Australian Rainfall And Runoff Research Articles

Development of a convolutional neural network based regional flood frequency analysis model for South-east Australia

Development of a convolutional neural network based regional flood frequency analysis model for South-east Australia

Non-Stationary Precipitation Frequency Estimates for Resilient Infrastructure Design in a Changing Climate: A Case Study in Sydney

The intensity–duration–frequency (IDF) curve is a commonly utilized tool for estimating extreme rainfall events that are used for many purposes including flood analysis. Extreme rainfall events are expected to become more intense under the changing climate, and there is a need to account for non-stationarity IDF curves to mitigate an underestimation of the risks associated with extreme rainfall events. Sydney, Australia, has recently started experiencing flooding under climate change and more intense rainfall events. This study evaluated the impact of climate change on altering the precipitation frequency estimates (PFs) used in generating IDF curves at Sydney Airport. Seven general circulation models (GCMs) were obtained, and the best models in terms of providing the extreme series were selected. The ensemble of the best models was used for comparing the projected 24 h PFs in 2031–2060 with historical values provided by Australian Rainfall and Runoff (ARR). The historical PFs consistently underestimate the projected 24 h PFs for all return periods. The projected 24 h 100 yr rainfall events are increased by 9% to 41% for the least and worst-case scenario compared to ARR historical PFs. These findings highlight the need for incorporating the impact of climate change on PFs and IDF curves in Sydney toward building a more prepared and resilient community. The findings of this study can also aid other communities in adapting the same framework for developing more robust and adaptive approaches to reducing extreme rainfall events’ repercussions under changing climates.

Confirmation of vehicle stability criteria through a combination of smoothed particle hydrodynamics and laboratory measurements

AbstractThis study combines laboratory experiments and numerical modelling in a novel manner to assess vehicle stability. Assessing vehicle stability forms the basis of hazard classification criteria, which in turn helps in forming safety guidelines for stream crossings and planning of evacuation routes in times of floods. These criteria are based on theoretical and physical model studies carried out on different vehicle models. This article demonstrates the application of a numerical method to determine the vehicle stability threshold so that the need for a physical model study for each kind of vehicle may be avoided. The numerical investigation is performed using smoothed particle hydrodynamics (SPH) with the vehicle oriented perpendicular to the flow direction, as this is the most critical orientation. A physical model study is also performed and its results are used to validate the SPH model. The results confirm the current Australian Rainfall and Runoff (ARR) safety criteria for stationary vehicles. It also suggests that the ARR stability curve can shift depending on the road conditions that affect the vehicle's sliding mechanism.

The influence of climate change and variability on the IFD Curves in NSW, Australia

In this study, the possible impacts of climate change and multi-decadal climate variability on intensity-frequency-duration (IFD) curves were investigated using both stationary and non-stationary generalized extreme value (GEV) distributions. The current study covers rainfall data recorded over 41 years for two rainfall stations, namely, Gowrie-055194 and Sydney Airport-066037, located within New South Wales state in Australia. Three future times (2030, 2060, and 2100), as well as 15 rainfall durations ranging from 6 min to 3-days, are considered. Consideration of the location parameter of the GEV distribution is influenced by climatic change and/or climate variability, providing a more consistent set of IFD curves. It is found that when the future period increases, the relative differences between the stationary and non-stationary IFD curves generally increase. When the new IFD curves (i.e., derived from the stationary and non-stationary approaches) are compared to the Australian Rainfall and Runoff (ARR) IFD curves, it is clear that the ARR IFD curves and the new stationary IFD curves are more closely aligned compared to the non-stationary IFD curves. The findings of this research are useful and provide valuable information for future planning of water resources, environmental and urbanization plans. It is essential to understand the expected behavior of hydro-meteorological processes regarding the possible changes in the rainfall design.

A Scaled Physical Model Study of Culvert Blockage Exploring Complex Relationships Between Influential Factors

ABSTRACT Blockage of cross-drainage hydraulic structures (e.g., bridges, culverts) is reported as an exacerbating factor during flash flooding in Wollongong and Newcastle. Lack of data from flooding events and the fragmentary nature of post-flood data are the factors hindering research in studying the impact of blockage on the performance of hydraulic structures. This paper proposes lab-scale simulations using scaled physical models of culverts to study the behaviour and effects of urban and vegetative debris. The first investigation studies the interaction between specific debris types with culvert inlet geometries and their impact on the hydraulic blockage. In the second investigation, a flood hydrograph is simulated in the laboratory to study complex relationships between blockage-related influential factors and to relate the observed visual blockage and hydraulic blockage. From the results of first investigation, urban debris was reported the main contributor in increasing the hydraulic blockage at structures. Furthermore, the degree of hydraulic blockage was found sensitive to the orientation of the debris. Results from the second investigation reported several insights regarding the complex relationships between blockage-related influential factors. The temporally variable nature of blockage was observed from the experiments that suggested revising the existing constant blockage based Australian Rainfall and Runoff (ARR) guidelines.

