AI-assisted river discharge measurement through citizen science and mobile technology

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dc.creatorVigneswaran, Kayathri
dc.creatorRetief, H.
dc.creatorClifford-Holmes, J.
dc.creatorGarcia Andarcia, Mariangel
dc.creatorTennakoon, Hansaka
dc.date2025-12-30
dc.date2026-02-11T06:24:40Z
dc.date2026-02-11T06:24:40Z
dc.date.accessioned2026-06-27T18:25:54Z
dc.descriptionThis report presents a novel protocol for measuring river discharge by integrating artificial intelligence with citizen science in the Limpopo River Basin. Developed under the Enabel/Wehubit “Citizen Science for Water Management” project and aligned with the LIMCOM–UNDP/GEF programme, the approach addresses a core constraint in data-scarce basins: limited observational infrastructure restricts the data needed to power digital decision-support systems. A WhatsApp-based platform enables community members to submit gauge-plate photographs and supporting metadata (station selection, location sharing, and validation) without requiring a dedicated mobile application. The backend includes a Vision API and a custom WhatsApp Bot Service deployed on AWS ECS to manage guided submissions and secure, station-linked user permissions consistent with LIMCOM governance. Gauge readings are derived via a two-step AI method that first detects waterline and scale, then converts these to water level, improving robustness under field conditions. Testing achieved strong accuracy (R² = 0.84; mean error 5.43 cm on high-quality images). Validated water levels are translated to discharge using station-specific rating curves accessed through the FlowTracker API. The protocol demonstrates that hybrid AI and embedded quality assurance can augment hydrological monitoring in transboundary basins while maintaining scientific rigour.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/181393
dc.identifier.urihttp://hdl.handle.net/123456789/155633
dc.languageen
dc.publisherInternational Water Management Institute
dc.publisherCGIAR Accelerator for Digital Transformation
dc.rightsOpen Access
dc.sourceVigneswaran, K.; Retief, H.; Clifford-Holmes, J.; Garcia Andarcia, M.; Tennakoon, H. 2025. AI-assisted river discharge measurement through citizen science and mobile technology. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Accelerator for Digital Transformation. 53p.
dc.subjectrivers
dc.subjectdischarge
dc.subjectstream flow
dc.subjectartificial intelligence
dc.subjectcitizen science
dc.subjecttechnology
dc.titleAI-assisted river discharge measurement through citizen science and mobile technology
dc.typeReport

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Instituto Internacional para el Manejo del Agua (IWMI)