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Flood economic vulnerability and risk assessment at the urban mesoscale based on land use: A case study in Changsha, China

Yang M, Mohammad Yusoff WF, Mohamed MF, Jiao S, Dai Y

J Environ Manage, 2024 Feb;351:119798.
PMID: 38103426 DOI: 10.1016/j.jenvman.2023.119798

With climate change and urbanization, flood disasters have significantly affected urban development worldwide. In this study, we developed a paradigm to assess flood economic vulnerability and risk at the urban mesoscale, focusing on urban land use. A hydrological simulation was used to evaluate flood hazards through inundation analyses, and a hazard-vulnerability matrix was applied to assess flood risk, enhancing the economic vulnerability assessment by quantifying the differing economic value and flood losses associated with different land types. The case study of Wangchengpo, Changsha, China, found average total economic losses of 126.94 USD/m2, with the highest risk in the settlement core. Residential areas had the highest flood hazard, vulnerability, and losses (61.10% of the total loss); transportation areas accounted for 27.87% of the total economic losses due to their high flooding depth. Despite low inundation, industrial land showed greater economic vulnerability due to higher overall economic value (10.52% of the total). Our findings highlight the influence of land types and industry differences on flood vulnerability and the effectiveness of land-use inclusion in urban-mesoscale analyses of spatial flood characteristics. We identify critical areas with hazard and economic vulnerability for urban land and disaster prevention management and planning, helping to offer targeted flood control strategies to enhance urban resilience.

Matched MeSH terms: Floods*
Fulltext HLD-DDoSDN: High and low-rates dataset-based DDoS attacks against SDN

Bahashwan AA, Anbar M, Manickam S, Issa G, Aladaileh MA, Alabsi BA, et al.

PLoS One, 2024;19(2):e0297548.
PMID: 38330004 DOI: 10.1371/journal.pone.0297548

Software Defined Network (SDN) has alleviated traditional network limitations but faces a significant challenge due to the risk of Distributed Denial of Service (DDoS) attacks against an SDN controller, with current detection methods lacking evaluation on unrealistic SDN datasets and standard DDoS attacks (i.e., high-rate DDoS attack). Therefore, a realistic dataset called HLD-DDoSDN is introduced, encompassing prevalent DDoS attacks specifically aimed at an SDN controller, such as User Internet Control Message Protocol (ICMP), Transmission Control Protocol (TCP), and User Datagram Protocol (UDP). This SDN dataset also incorporates diverse levels of traffic fluctuations, representing different traffic variation rates (i.e., high and low rates) in DDoS attacks. It is qualitatively compared to existing SDN datasets and quantitatively evaluated across all eight scenarios to ensure its superiority. Furthermore, it fulfils the requirements of a benchmark dataset in terms of size, variety of attacks and scenarios, with significant features that highly contribute to detecting realistic SDN attacks. The features of HLD-DDoSDN are evaluated using a Deep Multilayer Perception (D-MLP) based detection approach. Experimental findings indicate that the employed features exhibit high performance in the detection accuracy, recall, and precision of detecting high and low-rate DDoS flooding attacks.

Matched MeSH terms: Floods
Fulltext Mitigating infectious disease risks through non-stationary flood frequency analysis: a case study in Malaysia based on natural disaster reduction strategy

Mat Jan NA, Marsani MF, Thiruchelvam L, Zainal Abidin NB, Shabri A, Abdullah Sani SA

Geospat Health, 2023 Nov 13;18(2).
PMID: 37961980 DOI: 10.4081/gh.2023.1236

The occurrence of floods has the potential to escalate the transmission of infectious diseases. To enhance our comprehension of the health impacts of flooding and facilitate effective planning for mitigation strategies, it is necessary to explore the flood risk management. The variability present in hydrological records is an important and neglecting non-stationary patterns in flood data can lead to significant biases in estimating flood quantiles. Consequently, adopting a non-stationary flood frequency analysis appears to be a suitable approach to challenge the assumption of independent and identically distributed observations in the sample. This research employed the generalized extreme value (GEV) distribution to examine annual maximum flood series. To estimate non-stationary models in the flood data, several statistical tests, including the TL-moment method was utilized on the data from ten stream-flow stations in Johor, Malaysia, which revealed that two stations, namely Kahang and Lenggor, exhibited non-stationary behaviour in their annual maximum streamflow. Two non-stationary models efficiently described the data series from these two specific stations, the control of which could reduce outbreak of infectious diseases when used for controlling the development measures of the hydraulic structures. Thus, the application of these models may help prevent biased prediction of flood occurrences leading to lower number of cases infected by disease.

