Urban flood risk assessment under rapid urbanization in Zhengzhou City,China

With accelerated urbanization and climate change,urban flooding is becoming more and more serious.Flood risk assessment is an important task for flood management,so it is crucial to map the spatial and temporal distribution of flood risk.This paper proposed an urban flood risk assessment method that takes into account the influences of hazard,vulnerability,and exposure,by constructing a multi-index urban flood risk assessment framework based on Geographic Information System(GIS).To determine the weight values of urban flood risk index factors,we used the analytic hierarchy process(AHP).Also,we plotted the temporal and spatial distribution maps of flood risk in Zhengzhou City in 2000,2005,2010,2015,and 2020.The analysis results showed that,the proportion of very high and high flood risk zone in Zhengzhou City was 1.362%,5.270%,4.936%,12.151%,and 24.236%in 2000,2005,2010,2015,and 2020,respectively.It is observed that the area of high flood risk zones in Zhengzhou City showed a trend of increasing and expanding,of which Dengfeng City,Xinzheng City,Xinmi City,and Zhongmu County had the fastest growth rate and the most obvious increase.The flood risk of Zhengzhou City has been expanding with the development of urbanization.The method is adapted to Zhengzhou City and will have good adaptability in other research areas,and its risk assessment results can provide a scientific reference for urban flood management personnel.In the future,the accuracy of flood risk assessment can be further improved by promoting the accuracy of basic data and reasonably determining the weight values of index factors.The risk zoning map can better reflect the risk distribution and provide a scientific basis for early warning of flood prevention and drainage.

Assessing Future Flooding Risk in a Coastal Lagoon Using Hydrogeological Approaches and Analysis of the 2021 Flood Event: A Case Study of Tasi-Tolu Lagoon, Dili, Timor-Leste

This study aims to apply a hydrogeological approaches and analysis of the 2021 flood event of Tasi-Tolu Lagoon to achieve four specific goals. Firstly, the study seeks to determine the natural characteristics of the lagoon, which include factors such as size, depth, water quality, and ecosystem composition. Secondly, the influence of precipitation on the water volume in the lagoon will be examined. This analysis involves assessing historical rainfall patterns in the region, as well as the amount and frequency of precipitation during the 2021 flood event. Thirdly, the hydrogeologic and geologic conditions of the lagoon will be evaluated. This involves examining factors such as the type and structure of the soil and bedrock, the presence of aquifers or other underground water sources, and the movement of water through the surrounding landscape. Finally, the study seeks to assess the risk of future flooding in Tasi-Tolu Lagoon, based on the insights gained from the previous analyses. Overall, this study’s goal is to provide a comprehensive understanding of the hydrogeological factors that contribute to flooding in Tasi-Tolu Lagoon. This knowledge could be used to inform flood mitigation strategies or to improve our ability to predict and respond to future flooding events in the region.

Morphometric Analysis and Flash Floods Assessment for Drainage Basins of the Ras En Naqb Area, South Jordan Using GIS

Morphometric analysis and flash floods assessment were conducted for the watersheds of Ras En Naqb escarpment, south Jordan. The study area comprises of twelve small watersheds occupying the faulted-erosional slopes, and the dip slopes. The drainage network shows that dendritic and sub-dendritic patterns dominated the dip slopes, whereas trellis pattern characterized the faulted-erosional slopes. Stream orders range from fourth to sixth order. The mean bifurcation ratios vary between 4.2 and 5.38 for the dip slope basins, and between 3.5 and 5.0 for the faulted-erosional slope watersheds, indicating a noticeable influence of structural disturbances (i.e., faulting and uplifting), and rejuvenation of drainage networks. All watersheds have short basin lengths, ranging from 23.8 km to 42.2 km for the dip slope basins, and between 15.3 km and 45.4 km for the faulted-erosional slope catchments. This is indicative of high flooding susceptibility associated with heavy rainstorms of short duration. The circularity ratios range from 0.177 to 0.704 which denote that the catchments are moderately circular on the faulted-erosional slopes, and to some extent elongated on the dip slopes. The length of overland flow values ranges from 0.854 to 0.924 for the dip slope catchments, whereas LO values for the faulted-erosional slopes vary from 0.793 to 0.945 denoting steep slopes and shorter paths on both dip slope and faulted-erosional slope watersheds. Values of stream frequency range from 1.509 to 1.692 for the dip slope, and from 1.688 to 2.0 for the faulted-erosional slope catchments. FS values are also indicative of slope steepness, low infiltration rate, and high flooding potential. The watersheds of the dip slopes show lower values of form factor varying from 0.079 to 0.364, indicating elongated shape and suggesting a relatively flat hydrograph peak for longer duration. Similarly, values of Dd are high for catchments on the dip slope basins (1.709 - 1.85) and the faulted-erosional slope watersheds (1.587 - 2.0) indicating highly dissected topography, high surface runoff, low infiltration rate, and consequently high flooding potential. Furthermore, high relief values exist, ranging from 388 m to 714 m for the dip slope basins, and from 421 m to 846 m for the faulted-erosional slope catchments indicting high relief and steep slopes. Morphometric analysis, and flash flood assessment suggest that ten watersheds (83.3%) are categorized under high and intermediate flooding susceptibility, and the faulted-erosional slope catchments are more hazardous in terms of flooding. Thus the protection of Ma’an, El Jafr rural Bedouin settlements, and Amman-Aqaba highway from recurrent flooding is essential to ensure sustainable future development in Ras En Naqb-Ma’an area.

