Search results for: flood forecast

Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

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This research was conducted in the Mae Sot Watershed whereas located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urbanized in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recently years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood event in 2013 as the worst studied case for those all communities in this municipality. Moreover, other problems are also faced in this watershed such shortage water supply for domestic consumption and agriculture utilizations including deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of appropriated application of some short period rainfall forecasting model as the aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in short period of 7 - 10 days in advance during rainy season instead of real time record. The IDV product can be present in advance period of rainfall with time step of 3 - 6 hours was introduced to the communities. The result can be used to input to either the hydrologic modeling system model (HEC-HMS) or the soil water assessment tool model (SWAT) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfied. The result of IDV’s rainfall forecast data was compared to observed data and found fair. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: global rainfall, flood forecast, hydrologic modeling system, river analysis system

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Authors: Kashif Hassan, M.A. Ahanger

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Floods have become more frequent and severe due to effects of global climate change and human alterations of the natural environment. Flood prediction/ forecasting and control is one of the greatest challenges facing the world today. The forecast of floods is achieved by the use of hydraulic models such as HEC-RAS, which are designed to simulate flow processes of the surface water. Extreme flood events in river Jhelum , lasting from a day to few are a major disaster in the State of Jammu and Kashmir, India. In the present study HEC-RAS model was applied to two different reaches of river Jhelum in order to estimate the flood levels corresponding to 25, 50 and 100 year return period flood events at important locations and to deduce flood vulnerability of important areas and structures. The flow rates for the two reaches were derived from flood-frequency analysis of 50 years of historic peak flow data. Manning's roughness coefficient n was selected using detailed analysis. Rating Curves were also generated to serve as base for determining the boundary conditions. Calibration and Validation procedures were applied in order to ensure the reliability of the model. Sensitivity analysis was also performed in order to ensure the accuracy of Manning's n in generating water surface profiles.

Keywords: flood plain, HEC-RAS, Jhelum, return period

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Authors: A. L. Qureshi, A. A. Mahessar, A. Baloch

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Flood wave propagation in river channel flow can be enunciated by nonlinear equations of motion for unsteady flow. However, it is difficult to find analytical solution of these complex non-linear equations. Hence, verification of the numerical model should be carried out against field data and numerical predictions. This paper presents the verification of developed finite element model applying for unsteady flow in the open channels. The results of a proposed model indicate a good matching with both Preissmann scheme and HEC-RAS model for a river reach of 29 km at both sites (15 km from upstream and at downstream end) for discharge hydrographs. It also has an agreeable comparison with the Preissemann scheme for the flow depth (stage) hydrographs. The proposed model has also been applying to forecast daily discharges at 400 km downstream from Sukkur barrage, which demonstrates accurate model predictions with observed daily discharges. Hence, this model may be utilized for predicting and issuing flood warnings about flood hazardous in advance.

Keywords: finite element method, Preissmann scheme, HEC-RAS, flood forecasting, Indus river

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Authors: Albert Acheampong, Tamer Elshandidy

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We investigate the extent to which sustainability disclosure from the narrative section of European banks’ annual reports improves analyst forecast accuracy. We capture sustainability disclosure using a machine learning approach and use forecast error to proxy analyst forecast accuracy. Our results suggest that sustainability disclosure significantly improves analyst forecast accuracy by reducing the forecast error. In a further analysis, we also find that the induction of Directive 2014/95/European Union (EU) is associated with increased disclosure content, which then reduces forecast error. Collectively, our results suggest that sustainability disclosure improves forecast accuracy, and the induction of the new EU directive strengthens this improvement. These results hold after several further and robustness analyses. Our findings have implications for market participants and policymakers.

