메뉴 건너뛰기




Volumn 4, Issue 21, 2012, Pages 4284-4292

Development of an ANN-based model for forecasting River Kaduna discharge

Author keywords

Artificial neural networks; Discharge; Forecasting; River Kaduna; Water resources

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; CONVENTIONAL METHODS; CORRELATION VALUE; DATA SETS; DISCHARGE PREDICTIONS; INPUT VARIABLES; PAUCITY OF DATA; RIVER DISCHARGE; TRAINING DATA; VALIDATION DATA; WATER RESOURCES PLANNING;

EID: 84866039271     PISSN: 20407459     EISSN: 20407467     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (1)

References (34)
  • 1
    • 33645158824 scopus 로고    scopus 로고
    • Rainfall-runoff modelling using artificial neural network techniques: A Blue Nile catchment case study
    • Antar, M.A., I. Elassiouti and M.N. Allam, 2006. Rainfall-runoff modelling using artificial neural network techniques: A Blue Nile catchment case study. Hydrol. Process., 20: 1201-1216.
    • (2006) Hydrol. Process. , vol.20 , pp. 1201-1216
    • Antar, M.A.1    Elassiouti, I.2    Allam, M.N.3
  • 3
    • 0034174396 scopus 로고    scopus 로고
    • Task committee on application of artificial neural networks in hydrology, II: Hydrologic application
    • ASCE
    • ASCE, 2000a. Task committee on application of artificial neural networks in hydrology, II: Hydrologic application. J. Hydrol. Eng., 5: 124-136.
    • (2000) J. Hydrol. Eng. , vol.5 , pp. 124-136
  • 4
    • 0034174280 scopus 로고    scopus 로고
    • Task committee on application of artificial neural networks in hydrology, artificial neural networks in hydrology, I: Preliminary concepts
    • ASCE
    • ASCE, 2000b. Task committee on application of artificial neural networks in hydrology, artificial neural networks in hydrology, I: Preliminary concepts. J. Hydrol. Eng., 5: 115-123.
    • (2000) J. Hydrol. Eng. , vol.5 , pp. 115-123
  • 5
    • 0032701316 scopus 로고    scopus 로고
    • A neural network approach to identifying non-point sourcesa of microbial contamination
    • Brion, G.M. and S. Lingireddy, 1999. A neural network approach to identifying non-point sourcesa of microbial contamination. Water Resour., 33: 3099.
    • (1999) Water Resour. , vol.33 , pp. 3099
    • Brion, G.M.1    Lingireddy, S.2
  • 6
    • 0039514419 scopus 로고
    • Sensitivity of water resources in the great lakes region to changes temperature, precipitation, humidity and wind speed
    • (Proceedings of the Vancouver Symposium, August 1987), IAHS Publ. No. 168
    • Cohen, S., 1987. Sensitivity of water resources in the great lakes region to changes temperature, precipitation, humidity and wind speed. The Influence of Climate Change and Climate Variability on the Hydrologic Regime and Water Resources, (Proceedings of the Vancouver Symposium, August 1987), IAHS Publ. No. 168, pp: 489-499.
    • (1987) The Influence of Climate Change and Climate Variability on the Hydrologic Regime and Water Resources , pp. 489-499
    • Cohen, S.1
  • 8
    • 0029413797 scopus 로고
    • Artificial neural network modelling of the rainfall-runoff process
    • Hsu, K., H.V. Gupta and S. Sorooshian, 1995. Artificial neural network modelling of the rainfall-runoff process. Water Resour. Res., 31: 2517-2530.
    • (1995) Water Resour. Res. , vol.31 , pp. 2517-2530
    • Hsu, K.1    Gupta, H.V.2    Sorooshian, S.3
  • 9
    • 0034641121 scopus 로고    scopus 로고
    • River flow prediction using artificial neural networks, generalisation beyond calibration range
    • Imrie, C.E., S. Durucan and A. Korre, 2000. River flow prediction using artificial neural networks, generalisation beyond calibration range. J. Hydrol., 233: 138-153.
