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Water data management platforms 
Modern Tools & Techniques for Water Resources Assessments & Management 
Amit Parashar 
17 September 2014 New Delhi 
LAND & WATER FLAGSHIP
Contents 
• CSIRO 
• Data management challenges 
• Data sharing platforms 
• Hydrological geofabric 
• Cloud computing 
• Demo
Top 1% of global research 
institutions in 14 of 22 research 
fields 
Top 0.1% in 4 research fields 
Darwin 
Alice Springs 
Geraldton 
2 sites 
Atherton 
Townsville 
2 sites 
Rockhampton 
Toowoomba 
Gatton 
Myall Vale 
Narrabri 
Mopra 
Parkes 
Griffith 
Belmont 
Geelong 
Hobart 
Sandy Bay 
Wodonga 
Newcastle 
Armidale 
2 sites 
Perth 
3 sites 
Adelaide 
2 sites Sydney 5 sites 
Canberra 7 sites 
Murchison 
Cairns 
Irymple 
Melbourne 5 sites 
CSIRO: Who we are 
Werribee 2 sites 
Brisbane 
6 sites 
Bribie 
Island 
People 
Locations 
Flagships 
Budget 
6000 
58 
9 
$1B+
Challenges in data management 
• Lots of investment in water data 
collection (collecting, finding, 
accessing and formatting of data) 
• Multiple agencies collecting data – 
different ways of managing data 
• No single point of truth (overlaps 
between agencies) 
• Fragmented data silos 
• Difficult to aggregate quality 
assured data set as input to 
research and inform policy
Challenges in data management 
• Supporting information/data requests again and again and again 
(usually for the same data) Need scaleable mechanism to share 
data 
• Water management pressures require increasing complex and 
integrated assessments to support decision makers. 
• As India moves towards IWRM & Basin Level Planning, water data 
managers will increasingly need to support a variety of 
jurisdictions, agriculture, urban, environment, energy 
• Community pressure for access to data (increased transparency)
Discover Access Extract, Transform, Load Understand 
Use 
Time and effort 
Research Focus 
To enable more efficient and effective management of 
water by improving the availability, accessibility and 
usability of existing and new water information products 
and services. 
Action 
Knowledge 
Information 
Data 
Action 
Knowledge 
Information 
Data
Spatial Information Service 
Stack – Data Sharing Platforms 
Discovery/Access/Integrate
Why? 
Provide data uniformly and we use it diversely? 
GIS Reports Research 
Desktop simulations 
and modelling 
Cloud computing and many others...
The Spatial Information Services Stack 
Present day
Integration – WaterML 2.0 
• Framework exists, we need a 
mechanism of sharing data between 
each other 
• Under Australia’s 2007 Water Act, 
BoM collects observations of storage 
level and stream flow from over 200 
providers across the nation. 
• CSIRO has led the development of 
WaterML 2 standard specifically for 
quantity and is currently extending it 
for water quality as well. 
• Time series data, allows near real 
time model-data integration
Geofabric – towards a single 
point of truth
Why? 
• No consistent national scale water map of Australia 
• Differences between States, regions, different resolutions 
• Classic examples: 
• 5 different catchment boundaries for the same catchment 
• Stream network does not match the DEM 
• Stream network where the gauges are not on the streams 
• Makes it difficult to compare and do basin level and national scale 
assessments
Hydrological Geofabric of Australia 
• The Hydrological Geofabric 
provides: 
• A consistent spatial framework with 
a historical gazetteer (location 
names); 
• A specialised GIS that registers 
relationships between features from 
the hydrological system (rivers, 
lakes, reservoirs, dams, aquifers, 
drains and monitoring points) 
• It also stores the agreed boundaries 
of basins, drainage divisions, 
catchments, aquifer and priority 
aquatic ecosystems.
User oriented & model driven products
Clouds – A watershed moment
Trends in technology
Cloud infrastructure
Software as a Service to support Research 
• Provide modelling services through cloud computing 
• Opportunistically applied to catchment modelling in Koshi 
• eWater Source is the river system modelling software used
Source Modelling Service 
Data 
Centre 
Compute 
Node e.g. 
local 
machine 
Source 
Modelling 
Service 
Compute 
Node e.g. 
Azure 
Compute 
Node e.g. 
Amazon 
External Modeller 
uploading data and running 
models via the Web 
CSIRO Scientist updating model 
science and functionality 
With the Source Modelling Service, 
complex model runs and analysis can be 
undertaken from anywhere in the world 
and scaled to handle increasingly 
complex problems through use of 
commercial Cloud Providers
Remote Sensing Cloud 
• Typically time consuming to find 
data and to process 
• Very large data sets 
• Require a subset of data often, 
(x,y,t) 
• Earth Observations Data Cube 
• Spatially regular 
• Calibrated images (cloud cover etc) 
• Long time series (Landsat) 
• Openly accessible using cloud 
technologies 
Calibrated “Cubed” 
Data in AG-DC
Bringing it all together 
DEMO
Scenario – Water Sharing in the Ringarooma 
Moorina 
Gauge: 6 
cumecs e-flow 
Water Storage
Sensor Data Feeds
Managing flow
Sensor Cloud 
Conceptual 
Architecture 
ACTION 
 
