EGU24-2313, updated on 08 Mar 2024
https://doi.org/10.5194/egusphere-egu24-2313
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Targeting irrigation investments for people and planet: A novel big-data approach

Anton Urfels1,2,3, Andrew McDonald3, Maxwell Mkdondiwa4, Laura Arena Calles3, Hari Nayak Shankar1,3, Saral Karki5, Amit Srivastava1, Sonam Sherpa4, and Virender Kumar1
Anton Urfels et al.
  • 1International Rice Research Institute (IRRI), Los Baños, the Philippines (a.urfels@irri.org)
  • 2Water Resources Management Group, Wageningen University, Wageningen, Netherlands (anton.urfels@wur.nl)
  • 3College of Agriculture and Life Sciences, Cornell University, Ithaca, United States of America (avu4@cornell.edu)
  • 4International Maize and Wheat Improvement Center (CIMMYT), New Delhi, India
  • 5International Maize and Wheat Improvement Center (CIMMYT), Kathmandu, Nepal

Irrigated agriculture plays a foundational role for global food security while also being the largest water consumer worldwide. With little room to expand surface water irrigation, agricultural planners turn increasingly to groundwater for building climate resilience food security. This strategy has transformed major food baskets into highly productive but groundwater depleting systems. Outside these 'hotspots' however, there is still ample scope for promoting productive and sustainable groundwater use for agriculture. Here we present a big data approach for targeting groundwater irrigation investments in rice production across 4 states of India in safe shallow groundwater zones. Our results indicate that promoting one additional irrigation in parts of safe shallow groundwater zones where yield responses are especially high, can provide annual rice consumption needs for another 50m people. The spatial strucuture of the irrigation investment priority zones can further aid research and sustainable development planning. We conclude that combining increasingly abundant agronomic and hydrological data for sustainable development in low and middle income countries can help to guide the financing of more targeted and cost-effective sustainable development programs.

How to cite: Urfels, A., McDonald, A., Mkdondiwa, M., Arena Calles, L., Shankar, H. N., Karki, S., Srivastava, A., Sherpa, S., and Kumar, V.: Targeting irrigation investments for people and planet: A novel big-data approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2313, https://doi.org/10.5194/egusphere-egu24-2313, 2024.