Effects of spatial planning on future flood risks in urban environments

Eco-friendly dredging methods of changing fluvial landforms for enhancing hydraulic habitat quality and river corridor continuum

Hydraulic habitat connectivity, including the longitudinal continuum respect and lateral flood pulse, is critical for fish survival and organism dispersal. Inappropriate and excessive dredging for prevent flooding may harm river ecosystems. The main objective of this study is to evaluate whether eco-friendly dredging presented by changing local river landforms incorporating the concept of nature-based solutions could grow fish habitat quality for improving river continuity and achieving flood control effects. By combining various mathematical models and empirical formulas and verifying them with the data obtained through field surveys, we explore the interconnections of hydrology, river morphology, and the habitat dynamics of four endemic fishes in an alluvial river. The relationship between habitat structure, flood risk, and river topography, flow discharge was presented as the reference for developing the proper river dredging approaches. The results reveal that the primary habitat defects were lack of high-quality habitat, unsatisfied habitat diversity, deficiency in refugia, and disconnectivity. Longitudinal disconnectivity was induced due to shallow water depth, while lateral disconnectivity is primarily caused by fast flow velocity, suggesting different and specific dredging methods were instructed. We recommend that the corresponding eco-friendly dredging schemes for longitudinal and lateral suitable habitat linkages increase fish habitat quality and river corridor continuity. The win-win strategy for enhancing the connection between suitable habitats sustains a more beneficial aquatic corridor and simultaneously achieves alluvial flood disaster risk reduction.

Flood vulnerability mapping and urban sprawl suitability using FR, LR, and SVM models

Floods are among the most destructive disasters because they cause immense damage to human life, property (land and buildings), and resources. They also slow down a country's economy. Due to the dynamic and complex nature of floods, it is difficult to predict the areas that are prone to flooding. In this study, an attempt was made to create a suitability map for future urban development based on flood vulnerability maps for the catchment area of Taif, Saudi Arabia. Three models were used for this purpose, including bivariate (FR), multivariate (LR), and machine learning (SVM) were used. Thirteen parameters were used as flood-contributing parameters. The inventory map was constructed using field surveys, historical data, analysis of RADAR (Sentinel-1A), and Google Earth imagery collected between 2013 and 2020. In general, 70% flood locations were randomly selected from the flood inventory map to generate the flood susceptibility model, and the remaining 30% of the flood locations were used for model validation. The flood susceptibility map was classified into five zones: very low, low, moderate, high, and very high. The AUC value used to predict the performance of the models showed that the accuracy reached 89.5, 92.0, and 96.2% for the models FR, LR, and SVM, respectively. Accordingly, the flood susceptibility map produced by the SVM model is accurate and was used to produce a flood vulnerability map with the help of urban and road density maps. Then slope and elevation maps were integrated with the flood vulnerability model to produce the final suitability map, which was classified into three zones: isolated zone, low suitability, and high suitability areas. The results showed that the highly suitable areas are located in the east and northeast of the Taif Basin, where the flood risk is low and very low. The results of this work will improve the land use planning of engineers and authorities and take possible measures to reduce the flood hazards in the area.

Assessment of Urban Flood Vulnerability Using the Integrated Framework and Process Analysis: A Case from Nanjing, China

Flooding is a serious challenge that increasingly affects residents as well as policymakers. Many studies have noted that decreasing the urban flood vulnerability (UFV) is an indispensable strategy for reducing flood risks; however, some studies have several pertinent assessment limitations. The objective of this study is to assess the UFV of the Xuanwu-Qinhuai-Jianye-Gulou-Yuhua (XQJGY) region from 2012 to 2018 by integrating various indicators into a composite index. This study uses the environment for visualizing images (ENVI) and the geographic information system (GIS) to extract indicators that have geographic attributes for the assessment of UFV and the process analysis method is then used to explore the relationship between these indicators. The results indicated that: (1) The UFV of Xuanwu, Qinhuai, and Gulou decreased from 2012 to 2018 and the UFV of Jianye and Gulou increased from 2012 to 2015 and decreased from 2015 to 2018. (2) The vegetation coverage, precipitation during the flood season, population density, and highway density significantly contributed to the UFV. (3) There also exist transformation pathways between the indicators that led to vulnerability in five districts. This study provides a theoretical basis for the government to manage floods.

