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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 Australia. In this paper, the physical consequences of two floods from Queensland have been simulated, and the results have been compared with the performance of two selected methodologies and one newly derived model. Based on this analysis, the adaptability and applicability of the selected methodologies will be assessed in terms of Australian geographical conditions. Results obtained from the new empirically-based function and non-adapted methodologies indicate that it is apparent that the precision of flood damage models are strongly dependent on selected stage damage curves, and flood damage estimation without model validation results in inaccurate prediction of losses. Therefore, it is very important to be aware of the associated uncertainties in flood risk assessment, especially if models have not been adapted with real damage data.
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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 collected from an extreme event in Queensland, Australia, that occurred in 2013. Afterwards, the performance of the method developed in this work (contrasted to one Australian model and one model from USA) has been compared with the observed damage data collected from a 2012 flood event in Maranoa, Queensland. Based on this analysis, validation of the selected methodologies has been performed in terms of Australian geographical conditions. Results obtained from the new empirically based function (FLFArs) and the other models indicate that it is apparent that the precision of flood damage models is strongly dependent on selected stage damage curves, and flood damage estimation without model calibration might result in inaccurate predictions of losses. Therefore, it is very important to be aware of the associated uncertainties in flood risk assessment, especially if models have not been calibrated with real damage data.
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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 a spatial dependence model, which accounts for the net information available for regional analysis. It was found that the LFRM, which accounts for spatial dependence and that pools 1 or 3 maxima from a site, was able to estimate the 1 in 1000 annual exceedance probability flood quantile with consistency, showing a positive bias on average (5–7%) and modest median relative errors (30–33%).
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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 multivariate frequency analysis applied to flood events. Three specific implementations of the above approaches are evaluated on a case study – the estuarine portion of Swan River in Western Australia – highlighting the advantages and disadvantages of each approach. The theoretical understanding of the three approaches, combined with findings from the case study, enable the generation of guidance on method selection for estuarine flood probability estimation, recognizing issues such as data availability, the complexity of the application/analysis process, the location of interest within the estuarine region, the computational demands, and whether or not future conditions need to be assessed.
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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 for smaller return periods; however, for higher return periods, both the methods present a higher estimation error. The results of this study will help to recommend new AI-based RFFA methods in Australia.
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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 have notable implications on the regionalization of initial loss data, which is required for the application of Monte Carlo methods for design flood estimation in ungauged catchments.
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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 moments (for LP3, LN, and EV1) and L-moments (for GEV and GPD). Three-parameter distributions (e.g., LP3, GEV, and GPD) demonstrate a consistent estimation of confidence interval (CI), whereas two-parameter distributions show biased estimation. The results of this study also highlight the difficulty in flood frequency analysis, e.g., different probability distributions perform quite differently even in a smaller geographical area.
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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 in SWMOD represents the antecedent moisture condition. A quasi-Monte Carlo simulation framework is adopted, where the IM is stochastically varied according to a lognormal probability distribution. In calibration, it is found that the adopted modelling framework is able to simulate the majority of the observed flood hydrographs with a higher degree of accuracy; however, in a design context, when compared to the results of conventional flood frequency analysis, discrepancies are noted for a range of annual exceedance probabilities. The quasi-Monte Carlo simulation framework proved to be useful in assessing the effect of the IM content on design flood estimates.
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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 hydrological aspects. However, conducting a hydrological analysis is a challenging in rural areas, mainly owing to information scarcity. Floodways in rural areas often require a simple and economical solution contrast to more detailed hydrological analysis approaches adopted in urbanised areas. This paper aims to identify and apply the rational method to estimate maximum flood discharges at selected floodway locations in the Lockyer Valley Regional Council area. The paper further attempts to provide the first insight of flood characteristics during the 2011 and 2013 Queensland flood events at three catchment outputs across the selected case study area. It also highlights modern day challenges for practising engineers and researchers when estimating flood characteristics in rural areas. The paper shows that cross-cultivation of advancement in engineering practices and traditional approaches can promote quantitative approaches when assessing floodway damage in regional areas. Design/methodology/approach The research identifies limitations when assessing flood impact in rural regions in collaboration with experience from industry partners and authors themselves. The authors developed a framework to overcome those limitations arising from information scarcity to minimise the trial and error design approaches utilised in the current design practices for floodways. Findings This paper developed a simple and effective hydrological method with minimum inputs. It also provides an example on collating available but scattered resources and traditional method to quantitatively assess flood discharges of a rural catchment in Australia. Flood discharges at three catchment outlets along the Left-Hand Branch Road in the Lockyer Valley Region during both 2011 and 2013 Queensland flood events are estimated for the first time. The findings highlight the impact of flood discharges and flooded period on floodway failures. Research limitations/implications The current research is based on a selected case study area in Australia. However, similar challenges are expected all across the world, due to the scarcity of rainfall and flood measurement gauges. Practical implications Floodway designers can apply similar framework to estimate the flood discharges instead of current practice of trial and error process. This will provide more scientific and reliable estimation and assessment process. Social implications One of the social impacts identified in the broader research is the community outrages and disagreement between floodway design engineers and the community. Following the developed framework in the manuscript, design engineers will be able to justify their assumptions and design work. Originality/value The paper presents a novel framework on collating different and scattered information towards estimating flood discharges in rural areas. The manuscript presents the first insights on estimated flood discharges in the selected case study area during the 2011 and 2013 Queensland flood events. This will enable further research to be performed in a quantitative manner rather than the present approach of qualitative manner.
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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 (i.e. the 1% Annual Exceedance Probability – AEP). Such traditional approaches are overly simplistic in that risk is implicitly assumed to be static, in other words, that climatological processes are assumed to be randomly distributed in time. In this study, flood risk estimates are evaluated with regards to traditional statistical approaches as well as Pacific Decadal Oscillation (PDO)/El Niño-Southern Oscillation (ENSO) conditional estimates for a flood-prone catchment in eastern Australia. A paleo-reconstruction of pre-instrumental PDO/ENSO occurrence is then employed to estimate uncertainty associated with the estimation of the 1% AEP flood. The results indicate a significant underestimation of the uncertainty associated with extreme flood events when employing the traditional engineering estimates.
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Gamage, S. H. P. W., G. A. Hewa, and S. Beecham. "Probability distributions for explaining hydrological losses in South Australian catchments." Hydrology and Earth System Sciences Discussions 10, no. 4 (April 10, 2013): 4597–626. http://dx.doi.org/10.5194/hessd-10-4597-2013.
