) Hydrol. Process. , vol.22 , pp. 1180-1188
    • Krishna, B.1    Rao, Y.R.S.2    Vijaya, T.3
  • 20
    • 19744366167 scopus 로고    scopus 로고
    • On the use of neural networks to evaluate groundwater levels in fractured media
    • Lallahem S., Mania J., Hani A., Najjar Y. On the use of neural networks to evaluate groundwater levels in fractured media. J. Hydrol. 2005, 307(1-4):92-111.
    • (2005) J. Hydrol. , vol.307 , Issue.1-4 , pp. 92-111
    • Lallahem, S.1    Mania, J.2    Hani, A.3    Najjar, Y.4
  • 21
    • 84861648332 scopus 로고    scopus 로고
    • Sensitivity analysis of groundwater level in Jinci Spring Basin (China) based on artificial neural network modeling
    • Li X., Shu L., Liu L., Yin D., Wen J. Sensitivity analysis of groundwater level in Jinci Spring Basin (China) based on artificial neural network modeling. Hydrogeol. J. 2012, 20:727-738.
    • (2012) Hydrogeol. J. , vol.20 , pp. 727-738
    • Li, X.1    Shu, L.2    Liu, L.3    Yin, D.4    Wen, J.5
  • 22
    • 0042739695 scopus 로고    scopus 로고
    • Incorporating transient storage in conjunctive stream-aquifer modeling
    • Lin Y.C., Medina M.A. Incorporating transient storage in conjunctive stream-aquifer modeling. Adv. Water Resour. 2003, 26(9):1001-1019.
    • (2003) Adv. Water Resour. , vol.26 , Issue.9 , pp. 1001-1019
    • Lin, Y.C.1    Medina, M.A.2
  • 23
    • 0032034197 scopus 로고    scopus 로고
    • Understanding the behavior and optimizing the performance of backpropagation neural networks: an empirical study
    • Maier H.R., Dandy G.C. Understanding the behavior and optimizing the performance of backpropagation neural networks: an empirical study. Environ. Modeling Softw. 1998, 13:179-191.
    • (1998) Environ. Modeling Softw. , vol.13 , pp. 179-191
    • Maier, H.R.1    Dandy, G.C.2
  • 24
    • 0033957764 scopus 로고    scopus 로고
    • Neural networks for prediction and forecasting of water resources variables: a review of modeling issue and application
    • Maier H.R., Dandy G.C. Neural networks for prediction and forecasting of water resources variables: a review of modeling issue and application. Environ. Modeling Softw. 2000, 15:101-124.
    • (2000) Environ. Modeling Softw. , vol.15 , pp. 101-124
    • Maier, H.R.1    Dandy, G.C.2
  • 25
    • 33745831153 scopus 로고    scopus 로고
    • Water resources and climate change: an Indian perspective
    • Mall R.K., Gupta A., Singh R., Singh R.S., Rathore L.S. Water resources and climate change: an Indian perspective. Curr. Sci. 2006, 90(12):1610-1626.
    • (2006) Curr. Sci. , vol.90 , Issue.12 , pp. 1610-1626
    • Mall, R.K.1    Gupta, A.2    Singh, R.3    Singh, R.S.4    Rathore, L.S.5
  • 27
    • 77953325250 scopus 로고    scopus 로고
    • Artificial neural network modeling for groundwater level forecasting in a river island of eastern India
    • Mohanty S., Jha M.K., Kumar A., Sudheer K.P. Artificial neural network modeling for groundwater level forecasting in a river island of eastern India. Water Resour. Manage. 2010, 24:1845-1865.
    • (2010) Water Resour. Manage. , vol.24 , pp. 1845-1865
    • Mohanty, S.1    Jha, M.K.2    Kumar, A.3    Sudheer, K.P.4
  • 28
    • 84862831589 scopus 로고    scopus 로고
    • Hydrologic and hydrogeologic characterization of a deltaic aquifer system in Orissa, eastern India
    • Mohanty S., Jha M.K., Kumar A., Jena S.K. Hydrologic and hydrogeologic characterization of a deltaic aquifer system in Orissa, eastern India. Water Resour. Manage. 2012, 26(7):1899-1928.
    • (2012) Water Resour. Manage. , vol.26 , Issue.7 , pp. 1899-1928
    • Mohanty, S.1    Jha, M.K.2    Kumar, A.3    Jena, S.K.4
  • 29
    • 32044458602 scopus 로고    scopus 로고
    • Groundwater level forecasting in a shallow aquifer using artificial neural network approach
    • Nayak P.C., Rao Y.R.S., Sudheer K.P. Groundwater level forecasting in a shallow aquifer using artificial neural network approach. Water Resour. Manage. 2006, 20:77-90.