Coastal Land Use Management Methodologies under Pressure from Climate Change and Population Growth

Throughout history, humans living in the coastal area constantly adapt to the natural environment and create a changing environment. The rapid coastal development occurred in the mid-19th century and peaks in the mid-20th century, which was a common process in most industrialized areas. With increasing population growth and urban sprawl, many coastal lowlands are unprecedently vulnerable to climate change impacts such as sea level rise, increasing extreme storm events, and coastal flooding. Under the influence of urban revitalization and conservation, the landward shoreline movement accelerated and coastal land shrank, accompanied by community retreat. This research focuses on the importance of incorporating an understanding of the changing coastal land-ocean interaction into adaptive management strategies by illustrating the relationship of land use change, social-economic development, and climate change. Typical coastal changes in Connecticut were selected: New Haven Harbor reflects a dramatic seaward land accretion under industrial and transportation development, New London downtown waterfront reveals a trend of building retreat under industrial and commercial transformation and coastal hazard, New London Ocean Beach indicates how overdeveloped coastal low-lying community fully retreat after a natural disaster, and Jordan Cove barrier island shows a highly dynamic coastal land change and proactive management strategy. The results reveal that to cope with a constantly changing shoreline and the challenges of climate change, a resilient management process must incorporate a cycle of learning, experimenting, and creating with the goal of developing new solutions that are able to deal with our ever-changing environment.

Assessment of the impact of urban water system scheduling on urban flooding by using coupled hydrological and hydrodynamic model in Fuzhou City, China

With climate change and urbanization development, urban areas are facing more serious floods. As a result, hydrological and hydrodynamic models have recently shown a broad application prospect in urban flood simulating and forecasting. For the area with rich inland rivers, urban water resources can be effectively regulated and redistributed through river networks and hydraulic structures scheduling. However, the lack of research on the effect of scheduling becomes a major limitation in model applications. Based on a coupled hydrodynamics model, the current study simulates the flooding response to the combined rainstorm and scheduling scenarios and analyzes the river overflow at the community scale. The result indicated that three local regions in the Jin'an study area are inundated easily. The locations near Qinting Lake were more sensitive to the water regulation rules than others. In the model of control on Qinting Lake, section A is more sensitive to the schedule control than section B, while for section A, the water level increased by 1.44% under the return period (RP) (10 a), and the rate changed to 2.64% under the RP (100 a). The differences in inundation from various scenarios are relatively small. In the mode of joint discharge rules under RP (50 a), the water level changed by 4.77% in section A and 1.24% in section B. The simulation at the community scale considers the overflow process, and the results indicated that the total inundation area decreased by 12.8 ha under joint schedules. The significant effects to alleviate urban inundation mainly come from the decreased flood overflow from the channel, but not from the flooding nodes. This study provides promising references for urban flood management.

Stormwater retention performance of green roofs with various configurations in different climatic zones

Green roof stormwater retention performance is fundamentally related to design configurations and climates. Efficient tools for assessing stormwater retention performance of green roofs with various configurations in different climates are highly desirable for practical applications. In this study, a hydrological model which can be used to simulate dynamic changes in moisture content and evapotranspiration of green roofs is developed and tested (with average Nash-Sutcliffe Efficiency of 0.8197 for calibration and 0.8252 for verification) using monitoring data (2018-2019) of four green roofs with various configurations. The model is applied to simulate long-term (1970-2018) moisture content, actual evapotranspiration, and retention performance of green roofs in eight cities across different climates of China. Green roofs built with engineered soil and Portulaca grandiflora show the largest evapotranspiration and thus provide the largest stormwater retention rates (R_r), while green roofs with light growing medium and Sedum lineare show the lowest evapotranspiration and R_r. R_r of green roofs increases as climate changes from humid to arid. Green roofs at Guangzhou (humid climate) provide the lowest R_r (28% ± 3%) caused by plenty of rainfall (1827 mm), while green roofs at Urumqi (desert climate) show the lowest mean annual actual evapotranspiration (167-269 mm) but provide the largest R_r (84% ± 5%) as a result of the lowest annual rainfall (282 mm). The results highlight that stormwater retention performance of green roofs could be enhanced through configuration optimization. However, a limiting factor in improving green roofs water retention rates may be the peculiarity of local climatic conditions.

