Impact Of Floods Research Articles

Flood impact assessment in urban settings with porous buildings – insights from a fine-scale hydraulic-economic model

Flood impact assessment in urban settings with porous buildings – insights from a fine-scale hydraulic-economic model

The Impact of Floods on Livelihoods of Farmers in Bagalkot District of Karnataka, India

The Impact of Floods on Livelihoods of Farmers in Bagalkot District of Karnataka, India

Assessment of Flood Vulnerability and Coping Strategies of Communities Living along River Tana in Madogo Ward, Kenya

Purpose: Flood is a natural disaster that occurs due to the sudden onset of rainfall that causes runoff waters from high to low altitude area. Community living along the River Tana in Madogo ward, Tana River County are affected by the floods when it occurs. It was therefore important to assess factors contributing to their flood vulnerability and assess their flood coping and adaptation strategy for current and future planning. This study assessed the factors contributing to flood vulnerability, adaptation and coping strategies along River Tana in Madogo Ward, Tana River County, Kenya. The research objectives were to assess the trends of flood occurrence in Madogo Ward between 2000 and 2020 as well as the coping and adaptation strategies of communities to floods in Madogo Ward.
 Materials and Methods: A descriptive research design approach was used. Data collection approaches involved the use of questionnaires to identify coping strategies by communities. Key informant interviews were also conducted with government officers within the study area to provide information on factors contributing to flood vulnerability, flood trends, occurrence adaptation and coping strategies. Secondary data was acquired through journals, books, and maps. The Statistical Package for Social Science was used to analyze the quantitative data. The analyzed data was presented through maps, tables, figures and graphs.
 Findings: The results indicated that the floods occur after every two years in the study area with different magnitudes and durations. The main coping strategies employed by the community living along River Tana in Madogo Ward was relocation to the higher grounds. It was also established that the community in the area had developed adaptive strategies to flood by putting barriers round their houses. Further findings indicated that the major flood vulnerability factor was topography of the area.
 Implications to Theory, Practice and Policy: Based on the findings, it is being recommended that community leaders and county government of Tana River should not allocate plots in the flood zone area. Hence, there is a need for flood zone mapping for resident to know whether they are living within flood zone or not. Additionally, the people’s economic power should be enhanced through entrepreneurial training and giving them first priority in job opportunities. There is also a need to improve the quality of the infrastructures in the area to enhance their resilience to the negative impact of floods.

Flood impact assessment on agricultural and municipal areas using Sentinel-1 and 2 satellite images (case study: Kermanshah province)

Flood impact assessment on agricultural and municipal areas using Sentinel-1 and 2 satellite images (case study: Kermanshah province)

Geomorphological Response of Alluvial Streams to Flood Events during Base-Level Lowering: Insights from Drone-Based Photogrammetric Surveys in Dead Sea Tributaries

The geomorphological impact of base-level lowering on ephemeral alluvial streams has been extensively investigated through fieldwork, experimentation, and modeling. Yet, the understanding of hydrological parameters governing the dynamics of the stream’s geometry during discrete flood events is lacking due to limited direct measurements of flood-scale erosion/deposition. The emergence of novel remote sensing methods allows for quantifying morphological modifications caused by floods in alluvial streams. This study utilizes drone surveys and hydrological data to quantitatively investigate the relation between channel evolution in alluvial tributaries draining to the receding Dead Sea and the hydrological characteristics of flash floods. Drone-based photogrammetric surveys were conducted before and after 25 floods, over a period of four years, to generate centimeter-scale Digital Elevation Models (DEM) and orthophoto maps of two major streams. The outcomes of these DEMs are maps of ground elevation changes (erosion/deposition), thalweg longitudinal profiles, and channel cross sections, revealing the incision/aggradation along and across the streams. Statistical comparison of results with flow hydrographs identified potential relations linking the hydrological characteristics of each flood and the corresponding geomorphological modifications. Peak discharge emerged as the primary factor influencing sediment removal, leading to more efficient sediment evacuation and a negative sediment budget with increased discharge. Water volumes of floods also exhibited a secondary effect on the sediment budget. The chronological order of floods, whether first or later in the season, was identified as the primary factor determining incision magnitude. Knickpoints formed at the streams’ outlets during the dry period, when lake-level drops, amplifying the impact of the first flood. These findings have potential implications for infrastructure planning and environmental management in the context of climate change and altered water runoff. The research highlights the efficiency of drone-based photogrammetry for cost-effective and timely data collection, providing invaluable flexibility for field research.