Keywords: sustainability disclosure, machine learning, analyst forecast accuracy, forecast error, European banks, EU directive

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Authors: Karl-Erich Lindenschmidt, Apurba Das, Joel Trudell, Keanne Russell

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In this presentation, we explore options for mitigating ice-jam flooding along the Athabasca River in western Canada. Not only flood hazard, expressed in this case as the probability of flood depths and extents being exceeded, but also flood risk, in which annual expected damages are calculated. Flood risk is calculated, which allows a cost-benefit analysis to be made so that decisions on the best mitigation options are not based solely on flood hazard but also on the costs related to flood damages and the benefits of mitigation. The river ice model is used to simulate extreme ice-jam flood events with which scenarios are run to determine flood exposure and damages in flood-prone areas along the river. We will concentrate on three mitigation options – the placement of a dike, artificial breakage of the ice cover along the river, the installation of an ice-control structure, and the construction of a reservoir. However, any mitigation option is not totally failsafe. For example, dikes can still be overtopped and breached, and ice jams may still occur in areas of the river where ice covers have been artificially broken up. Hence, for all options, it is recommended that zoning of building developments away from greater flood hazard areas be upheld. Flood mitigation can have a negative effect of giving inhabitants a false sense of security that flooding may not happen again, leading to zoning policies being relaxed. (Text adapted from Lindenschmidt [2022] "Ice Destabilization Study - Phase 2", submitted to the Regional Municipality of Wood Buffalo, Alberta, Canada)

Keywords: ice jam, flood hazard, flood risk river ice modelling, flood risk

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Authors: Nguyen Quang Kim, Nguyen Thu Hien, Nguyen Thien Dung

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Flood disasters are increasing worldwide in both frequency and magnitude. Every year in Vietnam, flood causes great damage to people, property, and environmental degradation. The flood risk management policy in Vietnam is currently updated. The planning of flood mitigation strategies is reviewed to make a decision how to reach sustainable flood risk reduction. This paper discusses the basic approach where the measures of flood protection are chosen based on minimizing the present value of expected monetary expenses, total residual risk and costs of flood control measures. This approach will be proposed and demonstrated in a case study for flood risk management in Vinh Phuc province of Vietnam. Research also proposed the framework to find a solution of optimal protection level and optimal measures of the flood. It provides an explicit economic basis for flood risk management plans and interactive effects of options for flood damage reduction. The results of the case study are demonstrated and discussed which would provide the processing of actions helped decision makers to choose flood risk reduction investment options.

Keywords: drainage plan, flood planning, flood risk, residual risk, risk optimization

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Authors: Sapora Sipon, Mohd Fo’ad Sakdan, Che Su Mustaffa, Najib Ahmad Marzuki, Mohamad Sukeri Khalid, Mohd Taib Ariffin, Husni Mohd Radzi, Salhah Abdullah

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Flood disasters occur throughout the world including Malaysia. The major flood disaster that hit Malaysia in the 2014-2015 episodes proved the psychosocial and mental health consequences such as vivid images of destruction, upheaval, death and loss of lives. Flood, flood survivors reported that flood has changed one looks at their religious belief. The main objective of this paper is to investigate the changes in religious belief after the 2014-2015 Malaysia flood disaster. The total population of 1300 respondents who experienced the 2014-2015 Malaysia flood were surveyed a month after the disaster. The questionnaires were used to measure religiosity and stress. The results provide compelling evidence that religion played an important role in the lives of Malaysia flood disasters’ survivor where more than half of the respondents (>75%) experiencing the strengthening of their religious belief. It was also reported the victims’ strengthening of their religious belief proved to be a powerful factor in reducing stress in the aftermath of the flood.

Keywords: religious belief, flood disaster, humanity, society

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Authors: Alagie Salieu Nankey

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Flood-resistant house is the key mechanism to withstand flood hazards in Ebo-Town. It emerged simple yet powerful way of mitigating flooding in the community of Ebo- Town. Even though there are different types of buildings, little is known yet how and why flood affects building severely. In this paper, we examine three different types of flood-resistant buildings that are suitable for Ebo Town. We gather content and contextual features from six (6) respondents and used this data set to identify factors that are significantly associated with the flood-resistant house. Moreover, we built a suitable design concept. We found that amongst all the theories studied in the literature study Slit or Elevated House is the most suitable building design in Ebo-Town and Pile foundation is the most appropriate foundation type in the study area. Amongst contextual features, local materials are the most economical materials for the proposed design. This research proposes a framework that explains the theoretical relationships between flood hazard zones and flood-resistant houses in Ebo Town. Moreover, this research informs the design of sense-making and analytics tools for the resistant house.