Driving Forces behind Land Use and Land Cover Change: A Systematic and Bibliometric Review

This paper is based on reviewing the literature in the past 10 years on the drivers of land use and land cover change (LULCC) in urban areas. It combines quantitative and qualitative keyword analysis of papers drawn out from the Scopus database. The analysis is primarily based on the number of mentions of keywords in the titles and abstracts of the papers, in addition to the number of keywords appearing in the papers. On the basis of content analysis, a three-level structural categorization of the driving factors was developed. These are presented in a schematic diagram, where the contextual factors are shown as influencing economic and financial factors and policy and regulation, which in turn influences transportation investments and availability, and industrial and residential location choices. Transportation availability was seen as the most frequent factor identified in the literature. This research contends that LULCC is mostly determined by interactions among these four themes in a three-level structure, and on this basis, a model is presented that illustrates LULCC drivers based on local circumstances across the globe.

Knowledge Map of Spatial Planning and Sustainable Development: A Visual Analysis Using CiteSpace

Spatial planning has become an important measure for countries and regions to promote sustainable development. However, there remains a lack of systematic and quantitative research on spatial planning worldwide. In this study, CiteSpace was used to perform bibliometric analysis and visualization research on the Web of Science core collection and China National Knowledge Infrastructure database. It was found that: (1) The number of papers published in global spatial planning research shows an increasing trend, especially after 2018, with China showing an obvious increasing trend. (2) Globally, the United States has the largest number of relevant research results, and Italy has the most cooperation with other countries. The highest research output is from developed countries, while that of developing countries is relatively weak. (3) There is some intersection among countries, disciplines, and authors but it is not strong, indicating that cooperation should be strengthened. (4) Through keyword cluster, timeline, and time zone analysis, global development can be roughly divided into three stages: the first stage is characterized by the study of spatial planning system theory, the second stage is characterized by building green infrastructure and providing ecological services, and the third stage is characterized by an emphasis on public participation and the establishment of justice mechanisms. China’s development corresponds to three stages: the theory and experience learning stage, the spatial planning system focused on economic development stage, and the integration of multiple plans and the sustainable development exploration stage. (5) There are differences in burst words between the world and China, indicating that there are great differences in research hotspots in different countries’ periods and conditions.

Prioritizing sponge city sites in rapidly urbanizing watersheds using multi-criteria decision model

Spatial planning is crucial for sponge city (SC) construction; however, prioritizing SC sites at the watershed scale has not been fully explored. In this study, a multi-criteria decision model, considering demand and suitability of SC construction, was established by monitoring, model simulation, and index calculation. This new model was then tested in a rapidly urbanizing watershed, Beijing, China, and the priority of SC construction at both grid scale (1km×1km) and subwatershed scale was ranked. The results showed that the highest priority was found in emerging regions where urbanization is ongoing and followed by urban core areas. In addition, six indexes were identified by clustering heatmaps as key factors affecting the priority of SC planning, including topographic index, water pollution index, pollution rate based on the state standard of surface water environment quality, urbanization planning, urban levels, and vegetation index, which could guide SC planning in data-lacking regions. The approach and findings in this study cannot only provide helpful references for watershed managers and urban planners but also can be easily used in other regions.

Investigating the influence of three-dimensional building configuration on urban pluvial flooding using random forest algorithm

Urban pluvial flooding has emerged as a serious threat to environmental conditions and human lives. Identifying its key drivers is crucial for the mitigation of flood risks. Although previous studies have demonstrated that pluvial flooding is caused by both natural (e.g., topography) and anthropogenic factors (e.g., land cover condition), much less effort has been devoted to investigating the potential influence of three-dimensional building configuration on pluvial flooding. To shed some light on this topic, we first analyzed the linear relationship between the density of flooding hotspots and different potential drivers in a highly-urbanized city using Pearson correlation analysis. Next, we designed two random forest-based models to quantify the importance of various building metrics. The first model considers only common drivers, while the second one also includes different types of building metrics. Results indicate that the density of buildings, building congestion degree, and building coverage ratio have exerted considerable influence on the occurrence of pluvial flooding. For example, the root relative squared error of our enhanced model (28.36%) is lower than that of the baseline model (32.58%). Our findings are expected to provide practical guidance for the mitigation of pluvial flood risks from the perspective of three-dimensional urban planning. Moreover, this methodological framework can be further applied to the analysis of flooding in many other regions.