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Abstract. The wide variability of hydrological losses in catchments is due to multiple variables that affect the rainfall-runoff process. Accurate estimation of hydrological losses is required for making vital decisions in design applications that are based on design rainfall models and rainfall-runoff models. Using representative single values of losses, despite their wide variability, is common practice, especially in Australian studies. This practice leads to issues such as over or under estimation of design floods. Probability distributions can be used as a better representation of losses. In particular, using joint probability approaches (JPA), probability distributions can be incorporated into hydrological loss parameters in design models. However, lack of understanding of loss distributions limits the benefit of using JPA. The aim of this paper is to identify a probability distribution function that can successfully describe hydrological losses in South Australian (SA) catchments. This paper describes suitable parametric and non-parametric distributions that can successfully describe observed loss data. The goodness-of-fit of the fitted distributions and quantification of the errors associated with quantile estimation are also discussed a two-parameter Gamma distribution was identified as one that successfully described initial loss (IL) data of the selected catchments. Also, a non-parametric standardised distribution of losses that describes both IL and continuing loss (CL) data were identified. The results obtained for the non-parametric methods were compared with similar studies carried out in other parts of Australia and a remarkable degree of consistency was observed. The results will be helpful in improving design flood applications.
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Ratnayake, Dinesh C., Guna A. Hewa, and David J. Kemp. "Challenges in Quantifying Losses in a Partly Urbanised Catchment: A South Australian Case Study." Water 14, no. 8 (April 18, 2022): 1313. http://dx.doi.org/10.3390/w14081313.
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Quantifying hydrological losses in a catchment is crucial for developing an effective flood forecasting system and estimating design floods. This can be a complicated and challenging task when the catchment is urbanised as the interaction of pervious and impervious (both directly connected and indirectly connected) areas makes responses to rainfall hard to predict. This paper presents the challenges faced in estimating initial losses (IL) and proportional losses (PL) of the partly urbanised Brownhill Creek catchment in South Australia. The loss components were calculated for 57 runoff generating rainfall events using the non-parametric IL-PL method and parametric method based on two runoff routing models, Runoff Routing Burroughs (RORB) and Rainfall-Runoff Routing (RRR). The analysis showed that the RORB model provided the most representative median IL and PL for the rural portion of the study area as 9 mm and 0.81, respectively. However, none of the methods can provide a reliable loss value for the urban portion because there is no runoff contribution from unconnected areas for each event. However, the estimated non-parametric IL of 1.37 mm can be considered as IL of EIA of the urban portion. Several challenges were identified in the loss estimation process, mainly when selecting appropriate storm events, collecting data with the available temporal resolution, extracting baseflow, and determining the main-stream transmission losses, which reduced the urban flow by 5.7%. The effect of hydrograph shape in non-parametric loss estimation and how combined runoff from the effective impervious area and unconnected (combined indirectly connected impervious and pervious) areas affects the loss estimation process using the RORB and RRR models are further discussed. We also demonstrate the importance of identifying the catchment specific conditions appropriately when quantifying baseflow and runoff of selected events for loss estimation.
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Haddad, Khaled, and Ataur Rahman. "Regional Flood Estimation in New South Wales Australia Using Generalized Least Squares Quantile Regression." Journal of Hydrologic Engineering 16, no. 11 (November 2011): 920–25. http://dx.doi.org/10.1061/(asce)he.1943-5584.0000395.
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Aziz, K., M. M. Haque, A. Rahman, A. Y. Shamseldin, and M. Shoaib. "Flood estimation in ungauged catchments: application of artificial intelligence based methods for Eastern Australia." Stochastic Environmental Research and Risk Assessment 31, no. 6 (June 6, 2016): 1499–514. http://dx.doi.org/10.1007/s00477-016-1272-0.
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Noor, Farhana, Orpita U. Laz, Khaled Haddad, Mohammad A. Alim, and Ataur Rahman. "Comparison between Quantile Regression Technique and Generalised Additive Model for Regional Flood Frequency Analysis: A Case Study for Victoria, Australia." Water 14, no. 22 (November 11, 2022): 3627. http://dx.doi.org/10.3390/w14223627.
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For design flood estimation in ungauged catchments, Regional Flood Frequency Analysis (RFFA) is commonly used. Most of the RFFA methods are primarily based on linear modelling approaches, which do not account for the inherent nonlinearity of rainfall-runoff processes. Using data from 114 catchments in Victoria, Australia, this study employs the Generalised Additive Model (GAM) in RFFA and compares the results with linear method known as Quantile Regression Technique (QRT). The GAM model performance is found to be better for smaller return periods (i.e., 2, 5 and 10 years) with a median relative error ranging 16–41%. For higher return periods (i.e., 20, 50 and 100 years), log-log linear regression model (QRT) outperforms the GAM model with a median relative error ranging 31–59%.
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Franks, S. W. "Multi-decadal climate variability, New South Wales, Australia." Water Science and Technology 49, no. 7 (April 1, 2004): 133–40. http://dx.doi.org/10.2166/wst.2004.0437.
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Traditional hydrological risk estimation has treated the observations of hydro-climatological extremes as being independent and identically distributed, implying a static climate risk. However, recent research has highlighted the persistence of multi-decadal epochs of distinct climate states across New South Wales (NSW), Australia. Climatological studies have also revealed multi-decadal variability in the magnitude and frequency of El Niño/Southern Oscillation (ENSO) impacts. In this paper, examples of multi-decadal variability are presented with regard to flood and drought risk. The causal mechanisms for the observed variability are then explored. Finally, it is argued that the insights into climate variability provide (a) useful lead time for forecasting seasonal hydrological risk, (b) a strong rationale for a new framework for hydrological design and (c) a strong example of natural climate variability for use in the testing of General Circulation Models of climate change.
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Flatley, Alissa, and Ian Rutherfurd. "Comparison of Regionalisation Techniques for Peak Streamflow Estimation in Small Catchments in the Pilbara, Australia." Hydrology 9, no. 10 (September 24, 2022): 165. http://dx.doi.org/10.3390/hydrology9100165.
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Arid and semi-arid regions typically lack high-resolution river gauging data causing difficulties in understanding rainfall-runoff patterns. A common predictive method for discharge estimation within ungauged catchments is regional flood frequency estimation (RFFE), deriving peak discharge estimates from similar, gauged catchments and applying them to the catchment of interest. The majority of RFFE equations are developed for larger catchments where flow events may be larger and of greater interest. We test a series of RFFE methods derived for the Pilbara region, applying them to new ungauged small catchments under 10km2. Rainfall values are derived from a guideline Australian design rainfall database, Australian Rainfall and Runoff 2019 (ARR2019) which was recently updated with an additional 30 years of rainfall data. RFFE equations are compared to a direct rainfall model to evaluate their performance within small catchments, identifying key limitations and considerations when modelling small headwater catchments.
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Zhang, Yongqiang, and David Post. "How good are hydrological models for gap-filling streamflow data?" Hydrology and Earth System Sciences 22, no. 8 (August 30, 2018): 4593–604. http://dx.doi.org/10.5194/hess-22-4593-2018.
