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Using artificial neural network approach for simultaneous forecasting of weekly groundwater levels at multiple sites

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Title Using artificial neural network approach for simultaneous forecasting of weekly groundwater levels at multiple sites
Not Available
 
Creator Mohanty, S., Jha, M.K., Raul, S.K. and Panda, R.K.
 
Subject Groundwater-level forecasting . Neural network modeling . Backpropagation GDX algorithm . Alluvial aquifer system
 
Description Not Available
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 basin. Gradient descent with momentum and adaptive
learning rate backpropagation (GDX) algorithm was employed to predict groundwater levels
1 week ahead at 18 sites over the study area. Based on the domain knowledge and pertinent
statistical analysis, appropriate set of inputs for the ANN model was selected. This consisted of
weekly rainfall, pan evaporation, river stage, water level in the surface drain, pumping rates of
18 sites and groundwater levels of 18 sites in the previous week, which led to 40 input nodes
and 18 output nodes. During training of the ANN model, the optimum number of hidden
neurons was found to be 40 and the model performance was found satisfactory (RMSE=
0.2397 m, r=0.9861, and NSE=0.9722). During testing of the model, the values of statistical
indicators RMSE, r and NSE were 0.4118 m, 0.9715 and 0.9288, respectively. Using the same
inputs, the developed ANN model was further used for forecasting groundwater levels 2, 3 and
4 weeks ahead in 18 tubewells. The model performance was better while forecasting groundwater
levels at shorter lead times (up to 2 weeks) than that for larger lead times.
Not Available
 
Date 2018-11-26T04:10:18Z
2018-11-26T04:10:18Z
2015-10-03
 
Type Research Paper
 
Identifier Mohanty, S., Jha, M.K., Raul, S.K. and Panda, R.K. 2015. Using artificial neural network approach for simultaneous forecasting of weekly groundwater levels at multiple sites. Water Resource Management, 29:5521-5532
1573-1650
http://krishi.icar.gov.in/jspui/handle/123456789/13232
 
Language English
 
Relation Not Available;
 
Publisher springer