Understanding dynamics of population flood exposure in Canada with multiple high-resolution population datasets

In recent years, geospatial data (e.g. remote sensing imagery), and other relevant ancillary datasets (e.g. land use land cover, climate conditions) have been utilized through sophisticated algorithms to produce global population datasets. With a handful of such datasets, their performances and skill in flood exposure assessment have not been explored. This study proposes a comprehensive framework to understand the dynamics and differences in population flood exposure over Canada by employing four global population datasets alongside the census data from Statistics Canada as the reference. The flood exposure is quantified based on a set of floodplain maps (for 2015, 1 in 100-yr and 1 in 200-yr event) for Canada derived from the CaMa-Flood global flood model. To obtain further insights at the regional level, the methodology is implemented over six flood-prone River Basins in Canada. We find that about 9% (3.31 million) and 11% (3.90 million) of the Canadian population resides within 1 in 100-yr and 1 in 200-yr floodplains. We notice an excellent performance of WorldPop, and LandScan in most of the cases, which is unaffected by the representation of flood hazard, while Global Human Settlement and Gridded Population of the World showed large deviations. At last, we determined the long-term dynamics of population flood exposure and vulnerability from 2006 to 2019. Through this analysis, we also identify the regions that contain a significantly larger population exposed to floods. The relevant conclusions derived from the study highlight the need for careful selection of population datasets for preventing further amplification of uncertainties in flood risk. We recommend a detailed assessment of the severely exposed regions by including precise ground-level information. The results derived from this study may be useful not only for flood risk management but also contribute to understanding other disaster impacts on human-environment interrelationships.

Predicting Future Urban Flood Risk Using Land Change and Hydraulic Modeling in a River Watershed in the Central Province of Vietnam

Flood risk is a significant challenge for sustainable spatial planning, particularly concerning climate change and urbanization. Phrasing suitable land planning strategies requires assessing future flood risk and predicting the impact of urban sprawl. This study aims to develop an innovative approach combining land use change and hydraulic models to explore future urban flood risk, aiming to reduce it under different vulnerability and exposure scenarios. SPOT-3 and Sentinel-2 images were processed and classified to create land cover maps for 1995 and 2019, and these were used to predict the 2040 land cover using the Land Change Modeler Module of Terrset. Flood risk was computed by combining hazard, exposure, and vulnerability using hydrodynamic modeling and the Analytic Hierarchy Process method. We have compared flood risk in 1995, 2019, and 2040. Although flood risk increases with urbanization, population density, and the number of hospitals in the flood plain, especially in the coastal region, the area exposed to high and very high risks decreases due to a reduction in poverty rate. This study can provide a theoretical framework supporting climate change related to risk assessment in other metropolitan regions. Methodologically, it underlines the importance of using satellite imagery and the continuity of data in the planning-related decision-making process.

Integrated Methodology for Urban Flood Risk Mapping at the Microscale in Ungauged Regions: A Case Study of Hurghada, Egypt

Flood risk mapping forms the basis for disaster risk management and the associated decision-making systems. The effectiveness of this process is highly dependent on the quality of the input data of both hazard and vulnerability maps and the method utilized. On the one hand, for higher-quality hazard maps, the use of 2D models is generally suggested. However, in ungauged regions, such usage becomes a difficult task, especially at the microscale. On the other hand, vulnerability mapping at the microscale suffers limitations as a result of the failure to consider vulnerability components, the low spatial resolution of the input data, and the omission of urban planning aspects that have crucial impacts on the resulting quality. This paper aims to enhance the quality of both hazard and vulnerability maps at the urban microscale in ungauged regions. The proposed methodology integrates remote sensing data and high-quality city strategic plans (CSPs) using geographic information systems (GISs), a 2D rainfall-runoff-inundation (RRI) simulation model, and multicriteria decision-making analysis (MCDA, i.e., the analytic hierarchy process (AHP)). This method was implemented in Hurghada, Egypt, which from 1996 to 2019 was prone to several urban flood events. Current and future physical, social, and economic vulnerability maps were produced based on seven indicators (land use, building height, building conditions, building materials, total population, population density, and land value). The total vulnerability maps were combined with the hazard maps based on the Kron equation for three different return periods (REPs) 50, 10, and 5 years to create the corresponding flood risk maps. In general, this integrated methodology proved to be an economical tool to overcome the scarcity of data, to fill the gap between urban planning and flood risk management (FRM), and to produce comprehensive and high-quality flood risk maps that aid decision-making systems.