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Abstract. Gap-filling streamflow data is a critical step for most hydrological studies, such as streamflow trend, flood, and drought analysis and hydrological response variable estimates and predictions. However, there is a lack of quantitative evaluation of the gap-filled data accuracy in most hydrological studies. Here we show that when the missing data rate is less than 10 %, the gap-filled streamflow data obtained using calibrated hydrological models perform almost the same as the benchmark data (less than 1 % missing) when estimating annual trends for 217 unregulated catchments widely spread across Australia. Furthermore, the relative streamflow trend bias caused by the gap filling is not very large in very dry catchments where the hydrological model calibration is normally poor. Our results clearly demonstrate that the gap filling using hydrological modelling has little impact on the estimation of annual streamflow and its trends.
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Aziz, K., Sohail Rai, and A. Rahman. "Design flood estimation in ungauged catchments using genetic algorithm-based artificial neural network (GAANN) technique for Australia." Natural Hazards 77, no. 2 (February 10, 2015): 805–21. http://dx.doi.org/10.1007/s11069-015-1625-x.
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Caballero, Wilfredo Llacer, and Ataur Rahman. "Application of Monte Carlo simulation technique for flood estimation for two catchments in New South Wales, Australia." Natural Hazards 74, no. 3 (May 31, 2014): 1475–88. http://dx.doi.org/10.1007/s11069-014-1251-z.
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Caballero, Wilfredo Llacer, and Ataur Rahman. "Development of regionalized joint probability approach to flood estimation: a case study for Eastern New South Wales, Australia." Hydrological Processes 28, no. 13 (July 11, 2013): 4001–10. http://dx.doi.org/10.1002/hyp.9919.
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Mojtahedi, Mohammad, and Bee Lan Oo. "Built Infrastructure Conditions Mediate the Relationship between Stakeholders Attributes and Flood Damage: An Empirical Case Study." Sustainability 13, no. 17 (August 30, 2021): 9739. http://dx.doi.org/10.3390/su13179739.
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Most of the previous research has tended to focus on the impact of flood characteristics on built infrastructure damage rather than to investigate the condition of the infrastructure and stakeholders’ capacity to manage flood risks. The role of stakeholder attributes, such as the power, legitimacy, and urgency of local governments, in reducing the impact of disasters on built infrastructure remains ambiguous. Stakeholders’ organizational attributes, together with socio-economic and built infrastructure conditions, need to be considered to provide a better understanding of how to reduce disaster risk. The main aim of this research was to empirically investigate the mediating role of socio-economic and infrastructure conditions in the direct relationship between stakeholders’ attributes and economic damage to road infrastructure from flooding. Survey data collected from local governments in New South Wales, Australia and historical data for over 20 years from archive databases were analyzed using structural equation modeling with the partial least squares estimation approach. The results showed that socio-economic and infrastructure conditions have significant mediating effects on the direct relationship between stakeholders’ attributes and flood damage. Engaging stakeholders proactively empowers legitimate stakeholders in urgent conditions, and this is essential to reduce the economic impact of flood disasters and to better manage road infrastructure. Finally, to better manage flood risks, local governments need to improve their capacity of power, legitimacy, and urgency; state and federal governments need to improve the socio-economic conditions of the communities; and the transport infrastructure authorities need to develop long-term solutions for resilient roads and bridges.
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Haddad, Khaled, and Ataur Rahman. "Selection of the best fit flood frequency distribution and parameter estimation procedure: a case study for Tasmania in Australia." Stochastic Environmental Research and Risk Assessment 25, no. 3 (July 10, 2010): 415–28. http://dx.doi.org/10.1007/s00477-010-0412-1.
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Charalambous, James, Ataur Rahman, and Don Carroll. "Application of Monte Carlo Simulation Technique to Design Flood Estimation: A Case Study for North Johnstone River in Queensland, Australia." Water Resources Management 27, no. 11 (July 5, 2013): 4099–111. http://dx.doi.org/10.1007/s11269-013-0398-9.
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Shi, Zhuolin, Qianqian Chen, and Chang Huang. "The Influence of River Morphology on the Remote Sensing Based Discharge Estimation: Implications for Satellite Virtual Gauge Establishment." Water 14, no. 23 (November 26, 2022): 3854. http://dx.doi.org/10.3390/w14233854.
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Monitoring of river discharge is a key process for water resources management, soil and water conservation, climate change, water cycling, flood or drought warning, agriculture and transportation, especially for the sustainable development of rivers and their surrounding ecological environment. Continuous and comprehensive discharge monitoring was usually impossible before, due to sparse gauges and gauge deactivation. Satellite remote sensing provides an advanced approach for estimating and monitoring river discharge at regional or even global scales. River morphology is generally considered to be a direct factor that affects the accuracy of remote sensing estimation, but the specific indicators and the extent to which it affects the estimation accuracy have not yet been explored, especially for medium to small rivers (width < 100 m). In this paper, six sites with hydrological gauges in the upper Heihe River Basin (HRB) of northwestern China and the Murray Darling Basin (MDB) of southeastern Australia were selected as the study cases. River discharge was estimated from Landsat imagery using the C/M method accordingly. River gradient, sinuosity, and width were obtained from Digital Elevation Model data for each site. Global Surface Water Dataset (GSWD) was also employed for indicating the dynamic status of river morphology. A series of methods were applied to analyze the influence of river morphology on estimation accuracy qualitatively and quantitatively, based on which we established inference about the theory of selecting satellite virtual gauges (SVGs). The results confirm the feasibility of the C/M method for discharge estimation, with the accuracy affected by multiple river morphological indicators. Among them, river width was found to be the most significant one. Moreover, water occurrence and water extent extracted from GSWD also have impact on the discharge estimation accuracy. Another independent river section in MDB was set as an example to demonstrate the reasonability of the established theory. It is anticipated that this study would promote the application of remote sensing for discharge estimation by providing practical guidance for establishing appropriate SVGs.
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Glamore, William, and Buddhima Indraratna. "A two-stage decision support tool for restoring tidal flows to flood mitigation drains affected by acid sulfate soil: case study of Broughton Creek floodplain, New South Wales, Australia." Soil Research 42, no. 6 (2004): 639. http://dx.doi.org/10.1071/sr03166.
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A 2-stage flood estimation and water quality decision support tool (DST) was developed, calibrated, and applied to a field site in south-eastern New South Wales (NSW) to simulate tidal restoration in a flood mitigation drain affected by acid sulfate soils leachate. The first stage of the DST employs a digital terrain map, geographic information tools, and measured water levels to calculate drain water overtopping due to tidal variations. Simulations using the GIS technique at the study site indicated that the primary drainage network can safely contain full tidal flushing (0.91 m AHD or a 58% increase), whereas at the same level the secondary drainage network overtops along relict drainage channels. The second stage of the DST simulates the change in drain water quality using an ion-specific program code written within the open interface PHREEQC program. The results from the water quality model were calibrated against laboratory titration tests. Drain water pH was shown to increase above 6.0, and soluble aluminium and iron concentrations decreased by 73% and 56%, respectively. The extent of water quality change is directly related to the ionic strength of the intruding water and the ion-specific reaction kinetics of aluminium, iron, and sulfate.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences 18, no. 10 (October 15, 2014): 4065–76. http://dx.doi.org/10.5194/hess-18-4065-2014.
