scholarly journals Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation model

2015 ◽  
Vol 524 ◽  
pp. 385-400 ◽  
Author(s):  
Dapeng Yu ◽  
Tom J. Coulthard
Keyword(s):  
Surface Water ◽  
Urban Surface ◽  
Flood Modelling ◽  
Hydrological Parameters ◽  
Inundation Model

scholarly journals Urban surface water flood modelling – a comprehensive review of current models and future challenges

2020 ◽  
Author(s):  
Kaihua Guo ◽  
Mingfu Guan ◽  
Dapeng Yu
Keyword(s):  
Surface Water ◽  
Urban Areas ◽  
Scale Effects ◽  
Water Flooding ◽  
Urban Surface ◽  
Economic Losses ◽  
Intense Rainfall ◽  
Urban Flood ◽  
Comprehensive Review ◽  
Flood Modelling

Abstract. Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.

scholarly journals Urban surface water flood modelling – a comprehensive review of current models and future challenges

2021 ◽  
Vol 25 (5) ◽  
pp. 2843-2860
Author(s):  
Kaihua Guo ◽  
Mingfu Guan ◽  
Dapeng Yu
Keyword(s):  
Surface Water ◽  
Urban Areas ◽  
Scale Effects ◽  
Water Flooding ◽  
Urban Surface ◽  
Economic Losses ◽  
Intense Rainfall ◽  
Urban Flood ◽  
Comprehensive Review ◽  
Flood Modelling

Abstract. Urbanisation is an irreversible trend as a result of social and economic development. Urban areas, with high concentration of population, key infrastructure, and businesses, are extremely vulnerable to flooding and may suffer severe socio-economic losses due to climate change. Urban flood modelling tools are in demand to predict surface water inundation caused by intense rainfall and to manage associated flood risks in urban areas. These tools have been rapidly developing in recent decades. In this study, we present a comprehensive review of the advanced urban flood models and emerging approaches for predicting urban surface water flooding driven by intense rainfall. The study explores the advantages and limitations of existing model types, highlights the most recent advances, and identifies major challenges. Issues of model complexities, scale effects, and computational efficiency are also analysed. The results will inform scientists, engineers, and decision-makers of the latest developments and guide the model selection based on desired objectives.

scholarly journals Two-Step Urban Water Index (TSUWI): A New Technique for High-Resolution Mapping of Urban Surface Water

2018 ◽  
Vol 10 (11) ◽  
pp. 1704 ◽  
Author(s):  
Wei Wu ◽  
Qiangzi Li ◽  
Yuan Zhang ◽  
Xin Du ◽  
Hongyan Wang
Keyword(s):  
Surface Water ◽  
High Resolution ◽  
Urban Surface ◽  
Mapping Technique ◽  
Support Vector ◽  
Svm Classifier ◽  
P Value ◽  
Urban Water ◽  
Water Index ◽  
Water Mapping

Urban surface water mapping is essential for studying its role in urban ecosystems and local microclimates. However, fast and accurate extraction of urban water remains a great challenge due to the limitations of conventional water indexes and the presence of shadows. Therefore, we proposed a new urban water mapping technique named the Two-Step Urban Water Index (TSUWI), which combines an Urban Water Index (UWI) and an Urban Shadow Index (USI). These two subindexes were established based on spectral analysis and linear Support Vector Machine (SVM) training of pure pixels from eight training sites across China. The performance of the TSUWI was compared with that of the Normalized Difference Water Index (NDWI), High Resolution Water Index (HRWI) and SVM classifier at twelve test sites. The results showed that this method consistently achieved good performance with a mean Kappa Coefficient (KC) of 0.97 and a mean total error (TE) of 2.28%. Overall, classification accuracy of TSUWI was significantly higher than that of the NDWI, HRWI, and SVM (p-value < 0.01). At most test sites, TSUWI improved accuracy by decreasing the TEs by more than 45% compared to NDWI and HRWI, and by more than 15% compared to SVM. In addition, both UWI and USI were shown to have more stable optimal thresholds that are close to 0 and maintain better performance near their optimum thresholds. Therefore, TSUWI can be used as a simple yet robust method for urban water mapping with high accuracy.

scholarly journals Assessing real options in urban surface water flood risk management under climate change

2018 ◽  
Vol 94 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Haixing Liu ◽  
Yuntao Wang ◽  
Chi Zhang ◽  
Albert S. Chen ◽  
Guangtao Fu
Keyword(s):  
Climate Change ◽  
Risk Management ◽  
Surface Water ◽  
Real Options ◽  
Flood Risk ◽  
Flood Risk Management ◽  
Urban Surface
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