Scenario-based flood risk assessment for urbanizing deltas using future land-use simulation (FLUS): Guangzhou Metropolitan Area as a case study

Preparing cities for sea-level rise is one of the critical challenges of the twenty-first century. Extreme weather events, natural hazards, and the failure of climate mitigation and adaptation are substantial risks. These risks are especially significant in fast-urbanizing deltas, such as the Pearl River Delta in China, because the conflict between urbanization and flooding caused by climate change will be more significant in the future. This paper elaborates on an approach that employs a future land-use simulation (FLUS) model for scenario-based 100-year coastal flood risk assessment. Storylines of future scenarios from the Intergovernmental Panel on Climate Change (IPCC), called the representative concentration pathways (RCPs) 2.6 and 8.5, are utilized in the present study. The Guangzhou Metropolitan Area (GMA) is used as a case study to explore the probable implications of future land-use changes due to the ongoing urbanization process in the region in relation to projected environmental changes (sea-level rise, storm surge, and land subsidence). The results indicate that there will be a significant increase in flooded urban areas in the future. The simulations show that, as compared to 2015, the built-up area in the GMA will increase by 246.57 km² in 2030 and 513.03 km² in 2050. As compared to 2015, the flooding of built-up areas in 2030 and 2050 will respectively increase by about 31.32 km² and 48.49 km² under the RCP 8.5 scenario. It is also found that, as the main driving factor, urbanization will increase the flooding of built-up areas in Guangzhou in 2030 and 2050 by about 1.9 km² and 5.9 km², respectively, under the RCP 2.6 scenario as compared to 2015. Additionally, due to environmental changes, the flooding of built-up areas in Guangzhou will increase by about 24.2 km² and 26.8 km², respectively, under the RCP 8.5 scenario by 2030 and 2050 as compared to 2015. This increasing flood risk information determined by the simulation provides insight into the spatial distribution of future flood-prone urban areas to facilitate the development and prioritization of flood mitigation measures at the most critical locations in the region.

The spatial non-stationary effect of urban landscape pattern on urban waterlogging: a case study of Shenzhen City

The problem of urban waterlogging has consistently affected areas of southern China, and has generated widespread concerns among the public and professionals. The geographically weighted regression model (GWR) is widely used to reflect the spatial non-stationarity of parameters in different locations, with the relationship between variables able to change with spatial position. In this research, Shenzhen City, which has a serious waterlogging problem, was used as a case study. Several key results were obtained. (1) The spatial autocorrelation of flood spot density in Shenzhen was significant at the 5% level, but because the Z value was not large it was not very obvious. (2) The degree of impact on flood disasters from large to small was: Built up_ DIVISION > SHDI > Built up_ COHESION > CONTAG > Built up_ LPI. (3) The degree of waterlogging disasters in higher altitude regions was less affected by the landscape pattern. The results of this study highlight the important role of the landscape pattern on waterlogging disasters and also indicate the different impacts of different regional landscape patterns on waterlogging disasters, which provides useful information for planning the landscape pattern and controlling waterlogging.