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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary generalised Pareto distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on intensity–frequency–duration (IFD) relationships. The methodology developed was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, 3 h and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences Discussions 11, no. 6 (June 16, 2014): 6311–42. http://dx.doi.org/10.5194/hessd-11-6311-2014.
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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of, threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary Generalized Pareto Distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on Intensity–Frequency–Duration (IFD) relationships. The developed methodology was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, and 3 and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Newby, M., S. W. Franks, and C. J. White. "Estimating urban flood risk – uncertainty in design criteria." Proceedings of the International Association of Hydrological Sciences 370 (June 11, 2015): 3–7. http://dx.doi.org/10.5194/piahs-370-3-2015.
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Abstract. The design of urban stormwater infrastructure is generally performed assuming that climate is static. For engineering practitioners, stormwater infrastructure is designed using a peak flow method, such as the Rational Method as outlined in the Australian Rainfall and Runoff (AR&R) guidelines and estimates of design rainfall intensities. Changes to Australian rainfall intensity design criteria have been made through updated releases of the AR&R77, AR&R87 and the recent 2013 AR&R Intensity Frequency Distributions (IFDs). The primary focus of this study is to compare the three IFD sets from 51 locations Australia wide. Since the release of the AR&R77 IFDs, the duration and number of locations for rainfall data has increased and techniques for data analysis have changed. Updated terminology coinciding with the 2013 IFD release has also resulted in a practical change to the design rainfall. For example, infrastructure that is designed for a 1 : 5 year ARI correlates with an 18.13% AEP, however for practical purposes, hydraulic guidelines have been updated with the more intuitive 20% AEP. The evaluation of design rainfall variation across Australia has indicated that the changes are dependent upon location, recurrence interval and rainfall duration. The changes to design rainfall IFDs are due to the application of differing data analysis techniques, the length and number of data sets and the change in terminology from ARI to AEP. Such changes mean that developed infrastructure has been designed to a range of different design criteria indicating the likely inadequacy of earlier developments to the current estimates of flood risk. In many cases, the under-design of infrastructure is greater than the expected impact of increased rainfall intensity under climate change scenarios.
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Franks, S. W. "Identification of a change in climate state using regional flood data." Hydrology and Earth System Sciences 6, no. 1 (February 28, 2002): 11–16. http://dx.doi.org/10.5194/hess-6-11-2002.
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Abstract. Flood frequency analysis typically assumes that annual floods arise from a single distribution and are independent. However, there is significant evidence for the existence of persistent climate modes. Timescales associated with climate variability range from inter-annual through to longer, multi-decadal time scales. In the case of the Australian climate, previous studies of the Indian and Pacific Oceans have indicated marked multi-decadal variability in both mean Sea Surface Temperatures (SST) and typical circulation patterns. In this light, data from 40 stream gauges around New South Wales are examined to determine whether flood frequency data are indeed independent and distributed identically. Given likely correlation in flood records between gauges, an assessment of the regional significance of observed changes in flood frequency is required. To achieve this, flood observations are aggregated into a regional index. A simple non-parametric test is then employed to identify the timing and magnitude of any change in mean annual flood. Finally, it is shown that the identified change in flood frequency corresponds directly to an observed shift in SST and mean circulation. These results demonstrate the role of natural variability in climate parameters and the need for an improved conceptual framework for flood frequency estimation. Keywords: Floods, flood frequency, climate variability, IPO, PDO, climate change
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Ashouri, Hamed, Kuo-Lin Hsu, Soroosh Sorooshian, Dan K. Braithwaite, Kenneth R. Knapp, L. Dewayne Cecil, Brian R. Nelson, and Olivier P. Prat. "PERSIANN-CDR: Daily Precipitation Climate Data Record from Multisatellite Observations for Hydrological and Climate Studies." Bulletin of the American Meteorological Society 96, no. 1 (January 1, 2015): 69–83. http://dx.doi.org/10.1175/bams-d-13-00068.1.
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Abstract A new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band 60°S–60°N for the period of 1 January 1983 to 31 December 2012 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution, and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data. It is adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5° monthly scale throughout the entire record. Three case studies for testing the efficacy of the dataset against available observations and satellite products are reported. The verification study over Hurricane Katrina (2005) shows that PERSIANN-CDR has good agreement with the stage IV radar data, noting that PERSIANN-CDR has more complete spatial coverage than the radar data. In addition, the comparison of PERSIANN-CDR against gauge observations during the 1986 Sydney flood in Australia reaffirms the capability of PERSIANN-CDR to provide reasonably accurate rainfall estimates. Moreover, the probability density function (PDF) of PERSIANN-CDR over the contiguous United States exhibits good agreement with the PDFs of the Climate Prediction Center (CPC) gridded gauge data and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product. The results indicate high potential for using PERSIANN-CDR for long-term hydroclimate studies in regional and global scales.
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Roche, Kevin M., K. John McAneney, Keping Chen, and Ryan P. Crompton. "The Australian Great Flood of 1954: Estimating the Cost of a Similar Event in 2011." Weather, Climate, and Society 5, no. 3 (July 1, 2013): 199–209. http://dx.doi.org/10.1175/wcas-d-12-00018.1.
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Abstract As in many other parts of the globe, migration to the coast and rapid regional development in Australia is resulting in large concentrations of population and insured assets. One of the most rapidly growing regions is southeastern Queensland and northern New South Wales, an area prone to flooding. This study reexamines the Great Flood of 1954 and develops a deterministic methodology to estimate the likely cost if a similar event had occurred in 2011. This cost is estimated using council flood maps, census information, historical observations, and Risk Frontiers' proprietary flood vulnerability functions. The 1954 flood arose from heavy rainfall caused by the passage of a tropical cyclone that made landfall on 20 February near the Queensland–New South Wales border, before heading south. Responsible for some of the largest floods on record for many northern New South Wales' river catchments, it occurred prior to the availability of reliable insurance statistics and the recent escalation in property values. The lower-bound estimate of the insurance loss using current exposure and assuming 100% insurance penetration for residential buildings and contents is AU$3.5 billion, a cost that would make it the third-highest ranked insured loss due to an extreme weather event since 1967. The corresponding normalized economic loss is AU$7.6 billion but the uncertainty about this figure is high. The magnitude of these losses reflects the accumulation of exposure on the floodplains. Risk-informed land-use planning practices and improved building regulations hold the key to reducing future losses.