Floodplain Mapping and Risks Assessment of the Orashi River Using Re­mote Sensing and GIS in the Niger Delta Region, Nigeria

Residents along the shoreline of the Orashi River have yearly been dis­placed and recorded loss of lives,farmland,and infrastructures.The Gov­ernment’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures.This research employs Shuttle Radar Topographic Mission and Google Earth imagery in devel­oping a 3D floodplain map using ArcGIS software.The result indicates the drainage system in the study area is dendritic with catchment of 79 subbasins and 76 pour point implying the area is floodplain.Incorporating the 3D slope which reveals that>8 and<8 makes up 1.15%and 98.85%of the study area respectively confirms the area is a floodplain.Aspect indicate west-facing slope are dark blue,3D hillshade indicate yellow is very low area and the high area is pink and also the buffer analysis result reveals wa­terbodies reflecting blue with an estimated area of 1.88 km2,yellow indicate 0.79 km2 of the shoreline,red indicate 0.81 km2 of the minor floodplain and pink contain 0.82 km2 with the length of 32.82 km.The result from google earth image in 2007 indicate absent of settlement,2013 indicate minimal settlement and 2020 indicate major settlement in the study area when cor­related with 3D Floodplain mapping before and during the flood in other to analyze and manage flooding for further purpose and the majority of the area are under seize with flood like in 2020.Therefore,Remote Sensing and GIS techniques are useful for Floodplain mapping,risk analysis for control measures for better flood management.

Comprehensive Evaluation of Flood and Flood in the Yellow River Basin Based on Gray Correlation Analysis

Due to the concentrated rainfall and serious soil erosion in July and August in the Yellow River Basin, the flood discharge is not timely leading to serious floods. Therefore, a reasonable assessment of the flood-affected areas, advance arrangements for the deployment of the Yellow River basin flood disaster prevention and control plays a decisive role. For this purpose, this paper proposes a level assessment method based on the flood which analyzes three factors related to flooding disaster (disaster impact range, social index, and property index) through the gray correlation analysis method, to evaluate the level of flood disaster. Different from the traditional assessment method, which evaluates the nature of flood from the perspective of indicators such as frequency, duration, and magnitude, or indirect factors such as rainfall and soil loss, this paper conducts qualitative calculation of macro-scale indicators from the perspective of post-disaster losses in previous years. This study provides a new way of thinking and method for the classification of the flood disaster, which has certain practical application value under the condition of conforming to its own use.

Research on Flood Control Design Based on Joint Distribution of Flood Levels and Flood Peak Discharges

The return level of the joint distribution of flood levels and flood peak discharges was analyzed by Archimedean Gumbel-Hougaard copula and Kendall distribution functions.Using the annual maximum level(H)and discharge(Q)of flood peak at Boluo Hydrologic Station in the Dongjiang River in last 56 years,the"OR"return period,"AND"return period and Kendall return period of their joint distribution and the most likely design flood value were calculated.The main conclusions of this study can be summarized as follows:the Kendall return period can more accurately reflect the risk rate of the combination of flood elements,relative to"OR"return period and"AND"return period.The design value of univariate flood element based on the current specification can meet the design standard.While the design value calculated according to"OR"return period was on the high side,and the design value calculated by the"AND"return period was on low side.Based on the principle of maximum probability,the calculated design value of Kendall return period under the different combinations of flood peak discharge and water level can provide new options for flood control project safety and risk management.

