Groundwater level prediction of Varanasi wells during pre-monsoon and post-monsoon using intelligence approach

In general, groundwater management is a significant role in meeting water needs in society. However, the growing demand for groundwater must meet the needs of an enormous community to sustain the severe effects of limited water resources. Therefore, the groundwater level (GWL) should be analyzed for efficient groundwater management to identify groundwater usages. However, predicting the GWL is a challenging task in water resource management because of large complex data. So, this research has proposed generalized intelligence control with hybrid ant colony African buffalo optimization (GIC with HAC-ABO) approach to forecast the GWL in alluvial aquifers at Varanasi City. Initially, the well locations at Varanasi, Uttar Pradesh, are identified with the use of differential global positioning system (DGPS). Subsequently, the GWL in the well for post-monsoon and pre-monsoon is measured using a graduated steel tape. Then the fitness value of HAC-ABO in GIC was updated to predict the GWL in Varanasi wells. Here, the proposed technique has analyzed the GWL for both pre-monsoon and post-monsoon for every year and also predicts the future GWL in Varanasi well after 30 years. Henceforth, this approach has provided better results in the grounds of prediction accuracy, correlation coefficient, root mean square error (RMSE), and mean absolute error (MAE) compared to other approaches.