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Middelmann-Fernandes, M. H. "Flood damage estimation beyond stage-damage functions: an Australian example." Journal of Flood Risk Management 3, no. 1 (March 2010): 88–96. http://dx.doi.org/10.1111/j.1753-318x.2009.01058.x.
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Gamage, S. H. P. W., G. A. Hewa, and S. Beecham. "Probability distributions for explaining hydrological losses in South Australian catchments." Hydrology and Earth System Sciences 17, no. 11 (November 15, 2013): 4541–53. http://dx.doi.org/10.5194/hess-17-4541-2013.
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Abstract. Accurate estimation of hydrological losses is required for making vital decisions in design applications that are based on design rainfall models and rainfall–runoff models. The use of representative single values of hydrological losses, despite their wide variability, is common practice, especially in Australian studies. This practice leads to issues such as over or under estimation of design floods. The probability distribution method is potentially a better technique to describe losses. However, a lack of understanding of how losses are distributed can limit the use of this technique. This paper aims to identify a probability distribution function that can successfully describe hydrological losses of a catchment of interest. The paper explains the systematic process of identifying probability distribution functions, the problems faced during the distribution fitting process and a new generalised method to test the adequacy of fitted distributions. The goodness-of-fit of the fitted distributions are examined using the Anderson–Darling test and the Q–Q plot method and the errors associated with quantile estimation are quantified by estimating the bias and mean square error (MSE). A two-parameter gamma distribution was identified as one that successfully describes initial loss (IL) data for the selected catchments. Further, non-parametric standardised distributions that describe both IL and continuing loss data are also identified. This paper will provide a significant contribution to the Australian Rainfall and Runoff (ARR) guidelines that are currently being updated, by improving understanding of hydrological losses in South Australian catchments. More importantly, this study provides new knowledge on how IL in a catchment is characterised.
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Loveridge, Melanie, and Ataur Rahman. "Monte Carlo simulation for design flood estimation: a review of Australian practice." Australasian Journal of Water Resources 22, no. 1 (January 2, 2018): 52–70. http://dx.doi.org/10.1080/13241583.2018.1453979.
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Callaghan, David P., and Michael G. Hughes. "Assessing flood hazard changes using climate model forcing." Natural Hazards and Earth System Sciences 22, no. 8 (August 1, 2022): 2459–72. http://dx.doi.org/10.5194/nhess-22-2459-2022.
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Abstract. A modelling framework for using regional climate projections to assess flooding hazard has been developed and applied to the Gwydir River (catchment 26 600 km2 and floodplain 8100 km2), NSW, Australia. The model framework uses NSW and ACT Regional Climate Modelling version 1.5 projections combined with computationally efficient hydrologic and hydraulic models. Although it required model management and high-performance computing resources, the modelling framework successfully processed 18 regional climate projections into flood projections. Specifically, a six-member set of climate model combinations simulating a historical period (1951–2005) and a future period (2006–2100) under two global emission pathways (RCP4.5 and RP8.5) were used to predict flood depth and speed. In total, 1470 continuous years were simulated at hourly time steps. These flood (depth and speed) projections were analysed to assess the flood hazard changes under future climate scenarios by estimating changes in the annual probability of occurrence of a range of flood hazard classes. The six-member ensemble indicates that the flood hazard in the Gwydir Valley will decrease in the short, medium and long term. There are also cases within the ensemble, which includes increases in all non-safe flood hazard classifications while decreasing the safe flood hazard classification.
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Smith, Ian, and Clive McAlpine. "Estimating future changes in flood risk: Case study of the Brisbane River, Australia." Climate Risk Management 6 (2014): 6–17. http://dx.doi.org/10.1016/j.crm.2014.11.002.
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Samat, S. R., N. Othman, and N. F. M. Zaidi. "The Development of Rainfall Temporal Pattern for Kuantan River Basin." International Journal of Engineering Technology and Sciences 5, no. 2 (October 1, 2018): 14–21. http://dx.doi.org/10.15282/ijets.v5i2.1376.
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One of the design rainfall event used in flood estimation is rainfall temporal pattern that gives the proportion of total rainfall in different periods within a given duration. The study focuses on developing a temporal rainfall pattern for the Kuantan River Basin in Pahang. According to Urban Stormwater Manual Second Edition (MSMA 2) that used as guideline for designing stormwater in Malaysia, rainfall temporal patterns are divided by region. In this study, the developments of rainfall temporal pattern in Kuantan River Basin are based specifically on rainfall station in this river basin. The Average Variability Method (AVM) that used in MSMA 2 and recommended by the Australian Rainfall and Runoff were used in developing rainfall temporal pattern for this study. The rainfall data of every 5 minutes for 16 years starting from 2000 to 2015 were gathered from Department of Irrigation and Drainage (DID) for purpose of study. In this study, the rainfall temporal pattern is deriving for 15 minutes, 30 minutes, 60 minutes, 120 minutes, 180 minutes and 360 minutes. The results show the significance differences of the rainfall temporal patterns between the results from this study and available value in MSMA 2 for the region of Pahang (Region 2). Therefore, each specific rainfall station has its own reliable rainfall temporal pattern that crucially important for flood estimation in Kuantan River Basin for future development plan
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Hasanzadeh Nafari, Roozbeh, Mattia Amadio, Tuan Ngo, and Jaroslav Mysiak. "Flood loss modelling with FLF-IT: a new flood loss function for Italian residential structures." Natural Hazards and Earth System Sciences 17, no. 7 (July 6, 2017): 1047–59. http://dx.doi.org/10.5194/nhess-17-1047-2017.
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Abstract. The damage triggered by different flood events costs the Italian economy millions of euros each year. This cost is likely to increase in the future due to climate variability and economic development. In order to avoid or reduce such significant financial losses, risk management requires tools which can provide a reliable estimate of potential flood impacts across the country. Flood loss functions are an internationally accepted method for estimating physical flood damage in urban areas. In this study, we derived a new flood loss function for Italian residential structures (FLF-IT), on the basis of empirical damage data collected from a recent flood event in the region of Emilia-Romagna. The function was developed based on a new Australian approach (FLFA), which represents the confidence limits that exist around the parameterized functional depth–damage relationship. After model calibration, the performance of the model was validated for the prediction of loss ratios and absolute damage values. It was also contrasted with an uncalibrated relative model with frequent usage in Europe. In this regard, a three-fold cross-validation procedure was carried out over the empirical sample to measure the range of uncertainty from the actual damage data. The predictive capability has also been studied for some sub-classes of water depth. The validation procedure shows that the newly derived function performs well (no bias and only 10 % mean absolute error), especially when the water depth is high. Results of these validation tests illustrate the importance of model calibration. The advantages of the FLF-IT model over other Italian models include calibration with empirical data, consideration of the epistemic uncertainty of data, and the ability to change parameters based on building practices across Italy.