Tropical or extratropical cyclones: what drives the compound flood hazard, impact, and risk for the United States Southeast Atlantic coast?

Subtropical coastlines are impacted by both tropical and extratropical cyclones. While both may lead to substantial damage to coastal communities, it is difficult to determine the contribution of tropical cyclones to coastal flooding relative to that of extratropical cyclones. We conduct a large-scale flood hazard and impact assessment across the subtropical Southeast Atlantic Coast of the United States, from Virginia to Florida, including different flood hazards. The physics-based hydrodynamic modeling skillfully reproduces coastal water levels based on a comprehensive validation of tides, almost two hundred historical storms, and an in-depth hindcast of Hurricane Florence. We show that yearly flood impacts are two times as likely to be driven by extratropical than tropical cyclones. On the other hand, tropical cyclones are 30 times more likely to affect people during rarer 100-year events than extratropical cyclones and contribute to more than half of the regional flood risk. With increasing sea levels, more areas will be flooded, regardless of whether flooding is driven by tropical or extratropical cyclones. Most of the absolute flood risk is contained in the greater Miami metropolitan area. However, several less populous counties have the highest relative risks. The results of this study provide critical information for understanding the source and frequency of compound flooding across the Southeast Atlantic Coast of the United States.

Impact of climate-induced floods and typhoons on geriatric disabling health among older Chinese and Filipinos: a cross-country systematic review

BackgroundApart from both China and the Philippines continuing to be exposed to and affected by different climate-induced hazards, in particular floods and typhoons, they are also reported to be witnessing rapid ageing populations of 60 years and older. As such, this systematic review synthesized the existing evidence about the impacts aggravated by floods and typhoons on the geriatric disabling health of older Chinese and Filipinos, respectively.MethodsFour (4) electronic databases were systematically searched to identify eligible studies published between 2000 and early 2023. This process had to confirm the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (PRISMA), as well as the standard protocol registered with PROSPERO (CRD42023420549).ResultsOut of 317 and 216 initial records retrieved for China and the Philippines, respectively, 27 (China) and 25 (Philippines) studies were eligible for final review. The disabling conditions they reported to affect the health of older adults were grouped into 4 categories: cognitive and intellectual, physical, chronic and terminal illnesses, and mental and psychological, with the latter identified as the most prevalent condition to affect older Chinese and Filipinos. On a sub-category level, posttraumatic stress disorder (PTSD) was the most common condition reported in 27 flood-related studies in China, while injuries and wounds prevailed in the Philippines, according to 25 typhoon-related studies.ConclusionThe increasing occurrence of extreme climate hazards, especially floods and typhoons in China and the Philippines, respectively, impacted the health of their older adults with various disabling effects or conditions. Therefore, this calls for appropriate geriatric-informed interventions in the context of climate change and rapidly ageing settings beyond China and the Philippines to others that are also prone to floods and typhoons.

Impact of massive flood on drinking water quality and community health risk assessment in Patna, Bihar, India

Impact of massive flood on drinking water quality and community health risk assessment in Patna, Bihar, India

Performances of different yield-detrending methods in assessing the impacts of agricultural drought and flooding: A case study in the middle-and-lower reach of the Yangtze River, China