Effects of estimation techniques on generalised extreme value distribution (GEVD) parameters and their spatio-temporal variations

The application of generalised extreme value distribution (GEVD) requires the estimation of three parameters. Different researchers adopted different techniques for the estimation of the GEVD parameters and no standard comparison amongst those methods are available. This paper investigates the comparison of the commonly used GEVD parameters’ estimations for extreme rainfall modelling. The maximum likelihood estimation, generalised maximum likelihood estimation, Bayesian and L-moments methods were considered in this study to compare the magnitude of the GEVD parameters and the corresponding return level estimations. The analysis was performed using the monthly and yearly extreme rainfall of Tasmania, Australia. The GEVD was fitted to four different data sets using the four parameters estimation techniques. Estimated return levels of the GEVD for all the estimation techniques were compared with the return levels provided by the Australian Rainfall and Runoff (ARR), which is the national guideline for Australian rainfall and flood studies. The outcomes of the analysis suggest that the L-moments method is the better estimator of the return levels when comparing the ARR provided return levels.

Climate change and its influence on design rainfall at-site in New South Wales State, Australia

AbstractQuantification of rainfall is needed for planning, designing and operation of water engineering projects. Although there is lot of research on design rainfall in the literature, there is a lack of research considering the impact of climate change on design rainfall. This study focuses on the assessment of the impact of climate changes on design rainfall using data from New South Wales (NSW), Australia. Future stationary and non-stationary intensity–frequency–duration (IFD) curves have been estimated using generalized extreme value (GEV) distribution. The maximum-likelihood estimation method is employed to estimate the parameters of the GEV models. It has been found that the consideration of the climatic change on the rainfall data of the selected station confirms that the simulation exhibits non-stationary behaviour on the IFD curve data. In addition, the results show that when the future period increases, the relative differences between the stationary and non-stationary IFD curves generally increase. Comparison of the new IFD curves estimated in this study with the Australian Rainfall and Runoff (ARR) IFD curves demonstrates that there is a better match between the ARR IFD curves and the new stationary IFD curves compared with the non-stationary IFD curves.

Benchmarking the selection of probability neutral hydrologic design floods for use in 2D hydraulic models

ABSTRACTIn the 2016 release of Australian Rainfall and Runoff (ARR), variability of flood influencing factors (such as losses and temporal pattern) is now explicitly considered through application of Monte Carlo and ensemble approaches. However, hydrologic models are commonly an input for 2D hydraulic modelling, where computational constraints prevent a large number of floods from being modelled. Practitioners are therefore often required to select ‘representative floods’ for use in hydraulic modelling. When making this selection there is an implicit assumption that the probability of rainfall directly corresponds to the probability of flood levels—that is, the transformation is ‘probability neutral’. This assumption is often untested. The ‘representative flood’ approach was benchmarked against probability neutral estimates of flood depths constructed through Monte Carlo application of a 2D hydraulic model. Hydrographs that were found to be probability neutral with regards to peak outflows from the hydrologic model did not necessarily result in probability neutral estimates of flood depths. This demonstrates the need for running a greater selection of events to avoid generating biassed hydraulic model results.

Design rainfall estimation: comparison between GEV and LP3 distributions and at-site and regional estimates

Design rainfall, often known as intensity–frequency–duration (IFD) data, is an important input in rainfall runoff modelling exercise. IFD data are derived by fitting a probability distribution to observed rainfall data. Although there are many researches on IFD curves in the literature, there is a lack of systematic comparison among the IFD curves obtained by different distributions and methods. This study compares the latest IFD curves in Australia, published in 2013, as a part of the new Australian rainfall and runoff (ARR) with the at-site IFD curves to examine the expected degree of variation between the at-site and regional IFD data. Ten pluviography stations from eastern New South Wales (NSW) are selected for this study. The IFD curves generated by the two most commonly adopted probability distributions, generalised extreme value (GEV) and log Pearson type 3 (LP3) distributions are also compared. Empirical and polynomial regression methods in smoothing the IFD curves are compared. Based on the three goodness-of-fit tests, it has been found that both GEV and LP3 distributions fit the annual maximum rainfall data (at 1% significance level) for the ten selected stations. The developed IFD curves based on the second-degree polynomial present better fitting than the empirical method. It has been found that the ARR87 and ARR13 IFD curves are generally higher than the at-site IFD curves derived here. The median difference between the at-site and regional ARR-recommended IFD curves is in the range of 13–19%. It is expected that the outcomes of this research will provide better guidance in selecting the correct IFD data for a given application in NSW. The methodology developed here can be adapted to other parts of Australia and other countries.

