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About
Floods can come from several sources, such as rivers and streams and their overflow from the channel (fluvial, or river floods), then water flowing down the slopes, or surface runoff, runoff through the drainage system (pluvial floods), the exit of groundwater above the soil surface or coastal floods as a result of e.g. tidal waves.
This project attempts to address the combined fluvial and pluvial floods hazard, as these two types of floods are most common in Slovakia as well as Europe.
The main objective of the project is to create a methodology for mapping and assessment of flood hazard, representing the combined fluvial and pluvial hazard, with the use of detailed geo-spatial data and hybrid approaches integrating machine learning, hydrologic-hydraulic approaches and analysis of remote sensing data.
Objectives
The attention of the project team will be focused on the following specific objectives:
- Analysis of remote sensing data for obtaining the calibration/validation or training/testing data for hydrologic-hydraulic and machine learning models.
- Mapping of the fluvial and pluvial flood hazard using the hydrologic-hydraulic (H&H) models.
- Mapping of the fluvial and pluvial flood hazard using the machine learning (ML) models.
- Integration of the modeling results for the combined fluvial and pluvial flood hazard.
- Scenario-based modeling of climate and land use/land cover change and their effects on flood hazard prediction.
Work Packages
NV1: Data Pre-processing
Objectives:
- To select model areas,
- To obtain, prepare, process and share the input data for modeling,
- To prepare the data for further processing so that it can be used in the upcoming models.
NV2: Fluvial H&H models
Objectives:
- To perform 1D and 2D hydraulic modeling of fluvial flooding.
- To validate the hydraulic model using historical flood data.
NV3: Pluvial H&H models
Objectives:
- To perform rainfall-runoff modeling,
- To perform hydraulic modeling of surface flow,
- To validate the hydraulic model with the use of historical flood data.
NV4: Fluvial ML models
Objectives:
- To develop ML models for fluvial flood extent and flow depth simulation,
- To validate the fluvial ML models based on historical flood data.
NV5: Pluvial ML Models
Objectives:
- To develop ML models for pluvial flood extent and flow depth simulation,
- To validate the pluvial ML models based on historical flood data.
NV5: Scenario Modeling
Objectives:
- To develop final H&H/ML models for fluvial and pluvial flood hazard using the climate and land use/land cover scenarios.
Research and Publications
The project team published the following scientific papers where the team presents the findings of the project. The following papers have been already accepted and published in the research journals and conference proceedings:
Matej Vojtek, Soheyl Moradi, Davide Luciano De Luca, Andrea Petroselli & Jana Vojteková. 2024. Fluvial and pluvial flood hazard mapping: combining basin and municipal scale assessment. Geomatics, Natural Hazards and Risk, 15(1): 2432377. DOI: https://doi.org/10.1080/19475705.2024.2432377
Matej Vojtek & Soheyl Moradi. 2024. Assessment of vulnerability to fluvial floods: Case of municipalities of the Gidra River Basin, Slovakia. Acta Scientiarum Polonorum: Formatio Circumiectus, 23(2): 67-82. DOI: https://doi.org/10.15576/ASP.FC/189854
Project Outcomes
Our Research Team
The research team consists of scientists from the Department of Geography, Geoinformatics and Regional Development, Department of Ecology and Environmental Science, Department of Informatics and Department of Mathematics, which are located at the Faculty of Natural Sciences and Informatics, Constantine the Philosopher University in Nitra, Slovakia.
Contact Person
doc. RNDr. Matej Vojtek, PhD.
Address:
Department of Geography, Geoinformatics and Regional Development
Faculty of Natural Sciences and Informatics
Constantine the Philosopher University in Nitra
Tr. A. Hlinku 1
949 01 Nitra
Slovakia
Call: +421 37 6408 632
Email: mvojtek@ukf.sk
Credits
Photos from Pexels:
Author: Roman Biernacki
Author: Genaro Servín
Author: Burak The Weekender
Author: Irina Iriser
Author: Chris F
Author: Pok Rie
Author: Tom Fisk