• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer

Centre for Artificial Intelligence and Cybersecurity – AIRI

  • Home
  • About Us
    • Vision, Mission and Goals
    • Center Activities
    • Center Faculty
    • Steering Committee
    • Press
  • Research
    • Scientific Projects
    • Research Papers
  • Laboratories
    • Machine Learning
    • Natural Speech & Language Processing
    • Blockchain Technology
    • Information Processing & Pattern Recognition
    • AI in Medicine
    • Data Mining
    • Computer Vision
    • Human-Computer Interaction
    • Maritime Cybersecurity
    • Autonomous Navigation
    • AI in Mechatronics
    • AI in Education
    • Hybrid Computational Methods
    • Drug Design
    • Legal Aspects of AI
    • Ethically Aligned AI
    • Cultural Complexity
  • Collaboration
    • Industry Collaboration
    • Industry Projects
    • International Collaboration
  • News
  • Contact

Evaluation of Design Storms and Critical Rainfall Durations for Flood Prediction in Partially Urbanized Catchments

21.07.2020

This study investigates and compares several design storms for flood estimation in partially urbanized catchments. Six different design storms were considered: Euler II, Alternating Block Method, Average Variability Method, Huff’s curves, and uniform rainfall. Additionally, two extreme historical storms have been included for comparison. A small, ungauged, partially urbanized catchment in Novigrad (Croatia) was chosen as a study area to account for the infiltration impact on the rainfall-runoff process. The performance of each design storm was assessed based on the flood modelling results, namely the water depth, water velocity, flow rate, and overall flood extent. Also, several rainfall durations were considered to identify a critical scenario. The excess rainfall was computed using the Soil Conservation Service’s Curve Number method, and two-dimensional flooding simulations were performed by the HEC-RAS model. The results confirmed that the choice of the design storm and the rainfall duration have a significant impact on the flood modelling results. Overall, design storms constructed only from IDF curves overestimated flooding in comparison to historical events, whereas design storms derived from the analysis of observed temporal patterns matched or slightly underestimated the flooding results. Of the six considered design storms, the Average Variability Method showed the closest agreement with historical storms.

Authors:
Nino Krvavica, Josip Rubinić
Journal:
Water
Publishing date:
18.07.2020
View original article Download the paper

Primary Sidebar

Latest Projects

Machine Learning for Knowledge Transfer in Medical Radiology

Estimating River Discharges in Highly Stratified Estuaries

Multilayer Framework for the Information Spreading Characterization in Social Media during the COVID-19 Crisis (InfoCoV)

European Network for assuring food integrity using non-destructive spectral sensors

National Competence Centres in the Framework of EuroHPC (EUROCC)

Latest Research Papers

A Comparison of Approaches for Measuring the Semantic Similarity of Short Texts Based on Word Embeddings

Indoor Localization Based on Infrared Angle of Arrival Sensor Network

Gravitational-Wave Burst Signals Denoising Based on the Adaptive Modification of Intersection of Confidence Intervals Rule

Survey of Neural Text Representation Models

Je li blockchain tehnologija budućnost digitalizacije zemljišnih knjiga?

Latest News

UNIRI Excellence Awards in Science

Talk on conference “Exploring Digital Legal Landscapes”

ICAIH 2020 conference presentation

International conference “Exploring Digital Legal Landscapes” – 11th of December, 2020

Sanda Martinčić-Ipšić talk the Data Science Conference

We provide the expertise for solving real world problems using AI

If your company wants to implement artificial intelligence in your products or services, or increase your level of cybersecurity, our multidisciplinary team of scientists is your ideal partner.

Contact us

Footer

Center for Artificial Intelligence and Cybersecurity
  • jlerga@airi.uniri.hr
  • +385 51 406 500

University of Rijeka

University of Rijeka

About the Center

  • About Us
  • News
  • Privacy Policy
  • Contact

Center Activities

  • Laboratories
  • Scientific Projects
  • Industry Projects
  • Research Papers
  • Industry Collaboration
  • International Collaboration

Footer bottom left

© 2020 Center for Artificial Intelligence and Cybersecurity, all rights reserved.

Designed & developed by Nela Dunato Art & Design