Environmental Engineering Reference

In-Depth Information

Conclusions

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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