B. J. C. Perera

Victoria University

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A. W. M Ng

City University of Hong Kong

D. A. Sachindra

Maria Curie-Skłodowska University

Nitin Muttil

Victoria University

Fuchun Huang

Guangzhou College of Commerce

Andrew Barton

Federation University

Shobha Muthukumaran

Victoria University

Abdullah Gokhan Yilmaz

La Trobe University

Shiroma Maheepala

University of Sri Jayewardenepura

Iwan Juwana

National Institute of Technology

Stephanie Ashbolt

Victoria University

Cooperative Institutions

Victoria University

Victoria School of Management

CSIRO Land and Water

Commonwealth Scientific and Industrial Research Organisation

University of Sri Jayewardenepura

Swinburne University of Technology

Health Sciences and Nutrition

Monash University

UNSW Sydney

International Institute for Applied Systems Analysis

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Rainfall trend and its implications for water resource management within the Yarra River catchment, Australia

Hydrological Processes (2012)

Shishutosh Barua Nitin Muttil A. W. M Ng B. J. C. Perera

Abstract Rainfall is the key climatic variable that governs the regional hydrologic cycle and availability of water resources. Recent studies have analysed the changes in rainfall patterns at global as well as regional scales in Australia. Recent studies have also suggested that any analysis of hydroclimatic variables should be performed at the local scale rather than at a large or global scale because the trends and their effects may be different from one location to the other. Because no studies were found specific to the Yarra River catchment, which is an important catchment in Victoria, Australia, this study performs a spatiotemporal trend analysis on long‐term rainfall records at 15 measuring stations within the catchment. The Mann–Kendall test was used to detect trends, and Sen's slope estimator was used to calculate the slopes in both monthly and annual rainfall. Moreover, a cumulative summation technique was used to identify the trend beginning year, and prewhitening criteria were tested to check for autocorrelation in the data. The results showed that the monthly rainfall has generally decreasing trends except in January and June. Significant decreasing rainfall trends were observed in May (among the autumn months of March, April and May) at most stations and also in some other months at several stations. A decreasing trend was also observed in the annual rainfall at all stations. This study indicates that there has been a consistent reduction in rainfall over the catchment, both spatially and temporally over the past 50 years, which will have important implications for the future management of water resources. Copyright © 2012 John Wiley & Sons, Ltd.

Trend analysis

10.1002/hyp.9311

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Comparison of Structural Deterioration Models for Stormwater Drainage Pipes

Computer-Aided Civil and Infrastructure Engineering (2008)

D. H. Tran B. J. C. Perera A. W. M Ng

Abstract: Structural deterioration of pipes is the continuing reduction of load bearing capacity, which can be characterized through structural defects. Structural deterioration has been a major concern for asset managers in maintaining the required performance of stormwater drainage systems in Australia. Condition assessment using closed circuit television (CCTV) inspection is often carried out to assess the deteriorating condition of individual pipes. In this study, two models were developed using ordered probit and neural networks (NNs) techniques for predicting the structural condition of individual pipes. The predictive performances were compared using CCTV data collected for a local government authority in Melbourne, Australia. The significant input factors to the outputs of both models were also identified. The results showed that the NN model was more suitable for modeling structural deterioration than the ordered probit model. The hydraulic condition, pipe size, and pipe location were found to be significant factors for this case study.

10.1111/j.1467-8667.2008.00577.x

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Sensitivity Analysis for Evaluating Importance of Variables Used in an Urban water Supply Planning Model

Modelling and Simulation Society of Australia and New Zealand eBooks (2007)

David King B. J. C. Perera

The yield of an urban water supply system is defined as the average annual volume of water that can be supplied from the water supply system over a given planning period, subject to streamflow variability, operating rules and demand pattern, without violating the adopted level of service. Since yield plays a key role in the management of urban water supply systems, it is important for water authorities to accurately estimate it with minimal inherent uncertainty. Sensitivity analysis can identify key variables used in yield estimation, allowing water authorities to improve the knowledge of those variables (or input factors) and thus to improve the confidence and reliability of the system yield.

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Review of River Water Quality Modeling Software Tools

Water Encyclopedia (2004)

A. W. M Ng B. J. C. Perera

Abstract River water quality has generally declined due to many human activities. In order to prevent or to control the degradation of river water quality, an appropriate management strategies must be considered. To manage river water quality in the most effective and efficient way, the cause and effect relationship of the river system must be identified. This can be done with a river water quality modelling tool. Many of these modelling tools are generic and are available in the public domain at no cost. However, it is necessary to review available river water quality software modelling tools, so that the most appropriate tool can be selected for the specific application. This paper will concentrate on the review of river water quality modelling tool. Then a case study on the selection of a suitable tool for the development of a river water quality model for Yarra River, Australia will be discussed. Based on the investigation, QUAL2E was identified as the most suitable software for the development of a Yarra River water quality model.

