Artificial intelligence-based regional flood frequency analysis methods : a scoping review

Flood is one of the most destructive natural disasters, causing significant economic damage and loss of lives. Numerous methods have been introduced to estimate design floods, which include linear and non-linear techniques. Since flood generation is a non-linear process, the use of linear techniques has inherent weaknesses. To overcome these, artificial intelligence (AI)-based non-linear regional flood frequency analysis (RFFA) techniques have been introduced over the last two decades. There are limited articles available in the literature discussing the relative merits/demerits of these AI-based RFFA techniques. To fill this knowledge gap, a scoping review on the AI-based RFFA techniques is presented. Based on the Scopus database, more than 1000 articles were initially selected, which were then screened manually to select the most relevant articles. The accuracy and efficiency of the selected RFFA techniques based on a set of evaluation statistics were compared. Furthermore, the relationships among countries and researchers focusing on AI-based RFFA techniques are illustrated. In terms of performance, artificial neural networks (ANN) are found to be the best performing techniques among all the selected AI-based RFFA techniques. It is also found that Australia, Canada, and Iran have published the highest number of articles in this research field, followed by Turkey, the United Arab Emirates (UAE), India, and China. Future research should be directed towards identification of the impacts of data quantity and quality, model uncertainty and climate change on the AI-based RFFA techniques

Changes in Australian rainfall runoff and its implication for estimating design rainfall

Recently, Geoscience Australia has released updated national guidelines for the estimation of design floods in Australia, commonly known as Australian Rainfall Runoff (ARR). The methodologies and guidelines proposed in ARR are crucial for an accurate estimation of flood risk and for the design of safe and sustainable infrastructures in Australia. The newly proposed ARR (ARR2016) has adopted new methods and data compared to old ARR (ARR1987), which resulted differences in the estimation of design rainfall across Australia. For example, in ARR2016 additional 30 years’ rainfall data and 2300 extra rainfall stations have been included compared to ARR1987. Rainfall frequency analysis has been conducted by Generalised Extreme Value (GEV) distribution compared to Log-person Type III (LPIII), previously adopted in ARR1987. Bayesian Generalised Least Square Regression (BGLSR) is adopted in ARR2016 to predict daily rainfall from sub-daily rainfall statistics, which was previously done by Principal Component Analysis (PCA). In this paper, we review the guidelines for both ARR2016 and ARR1987 for design rainfall estimation and evaluate changes in design rainfall for selected stations in 8 major cities in Australia including Adelaide, Brisbane, Canberra, Darwin, Hobart, Melbourne, Sydney and Perth. Results presented in the paper will help Engineers and Managers of local governments to understand and implement new regulations proposed in ARR2016 for the estimation of design rainfall

Online quizzes to increase student learning in an engineering unit

Due to rapid changes in the communication technologies, the teaching and learning has changed dramatically over the last two decades. The face-to-face (class room based) teaching remains one of the most predominant ways of imparting knowledge to students. On the other hand, different online activities are increasingly being used to supplement traditional face-to-face engagement. In this paper, engagement strategies adopted while delivering one of the civil engineering subjects (units) from Bachelor of Engineering program offered by Western Sydney University are presented. The engineering course includes mathematical manipulation and engineering software learning. In addition, students participate in online in-lecture engagement tool and quizzes, tutorial sessions, group assignments and final exams. While some of the activities in the course such as in-lecture engagement tool and weekly quizzes are online, tutorial sessions are delivered via face-to-face mode. It was found that failure rate was significantly less for students who passed in online quizzes. Thus indicating that online quizzes may lead to deeper understanding of the lecture materials covered under the unit investigated as part of this study

Queensland flood in 2010-11 : will this type of flood occur soon?

During 2010-2011 Australia experienced one of the biggest flood events in Australia's history. Six major rain events affected large parts of the eastern states of Australia during this period. From December 2010 to January 2011, Queensland, Western Australia, Victoria and New South Wales experienced widespread flooding. There was extensive damage to both public and private properties, towns were evacuated and 37 lives were lost, 35 of those in Queensland. Three quarters of Queensland was declared a disaster zone, an area greater than France and Germany combined, and the total cost to the Australian economy has been estimated at more than $30 billion. The large scale of events, the number of lives lost and the scale of the damage incurred prompted numerous inquiries and review processes. The Queensland government convened a Commission of Inquiry to investigate the issues and consequences from the flood and to work towards learning lessons from the flooding to reduce the future vulnerability of the community to this type of disaster. To manage flood, minimise the risk, impact and damage due to flood, it is important to understand the cause of such flood and, frequency of occurrence. This paper presents the possible causes of such flood, possibility of its occurrence, insurance issues associated with flood, outcome of the 2010-11 floods commission of inquiry and the relation of global warming and climate change

