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A recent extreme wet weather event caused significant disruption to wastewater infrastructure causing Unitywater to experience numerous sewage overflows. Currently, overflow prediction is based on operations experience and the use of hydraulic models, which are inherently difficult and costly to calibrate. A cost-effective and timely solution that could help operations understand sewer overflow likelihood and risk before a wet weather event occurs was needed.

AquaLab provided the platform for co-creation of an innovative sewer overflow prediction tool that would allow Unitywater to improve responses to wet weather events. The team established that the solution should aim to use existing, readily available radar imagery and SCADA data. By understanding the link between radar images and eventual overflow occurrence in the past, the tool is able to generate a wet weather overflow prediction up to 6 hours in advance based on new, live radar images.

Our client is the only supplier of water in the region and their supply is sourced from 5 major dams.  In response to a rock-fall event at one of the dams, a geotechnical investigation of the area was required however this posed significant challenge in terms of safe accessibility for the inspectors and an innovative approach was required.

The investigation proceeded using a drone equipped with instrumentation to capture high-resolution photographic images and video footage of the valley slopes downstream of the dam wall.  A 3D model of the area was then developed using GHD’s proprietary software Photovis.  A large number of hazard features were able to be identified, assessed and ranked for treatment, with their locations accurately captured in the 3D model.

The benefits of this approach to the problem were that:

• the human inspection required was reduced from several weeks to just two days’ rope inspections for densely vegetated areas, significantly improving safety and reducing time and cost
• a more comprehensive hazard report could be generated than could have been achieved by traditional methods, allowing for a more robust treatment plan to be created
• hazard features could be easily located and re-examined as needed through the 3D model

Our client is a bulk water supplier managing assets including pump stations, pipelines and reservoirs.  With the advent of new technology, particularly BIM, people are exploring ways to display all asset information in one place. This is important for maintaining access to and consistency of information for all those involved in the operation and maintenance of assets.

The challenge for this project was to create a virtual environment that allowed design data, SCADA data and maintenance data to be accessed and viewed remotely on a number of different devices.

The solution that GHD developed leverages a 3D visual interface which has been demonstrated on PC and mobile tablet. It brings together various data sets including satellite imagery, design information, operations manuals, safe work procedures and videos and live SCADA data. This solution has demonstrated benefits in improved communication amongst teams operating and maintaining the asset, reduced time and cost spent on site and better safety outcomes due to easy access to safe work methods and videos.

Our client owns and operates a significant number of reservoirs in its bulk water transmission network.  These reservoirs are integral to the safe and effective operation of the water network and regular condition monitoring is very important in achieving the required levels of service.

Typically, the main objective of a monitoring program is to confirm the sanitary integrity of the reservoirs while also identifying defects in any asset.  GHD has developed a novel approach to the inspection and assessment of above-ground water assets through the combination of UAVs and an in-house developed application called PhotoVis. This approach achieves the typical program objectives while also providing photo-quality, spatially referenced digital versions of the assets.

The benefit of this approach is that detailed inspection of the asset can be undertaken anywhere, at any time and an accurate and detailed photographic record of both the inspection and the assessment is available for future reference.  This lays the foundation for future automation of the condition assessment process through the application of machine learning and other data analytics techniques.

Leslie Harrison Dam, part of south east Queensland’s drinking water supply, was completed in 1967 and upgraded in 1984 to increase its storage capacity.  During more recent geotechnical investigations, a zone of potentially liquefiable material was identified beneath the main embankment.  Further hydrological studies were undertaken which showed an increase in the size of the potential flood inflow volumes. This, coupled with the increased downstream population, created a set of circumstances that meant that the risk posed by the dam was no longer considered acceptable by Seqwater and an upgrade was required.

Dam upgrades are complex and require the synthesis and communication of large amounts of information to a variety of audiences.  Clear communication about the relationships between multiple data sets including geology, flood modelling and structural design is considered to be an important project success factor.  The addition of instrumentation data in the form of piezometer readings from actual locations on site further expands the flexibility and usefulness of the model.

