Flooding In Urban Areas Research Articles

Urban landscape planning adapting to flood in Can Tho city, Viet Nam

To promote flood resilience and reduce the damaging effects of flood in urban areas, the paper proposes an urban flood adaptation model based on an urban hydrological model, combined with the capacity of the flood ecological infracstruture. This model includes allowing flood to enter the city and restoring the interaction between flood and riparian ecosystems. This approach is called flood adaptive ecological awareness. To implement this idea, the paper translates into urban landscape planning principles that consider flood as a resource for urban ecosystems, establishing flood storage spaces based on ecological infrastructure adapted to dynamics of flood. The ability to regulate, collect, penetrate and purify pollution with water is due to the participation of landscape ecological infrastructure and enhance the regulatory capacity to mitigate the harmful effects of flood on Can Tho urban areas in Mekong Delta region, Vietnam.

Land use change mapping and its impact on storm water runoff using Remote sensing and GIS: a case study of Mumbai, India

The rapid increase in urbanization worldwide has induced a change in land use–land cover (LULC) over the years. In Mumbai, India, this has further altered the hydrological processes like infiltration, evapotranspiration, interception and erosion and also caused loss of current drainage capacity and flooding in urban areas. This paper mainly assesses the changes in land-use land-cover types and its impact on storm water discharge from 1973 to 2018 in Mumbai using ArcGIS software. The image was classified into five LULC categories after superimposing in Arch-GIS, such as forest, open land, wetland, water and built-up area. The analysis of LULC pattern for the area under study over a period of 45 years showed that there was 66% rise in the built-up area whereas the Forest, open land and Wetland and water body together had reduced by 21%, 36% and 28%, respectively with respect to overall catchment area of Mumbai. Also, the analysis results gave a rise in peak discharge of storm water by 36% because of the changes in LULC over the given time period. On the whole, the land area affected by water logging has significantly increased over the time. The study therefore indicates that the integration of GIS and remote sensing was an effective way of approach for assessing the process of land-use land-cover change.

Evaluating the Impact of Urban Growth on the Design of Storm Water Drainage Systems

Urban growth is one of the major causes of flooding in urban areas. This affects the runoff coefficients, which is among the most important factors that affect the design of storm water drainage systems. Changing the runoff coefficient will affect the design parameters of the drainage network, including outfall discharge, velocity, lag time and cost of construction. This study aims to assess the effect of changing the runoff coefficient due to urban growth on the design of a storm water drainage system. The hydrological models Hyfran, StormCAD and GIS are used to analyze different runoff coefficients. This study examines three zones in Dammam in the Kingdom of Saudi Arabia (KSA). The data developed from the models for the current case studies are used to develop an empirical equation to predict the max discharge for other catchments. The discharge is a function of the return period, runoff coefficient, drainage density, longest path, rainfall intensity and catchment area. To validate the developed equation, we use it to estimate the discharge in a real case study in South Korea. A comparison between the measured discharge and estimated discharge shows that the empirical equation is capable of predicting the maximum discharge for different catchments with high accuracy. Then, the validation of the models is carried out to determine the effect of the runoff coefficient on the design of a storm water drainage system in a case study in KSA. The results show that an increasing runoff coefficient due to urban growth increases the outfall discharge and velocity of storm water drainage systems, as well as affecting the cost of construction and decreasing the lag time. The cost increases by two to three times with increasing urbanization. This study provides a new perspective on the hydrologic impact of urban growth on the design of storm water drainage systems, which are essential for flood management. Moreover, the relationship between urban growth and the cost of storm drainage networks is explored, which could help decision makers to make appropriate judgements.

Trialing Innovative Technologies in Crisis Management—“Airborne and Terrestrial Situational Awareness” as Support Tool in Flood Response

Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but also to test and evaluate its benefit in a realistic environment before the disaster strikes. To bridge the gap between theoretic potential and actual integration into practice, the EU-funded project DRIVER+ has designed a methodical and technical environment to assess innovation in a realistic but non-operational setup through trials. The German Aerospace Center (DLR) interdisciplinary merged mature technical developments into the “Airborne and terrestrial situational awareness” system and applied it in a DRIVER+ Trial to promote a sustainable and demand-oriented R&D. Experienced practitioners assessed the added value of its modules “KeepOperational” and “ZKI” in the context of large-scale flooding in urban areas. The solution aimed at providing contextual route planning in police operations and extending situational awareness based on information derived through aerial image processing. The user feedback and systematically collected data through the DRIVER + Test-bed approved that DLR’s system could improve transport planning and situational awareness across organizations. However, the results show a special need to consider, for example, cross-domain data-fusion techniques to provide essential 3D geo-information to effectively support specific response tasks during flooding.