Proceedings of the 1st International Conference on Engineering Research and Practice, 4-5 February 2017, Dhaka, Bangladesh

Welcome by Conference Chair: It is my great pleasure to see that the 1st International Conference on Engineering Research and Practice is being held during 4-5 February 2017 in Dhaka, the capital city of Bangladesh. As the General Co-Chair of the 1st International Conference on Engineering Research and Practice and Chair of the Global Circle for Scientific, Technological and Management Research (GCSTMR), I wish every success with such an important international event. I very much appreciate all the hosts of this conference: Bangladesh Open University, Dhaka University, Islamic University of Technology and Dhaka University of Engineering and Technology for supporting such an international event. I would like to thank all the GCSTMR Board Members, sponsors, secretaries, IT team, Conference Committee Members, reviewers and local Organizing Committee for making this conference as a success. I am confident that this conference will provide a unique platform for effective exchange of ideas, reaffirming the existing collegial contacts, provide opportunities for establishing new ones as well as providing a forum for academics and researchers to present and share the results and findings of their latest research and practice on a wide range of topics relevant to this conference

Bayesian Belief Network analysis of soil salinity in a peri-urban agricultural field irrigated with recycled water

Continuous use of recycled water (treated wastewater) over a long period of time may lead to the accumulation of salt in the root zone soil. This is due to the relatively higher levels of salt content in the recycled water compared to surface water. In this study, an assessment framework is proposed to evaluate the level of salinity in recycled water that can have significant impact on the root zone salinity when recycled water is used for irrigating peri-urban agricultural paddocks. The framework is constructed with a probabilistic expert system, more specifically, Bayesian Belief Network (BBN). The BBN model analyses the salt accumulation process with quantifying uncertainty associated with various variables related to this pro-cess. The proposed BBN was first developed and tested with the results from laboratory batch study and continuous column study conducted over 264 days. Later, a salt transport model HYDRUS 1D was used to quantify salt accumulation in the paddock over 20 years of study period, and the result was used to update the BBN to accommodate field condition. The salt transport modelling identified that in some year root zone soil water electrical conductivity (ECSWin dS/m) was more than twice of the maximum thresh-old of salinity tolerance. The BBN was used to quantify the uncertainty associated with the reduction of salinity in terms of electrical conductivity in recycled water (ECrwin dS/m), which subsequently reduced the probability of exceeding the salt accumulation beyond the maximum threshold limit. It was found that, if ECrwcan be reduced by 13% (from 0.92 to 0.8 dS/m), there is around 49% probability that the ECSW would be reduced by around 39% (from 6.5 dS/m to 4 dS/m), and will keep it within the threshold salinity limit of 3.0–5.0 dS/m 100% of the time. The study highlighted that any strategies that help in the reduction of salt in the recycled water will be beneficial in managing the soil salinity as a result of recycled water use for irrigating peri-urban agricultural field. The methodology presented in the study provides much needed knowledge for the development of robust and enlightened management strategies in relation to wastewater reuse

Sustainable management of mine induced water

Water is an essential part of mining industries. Fresh water is needed in different stages of mining activities. Mine induced water (MIW), water generated by different mining activities, contains harmful ingredients which cannot be reused or disposed without proper treatment. While the amount of water used by different mining industries varies depending on the type of mining product, so do the characteristics and amount of MIW. For example, the amount and characteristics of MIW generated from coal mining is very different than the characteristics of MIW generated from metal mining operations. The characterisation of MIW is also essential to devise a proper management, treatment and reuse scheme. In this chapter, characterisation and quantification of MIW from different activities in coal and metal mining are reviewed. Then impacts of MIW on the environment are identified. Later, different available options are discussed to sustainably manage the quality of MIW from different mining activities

Modelling of the impact of future climate changes on salt accumulation in paddocks of different soil types due to recycled water irrigation

Recycled water contains elevated amounts of salt compared to irrigation water originating from surface water sources. As such, recycled water, if used for irrigation over a long period of time may increase the root zone salinity. However, the phenomenon depends on variability of climatic condition and soil characteristics. In this study, a salt transport model, HYDRUS 1D, was used to predict long-term salt accumulation in two paddocks containing loamy sand and loam soil. The paddocks are located within Western Sydney University, Hawkesbury campus. Impact of rainfall on salt accumulation was studied with the data from Global Climate Model for the years 2021–2040. The long-term (20 years) salt accumulation showed a cyclical pattern because of variation in rainfall and evapotranspiration. It was found that soil water electrical conductivity (ECSW) was 24% higher in loam soil paddock compared to that of loamy sand. Amount of leachate in the loamy sand paddock was 27% more than the amount leached from that of loam, which may pose a salinity risk to the ground water if there is a perched aquifer in the field at a depth <1 m. Results from this study indicate that salt accumulation depends on soil type which seems to be more pronounced under low rainfall condition