Risk of groundwater depletion in Jaipur district, India: a prediction of groundwater for 2028 using artificial neural network

The rapidly declining groundwater table calls for risk assessment for future water scarcity conditions in the Jaipur district, a naturally water-scarce region. The study tries to understand the spatio-temporal dynamics of groundwater depletion and predict the groundwater level in 2028 using time-series prediction by an Artificial Neural Network (ANN) of multi-layer perceptron (‘mlp’) modelling and estimate the projected populations under risk. It has been found that more than 21% of the district will have groundwater access deeper than 60 m.bgl by 2028. With time, groundwater depletion gets more severe in Chomu, Amber, Jaipur, and Sanganer tehsil. Groundwater depletion will intensify in the aeolian landforms of sand sheets and aeolian plains in the western part, along with the built-up areas, which are also densely populated urban centres. Around 58% of the district's total population is estimated to live with groundwater levels below 60 m.bgl in 2028. Analysis of groundwater levels corresponding to different geomorphological and land-use/land-cover facies advocates for groundwater recharge potentials in wetlands, aeolian landforms, flood plains, and pediment–peneplain complexes. Conservation of existing natural water bodies and using them for groundwater recharge can help to replenish the water table. Judicious and regulated groundwater extraction with legally binding policies can lower the groundwater depletion rate in the region.