Poster Presentation NCGRT/IAH Australasian Groundwater Conference 2019

Near real-time decision support insights with fully-integrated hydrologic models (154)

Steven K. Frey 1 2 , Steven J. Berg 1 2 , Graham Stonebridge 1 , Derek Steinmoeller 1 , David Lapen 3 , Andre R. Erler 1 , Edward A. Sudicky 1 2
  1. Aquanty Inc., Waterloo, Ontario, Canada
  2. Earth and Environmental Sciences, University of Waterloo, Waterloo, Ontario, Canada
  3. Agricuture and Agri-Food Canada, Ottawa, Ontario, Canada

Providing a scientific basis for water management, and assessing the physical characteristics underlying hydrologic risk, typically requires watershed-scale assessments that encompass a few hundred km2 at a minimum. However, as an example, water resources for agriculture or resource development often require an understanding of river basin scale processes, which can cover areas up to 100,000 km2. Given the recent increase in losses attributed to large-scale extreme climate related events (i.e. overland pluvial flooding, excess moisture, and drought), and the concern that the frequency of these events will progressively increase in response to climate change, there is growing demand for large-scale hydrologic risk forecasts to support decision making. Because of complex interactions between climate, surface water, groundwater, and soil moisture across large watersheds, robust physically-based 3-D integrated hydrologic models provide a holistic means of performing water-related risk forecasts.

 In this talk we will present a near real-time hydrologic forecasting platform for 80,000 km2 of Southern Ontario, Canada. This forecasting system leverages a regional database containing hydrostratigraphy, soils information, land cover/vegetation, and topography. From this database, local high-resolution forecasting models are developed driven by an ensemble of weather forecasts and updated using an advanced data assimilation scheme with field-based sensors.  Hydrologic forecasts are generated at daily frequency for a two-week forecast interval, or in the case of an extreme event a high-resolution 18 hr forecast is released hourly for emergency response support. Since the platform uses the fully-distributed, physically-based model, HydroGeoSphere, it can generate forecasts for both gauged and ungauged locations.  The forecasts are disseminated to watershed stakeholders via a cloud-based portal that has been developed with watershed-level dashboards and on-the-fly analytics to support both short- and medium-term decision making for watershed management, flood response, and agriculture.