Matched MeSH terms: Floods*
Run-off modelling of pervious and impervious areas using couple SWAT and a novel machine learning model in cross-rivers state Nigeria

Salele B, Dodo YA, Sani DA, Abuhussain MA, Sayfutdinovna Abdullaeva B, Brysiewicz A

Water Sci Technol, 2023 Oct;88(7):1893-1909.
PMID: 37831003 DOI: 10.2166/wst.2023.304

Using the soil and water assessment tool (SWAT), runoff in pervious and impervious urban areas was simulated in this study. In the meantime, as a novel application of machine learning, the emotional artificial neural network (EANN) model was employed to enhance the SWAT obtained for this study. As a result of the EANN model's capabilities in rainfall-runoff phenomena, the SWAT-EANN couple model has been used to assess urban flooding. The pervious, impervious, and water body areas of the study area were classified and mapped to estimate the cover change over three epochs. Land use map, precipitation data, temperature (minimum and maximum) data, wind speed, relative humidity, soil map, solar radiation, and digital elevation model were used as inputs for modelling rainfall-runoff of the study area in the ArcGIS environment. The accuracy assessment of this study was excellent (root-mean-square error 1 mm of precipitation). It also revealed that (a) a land use map illustrating changes in impervious, pervious surface, and water body for 1998, 2008, and 2018; (b) runoff modelling using a historical pattern of rainfall-runoff changes (1998-2018); and (c) descriptive statistical analysis of the runoff results of the research. This research will aid in urban planning, administration, and development. Specifically, it will prevent flooding and environmental problems.

Matched MeSH terms: Floods
Anthropogenic climate change exacerbates the risk of successive flood-heat extremes: Multi-model global projections based on the Inter-Sectoral Impact Model Intercomparison Project

Zhou J, Wu C, Yeh PJ, Ju J, Zhong L, Wang S, et al.

Sci Total Environ, 2023 Sep 01;889:164274.
PMID: 37209749 DOI: 10.1016/j.scitotenv.2023.164274

The successive flood-heat extreme (SFHE) event, which threatens the securities of human health, economy, and building environment, has attracted extensive research attention recently. However, the potential changes in SFHE characteristics and the global population exposure to SFHE under anthropogenic warming remain unclear. Here, we present a global-scale evaluation of the projected changes and uncertainties in SFHE characteristics (frequency, intensity, duration, land exposure) and population exposure under the Representative Concentration Pathway (RCP) 2.6 and 6.0 scenarios, based on the multi-model ensembles (five global water models forced by four global climate models) within the Inter-Sectoral Impact Model Intercomparison Project 2b framework. The results reveal that, relative to the 1970-1999 baseline period, the SFHE frequency is projected to increase nearly globally by the end of this century, especially in the Qinghai-Tibet Plateau (>20 events/30-year) and the tropical regions (e.g., northern South America, central Africa, and southeastern Asia, >15 events/30-year). The projected higher SFHE frequency is generally accompanied by a larger model uncertainty. By the end of this century, the SFHE land exposure is expected to increase by 12 % (20 %) under RCP2.6 (RCP6.0), and the intervals between flood and heatwave in SFHE tend to decrease by up to 3 days under both RCPs, implying the more intermittent SFHE occurrence under future warming. The SFHE events will lead to the higher population exposure in the Indian Peninsula and central Africa (<10 million person-days) and eastern Asia (<5 million person-days) due to the higher population density and the longer SFHE duration. Partial correlation analysis indicates that the contribution of flood to the SFHE frequency is greater than that of heatwave for most global regions, but the SFHE frequency is dominated by the heatwave in northern North America and northern Asia.