Status of transforming stormwater drainage to a systems approach to urban water cycle management – moving beyond green pilots

ABSTRACTThis investigation was motivated by revision of Australia’s national guide to rainfall run-off and flooding, Australian Rainfall and Runoff (ARR) and systems thinking about the future of urban stormwater management. Reflections on this change process revealed internationally relevant challenges and a need to reframe stormwater drainage as integrated management of the urban water cycle from a design, economic and policy perspective. Advances in stormwater management are mostly represented by demonstration projects and policies for integrated water management. Many different water management philosophies have emerged that are consistent with evolving dominant interests such as water authorities, government agencies and proprietary research consortiums. Substantial progress has been made in defining the challenges and necessary solutions but urban flooding and ecological degradation continues to be an escalating problem. Traditional drainage approaches with bottom of catchment management of quantity and quality remains a default implementation solution. Pathway dependence on past methods, competing ideas and ownership, uncertain perceptions of value and a lack of systems perspective may be a barrier that needs to be overcome by the new ARR. A systems approach is needed for water cycle management that includes stormwater management in urban areas. The insights from this paper will also apply to many other cities outside of Australia.

ARR, Hinc Quo?

With the release of the 2016 edition of Australian Rainfall and Runoff (ARR), this paper asks the question, from here to where? It focuses on the core business of ARR, which is the estimation of flood quantiles, and assesses the accuracy of the two main approaches: flood frequency (FF) and joint probability (JP), of which the design storm (DS) approach is the simplest. The sources of uncertainty affecting FF and JP quantile estimation are dissected, and it is argued that the prevailing wisdom of the DS approach being more accurate than FF is questionable. A comparative error analysis of quantile estimates derived using gauged and regional application of FF and DS methods is presented using data from twenty-six well-gauged catchments. While FF tended to have better skill than DS methods, the skill levels were low. In the worst case, the regional DS method produced 90% probability limits for the 1 in 100 AEP quantile of 35% to 290%! These findings bring little comfort and highlight the fact there is much “unfinished business”. Two strategies are offered as a way forward: the first to reduce quantile uncertainty and the second to communicate and manage the large uncertainty inherent in quantile estimation.

Regime shifts in annual maximum rainfall across Australia – implications for intensity–frequency–duration (IFD) relationships

Abstract. Rainfall intensity–frequency–duration (IFD) relationships are commonly required for the design and planning of water supply and management systems around the world. Currently, IFD information is based on the "stationary climate assumption" that weather at any point in time will vary randomly and that the underlying climate statistics (including both averages and extremes) will remain constant irrespective of the period of record. However, the validity of this assumption has been questioned over the last 15 years, particularly in Australia, following an improved understanding of the significant impact of climate variability and change occurring on interannual to multidecadal timescales. This paper provides evidence of regime shifts in annual maximum rainfall time series (between 1913–2010) using 96 daily rainfall stations and 66 sub-daily rainfall stations across Australia. Furthermore, the effect of these regime shifts on the resulting IFD estimates are explored for three long-term (1913–2010) sub-daily rainfall records (Brisbane, Sydney, and Melbourne) utilizing insights into multidecadal climate variability. It is demonstrated that IFD relationships may under- or over-estimate the design rainfall depending on the length and time period spanned by the rainfall data used to develop the IFD information. It is recommended that regime shifts in annual maximum rainfall be explicitly considered and appropriately treated in the ongoing revisions of the Engineers Australia guide to estimating and utilizing IFD information, Australian Rainfall and Runoff (ARR), and that clear guidance needs to be provided on how to deal with the issue of regime shifts in extreme events (irrespective of whether this is due to natural or anthropogenic climate change). The findings of our study also have important implications for other regions of the world that exhibit considerable hydroclimatic variability and where IFD information is based on relatively short data sets.

