Integrating Gravimetry Data With Thermal Infra‐Red Data From Satellites to Improve Efficiency of Operational Irrigation Advisory in South Asia

The rapid decline of groundwater resources in South Asia due to excessive irrigation during dry season requires awareness of optimal on‐field water requirements. Such information is currently provided on farmer cellphones through an operational Irrigation Advisory System (IAS). To minimize the cost of sending such irrigation advisory texts to farmers while maximizing impact of IAS on groundwater sustainability, we integrated Gravity Recovery and Climate Experiment (GRACE) data with Landsat Thermal Infrared (TIR) Imagery to target regions in greater need of the IAS service. We demonstrated the concept of an improved IAS over eight irrigation districts of the Ganges and Indus basins. The Surface Energy Balance Algorithm for Land (SEBAL) was used to monitor on‐field water consumption (evapotranspiration‐ET) over cropped areas using Landsat TIR data at plot‐scale spatial resolution. Comparison of SEBAL ET with crop water demand from Penman‐Monteith (FAO56) technique quantified the extent of overirrigation at the plot scale and provided a tangible pathway to microtarget the IAS service only to farmers with the largest groundwater use footprint, thereby improving the impact of the IAS service further. Our results suggested that an operational IAS that integrates GRACE and Landsat TIR data on average can save about 85% (80 million m3) of groundwater per dry season for irrigation districts of Northern India and 87% (or 150 million m3) per year for irrigation districts of Eastern Pakistan. Key Points An operational irrigation advisory was made more efficient with Gravity Recovery and Climate Experiment (GRACE) and Landsat Thermal data GRACE data identified rapidly depleting groundwater zones to allow strategic targeting of the irrigation advisory Landsat thermal data allowed plot scale strategic targeting of farmers with the highest groundwater waste to maximize water savings