Possibilities of Controlling the River Outlets by Weirs on the Example of Noteć Bystra River

The possibility of effective control of selected dams in the Noteć Bystra river is analyzed. Such a control is expected to permit inundation of selected arable areas, e.g., peat grasslands, to avoid flooding of the city of Czarnków and the terrains located downstream. The chosen case study is the reach of the Noteć River between the dams Pianowka–Mikolajewo–Rosko. The analysis was made on the basis of simulations of the flow and regulation of dams in flood conditions. The flow peaks of hypothetical flood waves were designed according to the directions of the ISOK project (Informatyczny System Osłony Kraju przed nadzwyczajnymi zagrożeniami—IT System of the Country’s Protection Against Extreme Hazards) as the maximum flows over 10-years (p = 10%), 100-years (p = 1%), and 500-years (p = 0.2%). The obtained results are presented as longitudinal profiles of the water surface, maps of inundated areas and maps of inundated soils. The main conclusion is that the robust control of dams reduces the peak of flow during flood wave propagation and forces inundation of the a priori selected areas. It helps to decrease the spatial range of the flood hazard and significantly reduces risk related to floods.

Social Vulnerability Assessment for Flood Risk Analysis

This paper proposes a methodology for the analysis of social vulnerability to floods based on the integration and weighting of a range of exposure and resistance (coping capacity) indicators. It focuses on the selection and characteristics of each proposed indicator and the integration procedure based on the analytic hierarchy process (AHP) on a large scale. The majority of data used for the calculation of the indicators comes from open public data sources, which allows the replicability of the method in any area where the same data are available. To demonstrate the feasibility of the method, a study case is presented. The flood social vulnerability assessment focuses on the municipality of Ponferrada (Spain), a medium-sized town that has high exposure to floods due to potential breakage of the dam located upstream. A detailed mapping of the social vulnerability index is generated at the urban parcel scale, which shows an affected population of 34,941 inhabitants. The capability of working with such detailed units of analysis for an entire medium-sized town provides a valuable tool to support flood risk planning and management.

A new bivariate risk classifier for flood management considering hazard and socio-economic dimensions

Identification of flood-risk dynamics is pivotal for refurbishing the existing and future flood-management options. The present study quantifies the marginal and compound contributions of hazard and vulnerability to flood-risk through an innovative concept of Risk-classifier, designed in the form of a 5 × 5 choropleth. The proposed framework is demonstrated at the finest administrative scale of village-level over Jagatsinghpur district in Mahanadi River basin, Odisha (India) for two-time frames: Scenario-I (1970-2011) and Scenario-II (1970-2001). An increase in high and very high hazard and vulnerable villages is noticed in Scenario-I, the majority of them lying in the coastal stretches (S-E region) and adjoining flood plains of Mahanadi River (N-W region). Scenario-I is characterized by the majority of hazard-driven and compound (both hazard and vulnerability) risk villages, while Scenario II is characterized by a majority of vulnerability driven-risk villages. For the vulnerability-driven risk villages, rigorous enforcement of policies and mitigation schemes are recommended, while for hazard-driven risk villages, enhancement of structural measures and flood-plain zoning should be exercised. Such exhaustive flood-risk information may serve as a valuable cartographic product for the civic authorities and stakeholders and help in prioritizing flood mitigation actions for improved environmental planning and management.

Evaluation of Selected Sub-Elements of Spatial Data Quality on 3D Flood Event Modeling: Case Study of Prešov City, Slovakia

Weather-related disasters represent a major threat to the sustainable development of society. This study focuses directly on the assessment of the state of spatial information quality for the needs of hydrodynamic modeling. Based on the selected procedures and methods designed for the collection and processing of spatial information, the aim of this study was to assess their qualitative level of suitability for 3D flood event modeling in accordance with the Infrastructure for Spatial Information in the European Community (INSPIRE) Directive. In the evaluation process we entered geodetic measurements and the digital relief model 3.5 (DMR 3.5) available for the territory of the Slovak Republic. The result of this study is an assessment of the qualitative analysis on three levels: (i) main channel and surrounding topography data from geodetic measurements; (ii) digital relief model; and (iii) hydrodynamic/hydraulic modeling. The qualitative aspect of the input data shows the sensitivity of a given model to changes in the input data quality condition. The average spatial error in the determination of a point’s position was calculated as 0.017 m of all measured points along a watercourse and its slope foot and slope edge. Although the declared accuracy of DMR 3.5 is assumed to be ±2.50 m, in some of the sections in the selected area there were differences in elevation up to 4.79 m. For this reason, we needed a combination of DMR 3.5 and geodetic measurements to refine the input model for the process of hydrodynamic modeling. The quality of the hydrological data for the monitored N annual flow levels was of fourth-class reliability for the selected area.