Keywords: flood-resistant, slit, flood hazard zone, pile foundation

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Authors: Ali Heidari

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This paper presents the principles for improving flood mitigation operation in multipurpose dams and maximizing reservoir performance during flood occurrence with a focus on the real-time operation of gated spillways. The criteria of operation include the safety of dams during flood management, minimizing the downstream flood risk by decreasing the flood hazard and fulfilling water supply and other purposes of the dam operation in mid and long terms horizons. The parameters deemed to be important include flood inflow, outlet capacity restrictions, downstream flood inundation damages, economic revenue of dam operation, and environmental and sedimentation restrictions. A simulation model was used to determine the real-time release of the Dez dam located in the Dez rivers in southwest Iran, considering the gate regulation curves for the gated spillway. The results of the simulation model show that there is a possibility to improve the current procedures used in the real-time operation of the dams, particularly using gate regulation curves and early flood forecasting system results. The Dez dam operation data shows that in one of the best flood control records, % 17 of the total active volume and flood control pool of the reservoir have not been used in decreasing the downstream flood hazard despite the availability of a flood forecasting system.

Keywords: dam operation, flood control criteria, Dez dam, Iran

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Authors: S. Pullteap, M. Pathomsuriyaporn

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In this article, a study of employee’s opinion to the factors that affect to the flood preventive and the corrective action plan in an electronic industry at the Sharp Manufacturing (Thailand) Co., Ltd. has been investigated. The surveys data of 175 workers and supervisors have, however, been selected for data analysis. The results is shown that the employees emphasize about the needs in a subsidy at the time of disaster at high levels of 77.8%, as the plan focusing on flood prevention of the rehabilitation equipment is valued at the intermediate level, which is 79.8%. Demonstration of the hypothesis has found that the different education levels has thus been affected to the needs factor at the flood disaster time. Moreover, most respondents give priority to flood disaster risk management factor. Consequently, we found that the flood prevention plan is valued at high level, especially on information monitoring, which is 93.4% for the supervisor item. The respondents largely assume that the flood will have impacts on the industry, up to 80%, thus to focus on flood management plans is enormous.

Keywords: flood prevention plan, flood event, electronic industrial plant, disaster, risk management

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Dinebari Akpee, Friday Aabe Gaage, Florence Fred Nwaigwu

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Natural disasters like flood affect many parts of the world including developing countries like Nigeria. As a result, many human lives are lost, properties damaged and so much money is lost in infrastructure damages. These hazards and losses can be mitigated and reduced by providing reliable spatial information to the generality of the people through about flood risks through flood inundation maps. Flood inundation maps are very crucial for emergency action plans, urban planning, ecological studies and insurance rates. Nigeria experience her worst flood in her entire history this year. Many cities were submerged and completely under water due to torrential rainfall. Poor city planning, lack of effective development control among others contributes to the problem too. Geographic information system (GIS) can be used to visualize the extent of flooding, analyze flood maps to produce flood damaged estimation maps and flood risk maps. In this research, the under listed steps were taken in preparation of flood risk maps for the study area: (1) Digitization of topographic data and preparation of digital elevation model using ArcGIS (2) Flood simulation using hydraulic model and integration and (3) Integration of the first two steps to produce flood risk maps. The results shows that GIS can play crucial role in Flood disaster control and mitigation.

Keywords: flood disaster, risk maps, geographic information system, hazards

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Authors: Karan Gupta

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The floods cause huge loos each year, and their impact gets manifold with the increase of total duration of flood as well as recession time. Moreover, floods have increased in recent years due to climate change in floodplains. In the context of global climate change, the agreement in Paris convention (2015) stated to keep the increase in global average temperature well below 2°C and keep it at the limit of 1.5°C. Thus, this study investigates the impact of increasing temperature on the stage, discharge as well as total flood duration and recession time in the Meghna River basin in Bangladesh. This study considers the 100-year return period flood flows in the Meghna river under the specific warming levels (SWLs) of 1.5°C, 2°C, and 4°C. The results showed that the rate of increase of duration of flood is nearly 50% lesser at ∆T = 1.5°C as compared to ∆T = 2°C, whereas the rate of increase of duration of recession is 75% lower at ∆T = 1.5°C as compared to ∆T = 2°C. Understanding the change of total duration of flood as well as recession time of the flood gives a better insight to effectively plan for flood mitigation measures.

