Flood Assessment Research Articles

Flash flood (Δ) risk and damage assessment in batu, East Java

Hydrometeorological disasters are showing an increasing trend in Indonesia. Flash floods are part of a hydrometeorological disaster that has a significant livelihood impact. Flash Flood is triggered by the intensity of extreme rain, several actions of mitigation can be taken by early warning systems, hazard and risk mapping, community preparedness, and climate change adaptation. So, how does future land use have an impact, and how much loss will result from the flash flood disaster in Batu City? The hydrometeorological disaster that occurred in Indonesia was the Batu Flash Flood. The Flash Flood occurred on November 4, 2021. The flash flood has a lot of impact on many locations, including the Bumiaji District and Junrejo District. Based on the disaster history recorded, the flash flood in Batu has only happened once, but the impact was quite big because there are many houses in the midstream of Bulukerto. Based on the losses caused, this can be the basis for efforts to control the spatial pattern of Batu City in the future. The methodology used in this study is risk assessment. While the risk study related to delta (Δ) the study of flash floods risk in spatiotemporal prevention uses the 2030 spatial plan for delta prediction (Δ), which can later predict the consequences of climate change and meteorological disasters from flash floods in Batu. The results of this study are the delta (Δ) of flash flood risk and the damage assessment of the flash flood that occurred in Batu.

Flood risk assessment by using an interpretative structural modeling based Bayesian network approach (ISM-BN): An urban-level analysis of Shenzhen, China

With increasingly uncertain environmental conditions under global change, it is rather important for water security management to evaluate the flood risk, which is influenced by the compound effect of severe weather events and strong anthropogenic activities. In this paper, a risk assessment model in the framework of Bayesian network (BN) was proposed through incorporating with the Interpretative Structural Modeling method (ISM), which would produce an integrated ISM-BN model for reliable flood assessments. The ISM is employed to identify the relations among multiple risk factors, and then helps to configure the BN structure to conduct a risk inference. The established model was further demonstrated in Shenzhen city of China to perform an urban-level risk analysis of the flood disaster, and the Enhanced Water Index (EWI) was introduced to derive model parameters for training and verification. The obtained results of risk assessment lead to an accuracy of 76% with the Area Under ROC Curve (AUC) of 0.82, and spatial distribution of risk levels also showed a satisfactory performance. In addition, it was found that the maximum daily rainfall among ten risk factors play a key part in flood occurrence, while the elevation and storm frequency are also sensitive indicators for the study area. Besides, the spatial flood risk map generated under various design rainfall scenarios would contribute to identifying potential areas that are worth paying particular attention. Thus, the developed assessment model would be a useful tool for supporting flood risk governance to achieve reliable urban water security.

Flood hazards and risk prediction by using the Analytical Hierarchy Process on GIS platform: a case study in lower Ajay basin, India

Flood is the most common and natural disaster of the world. Fluvial flood basically occurred by the combination of hydro-geomorphological effect. But during the flood risk assessment, geomorphological condition analysis is ignored. Present research aimed to focus on flood assessment in the lower part of the Ajay river basin on the basis of present hydro-geomorphological conditions. Flood character analysis on the basis of present hydro-geomorphological status of the river also helps in the management strategy formulation. Remote sensing data, traditional topographical sheet and field work reach the present status of the river. Different layers of hydrological and geomorphological parameters are prepared in the Geographic Information System (GIS) field as per objective. By using the Analytical Hierarchy Process (AHP), a decision based on comparison matrix, weighted score is extracted and in the field of GIS, the flood area is predicted. According to the categories of hazards, the extracted flood area is classified into three zones. Result depicts that 5 blocks lie in the high hazards prone area and 5 blocks are moderate. Hazards prone and validation prove that the model is 87 % correct in case of overall accuracy assessment and 81 % correct in case of Kappa statistics. Both the results of validation prove the suitability of the model.

Coastal Flooding Assessment Induced by Barometric Pressure, Wind-Generated Waves and Tidal-Induced Oscillations: Kaštela Bay Real-Time Early Warning System Mobile Application

Our work presents a reliable procedure to obtain real-time assessment of the sea water elevation at the Kaštela Bay site to ensure the a priori warning in the case of expected coastal flooding along the site area. In its origin, the presented procedure relies on relevant data sets which are site-specific and locally observed. Observed data sets are used within the procedure to assess sea water surface elevation when induced by barometric pressure changes and wind-generated waves. Tidal-induced changes are introduced into the assessment procedure by a pre-learned algorithm which relies on long-term sea level oscillations from the relevant tidal gauge. Wind-generated wave heights are determined in the near shore area, following the features of the depth and reflection of the shoreline subsections. By coupling three mechanisms, this paper offers a unique real-time procedure to determine the sea water elevation and assess the possibility for coastline structure to be flooded by the sea. Given information is visualized in a form of mobile application that implements the algorithm and allows end users to set the notifications based on the given ruleset.