River management

10.1002/047147844x.wq622

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Importance of Genetic Algorithm Operators in River Water Quality Model Parameter Optimisation

A. W. M Ng B. J. C. Perera

Other book title: Proceedings of the International Congress on Modelling and Simulation (MODSIM 2001), Canberra, Australia, 10-13 December 2001. Well-calibrated river water quality models are required to assess the effectiveness of various management strategies, which are aimed at improving river water quality. Model calibration (or parameter estimation) is an important part of overall model development. A river water quality model was developed for Yarra River in Victoria (Australia) and was calibrated using a genetic algorithm (GA). In general, the efficiency of GA depends on the proper selection of GA operators, which prompted an investigation of these operators in achieving the 'optimum' model parameter set for the Yarra River water quality model. This was conducted by considering a hypothetical river network water quality model with both insensitive and sensitive reaction parameters and later verified by the Yarra River water quality model. Based on limited numerical experiments, it was found that GA with a reasonable operator set obtained from literature was capable of achieving a near-optimum model parameter set in river water quality models. However, it is recommended that further studies be conducted to verify the above findings.

Operator (biology)

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Sensitivity Analysis of Yield Estimate of Urban Water Supply Systems

Australasian Journal of Water Resources (2011)

Dennis M. King B. J. C. Perera

Sensitivity analysis (SA) theory and techniques were used in this study to estimate the sensitivity of input variables on the yield estimate of an urban water supply system. The SA techniques considered were Morris method and Fourier amplitude sensitivity test (FAST), including the related extended FAST. A case study on a simple urban water supply system was conducted to assess the applicability and to study the limitations of these techniques and the SA framework adopted. Findings showed that the streamflow dominated all experiments, with the supply reliability threshold, the upper restriction rule curve and the consecutive months in restrictions threshold of subsequent importance. In a screening pass, importance ranking of the 26 considered variables from the Morris method were verified with FAST and extended FAST. Once minor errors were overcome by increasing the number of model simulations, a high resolution pass quantified the importance of the top 10 ranked variables. The case study also highlighted the need to improve the adopted SA framework by considering a different methodology considering different climate scenarios and alternative input variable handling strategies.

10.1080/13241583.2011.11465382

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Statistical downscaling of general circulation model outputs to evaporation, minimum temperature and maximum temperature using a key-predictand and key-station approach

Journal of Water and Climate Change (2014)

D. A. Sachindra Fuchun Huang Andrew Barton B. J. C. Perera

A key-predictand and key-station approach was employed in downscaling general circulation model outputs to monthly evaporation, minimum temperature (Tmin) and maximum temperature (Tmax) at five observation stations concurrently. Tmax was highly correlated (magnitudes above 0.80 at p ≤ 0.05) with evaporation and Tmin at each individual station, hence Tmax was identified as the key predictand. One station was selected as the key station, as Tmax at that station showed high correlations with evaporation, Tmin and Tmax at all stations. Linear regression relationships were developed between the key predictand at the key station and evaporation, Tmin and Tmax at all stations using observations. A downscaling model was developed at the key station for Tmax. Then, outputs of this downscaling model at the key station were introduced to the linear regression relationships to produce projections of monthly evaporation, Tmin and Tmax at all stations. This key-predictand and key-station approach was proved to be effective as the statistics of the predictands simulated by this approach were in close agreement with those of observations. This simple multi-station multivariate downscaling approach enabled the preservation of the cross-correlation structures of each individual predictand among the stations and also the cross-correlation structures between different predictands at individual stations.

10.2166/wcc.2014.145

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Use of the Extended Fourier Amplitude Sensitivity Test to Assess the Importance of Input Variables on Urban Water Supply System Yield - A Case Study.

David King B. J. C. Perera

This paper presents a Sensitivity Analysis (SA) of the input variables used in the estimation of yield, considering multiple 20 year hydroclimatic scenarios of system inflow, rainfall, evaporation and demand. The Barwon urban water supply system in Australia was considered as the case study, whilst the extended Fourier Amplitude Sensitivity Test (eFAST) method was used for the SA. Input variables of the simulation model of the Barwon system were divided into two categories for use in SA analysis: the climate dependant variables (i.e. system inflow, rainfall, evaporation and demand) used to generate various climate scenarios, and the system policy variables which were assumed to have knowledge deficiency in relation to their optimum values. The security of supply thresholds were found to be the most important input variables, followed by the upper restriction rule curve position. The remaining variable did not show a discernible trend, indicating sensitivity to system inflow variability rather than total system inflow volume. The yield estimate was found to increase as the total system inflow increased. However the yield estimate had a wide range of variability as the total system inflow increased showing that the model behaviour and the yield estimate is particularly sensitive to climate variability.

Inflow

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Green infrastructure practices for improvement of urban air quality

Urban forestry & urban greening (2016)

V. M. Jayasooriya A. W. M Ng Shobha Muthukumaran B. J. C. Perera

Green infrastructure

Urban Forestry

10.1016/j.ufug.2016.11.007

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Citations (259)