Environmental Engineering Reference
In-Depth Information
The dependence on ground water as a reliable source to meet the requirements for
irrigation, drinking and industrial uses in India has been rising rapidly during the
last few decades. This has resulted in depletion of groundwater table in some areas
causing concerns for the long-term sustainability. For the effective management of
ground water, it is important to predict groundwater level (GWL) fluctuations. In
this study, hybrid model has been developed to forecast the groundwater level fluc-
tuations. The proposed model is developed by comprising both ANN and regression
modelling techniques. The model is developed by replacing the output layer of
ANN structure by non-linear regression model. The model is calibrated and tested
based on the training and testing of the time-series data of rainfall and GWL in the
Sagar city. The model uses the rainfall and the preceding GWL as the input data to
predict the proceeding GWL. The performance of the models has been evaluated
using standard statistical measures, namely: Average Absolute Relative Error
(AARE), Coefficient of Correlation ( R ), Nash-Sutcliff Efficiency ( E ), Normalized
Root Mean Square Error (NRMSE), and Threshold Statistics ( TS ). The results of the
model are found to predict the GWL accurately and hence hybrid model can suc-
cessfully be used for prediction of GWL of the Sagar city, Madhya Pradesh, India.
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