Leveraging AI and Precision Agriculture to Restore Irrigation Infrastructure Damaged by El Niño and La Niña Events: A Case Study of Mwogo Marshland, Rwanda

The Mwogo Irrigation Scheme, launched in 2007 in Huye District, Southern Rwanda, was developed into a climate-resilient agricultural hub through a €20 million investment by Welthungerhilfe and its development partners—including EKN, BMZ, VcA, and the Canadian Embassy—until 2014. This extensive effort transformed the marshland into one of the country’s flagship rice production zones, supporting over 2,393 smallholder farmers organized into five cooperatives. However, the devastating effects of the 2024–2025 El Niño, coupled with the forecasted La Niña, have severely compromised this legacy. Key infrastructure, such as the Gatindingoma Dam, Kabakobwa Intake, and Ntaruka canal section, along with water wells for safe community drinking water, collapsed due to extensive flooding, erosion, and siltation. Over 300 hectares of rice land were left without irrigation, leading to a drop in yields from 5.0 to 2.9 tons/ha and threatening local food security and rural livelihoods. This study employs a combination of field evidence, Normalized Difference Vegetation Index (NDVI)-based crop stress analysis, and Random Forest machine learning algorithms to estimate yield loss and identify hotspots of agricultural damage. Furthermore, it proposes a comprehensive recovery strategy centered on smart irrigation systems, Internet of Things (IoT)-enabled monitoring, AI-based early warning systems, and climate-indexed insurance products. The findings call for urgent re-engagement by Welthungerhilfe and its development partners—both former and prospective—to reinvest in the Mwogo Marshland and ensure its transformation into a resilient, technology-enabled agricultural zone.