DATA PRODUCTION

Climate impact indicators
Global essential climate variables/indicators used

Precipitation and Temperature from the HydroGFD2.0 dataset. This will be used to bias correct global climate model (GCM) data from the IPCC CMIP5 project. Nineteen GCM scenarios for two RCPs, (4.5 and 8.5) are used to represent the range of temperature and precipitation change anticipated for our study region, using k-means clustering.

Regional/local indicators used and produced

Indicators of change will be hydrologic outputs, namely streamflow and runoff as well as some timing and volume metrics (yet to be determined).

Global data to regional/local scale

Step 1: Bias correct (QQ mapping approach) future climate forcing (GCM Precip + Temp data) using GFDv2

Step 2: Downscale HydroGFD2.0 forcing data (using inverse distance weighting, IDW methodology) to resolution of the hydrologic model (i.e., HYPE, mean sub-basin size ~650 km2). Compare precipitation amounts to those derived for HYPE from the original SMHI-derived Arctic-HYPE forcing (WFD), and other relevant Canadian datasets in the Nelson River basin (western Hudson Bay), where there is considerable disagreement among precipitation datasets.

Step 3: Calibrate hydrologic model using HydroGFD2.0 forcing and simulate streamflow and runoff for the entire historic period (1961-2015, model spin up from 1961-1979). Observed streamflow data (for calibration) from Dery et al. (2016), which presents a gap-filled, continuous dataset within the region of interest.

Step 4: Simulate streamflow and runoff using two future time periods (data from Step 1): 2030s (2021-2040) and 2050s (2041-2070). Evaluate changes in streamflow and runoff for each time period, and the entire period (2021-2070) relative to the simulated historic climate normal time period (1981-2010). Specific gauge locations of interest include major gauged outlets to Hudson Bay (Nelson and Churchill Rivers), and 16 control (regulation) points within the Nelson River basin.

Step 5: Compare specific simulation metrics to HYPE simulations driven by original SMHI-derived Arctic-HYPE forcing (WFD) during both the historical and future projections to assess the relative impact precipitation forcing data have on projections of future streamflow and runoff.


University of Manitoba


Global Water Futures

 

Poster displayed at the Kick–Off meeting, 7/8 September 2017, Norrköping, Sweden