Keywords: flood, climate change, Paris convention, Bangladesh, inundation duration, recession duration

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Authors: Ayoub El Bourtali, Abdessamed Najine, Amrou Moussa Benmoussa

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It is becoming more and more necessary to manage flood risk, and it must include all stakeholders and all possible means available. The goal of this work is to map the vulnerability of the Oued Derna-region Tagzirt flood zone in the semi-arid region. This is about implementing predictive models and flood control. This allows for the development of flood risk prevention plans. In this study, A resistivity survey was conducted over the area to locate and evaluate soil characteristics in order to calculate discharges and prevent flooding for the study area. The development of a one-dimensional (1D) hydrodynamic model of the Derna River was carried out in HEC-RAS 5.0.4 using a combination of survey data and spatially extracted cross-sections and recorded river flows. The study area was hit by several extreme floods, causing a lot of property loss and loss of life. This research focuses on the most recent flood events, based on the collected data, the water level, river flow and river cross-section were analyzed. A set of flood levels were obtained as the outputs of the hydraulic model and the accuracy of the simulated flood levels and velocity.

Keywords: derna river, 1D hydrodynamic model, flood modelling, HEC-RAS 5.0.4

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Authors: Wilmer Osvaldo Martinez, Manuel Dario Hernandez, Juan Manuel Julio

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We propose to assess the performance of k forecast procedures by exploring the distributions of forecast errors and error losses. We argue that non systematic forecast errors minimize when their distributions are symmetric and unimodal, and that forecast accuracy should be assessed through stochastic loss order rather than expected loss order, which is the way it is customarily performed in previous work. Moreover, since forecast performance evaluation can be understood as a one way analysis of variance, we propose to explore loss distributions under two circumstances; when a strict (but unknown) joint stochastic order exists among the losses of all forecast alternatives, and when such order happens among subsets of alternative procedures. In spite of the fact that loss stochastic order is stronger than loss moment order, our proposals are at least as powerful as competing tests, and are robust to the correlation, autocorrelation and heteroskedasticity settings they consider. In addition, since our proposals do not require samples of the same size, their scope is also wider, and provided that they test the whole loss distribution instead of just loss moments, they can also be used to study forecast distributions as well. We illustrate the usefulness of our proposals by evaluating a set of real world forecasts.

Keywords: forecast evaluation, stochastic order, multiple comparison, non parametric test

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Authors: Naci Büyükkaracığan, Hasan Uzun

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Flood is the event which damage to the surrounding lands, residential places, infrastructure and vibrant, because of the streams overflow events from its bed for several reasons. Flood is a natural formation which develops due to its region's climatic conditions, technical and topographical characteristics. However, factors causing floods with global warming caused by human activity are events such as uncontrolled urbanization. Floods in Turkey are natural disasters which cause huge economic losses after the earthquake. At the same time, the flood disaster is one of the most observed hydrometeorological disasters, compared to 30%, in Turkey. Every year, there are around 200 flood-flood disasters and the disaster as a result of financial losses of $ 100 million per year are reported to occur in public institutions. The amount allocated for carrying out investment-project activities for reducing and controlling of flood damage control are around US $ 30 million per year. The existence of a linear increase in the number of flood disasters is noteworthy due to various reasons in the last 50 years of observation. In this study, first of all, big events of the flood in Turkey and their reasons were examined. And then, the information about the work to be done in order to prevent flooding by government was given with examples. Meteorological early warning systems, flood risk maps and regulation of urban development studies are described for this purpose. As a result, recommendations regarding in the event of the occurrence of floods disaster management were issues raised.

Keywords: flood, disaster, disaster management, Türkiye

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Authors: To Quyen Le, Oswald Devisch, Tu Anh Trinh, Els Hannes

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Urban centres worldwide are affected differently by flooding. In Vietnam this impact is increasingly negative caused by a process of rapid urbanisation. Traditional spatial planning and flood mitigation planning are not able to deal with this growing threat. This article therefore proposes to focus on increasing the participation of local communities in flood control and management. It explores, on the basis of a design studio exercise, how lay knowledge on flooding can be integrated within planning processes. The article presents a theoretical basis for the structured criterion for site selection for a flood resilient urban park from the perspective of science, then discloses the tacit and explicit knowledge of the flood-prone area and finally integrates this knowledge into the design strategies for flood resilient urban park design.