Matched MeSH terms: Floods
Assessing urban flooding risk in response to climate change and urbanization based on shared socio-economic pathways

Wang M, Fu X, Zhang D, Chen F, Liu M, Zhou S, et al.

Sci Total Environ, 2023 Jul 01;880:163470.
PMID: 37076008 DOI: 10.1016/j.scitotenv.2023.163470

Global climate change and rapid urbanization, mainly driven by anthropogenic activities, lead to urban flood vulnerability and uncertainty in sustainable stormwater management. This study projected the temporal and spatial variation in urban flood susceptibility during the period 2020-2050 on the basis of shared socioeconomic pathways (SSPs). A case study in Guangdong-Hong Kong-Macao Greater Bay Area (GBA) was conducted for verifying the feasibility and applicability of this approach. GBA is predicted to encounter the increase in extreme precipitation with high intensity and frequency, along with rapid expansion of constructed areas, resulting in exacerbating of urban flood susceptibility. The areas with medium and high flood susceptibility will be expected to increase continuously from 2020 to 2050, by 9.5 %, 12.0 %, and 14.4 % under SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios, respectively. In terms of the assessment of spatial-temporal flooding pattern, the areas with high flood susceptibility are overlapped with that in the populated urban center in GBA, surrounding the existing risk areas, which is consistent with the tendency of construction land expansion. The approach in the present study will provide comprehensive insights into the reliable and accurate assessment of urban flooding susceptibility in response to climate change and urbanization.

Matched MeSH terms: Floods*
Sea-level projections using a NARX-NN model of tide gauge data for the coastal city of Kuala Terengganu in Malaysia

Bagheri M, Ibrahim ZZ, Wolf ID, Akhir MF, Talaat WIAW, Oryani B

Environ Sci Pollut Res Int, 2023 Jul;30(34):81839-81857.
PMID: 35789462 DOI: 10.1007/s11356-022-21662-4

The impact of global warming presents an increased risk to the world's shorelines. The Intergovernmental Panel on Climate Change (IPCC) reported that the twenty-first century experienced a severe global mean sea-level rise due to human-induced climate change. Therefore, coastal planners require reasonably accurate estimates of the rate of sea-level rise and the potential impacts, including extreme sea-level changes, floods, and shoreline erosion. Also, land loss as a result of disturbance of shoreline is of interest as it damages properties and infrastructure. Using a nonlinear autoregressive network with an exogenous input (NARX) model, this study attempted to simulate (1991 to 2012) and predict (2013-2020) sea-level change along Merang kechil to Kuala Marang in Terengganu state shoreline areas. The simulation results show a rising trend with a maximum rate of 28.73 mm/year and an average of about 8.81 mm/year. In comparison, the prediction results show a rising sea level with a maximum rate of 79.26 mm/year and an average of about 25.34 mm/year. The database generated from this study can be used to inform shoreline defense strategies adapting to sea-level rise, flood, and erosion. Scientists can forecast sea-level increases beyond 2020 using simulated sea-level data up to 2020 and apply it for future research. The data also helps decision-makers choose measures for vulnerable shoreline settlements to adapt to sea-level rise. Notably, the data will provide essential information for policy development and implementation to facilitate operational decision-making processes for coastal cities.

Matched MeSH terms: Floods*
Flooding tolerance in Rice: adaptive mechanism and marker-assisted selection breeding approaches

Haque MA, Rafii MY, Yusoff MM, Ali NS, Yusuff O, Arolu F, et al.

Mol Biol Rep, 2023 Mar;50(3):2795-2812.
PMID: 36592290 DOI: 10.1007/s11033-022-07853-9

