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AIP-6 Water SBA GEOSS Water Services (GWS) Introduction

AIP-6 Water SBA GEOSS Water Services (GWS) Introduction. AIP-6 Kickoff, Silver Spring MD, USA 28-29 March 2013 David Arctur David Maidment University of Texas at Austin. AIP-6 GEOSS Water Services Team. Globally Distributed Team. Weather. PYXIS. Disaster Mgmt. JRC-ECMWF GloFAS. GIWS.

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AIP-6 Water SBA GEOSS Water Services (GWS) Introduction

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  1. AIP-6 Water SBAGEOSS Water Services (GWS)Introduction AIP-6 Kickoff, Silver Spring MD, USA 28-29 March 2013 David Arctur David Maidment University of Texas at Austin

  2. AIP-6 GEOSS Water Services Team

  3. Globally Distributed Team Weather PYXIS Disaster Mgmt JRC-ECMWF GloFAS GIWS CUAHSI Suitability Analysis Agriculture BYU ISPRA ARPA NASA LDAS NOAA NWS UT Health GCI/DAB TBD? KISTERS NIWA HRC

  4. University of Texas at Austin CIESS – Center for Integrated Earth System Science David Maidment, David Arctur • Overall project coordination for GEOSS Water Services • Relations among standards orgs (OGC, WMO) and stakeholders

  5. Brigham Young University (BYU) Department of Civil & Environmental Engineering Jim Nelson, Dan Ames • WaterML development • Outreach and capacity building in Latin America • Web hosting services & toolkit for developing countries

  6. University of Saskatchewan, CanadaGlobal Institute for Water Security (GIWS) Howard Wheater, BrankoZdravkovic • Datasets for precipitation, stream flow, and non-standard hydro-meteorological variables, encoded in WaterML 2 • Development and testing of the software related to publishing, querying, and retrieving of the current and historical measurement data • Contribute to web portal user interface development for improved usability

  7. CUAHSI – Consortium of Universities for Advancement of Hydrologic Science Alva L. Couch, Rick P. Hooper • CUAHSI Hydrologic Information System: A five-year project to create a data discovery platform for water data • A catalog of water data time series (HIS Central). • A standard for water data publication (WaterML). • Community-moderated controlled vocabularies for time series metadata, including: • Measured variables, units, sample medium, etc. • An ontology of concepts, together with a novel ontologically-driven data discovery client.

  8. CUAHSI goals for GEOSS and AIP-6: Long term: CUAHSI catalog in GEOSS format. Short term (AIP-6): • Factor CUAHSI catalog into separate reusable subsystems for: • Publication and discovery • Controlled vocabulary curation, reusability, and internationalization. • Enable federated CUAHSI catalogs in Italy, South Korea, and New Zealand.

  9. US NASAHydrological Sciences Laboratory Matt Rodell, Bill Teng • Satellite data products, modeling, and observations from TRMM (precipitation), LDAS (soil moisture, evapo-transpiration) • WaterML 2 time series outputs from these sources

  10. US NOAAData Management and Integration Team Matt Austin, Michelle Hertzfeld • Satellite data products, modeling, and observations for global precipitation and other products • Coordination with Integrated Global Water Observations (IGWCO) Community of Practice • OGC standard services, GCI and GEO Portal support • Exploring implementation of WaterML; not operational for AIP-6

  11. Joint Research Centre (JRC)Institute for Environment and Sustainability Peter Salamon, Milan Kalas • JRC Climate Risk Management Unit within the Institute for Environment and Sustainability – focus on observation, evaluation, anticipation and communication of impacts of weather extremes and future climate change • Development of the Global Flood Awareness System (GloFAS) initiated in 2011, to study WaterML-based architecture and web services support

  12. European Centre for Mid-range Weather Forecasting (ECMWF) Florian Pappenberger, Fredrik Wetterhall • Carries out scientific and technical research for development and operation of global models and data-assimilation systems for the Earth system, and for improving quality of weather forecasts • Will provide test data of the TIGGE archive and a combination of the ECMWF land surface scheme HTessel and CamaFlood (a river routing algorithm) • Exploring use of WaterML for probabilistic discharge forecasts within GEOWOW

  13. Italian National Institute for Environmental Protection and Research (ISPRA) Martina Bussettini, Michele Munafò • Environmental research institute and national environmental agency to coordinate federation of regional systems • Has recently implemented WaterML service-based architecture to federate, standardize and publish hydrological time series • Will host a hydro-catalog of all Italian Regions, in which one can search and find water data in a standard format

  14. Regional Agency for Environmental Protection in Emilia-Romagna (ARPA ER) SilvanoPecora, Bordini Fabio • Gives technical support to regional, district and local authorities on environmental policy • Hydro-Meteo-Climate Service (SIMC) is a thematic operational node of ARPA ER; implementing WaterML-based architecture for real-time flood and other water management modeling for European Flood Awareness System (EFAS)

  15. New Zealand National Institute for Water and Atmospheric Research (NIWA) JochenSchmidt, Brent Wood • Manages about 20% of New Zealand water monitoring stations; coordinates NZ regional water agencies • Hosting OGC WMS, WFS, CSW, SOS services and WaterML time series data

