Prediction of groundwater levels from lake levels and climate data using ANN approach

Article English OPEN
Dogan, Ahmet; Demirpence, Husnu; Cobaner, Murat;
(2008)
  • Publisher: Water Research Commission (WRC)
  • Subject: surface water | artificial neural network | interaction | groundwater

There are many environmental concerns relating to the quality and quantity of surface and groundwater. It is very important to estimate the quantity of water by using readily available climate data for managing water resources of the natural environment. As a case study... View more
  • References (37)
    37 references, page 1 of 4

    ALP M and CIGIZOGLU HK (2007) Suspended sediment load simulation by two artificial neural network methods using hydrometeoro - logical data. Environ. Model. Software 22 2-13.

    ASCE Task Committee on Application of Artificial Neural Networks in Hydrology (2000) Artificial neural networks in hydrology. I. Pre - liminary concepts. J. Hydrol. Eng. 5 (2) 115-123.

    AZIZ ARA and WANG KFV (1992) Neural network approach to the determination of aquifer parameters. Ground Water 30 (2) 164-166.

    BATENI SM, BORGHEI SM and JENG DS (2007) Neural network and neuro-fuzzy assessments for scour depth around bridge piers. Eng. Appl. Artif. Intell. 20 401-414.

    CHIBANGA R, BERLAMONT J and VANDEWALLE J (2003) Modelling and forecasting of hydrological variables using artificial neural networks: the Kafue River sub-basin. Hydrol. Sci. J. 48 (3) 363-379.

    CHOI SU and CHEONG S (2006) Prediction of local scour around bridge piers using artificial neural networks. J. Am. Water Resour. Assoc. 42 (2) 487-494.

    CIGIZOGLU HK and KISI O (2005) Flow prediction by three back propagation techniques using k-fold partitioning of neural network training data. Nordic Hydrol. 36 (1) 49-64.

    CLARK WE, MUSGROVE RH, MENKE CG and CAGLE JW (JR) (1964) Water Resources of Alachua, Bradford, Clay and Union Counties, Florida. Florida Geological Survey Rep. of Investigations No. 35. Tallahassee, Florida.

    DAWSON WC and WILBY R (1998) An artificial neural network approach to rainfall-runoff modeling. Hydrol. Sci. J. 43 (1) 47-66.

    DIAS WPS and POOLIYADDA SP (2001) Neural networks for predicting properties of concretes with admixtures. Constr. Build. Mat. 15 371-379.

  • Similar Research Results (1)
  • Related Organizations (3)
  • Metrics
Share - Bookmark