메뉴 건너뛰기




Volumn 31, Issue 15-16, 2006, Pages 928-934

Forecasting runoff coefficients using ANN for water resources management: The case of Notwane catchment in Eastern Botswana

Author keywords

Artificial neural network; Principal component analysis; Runoff coefficient; Water balance method

Indexed keywords

ALGORITHMS; CATCHMENTS; COMPUTER ARCHITECTURE; FORECASTING; LAND USE; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS; TRANSFER FUNCTIONS; WATER RESOURCES;

EID: 33748891409     PISSN: 14747065     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.pce.2006.08.017     Document Type: Article
Times cited : (28)

References (19)
  • 2
    • 0031932822 scopus 로고    scopus 로고
    • Neural networks to assess influence of changing seasonal climates in modifying discharge, dissolved organic carbon, and nitrogen export in eastern Canadian rivers
    • Clair T.A., and Ehrman J.M. Neural networks to assess influence of changing seasonal climates in modifying discharge, dissolved organic carbon, and nitrogen export in eastern Canadian rivers. Water Resources Research 34 3 (1998) 447-455
    • (1998) Water Resources Research , vol.34 , Issue.3 , pp. 447-455
    • Clair, T.A.1    Ehrman, J.M.2
  • 4
    • 0030588334 scopus 로고    scopus 로고
    • Simulation of a century of runoff across the Tomales Watershed, Marian County, California
    • Fischer D.T., Smith S.V., and Churchill R.B. Simulation of a century of runoff across the Tomales Watershed, Marian County, California. Journal of Hydrology 186 (1996) 253-273
    • (1996) Journal of Hydrology , vol.186 , pp. 253-273
    • Fischer, D.T.1    Smith, S.V.2    Churchill, R.B.3
  • 5
    • 0031998129 scopus 로고    scopus 로고
    • Application example of neural networks for time series analysis: rainfall - runoff modelling
    • Furundzic D. Application example of neural networks for time series analysis: rainfall - runoff modelling. Signal Processing 64 (1997) 383-396
    • (1997) Signal Processing , vol.64 , pp. 383-396
    • Furundzic, D.1
  • 6
    • 13244251543 scopus 로고    scopus 로고
    • Self-organizing linear output map (SOLO): an artificial neural network suitable for hydrologic modelling and analysis
    • Hsu K., Gupta H.V., Gao X., Sorooshian S., and Imam B. Self-organizing linear output map (SOLO): an artificial neural network suitable for hydrologic modelling and analysis. Journal of Hydrology 38 12 (2002) 1-17
    • (2002) Journal of Hydrology , vol.38 , Issue.12 , pp. 1-17
    • Hsu, K.1    Gupta, H.V.2    Gao, X.3    Sorooshian, S.4    Imam, B.5
  • 7
    • 0344393246 scopus 로고    scopus 로고
    • Jones J.A.A., Liu C., Woo M., and Kung H. (Eds), Kulwer Academic Publishers, London
    • In: Jones J.A.A., Liu C., Woo M., and Kung H. (Eds). Regional Hydrological response to Climate Change (1996), Kulwer Academic Publishers, London
    • (1996) Regional Hydrological response to Climate Change
  • 8
    • 33748897835 scopus 로고    scopus 로고
    • Lungu, E.M., Sefe, F.T.K., 1989. Urban and peri-urban hydrology - groundwater pollution, rural dams and flood hazards. Swedeplan, Gaborone. Final report.
  • 9
    • 33748911940 scopus 로고    scopus 로고
    • Malasri, S., Lin, L., 1992. Forecasting with artificial neural networks. In: Proceedings of Arkansas Academy of Sciences, pp. 1-7.
  • 10
    • 33645973241 scopus 로고    scopus 로고
    • Nilsson, P., Uvo, C.B., Berndtsson, R., 2006. Monthly runoff simulation: comparing and combining conceptual and neural network models. 321, 344-363.
  • 11
    • 27644537224 scopus 로고    scopus 로고
    • Prediction of flow characteristics using multiple regression and neural networks: a case study in Zimbabwe
    • Mazvimavi D., Maijerink A.M.J., Savenije H.H.G., and Stein A. Prediction of flow characteristics using multiple regression and neural networks: a case study in Zimbabwe. Physics and Chemistry of the Earth 30 (2005) 639-647
    • (2005) Physics and Chemistry of the Earth , vol.30 , pp. 639-647
    • Mazvimavi, D.1    Maijerink, A.M.J.2    Savenije, H.H.G.3    Stein, A.4
  • 13
    • 4644296256 scopus 로고    scopus 로고
    • Predicting catchment flow in a semi-arid region via an artificial neural network technique
    • Riad S., Mania J., Bouchaou L., and Najjar Y. Predicting catchment flow in a semi-arid region via an artificial neural network technique. Hydrological Processes Journal 18 13 (2004) 2387-2393
    • (2004) Hydrological Processes Journal , vol.18 , Issue.13 , pp. 2387-2393
    • Riad, S.1    Mania, J.2    Bouchaou, L.3    Najjar, Y.4
  • 14
    • 0342506462 scopus 로고    scopus 로고
    • Application of a neural network technique to rainfall-runoff modelling
    • Shamseldin A.Y. Application of a neural network technique to rainfall-runoff modelling. Journal of Hydrology 199 (1997) 272-294
    • (1997) Journal of Hydrology , vol.199 , pp. 272-294
    • Shamseldin, A.Y.1
  • 15
    • 33748903786 scopus 로고    scopus 로고
    • The Mathworks Inc., 2002. Neural Network Toolbox; For Use with MATLAB, User's Guide Version 4.
  • 16
    • 33748912639 scopus 로고    scopus 로고
    • Thornthwaite, C.W., Mather, J.R., 1955. The Water Balance: Laboratory of Climatology. Pub. No. 8, Centerton, NJ.
  • 18
    • 33748898223 scopus 로고    scopus 로고
    • Vision 2016, 1997. Vision 2016 Towards Prosperity for All, Presential task Group for long Term Vision for Botswana, Gaborone, Botswana.
  • 19
    • 0033019602 scopus 로고    scopus 로고
    • Short term streamflow forecasting using artificial neural networks
    • Zealand C.M., Burn D.H., and Simonovic S.P. Short term streamflow forecasting using artificial neural networks. Journal of Hydrology 214 (1999) 32-48
    • (1999) Journal of Hydrology , vol.214 , pp. 32-48
    • Zealand, C.M.1    Burn, D.H.2    Simonovic, S.P.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.