In evaluating the impacts of drought and flooding disasters on crop yields, accurately calculating meteorological yield (i.e., detrended yield) is an important procedure. The present work aimed to compare various yield-detrending methods in terms of characterizing the regression relationships between meteorological yield and the intensities of drought and flooding. Taking the middle-and-lower reach of the Yangtze River (MLRYR) as the study region, the intensities of drought and flooding during the growing seasons of four study crops (cotton, oilseed rape, wheat, and maize) were quantified using the standardized precipitation evapotranspiration index. Nine popular yield-detrending methods and the first-difference method were employed to determine meteorological yields. The results indicated that the examined methods consistently identified the cases with very significant yield-reducing impacts of drought and flooding. The first-difference method identified 58 significant regression relationships, outperforming the yield-detrending methods (identifying 39–44 significant regression relationships). The 20-yr moving average and the linear fitting methods performed best at the provincial level, while the cubic smoothing spline and the quadratic polynomial fitting methods performed best at the district level. Based on these best-performing methods, the average method was proposed and exhibited wider applicability and better performance than the individual methods. In terms of meteorological yield losses, cotton was the most affected crop (35% of all districts experienced severe cotton yield loss) and Anhui was the most affected region (with an average crop yield loss of 14.06%). The yield-reducing impact of flooding was significant in 41 districts; in comparison, the impact of drought was significant only in 7 districts. Additionally, oilseed rape was the crop most affected by drought and flooding. These results can provide guidance for assessing agricultural drought and flooding disasters under climate change.

Empowering real-time flood impact assessment through the integration of machine learning and Google Earth Engine: a comprehensive approach.

Floods cause substantial losses to life and property, especially in flood-prone regions like northwestern Bangladesh. Timely and precise evaluation of flood impacts is critical for effective flood management and decision-making. This research demonstrates an integrated approach utilizing machine learning and Google Earth Engine to enable real-time flood assessment. Synthetic aperture radar (SAR) data from Sentinel-1 and the Google Earth Engine platform were employed to generate near real-time flood maps of the 2020 flood in Kurigram and Lalmonirhat. An automatic thresholding technique quantified flooded areas. For land use/land cover (LULC) analysis, Sentinel-2's high resolution and machine learning models like artificial neural networks (ANN), random forests (RF) and support vector machines (SVM) were leveraged. ANN delivered the best LULC mapping with 0.94 accuracy based on metrics like accuracy, kappa, mean F1 score, mean sensitivity, mean specificity, mean positive predictive value, mean negative value, mean precision, mean recall, mean detection rate and mean balanced accuracy. Results showed over 600,000 people exposed at peak inundation in July-about 17% of the population. The machine learning-enabled LULC maps reliably identified vulnerable areas to prioritize flood management. Over half of croplands flooded in July. This research demonstrates the potential of integrating SAR, machine learning and cloud computing to empower authorities through real-time monitoring and accurate LULC mapping essential for effective flood response. The proposed comprehensive methodology can assist stakeholders in developing data-driven flood management strategies to reduce impacts.

Peatland Forest Fire Mitigation Policies: Impact on Traditional Farmer’s Food Security and Environmental Improvement

Indonesia is one of the countries with the most vulnerable food security to the effects of climate change. Peatlands have a considerable potential for crop production, but they must be managed carefully. The government issued a regulation restricting burning the land for farming preparation in response to forest and land fires on peatlands. Unfortunately, traditional farmers lost their food security due to that policy. This research aims to: i) analyze farmers’ food security and its impact on improving the environment after the policy banning burning in land preparation. Data was collected through interviews, field observations, and focus group discussions. The acquired data is analyzed qualitatively and descriptively. According to the study’s findings, their land no longer supports farmer’s food availability, and they must pursue new livelihoods to afford to buy their daily needs from the nearest market. Food utilization is still superficial. Farmers’s food stability is extremely fragile due to the impact of policies, pest invasions, droughts, and floods. Although the policy bans burning in land preparation causes farmers to lose their self-sufficient food security, it has improved peatland ecosystems. The government must strengthen community empowerment programs to restore farmers’ food security.

