Pluvial Flooding in Kolkata: A Case Study of the Major Streets in Northern, Southern and Central Kolkata

2016 ◽  
Vol 4 (5) ◽  
pp. 51-65
Author(s):  
Deblina Mitra ◽  
Suranjana Banerji
Keyword(s):  
Pluvial Flooding

scholarly journals Global flood hazard map and exposed GDP comparison: a China case study

2020 ◽  
Author(s):  
Jerom P. M. Aerts ◽  
Steffi Uhlemann-Elmer ◽  
Dirk Eilander ◽  
Philip J. Ward
Keyword(s):  
Return Period ◽  
Flood Hazard ◽  
Regional Scale ◽  
Flood Protection ◽  
Economic Losses ◽  
Return Periods ◽  
Hazard Maps ◽  
High Exposure ◽  
Pluvial Flooding

Abstract. Floods are among the most frequent and damaging natural hazard events in the world. In 2016, economic losses from flooding amounted to $56 bn globally, of which $20 bn occurred in China (Munich Re, 2017). National or regional scale mapping of flood hazard is at present providing an inconsistent and incomplete picture of floods. Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing of the global hazard maps generated by these models in order to understand their applicability for international risk reduction strategies and for reinsurance portfolio risk assessments using catastrophe models. We expand on existing methods for comparing global hazard maps and analyse 8 global flood models (GFMs) that represent the current state of the global flood modelling community. We apply our comparison to China as a case study and, for the first time, we include industry models, pluvial flooding, and flood protection standards in the analysis. We find substantial variability between the flood hazard maps in modelled inundated area and exposed GDP across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. For example, for the 100 year return period undefended (assuming no flood protection) hazard maps the percentage of total affected GDP of China ranges between 4.4 % and 10.5 % for fluvial floods. For the majority of the GFMs we see only a small increase in inundated area or exposed GDP for high return period undefended hazard maps compared to low return periods, highlighting major limitations in the models’ resolution and their output. The inclusion of industry models which currently model flooding at higher spatial resolution, and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. Pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 % points. Our study strongly highlights the importance of flood defenses for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of area of China) but locally detailed layer of structural defenses in high exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

scholarly journals Socio-Economic Potential Impacts Due to Urban Pluvial Floods in Badalona (Spain) in a Context of Climate Change

Water ◽  
2019 ◽  
Vol 11 (12) ◽  
pp. 2658 ◽  
Author(s):  
Eduardo Martínez-Gomariz ◽  
Luca Locatelli ◽  
María Guerrero ◽  
Beniamino Russo ◽  
Montse Martínez
Keyword(s):  
Climate Change ◽  
Urban Areas ◽  
Rainfall Intensity ◽  
Economic Potential ◽  
Intergovernmental Panel ◽  
Adaptation Measures ◽  
Pluvial Flooding ◽  
The City ◽  
Impacts Of Climate Change

Pluvial flooding in Badalona (Spain) occurs during high rainfall intensity events, which in the future could be more frequent according to the latest report from the Intergovernmental Panel on Climate Change (IPCC). In this context, the present study aims at quantifying the potential impacts of climate change for the city of Badalona. A comprehensive pluvial flood multi risk assessment has been carried out for the entire municipality. The assessment has a twofold target: People safety, based on both pedestrians’ and vehicles’ stability, and impacts on the economic sector in terms of direct damages on properties and vehicles, and indirect damages due to businesses interruption. Risks and damages have also been assessed for the projected future rainfall conditions which enabled the comparison with the current ones, thereby estimating their potential increment. Moreover, the obtained results should be the first step to assess the efficiency of adaptation measures. The novelty of this paper is the integration of a detailed 1D/2D urban drainage model with multiple risk criteria. Although, the proposed methodology was tested for the case study of Badalona (Spain), it can be considered generally applicable to other urban areas affected by pluvial flooding.

Modeling the influence of urbanization on urban pluvial flooding: a scenario-based case study in Shanghai, China

2017 ◽  
Vol 87 (2) ◽  
pp. 1035-1055 ◽  
Author(s):  
Qingyu Huang ◽  
Jun Wang ◽  
Mengya Li ◽  
Moli Fei ◽  
Jungang Dong
Keyword(s):  
Pluvial Flooding ◽  
Urban Pluvial Flooding

scholarly journals Urban pluvial flooding prediction by machine learning approaches – a case study of Shenzhen city, China

2020 ◽  
Vol 145 ◽  
pp. 103719 ◽  
Author(s):  
Qian Ke ◽  
Xin Tian ◽  
Jeremy Bricker ◽  
Zhan Tian ◽  
Guanghua Guan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Learning Approaches ◽  
Shenzhen City ◽  
Pluvial Flooding ◽  
Urban Pluvial Flooding

scholarly journals A Depression-Based Index to Represent Topographic Control in Urban Pluvial Flooding