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Reifels, Lennart, Bridget Bassilios, Matthew J. Spittal, Kylie King, Justine Fletcher, and Jane Pirkis. "Patterns and Predictors of Primary Mental Health Service Use Following Bushfire and Flood Disasters." Disaster Medicine and Public Health Preparedness 9, no. 3 (April 14, 2015): 275–82. http://dx.doi.org/10.1017/dmp.2015.23.
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AbstractObjectiveTo examine patterns and predictors of primary mental health care service use following 2 major Australian natural disaster events.MethodsUtilizing data from a national minimum dataset, descriptive and regression analyses were conducted to identify levels and predictors of the use of the Access to Allied Psychological Services (ATAPS) program over a 2-year period following 2 major Australian bushfire and flood/cyclone disasters.ResultsThe bushfire disaster resulted in significantly greater and more enduring ATAPS service volume, while service delivery for both disasters peaked in the third quarter. Consumers affected by bushfires (IRR 1.51, 95% CI 1.20–1.89), diagnosed with depression (IRR 2.57, 95% CI 1.60-4.14), anxiety (IRR 2.06, 95% CI 1.21-3.49), or both disorders (IRR 2.15, 95% CI 1.35-3.42) utilized treatment at higher rates.ConclusionsThe substantial demand for primary mental health care services following major natural disasters can vary in magnitude and trajectory with disaster type. Disaster-specific ATAPS services provide a promising model to cater for this demand in primary care settings. Disaster type and need-based variables as drivers of ATAPS use intensity indicate an equitable level of service use in line with the program intention. Established service usage patterns can assist with estimating capacity requirements in similar disaster circumstances. (Disaster Med Public Health Preparedness.2015;9:275-282)
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Macdonald, Ben C. T., Graeme D. Schwenke, Annabelle McPherson, Clarence Mercer, Jonathan Baird, and Gunasekhar Nachimuthu. "Soil water deficit effects on soil inorganic nitrogen in alternate-furrow flood irrigated Australian cotton production systems." Soil Research 60, no. 2 (November 4, 2021): 137–46. http://dx.doi.org/10.1071/sr20223.
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Context Predicting the nitrogen (N) mineralisation from soil organic matter is a key aid to fertiliser decision-making and improving the N fertiliser use efficiency of a crop. Aims and methods Field experiments were conducted to assess the amount of inorganic N derived from soil organic matter mineralisation over two seasons (2017–2018 and 2018–2019) across treatments differing in irrigation frequency and amount. During both seasons, the plant line soil in each treatment was sequentially sampled at each irrigation event. Key results There was an effect of the soil water deficit on the measured accumulated soil inorganic N derived from mineralisation in both measurement years. It was observed that soil inorganic N accumulated in the plant line rather than in other hillside and furrow positions for all soil moisture deficit treatments in both years. In 2017–2018, N accumulated in the plant was significantly greater than the measured accumulated inorganic N (0–300 mm). Conclusions and implications The sequential soil sampling approach was challenging in irrigated systems and we propose a hybrid measurement of pre-season available soil N and/or plant N uptake in nil N fertiliser plots as a means of estimating N derived from soil organic matter mineralisation.
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Ali, Noorfathiah Che, Yuliarahmadila Erfen, Nurul Farehah Amat, Zawani Mohd Zahudi, and Mohd Shalahuddin Adnan. "Development of Temporal Rainfall Pattern for Segamat District." Applied Mechanics and Materials 773-774 (July 2015): 1205–9. http://dx.doi.org/10.4028/www.scientific.net/amm.773-774.1205.
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The designing of rainfall temporal pattern is very important in displaying the diversity and intensity of rainfall in addition to flood estimation and planning. The main purpose of this study was to develop a temporal rainfall pattern for Segamat District. Average Variability Method, AVM which had recommended by the Australian Rainfall and Runoff were used to derive design rainfall temporal patterns for this study. The survey data for 5 minute interval from 2003 to 2012 for 4 selected rainfall stations that obtained from the Drainage and Irrigation Department, DID have been selected. In this study, the temporal rainfall pattern is built for 10 minutes, 15 minutes, 30 minutes, 60 minutes, 120 minutes, 180 minutes, and 360 minutes. The results shows the actual rainfall on the field in the form of temporal rainfall pattern. Up to 75% of the temporal patterns in the region can be classified as intermediate type while the advance and delay type are 11% and 14%, respectively. From the temporal rainfall pattern, the duration of rainfall occurs can be predicted, therefore, the probability of the flooding during the period can be estimated.
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Timms, W. A., R. R. Young, and N. Huth. "Implications of deep drainage through saline clay for groundwater recharge and sustainable cropping in a semi-arid catchment, Australia." Hydrology and Earth System Sciences Discussions 8, no. 6 (November 15, 2011): 10053–93. http://dx.doi.org/10.5194/hessd-8-10053-2011.
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Abstract. The magnitude and timing of deep drainage and salt leaching through clay soils is a critical issue for dryland agriculture in semi-arid regions (<500 mm yr−1 rainfall), such as parts of Australia's Murray-Darling Basin (MDB). In this unique study, hydrogeological measurements and estimations of the historic water balance of crops grown on overlying Grey Vertosols were combined to estimate the contribution of deep drainage below crop roots to recharge and salinization of shallow groundwater. Soil sampling at two sites on the alluvial flood plain of the Lower Namoi catchment revealed significant peaks in chloride concentrations at 0.8–1.2 m depth under perennial vegetation and at 2.0–2.5 m depth under continuous cropping indicating deep drainage and salt leaching since conversion to cropping. Total salt loads of 91–229 t ha−1 NaCl equivalent were measured for perennial vegetation and cropping, with salinity to ≥10 m depth that is not detected by shallow soil surveys. Groundwater salinity varied spatially from 910 to 2430 mS m−1 at 21 to 37 m depth (N = 5), whereas deeper groundwater was less saline (290 mS m−1) with use restricted to livestock and rural domestic supplies in this area. The Agricultural Production Systems Simulator (APSIM) software package predicted deep drainage of 3.3–9.5 mm yr−1 (0.7–2.1% rainfall) based on site records of grain yields, rainfall, salt leaching and soil properties. Predicted deep drainage was highly episodic, dependent on rainfall and antecedent, and over a 39 yr period was restricted mainly to the record wet winter of 1998. During the study period, groundwater levels were unresponsive to major rainfall events (70 and 190 mm total), and most piezometers at about 18 m depth remained dry. In this area, at this time, recharge negligible due to low rainfall and large potential evapotranspiration, transient hydrological conditionsafter changes in land use and a thick clay dominated vadose zone. This is in contrast to regional groundwater modelling that assumes annual recharge of 0.5% of rainfall. Importantly, it was found that leaching from episodic deep drainage could not cause discharge of saline groundwater in the area, since the water table was several meters below the incised river bed.