Influencing Factors and Risk Assessment of Precipitation-Induced Flooding in Zhengzhou, China, Based on Random Forest and XGBoost Algorithms

Due to extreme weather phenomena, precipitation-induced flooding has become a frequent, widespread, and destructive natural disaster. Risk assessments of flooding have thus become a popular area of research. In this study, we studied the severe precipitation-induced flooding that occurred in Zhengzhou, Henan Province, China, in July 2021. We identified 16 basic indicators, and the random forest algorithm was used to determine the contribution of each indicator to the Zhengzhou flood. We then optimised the selected indicators and introduced the XGBoost algorithm to construct a risk index assessment model of precipitation-induced flooding. Our results identified four primary indicators for precipitation-induced flooding in the study area: total rainfall for three consecutive days, extreme daily rainfall, vegetation cover, and the river system. The Zhengzhou storm and flood risk evaluation model was constructed from 12 indicators: elevation, slope, water system index, extreme daily rainfall, total rainfall for three consecutive days, night-time light brightness, land-use type, proportion of arable land area, gross regional product, proportion of elderly population, vegetation cover, and medical rescue capacity. After streamlining the bottom four indicators in terms of contribution rate, it had the best performance, with an accuracy rate reaching 91.3%. Very high-risk and high-risk areas accounted for 11.46% and 27.50% of the total area of Zhengzhou, respectively, and their distribution was more significantly influenced by the extent of heavy rainfall, direction of river systems, and land types; the medium-risk area was the largest, accounting for 33.96% of the total area; the second-lowest-risk and low-risk areas together accounted for 27.09%. The areas with the highest risk of heavy rainfall and flooding in Zhengzhou were in the Erqi, Guanchenghui, Jinshui, Zhongyuan, and Huizi Districts and the western part of Xinmi City; these areas should be given priority attention during disaster monitoring and early warning and risk prevention and control.

Participatory risk assessment of pluvial floods in four towns of Niger

Intense rainfalls in Sub-Saharan Africa are increasing in frequency. Land degradation, watercourses siltation, and flood defence failure turn these events into disastrous floods. Over the last decade flood risk assessments have been prepared to face these disasters. However, they have frequent limitations in design, accuracy, and completeness. The objectives of this study are (i) to integrate local and scientific knowledge into a participated pluvial flood risk assessment (ii) to identify assets and (iii) to estimate the potential impact and efficiency of risk-reduction measures. The assessment is developed in four rapidly expanding towns of Niger, flooded several times in recent years. Flood-prone areas and assets are identified according four flood scenarios using local knowledge, 2D hydraulic modelling, and visual photointerpretation of very-high-resolution satellite images. Risk-reduction measures are singled-out through public participation. The residual risk and benefit/cost analyses provide a decision-making tool to accept or treat risk. During the last decade the expansion of the four towns has been more rapid in flood-prone zones than in safe areas. Nowadays more than half of the housing stock could be flooded by rainfalls with 20 years return period. Catchment treatment and building retrofitting can reduce risk. from 100 to 29–82. Nevertheless, the benefit/cost of risk reduction is high for towns settled in small catchments only.

Flash flood assessment at Upper Cisadane Watershed using land use/land cover and morphometric factors

The regions of upstream Cisadane watershed tend to gain more flash flood cases and reduce the water catchment due to encroachment of settlement areas. Researches on flash flood disaster and land use/land cover change are important to reduce the impact of flash flood disaster to the community and environment. This study aims to: 1). Determine morphometric characteristics and land use/land cover changes and 2). Prioritize sub-watersheds for flash flood disaster management. Land Use Land Cover (LULC) and morphometry parameters were used to prioritize the sub-watersheds as a basis for flash flood disaster mitigation in the research sites. The land use data from three different periods (2011, 2015, and 2020) were modelled to understand the land use change in the research sites. Morphometric characteristics were quantitatively analysed over three aspects including linear, relief, and shape aspects over seven sub-watersheds. Morphometric parameter was considered as an important parameter in order to understand the capacity and hydrology condition at a particular watershed towards precipitation rate. According to the land use change analysis gained from 2011 to 2020, the trend of land use change was dominated by settlement area and cultivated land. These areas tend to grow in 2015 and 2020. The integration results of LULC 2020 and morphometric analysis revealed that the Sub Basin 1 (SB 1) sub-watershed was the top most priority for flash flood mitigation planning, followed by SB 7, SB 3, SB 5, SB 4, SB 2, and SB 6.