To aid with this and future dam upgrade projects, it was decided to combine and view these interconnected data sets in a 3D virtual reality environment to allow stakeholders, designers and field staff to quickly understand the issues at hand and the impact of the various data sets on the decision-making process.

Melbourne Water manages more than 1000 constructed wetlands designed for treating stormwater runoff before it reaches natural waterways and Port Phillip Bay. Aquatic and semi-aquatic plants within these assets remove contaminants from the stormwater, therefore vegetation health is an indicator of asset performance and functionality. A rapid, repeatable and cost-effective method for assessing vegetation condition to assist in better managing the assets and capital works planning was needed.

Together, GHD and Melbourne Water created an automated analysis of high resolution satellite imagery to create numerical indicators of wetland health for a study area of more than 200,000 hectares. This innovative project won an Award for Spatial Enablement at the 2015 Victorian Spatial Excellence Awards, and has been presented at a number of conferences.

Object-based image analysis of high resolution satellite imagery was used to measure sparse, moderately dense and dense areas of vegetation as well as areas of open water and pathway, using a mix of spectral, spatial and geometric properties. GHD designed the process to be repeatable, robust and accurate to allow for the monitoring of condition and performance change over time.

The development of the methodology allows Melbourne Water to rapidly assess its wetland portfolio as a whole, previously fieldwork assessment was limited to a small portion of their asset portfolio every three years. Melbourne Water estimates a potential saving of $20 million over five years. This data enables more informed decision making in terms of prioritising works and capital projects to keep the assets performing at maximum efficiency using targeted maintenance.

The owners of a vast network of pressure water mains have recently experienced a number of breaks throughout the system and, while most of breaks experienced are relatively minor, there are about one or two per month where significant failures occur, requiring additional operational support to manage service interruptions, traffic, property damage or other impacts.

Several recent failures have demonstrated the risks associated with having pressure pipelines in close proximity to sensitive community areas.  There was a need to address gaps in understanding of the consequences of watermain break failure to assist in better managing the risks associated with pipeline rupture.

Using advances in computing hardware and software, an innovative methodology was developed to quantify the consequence of watermain failure at 5m intervals along the 250km of trunk water mains included in the study scope. The method used GIS and machine learning processes to build nearly 60,000 two-dimensional hydraulic models in TUFLOW. Population at Risk (PAR) assessments were also undertaken at each modelled location and models ran on multiple computers for weeks to process the significant number of simulations required.

This is the first instance that GHD knows of, in Australia, where a water utility has tried to determine the consequence of trunk watermain break flooding on residential properties and major roads. Now armed with a thorough understanding of the consequences and likelihoods of water main failure, it is possible to better prioritise further investigations or preventative works to reduce risk.  This is of particular value for utilities who are universally challenged to optimise their capital and operational spend.

The owners of a large power station observed a deterioration in the quality of the station’s cooling water makeup over a period of years and this was detrimentally affecting operations, including potentially limiting power supply.

Numerous water supply and treatment options existed to address the situation and all had to be considered within the context of a Zero Liquid Discharge target.  Because of regulatory constraints, the complex analysis had to be completed in a very short time frame.  Traditional methods would have been too time-consuming and so a novel approach was required.

The project team decided to apply a new software package, AqMB Designer™ which allowed them to build an integrated model that could simulate all the water treatment processes both upstream and downstream of the cooling tower, including the Zero Liquid Discharge system.  Other benefits of this approach included:

• Much faster and more economical process for option development and assessment (including automated production of key engineering deliverables), allowing the required timeframes to be met
• Improved decision-making confidence and risk management because of the new capability to model the entire process and check on impacts in other parts of the system over the long-term
• Better communication with stakeholders and regulators because of improved clarity of information and reporting

The simplicity of the user interface meant that both GHD and the client’s project team members were able to use and manipulate the model, working together to interrogate different scenarios and generate a preferred concept that met all parties’ objectives.

