Flood Impact Analysis Research Articles

Integration of UH SUH, HEC-RAS, and GIS in Flood Mitigation with Flood Forecasting and Early Warning System for Gilireng Watershed, Indonesia

A flood forecasting and early warning system is critical for rivers that have a large flood potential, one of which is the Gilireng watershed, which floods every year and causes many losses in Wajo Regency, Indonesia. This research also introduces an integration model between UH SUH and HEC-RAS in flood impact analysis, as a reference for flood forecasting and early warning systems in anticipating the timing and occurrence of floods, as well as GIS in the spatial modeling of flood-prone areas. Broadly speaking, this research is divided into four stages, namely, a flood hydrological analysis using UH SUH, flood hydraulic tracing using a 2D HEC-RAS numerical model, the spatial modeling of flood-prone areas using GIS, and the preparation of flood forecasting and early warning systems. The results of the analysis of the flood forecasting and early warning systems obtained the flood travel time and critical time at the observation point, the total time required from the upstream observation point to level 3 at Gilireng Dam for 1 h 35 min, Mamminasae Bridge for 4 h 35 min, and Akkotengeng Bridge for 8 h 40 min. This is enough time for people living in flood-prone areas to evacuate to the 15 recommended evacuation centers.

Enhancing Flood Impact Analysis through the Integration of Landsat and MODIS Imagery

This article explores the efficacy of integrating Landsat and MODIS satellite imagery for comprehensive flood impact analysis. By employing advanced remote sensing technologies and sophisticated data processing techniques, this study offers a methodological framework that enhances the precision and depth of environmental analysis. The core methodology involves the systematic processing of satellite data, including radiometric and geometric corrections, combined with the use of analytical indices such as the Normalized Difference Water Index (NDWI) and the Enhanced Vegetation Index (EVI). These indices play a crucial role in accurately delineating water bodies and assessing the extent of flooding. The approach not only improves the reliability of flood mapping but also contributes to the broader understanding of environmental changes and aids in effective disaster management. Through this study, we demonstrate how strategic data integration can provide valuable insights for policymakers, enhancing responses to environmental crises.

Automated geovisualization of flood disaster impacts in the global South cities with open geospatial data sets and ICEYE SAR flood data

Flooding is a highly destructive natural disaster affecting millions of people annually, causing substantial global economic losses. Especially in the Global South, vulnerable populations with limited resources for flood protection and recovery suffer the most. However, effective flood impact analysis and standardized geospatial data processing and visualization is lacking, hindering effective disaster risk reduction. This study employs Python to develop a standardized, automated analysis and visualization model to address flood impacts after a high magnitude event anywhere in the world by using global geospatial data sets.In order to test its applicability two relevant cases, with different locations and scales, were selected, (Bangkok, Thailand, and Tula de Allende, Mexico). In both cases the automated flood model efficiently processed flood extent and depth data from ICEYE SAR images, added the population estimates from the German Aerospace Center, and key infrastructure elements from OpenStreetMap. The output of the automated process is presented as web-based interactive maps, offering insights into flooding severity and impacts with minimal user input. This quick approach (processing time between 41 s and 10,5 min) facilitates timely responses by first responders, with great potential to aid and improve the efficiency of international humanitarian efforts.By leveraging global high-resolution geospatial data for local-level analysis, this study demonstrates the versatility and time-saving benefits of this automated analysis and visualization. Automated models standardize results, minimizing human errors, and enabling consistent historical flood data comparison. Even though the databases are gathered from trusted sources, additional evaluation of uncertainties of the results with field data should be considered in further development of this tool. Nevertheless, this research highlights the worldwide potential, and especially the Global South, of automated global geospatial analysis to improve disaster impact reduction by enhancing efficient response efforts.

Comprehensive flood vulnerability analysis in urban communities: Iowa case study

Floods are one of the most prevalent types of natural disasters affecting communities worldwide. It is expected to persist with increasing magnitude and frequency as a result of climate change, resulting in both direct and indirect negative consequences. The flood impact assessment is considered as a key component of flood risk management strategies, such as benefit-cost analysis for mitigation planning. This research aims to provide a comprehensive analysis of socio-economic impacts of the 100 and 500-year riverine flood scenarios for major communities in the State of Iowa, United States of America. The analysis includes impact on essential facilities, businesses, vehicles, loss of life, amount of debris transported downstream, and displaced population, using Hazards-United States (HAZUS) and the Hydrologic Engineering Center's Flood Impact Analysis (HEC-FIA) functions along with GIS-based analysis. Also, we have investigated the floodplain vulnerability using the combination of flood depth and velocity. Due to the differences in the topography and the spatial distribution of buildings and infrastructure, and the absence of sufficient flood prevention measures within the study area, our findings illustrate that some communities will suffer significant damage and losses during flooding. This research could aid communities in making more effective decisions regarding damage reduction, prioritizing mitigation actions, and preparing for future flood events.