Hazard assessment and prediction of ice-jam flooding for a river regulated by reservoirs using an integrated probabilistic modelling approach

To effectively alleviate ice-jam flood disasters, it is necessary to carry out hazard assessments and predictions of ice-jam flooding influenced by the operational scheme of a reservoir. However, traditional hydrologic flood routing techniques cannot effectively address the huge uncertainties caused by the many factors that lead to ice-jam flooding. In this paper, a hazard assessment system for regulating flood discharge schemes is developed; it is composed of a machine learning (ML) model, Long Short-Term Memory (LSTM), and a river-ice dynamic model (RIVICE) within a probabilistic method. The modelling system is to aid in the challenge of predicting ice-jam flooding downstream of reservoirs. The LSTM model forecasts the downstream flow under the operational discharge scheme and, combined with the RIVICE model, the backwater level profile of ice jams can be forecasted. Furthermore, a set of backwater level profiles can be provided by probabilistic modelling, and the probability of ice-jam flood inundation can be calculated by comparing backwater levels with the elevation of the river bank; this information can be used to warn of the hazard induced by operational discharges to better aid in the preparedness and mitigation of ice-jam floods. This system was tested successfully for the ice-cover breakup period in the spring of 2008 and 2018 along the Sanhuhekou bend reach of the Yellow River in China.

Susceptibility Assessment of Flash Floods: A Bibliometrics Analysis and Review

A flash flood disaster is one of the most destructive natural disasters. With the increase in extreme rainfall events, more and more areas will be threatened by flash floods. The flash flood susceptibility assessment is the basis of flash flood risk assessment and is also an important step in flash flood disaster management. Based on Citespace analysis tools, this study made a bibliometric and visualized analysis of 305 documents collected in the core collection of Web of Science in the past 15 years, including the analysis of the number of publications and citation frequency, influence analysis, keyword analysis, author co-citation analysis, and institutional co-operation analysis. This paper summarizes the current research status and future development trend of flash flood susceptibility assessment from five key research subfields, including assessment scale, assessment unit, assessment index, assessment model, and model assessment method, discusses the analysis of the application of remote sensing and GIS in flash flood susceptibility assessment, discusses the problems encountered in the current research of the five subfields, and provides suggestions for flash flood hazard control.

Partitioning the contributions of dependent offshore forcing conditions in the probabilistic assessment of future coastal flooding

Abstract. Getting a deep insight into the role of coastal flooding drivers is of great interest for the planning of adaptation strategies for future climate conditions. Using global sensitivity analysis, we aim to measure the contributions of the offshore forcing conditions (wave–wind characteristics, still water level and sea level rise (SLR) projected up to 2200) to the occurrence of a flooding event at Gâvres town on the French Atlantic coast in a macrotidal environment. This procedure faces, however, two major difficulties, namely (1) the high computational time costs of the hydrodynamic numerical simulations and (2) the statistical dependence between the forcing conditions. By applying a Monte Carlo-based approach combined with multivariate extreme value analysis, our study proposes a procedure to overcome both difficulties by calculating sensitivity measures dedicated to dependent input variables (named Shapley effects) using Gaussian process (GP) metamodels. On this basis, our results show the increasing influence of SLR over time and a small-to-moderate contribution of wave–wind characteristics or even negligible importance in the very long term (beyond 2100). These results were discussed in relation to our modelling choices, in particular the climate change scenario, as well as the uncertainties of the estimation procedure (Monte Carlo sampling and GP error).

