Precipitation threshold for urban flood warning - an analysis using the satellite-based flooded area and radar-gauge composite rainfall data

2020 ◽  
Vol 32 ◽  
pp. 48-61
Author(s):  
Duc Anh Dao ◽  
Dongkyun Kim ◽  
Jeongha Park ◽  
Taewoong Kim
Keyword(s):  
Rainfall Data ◽  
Urban Flood ◽  
Flood Warning ◽  
Precipitation Threshold ◽  
Flooded Area

ANN based Scaling of Rainfall Data for Urban Flood Simulations

2020 ◽  
Author(s):  
Vinay Ashok Rangari ◽  
K. Veerendra Gopi ◽  
Umamahesh V Nanduri ◽  
Roshan Bodile
Keyword(s):  
Rainfall Data ◽  
Urban Flood ◽  
Flood Simulations

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.

scholarly journals A Nonparametric Stochastic Approach for Disaggregation of Daily to Hourly Rainfall Using 3-Day Rainfall Patterns

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2306
Author(s):  
Heeseong Park ◽  
Gunhui Chung
Keyword(s):  
Time Series Data ◽  
Daily Rainfall ◽  
Rainfall Event ◽  
Rainfall Data ◽  
Series Data ◽  
K Nearest Neighbor ◽  
Urban Catchment ◽  
Urban Flood ◽  
Hourly Rainfall ◽  
Rainfall Patterns

As infrastructure and populations are highly condensed in megacities, urban flood management has become a significant issue because of the potentially severe loss of lives and properties. In the megacities, rainfall from the catchment must be discharged throughout the stormwater pipe networks of which the travel time is less than one hour because of the high impervious rate. For a more accurate calculation of runoff from the urban catchment, hourly or even sub-hourly (minute) rainfall data must be applied. However, the available data often fail to meet the hydrologic system requirements. Many studies have been conducted to disaggregate time-series data while preserving distributional statistics from observed data. The K-nearest neighbor resampling (KNNR) method is a useful application of the nonparametric disaggregation technique. However, it is not easy to apply in the disaggregation of daily rainfall data into hourly while preserving statistical properties and boundary continuity. Therefore, in this study, three-day rainfall patterns were proposed to improve reproducible ability of statistics. Disaggregated rainfall was resampled only from a group having the same three-day rainfall patterns. To show the applicability of the proposed disaggregation method, probability distribution and L-moment statistics were compared. The proposed KNNR method with three-day rainfall patterns reproduced better the characteristics of rainfall event such as event duration, inter-event time, and toral amount of rainfall event. To calculate runoff from urban catchment, rainfall event is more important than hourly rainfall depth itself. Therefore, the proposed stochastic disaggregation method is useful to hydrologic analysis, particularly in rainfall disaggregation.

scholarly journals Ensembles of radar nowcasts and COSMO-DE-EPS for urban flood management

2018 ◽  
Vol 2017 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Alrun Jasper-Tönnies ◽  
Sandra Hellmers ◽  
Thomas Einfalt ◽  
Alexander Strehz ◽  
Peter Fröhle
Keyword(s):  
Urban Areas ◽  
Flood Management ◽  
Short Term ◽  
Ensemble Forecasts ◽  
Urban Flood ◽  
Rainfall Events ◽  
Flood Warning ◽  
Urban Catchments ◽  
Heavy Rainfall Events

Abstract Sophisticated strategies are required for flood warning in urban areas regarding convective heavy rainfall events. An approach is presented to improve short-term precipitation forecasts by combining ensembles of radar nowcasts with the high-resolution numerical weather predictions COSMO-DE-EPS of the German Weather Service. The combined ensemble forecasts are evaluated and compared to deterministic precipitation forecasts of COSMO-DE. The results show a significantly improved quality of the short-term precipitation forecasts and great potential to improve flood warnings for urban catchments. The combined ensemble forecasts are produced operationally every 5 min. Applications involve the Flood Warning Service Hamburg (WaBiHa) and real-time hydrological simulations with the model KalypsoHydrology.

scholarly journals Optimize Short-Term Rainfall Forecast with Combination of Ensemble Precipitation Nowcasts by Lagrangian Extrapolation

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1752 ◽  
Author(s):  
Na ◽  
Yoo
Keyword(s):  
Flash Flood ◽  
Weighted Average ◽  
Warning System ◽  
Error Variance ◽  
Ensemble Forecast ◽  
Urban Flood ◽  
Target Time ◽  
Flood Warning ◽  
Flood Warning System ◽  
Better Than