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2115 ◽  
Author(s):  
Huabing Huang ◽  
Xi Chen ◽  
Xianwei Wang ◽  
Xina Wang ◽  
Lin Liu
Keyword(s):  
Limited Attention ◽  
Topographic Wetness Index ◽  
Digital Elevation ◽  
Pluvial Flooding ◽  
Elevation Model ◽  
The Stability ◽  
Urban Pluvial Flooding ◽  
The Impact ◽  
Flooded Areas

Extensive studies have highlighted the roles of rainfall, impervious surfaces, and drainage systems in urban pluvial flooding, whereas topographic control has received limited attention. This study proposes a depression-based index, the Topographic Control Index (TCI), to quantify the function of topography in urban pluvial flooding. The TCI of a depression is derived within its catchment, multiplying the catchment area with the slope, then dividing by the ponding volume of the depression. A case study is demonstrated in Guangzhou, China, using a 0.5 m-resolution Digital Elevation Model (DEM) acquired using Light Detection and Ranging (LiDAR) technology. The results show that the TCI map matches well with flooding records, while the Topographic Wetness Index (TWI) cannot map the frequently flooded areas. The impact of DEM resolution on topographic representation and the stability of TCI values are further investigated. The original 0.5 m-resolution DEM is set as a baseline, and is resampled at resolutions 1, 2, 5, and 10 m. A 1 m resolution has the smallest TCI deviation from those of 0.5 m resolution, and gives the optimal results in terms of striking a balance between computational efficiency and precision of representation. Moreover, the uncertainty in TCI values is likely to increase for small depressions.

scholarly journals Mitigation of Urban Pluvial Flooding: What Drives Residents’ Willingness to Implement Green or Grey Stormwater Infrastructures on Their Property?

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3069
Author(s):  
Francesco Pagliacci ◽  
Edi Defrancesco ◽  
Francesco Bettella ◽  
Vincenzo D’Agostino
Keyword(s):  
Perceived Threat ◽  
Direct Experience ◽  
Case Study Analysis ◽  
Pluvial Flooding ◽  
Prone Area ◽  
Future Events ◽  
Main Factors ◽  
Urban Pluvial Flooding ◽  
The Impact

As a consequence of climate change, the impact of pluvial flooding is expected to increase in the next decades. Despite citizens’ poor knowledge, several types of stormwater infrastructure can be implemented to mitigate the impact of future events. This paper focuses on the implementation of green and grey stormwater interventions (i.e., with or without vegetation) on private properties. Framed by the Protection Motivation Theory, a survey-based case study analysis, carried out in a pluvial flooding-prone area of the Veneto Region (Italy), highlights the main factors driving people’s willingness to implement these interventions. The analysis shows that the implementation of grey stormwater infrastructures is driven by the perceived threat and the amount of past pluvial flooding damage (i.e., the direct experience as a proxy of prior knowledge) while the implementation of green stormwater infrastructures is driven also by additional factors (awareness of these interventions, age and education level of the citizens). Based on these results, lack of knowledge on innovative stormwater interventions represents a critical barrier to their implementation on private properties, and it confirms the need for specific dissemination and information activities.

scholarly journals Comparison of estimates of global flood models for flood hazard and exposed gross domestic product: a China case study

2020 ◽  
Vol 20 (12) ◽  
pp. 3245-3260
Author(s):  
Jerom P. M. Aerts ◽  
Steffi Uhlemann-Elmer ◽  
Dirk Eilander ◽  
Philip J. Ward
Keyword(s):  
Gross Domestic Product ◽  
Flood Hazard ◽  
Domestic Product ◽  
Hazard Maps ◽  
High Exposure ◽  
Pluvial Flooding ◽  
Reduction Strategies ◽  
High Concentrations ◽  
Risk Reduction Strategies

Abstract. Over the past decade global flood hazard models have been developed and continuously improved. There is now a significant demand for testing global hazard maps generated by these models in order to understand their applicability for international risk reduction strategies and for reinsurance portfolio risk assessments using catastrophe models. We expand on existing methods for comparing global hazard maps and analyse eight global flood models (GFMs) that represent the current state of the global flood modelling community. We apply our comparison to China as a case study and, for the first time, include industry models, pluvial flooding, and flood protection standards in the analysis. In doing so, we provide new insights into how these components change the results of this comparison. We find substantial variability, up to a factor of 4, between the flood hazard maps in the modelled inundated area and exposed gross domestic product (GDP) across multiple return periods (ranging from 5 to 1500 years) and in expected annual exposed GDP. The inclusion of industry models, which currently model flooding at a higher spatial resolution and which additionally include pluvial flooding, strongly improves the comparison and provides important new benchmarks. We find that the addition of pluvial flooding can increase the expected annual exposed GDP by as much as 1.3 percentage points. Our findings strongly highlight the importance of flood defences for a realistic risk assessment in countries like China that are characterized by high concentrations of exposure. Even an incomplete (1.74 % of the area of China) but locally detailed layer of structural defences in high-exposure areas reduces the expected annual exposed GDP to fluvial and pluvial flooding from 4.1 % to 2.8 %.

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