Risk Assessment and Impact of Floods on the Transmission of Vector Borne Diseases

Floods are the result of natural disasters in an area due to prolonged continued and heavy rains and are frequently followed by a proliferation of mosquitoes due to the creation of a large number of breeding habitats. In the endemic zones for VBDs, vector mosquito species require special attention for planning immediate control measures as these areas may pose a threat to public health. Natural disasters continue to strike unabated, flash floods due to heavy rains, riverine floods,coastal floods and cloud burst floods. In general, floods are witnessed due to the concentrated spells of heavy rains during the monsoon months and seasonal disturbances. The low lying areas are submerged under water and remain water logged for a long duration. Slowly, the low lying water bodies thus created after receding of flood water, act as a breeding potential source for the vector mosquitoes. Some of the areas receive water from flushing of water from high altitude areas due to heavy rains or melting of ice. There is definite need for public health preparedness and response for the flood affected areas to reduce the transmission of VBDs with proper risk assessment. There are chances for the onset of transmission of VBDs to the population shifted to temporary shelter homes away from homes. Given the situation with the presence of congenial conditions owing to presence of favourable climatic variables for propagation of vectors, pathogens and susceptible population, there are chances of disease outbreaks. Therefore, the risk assessment of the flood affected area with the vulnerable population is essential to make preparedness and response to any onset of VBDs transmission. Disease and vector surveillance are the key elements to be in place for such flood affected areas during and after the floods.

Impact of Spatial Variation and Uncertainty of Rainfall Intensity on Urban Flooding Assessment

Impact of Spatial Variation and Uncertainty of Rainfall Intensity on Urban Flooding Assessment

A single interface for rainfall-runoff simulation and flood assessment—a case of new capability of HEC-RAS for flood assessment and management

A single interface for rainfall-runoff simulation and flood assessment—a case of new capability of HEC-RAS for flood assessment and management

Dynamic probabilistic risk assessment of seismic-induced flooding in pressurized water reactor by seismic, flooding, and thermal-hydraulics simulations

ABSTRACT Probabilistic risk assessment (PRA) is an essential approach to improving the safety of nuclear power plants. However, this method includes certain difficulties, such as modeling of combinations of multiple hazards. Seismic-induced flooding scenario includes several core damage sequences, i.e. core damage caused by earthquake, flooding, and combination of earthquake and flooding. The flooding fragility is time-dependent as the flooding water propagates from the water source such as a tank to compartments. Therefore, dynamic PRA provides realistic results and insights related to time-dependent accident sequences. This study analyzed the risk of seismic-induced flooding events by coupling seismic, flooding, and thermal-hydraulics simulations, considering the dependency between multiple hazards explicitly. For requirements of safety improvement, especially in light of the Fukushima Daiichi Nuclear Power Plant accident, sensitivity analysis was performed on the seismic fragilities, and the effectiveness of alternative steam generator injection by a portable pump was estimated. We demonstrate the use of this simulation-based dynamic PRA methodology to evaluate the risk induced by a combination of hazards.

Simulation and risk assessment of a possible glacial lake outburst flood (GLOF) in the Bhilangna Valley, central Himalaya, India

Simulation and risk assessment of a possible glacial lake outburst flood (GLOF) in the Bhilangna Valley, central Himalaya, India

Flash Flood Assessment and Management for Sustainable Development Using Geospatial Technology and WMS Models in Abha City, Aseer Region, Saudi Arabia

Abha city is distinguished by urbanization, infrastructure, deepening watercourses, and changes in runoff flow which encourage flash floods in the urban zones of many villages in the region. AlMahalah village is prone to flash flooding due to its geographic location near the outlet of convergence streams of significant flow. The Geographic Information System (GIS), Remote Sensing (RS), Water Modeling System (WMS), and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) were used to assess the effects of flash floods on AlMahala village. Precipitation data from 1978 to 2020 was statistically processed and analysed to provide more information about flash flood hazards. With a 3-h lag time in both watersheds, the higher peak discharge in Wadi Abha than in Wadi Al Akkas indicates that flooding was a primary concern in Wadi Abha. With an average yearly rainfall of 520 mm, the hydrograph simulation from 1 to 5 April 2020 would contribute to the junction (outlet) point of AlMahala village with a peak discharge rate of 474.14 m3/s. The vegetation cover increased by 243 km2 in 2020 compared to 2016. The HEC-RAS model was used to calculate the water depth, velocity, and elevation of the water surface with and without dam installation. The study provides the administration with practical and reasonable procedures for avoiding flash flood destruction in urban areas.