KNOWLEDGE 
 
INFORMATION 
 
DATA 
Sensor Cloud with real-time with eWater Source cloud 
modelling platform 
DATA 
Sensor Networks 
(real-time data) 
Data Providers 
(spatial, historical) 
 
 
APIs & Web Services 
 
Apps (DSS)
Sensor Cloud - benefits 
• Lots of projects under development in India: 
Hydrology projects – Sensor data, State Data, Central Data, Water Storage data, 
Climate data, River flow data, Ground water levels, Water Quality data & 
Historical data sets 
• Don’t need expensive clusters in-house 
• Easier to access and process parts of large data sets and much 
easier to share data and model outputs 
• Bring them all together in to sensor cloud to support community 
engagement, government to citizen and government to 
government engagement
Next steps? 
• Open data policy (real time and archived); Standards to support 
data exchange & standards based technology platforms (software 
and hardware) 
• Capacity building to support river basin planning 
• Build a community of practice, time, effort and focus. These are not 
easy things to implement. Focus efforts on an operational scenario.
Land & Water Flagship 
Amit Parashar 
t +91 8130443332 
E amit.parashar@csiro.au 
w www.csiro.au/ 
Thank you 
LAND & WATER FLAGSHIP

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22 - CSIRO - Water Data Management-Sep-17

