The Innovation in Larger Organisations Award recognises larger organisations such as utilities, universities, government departments and larger business that have fostered innovation to solve a significant environmental and/or water resource related problem; develop a product, solution or service; undertake research or trial applications; share, communicate and ensure acceptance and take up of new knowledge, technology or research; improve manufacturing or business processes and/or improve sales, promotion and product/service delivery.
Water utilities are challenged by the need to assess pathogenic risks without incurring unnecessary monitoring costs. For many years, SA Water's intensive monitoring strategy included both, 'routine' (e.g. monthly) and 'non-routine' (high rainfall event) monitoring. Despite the expensive effort, times of elevated risk were difficult to predict with certainty. Considering this, a question was asked: how can we optimise source water monitoring to improve data accuracy and minimise cost?
The refinement of our expensive cryptosporidium monitoring strategy was initiated by our operators, which has so far achieved operational savings of around $300,000 per year.
One of the components of this broader initiative was an innovative technological approach, assisting with the development of catchment and system-specific thresholds and triggers. Water Data Services designed a sampling device that could identify periods of peak water quality risk, using a programmed automated sequence of sample collection and discarding until the accurate peak flow sample was collected – a world-first!
This overall innovative approach reduced manual effort and monitoring costs; improved data quality; and, packaged-up with the revision of water quality incident triggers, resulted in health regulator-endorsed response protocols and streamlined follow-up and routine sampling requirements.
All whilst maintaining customer service levels and product water quality!
The Climate Resilience Analysis Framework and Tools (CRAFT) project has developed new tools to help water planners and policy-makers assess the impact of climate change on water resource systems and guide adaption planning.
Climate projections often include high levels of uncertainty, making it challenging for decision-makers to plan for the short-term future and capital-intensive assets with 50 to 100 year or more lifespans. CRAFT researchers took a novel approach to this problem by first looking at the system's purpose (for example, water security, water quality), its components (for example, surface water storage, managed aquifers, importing water), and what other options might be available. These options were then 'stress tested' against potential climate changes to identify the potentially unforeseen modes of system failure (sometimes referred to as 'black swans'), and develop the most resilient solution given a range of future climate scenarios. CRAFT encapsulated this process into a simple five-step framework and developed the companion software foreSIGHT, which tests the resilience of systems under a wide range of climate scenarios and weather conditions.
CRAFT addresses a significant knowledge gap – how to best use climate projections to modify or augment a system's design to improve its resilience in a changing hydroclimate.
SA Water is leading the way in the implementation of smart technology to improve water services and network management for their customers. In Penneshaw, a town situated on Kangaroo Island in South Australia, SA Water invested in the installation of flow and pressure sensors in the main supply network, plus installed 300 smart meters on all residential and business customer connections within the township.
The Penneshaw water supply network has a problematic history. Its remote location and scarcity of fresh water resources led to the construction of a desalination plant in 1999. In combination with the high energy burden required to operate the desalination plant, the system also has a high percentage of non-revenue water being lost, making it a costly system to operate.
The idea to install flow and pressure sensors within the network in combination with the installation of 300 smart meters for all residential and business properties, is an innovative solution to help identify and combat the network's non-revenue water loss issue.
This unique approach provides SA Water with the data to help identify and locate faults within the network causing water loss that will be remediated, leading to long-term environmental and financial benefits.
The South East Flows Restoration Project (SEFRP) is a $60m investment to assist salinity management in the Coorong South Lagoon, enhance flows to wetlands in the Upper South East, and reduce drainage outflow at Kingston beach. The project area extends 93.4 kilometres, predominately along the existing Taratap and Tilley Swamp drain corridors from the existing Blackford Drain near Kingston in the state's South East, extending to the Salt Creek outlet into the Coorong.
The SEFRP involves constructing a new flow path from the existing Blackford Drain to the Coorong at Salt Creek, providing capacity to deliver a further median volume of 26.5GL per year directly into the Coorong. The project also engineered the capacity to inundate the Tilley Swamp Watercourse by an additional 4200 hectares to total a 6100 hectare wetland area enabling a water storage capacity of up to 42GL. This provides the South Eastern Water Conservation and Drainage Board (SEWCD Board), as the operator/owner of the infrastructure, the flexibility and operational capacity to deliver water to the Coorong when required.
Water NIPA makes it cost-effective to deploy water pipe break detection systems for the sprawling suburban water networks present in America, Australia and New Zealand. It does this by coupling a predictive simulation model with machine learning to create a system that can detect pipe break events.
There are a number of existing solutions currently available for this problem. The first is to deploy a large number of expensive pressure, acoustic and other sensors to identify pipe breaks in real-time. This may be a cost-effective and valuable solution for high density areas (city CBDs and main arterial roads) but is not likely cost-effective for sprawling urban networks.
Secondly, there exist other systems that utilise machine learning using historical and ongoing data for break events. They are thus limited to areas for which data is available and need to be reconfigured if the network is altered in the course of expansion, repairs or regular operations.
This solution leverages technologies to overcome the shortcomings of other methods.
The impact is water utilities will know of broken pipes before their customers, which will improve service, limit water loss and increase customer satisfaction.