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Pratiwi, Dheka Shara, Mochamad Teguh, and Widodo Pawirodikromo. "An Implementation of the HAZUS Method for Estimating Potential Damage of Residential Houses at Pacitan Sub-district, East Java, Indonesia due to Earthquake." MATEC Web of Conferences 280 (2019): 01008. http://dx.doi.org/10.1051/matecconf/201928001008.
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Indonesia is not only known as an archipelago that is rich innatural resources but also known as a disaster-prone country. Because ofits location in four major Eurasian, Indo-Australian, Pacific, and Philippinetectonic plates, natural disasters such as earthquakes, floods, landslides, volcanic eruptions, droughts, forest fires, and tsunamis often occurthroughout the region. In 2006, a large earthquake shocked the denselypopulated Yogyakarta Province and its surrounding areas. This earthquakecaused huge fatalities and damaged thousands of buildings andinfrastructures. The Pacitan region is geographically close to Yogyakarta, and is located only 120 km from the epicenter of the quake. Therefore, awareness of disaster mitigation is a critical action in reducing disasterrisks. In addition, the Pacitan Regency is a hilly and mountainous regioncovering a total area of 1,389.87 km. Its territory also includes karstregions and lowland areas. A preliminary research utilizing the HAZUSmethod was conducted for assessing the damage probability of residentialhouses at an earthquake-prone area of Pacitan sub-district. The indicativeresults show that the unreinforced masonry (URML) types are the mostdestructive followed by Wood, light frame (W1), reinforced masonry lowrise(RM2L), and reinforced masonry mid-rise (RM2M) when appliedacross three scenarios of earthquake with magnitudes of 6, 6.5, and 7, respectively.
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Timms, W. A., R. R. Young, and N. Huth. "Implications of deep drainage through saline clay for groundwater recharge and sustainable cropping in a semi-arid catchment, Australia." Hydrology and Earth System Sciences 16, no. 4 (April 11, 2012): 1203–19. http://dx.doi.org/10.5194/hess-16-1203-2012.
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Abstract. The magnitude and timing of deep drainage and salt leaching through clay soils is a critical issue for dryland agriculture in semi-arid regions (<500 mm yr−1 rainfall, potential evapotranspiration >2000 mm yr−1) such as parts of Australia's Murray-Darling Basin (MDB). In this rare study, hydrogeological measurements and estimations of the historic water balance of crops grown on overlying Grey Vertosols were combined to estimate the contribution of deep drainage below crop roots to recharge and salinization of shallow groundwater. Soil sampling at two sites on the alluvial flood plain of the Lower Namoi catchment revealed significant peaks in chloride concentrations at 0.8–1.2 m depth under perennial vegetation and at 2.0–2.5 m depth under continuous cropping indicating deep drainage and salt leaching since conversion to cropping. Total salt loads of 91–229 t ha−1 NaCl equivalent were measured for perennial vegetation and cropping, with salinity to ≥ 10 m depth that was not detected by shallow soil surveys. Groundwater salinity varied spatially from 910 to 2430 mS m−1 at 21 to 37 m depth (N = 5), whereas deeper groundwater was less saline (290 mS m−1) with use restricted to livestock and rural domestic supplies in this area. The Agricultural Production Systems Simulator (APSIM) software package predicted deep drainage of 3.3–9.5 mm yr−1 (0.7–2.1% rainfall) based on site records of grain yields, rainfall, salt leaching and soil properties. Predicted deep drainage was highly episodic, dependent on rainfall and antecedent soil water content, and over a 39 yr period was restricted mainly to the record wet winter of 1998. During the study period, groundwater levels were unresponsive to major rainfall events (70 and 190 mm total), and most piezometers at about 18 m depth remained dry. In this area, at this time, recharge appears to be negligible due to low rainfall and large potential evapotranspiration, transient hydrological conditions after changes in land use and a thick clay dominated vadose zone. This is in contrast to regional groundwater modelling that assumes annual recharge of 0.5% of rainfall. Importantly, it was found that leaching from episodic deep drainage could not cause discharge of saline groundwater in the area, since the water table was several meters below the incised river bed.
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Kuntjoro, Wedyanto, D. D. Wijaya, A. Pramansyah, Z. A. J. Tanuwijaya, and Dhota Pradipta. "Zenith Wet Delay (ZWD) Seasonal Correlation with Rainfall in Cikapundung River Discharge, North Bandung Region, Indonesia." E3S Web of Conferences 94 (2019): 05004. http://dx.doi.org/10.1051/e3sconf/20199405004.
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In a GPS survey study, the biases produced by the ionosphere and troposphere layers are known as ionospheric biases and troposphere bias. The distance deviation due to the slowing travel time of GPS signals in troposphere is commonly referred to as Zenith Tropospheric Delay (ZTD). The magnitude of this ZTD can also be used to characterize and analyze the troposphere conditions around the GPS observation area. This can be done by separating the wet delay component from ZTD, so as to obtain Zenith Wet Delay (ZWD) and dry component so as to obtain Zenith Hydrostatic Delay (ZHD). The total moisture content in the troposphere (precipitable water vapor, PWV) of an area can be estimated based on the bias characteristics of zenith wet delay (ZWD). The ZWD pattern is very important in the study of atmospheric water cycles which are associated with rainfall patterns and flood events. The methods used in the research include preliminary data processing and estimation of ZTD value using RTKLIB 2.4.2. This article analyzes the correlation between ZWD, rainfall and Cikapundung river discharge in the North Bandung Region (KBU), based on the daily average data in the 2011-2015 observation period. Based on the reconstruction of harmonic components, it was found that the seasonal pattern of river discharge is correlating with the seasonal pattern of rainfall and moisture content in the troposphere. The pattern of the three variables is strongly influenced by the Asian and Australian Monsoon exchanges phenomena. Linear correlation between ZWD and river discharge exhibits clear results, which is based on the Pearson correlation value is 88.84% with a 95% confidence level using t-student statistic. Based on cross-spectrum analysis, the three variables are dominated by the seasonal cycle of one-year monsoon (annual) and the six-month cycle phenomenon (semi-annual).
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Cartwright, I., B. Gilfedder, and H. Hofmann. "Contrasts between chemical and physical estimates of baseflow help discern multiple sources of water contributing to rivers." Hydrology and Earth System Sciences Discussions 10, no. 5 (May 14, 2013): 5943–74. http://dx.doi.org/10.5194/hessd-10-5943-2013.