  16. Horizons Regional Council (HRC) of New Zealand Jeff Watson, Sean Hodges • Regional water agency • Plans to implement WaterML-based architecture for time series data and services • Interested to use NASA LDAS to define severity and spatial variability of current drought conditions

  17. KISTERS Water Solutions Michael Natschke, Stefan Fuest • Provides environmental data management solutions in many countries, and helped develop WaterML 2 • WISKI and Hydstra products used to collect, process and disseminate hydrological information • Interoperability Server KIWIS serves hydrological data and derived data products from various sources through WaterOneFlow/WaterML1, SOS1/O&M and SOS2/WaterML2 • Will contribute to the architectural design and infrastructure of GEOSS Water Services, and offer their professional server and service components KiTSM and KIWIS

  18. the PYXIS innovation, Inc. Perry Peterson, IdanShatz • Software company that develops geospatial-intelligence technologies • Provides WorldView client application based on use of an optimized hexagonal discrete global grid (DGG); this will be used for analysis and modeling of hydrologic processes on disparate data discovered through GEOSS resources and populated into the DGG • Directly accesses GEOSS registries via CSW; supports OGC WMS, WFS, WCS, SOS, WPS

  19. AIP-6 GEOSS Water Services • Purpose: Provide additional operational, federated water information resources in GEOSS • Scope: A global registry of water data, map and modeling services catalogued using the standards and procedures of the OGC and the WMO • In collaboration with WMO CHyTheme 2 “Data Operations and Management”, 2012-16 • In support of GEO Water Task and Integrated Global Water Cycle Observations (IGWCO) Community of Practice

  20. AIP-6 GEOSS Water Services • Application Services • Community info services, for serving: • Observation Services • Water time series • Model Services • Computed water time series • Map Services • Web maps, geoprocessing Based on OGC WaterML, WFS, WMS, SOS, CSW

  21. Water Time Series Services Stack

  22. From AIP-5 Water SBA

  23. AIP-5 Architecture and Interaction WFS GRDC Metadata (UnivTx host) GEOSS Search WFS Dominican Republic Metadata (UnivTx host) WWO Map Viewer ArcGIS Online / PYXIS WorldView WFS USGS Metadata (UnivTx host)

  24. AIP-5 Architecture and Interaction SOS GRDC WaterML2 (Kisters host) WWO Map Viewer WOF Dominican Republic WaterML1 (BYU host) ArcGIS Online / PYXIS WorldView REST USGS WaterML1 (USGS host)

  25. Time Series Metadata (differences)

  26. AIP-6 Thematic Goals – 1 • Provide a systematic way for publishing map services of water observations that index locations of accessible WaterML time series services. • Produce web services of the results of global models for flood and drought analysis, including: • EC Global Flood Awareness System (GloFAS) • NASA/NOAA Global Land Data Assimilation System for drought assessments • Link web services for observations and modeling, so observations can inform model calibration, and so models can furnish larger context for observations

  27. AIP-6 Thematic Goals – 2 • Form federated national water data services for common variables • Italy: ISPRA national, ARPA regional agencies • New Zealand: NIWA national, HRC regional • Synthesize data, map, and modeling services to support specific useful applications, eg, linkage of watershed delineation with precipitation mapping over watershed + flow observations + model results at outlet • Advance the utilization of water services in developing countries, through access to global web services, and lightweight methods of publishing local data

  28. AIP-6 Connections • GEOSS Water Services can connect to • Other Water SBA threads (Esri, GLOS, MEDINA) • Technical threads (Esri, GEOWOW) • Other related threads (GeoViQua (Ag), FCU1 (DM), FCU2 (Ag)) • Capacity Building, End-User focus

  29. Project Output: enabling Thematic Mapsof water information anyone can find & use • Water data & model output providers follow consistent practices in applying the OGC O&M model and WaterML 2 standard • This model description becomes part of the WMO Glossary of Terms • GEOSS provides rules for publishing these maps • Easy registration and quick, consistent discovery How we’ll know we’re done: • We can search GEOSS for time series of soil moisture, precipitation, stream flow and get a federated map of the results • Other results…?

  30. World Soil Moisture from the NASA Global Land Data Assimilation System (GLDAS) http://www.arcgis.com/home/webmap/viewer.html?webmap=7d6cefdf3f324b55b08c136654e91612 Charts show 3-hourly variation (37,000 values) of soil water content of the top 1m of soil from 2000 to 2012 Popup on point links to data and chart New Zealand A very wet region with little seasonality A dryer region with significant seasonality

  31. Global Water Maps Describe a water property over a domain of space and time • History • Current conditions • Forecasts Water Property ModelWeb SensorWeb Precipitation Evaporation Transpiration Soil Moisture Streamflow Groundwater Reservoirs Future Past Present

  32. Water SBA Breakout Discussion • Mature AIP-5 • User Requirements • Use of GCI • New elements, alterations • Ministerial Summit demo proposals • Data Sharing • More in-situ observations • Involvement of Developing Countries / Capacity Building

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