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A practitioner-oriented regional hydrology data product for use in site-specific hydraulic applications
Kevin R Shook1, Zhihua He1, John W Pomeroy1
1Centre for Hydrology, University of Saskatchewan, Saskatoon, SK, Canada.
New hydrological data for the Canadian Prairies (PHyDAP) addresses sparse monitoring networks. This comprehensive dataset aids water management and infrastructure design in a water-stressed region.
Area of Science:
- Hydrology and Water Resources
- Environmental Modeling
- Canadian Prairies Ecozone
Background:
- Sparse monitoring networks and intermittently connected streams limit hydrological data availability in the Canadian Prairies.
- Water-stressed conditions necessitate improved data for effective water management and infrastructure design.
- Existing data gaps hinder robust hydraulic model applications in the region.
Purpose of the Study:
- To develop and present the Prairie Hydrology Design and Analysis Product (PHyDAP), a comprehensive regional hydrological dataset.
- To address limitations in hydrological input data for hydraulic modeling in the Canadian Prairies.
- To provide valuable data for water management decisions and infrastructure design.
Main Methods:
- Utilized a physically based hydrological modeling framework.
- Ran simulations for 38 to 150 years using three distinct climate forcing datasets.
- Generated outputs for over 4000 small basins (approx. 100 km²) across the ecozone.
Main Results:
- Created a dataset including vertical and lateral fluxes (rainfall, snowmelt, upland runoff, open water evaporation).
- Included basin streamflow data at hourly or 3-hourly intervals.
- The dataset covers extensive periods and a large number of small basins.
Conclusions:
- PHyDAP offers a significant advancement for hydraulic modeling applications in the Canadian Prairies.
- The dataset enhances capabilities for water management and infrastructure design in a data-scarce, water-stressed region.
- The study details the data derivation methodology, summarizes the product, and outlines potential use cases.
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