A Method to Improve the Flood Maps Forecasted by On-Line Use of 1D Model

Forecasting floods in urban areas during a heavy rainfall is the aim of every early warning system. 2D-models produce the most accurate flood maps, but they are practically useless as quasi real-time tools, because their run times are comparable to times of propagation of floods. Run times of 1D-model are of tens of seconds, but their predictions lack accuracy and many useful indicators of flood severity. Our aim is the identification of the 2D-model map that is more similar to the actual map, chosen among those simulated off-line. To this aim, we produce a rough flood map of the occurring event, through a quasi real-time simulation of the rainfall-runoff using a 1D-model. Then we apply an original method, named “ranking approach”, to perform the best matching. This method is applied to the Corace torrent (Calabria, Southern Italy), using 17 synthetic hyetographs to simulate the same number of rainfall-runoff events, using 1D (SWMM) and 2D (MIKE) models. The method proves to be effective in 65% of the cases, while in 82% of cases (i.e., for 14 cases out 17), the event produced by the same ietograph falls within the third rank.

Applicability of urban streets as temporary open floodways

Abstract Climate change coupled with urbanization and its increasing impervious surfaces have caused major challenges for the water sector worldwide. In Norway, an ageing infrastructure with already insufficient drainage capacities results in large amounts of runoff during high-intensity rainfall events causing frequent floods in urban areas. Due to limited available space to handle the future projected increase in stormwater, there is a need to utilize already occupied space for stormwater management, such as roads and streets, during extreme events. Limited research has been done on the design and applicability of urban streets as temporarily flood ways diverting stormwater to the nearest recipient. This paper will study the benefits and limitations of adapting urban streets as safe flood ways to route stormwater by modelling an urban street as a floodway. Streets as floodways will require additional hydraulic performance criteria and safety criteria. Performance criteria are identified and evaluated, and a method is proposed for the evaluation of urban streets applicability as floodways. The method can be used to evaluate the applicability of multifunctional streets used as urban floodways and can be adapted by municipalities as a decision support tool for stormwater management.

The Effect of Climate Change and Urbanization on the Demand for Low Impact Development for Three Canadian Cities

Climate change and urbanization are increasing the intensity and frequency of floods in urban areas. Low Impact Development (LID) is a technique which attenuates runoff and manages urban flooding. However, the impact of climate change and urbanization on the demand or need for LID in cities for both current and future conditions is not known. The primary goal of this research was to evaluate the demand for LID under different climate change and urban growth scenarios based on a physical-based geospatial framework called the hydrological-hydraulic index (HHI). To do this, 12 scenarios considering four climate change and three urbanization conditions were developed. The HHI for three cities in Canada (Toronto, Montreal, and Vancouver) were estimated, evaluated, and compared for these scenarios. The results show that both urbanization and climate change increase the demand for LID. The contribution of climate change and urbanization on LID demand, measured using HHI, varies for each city: in Toronto and Montreal, high rainfall intensity and low permeability mean that climate change is dominant, whereas, in Vancouver, both climate change and urbanization have a similar impact on LID demand. Toronto and Montreal also have a higher overall demand for LID and the rate of increase in demand is higher over the study period. The results of this study provide us with a comprehensive understanding of the effect of climate and urbanization on the demand for LID, which can be used for flood management, urban planning, and sustainable development of cities.

