Urban Hydrological Monitoring & Citizen Science
Project Overview
The Mburicaó Monitoring Project is a comprehensive urban hydrological monitoring network in Asunción, Paraguay. It combines IoT sensor technology, machine learning models, and citizen science to provide early warning systems for flooding events in rapid urban streams.
Our mission is to support sustainable water resource management and community resilience in the face of increasingly extreme weather events.
Institutional Partners
Lead Institution:
- Faculty of Engineering (FIUNA) - Universidad Nacional de Asunción
Supporting Organizations:
- PUBIABM - Programa Universitario de Becas para la Investigación Andrés Borgognon Montero
- International research collaborations in water resource management
Research Team
Principal Investigators: Dr. Andrés Wehrle and Diego H. Stalder
Research Team:
- (PHD candidate) Jazmín Ojeda (Hydrology, Land Use)
- (MSc Candidate) Federico Morán( FIUNA-UCA) - (AI Models)
- (Eng. Student )Juan Cardozo (Thotogrammetry and Topography)
- (Eng. Student )Mathias Aguilar and Héctor Velázquez (Water level sensors, precipitation gauges)
- (Eng. Student )Victoria Paredes and Francisco Gonzalez(IoT, Nowcasting precipitation)
- (Eng. Student )Evelyn Paredes and Venus Ayala (Citizen Science)
International Collaboration
IFASt Project Partner: Dr. Leonardo B.L. Santos
The project features international collaboration focused on:
- Developing machine learning models for water level prediction
- Implementing IoT sensor networks in resource-limited urban environments
- Creating practical early warning systems for data-scarce regions
- Supporting sustainable urban water management practices
Network Expansion
Phase 1: Initial monitoring station installation (supported by FIUNA grant)
Phase 2: Network expansion to additional monitoring stations
Expanded Support: PUBIABM Research Grant Program
Data & Technology
- Monitoring Frequency: 10-minute intervals for all sensors
- Sensor Types: Water level sensors, precipitation gauges, meteorological stations
- Prediction Models: Support Vector Machine (SVM) and Multilinear Regression
- Data Visualization: Real-time monitoring dashboards with Grafana
- Geographic Focus: Mburicaó Stream, Asunción, Paraguay
Citizen Science
The project actively engages the community through:
- Participatory monitoring and reporting
- Community data collection and observation
- Public access to water level and precipitation data
- Educational workshops and awareness campaigns
Environmental Impact
This monitoring system contributes to:
- Early flood warning and disaster preparedness
- Improved water resource management in urban areas
- Protected infrastructure and community safety
- Scientific understanding of rapid urban hydrology
- Climate adaptation strategies in growing cities