Problems of Local Flooding in Functional Urban Areas in Poland

The research process of developing recommendations for rural communities directly adjacent to metropolitan cities in the field of local flooding protection, especially retention fee was preceded by: analysis of secondary data in 100 communities in three Functional Urban Areas (Metropolitan Areas, MA) in Poland: Poznań MA, Wrocław MA and Łódź MA (assessment of flooding and urbanization), analysis of primary data in 18 rural communities immediately adjacent to the metropolitan centers: semi-structured telephone interviews (stormwater fee from the stakeholder perspective) and survey research (local floodings from the citizen perspectives). To illustrate the scale of the flooding problem in MAs, flood risk maps were used along with data from the State Fire Service on local threats, and for assessing the scale of suburbanization data obtained from Statistics Poland. Although residents confirmed their readiness to co-finance the activities supporting the development of water retention, local authorities were hesitant to introduce additional charges for the residents. Therefore, a better solution would be to set the fees already at the national level. However, communities should be given more power with regards to the distribution of collected funds which, in turn, should be allocated directly to the local programs for the enhancement of retention capacity in the local catchments.

Effectiveness of Sentinel-1 and Sentinel-2 for flood detection assessment in Europe

Abstract. Inundation is one of the major natural hazards in Europe. The evaluation of the flood hazard and risk is not straightforward mainly due to the monitoring system that is poor or not uniformly distributed in the territory. The ESA Earth Observation Program, including a series of satellites, Sentinels, for the operative observation of the natural phenomenon, e.g. the inundations, can potentially reduce the gap. Sentinel-1 (SAR: synthetic aperture radar) and Sentinel-2 (optical) have been demonstrated to be suitable for mapping flooded areas, but despite the medium–high spatial and temporal resolution of the sensors, the mapping of inundated territories is often partial or missing. The objective of this study is to evaluate through a synthetic study the effectiveness of Sentinel-1 and Sentinel-2 in the systematic assessment of floods in Europe, where the flood events have durations ranging from some hours to a few days. To reach the target, we analysed 10 years of river discharge data over almost 2000 sites in Europe, and we extracted flood events over some established thresholds as proxies of riverine inundations. Based on the revisit time of the satellite constellations and cloud coverage, we derived the percentage of potential inundation events that Sentinel-1 and Sentinel-2 could be able to observe. Results show that assuming the configuration of a constellation of two satellites for each mission and considering the ascending and descending orbit, on average 58 % of flood events are potentially observable by Sentinel-1 and only 28 % by Sentinel-2 due to the cloud coverage.

Flood assessment after Cempaka Cyclone 2019 in Imogiri District, Bantul Regency of Yogyakarta, Indonesia

Imogiri District is one of the areas located at the foot of the southern mountains, with many rivers crossing the area. The Cempaka Cyclone in March 2019 caused a big flood in the Imogiri district and its surrounding area. Flood may affect various sectors of the socioeconomics life of a society, such as sectors of the economy, and agriculture, especially a severe effect on environmental and surface/groundwater systems in areas. The research objective is to assess flood hazards and their impact in the Imogiri District, Bantul Regency, Yogyakarta Special Region. The research was conducted by field survey and interview with an impacted community from the flood. The outcome of this study revealed that the area with high flood-prone potentials is distributed in the eastern and central part of the study area, along the river flood zone. The flood disaster caused property and agricultural losses but did not cause any casualties. The community was unprepared for the flood disaster, which had not occurred as big as in 2017.

Urban Flood Resilience Assessment Based on VIKOR-GRA: A Case Study in Chongqing, China

Flooding has been considered as one of the major challenges of urban hazards resilience assessment. Improving urban flood risk resilience has become a critical issue for city management. However, urban flood assessment models on the resilience perspective are rare. Meanwhile, in the perspective of resilience, the existing studies using the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) assessment method for disaster assessment lack consideration of evaluation scenarios located in the midpoint of positive and negative ideal solutions. To address these issues, this study establishes an urban flood disaster resilience assessment model, selects indicators according to the TOSE (Technical, Organizational, Social and Economic) framework, ranks cities through the VIKOR-GRA (VlseKriterijumska Optimizacija I Kompromisno Resenje, Grey Relational Analysis) method, and proposes measures to improve urban disaster resilience through the resilience assessment. Chongqing is taken as an example in this study to verify the feasibility and effectiveness of the proposed model, and practical management opinions are presented to improve flood resilience in these cities. Through the analysis of actual cases, it can be seen that the model has good applicability and can better reflect the actual situation. The knowledge of flood resilience assessment methods is of particular value to policy makers, researchers and industry professionals in assessing potential risks and recognizing the importance of flood prevention mechanisms.