Australia has many regions with well-known histories of flooding caused by severe weather events and storm tides, impacting rivers and creeks.  Following a series of floods and weather events, our client identified a need to create a comprehensive and robust overland flow path map to replace older, out-of-date mapping.

The stormwater drainage network consists of over 200,000 pipelines, 10,000 culverts and many bridges. Due to physical and financial limitations of accessing each asset, GHD was required to employ an innovative approach to map them. Modelling the entire system using traditional, non-digital methods would have required extensive time, money and comprehensive existing data. The GHD team developed a method that allowed for the simulation of stormwater systems in a way which greatly reduced the data and time requirements, whilst simultaneously increasing modelling speed.

This approach is extremely cost efficient and allows the modelling of an entire city, for the cost of modelling a single catchment using traditional methods. Deliverables produced for this project will continue to help the client to reduce the cost of flood related damage to the community, property and infrastructure.

Our client wanted to explore the idea that water main breaks occur in clusters rather than as individual one-off events to assist them in better understanding the behaviour of the asset base so they could improve the efficiency of their network maintenance activities and capital spend.

The team adopted GIS-based software and methods to analyse historical incident data and conduct the cluster analysis.  The results were reported using a simple-to-use, interactive dashboard system which contained mapping of the clusters, various statistics and access to actual incident detail.  The dashboards were collected into a single web-based app, allowing users to filter data and run sensitivity analyses to see instant results.

Now that it is in use, the dashboard has improved general understanding of the asset behaviour, leading in turn to further cluster analysis and providing a robust basis for data-driven decision-making.  Due to its ease-of-use and clean presentation, the dashboard is proving its value as a communication tool that anyone in the organisation can use.

A bulk water supplier operates a significant fleet of bulk potable water meters (~100 used for billing alone), located at the water treatment plants and in the bulk supply networks.

As a result of internal and external audits of all business processes associated with bulk metering, the supplier initiated a meter review program to develop and implement actions to bring an acceptable level of metrological assurance to all metering processes.

The challenge included developing a methodology to cost-effectively determine if flow characteristics through a bulk flow meter could be adversely affecting the accuracy of the meter. The particular objective of this work package was to formulate the analysis and reporting requirements and then run the low flow and potential error analytics on data for a number of the top meters, ranked by flow volume).

The outcome of the assessment provided a basis for dual-ranking of meter criticality, i.e. by volume and by potential low-flow error, and also provided a basis for comparison with data logging results from previous work undertaken. This information was used to assess meter criticality, to formulate priorities for the in-situ flow validation program and to provide assurance to downstream water distributors on one component of potential meter error.

The software and data management tools developed to handle the data were proven to be a robust, repeatable form of analysis. The primary aim, to identify whether low flow regimes may be prevalent and potentially impacting on the accuracy of measurement, was achieved.

Melbourne Water (MW) commissioned GHD to develop a live water operations decision support tool for their Network Operations and Strategy team using Innovyze software IWLive Pro and DemandWatch as the core tool for operational modelling.

MW’s drivers for this project centred on being able to make safer, faster, smarter and justifiable decisions for the operation of its infrastructure.

This project was the first of its kind for MW and the objective was to work with a broad range of stakeholders including operators, software providers, IT and planners to determine the functional requirements for the model. GHD was required to create and operate the model within MW’s IT environment.

The overall approach adopted by GHD to develop the live model saw early stakeholder input to establish the functional requirements of the model, a review of the existing information to provide recommendations for short and long term improvements in data collection and management and finally model creation and configuration within MW’s IT environment.

After completion of the model configuration, demand forecast predictions were compared against actual consumptions for each of the 38 supply zones with outputs demonstrating the model’s ability to meet the allowable prediction tolerance.

Training material was prepared and presented to a range of MW staff. The training provided an overview of each element of the live model, how to use the live model in an operational context and example pre-established scenarios.