Diana Allen
Department of Earth Sciences
Simon Fraser University, British
Columbia, Canada
Workshop on Climate Change Risk Assessments
Climate-Change Impacts Research Group – October 30, 2008
Aquifer-Stream Interactions
•  Aquifers are recharged by directly
by precipitation and indirectly by
interaction with surface water.
•  Some aquifers have a strong
interaction with surface waters.
•  Indirect recharge occurs where
water enters the aquifer (losing
stream)
•  Discharge to the stream from the
aquifer can also occur (gaining
streams)
From Winter et al., 1998
Interaction with a River
(Leith and Whitfield, 1998)
Sustaining Low Flows
•  In BC, unglacierized catchments tend to show low flows
during late summer.
–  In low elevation coastal regions, summer is the main
low flow time of the year,
–  in snow-dominated mountain or interior regions, latesummer is the secondary low flow period (besides
winter low flow due to freezing and storage of
precipitation as snow).
•  During summer low flow conditions it can be expected
that stream flows are mainly fed by groundwater.
If low flows are sustained by groundwater, then
any changes to the groundwater system
(particularly recharge and use) can affect low flows
Climate Change Models
and
Regional Forecasts
Since 1990, the has been
increasing spatial
resolution
of global climate models
(GCMs)
IPCC (2007)
4th Assessment Report
gives the most up-to-date
climate change model
results
Source: IPCC 4th Assessment Report, 2007
Observed temperature (top) and
modeled temperature (bottom)
Observed (top) and modeled
precipitation (bottom)
Source: IPCC 4th Assessment Report, 2007
Global Climate Models
Source: IPCC 4th Assessment Report, 2007
Scenarios and Model Uncertainty
Multi-Model Global Predictions
Source: IPCC 4th Assessment Report, 2007
Changes are annual means for the SRES A1B scenario (mid-line)
for the period 2080 to 2099 relative to 1980 to 1999.
Predicted Changes for North America
Source: IPCC 4th Assessment Report, 2007
Climate Change Projections for the Pacific Northwest
Changes in Annual Mean
Temperature
Precipitation
2020s
Low
+ 1.1ºF (0.6ºC)
-9%
Average
+ 2.2ºF (1.2ºC)
+1%
High
+ 3.4ºF (1.9ºC)
+12%
2040s
Low
+ 1.6ºF (0.9ºC)
-11%
Average
+ 3.5ºF (2.0ºC)
+2%
High
+ 5.2ºF (2.9ºC)
+12%
2080s
Low
+ 2.8ºF (1.6ºC)
-10%
Average
+ 5.9ºF (3.3ºC)
+4%
High
+ 9.7ºF (5.4ºC)
+20%
Source: Climate Change Group, University of Washington
Summary of Predicted Climate Change in BC
•
Average annual temperature in BC may increase by 1ºC to
4ºC.
•  Average annual precipitation may increase by 10 to 20
percent, but could decrease by up to 10%.
•  Many small glaciers in southern BC may disappear.
•  Some interior rivers may dry up during the summer and early
fall.
No predictions for groundwater conditions because these
require site-specific models
1. Problem Definition
1.  Threat – change in groundwater levels (due to climate
change) and consequent impacts
1.  on ability to sustain groundwater levels
2.  on low flows
The case study: the Grand Forks aquifer in southcentral British Columbia, Canada
Attempt to quantify impact of climate change on
seasonal groundwater levels within an aquifer that is
strongly influenced by surface water.
Grand Forks Valley
N
E
W
S
Granby River
City of Grand
Forks
BC
Kettle River
Washington
State
Observation well
-  monthly measurements
-  good connection to river
water levels
Modelling Approach
aquifer geological model
numerical model
Climate
model
river
discharge
river flow models
downscaling
precipitation and
temperature
weather generation
recharge model
(spatially distributed)
scenario simulations
2. Management Objective
1.  There really wasn’t one for this case study. This was
not a risk assessment project.
2.  There might have been though. We could have had a
management objective of maintaining some minimum
groundwater level in the aquifer or some minimum
baseflow in Kettle River during summer under the
following conditions:
1.  Climate change
2.  Groundwater extraction
3. Indicators of Risk
1.  We had no performance measures in respect of trying
to determine how the impact to the groundwater level
might have been minimized under climate change and
pumping conditions. We only looked at climate
change, to understand the system.
2.  However, we could have used magnitude of
groundwater level decline alone or to infer declines in
baseflow during summer.
3.  We did have performance measures in respect of
trying to calibrate the numerical groundwater model
how well the model reproduced the groundwater
levels under the current climate scenario
4. Management Options
1.  None considered in this study, but we could have
looked at different future pumping scenarios to
determine which one would have the smallest impact
on groundwater levels or low flows.
In our study we held the pumping rates constant so as to
isolate the climate change impact on the groundwater
system.
5. Uncertainties that were Analyzed Quantitatively
1.  Downscaled climate data – how well did the
downscaled climate data match the historic climate
data?
