Gotowe bibliografie tematyczne / Flood estimation (Australia)

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Gotowa bibliografia na temat „Flood estimation (Australia)”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 20 lutego 2023

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Artykuły w czasopismach na temat "Flood estimation (Australia)"

Hasanzadeh Nafari, R., T. Ngo, and W. Lehman. "Results comparison and model validation for flood loss functions in Australian geographical conditions." Natural Hazards and Earth System Sciences Discussions 3, no. 6 (June 12, 2015): 3823–60. http://dx.doi.org/10.5194/nhessd-3-3823-2015.

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Abstract. Rapid urbanisation, climate change and unsustainable developments are increasing the risk of floods, namely flood frequency and intensity. Flood is a frequent natural hazard that has significant financial consequences for Australia. The emergency response system in Australia is very successful and has saved many lives over the years. However, the preparedness for natural disaster impacts in terms of loss reduction and damage mitigation has been less successful. This study aims to quantify the direct physical damage to residential structures that are prone to flood phenomena in Austra

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Hasanzadeh Nafari, R., T. Ngo, and W. Lehman. "Calibration and validation of FLFA<sub>rs</sub> -- a new flood loss function for Australian residential structures." Natural Hazards and Earth System Sciences 16, no. 1 (January 18, 2016): 15–27. http://dx.doi.org/10.5194/nhess-16-15-2016.

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Abstract. Rapid urbanisation, climate change and unsustainable developments are increasing the risk of floods. Flood is a frequent natural hazard that has significant financial consequences for Australia. The emergency response system in Australia is very successful and has saved many lives over the years. However, the preparedness for natural disaster impacts in terms of loss reduction and damage mitigation has been less successful. In this paper, a newly derived flood loss function for Australian residential structures (FLFArs) has been presented and calibrated by using historic data collect

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Haddad, Khaled, and Ataur Rahman. "Development of a Large Flood Regionalisation Model Considering Spatial Dependence—Application to Ungauged Catchments in Australia." Water 11, no. 4 (April 1, 2019): 677. http://dx.doi.org/10.3390/w11040677.

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Estimation of large floods is imperative in planning and designing large hydraulic structures. Due to the limited availability of observed flood data, estimating the frequencies of large floods requires significant extrapolation beyond the available data. This paper presents the development of a large flood regionalisation model (LFRM) based on observed flood data. The LFRM assumes that the maximum observed flood data over a large number of sites in a region can be pooled together by accounting for the at-site variations in the mean and coefficient of variation. The LFRM is enhanced by adding

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Wu, Wenyan, Seth Westra, and Michael Leonard. "Estimating the probability of compound floods in estuarine regions." Hydrology and Earth System Sciences 25, no. 5 (May 26, 2021): 2821–41. http://dx.doi.org/10.5194/hess-25-2821-2021.

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Abstract. The quantification of flood risk in estuarine regions relies on accurate estimation of flood probability, which is often challenging due to the rareness of hazardous flood events and their multi-causal (or “compound”) nature. Failure to consider the compounding nature of estuarine floods can lead to significant underestimation of flood risk in these regions. This study provides a comparative review of alternative approaches for estuarine flood estimation – namely, traditional univariate flood frequency analysis applied to both observed historical data and simulated data, as well as m

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Zalnezhad, Amir, Ataur Rahman, Nastaran Nasiri, Mehdi Vafakhah, Bijan Samali, and Farhad Ahamed. "Comparing Performance of ANN and SVM Methods for Regional Flood Frequency Analysis in South-East Australia." Water 14, no. 20 (October 20, 2022): 3323. http://dx.doi.org/10.3390/w14203323.

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Design flood estimations at ungauged catchments are a challenging task in hydrology. Regional flood frequency analysis (RFFA) is widely used for this purpose. This paper develops artificial intelligence (AI)-based RFFA models (artificial neural networks (ANN) and support vector machine (SVM)) using data from 181 gauged catchments in South-East Australia. Based on an independent testing, it is found that the ANN method outperforms the SVM (the relative error values for the ANN model range 33–54% as compared to 37–64% for the SVM). The ANN and SVM models generate more accurate flood quantiles fo

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Loveridge, Melanie, and Ataur Rahman. "Effects of Probability-Distributed Losses on Flood Estimates Using Event-Based Rainfall-Runoff Models." Water 13, no. 15 (July 27, 2021): 2049. http://dx.doi.org/10.3390/w13152049.

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Probability distributions of initial losses are investigated using a large dataset of catchments throughout Australia. The variability in design flood estimates caused by probability-distributed initial losses and associated uncertainties are investigated. Based on historic data sets in Australia, the Gamma and Beta distributions are found to be suitable for describing initial loss data. It has also been found that the central tendency of probability-distributed initial loss is more important in design flood estimation than the form of the probability density function. Findings from this study

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Khan, Zaved, Ataur Rahman, and Fazlul Karim. "An Assessment of Uncertainties in Flood Frequency Estimation Using Bootstrapping and Monte Carlo Simulation." Hydrology 10, no. 1 (January 10, 2023): 18. http://dx.doi.org/10.3390/hydrology10010018.