The growth mode of built-up land in floodplains and its impacts on flood vulnerability

Built-up land in floodplains (BLF) is a vital indicator of the socio-hydrological system, and its dynamics are key to understanding and managing flood risk. However, previous studies have neglected the impacts of BLF growth modes (e.g., patch sizes and expansion types) on flood vulnerability. This paper fills this gap by assessing the BLF's growth modes and revealing their divergent impacts on flood vulnerability using a case study in the Yangtze River Economic Belt (YREB), China. The results show that the BLF has nearly doubled in the YREB during 1990-2014. A considerable proportion (35.43%) of the BLF growth is scattered in small patches (≤1 km²), which have a much stronger correlation with flood occurrence than that of the other patch sizes. In terms of expansion types, the edge-expansion type dominates 57.52% of the BLF growth, followed by the leapfrogging and infilling expansions. Both the leapfrogging and the edge-expanding BLFs are significantly associated with flood occurrence, while the infilling type is not. The patch size and expansion type can thus influence the vulnerability of BLF patches, which is also supported by real-world cases. These findings enrich a general understanding of BLF growth and its impacts on flood vulnerability. The scientific community and policymakers should pay attention to not only the quantity of BLF growth, but also its spatial arrangement.

A nonstructural flood prevention measure for mitigating urban inundation impacts along with river flooding effects

In recent decades, urban developments along rivers have experienced high flooding risks, elevated by increasing urbanization. Due to the expansion of urban areas, flood mitigation strategies must rely on nonstructural flood management policies. This study evaluated the impacts of pluvial floods considering fluvial flooding effects through field surveys and numerical model simulations. Nonstructural flood protection measures are provided by establishing warning water levels based on variant scenario simulations. The results reveal that the aggravated drainage system overflow induced by elevated river water is significant when considering river flooding effects. As a result, current drainage systems have failed to meet the designed flood protection standards, indicating the need to produce potential inundation maps and to establish warning water levels. To prevent the main evacuation route of each settlement from being blocked due to flooding, the proposed warning water levels support timely and effective evacuations. Public community centers and schools in noninundation areas near settlements were identified as possible shelters based on the proposed warning water levels and inundation maps. We conclude that although the riverside areas without dike protection could sustain natural environments and landscapes, they must incorporate nonstructural flood protection measures. At the same time, it must be considered that river flood levels may reduce urban drainage capacity.

River flooding risk prevention: A cooperative game theory approach

Socio-economic development combined with changing hydrological factors represents a challenge for extending flood protection. In particular, land owners should be encouraged to use their land in a way that improves its water retention capacity. However, problems of fairness may arise because a landowner can benefit or lose out depending on the use of other lands. This paper sets out to study the possibility of applying game theory through a cooperative game to solve this problem. Specifically, we look for a sharing rule function to help the planners to distribute the total benefit among landowners, taking into account a principle of stability. We concentrate on enhancing upstream water retention and focus on the role played by forests as natural water retention features. This is a methodological contribution that analyzes land use management for flood retention. Land planners, governments and landowners could use cooperative games as a flood risk management tool. With this method, compensations and benefits could be established to raise awareness and encourage land owners to cooperate.

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

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.

Using High-Density LiDAR Data and 2D Streamflow Hydraulic Modeling to Improve Urban Flood Hazard Maps: A HEC-RAS Multi-Scenario Approach

The ability to extract streamflow hydraulic settings using geoinformatic techniques, especially in high populated territories like urban and peri-urban areas, is an important aspect of any disaster management plan and flood mitigation effort. 1D and 2D hydraulic models, generated based on DEMs with high accuracy (e.g., Light Detection and Ranging (LiDAR)) and processed in geographic information systems (GIS) modeling software (e.g., HEC-RAS), can improve urban flood hazard maps. In this study, we present a small-scale conceptual approach using HEC-RAS multi-scenario methodology based on remote sensing (RS), LiDAR data, and 2D hydraulic modeling for the urban and peri-urban area of Bacău City (Bistriţa River, NE Romania). In order to test the flood mitigation capacity of Bacău 1 reservoir (rB1) and Bacău 2 reservoir (rB2), four 2D streamflow hydraulic scenarios (s1–s4) based on average discharge and calculated discharge (s1–s4) data for rB1 spillway gate (Sw1) and for its hydro-power plant (H-pp) were computed. Compared with the large-scale flood hazard data provided by regional authorities, the 2D HEC-RAS multi-scenario provided a more realistic perspective about the possible flood threats in the study area and has shown to be a valuable asset in the improvement process of the official flood hazard maps.