Natural and man-made ecosystems worldwide are subjected to flooding, which is a form of environmental stress. Genetic variability in the plant response to flooding involves variations in metabolism, architecture, and elongation development that are related with a low oxygen escape strategy and an opposing quiescence scheme that enables prolonged submergence endurance. Flooding is typically associated with a decrease in O2 in the cells, which is especially severe when photosynthesis is absent or limited, leading to significant annual yield losses globally. Over the past two decades, considerable advancements have been made in understanding of mechanisms of rice adaptation and tolerance to flooding/submergence. The mapping and identification of Sub1 QTL have led to the development of marker-assisted selection (MAS) breeding approach to improve flooding-tolerant rice varieties in submergence-prone ecosystems. The Sub1 incorporated in rice varieties showed tolerance during flash flood, but not during stagnant conditions. Hence, gene pyramiding techniques can be applied to combine/stack multiple resistant genes for developing flood-resilient rice varieties for different types of flooding stresses. This review contains an update on the latest advances in understanding the molecular mechanisms, metabolic adaptions, and genetic factors governing rice flooding tolerance. A better understanding of molecular genetics and adaptation mechanisms that enhance flood-tolerant varieties under different flooding regimes was also discussed.

Matched MeSH terms: Floods
Adaptation measures under the impacts of climate and land-use/land-cover changes using HSPF model simulation: Application to Gongola river basin, Nigeria

Salaudeen A, Shahid S, Ismail A, Adeogun BK, Ajibike MA, Bello AD, et al.

Sci Total Environ, 2023 Feb 01;858(Pt 2):159874.
PMID: 36334669 DOI: 10.1016/j.scitotenv.2022.159874

Recently, there is an upsurge in flood emergencies in Nigeria, in which their frequencies and impacts are expected to exacerbate in the future due to land-use/land cover (LULC) and climate change stressors. The separate and combined forces of these stressors on the Gongola river basin is feebly understood and the probable future impacts are not clear. Accordingly, this study uses a process-based watershed modelling approach - the Hydrological Simulation Program FORTRAN (HSPF) (i) to understand the basin's current and future hydrological fluxes and (ii) to quantify the effectiveness of five management options as adaptation measures for the impacts of the stressors. The ensemble means of the three models derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5) are employed for generating future climate scenarios, considering three distinct radiative forcing peculiar to the study area. Also, the historical and future LULC (developed from the hybrid of Cellular Automata and Markov Chain model) are used to produce the LULC scenarios for the basin. The effective calibration, uncertainty and sensitivity analyses are used for optimising the parameters of the model and the validated result implies a plausible model with efficiency of up to 75 %. Consequently, the results of individual impacts of the stressors yield amplification of the peak flows, with more profound impacts from climate stressor than the LULC. Therefore, the climate impact may trigger a marked peak discharge that is 48 % higher as compared to the historical peak flows which are equivalent to 10,000-year flood event. Whilst the combine impacts may further amplify this value by 27 % depending on the scenario. The proposed management interventions such as planned reforestation and reservoir at Dindima should attenuate the disastrous peak discharges by almost 36 %. Furthermore, the land management option should promote the carbon-sequestering project of the Paris agreement ratified by Nigeria. While the reservoir would serve secondary functions of energy production; employment opportunities, aside other social aspects. These measures are therefore expected to mitigate feasibly the negative impacts anticipated from the stressors and the approach can be employed in other river basins in Africa confronted with similar challenges.

Matched MeSH terms: Floods
Fulltext A novel framework for addressing uncertainties in machine learning-based geospatial approaches for flood prediction

Adnan MSG, Siam ZS, Kabir I, Kabir Z, Ahmed MR, Hassan QK, et al.

J Environ Manage, 2023 Jan 15;326(Pt B):116813.
PMID: 36435143 DOI: 10.1016/j.jenvman.2022.116813

Globally, many studies on machine learning (ML)-based flood susceptibility modeling have been carried out in recent years. While majority of those models produce reasonably accurate flood predictions, the outcomes are subject to uncertainty since flood susceptibility models (FSMs) may produce varying spatial predictions. However, there have not been many attempts to address these uncertainties because identifying spatial agreement in flood projections is a complex process. This study presents a framework for reducing spatial disagreement among four standalone and hybridized ML-based FSMs: random forest (RF), k-nearest neighbor (KNN), multilayer perceptron (MLP), and hybridized genetic algorithm-gaussian radial basis function-support vector regression (GA-RBF-SVR). Besides, an optimized model was developed combining the outcomes of those four models. The southwest coastal region of Bangladesh was selected as the case area. A comparable percentage of flood potential area (approximately 60% of the total land areas) was produced by all ML-based models. Despite achieving high prediction accuracy, spatial discrepancy in the model outcomes was observed, with pixel-wise correlation coefficients across different models ranging from 0.62 to 0.91. The optimized model exhibited high prediction accuracy and improved spatial agreement by reducing the number of classification errors. The framework presented in this study might aid in the formulation of risk-based development plans and enhancement of current early warning systems.