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Reducing uncertainty in design flood estimates is an essential part of flood risk planning and management. This study presents results from flood frequency estimates and associated uncertainties for five commonly used probability distribution functions, extreme value type 1 (EV1), generalized extreme value (GEV), generalized pareto distribution (GPD), log normal (LN) and log Pearson type 3 (LP3). The study was conducted using Monte Carlo simulation (MCS) and bootstrapping (BS) methods for the 10 river catchments in eastern Australia. The parameters were estimated by applying the method of mome

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Loveridge, Melanie, Ataur Rahman, and Peter Hill. "Applicability of a physically based soil water model (SWMOD) in design flood estimation in eastern Australia." Hydrology Research 48, no. 6 (December 28, 2016): 1652–65. http://dx.doi.org/10.2166/nh.2016.118.

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Abstract Event-based rainfall–runoff models are useful tools for hydrologic design. Of the many loss models, the ‘initial loss-continuing loss’ model is widely adopted in practice. Some of the key limitations with these types of loss models include the arbitrary selection of initial moisture (IM) conditions and lack of physically meaningful parameters. This paper investigates the applicability of a physically based soil water balance model (SWMOD) with distributed IM conditions for flood modelling. Four catchments from the east coast of New South Wales, Australia, are modelled. The IM content

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Wahalathantri, Buddhi, Weena Lokuge, Warna Karunasena, and Sujeeva Setunge. "Quantitative assessment of flood discharges and floodway failures through cross-cultivation of advancement in knowledge and traditional practices." International Journal of Disaster Resilience in the Built Environment 9, no. 4/5 (November 16, 2018): 435–56. http://dx.doi.org/10.1108/ijdrbe-09-2017-0051.

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Purpose The 2011 and 2013 Queensland, Australia flood events caused massive infrastructure damage for low-level stream crossings such as floodways and culverts in regional Queensland. Failures of newly built floodways during the 2013 Queensland flood event in the Lockyer Valley Regional Council area raised significant concerns with respect to floodway design practices adopted in Australia and attracted significant research interest to enhance the resilience of floodways. Review of existing floodway design guidelines indicates that floodway design process is closely related to hydraulic and hyd

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Franks, S. W., C. J. White, and M. Gensen. "Estimating extreme flood events – assumptions, uncertainty and error." Proceedings of the International Association of Hydrological Sciences 369 (June 11, 2015): 31–36. http://dx.doi.org/10.5194/piahs-369-31-2015.

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Abstract. Hydrological extremes are amongst the most devastating forms of natural disasters both in terms of lives lost and socio-economic impacts. There is consequently an imperative to robustly estimate the frequency and magnitude of hydrological extremes. Traditionally, engineers have employed purely statistical approaches to the estimation of flood risk. For example, for an observed hydrological timeseries, each annual maximum flood is extracted and a frequency distribution is fit to these data. The fitted distribution is then extrapolated to provide an estimate of the required design risk

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Rozprawy doktorskie na temat "Flood estimation (Australia)"

Haddad, Khaled. "Design flood estimation for ungauged catchments in Victoria : ordinary and generalised least squares methods compared." Thesis, View thesis, 2008. http://handle.uws.edu.au:8081/1959.7/30369.

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Design flood estimation in small to medium sized ungauged catchments is frequently required in hydrologic analysis and design and is of notable economic significance. For this task Australian Rainfall and Runoff (ARR) 1987, the National Guideline for Design Flow Estimation, recommends the Probabilistic Rational Method (PRM) for general use in South- East Australia. However, there have been recent developments that indicated significant potential to provide more meaningful and accurate design flood estimation in small to medium sized ungauged catchments. These include the L moments based index

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Charalambous, James, University of Western Sydney, of Science Technology and Environment College, and School of Engineering and Industrial Design. "Application of Monte Carlo Simulation Technique with URBS Runoff-Routing Model for design flood estimation in large catchments." THESIS_CSTE_EID_Charalambous_J.xml, 2004. http://handle.uws.edu.au:8081/1959.7/769.

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In recent years, there have been significant researches on holistic approaches to design flood estimation in Australia. The Monte Carlo Simulation technique, an approximate form of Joint Probability Approach, has been developed and tested to small gauged catchments. This thesis presents the extension of the Monte Carlo Simulation Technique to large catchments using runoff routing model URBS. The URBS-Monte Carlo Technique(UMCT),has been applied to the Johnstone River and Upper Mary River catchments in Queensland. The thesis shows that the UMCT can be applied to large catchments and be readily

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Charalambous, James. "Application of Monte Carlo Simulation Technique with URBS Runoff-Routing Model for design flood estimation in large catchments." Thesis, View thesis, 2004. http://handle.uws.edu.au:8081/1959.7/769.