Comparison of Neighborhood-Scale, Residential Property Flood-Loss Assessment Methodologies

Leading flood loss estimation models include Federal Emergency Management Agency’s (FEMA’s) Hazus, FEMA’s Flood Assessment Structure Tool (FAST), and (U.S.) Hydrologic Engineering Center’s Flood Impact Analysis (HEC-FIA), with each requiring different data input. No research to date has compared the resulting outcomes from such models at a neighborhood scale. This research examines the building and content loss estimates by Hazus Level 2, FAST, and HEC-FIA, over a levee-protected census block in Metairie, in Jefferson Parish, Louisiana. Building attribute data in National Structure Inventory (NSI) 2.0 are compared against “best available data” (BAD) collected at the individual building scale from Google Street View, Jefferson Parish building inventory, and 2019 National Building Cost Manual, to assess the sensitivity of input building inventory selection. Results suggest that use of BAD likely enhances flood loss estimation accuracy over existing reliance on default data in the software or from a national data set that generalizes over a broad scale. Although the three models give similar mean (median) building and content loss, Hazus Level 2 results diverge from those produced by FAST and HEC-FIA at the individual building level. A statistically significant difference in mean (median) building loss exists, but no significant difference is found in mean (median) content loss, between building inventory input (i.e., NSI 2.0 vs BAD), but both the building and content loss vary at the individual building scale due to difference in building-inventory-reported foundation height, foundation type, number of stories, replacement cost, and content cost. Moreover, building loss estimation also differs significantly by depth-damage function (DDF), for flood depths corresponding with the longest return periods, with content loss differing significantly by DDF at all return periods tested, from 10 to 500 years. Knowledge of the extent of estimated differences aids in understanding the degree of uncertainty in flood loss estimation. Much like the real estate industry uses comparable home values to appraise a home, flood loss planners should use multiple models to estimate flood-related losses. Moreover, results from this study can be used as a baseline for assessing losses from other hazards, thereby enhancing protection of human life and property.

Flood Damage Assessment for Pergau Hydroelectric Power Project using HEC-FIA

Dams play a vital role in our modern life but it may fail in any undesirable situation and have a disastrous effect on society, economy and environment. As most of the dams in Malaysia undergo aging factors, the integrity of dams should be examined. This research assesses the flood impact analysis on direct damages and loss of life (LOL) for the Pergau Hydroelectric Dam breach under the probable maximum flood (PMF) scenario using Hydrologic Engineering Center’s Flood Impact Analysis (HEC-FIA) software. The results are also compared with the United States Bureau of Reclamation method. The model was populated with inundation and flood arrival time grid, LOL parameters and structure inventories as input and the simulation results showed that 17 affected villages would subject to direct damage of RM 79,433,437 and 380 LOL. The percentage difference between the two methods is 2.75% for direct damage and 4.12% for LOL.

Urban flood hazard analysis in present and future climate after statistical downscaling: a case study in Ha Tinh city, Vietnam

ABSTRACT Vietnamese cities are highly vulnerable to urban flooding as a consequence of climate change and rapid urbanisation. In this study, current and future pluvial urban flood hazard was assessed for Ha Tinh city. Climate scenarios were obtained after statistical downscaling by applying a quantile-perturbation approach on ensembles of 170 global and 20 regional climate models. Flood impact analysis was based on the 1D-2D dual drainage modelling approach. Extreme daily rainfall intensities are projected to increase by 5 to 20%, whereas wet day frequency will decrease with some uncertainty. Larger changes in rainfall intensities were obtained for the finer scale climate models. Under the 95% upper limit scenario for future rainfall intensities (2071–2100), a 20-year intensity in the current climate would become a 2-year storm in the future and the flood extent is projected to increase by 30–40%. This indicates a need for climate adaptation measures and sustainable future urban planning.

Comparison and analysis of calculation of Bridge backwater based on Mike21 hydrodynamic model

The construction of bridges and other structures across the river will affect the flood discharge capacity and local water potential of the river.Based on navier-Stokes equation of MIKE21FM hydrodynamic module, this paper carries out two-dimensional numerical simulation of part of Shixi River. By optimizing the grid near the piers to reduce the difference brought by the terrain generalized grid of the real river, it simulates and analyzes the length of the curve of yong-high and Yong-water under different flood frequencies,the Nash-Sutcliffe efficiency coefficient and relative error analysis are used to verify the rationality of the results. The simulation results can accurately reflect the real changes of river water level, It provides a theoretical basis for flood impact analysis.

