Abstract

Groundwater irrigated agriculture accounts for approximately 70% of global groundwater withdrawals and around 38% of the total irrigated area. The indiscriminate use of groundwater has resulted in the depletion of groundwater resources across many regions globally. To ensure sustainable use, it is imperative to limit abstraction to within the average annual recharge rate. However, in agricultural systems in many developing countries, including India, where millions of smallholder farmers use individual wells for pumping, monitoring, and reliable data are lacking. This study proposes an energy-based approach to estimate groundwater abstraction, providing a low-cost method for deriving estimates of moderate accuracy. The research focuses on two areas with contrasting aquifer conditions in Gujarat, India: one alluvial and one hard rock. Using pump and well data, a conversion factor (CF) relating to the volume of water abstracted per unit of energy consumed is determined. In hard rock aquifers, the conversion factor decreases from an average of 6.0 m³ kWh−1 for 3 HP pumps to 4.7 m³ kWh−1 for 7.5 HP pumps. In alluvial aquifers characterized by higher aquifer transmissivity and flow rates, the conversion factor decreases from an average of 9.4 m³ kWh−1 for 10 HP pumps to 4.7 m³ kWh− 1 for 20 HP pumps. The developed relationship shows that CF is related to factors such as pump horsepower, well characteristics, groundwater levels, and pump age. The CF relationship with pump and well characteristics is more robust (R2 ∼ 0.75) in alluvial aquifers compared to the hard rock aquifer (R2 ∼ 0.49). The developed models provide satisfactory estimates of groundwater abstraction, with R2 ∼ 0.92 for alluvial aquifers and ∼0.69 for hard rock aquifers, as compared to observed data on groundwater abstraction. This energy-based approach offers a cost-effective means of monitoring groundwater abstraction, particularly crucial in regions with heavily developed groundwater resources.

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