Matched MeSH terms: Floods*
Fulltext Hydrological Analysis of Batu Dam, Malaysia in the Urban Area: Flood and Failure Analysis Preparing for Climate Change

Allias Omar SM, Wan Ariffin WNH, Mohd Sidek L, Basri H, Moh Khambali MH, Ahmed AN

Int J Environ Res Public Health, 2022 Dec 09;19(24).
PMID: 36554413 DOI: 10.3390/ijerph192416530

Extensive hydrological analysis is carried out to estimate floods for the Batu Dam, a hydropower dam located in the urban area upstream of Kuala Lumpur, Malaysia. The study demonstrates the operational state and reliability of the dam structure based on hydrologic assessment of the dam. The surrounding area is affected by heavy rainfall and climate change every year, which increases the probability of flooding and threatens a dense population downstream of the dam. This study evaluates the adequacy of dam spillways by considering the latest Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) values of the concerned dams. In this study, the PMP estimations are applied using comparison of both statistical method by Hershfield and National Hydraulic Research Institute of Malaysia (NAHRIM) Envelope Curve as input for PMF establishments. Since the PMF is derived from the PMP values, the highest design flood standard can be applied to any dam, ensuring inflow into the reservoirs and limiting the risk of dam structural failure. Hydrologic modeling using HEC-HMS provides PMF values for the Batu dam. Based on the results, Batu Dam is found to have 200.6 m3/s spillway discharge capacities. Under PMF conditions, the Batu dam will not face overtopping since the peak outflow of the reservoir level is still below the crest level of the dam.

Matched MeSH terms: Floods*
Fulltext Understanding human vulnerability to climate change: A global perspective on index validation for adaptation planning

Birkmann J, Jamshed A, McMillan JM, Feldmeyer D, Totin E, Solecki W, et al.

Sci Total Environ, 2022 Jan 10;803:150065.
PMID: 34525713 DOI: 10.1016/j.scitotenv.2021.150065

Climate change is a severe global threat. Research on climate change and vulnerability to natural hazards has made significant progress over the last decades. Most of the research has been devoted to improving the quality of climate information and hazard data, including exposure to specific phenomena, such as flooding or sea-level rise. Less attention has been given to the assessment of vulnerability and embedded social, economic and historical conditions that foster vulnerability of societies. A number of global vulnerability assessments based on indicators have been developed over the past years. Yet an essential question remains how to validate those assessments at the global scale. This paper examines different options to validate global vulnerability assessments in terms of their internal and external validity, focusing on two global vulnerability indicator systems used in the WorldRiskIndex and the INFORM index. The paper reviews these global index systems as best practices and at the same time presents new analysis and global results that show linkages between the level of vulnerability and disaster outcomes. Both the review and new analysis support each other and help to communicate the validity and the uncertainty of vulnerability assessments. Next to statistical validation methods, we discuss the importance of the appropriate link between indicators, data and the indicandum. We found that mortality per hazard event from floods, drought and storms is 15 times higher for countries ranked as highly vulnerable compared to those classified as low vulnerable. These findings highlight the different starting points of countries in their move towards climate resilient development. Priority should be given not just to those regions that are likely to face more severe climate hazards in the future but also to those confronted with high vulnerability already.

Matched MeSH terms: Floods
Fulltext Facing flood disaster: A cluster randomized trial assessing communities' knowledge, skills and preparedness utilizing a health model intervention

Mhd Noor MT, Kadir Shahar H, Baharudin MR, Syed Ismail SN, Abdul Manaf R, Md Said S, et al.

