Metaheuristic Algorithms to Enhance the Performance of a Feedforward Neural Network in Addressing Missing Hourly Precipitation

This research study investigates the implementation of three metaheuristic algorithms, namely, Grey wolf optimizer (GWO), Multi-verse optimizer (MVO), and Moth-flame optimisation (MFO), for coupling with a feedforward neural network (FNN) in addressing missing hourly rainfall observations, while overcoming the limitation of conventional training algorithm of artificial neural network that often traps in local optima. The proposed GWOFNN, MVOFNN, and MFOFNN were compared against the conventional Levenberg Marquardt Feedforward Neural Network (LMFNN) in addressing the artificially introduced missing hourly rainfall records of Kuching Third Mile Station. The findings show that the proposed approaches are superior to LMFNN in predicting the 20% hourly rainfall observations in terms of mean absolute error (MAE) and coefficient of correlation (r). The best performance ANN model is GWOFNN, followed with MVOFNN, MFOFNN and lastly LMFNN

Metaheuristic Algorithms to Enhance the Performance of a Feedforward Neural Network in Addressing Missing Hourly Precipitation

This research study investigates the implementation of three metaheuristic algorithms, namely, Grey wolf optimizer (GWO), Multi-verse optimizer (MVO), and Moth-flame optimisation (MFO), for coupling with a feedforward neural network (FNN) in addressing missing hourly rainfall observations, while overcoming the limitation of conventional training algorithm of artificial neural network that often traps in local optima. The proposed GWOFNN, MVOFNN, and MFOFNN were compared against the conventional Levenberg Marquardt Feedforward Neural Network (LMFNN) in addressing the artificially introduced missing hourly rainfall records of Kuching Third Mile Station. The findings show that the proposed approaches are superior to LMFNN in predicting the 20% hourly rainfall observations in terms of mean absolute error (MAE) and coefficient of correlation (r). The best performance ANN model is GWOFNN, followed with MVOFNN, MFOFNN and lastly LMFNN

Preliminary assessment of the effectiveness of rainwater tanks (STEM Blitz August 2015)

Rainwater tanks have been recognised as alternative source of water supply in Greater Melbourne, Australia. Rainwater tanks benefits included not only water savings for households but also in water supply systems and in flood mitigation. Analysis of 4000 households who availed the Victorian Government Rebate Scheme and another 4000 households who did not install rainwater tanks revealed that rainwater tanks contributed to the 42.5% reduction in average household annual water consumption. The results also show that rainwater tanks with indoor plumbing have longer payback period than those solely for outdoor purposes due to higher capital and operating costs even with higher rebates from the government. It was also revealed that the tank size>4500 had the highest NPV and a lowest levelised cost of water of 9cents/kl. The effect of household rainwater tanks on the diurnal patterns of water usage and on peak demand factors were also investigated on100 households whose water consumption were monitored by Yarra Valley Water at 5-minute interval. Analysis of the data revealed that water usage of households with rainwater tanks is lesser than households without. The diurnal patterns showed almost the same peak in the morning due to non consumption from rainwater tanks. However the afternoon peak is lower in households with rainwater tanks due to garden watering from rainwater tanks. In terms of flood mitigation, rainwater tanks resulted to peak flow reductions, downstream water quality improvements and reduction in the total annual volume of stormwater leaving the catchment. Recorded on 14 August 2015

Special Issue: Stormwater/Drainage Systems and Wastewater Management

For the purposes of this Special Issue of Hydrology, “Stormwater/Drainage Systems and Wastewater Management”, it is worth noting that hydrology, as defined by the US National Research Council [...

Characterising low rainfall events in Greater Melbourne using Standard Precipitation Index

There are different drought indices available for drought identification, monitoring and forecasting. The simpler ones include Standard Precipitation Index (SPI), Deciles and Percentiles. In this report, low rainfall events in a number of rainfall gauging stations monitored by Bureau or Meteorology (BOM) in Greater Melbourne were analysed using SPI. SPI series for different time scales were determined and low rainfall events were classified and categorised. Results were compared with that of other indices such as Deciles and Percentiles. Results showed that the worst drought occurred in 2000's based on all the time scales considered in this report. SPI enable the determination of probability, percent of average precipitation and drought magnitude which are useful measures of dry and wet condition

