POSTER TEMPLATE BY:

www.PosterPresentations.com

Presenting Author:

Colin Fraser, colin.fraser@lorax.ca

Lorax Environmental Services Ltd., 2289 Burrard Street, Vancouver, BC, Canada V6J 3H9

Co-authors (alphabetically by last name):

Jennie Gjertsen, Jennie.Gjertsen@goldcorp.com

Goldcorp Inc., 666 Burrard St #3400, Vancouver, BC, Canada V6C 2X8

Scott Jackson, scott.jackson@lorax.ca

Lorax Environmental Services Ltd., 2289 Burrard Street, Vancouver, BC, Canada V6J 3H9

James Scott, James.Scott@goldcorp.com

Goldcorp Inc., 666 Burrard St #3400, Vancouver, BC, Canada V6C 2X8

A Changing Climate: Environmental Assessment for a Proposed Mine in Yukon, Canada

1. Background

This poster pertains to the construction, operation, reclamation and closure of

the Coffee Gold Mine (Project), a proposed gold development project in west-

central Yukon, approximately 130 km south of Dawson, YT, Canada (Figure

1a). Major infrastructure related to mining and processing at the Project area

includes: an upgraded road; a primary waste rock storage facility; several

open pits; water diversion structures and storage ponds; haul roads; primary

and secondary crushing facilities; heap leach facilities; a gold refinery; an

accommodation complex; and an all-weather airstrip. Most of the proposed

infrastructure will be situated at high elevation (~1,250 m asl).

Local climate conditions for the site are typical for the region: average annual

air temperature (T) is -2.6 °C and mean annual precipitation (P) is estimated

to be 485 mm (65% rain, 35% snow) at elevation 1,300 m. Inspection of the

instrumental record from nearest weather stations (e.g., Dawson; Mayo, YT;

Pelly Ranch. YT) confirms T and P have been increasing on an annual basis

since the 1960s (refer to Figure 1b, T trends are shown). Further, climate

change scenario data for the Project area indicate continued change for

these key water balance variables (i.e., +5°C and +20% increases by 2100;

Figure 1c and 1d). Against this changing climate context, engineering and

permitting studies are ongoing at the mine site.

3. Baseline Monitoring

A baseline hydrology program was initiated at the Project site in the

autumn of 2010, starting with installation of 3 automated hydrometric

stations. Eight additional stations were established in 2014 to further

characterize the streamflow regime of headwater basins containing Project

infrastructure. Monthly sampling trips are made year-round to develop

rating curves and maintain the stations. Hourly discharge records are

computed from rating curves and high-resolution water level data.

A high-elevation climate station was installed in summer 2012 and

measures: air temperature and relative humidity (2 m); wind speed and

direction (10 m); incoming solar radiation (2 m); barometric pressure; and

precipitation (tipping bucket rain gauge with solid phase adapter and Alter

shield). Snow course measurements are also carried out at several

stations (i.e., various elevations, aspects and cover types) following YT

protocols. Figure 2 shows a comparison of mine site- and regional T and

P data.

5. Water Balance Model Description

The Coffee Gold WBM is built using GoldSim software, a highly-structured, robust platform designed for

flow/contaminant tracking. The WBM is climate-driven (i.e., uses the 84-year, daily- reconstructed climate record

which accounts for climate change to generate flows) and is comprised of two sub-models:

• Natural Flow/Baseline (No Project) – This sub-model was constructed first and calibrated to accurately predict

streamflow conditions for a Baseline condition (refer to Table 1 and Figure 4a for additional detail and a

representative calibration example).

• Base Case (With Project) – For this sub-model of the WBM, year-by-year mine footprints for open pits, the

waste rock storage facility, the heap leach facility, soil and ore stockpiles and related Project infrastructure were

encoded onto the Baseline sub-model.

4. Generating the Long-term Climate Record

The procedures below were followed to generate a long-term,

daily- climate record for the Coffee Gold mine site:

• Daily climate data (i.e., T and P) from the mine site and a

nearby regional station (McQuesten, YT) were assembled to

create monthly predictive relationships based on overlapping

data.