GIS-based Social Vulnerability Integration for Robust Flood Response, Disease Prevention and Community Resilience in Chennai Metropolitan Area post-Cyclone Michaung

The present study outlines a comprehensive strategy for flood response, disease prevention and long-term community resilience in the aftermath of a recent Cyclone Michaung, with the proximity of landfall near Chennai and the increased likelihood of flooding in the CMA. Drawing insights from an existing social vulnerability map, the study addresses the unique challenges posed by flooding and aims to mitigate the heightened risk of waterborne and vector-borne diseases. Objectives encompass assessing social vulnerability, formulating a targeted flood response strategy, implementing healthcare interventions for disease prevention, strengthening information dissemination and advocating for long-term resilience planning. The methodology involves reviewing the existing vulnerability map, identifying vulnerable communities, integrating flood impact data and developing a comprehensive response plan. The study utilizes GIS and Remote Sensing technologies for monitoring and assessing the results. Key findings from the social vulnerability assessment inform prioritized intervention areas for both flood response and disease prevention. The discussion interprets results in the context of strategy effectiveness, emphasizing the significance of a nuanced and inclusive approach. This manuscript serves as a guide for stakeholders in implementing a holistic strategy that addresses immediate concerns, prevents disease outbreaks and fosters long-term community resilience.

Compilation method of a catalogue of reasonable worst-case rainfall series for flash flood simulations of short, convective rainstorms

In this study, a categorisation method was developed and applied to identify, select and rank reasonable worst-case rainfall storm events with time-series resolution of one minute and duration of up to one hour. The method yields a catalogue of 24 reasonable worst-case rainfall series, i.e. potentially catastrophic events that could be used for safe-to-fail flash flood model scenarios, thus encouraging the testing of critical infrastructure and pedestrian safety for people trapped in floods. The identified 24 events were shown to be considerably more extreme than corresponding design storms, with a return interval of 100 years. In the selection of the extremes, special care was taken to consider different hazard attributes, which are associated with intrinsically different observed hyetograph shapes, including rectangular, short and long triangle, and double peak shape categories. Hydrodynamic simulations were carried out using the 2D robust shallow water model hms++ to quantify the flooding impact of the 24 rainfall scenarios in a small urbanised catchment, which enabled the ranking of the scenarios based on different hazard attributes. Overall, the rectangular and long-triangle events showed the highest total discharge, and the rectangular events comprise both the longest duration for hazard velocity and deep flooding. The long-triangle events presented the highest peak discharge and peak water depths. The short-triangle ones showed the highest flashiness (shortest time to peak), whereas the double peak events yielded the longest time to peak. The ranking emphasised the importance of the hyetograph shape characteristics of extreme storms and which needs to be taken into account in flash flood management. The novel categorisation method is easily transferable to other regions, if high-resolution rain series are available.

Flood Impacts on Agriculture under Climate Change: The case of the Awanui Catchment, New Zealand

We assess the economic and environmental impacts on agriculture of flooding under projected climate change, including land-use change as an adaption response to floods. Our case study area is the Awanui catchment located in the far north of New Zealand, where flooding is a significant hazard. The study uses an integrated approach and combines spatial information on agricultural exposure and damage from flooding, economic land-use modelling, and valuation approaches. We analyse direct tangible and direct intangible flood impacts under various extents, frequencies, and water depth levels. Our results show areas with flood exposure and damage costs increase with projected climate change. As an adaptation measure to reduce flood damage costs, pastoral farms convert to other land uses, mainly to unfarmed land. Flooding reduces the net revenue for the catchment, while it can result in some reduction of environmental pollution. When the probability of all possible flood events are considered, the value of the changes in greenhouse gas emissions are equivalent to approximately 18% of the change in total net revenue, while the value of changes in other environmental outputs is equivalent to less than 1% of the change in total net revenue. Based on this study, the assessment of various flood impacts and adaptation responses to them can help to develop resilience strategies for the agricultural sector to future climate-induced flooding.