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Haddad, Khaled, University of Western Sydney, College of Health and Science, and School of Engineering. "Design flood estimation for ungauged catchments in Victoria : ordinary and generalised least squares methods compared." 2008. http://handle.uws.edu.au:8081/1959.7/30369.

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Patel, Hitesh D. "Stochastic runoff routing model parameter for design flood estimation using joint probability approach." Thesis, 2010. http://handle.uws.edu.au:8081/1959.7/506747.

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The Design Event Approach is currently recommended rainfall-based flood estimation method in Australia according to Australian Rainfall and Runoff. However, Design Event Approach does not account for the probabilistic nature of the key flood producing variables except for the rainfall depth. This arbitrary treatment of key inputs and model parameters in Design Event Approach can lead to inconsistencies and significant bias in flood estimates for a given average recurrence interval. A significant improvement in design flood estimates can be achieved through a Joint Probability Approach, which i

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Loveridge, Melanie. "Loss models for design flood estimation : toward applications within a Monte Carlo environment." Thesis, 2016. http://hdl.handle.net/1959.7/uws:38506.

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This thesis focusses on more holistic approaches to flood modelling. For instance, joint probability/Monte Carlo approaches have received a great deal of attention in recent years, particularly since their use was advocated in Australian Rainfall and Runoff (ARR) 2015. In Monte Carlo simulation, rainfall-runoff model inputs are described by probability distributions, rather than fixed inputs as previously carried out with the Design Event Approach (DEA). There is no compelling evidence of the most appropriate loss model for flood estimation within a Monte Carlo framework. Furthermore, the func

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Części książek na temat "Flood estimation (Australia)"

Aziz, Kashif, Ataur Rahman, and Asaad Shamseldin. "Development of Artificial Intelligence Based Regional Flood Estimation Techniques for Eastern Australia." In Artificial Neural Network Modelling, 307–23. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28495-8_13.

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Stephens, D. A., M. J. Scorah, P. I. Hill, and R. J. Nathan. "Australian experience with application of Monte Carlo approach to extreme flood estimation." In Sustainable and Safe Dams Around the World, 3261–75. CRC Press, 2019. http://dx.doi.org/10.1201/9780429319778-294.

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Streszczenia konferencji na temat "Flood estimation (Australia)"

Haddad, Khaled. "A NEW FLOOD REGIONALISATION MODEL FOR LARGE FLOOD ESTIMATION IN AUSTRALIA." In SGEM2011 11th International Multidisciplinary Scientific GeoConference and EXPO. Stef92 Technology, 2011. http://dx.doi.org/10.5593/sgem2011/s13.101.

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"Development of a regional flood frequency estimation model for Pilbara, Australia." In 21st International Congress on Modelling and Simulation (MODSIM2015). Modelling and Simulation Society of Australia and New Zealand, 2015. http://dx.doi.org/10.36334/modsim.2015.l6.haque.

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Aziz, Kashif, Ataur Rahman, Gu Fang, Khaled Haddad, and Surendra Shrestha. "Design Flood Estimation for Ungauged Catchments: Application of Artificial Neural Networks for Eastern Australia." In World Environmental and Water Resources Congress 2010. Reston, VA: American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41114(371)293.

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"Development and validation of Artificial Intelligence Based Regional Flood Estimation Model for Eastern Australia." In 21st International Congress on Modelling and Simulation (MODSIM2015). Modelling and Simulation Society of Australia and New Zealand, 2015. http://dx.doi.org/10.36334/modsim.2015.l6.aziz.

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Zaman, Mohammad, Ishita Rahman, Khaled Haddad, and Ataur Rahman. "Scaling Issues in Design Flood Estimation for Ungauged Catchments: A Case Study for Eastern Australia." In World Environmental and Water Resources Congress 2010. Reston, VA: American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41114(371)295.

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"Regional flood estimation in Australia: application of gene expression programming and artificial neural network techniques." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand (MSSANZ), Inc., 2013. http://dx.doi.org/10.36334/modsim.2013.l1.aziz.

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"A New Probabilistic Rational Method for design flood estimation in ungauged catchments for the State of New South Wales in Australia." In 21st International Congress on Modelling and Simulation (MODSIM2015). Modelling and Simulation Society of Australia and New Zealand, 2015. http://dx.doi.org/10.36334/modsim.2015.l6.alsuwaidi.

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"Features of Regional Flood Frequency Estimation (RFFE) Model in Australian rainfall and runoff." In 21st International Congress on Modelling and Simulation (MODSIM2015). Modelling and Simulation Society of Australia and New Zealand, 2015. http://dx.doi.org/10.36334/modsim.2015.l6.rahman2.

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