Operation Techniques and Hydrological Applications of X-band Dual-polarization Radar for Monitoring Flash Flood in Metropolitan Area

Radar is useful for monitoring flash flood in urban areas because it provides rainfall data with high spatial and temporal resolution for a wide area. In 2014, the Korea Institute of Civil Engineering and Building Technology introduced the first X-band dual-polarization radar in Korea and has subsequently been researching on flash floods in the metropolitan area using the rainfall data. Considering the various advantages of X-band dual-polarization radar, the Water Hazard Information Platform in Korea introduced two X-band dual-polarization radars (KRU and YSU radars) into the metropolitan area, in 2017. This study described the characteristics of KRU and YSU radars, their observation strategies, and quality control techniques. Moreover, we also assessed the hydrological applications of the X-band dual-polarization radars in the metropolitan area by analyzing three years of rainfall data from 2017 to 2019.

Application of remote sensing and GIS for assessing and proposing mitigation measures in flood-affected urban areas, Egypt

This study investigates the impact of the October 2016 flash floods in urban areas located in selected catchments along the Nile Valley and Red Sea regions for the assessment and the proposal of feasible mitigation measures. Optical and radar satellite images acquired before and shortly after flash flood events were analyzed to detect and map the active contributing channels, the interfering urban areas, the response of natural depressions and storage areas, and the conveying channels to the flash floods. The quantitative estimates of October 2016 flash floods parameters including total rainfall depths, the active channel cross-sectional areas, and the spatial extent of storage areas of the accumulated flood water were measured. Various hydrological parameters were extracted using the Digital Elevation Model (DEM) for the estimation of water volumes of largely inundated depressions. It was determined that the October 2016 flash floods were devastating in the Ras Gharib area; however, these floods were properly managed at both the New El Minya and New Qena urban areas. In contrast, the flash floods at the Al-Saaf and Atfih urban area require urgent mitigation measures given that wastewater depressions and sanitary facilities are prevalent in the downstream reaches of the studied drainage basins.

GIS-based multidimensional decision model for enhancing flood risk prioritization in urban areas

Flooding can be an unexpected event which causes high impacts on everyone in society. These can include loss of life, injuries, creating homelessness, as well as causing damage to properties, and disrupting commerce and public services. Hence, seeking to reduce disasters caused by flooding is a significant challenge for policymakers, technical professionals, organizations, and civil society. However, ensuring that they interact with each other demands multiple objectives be set and achieved - such as those concerning economic, social, human, public health and accessibility factors, even though these factors may conflict with each other. Thus, this paper proposes a multidimensional decision model to prioritize risks from flooding in urban areas, and to assess the overall risk by using probabilistic analysis. The modeling is based on Multi-Attribute Utility Theory (MAUT). In order to validate the model, a case study that was carried out in a municipality in the Northeast of Brazil is simulated with realistic data. Furthermore, the results are discussed by taking advantage of visualizations of risk mapping developed from a Geographic Information System (GIS) that acts as a supplementary tool to guide local policies on preventing and mitigating floods. In addition, it can be used to improve practices, such as resource allocation planning, to achieve this goal. Moreover, the model is flexible and can be replicated in any region of the world. It presents an alternative proposal with potential for management improvements, since the decision-maker (DM) can access a broader range of information.

Urban growth and groundwater sustainability: Evaluating spatially distributed recharge alternatives in the Mexico City Metropolitan Area

Groundwater-dependent cities face increasing population and changes in urban land use, threatening long-term aquifer sustainability by simultaneously increasing pumping demand while modifying recharge rates. Aquifer management involves a portfolio of alternatives to balance the sustainability of multiple water supply sources, including novel recharge alternatives to supplement traditional groundwater and surface water sources. However, potential managed aquifer recharge solutions can lead to unintended consequences as modern infrastructure and management alter natural hydrology, changing the underlying groundwater paradigm. This study uses a multiobjective analysis approach to evaluate the performance of spatially distributed aquifer management alternatives for the Mexico City Metropolitan Area (MCMA), a region where the population has increased by 48% and urban land use by 35% in the last 30 years. Recharge alternatives are evaluated using a physically based groundwater model that incorporates land and water use trends, and include: repairs to the water supply distribution network, increased wastewater treatment and infiltration, and increased infiltration of imported water supplies. These alternatives are compared according to planning objectives aggregated over three overlapping subregions within the model to minimize energy use for pumping, minimize water quality risks in subsidence-prone areas, and minimize groundwater flooding in urban areas. Results indicate that management alternatives resulting in equivalent changes in storage can exhibit spatially distinct reductions in drawdown over the historical period. Additionally, combining multiple alternatives results in a more than an additive risk of groundwater flooding, demonstrating the need for mitigation of rising water tables. This model will serve as the basis for future spatial optimization studies under future climate and land use scenarios. These approaches have broad applicability in other rapidly urbanizing regions dependent on groundwater supplies.

