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The innovation focuses on adapting the SHEE computer application to enhance flood prediction accuracy. SHEE manages regional databases and simulates hydrometeorological events, including rainfall distribution, land conditions, and flood circulation.
This innovation targets the prediction and management of river and pluvial floods, particularly in small and medium catchments. It updates flood prediction methodologies to significantly reduce the risk of floods, thereby minimizing material and personal losses. The innovation provides a comprehensive risk analysis tool that can be utilized by various stakeholders, including those involved in territorial planning, civil engineering, drainage infrastructure design, environmental risk analysis (e.g., in waste management and mining), and civil protection tasks. This versatile tool enhances flood preparedness and resilience across multiple sectors.
See more information about this level and the TRL and SRL levels.
Very significant reduction of material and personal losses. Provision of a risk situation analysis tool for use by all stakeholders. Application in territorial planning. Application in the design of drainage infrastructures fields such as civil engineering. Application for analysis of environmental risks in multiple fields such as waste management and mining. Application for certain civil protection tasks.
The innovation was developed within the scope of a doctoral thesis [https://zaguan.unizar.es/record/5750/files/TESIS-2011-031.pdf]. The software has been improved and has been gradually contrasted through the application in reports and real projects such as risk studies for planning of various municipalities, road drainage works, flow regulation works, river defense works. On the other hand, it has given rise to publications in the international arena, both in computer science journals and in hydrology journals.
Here are some examples:
• Mateo-Lázaro J., Sánchez-Navarro J.A., García-Gil A., Edo-Romero V. 2013. Developing and programming a watershed traversal algorithm (WTA) in GRID-DEM and adapting it to hydrological processes. Computers and Geosciences 51:418–429. https://doi.org/10.1016/j.cageo.2012.07.024
• Mateo-Lázaro J., Sánchez-Navarro J.A., García-Gil A., Edo-Romero V. 2013b. Análisis de frecuencia y clasificación de eventos hidrometeorológicos reales en tres cuencas del NE de España. Geogaceta, 53, 117–120. https://sge.usal.es/archivos/geogacetas/geo53/G53art29.pdf
• Mateo-Lázaro, J., Sánchez-Navarro, J.A., García-Gil, A., Edo-Romero, V. 2014. Sensitivity analysis of main variables present on flash flood processes. Application in two Spanish catchments: Arás and Aguilón. Environmental Earth Sciences. 71(6):2925-2939. https://doi.org/10.1007/s12665-013-2668-5.
• Mateo-Lázaro, J., Sánchez-Navarro, J.A., García-Gil, A., Edo-Romero, V. 2016. Flood Frequency Analysis (FFA) in Spanish catchments. Journal of Hydrology. 538. 598–608. http://dx.doi.org/10.1016/j.jhydrol.2016.04.058
Obviously, the prediction of hydrological processes will always have a certain degree of uncertainty. It is about minimizing uncertainty and being aware of the probability and frequency with which this risk occurs. Regarding the sensitivity of the different parameters that control the hydrometeorological sub-models, refer to the publication [Mateo-Lázaro, J., Sánchez-Navarro, J.A., García-Gil, A., Edo-Romero, V. 2014. Sensitivity analysis of main variables present on flash flood processes. Application in two Spanish catchments: Arás and Aguilón. Environmental Earth Sciences. 71(6):2925-2939. https://doi.org/10.1007/s12665-013-2668-5] where the hydrological characteristics of the soil prior to extreme events are identified as the most determining factor, as is recognized, cited and disseminated in [Tarasova L, Merz R., Kiss A, Basso S, Blöschl G, Merz B, Viglione A, Plötner S, Guse B, Schumann A, Fischer S, Ahrens B, Anwar F, Bárdossy A, Bühler P, Haberlandt U, Kreibich H, Krug A, Lun D, Müller-Thomy H, Pidoto R, Primo C, Seidel J, Vorogushyn S, Wietzke L. 2019. Causative classification of river flood events. Wiley. WIREs Water Volume 6. https://wires.onlinelibrary.wiley.com/doi/epdf/10.1002/wat2.1353] with authors among which are the most outstanding of current Hydrology.
The innovation focuses on adapting the SHEE computer application to enhance flood prediction accuracy. SHEE manages regional databases and simulates hydrometeorological events, including rainfall distribution, land conditions, and flood circulation.
This innovation targets the prediction and management of river and pluvial floods, particularly in small and medium catchments. It updates flood prediction methodologies to significantly reduce the risk of floods, thereby minimizing material and personal losses. The innovation provides a comprehensive risk analysis tool that can be utilized by various stakeholders, including those involved in territorial planning, civil engineering, drainage infrastructure design, environmental risk analysis (e.g., in waste management and mining), and civil protection tasks. This versatile tool enhances flood preparedness and resilience across multiple sectors.
The main components of the system have been tested separately, and an initial integration exercise has been conducted.
Very significant reduction of material and personal losses. Provision of a risk situation analysis tool for use by all stakeholders. Application in territorial planning. Application in the design of drainage infrastructures fields such as civil engineering. Application for analysis of environmental risks in multiple fields such as waste management and mining. Application for certain civil protection tasks.
The innovation was developed within the scope of a doctoral thesis [https://zaguan.unizar.es/record/5750/files/TESIS-2011-031.pdf]. The software has been improved and has been gradually contrasted through the application in reports and real projects such as risk studies for planning of various municipalities, road drainage works, flow regulation works, river defense works. On the other hand, it has given rise to publications in the international arena, both in computer science journals and in hydrology journals.
Here are some examples:
• Mateo-Lázaro J., Sánchez-Navarro J.A., García-Gil A., Edo-Romero V. 2013. Developing and programming a watershed traversal algorithm (WTA) in GRID-DEM and adapting it to hydrological processes. Computers and Geosciences 51:418–429. https://doi.org/10.1016/j.cageo.2012.07.024
• Mateo-Lázaro J., Sánchez-Navarro J.A., García-Gil A., Edo-Romero V. 2013b. Análisis de frecuencia y clasificación de eventos hidrometeorológicos reales en tres cuencas del NE de España. Geogaceta, 53, 117–120. https://sge.usal.es/archivos/geogacetas/geo53/G53art29.pdf
• Mateo-Lázaro, J., Sánchez-Navarro, J.A., García-Gil, A., Edo-Romero, V. 2014. Sensitivity analysis of main variables present on flash flood processes. Application in two Spanish catchments: Arás and Aguilón. Environmental Earth Sciences. 71(6):2925-2939. https://doi.org/10.1007/s12665-013-2668-5.
• Mateo-Lázaro, J., Sánchez-Navarro, J.A., García-Gil, A., Edo-Romero, V. 2016. Flood Frequency Analysis (FFA) in Spanish catchments. Journal of Hydrology. 538. 598–608. http://dx.doi.org/10.1016/j.jhydrol.2016.04.058
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