  • 1. Water data management platforms Modern Tools & Techniques for Water Resources Assessments & Management Amit Parashar 17 September 2014 New Delhi LAND & WATER FLAGSHIP
  • 2. Contents • CSIRO • Data management challenges • Data sharing platforms • Hydrological geofabric • Cloud computing • Demo
  • 3. Top 1% of global research institutions in 14 of 22 research fields Top 0.1% in 4 research fields Darwin Alice Springs Geraldton 2 sites Atherton Townsville 2 sites Rockhampton Toowoomba Gatton Myall Vale Narrabri Mopra Parkes Griffith Belmont Geelong Hobart Sandy Bay Wodonga Newcastle Armidale 2 sites Perth 3 sites Adelaide 2 sites Sydney 5 sites Canberra 7 sites Murchison Cairns Irymple Melbourne 5 sites CSIRO: Who we are Werribee 2 sites Brisbane 6 sites Bribie Island People Locations Flagships Budget 6000 58 9 $1B+
  • 4. Challenges in data management • Lots of investment in water data collection (collecting, finding, accessing and formatting of data) • Multiple agencies collecting data – different ways of managing data • No single point of truth (overlaps between agencies) • Fragmented data silos • Difficult to aggregate quality assured data set as input to research and inform policy
  • 5. Challenges in data management • Supporting information/data requests again and again and again (usually for the same data) Need scaleable mechanism to share data • Water management pressures require increasing complex and integrated assessments to support decision makers. • As India moves towards IWRM & Basin Level Planning, water data managers will increasingly need to support a variety of jurisdictions, agriculture, urban, environment, energy • Community pressure for access to data (increased transparency)
  • 6. Discover Access Extract, Transform, Load Understand Use Time and effort Research Focus To enable more efficient and effective management of water by improving the availability, accessibility and usability of existing and new water information products and services. Action Knowledge Information Data Action Knowledge Information Data
  • 7. Spatial Information Service Stack – Data Sharing Platforms Discovery/Access/Integrate
  • 8. Why? Provide data uniformly and we use it diversely? GIS Reports Research Desktop simulations and modelling Cloud computing and many others...
  • 9. The Spatial Information Services Stack Present day
  • 10. Integration – WaterML 2.0 • Framework exists, we need a mechanism of sharing data between each other • Under Australia’s 2007 Water Act, BoM collects observations of storage level and stream flow from over 200 providers across the nation. • CSIRO has led the development of WaterML 2 standard specifically for quantity and is currently extending it for water quality as well. • Time series data, allows near real time model-data integration
  • 11. Geofabric – towards a single point of truth
  • 12. Why? • No consistent national scale water map of Australia • Differences between States, regions, different resolutions • Classic examples: • 5 different catchment boundaries for the same catchment • Stream network does not match the DEM • Stream network where the gauges are not on the streams • Makes it difficult to compare and do basin level and national scale assessments
  • 13. Hydrological Geofabric of Australia • The Hydrological Geofabric provides: • A consistent spatial framework with a historical gazetteer (location names); • A specialised GIS that registers relationships between features from the hydrological system (rivers, lakes, reservoirs, dams, aquifers, drains and monitoring points) • It also stores the agreed boundaries of basins, drainage divisions, catchments, aquifer and priority aquatic ecosystems.
  • 14. User oriented & model driven products
  • 15. Clouds – A watershed moment
  • 18. Software as a Service to support Research • Provide modelling services through cloud computing • Opportunistically applied to catchment modelling in Koshi • eWater Source is the river system modelling software used
  • 19. Source Modelling Service Data Centre Compute Node e.g. local machine Source Modelling Service Compute Node e.g. Azure Compute Node e.g. Amazon External Modeller uploading data and running models via the Web CSIRO Scientist updating model science and functionality With the Source Modelling Service, complex model runs and analysis can be undertaken from anywhere in the world and scaled to handle increasingly complex problems through use of commercial Cloud Providers
  • 20. Remote Sensing Cloud • Typically time consuming to find data and to process • Very large data sets • Require a subset of data often, (x,y,t) • Earth Observations Data Cube • Spatially regular • Calibrated images (cloud cover etc) • Long time series (Landsat) • Openly accessible using cloud technologies Calibrated “Cubed” Data in AG-DC
  • 21. Bringing it all together DEMO
  • 22. Scenario – Water Sharing in the Ringarooma Moorina Gauge: 6 cumecs e-flow Water Storage
  • 25. Sensor Cloud Conceptual Architecture ACTION  KNOWLEDGE  INFORMATION  DATA Sensor Cloud with real-time with eWater Source cloud modelling platform DATA Sensor Networks (real-time data) Data Providers (spatial, historical)   APIs & Web Services  Apps (DSS)
  • 26. Sensor Cloud - benefits • Lots of projects under development in India: Hydrology projects – Sensor data, State Data, Central Data, Water Storage data, Climate data, River flow data, Ground water levels, Water Quality data & Historical data sets • Don’t need expensive clusters in-house • Easier to access and process parts of large data sets and much easier to share data and model outputs • Bring them all together in to sensor cloud to support community engagement, government to citizen and government to government engagement
  • 27. Next steps? • Open data policy (real time and archived); Standards to support data exchange & standards based technology platforms (software and hardware) • Capacity building to support river basin planning • Build a community of practice, time, effort and focus. These are not easy things to implement. Focus efforts on an operational scenario.
  • 28. Land & Water Flagship Amit Parashar t +91 8130443332 E amit.parashar@csiro.au w www.csiro.au/ Thank you LAND & WATER FLAGSHIP