The rainfall forecasts currently available in Korea are not sufficiently accurate to bedirectly applied to the flash flood warning system or urban flood warning system. As the lead timeincreases, the quality becomes even lower. In order to overcome this problem, this study proposesan ensemble forecasting method. The proposed method considers all available rainfall forecasts asensemble members at the target time. The ensemble members are combined based on the weightedaverage method, where the weights are determined by applying the two conditions of theunbiasedness and minimum error variance. The proposed method is tested with McGill Algorithmfor Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) rainfall forecasts for four stormevents that occurred during the summers of 2016 and 2017 in Korea. In Korea, rainfall forecasts aregenerated every 10 min up to six hours, i.e., there are always a total of 36 sets of rainfall forecasts.As a result, it is found that just six ensemble members is sufficient to make the ensemble forecast.Considering additional ensemble members beyond six does not significantly improve the quality ofthe ensemble forecast. The quality of the ensemble forecast is also found to be better than that of thesingle forecast, and the weighted average method is found to be better than the simple arithmeticaverage method.

scholarly journals Urban Storm Flooding: Characteristics and Management in Beijing

2018 ◽  
Vol 246 ◽  
pp. 01042 ◽  
Author(s):  
Chao-chen Fu ◽  
Jia-hong Liu ◽  
Hao Wang ◽  
Chen-yao Xiang ◽  
Xiao-ran Fu ◽  
...  
Keyword(s):  
Management System ◽  
Flood Control ◽  
Public Awareness ◽  
Warning System ◽  
Flood Events ◽  
Land Utilization ◽  
Urban Flood ◽  
Flood Warning ◽  
Extreme Storm ◽  
Urban Storm

Beijing is located on the North China Plain with five rivers, which belong to the Hai River Basin. Its continental monsoon climate with uneven precipitation distribution is extreme likely lead to serious urban flood disasters. According to the disaster results, urban storm flood in Beijing can be classified into four types. Here typical extreme storm flood events and their characteristics in Beijing were analyzed in detail. It showed that storm flood events in recently decades had a trend, which centered in a relatively small area with high intensity and short duration. The main reasons of urban storm flood disaster were urbanization and basic facilities with low flood and drainage standard. Urbanization means land utilization significantly altering hydraulic processes, and extreme storm can easily exceed those facilities capacity. In order to deal with urban storm flood, Beijing government have taken four measurements, which were upgrading and reconstruction of rainwater pumping stations, improving projects of small and medium rivers, building sponge city, and implementing the West Suburb Storm-water Regulation Project. In addition, the flood warning and emergency management system has been established. Furthermore, some measurements were pointed to be done in the future, including improvement of the flood control management system, improvement of flood control plans, strengthening flood warning system, and strengthening social management and public awareness of flood prevention. With these improvements of management and engineering measurements, it can be more secure under intensive storms in Beijing. These experiences of flood control in Beijing can provide references for other cities.

scholarly journals Evaluation of ECMWF's forecasting system for probabilistic urban flood prediction: a case study in Mexico City

2021 ◽  
Author(s):  
Marco R. López ◽  
Adrián Pedrozo-Acuña ◽  
Marcela L. Severiano Covarrubias
Keyword(s):  
Mexico City ◽  
Local Level ◽  
Warning System ◽  
Precipitation Forecast ◽  
Ensemble Prediction ◽  
Forecast Horizon ◽  
Ensemble Forecasts ◽  
Flood Prediction ◽  
Urban Flood ◽  
Flood Warning

Abstract As the world continues urbanizing, including efforts to forge a new framework of urban development is necessary. Recent studies related to flood prediction and mitigation have shown that Ensemble Prediction Systems (EPSs) constitute a valuable and essential tool for an Early Warning System. However, the use of EPS for flood forecasting in urban zones has yet to be understood. This work has the objective to investigate the potential use of the Operational EPS, issued by the European Centre for Medium-Range Weather Forecasts (ECMWF), for probabilistic urban flood prediction. In this research, a precipitation forecast verification was carried out in two study zones: (1) Mexico Valley Basin and (2) Mexico City, where for the latter, forecasts were compared against real-time observed data. The results showed good forecast reliability for a rain threshold of up to 20 mm in 24-hourly accumulations, with the first 36 h of the forecast horizon being the most reliable. The EPS has sufficient resolution and precision for flood prediction in Mexico City, which represents a further step toward developing a flood warning system at the local level based on ensemble forecasts.

scholarly journals Review and Prospect on Development of Urban Flood Warning System

2018 ◽  
Vol 246 ◽  
pp. 01008
Author(s):  
Jianhua Li ◽  
Zhaosong Qu ◽  
Jun Zheng ◽  
Chong Jiang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Driving Forces ◽  
Warning System ◽  
Urban Flood ◽  
Flood Warning ◽  
The Future ◽  
Flood Warning System ◽  
Further Development

An overall research and analysis on past development track was of great significance for the further development of new theories, models, technologies and applications of urban flood warning system. Thus, the paper comprehensively discussed the development track of urban flood warning system, especially its structures and supporting technologies. From the analysis, it could be seen clearly that demands and technologies were two major driving forces for the development of urban flood warning system in the era of big data. Moreover, it was illustrated that new demands and problems had to be faced, and discussed how to meet them in the future by integrating technologies of big data and cloud computing.

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