PLoS One, 2022;17(11):e0271258.
PMID: 36441735 DOI: 10.1371/journal.pone.0271258

Floods occur when a body of water overflows and submerges normally dry terrain. Tropical cyclones or tsunamis cause flooding. Health and safety are jeopardized during a flood. As a result, proactive flood mitigation measures are required. This study aimed to increase flood disaster preparedness among Selangor communities in Malaysia by implementing a Health Belief Model-Based Intervention (HEBI). Selangor's six districts were involved in a single-blinded cluster randomized controlled trial Community-wide implementation of a Health Belief Model-Based Intervention (HEBI). A self-administered questionnaire was used. The intervention group received a HEBI module, while the control group received a health talk on non-communicable disease. The baseline variables were compared. Immediate and six-month post-intervention impacts on outcome indicators were assessed. 284 responses with a 100% response rate. At the baseline, there were no significant differences in ethnicity, monthly household income, or past disaster experience between groups (p>0.05). There were significant differences between-group for intervention on knowledge, skills, preparedness (p<0.001), Perceived Benefit Score (p = 0.02), Perceived Barrier Score (p = 0.03), and Cues to Action (p = 0.04). GEE analysis showed receiving the HEBI module had effectively improved knowledge, skills, preparedness, Perceived Benefit Score, Perceived Barrier Score, and Cues to Action in the intervention group after controlling the covariate. Finally, community flood preparedness ensured that every crisis decision had the least impact on humans. The HEBI module improved community flood preparedness by increasing knowledge, skill, preparedness, perceived benefit, perceived barrier, and action cues. As a result, the community should be aware of this module. Clinical trial registration: The trial registry name is Thai Clinical Trials Registry, trial number TCTR20200202002.

Matched MeSH terms: Floods
Impacts of droughts and floods on croplands and crop production in Southeast Asia - An application of Google Earth Engine

Venkatappa M, Sasaki N, Han P, Abe I

Sci Total Environ, 2021 Nov 15;795:148829.
PMID: 34252779 DOI: 10.1016/j.scitotenv.2021.148829

While droughts and floods have intensified in recent years, only a handful of studies have assessed their impacts on croplands and production in Southeast Asia. Here, we used the Google Earth Engine to assess the droughts and floods and their impacts on croplands and crop production over 40 years from 1980 to 2019. Using the Palmer Drought Severity Index (PDSI) as the basis for determining the drought and flood levels, and crop damage levels, crop production loss in both the Monsoon Climate Region (MCR) and the Equatorial Climate Region (ECR) of Southeast Asia was assessed over 47,192 grid points with 10 × 10-kilometer resolution. We found that rainfed crops were severely affected by droughts in the MCR and floods in the ECR. About 9.42 million ha and 3.72 million ha of cropland was damaged by droughts and floods, respectively. We estimated a total loss of 20.64 million tons of crop production between 2015 and 2019. Rainfed crops in Thailand, Cambodia, and Myanmar were strongly affected by droughts, whereas Indonesia, the Philippines, and Malaysia were more affected by floods over the same period. Accordingly, four levels of policy interventions were prioritized by considering the geolocated crop damage levels.

Matched MeSH terms: Floods*
A review of the impacts of dams on the hydromorphology of tropical rivers

Chong XY, Vericat D, Batalla RJ, Teo FY, Lee KSP, Gibbins CN

Sci Total Environ, 2021 Nov 10;794:148686.
PMID: 34218154 DOI: 10.1016/j.scitotenv.2021.148686

A major programme of dam building is underway in many of the world's tropical countries. This raises the question of whether existing research is sufficient to fully understand the impacts of dams on tropical river systems. This paper provides a systematic review of what is known about the impacts of dams on river flows, sediment dynamics and geomorphic processes in tropical rivers. The review was conducted using the SCOPUS® and Web of Science® databases, with papers analysed to look for temporal and geographic patterns in published work, assess the approaches used to help understand dam impacts, and assess the nature and magnitude of impacts on the flow regimes and geomorphology ('hydromorphology') of tropical rivers. As part of the review, a meta-analysis was used to compare key impacts across different climate regions. Although research on tropical rivers remains scarce, existing work is sufficient to allow us to draw some very broad, general conclusions about the nature of hydromorphic change: tropical dams have resulted in reductions in flow variability, lower flood peaks, reductions in sediment supply and loads, and complex geomorphic adjustments that include both channel incision and aggradation at different times and downstream distances. At this general level, impacts are consistent with those observed in other climate regions. However, studies are too few and variable in their focus to determine whether some of the more specific aspects of change observed in tropical rivers (e.g. time to reach a new, adjusted state, and downstream recovery distance) differ consistently from those in other regions. The review helps stress the need for research that incorporates before-after comparisons of flow and geomorphic conditions, and for the wider application of tools available now for assessing hydromorphic change. Very few studies have considered hydromorphic processes when designing flow operational policies for tropical dams.