Performance of Flood Early Detection System (FEDS) and Artificial Neural Network on Predicting Flood in the City

An integrated flood detection system that is easily accessible to the public is one of the efforts to reduce the impact of flooding in flood-prone locations. The performance of flood detectors integrated with the internet helps make it easy Public for access information about possibility happening flood. Information about bulk rain, high water level, the water discharge will Becomes indication possibility happening downstream flooding. Tool prototype detector flood this be equipped with temperature and humidity sensor as addition information for society. Research results show that performance tool detector flood already good because capable give information related to data that can be made indication possibility happening flood. Sensors used have score small mistake and after calibrated got score constant for standardize results testing. Bulk sensor test results rain produces an average error of 3% and after calibration obtained constant of 1.03. High sensor test results water level has an average error of 1.07% and after calibrated obtained score constant of 0.98. Humidity sensor testing have the average error value is 3% and after calibration obtained score constant 1.03

Projected seasonal flooding in Canada under climate change with statistical and machine learning

Study regionCanada Study focusFloods are among the costliest and deadliest natural hazards in the world. To date, little is known about future seasonal flooding across all Canada. In this paper, data-driven models for flood occurrence (i.e., happening of a flood) and impact (i.e., displaced population) were calibrated for spring and summer seasons in 14,000 watersheds across Canada. Generalized Additive Models (GAM), Random Forests (RF) and Gradient Boosting Machines (GBM) were considered to model seasonal floods. The best-performing flood models were then used with regional climate models to assess the effect of climate change on flooding for three time horizons: historical, medium-term (∼2050) and long-term (∼2080). New hydrological insights for the regionGAM offered the best out-of-sample performance trade-off in both seasons for predicting flooding in Canada. Projections with GAM showed a general increase in summer flooding occurrence and impact in 2050 and 2080, mainly in the Yukon, western British Columbia, southern Prairies, Ontario and Quebec and some Atlantic provinces. Results for spring flooding were more mixed, but there seemed to be a slight decrease in the impact of spring flooding in the southern Prairies, particularly in 2080. The combination of statistical/machine learning and climate models have provided a more detailed and contrasted picture of the projected seasonal flooding situation over Canada that will help authorities better mitigate future flood risks.

Spatial Analysis of Exposure of Roads to Flooding and Its Implications for Mobility in Urban/Peri-Urban Accra

Climate change seriously threatens human systems, properties and livelihoods. Global projections suggest a continuous increase in the frequency and severity of weather events, with severe outcomes. Although the trends and impacts are highly variable depending on location, most studies tend to concentrate on either the urban or rural areas, with little focus on peri-urban areas. Yet, in Sub-Saharan Africa, peri-urban areas display unique characteristics: inadequate infrastructure, unplanned development, weak governance, and environmental degradation, all of which exacerbate flood impact and thus need academic attention. This study contributes to filling this gap by assessing the flood vulnerability of roads in peri-urban Accra and its implications for mobility. Based on the fieldwork, the study delineated and analysed potential zones within the research locations. The researchers calculated roads’ absolute and relative lengths, using a spatial overlay (intersection) of potentially flooded roads with the total road network within the grid cells of 500 m by 500 m. These measures were adopted and used as exposure measures. The findings revealed that over 80% of roads with lengths between 100 m and 500 m were exposed to floods. Some areas had higher exposure indices, with absolute road lengths ranging from 1.5 km to 3.2 km and relative road lengths between 0.8 and 1.0. There were significant variations in road exposure between and within neighbourhoods. Depending on the depth and duration of the floodwater, residents may be unable to access their homes or carry out their daily activities. In conclusion, this study highlights the differential vulnerability of peri-urban areas to road flooding and recommends targeted provision of flood-resilient infrastructure to promote sustainable development.

A novel framework for assessment of human impact of floods: Demonstrated for the Indian subcontinent

