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September 25, 2025Journal of Information and Technology

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

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Authors

JNJonathan NturoJNJonathan NgugiDSDjuma Sumbiri

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Overview

Case study highlights the impact of El Niño and La Niña on irrigation systems, suggesting advanced AI solutions for recovery.

Key Points

  • Irrigation system damage due to 2024–2025 El Niño events led to a significant drop in rice yield from 5.0 to 2.9 tons/ha, affecting food security.
  • Over 300 hectares of rice land were left without irrigation, threatening the livelihoods of 2,393 smallholder farmers in Mwogo Marshland.
  • Analysis using machine learning and NDVI-based approaches identified agricultural hotspots and estimated yield losses accurately.
  • Proposed recovery strategy incorporates smart irrigation systems with AI monitoring to improve resilience against future climate events.

Cite This Study

Nturo et al. (2025) studied this question.

synapsesocial.com/papers/68d5bd69dc445aa9033b055bhttps://doi.org/10.70619/vol5iss9pp56-73
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