Integrating Reservoir Operations and Flood Modeling with HEC-RAS 2D

Current free to use models developed by the United States Army Corps of Engineers (USACE) perform unique functions (e.g., hydrology, hydraulics, reservoir operations, and flood impact analysis) that are widely used in numerous studies and applications. These models are commonly set up in a framework that is limited to point source connections, which is problematic in regions with flat topography and complex hydrodynamics. The separate models need to be integrally linked and jointly considered for accurate risk communication and decision-making, especially during major storm events. Recently, Hurricane Harvey (2017) exposed the shortcomings of the existing framework in West Harris County, TX, where an insufficient understanding of potential flood risk and impacts contributed to the extensive flood damages sustained in the region. This work illustrates the possibility of using a single hydraulic model, HEC-RAS 2D, to perform all hydrologic, hydraulic, and reservoir operations modeling necessary for accurate flood impact assessments. Implications of this study include a simplification of the entire flood impact analysis, which could help future flood risk communication and emergency planning.

Semi-probabilistic coastal flood impact analysis: From deterministic hazards to multi-damage model impacts

Coastal flood impact assessments are important tools for risk management and are performed by combining the hazard component with the vulnerability of exposed assets, to quantify consequences (or impacts) in terms of relative or absolute (e.g. financial) damage. The process generates uncertainties that should be taken into account for the correct representation of the consequences of floods. This study presents a coastal flood impact application at the spatial level of the Stavanger municipality (Norway), based on a multi-damage model approach able to represent impacts, and their overall uncertainty. Hazard modelling was performed using the LISFLOOD-FP code, taking into account historical extreme water level events (1988–2017) and relative sea level rise scenarios. Direct impacts were calculated in the form of relative and financial damage for different building categories, using flood damage curves. The results showed that the expected impacts are fewer than 50 flooded receptors and less than €1 million in damage in the current sea level scenario. The impacts could double by the end of the century, considering the most optimistic relative sea level scenario. The results were discussed considering the limitations of the approach for both hazard and impact modelling, that will be improved in future implementations. The outcome of this study may be useful for cost–benefit analyses of mitigation actions and local-scale plans for adaptation.

Impacts of Natural Disasters on Households and Small Businesses in India

Extreme precipitation and flooding cause large-scale impacts on people, and are further intensified by rapid urbanization, infrastructure expansion, and large numbers of people residing in informal settlements in destitute conditions. This underscores the need to characterize the impacts of extreme precipitation on different stakeholders and help formulate policies and plans to mitigate them. The focus of this paper is on characterizing and analyzing the impacts of extreme precipitation events at the micro level on vulnerable households and small and medium-sized enterprises in three locations in India: Mumbai, Chennai, and Puri district. These areas have faced devastating extreme rainfall events in recent years and offer critical insights into asset the exposure of, and direct and indirect impacts on, urban and rural entities. The flood impact analysis in this paper provides a multidimensional view with quantitative damage estimates and qualitative insights into the devastation and distress caused. It also highlights the heterogeneity of flood impacts and the potential to push the poor into a debt trap and further poverty.

Evaluating flood resilience in rural communities: a case-based assessment of Dyer County, Tennessee

Communities everywhere are being subjected to a variety of natural hazard events that can result in significant disruption to critical functions. As a result, community resilience assessment in these locations is gaining popularity as a means to help better prepare for, respond to, and recover from potentially disruptive events. The objective of this study was to identify key vulnerabilities relevant to addressing rural community resilience through conducting an initial flood impact analysis, with a specific focus on emergency response and transportation network accessibility. It included a use case involving the flooding of a rural community along the US inland waterway system. Special consideration was given to impacts experienced by at-risk populations (e.g., low economic status, youth, and elderly), given their unique vulnerabilities. An important backdrop to this work is recognition that Federal Emergency Management Agency’s Hazus, a free, publicly available tool, is commonly recommended by the agency for counties, particularly those with limited resources (i.e., rural areas), to use in developing their hazard mitigation plans. The case study results, however, demonstrate that Hazus, as currently utilized, has some serious deficiencies in that it: (1) likely underestimates the flood extent boundaries for study regions in a Level 1 analysis (which solely relies upon filling digital elevation models with precipitation), (2) may be incorrectly predicting the number and location of damaged buildings due to its reliance on out-of-date census data and the assumption that buildings are evenly distributed within a census block, and (3) is incomplete in its reporting of the accessibility of socially vulnerable populations and response capabilities of essential facilities. Therefore, if counties base their flood emergency response plans solely on Hazus results, they are likely to be underprepared for future flood events of significant magnitude. An approach in which Hazus results can be augmented with additional data and analyses is proposed to provide a more risk-informed assessment of community-level flood resilience.

