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Integrating Near Real-Time Hydrological Data for Monitoring and Alerting: The RoWaterAPI Framework.

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Title: Integrating Near Real-Time Hydrological Data for Monitoring and Alerting: The RoWaterAPI Framework.
Authors: Popa, Mihnea Cristian, Diaconu, Daniel Constantin, Simion, Adrian Gabriel, Voicu, Ioan Florin, Romulus, Costache
Source: Geosciences (2076-3263); Feb2026, Vol. 16 Issue 2, p87, 16p
Subject Terms: DATA integration, REAL-time computing, FLOOD warning systems, OPEN source software, HYDROLOGICAL databases, PUBLIC safety, HAZARD mitigation, GEOGRAPHIC spatial analysis
Abstract: The paper addresses the limitations of fragmented and delayed hydrological information systems in supporting timely disaster risk mitigation. The paper introduces the RoWaterAPI, a framework that integrates near real-time hydrological measurements with geospatial analytics to improve awareness during flood-related events. The methodology utilizes open-source technologies, including Django, Kafka, and PostGIS, to support scalable data ingestion and hazard mapping. Initial baseline evaluation under a simulated bursty workload indicates an end-to-end latency of ≈1–3 s and a peak throughput of ≈6000–8500 messages/s. This performance supports real-time alerts for data variations, bridging advanced geoprocessing with user-centered design for public and institutional stakeholders. Ultimately, RoWaterAPI provides a transferable implementation model that can be adapted to any national context facing similar constraints in data fragmentation and operational accessibility. [ABSTRACT FROM AUTHOR]
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Abstract:The paper addresses the limitations of fragmented and delayed hydrological information systems in supporting timely disaster risk mitigation. The paper introduces the RoWaterAPI, a framework that integrates near real-time hydrological measurements with geospatial analytics to improve awareness during flood-related events. The methodology utilizes open-source technologies, including Django, Kafka, and PostGIS, to support scalable data ingestion and hazard mapping. Initial baseline evaluation under a simulated bursty workload indicates an end-to-end latency of ≈1–3 s and a peak throughput of ≈6000–8500 messages/s. This performance supports real-time alerts for data variations, bridging advanced geoprocessing with user-centered design for public and institutional stakeholders. Ultimately, RoWaterAPI provides a transferable implementation model that can be adapted to any national context facing similar constraints in data fragmentation and operational accessibility. [ABSTRACT FROM AUTHOR]
ISSN:20763263
DOI:10.3390/geosciences16020087