2.  How well did the recharge match the observed
recharge – semi-quantitative
3.  How well did the calculated groundwater levels match
the observed groundwater levels under current climate
conditions
4.  We did not consider the uncertainty in the following:
1.  The GCM used
2.  The future scenario used
6. Taking Uncertainties into Account
1.  Normally, a sensitivity analysis is carried out when
modeling to look at the potential range of properties
that could be used in the model and what effect
varying those properties has on the model outcome.
2.  This is a matter of course in groundwater modeling –
•  we vary recharge to see what happens to the
groundwater levels
•  we vary the aquifer properties to see what
happens
the sensitivity analysis had been done previously
during the construction of the model, but no sensitivity
analysis was undertaken in respect of the climate
change study.
7. Description of the System’s Processes
1.  We built a groundwater model and used it to quantify
how future climate change might impact groundwater
levels.
The following series of slides show the stages of model
development
GEOLOGIC MODEL:
1) Standardize litholog database
2) Reclassify / simplify
(database-level geologic interpretation)
1) Interpret hydrostratigraphy
generalize
Construct layer model in GMS
- uniform hydraulic properties
(homogeneous)
3D litholog database
reduced to 5 material
classes
Cross-section layout
(selection of boreholes)
and interpretation
Cross-section interpretation
(layer extent, lenses)
Bedrock surface
model (bottom of
valley sediment fill)
Deep sands
(probably more
extensive in reality)
Clay / Till
(deep, mostly
unknown sediments)
Silt / silty sands
(lacustrine deposits,
with fluvial sediments)
Sands (“aquifer”)
(fluvial & glaciofluvial
sediments)
Gravels (“aquifer”)
(most recent fluvial
sediments)
MODEL CONSTRUCTION:
3D MODFLOW
Recharge applied in a
distributed fashion
to top active layer
Specified head
for rivers
RECHARGE MODELING:
There were 2 steps to derive recharge estimates:
Generation of Climate Scenarios
Mapping Distributed Direct Recharge
Historical climate data included daily, monthly and annual
summaries.
Daily climate data from CGCM1 (GHG+A1) (current, 2020’s,
2050’s) were downscaled using 2 methods:
- Environment Canada (principal-component knearest neighbour method (PCA k-nn).
- Statistical DownScaling Model (SDSM)
CGCM1 downscaling results:
Precipitation
Temperature
CGCM1 downscaling results:
Precipitation
Temperature
CLIMATE SCENARIOS FROM GCMs:
LARS-WG Weather Generator
Climate scenario daily weather
Recharge model
(calibrated to local weather)
(perturb local weather)
Groundwater flow
model
Calibration of
LARS-WG
RECHARGE ESTIMATION:
•  Determined recharge zones based on soil and aquifer
properties and depth of water
•  Used the HELP 1-D recharge model produce estimates
of recharge for each recharge zone
•  We included irrigation return flow in irrigation districts
•  Recharge linked to the model using a GIS
HELP recharge model
-  one dimensional flow
-  64 percolation columns
-  “better than guessing recharge”
Recharge “zones”
Irrigation return flow
“zones” (irrigated fields)
increase recharge to
aquifer under irrigated
fields
Pumping from
production wells
estimated from water
usage in summer only
RESULTS
Mean annual recharge
at present climate
% changes in future
climate scenarios
HYDROLOGY AND RIVER MODELING:
1.  Analysis of hydrometric data
2.  Used BRANCH to model stage-discharge relation at
different locations along the Kettle and Granby Rivers
3.  Downscaled GCM climate data using PCA k-nn method to
derive hydrographs of daily discharge for climate change
scenarios:
Current (simulated)
2010-2039
2040-2069
Daily discharge derived
from downscaled GCM
earlier peak flow
longer low flow
higher flow in winter
(more snowmelt / rain)
lower baseflow
CALIBRATION RESULTS:
Overall model error <6% RMS
2010-2039
Difference in water levels between historical
and future climate scenarios
May 11
June 29
Aug 29
Nov 1
2040-2069
Exchange with the
River
(no pumping)
- historical climate
- pumping
reduces outflow to
river in summer
(less baseflow)
(pumping)
Floodplain
Non-pumping
Pumping
Change in
Groundwater
Storage
with Climate
Big Y Irrigation
District
Change in
Groundwater
Storage with
climate
Non-pumping
Pumping
8. Analysis of the Sensitivity of Conclusions
•  How sensitive are our conclusions in
respect of:
•  Assumptions
–  Fundamentally we assume that the statistical
relationships, linking observed time series to
GCM variables, will remain valid under future
climate conditions.
–  Because we only used one GCM - that it is
representative of potential future climate
–  That our selection of downscaling method was
correct
8. Analysis of the Sensitivity of Conclusions
•  Parameter values – for historical model
–  Historical climate is well represented – pretty
confident due to weather generation match
–  Modeled recharge is accurate – we only used one
model – uncertain
–  Aquifer geology is correct – as best we could do
–  Aquifer properties are correct – could be an order of
magnitude off
–  River stage is accurate
•  Generally we are confident in these
numbers to within 6% of observed
groundwater levels
8. Analysis of the Sensitivity of Conclusions
•  Parameter values – for future model
–  Future climate – based on only one GCM, one
scenario for that GCM, and one downscaling method
•  Total potential error could be significant,
but we did not evaluate different
possibilities
Thank you