Keywords: analytic hierarchy process, AHP, design resilience, flood resilient urban park, knowledge integration

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Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

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Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

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Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: Muhammad Luthfi, Sutikno Sutikno, Purhadi Purhadi

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Weather forecast has necessarily been improved to provide the communities an accurate and objective prediction as well. To overcome such issue, the numerical-based weather forecast was extensively developed to reduce the subjectivity of forecast. Yet the Numerical Weather Predictions (NWPs) outputs are unfortunately issued without taking dynamical weather behavior and local terrain features into account. Thus, NWPs outputs are not able to accurately forecast the weather quantities, particularly for medium and long range forecast. The aim of this research is to aid and extend the development of ensemble forecast for Meteorology, Climatology, and Geophysics Agency of Indonesia. Ensemble method is an approach combining various deterministic forecast to produce more reliable one. However, such forecast is biased and uncalibrated due to its underdispersive or overdispersive nature. As one of the parametric methods, Bayesian Model Averaging (BMA) generates the calibrated ensemble forecast and constructs predictive PDF for specified period. Such method is able to utilize ensemble of any size but does not take spatial correlation into account. Whereas space dependencies involve the site of interest and nearby site, influenced by dynamic weather behavior. Meanwhile, Geostatistical Output Perturbation (GOP) reckons the spatial correlation to generate future weather quantities, though merely built by a single deterministic forecast, and is able to generate an ensemble of any size as well. This research conducts both BMA and GOP to generate the calibrated ensemble forecast for the daily temperature at few meteorological sites nearby Indonesia international airport.

Keywords: Bayesian Model Averaging, ensemble forecast, geostatistical output perturbation, numerical weather prediction, temperature

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: Stefano Zappacosta, Cristiano Bove, Maria Carmela Marinelli, Paola di Lauro, Katarina Spasenovic, Lorenzo Ostano, Giuseppe Aiello, Marco Pietrosanto

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This paper proposes a novel neural network approach for assessing flood hazard mapping. The core of the model is a machine learning component fed by frequency ratios, namely statistical correlations between flood event occurrences and a selected number of topographic properties. The proposed hybrid model can be used to classify four different increasing levels of hazard. The classification capability was compared with the flood hazard mapping River Basin Plans (PAI) designed by the Italian Institute for Environmental Research and Defence, ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). The study area of Piemonte, an Italian region, has been considered without loss of generality. The frequency ratios may be used as a standalone block to model the flood hazard mapping. Nevertheless, the mixture with a neural network improves the classification power of several percentage points, and may be proposed as a basic tool to model the flood hazard map in a wider scope.

Keywords: flood modeling, hazard map, neural networks, hydrogeological risk, flood risk assessment

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Authors: B. Sir, M. Podhoranyi, S. Kuchar, T. Kocyan

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Rainfall-runoff models play important role in hydrological predictions. However, the model is only one part of the process for creation of flood prediction. The aim of this paper is to show the process of successful prediction for flood event (May 15–May 18 2014). The prediction was performed by rainfall runoff model HEC–HMS, one of the models computed within Floreon+ system. The paper briefly evaluates the results of automatic hydrologic prediction on the river Olše catchment and its gages Český Těšín and Věřňovice.

Keywords: flood, HEC-HMS, prediction, rainfall, runoff

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Authors: Marju Ben Sayed, Shigeko Haruyama

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Among all kinds of natural disaster, the flood is a common feature in rapidly urbanizing Dhaka city. In this research, assessment of flood risk of Dhaka metropolitan area has been investigated by using an integrated approach of GIS, remote sensing and socio-economic data. The purpose of the study is to measure the flooding risk concerning with the flood protection embankment in big flooding events (1988, 1998 and 2004) and urbanization of Dhaka metropolitan zone. In this research, we considered the Dhaka city into two parts; East Dhaka (outside the flood protection embankment) and West Dhaka (inside the flood protection embankment). Using statistical data, we explored the socio-economic status of the study area population by comparing the density of population, land price and income level. We have drawn the cross section profile of the flood protection embankment into three different points for realizing the flooding risk in the study area, especially in the big flooding year (1988, 1998 and 2004). According to the physical condition of the study area, the land use/land cover map has been classified into five classes. Comparing with each land cover unit, historical weather station data and the socio-economic data, the flooding risk has been evaluated. Moreover, we compared between DEM data and each land cover units to find out the relationship with flood. It is expected that, this study could contribute to effective flood forecasting, relief and emergency management for a future flood event in Dhaka city.