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Abstract. This study compares geochemical and physical methods of estimating baseflow in the upper reaches of the Barwon River, southeast Australia. Estimates of baseflow from physical techniques such as local minima and recursive digital filters are higher than those based on chemical mass balance using continuous electrical conductivity (EC). Between 2001 and 2011 the baseflow flux calculated using chemical mass balance is between 1.8 × 103 and 1.5 × 104 ML yr−1 (15 to 25% of the total discharge in any one year) whereas recursive digital filters yield baseflow fluxes of 3.6 × 103 to 3.8 × 104 ML yr−1 (19 to 52% of discharge) and the local minimum method yields baseflow fluxes of 3.2 × 103 to 2.5 × 104 ML yr−1 (13 to 44% of discharge). These differences most probably reflect how the different techniques characterise baseflow. Physical methods probably aggregate much of the water from delayed sources as baseflow. However, as many delayed transient water stores (such as bank return flow or floodplain storage) are likely to be geochemically similar to surface runoff, chemical mass balance calculations aggregate them with the surface runoff component. The mismatch between geochemical and physical estimates is greatest following periods of high discharge in winter, implying that these transient stores of water feed the river for several weeks to months. Consistent with these interpretations, modelling of bank storage indicates that bank return flows provide water to the river for several weeks after flood events. EC vs. discharge variations during individual flow events also imply that an inflow of low EC water stored within the banks or on the floodplain occurs as discharge falls. The joint use of physical and geochemical techniques allows a better understanding of the different components of water that contribute to river flow, which is important for the management and protection of water resources.
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Lázaro, Mariano, David Lázaro, Edurne Cortabarria, and Daniel Alvear. "Innovations for smoke management in passenger trains." Journal of Fire Sciences 38, no. 2 (December 24, 2019): 194–211. http://dx.doi.org/10.1177/0734904119895775.
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Spanish manufacturer Construcciones y Auxiliar de Ferrocarriles developed an innovative alternative for compartmentation, based on a smoke extraction system, to guarantee safe conditions during evacuation processes in a passenger unit. To demonstrate its performance in a train unit, a real-scale experimental programme, supported by the application of fire computer modelling, was applied in a new Construcciones y Auxiliar de Ferrocarriles’ rolling stock. The new smoke exhaust system aims to extract the smoke generated during a fire in the passenger area by exhaust fans of the heating, ventilation, and air conditioning system, allowing the ingress of fresh exterior air in the lower part of the rear ends of the car. These key elements create an air flow that evacuates the smoke to prevent people from being exposed to it. Full-scale fire tests were developed in the train unit following the Australian standard AS 4391-1999. A fire of 140 kW was used, and the smoke was generated by a clean smoke machine. Measurement points included six thermocouple trees, 10 gas flow velocity probes and two GoPro HD video cameras (for the estimation of the visibility). The system performance was successful with the tenability criteria, since the value of visibility at the non-fire car was greater than 30 m and the temperature was lower than 30°C during all the tests at a height of 1.7 m above the floor. Experimental results were used to validate the computational model. The computational model results show a good accuracy compared with the tests.
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Dunne, Jarrod C., Greg Beresford, and Brian L. N. Kennett. "Guidelines for building a detailed elastic depth model." GEOPHYSICS 65, no. 1 (January 2000): 35–45. http://dx.doi.org/10.1190/1.1444723.
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We developed guidelines for building a detailed elastic depth model by using an elastic synthetic seismogram that matched both prestack and stacked marine seismic data from the Gippsland Basin (Australia). Recomputing this synthetic for systematic variations upon the depth model provided insight into how each part of the model affected the synthetic. This led to the identification of parameters in the depth model that have only a minor influence upon the synthetic and suggested methods for estimating the parameters that are important. The depth coverage of the logging run is of prime importance because highly reflective layering in the overburden can generate noise events that interfere with deeper events. A depth sampling interval of 1 m for the P-wave velocity model is a useful lower limit for modeling the transmission response and thus maintaining accuracy in the tie over a large time interval. The sea‐floor model has a strong influence on mode conversion and surface multiples and can be built using a checkshot survey or by testing different trend curves. When an S-wave velocity log is unavailable, it can be replaced using the P-wave velocity model and estimates of the Poisson ratio for each significant geological formation. Missing densities can be replaced using Gardner’s equation, although separate substitutions are required for layers known to have exceptionally high or low densities. Linear events in the elastic synthetic are sensitive to the choice of inelastic attenuation values in the water layer and sea‐floor sediments, while a simple inelastic attenuation model for the consolidated sediments is often adequate. The usefulness of a 1-D depth model is limited by misties resulting from complex 3-D structures and the validity of the measurements obtained in the logging run. The importance of such mis‐ties can be judged, and allowed for in an interpretation, by recomputing the elastic synthetic after perturbing the depth model to simulate the key uncertainties. Taking the next step beyond using simplistic modeling techniques requires extra effort to achieve a satisfactory tie to each part of a prestack seismic record. This is rewarded by the greater confidence that can then be held in the stacked synthetic tie and applications such as noise identification, data processing benchmarking, AVO analysis, and inversion.
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Minh, Pham Thi, Bui Thi Tuyet, Tran Thi Thu Thao, and Le Thi Thu Hang. "Application of ensemble Kalman filter in WRF model to forecast rainfall on monsoon onset period in South Vietnam." VIETNAM JOURNAL OF EARTH SCIENCES 40, no. 4 (September 18, 2018): 367–94. http://dx.doi.org/10.15625/0866-7187/40/4/13134.
Full textAbstract:
This paper presents some results of rainfall forecast in the monsoon onset period in South Vietnam, with the use of ensemble Kalman filter to assimilate observation data into the initial field of the model. The study of rainfall forecasts are experimented at the time of Southern monsoon outbreaks for 3 years (2005, 2008 and 2009), corresponding to 18 cases. In each case, there are five trials, including satellite wind data assimilation, upper-air sounding data assimilation, mixed data (satellite wind+upper-air sounding data) assimilation and two controlled trials (one single predictive test and one multi-physical ensemble prediction), which is equivalent to 85 forecasts for one trial. Based on the statistical evaluation of 36 samples (18 meteorological stations and 18 trials), the results show that Kalman filter assimilates satellite wind data to forecast well rainfall at 48 hours and 72 hours ranges. With 24 hour forecasting period, upper-air sounding data assimilation and mixed data assimilation experiments predicted better rainfall than non-assimilation tests. The results of the assessment based on the phase prediction indicators also show that the ensemble Kalman filter assimilating satellite wind data and mixed data sets improve the rain forecasting capability of the model at 48 hours and 72 hour ranges, while the upper-air sounding data assimilation test produces satisfactory results at the 72 hour forecast range, and the multi-physical ensemble test predicted good rainfall at 24 hour and 48 hour forecasts. The results of this research initially lead to a new research approach, Kalman Filter Application that assimilates the existing observation data into input data of the model that can improve the quality of rainfall forecast in Southern Vietnam and overall country in general.References Bui Minh Tuan, Nguyen Minh Truong, 2013. 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