Water Resources Observation Network

Transcription

1 Water Resources Observation Network Ross Ackland WRON Theme Leader, CSIRO SEEGrid-III December 1 st 2006 Enabling a national perspective on Australia s water resources... 1

2 Murray Darling system is running on empty As of today, Murray Irrigation will cease supply to nearly 2,500 NSW farms 2

3 Drying & Warming Climate Growing Urban Demand Over allocation to Irrigation Uncapped Groundwater Extraction Water is becoming increasingly scarce Expanding Plantations Preserving Environmental Flows Expanding Farm Dams Bushfire Recovery 3

4 The Water Scarcity Challenge Ensuring integrity of our environment (aquifers, rivers, floodplains) Ensuring security of supply to users 4

5 Towards a solution Infrastructure Entitlements Trading Good Water Information is the Key Pricing Planning Management We can t make more, but we can reduce cost, reduce wastage, and use it more efficiently 5

6 Water Information Value Forecasting Reporting Analysis Done poorly Integration Distribution Done poorly to very well Aggregation Quality Assurance Increasing Value Collation Monitoring Generally done well, by over 100 groups, but could be vastly improved 6

7 Current approaches to water information sharing 7

8 Moving beyond the portal approach Key phrases I picked up at SEEGrid III Intelligent search is needed Data structures developed that enable intelligent search Human readability to machine readability Decomposition Collaborative tools (collaboration not competition) Interoperability is a disruptive technology Community agreed standards The problem is not technical Strong typing vs Weak Typing (SOAP vs REST) 8

9 What will WRON be? A set of components brought together as a loosely coupled system based on web services conforming to standard interfaces Databases Implementations of models Real time in situ sensors Remote sensing devices (eg. satellites) Reporting & Forecasting Tools (eg. real-time trend analysis) 9

10 Hydrometric data Usage & entitlement data Geospatial data Models 10

11 Standards are central to WRON Compliant WRON is a large scale knowledge-intensive interoperability problem. Not feasible to develop WRON by predefining all the standards for information models and component interfaces. Needs an evolvable architecture for information resources and information needs. WRON Compliance will be an incremental process of definition, implementation, evaluation, refinement. WRON Reference Model will define the interoperability standards and interfaces required discoverability, access, interchange. 11

12 WRON Reference Model Based on ISO RM ODP a framework for specification 1. An object modelling approach to system specification. 2. The specification of a system in terms of viewpoints. 3. The definition of a system infrastructure providing distribution transparencies for system applications. 4. A framework for assessing system conformance. Will rely heavily on existing standards efforts from OGC, ISO, W3C, OASIS, OMG etc.. Will rely heavily on the domain experts in water (collaboration) 12

13 Reference Model as an iterative process 13

14 CSIRO Research Investment WRON Framework ($3.3m) Reference Model Development Semantic service composition, workflows Ontology engineering Sensor networks 2. WRON Technologies ($3.1m) National scale hydrological model, fine scale models Model Data Fusion methods Interfaces to legacy systems Water quality trend analysis methods 3. WRON Systems ($1.4m) UGroWRON Urban surface water/ground water urban design WRON integration of legacy systems, building on AWDIP WRON/MTSRF Water Quality Report Card for GBR catchments Australian Dam Levels Monitor extension to risk management tools Burdekin Saltwater Intrusion Proposed Groundwater monitoring Tasmania to calibrate ground water models Condamine Balonne real time operational decision support 14

15 WRON Computational and Storage infrastructure $1.4m investment in computing infrastructure. 60Tb storage, 20 high end blade server cluster Will host CSIRO remote sensing archives including AVHRR, MODIS and legacy water resource datasets Will host web service hydrological models and enable rapid model runs Facility to be used by WRON partners to deliver WRON products. 15

16 Semantic service composition The uptake of Web Services technology for cross-domain apps is huge Based on the promise of component re-use and interoperability between software systems Targeted inter-organisations, used intra-organisations Key standards: XML, WSDL, SOAP, BPEL4WS (+security) Limiting factors Service granularity (too big, description limitations) Explosion of services will become unmanageable Solution: Build in machine-processable semantics Abstract models (top-down) deal with too many resources Semantic metadata permits inference to support the composition Benefits Provides a non-programmatic language to express problem goals Supports the domain experts to build a cross-domain application (like a spreadsheet) Permits opportunistic, rapid development of information resources Uses standard ontology language (OWL) Ontology development tools UO/XO provide domain models for expert user User specifies problem using composer s workbench Composition compiler generates optimised executable plan over network resources Which can be embedded in any application 16

17 Now extend this to WRON Expose the simulation models as web services How do we provide information into and out of a model? How do we describe a model and its constraints as a service? Add the sensors to the picture (big ones and little ones) How do we get information out of sensors? How do we make sensor networks tell us what we want? Formal ontologies can play many roles 17

18 The need for names for things Terminology and descriptions of key parameters or attributes is quite varied. States and territories use different language to describe key components of water resource management (e.g. allocations/entitlements/use/diversions sustainable yield, farm dams, catchment storages)... In some areas there are also inconsistencies between assessed overallocation at a Basin scale compared with component water systems (e.g. Murray-Darling Basin, Snowy river) This can produce confusion when reporting and analysing data Formal semantics can help here In developing the taxonomy (ensure consistency, and defined relationships) In verifying the data (does it conflict with the axioms?) Ontology mappings allow multiple vocabularies 18

19 19 Close the Semantic gap! Accelerate and make the aggregation process more transparent!

20 OGC Web Services Initiative Phase 4 Interoperability experiment to help advance OGC standards Sponsored industry participation in seven Threads Sensor Web Enablement SWE: SOS, WNS, SPS, SAS Developed using 52 o North open source implementation Evaluate the potential use of OGC standards for sensor networks in WRON Influence the standards process Gain expertise in OGC services 20

21 SOS & SAS implementation QCAT CBR QCAT Node Servlet Container WNS Gatton Node Activemq (JMS) SOS SOS Client Belmont Node Registration Message Translator SAS Ejabberd SAS Client Burdekin Node (XMPP) 21

22 Services publicly available 22

23 SOS & SAS clients 23

24 Testbed Project Status Jun 13 Aug 15 Oct 15 Dec 22 Basic Services Robust Services External Use August 15 Basic Sensor Observation Services available SAS Report near completion BONUS: Sensor Alert Service available. October 15 Reliable data feed from QCAT to services Alpha clients Sensor Observation Service Report near completion December 22 Final Reports including Sensor Planning Service. Stable clients Example SensorML and compliant Units. 24

25 Burdekin Sensor Network Fleck designed as programmable self-powered node for ad hoc networks. Used in sugar cane farmlands in Queensland s Burdekin region. Sensors distributed around water bores monitor how much water is being pumped out, and the effect this has on salinity levels and the watertable. Information is fed through a wireless network directly to the office of the local water board. With very low standby current and a long radio range, Flecks are delivering WRON compliant data streams for improved management. 25

26 WRON Web based applications Demonstration Australian Dam Levels Monitor Web service delivery of dam levels 26

27 Conclusion WRON provides a national vision of how to improve the management of water resources through better management of the information about water. Achieving WRON will require collaboration at a national level through an incremental process delivering benefits in the short, medium and long term. CSIRO s investment in WRON is intended to research and develop the next generation technologies required to deliver WRON. 27