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Addressing the gap: advancements in flow forecasting systems for small mountainous catchments

Author

Listed:
  • M. R. Fagundes

    (Federal University of Rio Grande do Sul)

  • F. M. Fan

    (Federal University of Rio Grande do Sul)

  • C. H. A. Gama

    (Federal University of Rio Grande do Sul)

  • K. Campagnolo

    (Federal University of Rio Grande do Sul)

  • M. A. Paixão

    (Federal University of Rio Grande do Sul)

  • M. Kobiyama

    (Federal University of Rio Grande do Sul)

Abstract

A comparison of methodologies was carried out to develop an operational flow forecasting system for a mountainous catchment. The case studied was the Boi River, which is located in a small mountainous catchment in southern Brazil. This catchment is part of a conservation unit well known for the beautiful landscapes and ecotourism activities carried out in that place. Among the activities, the Boi River trail can be highlighted, which is carried out following the riverbed. For this reason, the development of an alert system for this basin can help in determining the trail's closure in situations where the water flow is strong and could present risks to tourists’ safety. Thereby, the aim of this study was to assess two distinct scenarios for the development of the forecasting system. First, the flow forecasts were performed using SOPREVA and considered a horizon of 1 day (short-term forecasts). The second scenario considered medium-term forecasts (1–10 days horizon) and utilized the HEC-RTS as a basis for developing the forecast system. In both cases, the forecasts were based on the ensemble precipitation estimates of GEFS. The obtained results showed that the actual alarm rates were 0.77 and 0.86 for SOPREVA and HEC-RTS, respectively, when considering a horizon of one day in advance. The evaluation of the medium-term forecasts presented good results of this system for horizons up to 3 days in advance. Finally, the results of both considered scenarios showed that the systems could be used as a basis for management of the Boi River trail.

Suggested Citation

  • M. R. Fagundes & F. M. Fan & C. H. A. Gama & K. Campagnolo & M. A. Paixão & M. Kobiyama, 2024. "Addressing the gap: advancements in flow forecasting systems for small mountainous catchments," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(6), pages 5033-5055, April.
    • Handle: RePEc:spr:nathaz:v:120:y:2024:i:6:d:10.1007_s11069-024-06407-5
    DOI: 10.1007/s11069-024-06407-5
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    References listed on IDEAS

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    1. Sofia Melo Vasconcellos & Masato Kobiyama & Fernanda Stachowski Dagostin & Claudia Weber Corseuil & Vinicius Santana Castiglio, 2021. "Flood Hazard Mapping in Alluvial Fans with Computational Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(5), pages 1463-1478, March.
    2. Bosy A. El-Haddad & Ahmed M. Youssef & Hamid R. Pourghasemi & Biswajeet Pradhan & Abdel-Hamid El-Shater & Mohamed H. El-Khashab, 2021. "Flood susceptibility prediction using four machine learning techniques and comparison of their performance at Wadi Qena Basin, Egypt," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 105(1), pages 83-114, January.
    3. Djamil Al-Halbouni & Osama AlRabayah & David Nakath & Lars Rüpke, 2022. "A Vision on a UNESCO Global Geopark at the Southeastern Dead Sea in Jordan—How Natural Hazards May Offer Geotourism Opportunities," Land, MDPI, vol. 11(4), pages 1-28, April.
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