Urban Flood Prediction Using Deep Neural Network with Data Augmentation

Data-driven models using an artificial neural network (ANN), deep learning (DL) and numerical models are applied in flood analysis of the urban watershed, which has a complex drainage system. In particular, data-driven models using neural networks can quickly present the results and be used for flood forecasting. However, not a lot of data with actual flood history and heavy rainfalls are available, it is difficult to conduct a preliminary analysis of flood in urban areas. In this study, a deep neural network (DNN) was used to predict the total accumulative overflow, and because of the insufficiency of observed rainfall data, 6 h of rainfall were surveyed nationwide in Korea. Statistical characteristics of each rainfall event were used as input data for the DNN. The target value of the DNN was the total accumulative overflow calculated from Storm Water Management Model (SWMM) simulations, and the methodology of data augmentation was applied to increase the input data. The SWMM is one-dimensional model for rainfall-runoff analysis. The data augmentation allowed enrichment of the training data for DNN. The data augmentation was applied ten times for each input combination, and the practicality of the data augmentation was determined by predicting the total accumulative overflow over the testing data and the observed rainfall. The prediction result of DNN was compared with the simulated result obtained using the SWMM model, and it was confirmed that the predictive performance was improved on applying data augmentation.

Implications of land use transitions and climate change on local flooding in urban areas: An assessment of 42 Indian cities

Urban development induced land transitions affect urban hydrology, resulting in increased flooding risks. Climate change-related precipitation changes are an added complexity to the flood risks of cities. This study examines the role of land use changes in determining the occurrence of urban flooding events across 42 Indian cities under current and future climate change scenarios. Landsat images for 1990, 2000, 2010, and 2017 have been processed using a hybrid classification technique to determine the land use shares for all cities. A typical event-count study using newspaper archives has been conducted to create a flooding event database. A multilevel model employing logistic mixed-effects approach was used. Future projections of the occurrence of flooding events for nine models under three climate change-related Representative Concentration Pathways (RCPs)—2.6, 4.5, and 8.5—and three urban development scenarios have been carried out. The results suggest that cities should preserve the land uses that act as a sponge—the green, open and blue spaces. As these spaces decrease, the projected flooding events increase. Under the RCP 2.6 scenario, the number of flooding events is significantly lower (95 % confidence) than under RCPs 4.5 and 8.5. The expected flooding occurrences between RCP4.5 and RCP8.5 are not significantly different (95 % confidence) for many scenarios, suggesting that Indian cities should aim for a world temperature increase of below 2 °C, or devastating consequences are imminent. This study highlights the need for Indian cities to undertake integrated spatial planning measures for a resilient, sustainable urban future.

건축물 정보를 활용한 도시침수 취약성 진단방법 개발

Unusual meteorological phenomena in urban areas are causes of life loss and economic damage. Flooding is the major cause of large economic damage among natural disasters that occurs in cities. Especially, localized torrential rains in urban areas cause substantial economic damage in only a short time. Although similar torrential rain falls occur in both the city and nature, the occurrence patterns for flooding are very different. Urbanization is one reason for flooding to exhibit different characteristics, which we refer to as urban characteristics. However, the vulnerabilities of flooding in urban areas to do urbanization are unclear. Thus, it is necessary to analyze and perform a vulnerability diagnosis of the characteristics of different areas and buildings that are repeatedly damaged by flooding. This study identified vulnerabilities using a modified spatial regression model (OLS) using big data for buildings in 2012 in Seoul, which was repeatedly flooded by heavy rains of more than 50 mm/hour since 2000. In addition, the vulnerability diagnosis model was applied to individual parcels containing buildings in Seoul in order to spatially derive and verify the probability distribution of buildings vulnerable to urban flooding.