• Next, the regional station (predictor) and monthly predictive

relationships derived for T and P were utilized to compute a

long-term synthetic climate record representative of the mine

site.

• To span the full Project life (i.e., Construction (2018 to 2020);

Operations (2021 to 2032); Closure (2033 to 2042); and Post-

closure (2043 to 2100), the Coffee Gold climate record was

looped three times to create an 84-year, daily- climate record.

• To represent a plausible future condition, climate change

scenario data were downloaded from the Scenario Network for

Alaska and Arctic Planning, a research collaborative that

produces downscaled, historical and projected climate data for

sub-Arctic and Arctic regions (SNAP, 2016).

• Monthly T and P predictions (2001 to 2100, CMIP3/AR4 – A2

Scenario, 2 km grid) for grid points covering the mine site

extent were downloaded, averaged and used to scale the 84-

year daily climate record.

• At monthly time step, assembled climate data are shown in

Figure 3.

2. Objectives of the Poster

The panels below: i) summarize steps taken to

create a long-term (84-year), daily- climate

record that accounts for a changing climate;

and ii) introduce a water balance model (WBM)

that was constructed and calibrated using

GoldSim modelling software.

To evaluate potential water quantity issues and

risks associated with the Project, and to fulfill

requirements of the environmental assessment

process, the 84-year climate record was used to

drive the WBM with outputs used to quantify

residual streamflow changes attributable to the

Project in a valued component context.

a c

db

Figure 2: Coffee Gold baseline climate data compared to period of record for 21 regional climate stations.

Building upon applicable research and modelling of

Christophersen and Seip, 1982 and Seip et al., 1985, the

architecture of the watershed model is predicated on the

concept that natural streamflow, or runoff generated from mine

footprint areas, is comprised of three types of flow as

described by Maidment (1993): i) quickflow, generated by

storm or snowmelt events and often resulting in peak flow

events; ii) interflow, derived from near-surface, lateral

movement of infiltrated meteoric water; and iii) baseflow, the

portion of surface discharge derived from GW discharge. This

architecture is shown in Figure 4b.

Same catchment boundaries, climate and hydrology inputs

described for the Natural Flow sub-model (Table 1) were used

to populate undisturbed portions of watersheds in the Base

Case sub-model. However, to represent the disturbed

condition, mine footprints for open pits, waste rock storage

facilities, the heap leach facility, soil and ore stockpiles and

related Project infrastructure were encoded into the Base

Case sub-model.

Table 1: Natural Flow (Baseline) Sub-model

Catchment Boundaries, Elevation Data

• Watershed boundaries and hypsometric outputs (i.e., curves and representative bands of elevation data) for local catchments were generated from 1:50,000 mapping data.

• To encode elevation dependent climate parameterizations into the WBM, drainages were separated into three elevation bands (400-800 m, 800-1200 m and >1200 m).

Climate

• The natural flow sub-model of the WBM was driven by a 28-year precipitation, air temperature and evaporation record that was looped three times.

• Precipitation and air temperature inputs were scaled by elevation using gradients ascertained from site- and regional climate data.

• Monthly climate change scenario data (from the Scenario Network for Arctic Planning) for the A2 emission scenario (2-km resolution) were used to scale precipitation and air temperature inputs over the long term (Closure and Post-closure phases).

Hydrology

• Baseline hydrology data from autumn 2010 to December 2015 were combined with regional streamflow data to generate long-term synthetic streamflow records.

• The sub-model was calibrated at daily time-step using long-term, daily- synthetic streamflow data as the target.

Outputs

• For this sub-model, 84-year long predicted streamflow records are generated by the WBM. Flow records are produced for seven local tributaries and three large river nodes at a monthly time step.

• The outputs per WBM node consist of 28 unique iterations (i.e., 28-year climate record is time stepped) each extending the 84-year time-period.