Matched MeSH terms: Floods
Mapping flood by the object-based method using backscattering coefficient and interference coherence of Sentinel-1 time series

Zhang X, Chan NW, Pan B, Ge X, Yang H

Sci Total Environ, 2021 Nov 10;794:148388.
PMID: 34217078 DOI: 10.1016/j.scitotenv.2021.148388

The SAR has the ability of all-weather and all-time data acquisition, it can penetrate the cloud and is not affected by extreme weather conditions, and the acquired images have better contrast and rich texture information. This paper aims to investigate the use of an object-oriented classification approach for flood information monitoring in floodplains using backscattering coefficients and interferometric coherence of Sentinel-1 data under time series. Firstly, the backscattering characteristics and interference coherence variation characteristics of SAR time series are used to analyze whether the flood disaster information can be accurately reflected and provide the basis for selecting input classification characteristics of subsequent SAR images. Subsequently, the contribution rate index of the RF model is used to calculate the importance of each index in time series to convert the selected large number of classification features into low dimensional feature space to improve the classification accuracy and reduce the data redundancy. Finally, the SAR image features in each period after multi-scale segmentation and feature selection are jointly used as the input features of RF classification to extract and segment the water in the study area to monitor floods' spatial distribution and dynamic characteristics. The results showed that the various attributes of backscatter coefficients and interferometric coherence under time series could accurately correspond with the actual flood risk, and the combined use of backscattering coefficient and interferometric coherence for flood extraction can significantly improve the accuracy of flood information extraction. Overall, the object-based random forest method using the backscattering coefficient and interference coherence of Sentinel-1 time series for flood extraction advances our understanding of flooding's temporal and spatial dynamics, essential for the timely adoption of adaptation and mitigation strategies for loss reduction.

Matched MeSH terms: Floods*
Fulltext A cluster-randomized trial study on effectiveness of health education based intervention (HEBI) in improving flood disaster preparedness among community in Selangor, Malaysia: a study protocol

Mohd Tariq MN, Shahar HK, Baharudin MR, Ismail SNS, Manaf RA, Salmiah MS, et al.

BMC Public Health, 2021 09 24;21(1):1735.
PMID: 34560858 DOI: 10.1186/s12889-021-11719-3

BACKGROUND: Flood disaster preparedness among the community seldom received attention. Necessary intervention must be taken to prevent the problem. Health Education Based Intervention (HEBI) was developed following the Health Belief Model, particularly in improving flood disaster preparedness among the community. The main objective of this study is to assess the effect of HEBI on improving flood disaster preparedness among the community in Selangor. This study aims to develop, implement, and evaluate the impact of health education-based intervention (HEBI) based on knowledge, skills, and preparedness to improve flood disaster preparedness among the community in Selangor.
METHOD: A single-blind cluster randomized controlled trial will conduct at six districts in Selangor. Randomly selected respondents who fulfilled the inclusion criteria will be invited to participate in the study. Health education module based on Health Believed Theory will be delivered via health talks and videos coordinated by liaison officers. Data at three-time points at baseline, immediate, and 3 months post-intervention will be collected. A validated questionnaire will assess participants' background characteristics, knowledge, skill, and preparedness on disaster preparedness and perception towards disaster. Descriptive and inferential statistics will be applied for data analysis using IBM Statistical Package for Social Sciences version 25. Longitudinal correlated data on knowledge, skills, preparedness, and perception score at baseline, immediate post-intervention, and 6 months post-intervention will be analyzed using Generalized Estimating Equations (GEE).
DISCUSSION: It is expected that knowledge, skills, preparedness, and flood disaster perception score are more significant in the intervention group than the control group, indicating the Health Education Based Intervention (HEBI).
TRIAL REGISTRATION: Thai Clinical Trial TCTR20200202002 .