Comparison of fluvial and pluvial flood risk curves in urban cities derived from a large ensemble climate simulation dataset: A case study in Nagoya, Japan

Flood disasters are caused by two types of flooding: pluvial and fluvial flooding. The different hydrodynamic characteristics of these two types have been intensively discussed in a literature. However, their impact and the resulting damage have not yet been examined in a comprehensive manner due to the lack of extreme rainfall data and/or computational costs of flood simulations. Recently, an increasing number of ensemble climate simulation data has become available, providing long-term rainfall data based on numerical climate simulations. This is a case study of a flooding in an urban area set in Nagoya City, Japan. We applied a large ensemble climate simulation database, d4PDF, to a pluvial and fluvial flood model and derived the flood risk curves for each type of flooding. The results indicated that pluvial flooding presents comparable economic risk to fluvial flooding (only 16% and 17% lesser damage at 50- and 100-year return periods, respectively) despite its significantly shallower flood depths (area with flood depth over 45 cm was only 10.5% and 5.4%, respectively). The significant impact of pluvial flooding is attributable to its wider flood area (despite shallower depths), impacting major economic assets sprawled over the city, including areas further away from the river. Furthermore, fluvial flood risk was managed by settling the Nagoya Castle (now the central economic district) on higher altitudes. The results suggest that pluvial flooding could have comparable economic risks to fluvial flooding in urban areas where major economic assets are not concentrated around streams as well as historical countermeasures are installed against fluvial flooding.

Using High Resolution Images from UAV and Satellite Remote Sensing for Best Management Practice Analyses

Best Management Practices (BMPs) are commonly adopted to ameliorate the quality of runoff and reduce the frequency and intensity of flash floods in urban areas. To date, many of the BMP studies are conducted using coarse resolution data. However, the accuracy of such studies may be compromised due to the shortcomings inherent in the input data; as such, the evaluation of the BMP cost-effectiveness may not be accurate. The objective of this paper is to demonstrate the improvements of higher resolution images over coarse resolution data in BMP analyses. An unmanned aerial vehicle (UAV) was used to collect a more detailed and accurate picture of the digital surface model and digital elevation model. Landsat 8 multi-spectral imagery was classified by object-oriented classification to generate a land use/land cover map. The method used in this study provided more detailed and accurate information of the physical conditions of the study area, an improved subwatershed delineation, a more comprehensive list of the suitable locations for BMPs, and a more reliable estimate of the cost-effectiveness of the BMP ensembles than that generated using coarse resolution data. Using the fine resolution data, this study further determined the utility of the selected BMP ensembles under a changed future climate regime and identified the best BMP and BMP ensemble in reducing urban surface runoff. This method can be especially useful in areas without quality topography and land use data.

ДРЕНИРУЮЩИЙ ЦЕМЕНТОБЕТОН В ДОРОЖНОМ СТРОИТЕЛЬСТВЕ

This paper considers the use of highly permeable concrete, al-so known as drainage, porous, coarse-grained, moisture-permeable, permeable concrete, in road construction, which is a special type of concrete whose porosity is higher than most others. High permeability of water through the body of the concrete structure to the lower layers of the base is achieved due to interconnected pores and voids. Highly permeable concrete pavement is used to reduce local floods in ur-ban areas, acting as a sustainable drainage system. The permeability of permeable con-crete can be reduced during operation due to clogging of pores, this leads to a limitation of the service life of such a coating. The issues of studying the mechanism of clogging and ways to combat it remain open.

Precipitation spatial patterns in cities with different urbanisation types: Case study of Novi Sad (Serbia) as a medium-sized city