Culvert blockages in two Australian flood events and implications for design

For 25 years, the de facto code-of-practice Australian Rainfall and Runoff (ARR) has recommended that the design of roadside and property drainage systems include the design of overland floodways which come into play whenever a flood exceeds the capacity of the closed conduit system. There is no encouragement that the same ‘safe-fail’ design procedure be adopted for larger, trunk drainage systems. Floods at Wollongong in 1998 and, at Newcastle in 2007, generally exceeded all drainage channel capacities. Some engineers misinterpreted the post-flood debris in the vicinity of culvert and bridge waterways as indicating hydraulic blockage of waterways by flood-borne debris and hence as a major contributor to higher flood levels and damage. A review of the two flood events shows that heavy rainfall resulted in flood discharges which exceeded the drainage capacities such that excess water flowed through natural and artificial urban floodways. Unexpected levels of damage were not caused by culvert blockage, but by the urban floodways which had not been included in prior hydraulic designs of culvert and bridge waterways and thus not identified and planned for. The recommendation is that the ‘safe-fail’ design approach be used for all sizes of drainage systems so that the inevitable hydraulic failures of drainage works can be anticipated in terms of where and how excess floodwater is managed.

Time-varying character of storm intensity frequency and duration curves

Recent climate change impact studies suggest that current rainfall intensity-frequency-duration (IFD) curves are likely to change as a result of climate change. In this paper, an effort was made to quantify the changing character of storm IFD curves using data of four consecutive 30-year time slices from 1880 to 2010. The Melbourne Regional Office rainfall data were used for the purposes of the study. Annual maximum series and generalised extreme value distribution were employed to derive the IFD curves using the data of different time slices and the whole period. Results of IFD curves produced from data for the whole period and the current IFD procedure in Australia, described in Australian Rainfall and Runoff (ARR), showed that the former had produced higher intensities for all sub-hourly storms of return periods of 10 to 100 years compared to the latter, and vice versa for return periods below 10 years. For all other storm durations (ie. 1–72 hours) and for short return periods (<10 years), the current ARR method had generated more intense storms. The above results demonstrate that there is a need to conduct further analysis to investigate changing character of storm IFD curves using rainfall data at several stations.

Probability distributions for explaining hydrological losses in South Australian catchments

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.

Comparison of Ordinary and Generalised Least Squares Regression Models in Regional Flood Frequency Analysis: A Case Study for New South Wales

Regional flood frequency analysis (RFFA) techniques are commonly used to estimate design floods for ungauged catchments. In Australian Rainfall and Runoff (ARR), the probabilistic rational method (PRM) was recommended for eastern New South Wales (NSW). Recent studies in Australia have shown that regression-based RFFA methods can provide more accurate design flood estimates than the PRM. This paper compares ordinary least squares (OLS) and generalised least squares (GLS) based quantile regression techniques using data from 96 small-to medium-sized catchments across NSW for average recurrence intervals of 2 to 100 years. The advantages of the GLS regression are that this accounts for the inter-station correlation and varying record lengths from site to site. An independent test based on both the split-sample and one-at-a-time validation approaches employing a wide range of statistical diagnostics indicates that the GLS regression provides more accurate flood quantile estimates than the OLS one. The developed regression equations are relatively easy to apply, which require data for only two to three predictors, catchment area, design rainfall intensity and stream density. The findings from this study together with those from other RFFA studies being examined as a part of ARR upgrade projects will inform the development of RFFA techniques for inclusion in the revised edition of ARR.

Overcoming the joint probability problem associated with initial loss estimation in desgn flood estimation

Design flood estimation techniques currently used in Australia only partially account for the joint probability interactions between flood producing variables. The joint probability problem associated with initial loss estimation is particularly important. Failure to deal with it can introduce considerable bias into estimated flood frequency distributions for ungauged catchments. One solution to this problem is to use continuous simulation whereby a rainfall generation model is linked to a catchment water balance and flood routing model. This technique has been used to explore less complicated ways of overcoming the joint probability problem by allowing design rainfall obtained from Australian Rainfall and Runoff (ARR) to be directly converted into rainfall excess. This eliminates the need for assumptions regarding initial loss. A continuous simulation approach has been utilised here by means of a stochastic point rainfall model, coupled with a stochastic evaporation model and modified AWBM model. This enables the determination of the scaling required for the conversion of rainfall into rainfall excess. The technique is validated using a kinematic wave catchment runoff model and comparison with observed flood frequency curves. Through this method, the simplicity of the design flood estimation approach is retained by the use of rainfall excess frequency duration (REFD) curves instead of rainfall IFD curves. The REFD method has been calibrated and tested on a number of catchments in Australia. Presented here are the results from the Boggy Creek catchment in Victoria. The scaling of the ARR design rainfall required has been very similar across all average recurrence intervals and event durations. This should allow the approach to be extended to other catchments.