Keywords: land use, land cover change, socio-economic, Dhaka city, GIS, flood

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Authors: Mohamad Sukeri Khalid, Che Su Mustaffa, Mohd Najib Marzuki, Mohd Fo’ad Sakdan, Sapora Sipon, Mohd Taib Ariffin, Shazwani Shafiai

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This paper describes the issues relating to the role of the flash flood early warning system provided by the Malaysian Government to the communities in Malaysia, specifically during the flash flood disaster in the Cameron Highlands, Malaysia. Normally, flash flood disasters can occur as a result of heavy rainfall in an area, and that water may possibly cause flooding via streams or narrow channels. For this study, the flash flood disaster in the Cameron Highlands occurred on 23 October 2013, and as a result the Sungai Bertam overflowed after the release of water from the Sultan Abu Bakar Dam. This release of water from the dam caused flash flooding which led to damage to properties and also the death of residents and livestock in the area. Therefore, the effort of this study is to identify the perceptions of the flash flood victims on the role of the flash flood early warning system. For the purposes of this study, data collection was gathered from those flood victims who were willing to participate in this study through face-to-face interviews. This approach helped the researcher to glean in-depth information about their feeling and perceptions on the role of the flash flood early warning system offered by the government. The data were analysed descriptively and the findings show that the respondents of 22 flood victims believe strongly that the flash flood early warning system was confusing and dysfunctional, and communities had failed to response positively to it. Therefore, most of the communities were not well prepared for the releasing of water from the dam that caused property damage and 3 people were killed in Cameron Highland flash flood disaster.

Keywords: communities affected, disaster management, early warning system, flash flood disaster

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Authors: Sherly M. A., Subhankar Karmakar, Terence Chan, Christian Rau

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Floods are one of the most frequent natural disasters, causing widespread devastation, economic damage and threat to human lives. Hydrologic impacts of climate change and intensification of urbanization are two root causes of increased flood occurrences, and recent research trends are oriented towards understanding these aspects. Due to rapid urbanization, population of cities across the world has increased exponentially leading to improperly planned developments. Climate change due to natural and anthropogenic activities on our environment has resulted in spatiotemporal changes in rainfall patterns. The combined effect of both aggravates the vulnerability of urban populations to floods. In this context, an efficient and effective flood risk management with its core component as flood risk mapping is essential in prevention and mitigation of flood disasters. Urban flood risk mapping involves zoning of an urban region based on its flood risk, which depicts the spatiotemporal pattern of frequency and severity of hazards, exposure to hazards, and degree of vulnerability of the population in terms of socio-economic, environmental and infrastructural aspects. Although vulnerability is a key component of risk, its assessment and mapping is often less advanced than hazard mapping and quantification. A synergic effort from technical experts and social scientists is vital for the effectiveness of flood risk management programs. Despite an increasing volume of quality research conducted on urban flood risk, a comprehensive multidisciplinary approach towards flood risk mapping still remains neglected due to which many of the input parameters and definitions of flood risk concepts are imprecise. Thus, the objectives of this review are to introduce and precisely define the relevant input parameters, concepts and terms in urban flood risk mapping, along with its methodology, current status and limitations. The review also aims at providing thought-provoking insights to potential future researchers and flood management professionals.

Keywords: flood risk, flood hazard, flood vulnerability, flood modeling, urban flooding, urban flood risk mapping

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Authors: Ankit Shah, R. K. Shrivastava

Abstract:

