Using Artificial Neural Network Approach for Simultaneous Forecasting of Weekly Groundwater Levels at Multiple Sites

Reliable forecast of groundwater level is necessary for its sustainable use and for planning land and water management strategies. This paper deals with an application of artificial neural network (ANN) approach to the weekly forecasting of groundwater levels in multiple wells located over a river b...

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Veröffentlicht in:	Water resources management Jg. 29; H. 15; S. 5521 - 5532
Hauptverfasser:	Mohanty, S., Jha, Madan K., Raul, S. K., Panda, R. K., Sudheer, K. P.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.12.2015 Springer Nature B.V
Schlagworte:	Algorithms Aquifers Artificial neural networks Atmospheric Sciences Back propagation Civil Engineering Earth and Environmental Science Earth Sciences Environment Evaporation Forecasting Forecasting techniques Geotechnical Engineering & Applied Earth Sciences Groundwater Groundwater levels Hydrogeology Hydrology Hydrology/Water Resources Irrigation Lead time Learning theory Mathematical models Monsoons Neural networks Pan evaporation Parameter estimation Rain River basins Rivers Statistical analysis Studies Sustainable use Water management Water resources Water resources management Wind Neural network modeling Backpropagation GDX algorithm Alluvial aquifer system Groundwater-level forecasting
ISSN:	0920-4741, 1573-1650
Online-Zugang:	Volltext
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