Understanding peak demand factors for water and wastewater supply systems design

The design of water and wastewater supply systems is traditionally based on maximum water demand which is a function of multiple factors. Understanding these factors and how these affect maximum water demand will lead to the estimation of appropriate peak design factors for a more cost effective design of water and wastewater supply systems. This paper describes the maximum water demand of seven separate residential suburbs in Greater Melbourne, Australia with populations ranging from 1000 to 23000. The study involves the analysis of water consumption data recorded at five-minute interval over one year. The effects of population and the sampling interval on the peak factor have been analysed. From a set of data collected at five-minute interval, further data sets at 10, 20, 30 and 60-minute have been derived. New equations to estimate the peak flow demand for small number of population have been developed. Results also show that at five-minute interval a more accurate peak design factor have been estimated. It is however, recommended that more suburbs be analysed to enable generalisation of results

A GIS based water end use demand modelling

The 'end use' of water is a breakdown of the total household water usage such as water used for toilets, showers, washing machines, taps, lawn watering, etc. The Victorian Government, in Australia set a 15% per capita consumption reduction target by 2010 based on the Water Resources Strategy that has been developed for Melbourne. Therefore, there is a need to measure and model residential end uses of water to ensure the effectiveness of conservation efforts and to determine whether the set target reduction is achieved. This paper describes GIS-based modelling of end uses of water from a number of single-family homes in Greater Melbourne, Australia. The study involves the analysis of water demand data at 1-minute and 5-second intervals from logged households collected by Yarra Valley Water in Melbourne, Australia in 2001 and 2004. The result of this study improves understanding on the end uses of water and provides information to assist where to focus water conservation efforts that would yield the most effective result financially, environmentally and acceptable to everyone

Climatic variabilities of potential rainwater savings: A case study for Adelaide

For determining potential water savings from a rainwater tank, a daily water balance method is often seen as the most feasible option with reasonable accurate estimations. However, most of the relevant studies were conducted using continuous simulations of historical daily data for a long period and report an average of cumulative historical water savings. Reporting averaged variables may result in rainwater tank users not getting an adequate insight of the expected variability of water savings. With the impacts of climate change, such variability ranges of outcomes are expected to increase. This paper presents analyses from a newly developed daily water balance model (eTank), which calculates rainwater tank outcomes under three different climatic conditions (i.e. dry, average and wet years). Fifteen representative years (five for each dry, average and wet condition) were selected from historical rainfall data to investigate the impact of climate variability on potential water savings.. An Australian major coastal city, Adelaide, was selected as a case study. eTank results for potential rainwater savings were compared with the another available daily water balance model (Raintank Analyzer), which is widely used by local government authority in South Australia for policy making. 'RainTank Analyser' uses historical daily rainfall data for a long period and reports an average of cumulative historical water savings. Calculations were performed using daily rainfall data from 'Adelaide Airport' raingauge station, considering same conditions in regard to daily rainwater demand, roof area, losses and tank volume. It was found that 'Raintank Analyzer' calculated potential savings are comparable with eTank calculated potential savings in average year only. eTank identified significant variations were between dry, average and wet years except for very few cases (i.e. smaller roof with low demand)

Understanding the Role of Constructed Wetlands in Stormwater Management

Constructed wetlands have been utilized for some time in the treatment of wastewater and have been recognized for the treatment of stormwater runoff and flood protection in the last couple of decades. Constructed wetlands are built to remove sediment and nutrients, primarily phosphorus and nitrogen, from contaminated water. However, with increased urbanization and enhanced climate change, these constructed wetlands need to be managed and their treatment effectiveness monitored and maintained especially at the post-construction phase. In addition, a greater understanding of the role of these systems in the urbanized environment and how they treat wastewater are needed to optimize their performance. As more advanced computer modeling is developed there is a need to ascertain what parameters and how these changes overtime and what skills are required to enable the adoption of constructed wetlands for future planning and management. There has been limited research into constructed wetlands for flood mitigation and with some receiving inflows larger than their design intent, it is necessary to determine if these systems would still be able to treat pollutants. This chapter involves a review of the literature to address these concerns relating to constructed wetlands

Development of a catchment water quality model for continuous simulations of pollutants build-up and wash-off

Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model