Flood and drought are two main features of hydrology which affect the human life. Floods are natural disasters which cause millions of rupees’ worth of damage each year in India and the whole world. Flood causes destruction in form of life and property. An accurate estimate of the flood damage potential is a key element to an effective, nationwide flood damage abatement program. Also, the increase in demand of water due to increase in population, industrial and agricultural growth, has let us know that though being a renewable resource it cannot be taken for granted. We have to optimize the use of water according to circumstances and conditions and need to harness it which can be done by construction of hydraulic structures. For their safe and proper functioning of hydraulic structures, we need to predict the flood magnitude and its impact. Hydraulic structures play a key role in harnessing and optimization of flood water which in turn results in safe and maximum use of water available. Mainly hydraulic structures are constructed on ungauged sites. There are two methods by which we can estimate flood viz. generation of Unit Hydrographs and Flood Frequency Analysis. In this study, Regional Flood Frequency Analysis has been employed. There are many methods for estimating the ‘Regional Flood Frequency Analysis’ viz. Index Flood Method. National Environmental and Research Council (NERC Methods), Multiple Regression Method, etc. However, none of the methods can be considered universal for every situation and location. The Narmada basin is located in Central India. It is drained by most of the tributaries, most of which are ungauged. Therefore it is very difficult to estimate flood on these tributaries and in the main river. As mentioned above Artificial Neural Network (ANN)s and Multiple Regression Method is used for determination of Regional flood Frequency. The annual peak flood data of 20 sites gauging sites of Narmada Basin is used in the present study to determine the Regional Flood relationships. Homogeneity of the considered sites is determined by using the Index Flood Method. Flood relationships obtained by both the methods are compared with each other, and it is found that ANN is more reliable than Multiple Regression Method for the present study area.

Keywords: artificial neural network, index flood method, multi layer perceptrons, multiple regression, Narmada basin, regional flood frequency

Procedia PDF Downloads 418

Authors: Husni Mohd Radzi, Lilie Zahara Ramly, Sapora Sipon, Salhah Abdullah

Abstract:

Malaysia have been experiencing series of huge floods all around the country for the past decades despide planned development done by local authorities. The floods incurred due to factors like natural climate change or man-made disaster. Floods have caused a lot of damages, destructions and losses in term of infrastructure, financial implications and physical health. However, other damaging aspect was not being given much attention are the psychological need of the flood victim. The traumatic impact from the natural disaster like floods may cause serious psychological and spiritual deterioration. Many flood relief shelters in the past did not provide counseling services for flood victims to consult, and as a result, it contributes to added stress among the flood victims, as the issue were not being addressed. Some studies indicates that flood victims did not look for counseling service being offered. A total of 257 flood victim was involved in this study. Main area of the study was Kg Bukit Changgang, Kg. Rancangan Tanah Belia, Kg. Labohan Dagang and Kg.Olak Lempit in Kuala Langat, Selangor. The flood victims have responded to the survey given and the data was analyze using SPSS for descriptive information and other measures. At least 13 victims were reported to have experienced moderate to severe level of stress and anxiety over the flood disaster incidents and a total of 88 respondents admitted to have at least thought and consider getting counseling service.

Keywords: perception, acceptance towards counseling, counseling service for flood victim, disaster

Procedia PDF Downloads 318

Authors: Siti Hajar Ya’acob, Nor Sayzwani Sukri, Farah Khaliz Kedri, Rozidaini Mohd Ghazi, Nik Raihan Nik Yusoff, Aweng A/L Eh Rak

Abstract:

Flood event that occurred in mid-December 2014 in East Coast of Peninsular Malaysia has driven attention from the public nationwide. Apart from loss and damage of properties and belongings, the massive flood event has introduced environmental disturbances on surface water resources in such flood affected area. A study has been conducted to measure the physical and chemical composition of Galas River and Pergau River prior to identification the flood impact towards environmental deterioration in surrounding area. Samples that have been collected were analyzed in-situ using YSI portable instrument and also in the laboratory for acid digestion and heavy metals analysis using Atomic Absorption Spectroscopy (AAS). Results showed that range of temperature (0C), DO (mg/L), Ec (µs/cm), TDS (mg/L), turbidity (NTU), pH, and salinity were 25.05-26.65, 1.51-5.85, 0.032-0.054, 0.022-0.035, 23.2-76.4, 3.46-7.31, and 0.01-0.02 respectively. The results from this study could be used as a primary database to evaluate the status of water quality of the respective river after the massive flood.

Keywords: flood, river, heavy metals, AAS

Procedia PDF Downloads 379

Authors: Widyani Fatwa Dewi, Subroto Athor

Abstract:

In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

Procedia PDF Downloads 164