    • (2006) Water Resour. Manage. , vol.20 , pp. 77-90
    • Nayak, P.C.1    Rao, Y.R.S.2    Sudheer, K.P.3
  • 30
    • 50449094792 scopus 로고    scopus 로고
    • Artificial neural networks as an alternative approach to groundwater numerical modeling and environmental design
    • Nikolos I.K., Stergiadi M., Papadopoulou M.P., Karatzas G.P. Artificial neural networks as an alternative approach to groundwater numerical modeling and environmental design. Hydrol. Process. 2008, 22:3337-3348.
    • (2008) Hydrol. Process. , vol.22 , pp. 3337-3348
    • Nikolos, I.K.1    Stergiadi, M.2    Papadopoulou, M.P.3    Karatzas, G.P.4
  • 31
    • 84871024941 scopus 로고    scopus 로고
    • Classification of groundwater level data using SOM to develop ANN-based forecasting model
    • Nourani V., Baghanam A.H., Vousoughi V.D., Alami M.T. Classification of groundwater level data using SOM to develop ANN-based forecasting model. Int. J. Soft Comput. Eng. 2012, 2(1):2231-2307.
    • (2012) Int. J. Soft Comput. Eng. , vol.2 , Issue.1 , pp. 2231-2307
    • Nourani, V.1    Baghanam, A.H.2    Vousoughi, V.D.3    Alami, M.T.4
  • 32
    • 0006139008 scopus 로고
    • Regional management modeling of a complex groundwater system for land subsidence control
    • Onta P.R., Das Gupta A. Regional management modeling of a complex groundwater system for land subsidence control. Water Resour. Manage. 1995, 9(1):1-25.
    • (1995) Water Resour. Manage. , vol.9 , Issue.1 , pp. 1-25
    • Onta, P.R.1    Das Gupta, A.2
  • 33
    • 34248343038 scopus 로고    scopus 로고
    • A numerical modeling and neural network approach to estimate the impact of groundwater abstractions on river flows
    • Parkin G., Birkinshaw S.J., Younger P.L., Rao Z., Kirk S. A numerical modeling and neural network approach to estimate the impact of groundwater abstractions on river flows. J. Hydrol. 2007, 339:15-28.
    • (2007) J. Hydrol. , vol.339 , pp. 15-28
    • Parkin, G.1    Birkinshaw, S.J.2    Younger, P.L.3    Rao, Z.4    Kirk, S.5
  • 34
    • 0034733525 scopus 로고    scopus 로고
    • Annual replenishable groundwater potential of India - an estimate based on injected tritium studies
    • Rangarajan R., Athavale R.N. Annual replenishable groundwater potential of India - an estimate based on injected tritium studies. J. Hydrol. 2000, 234(1&2):38-53.
    • (2000) J. Hydrol. , vol.234 , Issue.1-2 , pp. 38-53
    • Rangarajan, R.1    Athavale, R.N.2
  • 35
    • 0035282705 scopus 로고    scopus 로고
    • Regional groundwater flow modeling of the Glacial Lake Agassiz Peatlands, Minnesota
    • Reeve A.S., Warzocha J., Glaser P.H., Siegel D.I. Regional groundwater flow modeling of the Glacial Lake Agassiz Peatlands, Minnesota. J. Hydrol. 2001, 243(2):91-100.
    • (2001) J. Hydrol. , vol.243 , Issue.2 , pp. 91-100
    • Reeve, A.S.1    Warzocha, J.2    Glaser, P.H.3    Siegel, D.I.4
  • 36
    • 0029511266 scopus 로고
    • Groundwater-surface water management with stochastic water supplies: a simulation-optimization approach
    • Reichard E.G. Groundwater-surface water management with stochastic water supplies: a simulation-optimization approach. Water Resour. Res. 1995, 31(11):2845-2865.
    • (1995) Water Resour. Res. , vol.31 , Issue.11 , pp. 2845-2865
    • Reichard, E.G.1
  • 37
    • 69149086364 scopus 로고    scopus 로고
    • Satellite-based estimates of groundwater depletion in India
    • Rodell M., Velicogna I., Famiglietti J.S. Satellite-based estimates of groundwater depletion in India. Nature 2009, 460:999-1002.
    • (2009) Nature , vol.460 , pp. 999-1002
    • Rodell, M.1    Velicogna, I.2    Famiglietti, J.S.3
  • 38
    • 33645888114 scopus 로고    scopus 로고
    • Modeling stream-aquifer interactions in a shallow aquifer Choele Choel Island, Patagonia, Argentina
    • Rodriguez L.B., Cello P.A., Vionett C.A. Modeling stream-aquifer interactions in a shallow aquifer Choele Choel Island, Patagonia, Argentina. Hydrogeol. J. 2006, 14:591-602.
