scholarly journals Crowdsourcing and interactive modelling for urban flood management

2020 ◽  
Vol 13 (2) ◽  
Author(s):  
Eskedar T. Gebremedhin ◽  
Laura Basco‐Carrera ◽  
Andreja Jonoski ◽  
Mark Iliffe ◽  
Hessel Winsemius
Keyword(s):  
Flood Management ◽  
Urban Flood ◽  
Interactive Modelling

scholarly journals Uncertainty Assessment of Urban Hydrological Modelling from a Multiple Objective Perspective

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1393 ◽  
Author(s):  
Bo Pang ◽  
Shulan Shi ◽  
Gang Zhao ◽  
Rong Shi ◽  
Dingzhi Peng ◽  
...  
Keyword(s):  
Flood Management ◽  
Uncertainty Assessment ◽  
Multiple Objective ◽  
Hydrological Models ◽  
Validation Period ◽  
Urban Flood ◽  
Calibration Period ◽  
Storm Water Management Model ◽  
Glue Method ◽  
Generalized Likelihood Uncertainty Estimation

The uncertainty assessment of urban hydrological models is important for understanding the reliability of the simulated results. To satisfy the demand for urban flood management, we assessed the uncertainty of urban hydrological models from a multiple-objective perspective. A multiple-criteria decision analysis method, namely, the Generalized Likelihood Uncertainty Estimation-Technique for Order Preference by Similarity to Ideal Solution (GLUE-TOPSIS) was proposed, wherein TOPSIS was adopted to measure the likelihood within the GLUE framework. Four criteria describing different urban stormwater characteristics were combined to test the acceptability of the parameter sets. The TOPSIS was used to calculate the aggregate employed in the calculation of the aggregate likelihood value. The proposed method was implemented in the Storm Water Management Model (SWMM), which was applied to the Dahongmen catchment in Beijing, China. The SWMM model was calibrated and validated based on the three and two flood events respectively downstream of the Dahongmen catchment. The results showed that the GLUE-TOPSIS provided a more precise uncertainty boundary compared with the single-objective GLUE method. The band widths were reduced by 7.30 m3/s in the calibration period, and by 7.56 m3/s in the validation period. The coverages increased by 20.3% in the calibration period, and by 3.2% in the validation period. The median estimates improved, with an increase of the Nash–Sutcliffe efficiency coefficients by 1.6% in the calibration period, and by 10.0% in the validation period. We conclude that the proposed GLUE-TOPSIS is a valid approach to assess the uncertainty of urban hydrological model from a multiple objective perspective, thereby improving the reliability of model results in urban catchment.

Challenges in urban flood management: travelling across spatial and temporal scales

2008 ◽  
Vol 1 (2) ◽  
pp. 81-88 ◽  
Author(s):  
C. Zevenbergen ◽  
W. Veerbeek ◽  
B. Gersonius ◽  
S. Van Herk
Keyword(s):  
Flood Management ◽  
Temporal Scales ◽  
Urban Flood ◽  
Spatial And Temporal Scales

Developing an Algorithm for Urban Flood Management With the Aim of Reducing Damage and Costs Using the Concept of Conditional Value at Risk 

2021 ◽  
Author(s):  
Pedram Eshaghieh Firoozabadi ◽  
sara nazif ◽  
Seyed Abbas Hosseini ◽  
Jafar Yazdi
Keyword(s):  
At Risk ◽  
Hybrid Model ◽  
Best Management Practices ◽  
Value At Risk ◽  
Management Practices ◽  
Flood Management ◽  
Surface Flow ◽  
Conditional Value At Risk ◽  
Urban Flood ◽  
Proposed Model

Abstract Flooding in urban area affects the lives of people and could cause huge damages. In this study, a model is proposed for urban flood management with the aim of reducing the total costs. For this purpose, a hybrid model has been developed using SWMM and a quasi-two-dimensional model based on the cellular automata (CA) capable of considering surface flow infiltration. Based on the hybrid model outputs, the best management practices (BMPs) scenarios are proposed. In the next step, a damage estimation model has been developed using depth-damage curves. The amount of damage has been estimated for the scenarios in different rainfall return periods to obtain the damage and cost- probability functions. The conditional value at risk (CVaR) are estimated based on these functions which is the basis of decision making about the scenarios. The proposed model is examined in an urban catchment located in Tehran, Iran. In this study, five scenarios have been designed on the basis of different BMPs. It has been found that the scenario of permeable pavements has the lowest risk. The proposed model enables the decision makers to choose the best scenario with the minimum cost taking into account the risk associated with each scenario.

scholarly journals Decision support system for urban flood management

2005 ◽  
Vol 7 (1) ◽  
pp. 3-15 ◽  
Author(s):  
A. J. Abebe ◽  
R. K. Price
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Data Acquisition ◽  
Support System ◽  
Urban Areas ◽  
Flood Management ◽  
Urban Flood ◽  
Flood Warning ◽  
Forecast Models

This paper presents the development of a decision support system (DSS) for flood warning and instantiation of restoration activities in two urban areas, the Liguria Region in Italy and the Greater Athens catchment in Greece, with the potential of extension to other locations with similar flooding problems. The tool is designed to work at the centre of a set of meteorological and hydrologic/hydraulic forecast models together with telemetric data acquisition networks. The study reveals the complexity and uncertainty involved in managing flooding in the study areas. Issues about the validity and extended benefits of the system are also discussed.

Eco-composite Porous Concrete Drainage Systems: An Alternative Mitigation for Urban Flood Management

2021 ◽  
pp. 195-201
Author(s):  
Feroz Hanif Mohamed Ahmad ◽  
Mohamad Hidayat Jamal ◽  
Abdul Rahman Mohd. Sam ◽  
Nuryazmeen Farhan Haron
Keyword(s):  
Flood Management ◽  
Urban Flood ◽  
Drainage Systems ◽  
Porous Concrete
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