Assessment and Prediction of Groundwater using Geospatial and ANN Modeling

Ankita P Dadhich,Pran N Dadhich,Rohit Goyal

doi:10.1007/s11269-021-02874-8

Abstract

In semi-arid regions, the deterioration in groundwater quality and drop in water level upshots the importance of water resource management for drinking and irrigation. Therefore geospatial techniques could be integrated with mathematical models for accurate spatiotemporal mapping of groundwater risk areas at the village level. In the present study, changes in water level, quality patterns, and future trends were analyzed using eight years (2012–2019) groundwater data for 171 villages of the Phagi tehsil, Jaipur district. Kriging interpolation method was used to draw spatial maps for the pre-monsoon season. These datasets were integrated with three different time series forecasting models (Simple Exponential Smoothing, Holt's Trend Method, ARIMA) and Artificial Neural Network models for accurate prediction of groundwater level and quality parameters. Results reveal that the ANN model can describe groundwater level and quality parameters more accurately than the time series forecasting models. The change in groundwater level was observed with more than 4.0 m rise in 81 villages during 2012–2013, whereas ANN predicted results of 2023–2024 predict no rise in water level > 4.0 m. However, based on predicted results of 2024, the water level will drop by more than 6.0 m in 16 villages of Phagi. Assessment of water quality index reveals unfit groundwater in 74% villages for human consumption in 2024. This time series and projected groundwater level and quality at the micro-level can assist decision-makers in sustainable groundwater management.

Highlights

In arid and semi-arid environment where rainfall is scanty and highly variable with very high evaporation rate; groundwater is the vital local source for drinking, agricultural, industrial and domestic uses
The aim of this research is: 1) to ascertain the spatial and temporal variations in the groundwater level and groundwater quality of Phagi tehsil during last 8 years (2012 to 2019) by developing spatial interpolation maps; 2) modeling of water level and important water quality parameters using time series forecasting & ANN models and identification of optimum model based on model validation using historic data; 3) to predict the groundwater level changes and groundwater quality during 2019 to 2024 using the best forcasting model identified for understanding the variations with space and time at village level
In this research performance of models was evaluated by comparing the simulated and observed outcomes of SES, Holt's Trend Method (HTM) and AutoRegressive Integrated Moving Average (ARIMA) with optimum ANN model for the year 2019 and best method was selected to predict the values for the year 2024

Summary

Introduction

In arid and semi-arid environment where rainfall is scanty and highly variable with very high evaporation rate; groundwater is the vital local source for drinking, agricultural, industrial and domestic uses. Groundwater is generally considered better than surface water because of its higher quality, less evapo-transpiration and less susceptible to contamination (Chenini and Ben 2010; Kumar et al 2016). In the last few decades, the availability of ground water is at a greater risk in Rajasthan state of India due to growing population, urbanization, and large quantities of groundwater withdrawal for crop production. Over-exploitation of groundwater resources and drought events have caused severe drop in water table level of Rajasthan. The variations in the groundwater level reflects the impact of climatic condition, groundwater consumption, water storage and other human activities (Minville et al 2010; Ghazavi et al.2012); groundwater level fluctuation is an important indicator of the ecology and hydrology of the arid region (Jolly et al 2008)

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Conclusion