Displaying publications 1 - 20 of 120 in total

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  1. 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*
  2. Syed Musa SMS, Md Noorani MS, Abdul Razak F, Ismail M, Alias MA, Hussain SI
    Int J Environ Res Public Health, 2020 Aug 24;17(17).
    PMID: 32846870 DOI: 10.3390/ijerph17176131
    The theory of critical slowing down (CSD) suggests an increasing pattern in the time series of CSD indicators near catastrophic events. This theory has been successfully used as a generic indicator of early warning signals in various fields, including climate research. In this paper, we present an application of CSD on water level data with the aim of producing an early warning signal for floods. To achieve this, we inspect the trend of CSD indicators using quantile estimation instead of using the standard method of Kendall's tau rank correlation, which we found is inconsistent for our data set. For our flood early warning system (FLEWS), quantile estimation is used to provide thresholds to extract the dates associated with significant increases on the time series of the CSD indicators. We apply CSD theory on water level data of Kelantan River and found that it is a reliable technique to produce a FLEWS as it demonstrates an increasing pattern near the flood events. We then apply quantile estimation on the time series of CSD indicators and we manage to establish an early warning signal for ten of the twelve flood events. The other two events are detected on the first day of the flood.
    Matched MeSH terms: Floods*
  3. Abdelhaq M, Alsaqour R, Abdelhaq S
    PLoS One, 2015;10(5):e0120715.
    PMID: 25946001 DOI: 10.1371/journal.pone.0120715
    A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs.
    Matched MeSH terms: Floods*
  4. 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*
  5. 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*
  6. 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*
  7. 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*
  8. 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*
  9. Kabirzad SA, Rehan BM, Zulkafli Z, Yusuf B, Hasan-Basri B, Toriman ME
    Water Sci Technol, 2024 Jul;90(1):142-155.
    PMID: 39007311 DOI: 10.2166/wst.2024.202
    Investment to reduce flood risk for social and economic wellbeing requires quantitative evidence to guide decisions. Direct and indirect flood damages at individual household and business building levels were assessed in this study using multivariate analysis with three groups of flood damage attributes, i.e., flood characteristics, socioeconomic conditions, and building types. A total of 172 and 45 respondents from residential and commercial buildings were gathered through door-to-door interviews at areas in Peninsular Malaysia that were pre-identified to have frequently flooded. Two main findings can be drawn from this study. First, flood damage is greatly contributed by high-income households and businesses, despite them being less exposed to floods than low-income earners. This supports the current use of mean economic damage in engineering-based flood intervention analysis. Second, indirect damages increase with the increase in family size, indicating the importance of strengthening preparedness and social support to those with great social responsibility. Overall, the study highlights the importance of holistic flood management accounting for both direct and indirect losses.
    Matched MeSH terms: Floods*
  10. 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*
  11. 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
  12. 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*
  13. Keya TA, Balakrishnan SS, Solayappan M, Dheena Dhayalan SS, Subramaniam S, An LJ, et al.
    PLoS One, 2024;19(11):e0310435.
    PMID: 39509412 DOI: 10.1371/journal.pone.0310435
    Malaysia, particularly Pahang, experiences devastating floods annually, causing significant damage. The objective of the research was to create a flood susceptibility map for the designated area by employing an Ensemble Machine Learning (EML) algorithm based on geographic information system (GIS). By analyzing nine key factors from a geospatial database, flood susceptibility map was created with the ArcGIS software (ESRI ArcGIS Pro v3.0.1 x64). The Random Forest (RF) model was employed in this study to categorize the study area into distinct flood susceptibility classes. The Feature selection (FS) method was used to ranking the flood influencing factors. To validate the flood susceptibility models, standard statistical measures and the Area Under the Curve (AUC) were employed. The FS ranking demonstrated that the primary attributes to flooding in the study region are rainfall and elevation, with slope, geology, curvature, flow accumulation, flow direction, distance from the river, and land use/land cover (LULC) patterns ranking subsequently. The categories of 'very high' and 'high' class collectively made up 37.1% and 26.3% of the total area, respectively. The flood vulnerability assessment of Pahang found that the Eastern, Southern, and central regions were at high risk of flooding due to intense precipitation, low-lying topography with steep inclines, proximity to the shoreline and rivers, and abundant flooded vegetation, crops, urban areas, bare ground, and rangeland. Conversely, areas with dense tree canopies or forests were less susceptible to flooding in this research area. The ROC analysis demonstrated strong performance on the validation datasets, with an AUC value of >0.73 and accuracy scores exceeding 0.71. Research on flood susceptibility mapping can enhance risk reduction strategies and improve flood management in vulnerable areas. Technological advancements and expertise provide opportunities for more sophisticated methods, leading to better prepared and resilient communities.
    Matched MeSH terms: Floods*
  14. 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*
  15. Mohd Radi MF, Hashim JH, Jaafar MH, Hod R, Ahmad N, Mohammed Nawi A, et al.
    Am J Trop Med Hyg, 2018 05;98(5):1281-1295.