Figure 3: Air temperature (upper panel) and precipitation (lower panel) inputs to the

Coffee Gold Water Balance Model. Shading in the upper and lower panels

demarcates the main phases of the Coffee Gold Mine Plan. The final climate record is

a daily dataset, but shown at monthly frequency above.

Figure 4: a) Daily water balance model output (red) for a node located

on Halfway Creek, compared to a reconstructed streamflow time-

series (blue) for corresponding time period (2010-2014); b) A

schematic presenting an overview of the three-reservoir water

balance model in conceptual format.

Figure 1 (to left) : a) Map of Canada showing location of the

Coffee Gold Mine; b) Temperature trends by season for the

Dawson A and Pelly Ranch climate stations (1952 to 2013); c)

Climate change scenario data (T) for a grid point near the Project

and worst case (i.e., RCP8.5 or A2); and d) Climate change

scenario data (P) for a grid point near the Project and worst case

(i.e., RCP8.5 or A2).

Climate Change and Streamflow in the Yukon

As part of the streamflow assessment, decadal trends were

assessed by analyzing Natural Flow sub-model outputs (Figure

6). Consistent with findings for the Yukon (e.g., Streiker, 2016),

GoldSim WBM results confirm the following streamflow

changes for a warmer and wetter future climate regime:

• Progressively earlier onset of freshet, later occurrence of

autumn freeze up, longer ice-free season.

• Shifts to the proportions of P realized as rain vs. snowfall.

• Increases in baseflow conditions and likelihood of mid-winter

melt events.

• Progressive increases in total annual discharge.

a

b

6. Data Analysis and Streamflow Changes

For each identified WBM node, GoldSim outputs (i.e., resultant flow series from the Natural

Flow and Base Case sub-models) were compared to one another with Project-related flow

changes being indexed against natural/baseline conditions. WBM model outputs were

averaged to monthly flow values and predicted streamflow changes were summarized by a

percent change metric as follows:

Percent change (%) = ((Mine Altered Flow – Natural Flow)/Natural Flow) x 100 (Eqn: 1)

A suite of streamflow change characteristics (i.e., direction, magnitude, frequency and

reversibility of streamflow change) are proposed to guide a detailed streamflow change

assessment. These change characteristics are selected to best quantify and describe

potential changes against key components of a natural flow regime (Poff et al., 1997).

WBM outputs were screened using tabular and graphical formats (e.g., flow vs. percent

change plots, flow duration curve plots and time series plots comparing Natural Flow vs.

Base Case outputs by Project phase). Example plots for the CC-1.5 model node are shown

below (Figure 5). Identified streamflow changes will ultimately be described in a valued

component context for the surface hydrology (water quantity) discipline, noting the

streamflow summary will also inform other water-related studies (e.g., GW, surface water

quality, fish and aquatic habitat) to be described as part of the environmental assessment.

Figure 5: Example plots based on Goldsim WBM outputs.

Figure 6: Decadal averaged- monthly streamflow patterns for

the CC1.5 WBM node (22 km2 drainage area). Results are

shown for three time bands: 2030-39, 2060-69 and 2090-99.

References:

Christophersen, N. and H.M. Seip. 1982. A model for streamwater chemistry at

Birkenes, Norway. Water Resources Research. 18:4, 977-996.

Poff, N.L. et al. 1997. The natural flow regime: a new paradigm for riverine

conservation and restoration. BioScience 47:769-784.

Seip, H.M. et al. 1985. Model of sulphate concentration in a small stream in the Harp

Lake catchment, Ontario. Can. J. Fish Aquat. Sci. 42: 927-937.

SNAP, 2016. Scenario Network for Alaska and Arctic Planning. Data portal for climate

change scenario data: https://www.snap.uaf.edu/tools/data-downloads

Streicker, J., 2016. Yukon Climate Change Indicators and Key Findings 2015.

Northern Climate ExChange, Yukon Research Centre, Yukon College, 84 p.