Abstract
India is the greatest groundwater consumer in the world, with estimated annual withdrawals exceeding 230 km3. More than 60% of irrigated agriculture, 85% of drinking water supplies, and 50% of urban and industrial water needs are dependent on sustainable groundwater management. Regardless, groundwater overextraction is a growing problem in many regions. Predictions of groundwater resource availability in India are problematic in part because of a limited number of monitoring sites and insufficient data quality and quantity. Regional groundwater assessments are further complicated because of sporadic and low-frequency data. To help overcome these issues and more accurately quantify groundwater resource availability, scientists have begun using satellite-derived remote sensing data. In this study, the authors used seasonal and annual hydrologic signals obtained by NASA Gravity Recovery and Climate Experiment (GRACE) satellites and simulated soil moisture variations from land data assimilation systems to show groundwater depletion trends in the northwest state of Gujarat (surface area of 196 030 km2), India. Results were evaluated using direct measurement data from 935 wells. Remote sensing generated results compared favorably with well data (e.g., r2 = 0.89 for Gandhinagar, a representative highly urbanized district in Gujarat: confidence interval (CI) = 0.05 and P = 0.002). Results show that remote sensing is an effective tool to compliment and interpolate observed regional groundwater well data and improve groundwater storage estimations in Gujarat, India. Properly implemented, the method will supply reliable science-based information to enhance management of groundwater resources in India and other geographic locations.
Merging remote sensing data and national agricultural statistics to model change in irrigated agriculture