    • (2000) J. Hydrol. , vol.233 , pp. 138-153
    • Imrie, C.E.1    Durucan, S.2    Korre, A.3
  • 10
    • 0344630525 scopus 로고
    • Change in annual, seasonal and monthly Rainfall in Nigeria, during 1961-1990 and consequences to agriculture
    • Jagtap, S.S., 1995. Change in annual, seasonal and monthly Rainfall in Nigeria, during 1961-1990 and consequences to agriculture. Acad. Sci., 7(4): 311- 426.
    • (1995) Acad. Sci. , vol.7 , Issue.4 , pp. 311-426
    • Jagtap, S.S.1
  • 11
    • 0033197895 scopus 로고    scopus 로고
    • Application of ANN for reservoir inflow prediction and operation
    • Jain, S.K., D. Das and D.K. Srivastava, 1999. Application of ANN for reservoir inflow prediction and operation. J. Water Resour. Plann. Mgmt. ASCE, 125(5): 263-271.
    • (1999) J. Water Resour. Plann. Mgmt. ASCE , vol.125 , Issue.5 , pp. 263-271
    • Jain, S.K.1    Das, D.2    Srivastava, D.K.3
  • 13
    • 1642497522 scopus 로고    scopus 로고
    • River flow modelling using artificial neural networks
    • Kisi, O., 2004. River flow modelling using artificial neural networks. ASCE J. Hydrol. Eng., 9(1): 60-63.
    • (2004) ASCE J. Hydrol. Eng. , vol.9 , Issue.1 , pp. 60-63
    • Kisi, O.1
  • 14
    • 12544259920 scopus 로고    scopus 로고
    • Daily river flow forecasting using artificial neural networks
    • Kisi, O., 2005. Daily river flow forecasting using artificial neural networks. Turkey J. Eng. Environ. Sci., 29: 9-20.
    • (2005) Turkey J. Eng. Environ. Sci. , vol.29 , pp. 9-20
    • Kisi, O.1
  • 15
    • 0027789273 scopus 로고
    • Frequency of extremes runoff and its relation to climate fluctuations
    • Krasovskaia, I. and I. Gottenschalk, 1993. Frequency of extremes runoff and its relation to climate fluctuations. Nordic Hydrol., 24: 1-12.
    • (1993) Nordic Hydrol. , vol.24 , pp. 1-12
    • Krasovskaia, I.1    Gottenschalk, I.2
  • 16
    • 84866038897 scopus 로고
    • Development and application of procedures for classifying flow regimes in northern and Western Europe
    • (Proceeding of 2nd International FRIEND Conference, UNESCO, Braunschweig, Germany, Oct., 1993), IAHS Publ. 6 No.221
    • Krasovskaia, I., N.W. Arnell and I. Gottenschalk, 1993. Development and application of procedures for classifying flow regimes in northern and Western Europe, In: FRIEND:-flow regimes from international experimental and network data. (Proceeding of 2nd International FRIEND Conference, UNESCO, Braunschweig, Germany, Oct., 1993), IAHS Publ. 6 No.221, pp: 185-193.
    • (1993) FRIEND:-flow regimes from international experimental and network data , pp. 185-193
    • Krasovskaia, I.1    Arnell, N.W.2    Gottenschalk, I.3
  • 17
    • 0025231021 scopus 로고
    • Hydrologic sensitivities of the Sacramento-san Joaquin river basin, California, to global warming
    • Lettenmaier, D.P and T.Y. Gan, 1990. Hydrologic sensitivities of the Sacramento-san Joaquin river basin, California, to global warming. Water Resour. J., 26(1): 69-86.
    • (1990) Water Resour. J. , vol.26 , Issue.1 , pp. 69-86
    • Lettenmaier, D.P.1    Gan, T.Y.2
  • 19
    • 0029663621 scopus 로고    scopus 로고
    • The use of artificial neural networks for the prediction of water quality parameters
    • Maier, H.R. and G.C. Dandy, 1996. The use of artificial neural networks for the prediction of water quality parameters. Water Resour., 32: 1013-1022.
    • (1996) Water Resour. , vol.32 , pp. 1013-1022
    • Maier, H.R.1    Dandy, G.C.2
  • 20
    • 0020178893 scopus 로고