Flood damages are a result of mutual interaction between flood hazard and socio-economic factors. The increase in flood damages over time can be attributed to various enhancements in the magnitude and frequency of floods as well as socio-economic development in the floodplains. The quantification and analysis of the human dimensions of flood damages is challenged due to irreversibility and lack of understanding of complex-human flood interactions, especially in less developed regions. Since flood damage assessments play a critical role in designing effective flood preparedness plans, we suggest including the human dimension in evaluating damages. We present a framework for the assessment of the human impact of floods by incorporating statistics on the number of people exposed, displaced, and fatalities recorded for each flood event. The framework involves categorizing human impact, identifying spatial clusters of different categories, and exploring the role of various hazard and socio-economic characteristics in determining impact. While categorizing and clustering of impact helps to distinguish between regions prone to different impact, understanding the role of socio-economic and demographic factors is expected to help in developing tailor-made strategies to mitigate flood disasters. The methodology broadly consists of categorization using unsupervised learning, spatial clustering using Local Indicators of Spatial Autocorrelation (LISA), and spatial regression. The results indicate that the impact varies from one region to another and so does the role of hazard and socio-demographic variables in determining impact. Moreover, the framework developed may be used to study the relevance of various socio-hydrological theories and their role in determining the human impact of floods.

Understanding flash flooding in the Himalayan Region: a case study

The Himalayan region, characterized by its substantial topographical scale and elevation, exhibits vulnerability to flash floods and landslides induced by natural and anthropogenic influences. The study focuses on the Himalayan region, emphasizing the pivotal role of geographical and atmospheric parameters in flash flood occurrences. Specifically, the investigation delves into the intricate interactions between atmospheric and surface parameters to elucidate their collective contribution to flash flooding within the Nainital region of Uttarakhand in the Himalayan terrain. Pre-flood parameters, including total aerosol optical depth, cloud cover thickness, and total precipitable water vapor, were systematically analyzed, revealing a noteworthy correlation with flash flooding event transpiring on October 17th, 18th, and 19th, 2021. Which resulted in a huge loss of life and property in the study area. Contrasting the October 2021 heavy rainfall with the time series data (2000–2021), the historical pattern indicates flash flooding predominantly during June to September. The rare occurrence of October flash flooding suggests a potential shift in the area's precipitation pattern, possibly influenced by climate change. Robust statistical analyses, specifically employing non-parametric tests including the Autocorrelation function (ACF), Mann–Kendall (MK) test, Modified Mann–Kendall, and Sen's slope (q) estimator, were applied to discern extreme precipitation characteristics from 2000 to 201. The findings revealed a general non-significant increasing trend, except for July, which exhibited a non-significant decreasing trend. Moreover, the results elucidate the application of Meteosat-8 data and remote sensing applications to analyze flash flood dynamics. Furthermore, the research extensively explores the substantial roles played by pre and post-atmospheric parameters with geographic parameters in heavy rainfall events that resulted flash flooding, presenting a comprehensive discussion. The findings describe the role of real time remote sensing and satellite and underscore the need for comprehensive approaches to tackle flash flooding, including mitigation. The study also highlights the significance of monitoring weather patterns and rainfall trends to improve disaster preparedness and minimize the impact of flash floods in the Himalayan region.

Analysis of the perceptions of flood and effect of adoption of adaptation strategies on income of informal settlements of Mamelodi in South Africa

Extreme weather events are being experienced all over the world because of climate change, posing challenges for individuals and households who rely on agricultural operations as their major source of livelihood. Household-level adaptation is an efficient way of dealing with global climate change. As such, this study aims to examine the perception of informal settlers to flood risk and their adoption of adaptation strategies to flood. This study applied the seemingly unrelated regression (SUR) to identify factors influencing the perception of flooding on community members and probit regression to identify the factors influencing the adoption of adaptation strategies to floods and examined the impact of the adoption of adaptation strategies on income in Eerste Fabriek informal settlement in Mamelodi using two-step quasi-maximum likelihood estimates of fractional response model. Our results show that community members are perceptive of floods and their impact on the environment and their livelihoods, and on average, they believe flood impact is significant. Age, marital status, education, employment status, income, and household size are demographic factors that tend to influence their perception of the impact of flood events. Access to institutional facilities such as health and recreational facilities was also a significant factor in how community members adapt to the impact of floods. Timely healthcare access services are a significant precursor for people to form their perception, which is intended to help them adapt appropriately to situations as health is wealth. Community members' perceptions and adaptive capacity can be improved through policies that foster the adoption of effective adaptation strategies. Community-based adaptation strategies are necessary for involving all stakeholders and necessary for mitigating the effects of flooding.