An integrated decision support system for Sydney Catchment Authority's water supply planning and operations

被引:0
|
作者
Harris, J. E.
Dallimore, C.
Loveless, A.
Yeates, P. S.
Maheswaren, S.
Kibria, G.
机构
关键词
Decision support systems; SCARMS; reservoir; three dimensional modelling;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Australia's surface drinking water resources are commonly comprised of multiple interconnecting dams with numerous users and various water quality priorities. Managing such systems is challenging and requires innovative methods to make use of complex database systems and therefore enable optimal decision-making. Decision support systems are designed to assist decision makers, managers and operators access relevant information and make informed short and long term operational and strategic decisions through the use of data, tools and knowledge. The Sydney Catchment Authority (SCA) is responsible for the provision of water to Sydney Water Corporation for treatment and distribution of drinking water to more than four million people in Sydney, the Blue Mountains and the Illawarra, and supply to Southern Highlands, Goulburn, and Shoalhaven communities. The water supply storages comprise 2600 GL across 10 major (plus 6 minor) water storage dams. Of these, Lake Burragorang, the Shoalhaven Scheme and Prospect Reservoir account for 81% of the SCA water storage capacity. These systems have multiple water users and varying water quality issues. A key concern in Warragamba Dam is flood inflow dynamics and the load of catchment contaminants that can lead to outlet water quality problems, including blue-green algae. The Shoalhaven Scheme, comprised of Lake Yarrunga, Fitzroy Falls Reservoir and Wingecarribee Reservoir, is managed with respect to hydroelectric power transfers, recreational use and downstream impacts. To manage the multiple dimensions of the storage network, a customised innovative tool is used for water supply planning and operations. The Sydney Catchment Authority Reservoir Management System (SCARMS) integrates observational data and validated catchment, hydrodynamic and water quality models into a decision support system. Five major SCA storages (Warragamba Dam, Tallowa Dam, Fitzroy Falls Dam, Wingecarribee Dam and Prospect Dam) are currently integrated into SCARMS. SCARMS integrates an extensive supply of both real-time and historical data sources for the five storages. Real-time data sources include stream flow rates and properties, in-lake meteorology and in-lake water column temperature and water quality. Historical data sources include routine physical, chemical and biological monitoring data collected by SCA over the past 40 years. All relevant data are integrated into SCARMS and are processed, quality assessed and visualised. The data are used to drive and validate coupled three-dimensional hydrodynamics and water quality models (The Estuary, Lake and Coastal Ocean Model, ELCOM, and the Computational Aquatic Ecosystems Dynamics Model, CAEDYM). The integration of field data and numerical models allows a combination of real-time, forecast and hindcast simulations of reservoir conditions to be conducted on an ongoing basis. Collation of the field data and model scenario output in a user-friendly interface provides decision support for daily operations and long-term strategic planning. Customised reports can be generated to communicate knowledge to the range of operators, managers and selected stakeholders. This data, model and knowledge package is housed at SCA and demonstrates successful innovations in collating a range of necessary tools into a seamlessly linked and customised decision support system for the management of large-scale water resource systems.
引用
收藏
页码:4043 / 4049
页数:7
相关论文
共 50 条
  • [31] An Integrated Water Assessment Decision Support System (IWADSS) for Government Decision Makers
    Ramsay, I
    Harris, C.
    Howes, T.
    Stevens, A.
    MODSIM 2005: INTERNATIONAL CONGRESS ON MODELLING AND SIMULATION: ADVANCES AND APPLICATIONS FOR MANAGEMENT AND DECISION MAKING: ADVANCES AND APPLICATIONS FOR MANAGEMENT AND DECISION MAKING, 2005, : 2387 - 2393
  • [32] A Decision Support System for Logistics Operations
    R-Moreno, Maria D.
    Camacho, David
    Barrero, David F.
    Gutierrez, Miguel
    SOFT COMPUTING MODELS IN INDUSTRIAL AND ENVIRONMENTAL APPLICATIONS, 2010, 73 : 103 - +
  • [33] Integrated water quality-water supply modeling to support long-term planning
    Weiss, W. Joshua
    Pyke, Grantley W.
    Becker, William C.
    Sheer, Daniel P.
    Gelda, Rakesh K.
    Rush, Paul V.
    Johnstone, Tina L.
    JOURNAL AMERICAN WATER WORKS ASSOCIATION, 2013, 105 (04): : 57 - 58
  • [34] THE DECISION AID PLANNING FOR A WATER-SUPPLY SYSTEM IN A FUZZY ENVIRONMENT
    YI, YW
    ZHANG, YS
    SYSTEMS ANALYSIS MODELLING SIMULATION, 1989, 6 (07): : 513 - 521
  • [35] Collaborative planning in integrated water resources management: the use of decision support tools
    Ubbels, A
    Verhallen, AJM
    INTEGRATED WATER RESOURCES MANAGEMENT, 2001, (272): : 37 - 43
  • [36] Decision Support Tool for Operational Planning of Field Operations
    Nilsson, Rene Sondergaard
    Zhou, Kun
    AGRONOMY-BASEL, 2020, 10 (02):
  • [37] Methods for Operations Planning in Airport Decision Support Systems
    Jesús GarcÍa Herrero
    Antonio Berlanga
    José M. Molina
    José R. Casar
    Applied Intelligence, 2005, 22 : 183 - 206
  • [38] Methods for operations planning in airport decision support systems
    Herrero, JG
    Berlanga, A
    Molina, JM
    Casar, JR
    APPLIED INTELLIGENCE, 2005, 22 (03) : 183 - 206
  • [39] AN INTEGRATED DECISION SUPPORT SYSTEM
    SIDDIQUI, KJ
    LIU, YH
    DOREEN, DD
    PROCEEDINGS OF THE 17TH ANNUAL NORTH AMERICAN CONFERENCE OF THE INTERNATIONAL BUSINESS SCHOOLS COMPUTER USERS GROUP: MANAGING INFORMATION TECHNOLOGY : BUSINESS SCHOOLS ROLE IN THE 1990S, 1989, : 124 - 130
  • [40] Decision support system for integrated management of mycotoxins in feed and food supply chains
    van der Fels-Klerx, H. J.
    Liu, C.
    Focker, M.
    Montero-Castro, I
    Rossi, V
    Manstretta, V
    Magan, N.
    Krska, R.
    WORLD MYCOTOXIN JOURNAL, 2022, 15 (02) : 119 - 133