Flood Hazard Mapping of Lower Indus Basin Using Multi-Criteria Analysis

Flooding has been one of the recurring occurred natural disasters that induce detrimental impacts on humans, property and environment. Frequent floods is a severe issue and a complex natural phenomenon in Pakistan with respect to population affected, environmental degradations, and socio-economic and property damages. The Super Flood, which hit Sindh in 2010, has turned out to be a wakeup call and has underlined the overwhelming challenge of natural calamities, as 2010 flood and the preceding flood in 2011 caused a huge loss to life, property and land use. These floods resulted in disruption of power, telecommunication, and water utilities in many districts of Pakistan, including 22 districts of Sindh. These floods call for risk assessment and hazard mapping of Lower Indus Basin flowing in the Sindh Province as such areas were also inundated in 2010 flood, which were not flooded in the past in this manner. This primary focus of this paper is the use of Multi-criteria Evaluation (MCE) methods in integration with the Geographical Information System (GIS) for the analysis of areas prone to flood. This research demonstrated how GIS tools can be used to produce map of flood vulnerable areas using MCE techniques. Slope, Aspect, Curvature, Soil, and Distance from Drainage, Land use, Precipitation, Flow Direction, and Flow Accumulation are taken as the causative factors for flooding in Lower Indus Basin. Analytical Hierarchy Process-AHP was used for the calculation of weights of all these factors. Finally, a flood hazard Map of Lower Indus Basin was generated which delineates the flood prone areas in the Sindh province along Indus River Basin that could be inundated by potential flooding in future. It is aimed that flood hazard mapping and risk assessment using open source geographic information system can serve as a handy tool for the development of land-use strategies so as to decrease the impact from flooding.

Implementation of Remote Sensing and GIS Techniques to Study the Flash Flood Risk at NEOM Mega-City, Saudi Arabia

Southern Red Sea flooding is common. Assessing flood-prone development risks helps decrease life and property threats. It tries to improve flood awareness and advocate property owner steps to lessen risk. DEMs and topography data were analyzed by RS and GIS. Fifth-through seventh-order rivers were studied. Morphometric analysis assessed the area’s flash flood danger. NEOM has 14 catchments. We determined each catchment’s area, perimeter, maximum length, total stream length, minimum and maximum elevations. It also uses remote sensing. It classifies Landsat 8 photos for land use and cover maps. Image categorization involves high-quality Landsat satellite images and secondary data, plus user experience and knowledge. This study used the wetness index, elevation, slope, stream power index, topographic roughness index, normalized difference vegetation index, sediment transport index, stream order, flow accumulation, and geological formation. Analytic hierarchy considered all earlier criteria (AHP). The geometric consistency index GCI (0.15) and the consistency ratio CR (4.3%) are calculated. The study showed five degrees of flooding risk for Wadi Zawhi and four for Wadi Surr, from very high to very low. 9.16% of Wadi Surr is vulnerable to very high flooding, 50% to high flooding, 40% to low flooding, and 0.3% to very low flooding. Wadi Zawhi’s flood risk is 0.23% high, moderate, low, or extremely low. They’re in Wadi Surr and Wadi Zawhi. Flood mapping helps prepare for emergencies. Flood-prone areas should prioritize resilience.

A framework for a microscale flood damage assessment and visualization for a building using BIM-GIS integration

Flood damage assessment(FDA)is a key component of risk-based method for flood management.In the current FDA approaches,generally the uniqueness of the building is disregarded in the analysis.Therefore,they are unfit for detailed applications in which case-by-case analysis of building damage is an essential requirement.This limitation is compounded by the use of incomplete and often low-quality data inputs about the building and the assumptions and approximations made regarding the geometry and materials of its components.Such shortcomings may result in incomplete and uncertain outcomes.Considering the benefits and increasing use of three-dimensional(3D)urban modeling and Building Information Model in various urban management processes,in this paper,an integrated framework for utilization of detailed 3D building models for the assessment and 3D visualization of flood damage to building according to its distinct behavior against flood is presented.A proof-ofconcept demonstration of the framework in a case study underlined the feasibility of implementation of the framework,which can potentially benefit a variety of users and be used as a complementary approach to the current FDA methods for improving the resilience of the community toward floods and their adverse impacts.

Urban flood inundation and damage assessment based on numerical simulations of design rainstorms with different characteristics

In the context of global climate change and urbanization,urban flooding is an important type of natural disaster that affects urban development,especially in China,which is experiencing rapid urbanization.In the past 10 years,urban flooding events have caused huge disaster losses in Chinese cities.This has resulted in significant negative effects on the urban infrastructure,socioeconomic systems,and urban residents,thus causing widespread concern.Studies have confirmed the change in extreme rainstorms is due to the changing environments in many cities globally.Conducting studies on the impact of these rainstorms with different characteristics for urban flooding is valuable for coping with unfavorable situations.In addition,numerical simulations provide an economical and viable means to perform these studies.This paper presents a numerical model of Xiamen Island in China.Simulations were conducted for 12 design rainstorm events with different return periods,rain patterns,and durations.The results indicate that,in the case of an equal rainfall amount,the rainfall intensity is the key factor that affects the inundated area,depth,and damages.However,the rainfall intensity is not the only determining factor;the rainfall pattern also affects the inundations.In regard to the rainfall pattern,a higher rainfall peak coefficient usually leads to severe urban inundation and damage.As a result,the lag time would be shorter,which may further exacerbate the impact of urban flood disasters.The results of this study provide insights into managing flood risks,developing urban flood prevention strategies,and designing flood prevention measures.