Matched MeSH terms: Floods*
The influence of ecosystems services depletion to climate change adaptation efforts in Africa

Leal Filho W, Azeiteiro UM, Balogun AL, Setti AFF, Mucova SAR, Ayal D, et al.

Sci Total Environ, 2021 Jul 20;779:146414.
PMID: 33735656 DOI: 10.1016/j.scitotenv.2021.146414

Climate change is one of the major challenges societies round the world face at present. Apart from efforts to achieve a reduction of emissions of greenhouse gases so as to mitigate the problem, there is a perceived need for adaptation initiatives urgently. Ecosystems are known to play an important role in climate change adaptation processes, since some of the services they provide, may reduce the impacts of extreme events and disturbance, such as wildfires, floods, and droughts. This role is especially important in regions vulnerable to climate change such as the African continent, whose adaptation capacity is limited by many geographic and socio-economic constraints. In Africa, interventions aimed at enhancing ecosystem services may play a key role in supporting climate change adaptation efforts. In order to shed some light on this aspect, this paper reviews the role of ecosystems services and investigates how they are being influenced by climate change in Africa. It contains a set of case studies from a sample of African countries, which serve the purpose to demonstrate the damages incurred, and how such damages disrupt ecosystem services. Based on the data gathered, some measures which may assist in fostering the cause of ecosystems services are listed, so as to cater for a better protection of some of the endangered Africa ecosystems, and the services they provide.

Matched MeSH terms: Floods
Fulltext Evidence-informed policy for tackling adverse climate change effects on health: Linking regional and global assessments of science to catalyse action

Fears R, Abdullah KAB, Canales-Holzeis C, Caussy D, Haines A, Harper SL, et al.

PLoS Med, 2021 Jul;18(7):e1003719.
PMID: 34283834 DOI: 10.1371/journal.pmed.1003719

Robin Fears and co-authors discuss evidence-informed regional and global policy responses to health impacts of climate change.

Matched MeSH terms: Floods
Assessment of health risks and individuals' willingness to participate in drinking water management at flood-prone Pahang River Basin, Malaysia

Alam L, Rahman LF, Ahmed MF, Bari MA, Masud MM, Mokhtar MB

Environ Geochem Health, 2021 May;43(5):2049-2063.
PMID: 33389458 DOI: 10.1007/s10653-020-00783-0

Rivers, the main source of the domestic water supply in Malaysia, have been threatened by frequent flooding in recent years. This study aims to assess human health risks associated with exposure to concentrated heavy metals in a flood-prone region of Malaysia and investigate the affected individuals' willingness to participate in managing water resources. Hazard indices and cancer risks associated with water contamination by heavy metals have been assessed following the method prescribed by the US Environmental Protection Agency. Yearly data of heavy metal contamination (Cd, Cr, Pb, Zn, Fe), water quality parameters (DO, BOD, COD, pH), and climatic information (annual rainfall, annual temperature) have been collected from the Department of Environment and Meteorological Department of Malaysia, respectively. The inductively coupled plasma mass spectrometry technique has been used by the department of environment for analyzing heavy metal concentration in river water samples. In this study, data from a stratified random sample of households in the affected region were analyzed, using partial least squares structural equation modeling, to predict the link between individuals' perceptions and attitudes about water resources and their willingness to engage in water management program. The health risk estimation indicated that the hazard index values were below the acceptable limit, representing no non-carcinogenic risk to adults and children residing in the study area via oral intake and dermal adsorption of water. However, the calculated value for cancer risk signified possible carcinogenic risks associated with Pb and Cd. In general, contamination due to pollution and flooding tends to increase in the basin region, and appropriate management is needed. The results identified perceived water quality as a significant factor influencing people's attitudes toward involvement in water management programs. As in many developing countries, there is no legal provision guaranteeing public representation in water management in Malaysia. The conclusion discusses the importance of these for the literature and for informing future policy actions.

Matched MeSH terms: Floods

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