Experimental study for effects of terrain features and rainfall intensity on infiltration rate of modelled permeable pavement

In order to investigate the effects of the terrain slopes and rainfall intensity on the steady infiltration rate of permeable pavement, an experiment with the combinations of three types of permeability, three kinds of rainfall intensity, different cross slope and longitudinal slope are undertaken. Through analyzing the experimental data, it is indicated that: (1) the relation between the steady infiltration rate and the cross and longitudinal slopes can be described by power functions, i.e. as the slopes increase, the steady infiltration rate decreases. The steady infiltration rate can be reduced by 23.3%-72.2% and 12.6%-22.2% for the slopes ranging from 0° to 5° and from 5° to 10°, respectively, illustrating the infiltration is more sensitive to the 0°-5° slope; (2) Under the same conditions, the effect of the cross slope on the steady infiltration rate is about 1.1-1.4 times as high as that of the longitudinal slope, i.e. the cross slope varying could lead to more obvious infiltration change, comparing to the longitudinal slope; (3) The relation between the rainfall intensity and the infiltration rate can be reflected by power function as well. The higher the rainfall intensity, the more the steady infiltration rate increases; (4) The comprehensive effect of the cross slope, longitudinal slope and rainfall intensity on steady infiltration rate can be expressed by quadratic polynomial functions. The main purpose of the manuscript is to determine how the slopes and the rainfall intensities affect the infiltration process and guide the plan and design of the permeable pavement in practical engineering.

Drivers of changing urban flood risk: A framework for action

This study focuses on drivers for changing urban flood risk. We suggest a framework for guiding climate change adaptation action concerning flood risk and manageability in cities. The identified key drivers of changing flood hazard and vulnerability are used to provide an overview of each driver's impact on flood risk and manageability at the city level. We find that identified drivers for urban flood risk can be grouped in three different priority areas with different time horizon. The first group has high impact but is manageable at city level. Typical drivers in this group are related to the physical environment such as decreasing permeability and unresponsive engineering. The second group of drivers is represented by public awareness and individual willingness to participate and urbanization and urban sprawl. These drivers may be important and are manageable for the cities and they involve both short-term and long-term measures. The third group of drivers is related to policy and long-term changes. This group is represented by economic growth and increasing values at risk, climate change, and increasing complexity of society. They have all high impact but low manageability. Managing these drivers needs to be done in a longer time perspective, e.g., by developing long-term policies and exchange of ideas.

Flood Risk Evaluation in Urban Spaces: The Study Case of Tormes River (Salamanca, Spain)

The expansion of cities towards flood zones, and the increasingly frequent episodes of torrential rains arising from global warming, mean that the population is becoming more exposed to floods. Due to this, a correct assessment of flood events is of great help in the development of preventive actions, planning and resource management, or interventions. For this reason, in this work we aim to establish guidelines to assess the hazard, exposure, and vulnerability of the population and its properties to flood events, using Hec-Ras for the simulation of the flood and ArcGis and GeoHecRas to treat geographic information and prepare the cartography. The study was focused on the Tormes River in Salamanca (Spain). We studied three return periods with different probabilities of occurrence and intensity, corresponding to 5, 100, and 500 years. The flow corresponding to each episode was calculated, along with the extension, speed, and depth that would be achieved in each case. Then, the probability of occurrence was delimited, as well as the magnitude, allowing us to obtain different hazard maps. In addition, the areas of greatest hazard to people and property were established for each event. Regarding the exposure, the areas and land use, infrastructure, and buildings that would be flooded in each case were identified, quantifying the extension or length of the affected properties at the different levels of hazard in each case. Additionally, the vulnerability of the different buildings and exposed infrastructure was studied. Finally, the flood risk was estimated by combining these three components.