Combining GRACE Gravimetry Data with Satellite Thermal Infrared Imagery to Make an Operational Irrigation Advisory System More Efficient for South Asia

To address the continually decreasing groundwater (GW) resources in South Asia due to excessive dry season (November to April) irrigation and increasing cost of irrigation advisory texts to farmers, continuous improvement of existing Irrigation Advisory System (IAS) services is critical. In this study we used Gravity Recovery and Climate Experiment (GRACE) data with Landsat Thermal Infrared (TIR) Imagery to rapidly and cost-effectively identify regions with unsustainable GW extraction and assess how much GW can be saved with need-based irrigation provided by operational IAS. We demonstrated improvements in the IAS over the Ganges basin. First, we generated the spatial and temporal trend of GRACE terrestrial water storage (TWS) anomaly from 2002-2016 with the rationale that TWS anomaly is a strong proxy for GW storage anomaly during the dry season of South Asia when there is no precipitation and other water budget components (runoff, soil moisture or snow) are at steady-state. We identified the appropriate spatial scale for GRACE TWS data for rapid prioritization of such GW-stressed region­s by comparing GRACE TWS with the Water Budget Model derived TWS. Next, we applied the Surface Energy Balance Algorithm for Land (SEBAL) to compute observed evapotranspiration (ET) over cropped areas in those prioritized regions. Comparison of SEBAL ET with crop water demand from Penman-Monteith (FAO56) technique over the same cropped areas revealed the extent of over-irrigation from potential GW extraction. Finally, to verify that SEBAL ET is a strong proxy for GW storage change during dry seasons, we compared it with depth to water table trends to reveal consistently positive and strong correlation when compared to well data from non-cropped areas. We demonstrated the application of the GRACE-TIR based IAS over four irrigation districts of Northern India (Kanpur Nagar, Kanpur Dehat, Lucknow and Agra) for the period of 2002-2014. Our results suggested that an operational IAS can achieve a minimum saving of 85% (80 million m³) of GW per dry season/district. Our proposed enhanced IAS also allows continuous monitoring of farmer behavioral change in reducing over-irrigation and long-term impact on GW resources with need based irrigation practices via follow up assessment of GRACE TWS (after dry season) and TIR data (during dry season).