    PMID: 29532771 DOI: 10.4269/ajtmh.16-0922
    Severe floods increase the risk of leptospirosis outbreaks in endemic areas. This study determines the spatial-temporal distribution of leptospirosis in relation to environmental factors after a major flooding event in Kelantan, Malaysia. We conducted an observational ecological study involving incident leptospirosis cases, from the 3 months before, during, and three months after flood, in reference to the severe 2014 Kelantan flooding event. Geographical information system was used to determine the spatial distribution while climatic factors that influenced the cases were also analyzed. A total of 1,229 leptospirosis cases were notified within the three study periods where incidence doubled in the postflood period. Twelve of 66 subdistricts recorded incidence rates of over 100 per 100,000 population in the postflood period, in comparison with only four subdistricts in the preflooding period. Average nearest neighborhood analysis indicated that the cases were more clustered in the postflood period as compared with the preflood period, with observed mean distance of 1,139 meters and 1,666 meters, respectively (both at P < 0.01). Global Moran's I was higher in the postflood period (0.19; P < 0.01) as compared with the preflood period (0.06; P < 0.01). Geographic weighted regression showed that living close to water bodies increased the risk of contracting the disease. Postflooding hotspots were concentrated in areas where garbage cleanup occurred and the incidence was significantly associated with temperature, humidity, rainfall, and river levels. Postflooding leptospirosis outbreak was associated with several factors. Understanding the spatial distribution and associated factors of leptospirosis can help improve future disease outbreak management after the floods.
    Matched MeSH terms: Floods*
  16. Shariff NNM, Hamidi ZS
    Jamba, 2019;11(1):598.
    PMID: 30863510 DOI: 10.4102/jamba.v11i1.598
    Floods have caused inevitable major disasters around the world as well as in Malaysia. This paper demonstrates that lessons can be taken from the previous flood disasters when developing an effective flood preparedness plan. As a common practice, disaster management is based on a top-down approach or is government-centred. This article attempts to highlight the significance of developing a flood preparedness plan by involving the communities affected. Qualitative analysis was adopted in order to gain in-depth insight of the communities. Two flood-prone communities were chosen: (1) Machang, Kelantan; and (2) Kuala Lipis, Pahang. There were two important things executed by the community for the preparation: (1) community-based disaster risk management; and (2) intensive mutual assistance.
    Matched MeSH terms: Floods
  17. Bong, C.H.J., Mah, D.Y.S, Putuhena, F.J., Said, S., Bustami, R.A.
    ASM Science Journal, 2012;6(1):47-60.
    MyJurnal
    Hydraulics simulation can be used as a supporting tool for planning and developing a framework, such as Integrated Flood Management for river management. To demonstrate this, a hydraulics model for the Sarawak River Basin was run using InfoWorks RS software by Wallingford Software, UK. InfoWorks River Simulation (RS) was chosen because its applicability has been proven and widely used to model Malaysian rivers. The extraction of computed floodwater level and flood maps for different time intervals would produce the rate of floodplain submergence from river bank level. This information could be incorporated into a logical framework to support decisions on flood management measures. Thus, hydraulics models can be used as tools to provide the necessary decision parameters for developing logical frameworks which would act as to guide the planning when it involved various stakeholders’ participation.
    Matched MeSH terms: Floods
  18. Kmil, D., Baesah, G., Dewi Mumi, M.Y.
    MyJurnal
    Flooding is the most frequent of all natural disasters. A flood is any water flow that exceeds the capacity of the drainage system and usually subsides in relatively shorter period. However, the flood that hit Batu Pahat District were different from other districts. Batu Pahat flooding extended for 48 days from the first wave until it subsided fully. It gives positive and negative effects not only to the victims but also to the health care workers (HCWs) while executing their duties during and post flood. This write up aims to share HCW’s experience and voices from those who were involved in the flood disaster. Methods used are brainstorming sessions, discussion, observation and interview. From this study, 10 main themes were highlighted. This flood disaster has given the HCWs to prepare mentally, physically and increase knowledge and skills to face any disaster in the future.
    Matched MeSH terms: Floods
  19. Alaghmand, S., Abdullah, R., Abustan, I., Vosoogh, B.
    MyJurnal
    As a crucial demand in urban areas, flood risk management has been considered by researchers and decision makers around the world. In this case, hydrological modelling that simulates rainfall-runoff process plays a significant role. This paper quantified the roles of three main parameters in river basin hydrological response, namely, rainfall event duration, rainfall event ARI (magnitude) and land-use development condition. The case study area of this research was Sungai Kayu Ara basin which is located in the western part of Kuala Lumpur, Malaysia. A total of twenty seven scenario were defined for this research, including three different rainfall event durations (60, 120 and 360 minutes), three different ARIs (20, 50 and 100 years) and in three different land-use conditions (existing, intermediate and ultimate). The results of this research indicate that rainfall event duration, rainfall event ARI (magnitude) and land-use development condition have considerable effects of the surface runoff hydrographs in terms of peak discharge and volume.
    Matched MeSH terms: Floods
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