    • (2006) Hydrogeol. J. , vol.14 , pp. 591-602
    • Rodriguez, L.B.1    Cello, P.A.2    Vionett, C.A.3
  • 41
    • 20044380216 scopus 로고    scopus 로고
    • Groundwater recharge and sustainability in the high plains aquifer in Kansas, USA
    • Sophocleous M.A. Groundwater recharge and sustainability in the high plains aquifer in Kansas, USA. Hydrogeol. J. 2005, 13(2):351-365.
    • (2005) Hydrogeol. J. , vol.13 , Issue.2 , pp. 351-365
    • Sophocleous, M.A.1
  • 42
    • 0031905336 scopus 로고    scopus 로고
    • Development of a preliminary groundwater flow model for water resources management in the Pingtung Plain, Taiwan
    • Ting C.S., Zhou Y., Vries J.J.de, Simmers I. Development of a preliminary groundwater flow model for water resources management in the Pingtung Plain, Taiwan. Groundwater 1998, 35(6):20-35.
    • (1998) Groundwater , vol.35 , Issue.6 , pp. 20-35
    • Ting, C.S.1    Zhou, Y.2    Vries, J.3    Simmers, I.4
  • 43
    • 70349251374 scopus 로고    scopus 로고
    • Optimal selection of artificial neural network parameters for the prediction of a karstic aquifer's response
    • Trichakis I.C., Nikolos I.K., Karatzas G.P. Optimal selection of artificial neural network parameters for the prediction of a karstic aquifer's response. Hydrol. Process. 2009, 23(20):2956-2969.
    • (2009) Hydrol. Process. , vol.23 , Issue.20 , pp. 2956-2969
    • Trichakis, I.C.1    Nikolos, I.K.2    Karatzas, G.P.3
  • 44
    • 33846095406 scopus 로고    scopus 로고
    • Using statistical and artificial neural network models to forecast potentiometric levels at a deep well in South Texas
    • Uddameri V. Using statistical and artificial neural network models to forecast potentiometric levels at a deep well in South Texas. Environ. Geol. 2007, 51:885-895.
    • (2007) Environ. Geol. , vol.51 , pp. 885-895
    • Uddameri, V.1
  • 45
    • 84876534283 scopus 로고    scopus 로고
    • Groundwater depletion in middle east from GRACE with implications for transboundary water management in the Tigris-Euphrates-Western Iran region
    • Voss K.A., Famiglietti J.S., Lo M., de Linage C., Rodell M., Swenson S.C. Groundwater depletion in middle east from GRACE with implications for transboundary water management in the Tigris-Euphrates-Western Iran region. Water Resour. Res. 2013, 49:904-914. 10.1002/wrcr.20078.
    • (2013) Water Resour. Res. , vol.49 , pp. 904-914
    • Voss, K.A.1    Famiglietti, J.S.2    Lo, M.3    de Linage, C.4    Rodell, M.5    Swenson, S.C.6
  • 47
    • 44449131375 scopus 로고    scopus 로고
    • The United Nations World Water Development Report 1: Water for People Water for Life
    • World Water Assessment Program, UNESCO, Paris and Berghahn Books
    • World Water Assessment Program, 2003. The United Nations World Water Development Report 1: Water for People Water for Life. UNESCO, Paris and Berghahn Books, 575 pp.
    • (2003) , pp. 575
  • 48
    • 84155181080 scopus 로고    scopus 로고
    • Integration of SWAP and MODFLOW-2000 for modeling groundwater dynamics in shallow water table areas
    • Xu X., Huang G., Zhan H., Qu Z., Huang Q. Integration of SWAP and MODFLOW-2000 for modeling groundwater dynamics in shallow water table areas. J. Hydrol. 2012, 412-413:170-181.
    • (2012) J. Hydrol. , pp. 170-181
    • Xu, X.1    Huang, G.2    Zhan, H.3    Qu, Z.4    Huang, Q.5
  • 49
    • 78650179085 scopus 로고    scopus 로고
    • A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer
    • Yoon H., Jun S.C., Hyun Y., Bae G.O., Lee K.K. A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer. J. Hydrol. 2011, 396:128-138.
    • (2011) J. Hydrol. , vol.396 , pp. 128-138
    • Yoon, H.1    Jun, S.C.2    Hyun, Y.3    Bae, G.O.4    Lee, K.K.5
  • 51
    • 45849149302 scopus 로고    scopus 로고
    • Simulating the impacts of groundwater pumping on stream-aquifer dynamics in semi-arid north-western Oklahoma, USA
    • Zume J., Tarhule A. Simulating the impacts of groundwater pumping on stream-aquifer dynamics in semi-arid north-western Oklahoma, USA. Hydrogeol. J. 2008, 16:797-810.
    • (2008) Hydrogeol. J. , vol.16 , pp. 797-810
    • Zume, J.1    Tarhule, A.2


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