A direct outcome of the global climate change is the modification of seasonal precipitation patterns, apparent on a monthly temporal scale. In Central Europe, it includes more frequent high-intensity rainfalls, occurring mostly during spring and summer. These heavy rainfalls induce pluvial floods in urban areas due to a high percentage of impervious surfaces and limited drainage systems. This hazard affects Central European cities and impacts many receptors, including lives, infrastructures, private properties or the functioning of cities. This study focuses on the monitoring of precipitation events with the aim of revealing precipitation patterns across two different types of land cover: urban and suburban/rural areas of Novi Sad (Serbia). Measurements from seven rain gauge stations were used as input data, covering the 2015-2018 period. The precipitation data were analysed using 12 precipitation indices, nine of which were defined by the Expert Team on Climate Change Detection and Indices (ETCCDI), while three additional were designed specifically for this study. Based on their locations, the stations were classified into the 'urbanized' and 'non-urbanised' group. The concept of the Local Climate Zone (LCZ) was used to classify urbanised areas LCZ1-8, non-urbanised areas LCZ9 and the land cover zones (LCZ A-G). A statistical analysis based on the ANOVA F-test was conducted, defining the significance threshold at 90% for a = 0.01 and at 95% for a = 0.05. The obtained results revealed one relation for the CDD index at 95% and two relations at 90% for CDD and Rp95 indices, showing a relation between heavy rainfall and the type of land cover. Statistical results underline the need for a denser station network and longer monitoring periods in order to proceed to stronger statistical tests and make it possible to establish other relations with the climate indices.

ГЕОФІЗИЧНІ ДОСЛІДЖЕННЯ ПІДТОПЛЕННЯ ТЕРИТОРІЙ МІСЬКИХ АГЛОМЕРАЦІЙ

The article is dedicated to using of thegeophysical study of flooding of urban conglomerates areas. The studies were performed within the framework of three stages of exploration of flooding area:reconnaissance-methodical, detailed and monitored ones. The most effective principles of the geophysical mapping of flooding area with geoelectrical horizontal section in depth, creation of geological and geophysical model of the upper part of the section are described. This approach made an assessment tool for classification of the flooding-prone urban areas (on example of flooding area of the Expocenter of Ukraine territory, Kyiv). It is important to note that there is no universal set of geophysical methods for the study of flooding of urban area. This point must be taken into account when choosing the proper geophysical method, elimination of the effects of physical differentiation of soils and economic efficiency of the chosen complex of geophysical methods.

Assessment of GPM IMERG and radar quantitative precipitation estimation (QPE) products using dense rain gauge observations in the Guangdong-Hong Kong-Macao Greater Bay Area, China

The recent intensification of extreme rainfall events has the potential to aggravate the frequency and intensity of floods in urban areas and signals the urgent need for accurate and high spatiotemporal resolution precipitation data for flood monitoring and warning to alleviate the associated damages. In this context, this paper aims to statistically assess the latest Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) multisatellite constellation and radar quantitative precipitation estimation (QPE) products against dense rain gauge network observations under multiple temporal scales (hourly and 3-hourly) and three spatial scales (grid cumulative, regional, and grid) over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) in China. The results indicate that (1) at the grid cumulative scale, QPE significantly outperforms IMERG products. The correlation coefficients of QPE (0.83 ≤ CORR ≤ 0.85) are much higher than those of IMERG products (0.35 ≤ CORR ≤ 0.56), the estimation of QPE is generally significantly underestimated (−0.23 ≤ BIAS ≤ -0.16), and the BIAS of IMERG products is larger than that of QPE (−0.24 ≤ BIAS ≤ 0.23). (2) At the regional scale, the accuracy of IMERG products has been significantly improved, with relatively high correlation coefficients (CORR≥0.8) and decreased root mean squared error (RMSE) values (1.18 mm ≤ RMSE ≤ 0.22 mm), and Taylor diagrams visually show that QPE is closer to the gauge observations than are IMERG products. (3) The evaluation results at the grid scale show that both IMERG products and QPE can accurately reflect the spatial distribution of precipitation. Among these results, the spatial distribution of QPE is the most consistent with the actual rainfall, although an obvious underestimation of rainfall occurs in areas with strong rainfall. (4) In terms of detection indicators, the three IMERG products are superior to QPE at capturing rainfall events and have more advantages over QPE in the estimation of instantaneous precipitation, especially for light rain events. However, QPE has better detection effects for rainfall events under rainstorm and heavy rainstorm events, indicating the hydrologic utility of this product. Among the three IMERG products, the IMERG Early Run (ER) product has the advantages of a short lag time and high accuracy, and it has the potential to be applied in flood forecasting. Future studies should improve IMERG algorithms and promote the application of QPE in urban rainstorm and flood research.