UTILIZATION OF SPACEBORNE C-BAND SAR DATA FOR ANALYSIS OF FLOOD IMPACT ON AGRICULTURE AND ITS MANAGEMENT

Abstract. North India, since time immemorial remained the cradle of agricultural development. Every year during the monsoons, there is a high upsurge in the river Rapti. This leads to heavy flooding in the area and takes a toll on life and property besides submerging acres of precious agricultural land. Till now, such floods have been mapped using satellite data from optical sensors, but in monsoons due to cloud cover the task becomes difficult. Spaceborne SAR (Synthetic Aperture RADAR) data solves this problem by offering all-weather availability. This study aims to utilize the potential of C-band dual PolSAR data from Sentinel-1A for flood mapping and analysis of its impact on agriculture along with suggesting mitigation measures. Sentinel-1A data of January and September 2018 was taken and pre-processed. Thereafter, an interferogram was prepared and was phase filtered using modified Goldstein phase filter to remove phase distortions and a DEM (Digital Elevation Model) was prepared. The phase maps generated were analyzed for phase variations after removing the topographic phase and it was found that there was very less phase variation from urban and agricultural lands surrounding the river which clearly indicated heavy flooding and submergence of land in water. Using the DEM map generated, hydrological processing was done to delineate flow lines and calculation of catchment area at point of maximum submergence of agricultural land. This was followed by the generation of contours in the area and finally, the flood impact analysis was done by calculating the water volume in watershed during the flood.

Flood Resilience of Critical Infrastructure: Approach and Method Applied to Fort Lauderdale, Florida

In order to increase the flood resilience of cities (i.e., the ability to cope with flood hazards), it is also crucial to make critical infrastructure functions resilient, since these are essential for urban society. Cities are complex systems with many actors of different disciplines and many interdependent critical infrastructure networks and functions. Common flood risk analysis techniques provide useful information but are not sufficient to obtain a complete overview of the effects of flooding and potential measures to increase flood resilience related to critical infrastructure networks. Therefore, a more comprehensive approach is needed which helps accessing knowledge of actors in a structured way. Fort Lauderdale, Florida, United States has suffered from flood impacts, especially from disruptions in critical infrastructure. This paper shows how shared insight among different sectors and stakeholders into critical infrastructure resilience and potential resilience-enhancing measures was obtained using input from these actors. It also provides a first quantitative indication of resilience, indicated by the potential disruption due to floods and the effect of measures on resilience. The paper contributes to the existing literature on resilience specifically by considering the duration of disruption, the inclusion of critical infrastructure disruption in flood impact analysis, and the step from resilience quantification to measures.

Using HEC-FIA to identify Indirect Economic Losses

The United States Army Corps of Engineers’ Hydrologic Engineering Center developed the HEC-FIA (Flood Impact Analysis) software to assist in the estimation of consequences with uncertainty. By estimating the consequences, the benefits of existing and future flood risk management measures can be evaluated and compared.HEC-FIA utilizes geospatial datasets to help users build structure inventories and assign values and population per structure. Using this information and geospatially derived flood depth grids (provided by most hydraulic models), HEC-FIA estimates direct economic, indirect economic, agricultural, and life loss consequences for flood hazards. HEC-FIA can compute results for a single event in either deterministic mode or in uncertainty mode which utilizes a Monte Carlo approach. The user can define the uncertainties about any structure in the floodplain in many ways, and each has various impacts on the different consequence calculations. For example, foundation heights, structure values, and depth-damage relationships impact economic consequences, while foundation heights, warning issuance times, and fatality rates impact the life loss calculations. All of these parameters can be defined with uncertainty. HEC-FIA can also be linked into HEC-WAT (Watershed Analysis Tool) with the FRA (Flood Risk Analysis) compute option to randomize the hydraulic events being evaluated in HEC-FIA so that hydrologic, hydraulic, geotechnical, and economic uncertainties can all be represented and evaluated by alternative within the floodplain.This paper will describe how HEC-FIA can be utilized to help evaluate the indirect economic consequences for various alternatives within a floodplain. The computational methods for indirect economic losses utilize a Computable General Equilibrium model to describe the secondary and tertiary impacts of loss of service, loss of laborers, and reductions in demand for intermediary goods.

Micro-scale flood risk analysis based on detailed 2D hydraulic modelling and high resolution geographic data

The paper presents a consistent micro-scale flood risk analysis procedure, relying on detailed 2D inundation modelling as well as on high resolution topographic and land use database. The flow model is based on the shallow-water equations, solved by means of a finite volume scheme on multi-block structured grids. Using highly accurate laser altimetry, the simulations are performed with a typical grid spacing of 2 m, which is fine enough to represent the flow at the scale of individual buildings. Consequently, the outcomes of hydraulic modelling constitute suitable inputs for the subsequent exposure analysis, performed at a micro-scale using detailed land use maps and geographic database. Eventually, the procedure incorporates social flood impact analysis and evaluation of direct economic damage to residential buildings. Besides detailing the characteristics and performance of the hydraulic model, the paper describes the flow of data within the overall flood risk analysis procedure and demonstrates its applicability by means of a case study, for which two different flood protection measures were evaluated.