Flood Duration Estimation Based on Multisensor,Multitemporal Remote Sensing:The Sardoba Reservoir Flood

Single-sensor monitoring of flood events at high spatial and temporal resolutions is difficult because of the lack of data owing to instrument defects,cloud contamination,imaging geometry.However,combining multisensor data provides an impressive solution to this problem.In this study,11 synthetic aperture radar(SAR)images and 13 optical images were collected from the Google Earth Engine(GEE)platform during the Sardoba Reservoir flood event to constitute a time series dataset.Threshold-based and indices-based methods were used for SAR and optical data,respectively,to extract the water extent.The final sequential flood water maps were obtained by fusing the results from multisensor time series imagery.Experiments show that,when compare with the Global Surface Water Dynamic(GSWD)dataset,the overall accuracy and Kappa coefficient of the water body extent extracted by our methods range from 98.8%to 99.1%and 0.839 to 0.900,respectively.The flooded extent and area increased sharply to a maximum between May 1 and May 4,and then experienced a sustained decline over time.The flood lasted for more than a month in the lowland areas in the north,indicating that the northern region is severely affected.Land cover changes could be detected using the temporal spectrum analysis,which indicated that detailed temporal information benefiting from the multisensor data is highly important for time series analyses.

白格滑坡再次堵江洪水评估和早期预警

On 10th Oct.and 3rd Nov.2018,two successive landslides occurred in the Jinsha River catchment at Baige Village,Tibet Autonomous Region,China.The landslides blocked the major river and formed the barrier lake,which finally caused the huge flood disaster loss.The hillslope at Baige landslide site has been still deforming after the 2018 slidings,which is likely to fail and block the Jinsha River again in the future.Therefore the investigation of 2018 flood disaster at the Baige landslide is of a great significance to provide a classic case for flood assessment and early warning for the future disaster.The detailed survey revealed that the outstanding inundations induced bank collapse disasters upstream the Baige landslide dams,and the field investigations and hydrological simulation suggested that the downstream of the Baige landslide were seriously flooded due to the two periods of the outburst floods.On these bases,the early warning process of potential outburst floods at the Baige landslide was advised,which contains four stages:Outburst Flood Simulating Stage,Outburst Flood Forecasting Stage,Emergency Plan and Emergency Evacuation Stage.The study offers a conceptual model for the mitigation of landslides and flood disasters in the high-relief mountain-ous region in Tibet.

Leveraging Hazard,Exposure,and Social Vulnerability Data to Assess Flood Risk to Indigenous Communities in Canada

This study integrates novel data on 100-year flood hazard extents,exposure of residential properties,and place-based social vulnerability to comprehensively assess and compare flood risk between Indigenous communities living on 985 reserve lands and other Canadian communities across 3701 census subdivisions.National-scale exposure of residential properties to fluvial,pluvial,and coastal flooding was estimated at the 100-year return period.A social vulnerability index(SVI)was developed and included 49 variables from the national census that represent demographic,social,economic,cultural,and infrastructure/community indicators of vulnerability.Geographic information system-based bivariate choropleth mapping of the composite SVI scores and of flood exposure of residential properties and population was completed to assess the spatial variation of flood risk.We found that about 81%of the 985 Indigenous land reserves had some flood exposure that impacted either population or residential properties.Our analysis indicates that residential property-level flood exposure is similar between non-Indigenous and Indigenous communities,but socioeconomic vulnerability is higher on reserve lands,which confirms that the overall risk of Indigenous communities is higher.Findings suggest the need for more local verification of flood risk in Indigenous communities to address uncertainty in national scale analysis.

Advancing flood susceptibility modeling using stacking ensemble machine learning: A multi-model approach

Flood susceptibility modeling is crucial for rapid flood forecasting, disaster reduction strategies, evacuation planning, and decision-making. Machine learning(ML) models have proven to be effective tools for assessing flood susceptibility. However, most previous studies have focused on individual models or comparative performance, underscoring the unique strengths and weaknesses of each model. In this study, we propose a stacking ensemble learning algorithm that harnesses the strengths of a diverse range of machine learning models. The findings reveal the following:(1) The stacking ensemble learning, using RF-XGBCB-LR model, significantly enhances flood susceptibility simulation.(2) In addition to rainfall,key flood drivers in the study area include NDVI, and impervious surfaces. Over 40% of the study area, primarily in the northeast and southeast, exhibits high flood susceptibility, with higher risks for populations compared to cropland.(3) In the northeast of the study area,heavy precipitation, low terrain, and NDVI values are key indicators contributing to high flood susceptibility, while long-duration precipitation, mountainous topography, and upper reach vegetation are the main drivers in the southeast. This study underscores the effectiveness of ML, particularly ensemble learning, in flood modeling. It identifies vulnerable areas and contributes to improved flood risk management.