    • Sensitivity of water resources systems to climate variation
    • Nemec, J. and J. Schaake, 1982. Sensitivity of water resources systems to climate variation. Hydrol. Sci. J., 27(3): 327-343.
    • (1982) Hydrol. Sci. J. , vol.27 , Issue.3 , pp. 327-343
    • Nemec, J.1    Schaake, J.2
  • 22
    • 0029413038 scopus 로고
    • Multivariate modelling of water resources time-series using artificial neural networks
    • Raman, H. and R. Sunilkumar, 1995. Multivariate modelling of water resources time-series using artificial neural networks. J. Hydrol. Sci., 40: 145-163.
    • (1995) J. Hydrol. Sci. , vol.40 , pp. 145-163
    • Raman, H.1    Sunilkumar, R.2
  • 25
    • 79960055476 scopus 로고    scopus 로고
    • Temperature variability and outbreak of meningitis and measles in Zaria, northern Nigeria
    • Sawa, B.A. and B. Buhari, 2010. Temperature variability and outbreak of meningitis and measles in Zaria, northern Nigeria. Resc. J. Appl. Sci. Egnr. Technol., 3(5): 399-402.
    • (2010) Resc. J. Appl. Sci. Egnr. Technol. , vol.3 , Issue.5 , pp. 399-402
    • Sawa, B.A.1    Buhari, B.2
  • 26
    • 0342506462 scopus 로고    scopus 로고
    • Application of a neural network techniques to rainfall-runoff modelling
    • Shamseldin, A.Y., 1997. Application of a neural network techniques to rainfall-runoff modelling. J. Hydrol., 199: 272-294.
    • (1997) J. Hydrol. , vol.199 , pp. 272-294
    • Shamseldin, A.Y.1
  • 27
    • 0037199712 scopus 로고    scopus 로고
    • River flow Forecasting: Use of phase space reconstruction and artificial neural networks Approaches
    • Sivakumar, B., A.W. Jayawardena and T.M.K.G. Fernando, 2002. River flow Forecasting: Use of phase space reconstruction and artificial neural networks Approaches. J. Hydrol., 265: 225-245.
    • (2002) J. Hydrol. , vol.265 , pp. 225-245
    • Sivakumar, B.1    Jayawardena, A.W.2    Fernando, T.M.K.G.3
  • 28
    • 0029416249 scopus 로고
    • Neural network models of rainfall-runoff process
    • Smith, J. and R.N. Eli, 1995. Neural network models of rainfall-runoff process. J. Water Resour. Plan. Mgmt., 121: 499-508.
    • (1995) J. Water Resour. Plan. Mgmt. , vol.121 , pp. 499-508
    • Smith, J.1    Eli, R.N.2
  • 29
    • 0033167344 scopus 로고    scopus 로고
    • Rainfall-runoff modelling using artificial neural networks
    • Tokar, A.S. and P.A. Johnson, 1999. Rainfall-runoff modelling using artificial neural networks. J. Hydrol. Eng., 4(3): 232-239.
    • (1999) J. Hydrol. Eng. , vol.4 , Issue.3 , pp. 232-239
    • Tokar, A.S.1    Johnson, P.A.2
  • 30
    • 0026284389 scopus 로고
    • Effects of climate change on discharges and snow cover in Finland
    • Vehvilainen, B. and J. Lohvansuu, 1991. Effects of climate change on discharges and snow cover in Finland. J. Hydrol. Sci., 36: 109-121.
    • (1991) J. Hydrol. Sci. , vol.36 , pp. 109-121
    • Vehvilainen, B.1    Lohvansuu, J.2
  • 31
    • 0000908208 scopus 로고
    • Some runoff characteristics of British River
    • Ward, R.C., 1968. Some runoff characteristics of British River. J. Hydrol., 6: 358-372.
    • (1968) J. Hydrol. , vol.6 , pp. 358-372
    • Ward, R.C.1
  • 34
    • 0031239528 scopus 로고    scopus 로고
    • Forecasting raw-water quality parameters for the north saskatchewan river by neural network modelling
    • Zhang, Q. and S.J. Stanley, 1997. Forecasting raw-water quality parameters for the north saskatchewan river by neural network modelling. Water Resour., 31: 2340-2350.
    • (1997) Water Resour. , vol.31 , pp. 2340-2350
    • Zhang, Q.1    Stanley, S.J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.