Monitoring and assessment of groundwater in Uttarakhand state: a geospatial and ARIMA time series forecasting approach

ABSTRACT Groundwater level, rainfall, and groundwater quality data collection, Geographic Information Systems-based spatial interpolation using the ordinary Kriging technique, geospatial analysis, time-series forecasting using autoregressive integrated moving average, groundwater quality assessment, identification of groundwater risk zone, and groundwater sustainable management plan preparation; this is shown graphically in the study workflow. Groundwater is vital for ecological balance and domestic, agricultural, and industrial water supplies. In Uttarakhand, rapid urbanisation, population growth, and limited surface-water availability have increased dependence on groundwater, raising concerns about its sustainability. This study assesses and predicts groundwater-level changes in Dehradun District using an integrated Geographic Information System (GIS), Ordinary Kriging (OK), and Autoregressive Integrated Moving Average (ARIMA) modelling framework. Groundwater-level and quality data collected from 2012 to 2022 were analysed to identify spatial and temporal variations, while ARIMA models were applied to forecast groundwater conditions up to 2027. Results reveal substantial spatial variability, with groundwater-stress areas concentrated mainly in valley regions. Forecasts indicate groundwater-level declines exceeding 9 m in several tehsils. Increasing trends in chloride, total hardness, and electrical conductivity were also observed, while drinking-water standards are projected to be exceeded for fluoride, nitrate, and other parameters in some tehsils. These findings indicate increasing groundwater stress associated with rapid urbanisation and growing water demand. The integrated GIS–ARIMA framework provides an effective decision-support tool for groundwater monitoring, artificial-recharge planning, regulated abstraction, and sustainable groundwater management aligned with SDG 6. The approach can also be adapted for groundwater assessment in other complex mountainous regions.