Assessment of empirically-derived parameters and their transferability in mountain glacier modeling and application for regional melt projections under climate change scenarios

• Author / Creator

  Kotila, Amanda

• Mountain glaciers, key sources of freshwater to downstream ecosystems and users, are
  responsive and vulnerable to changes in climate. Understanding their current influence, their
  potential future changes, and consequences of those changes are all important research goals, so
  many modeling approaches have been developed to address these questions. However, modeling
  at the regional scale can be difficult since input data from field measurements is limited and there
  is high spatiotemporal variability. High uncertainty in model predictions can come from empirical
  modeling parameters, often based on limited observations which are then applied to other glaciers
  in potentially very different topographic settings. In this study, we aim to assess parameter
  uncertainty and transferability by revisiting empirical parameters that are commonly used in
  glacier modeling and explore potential future glacier behaviours by utilizing a range of values for
  each glacier modeling parameter. This approach allows us to quantify uncertainty bands due to
  both projected future climate uncertainty and predicted model uncertainty.
  First, rather than using a set of single parameter values we explore a range for the value of
  each parameter based on their physically meaningful maximum and minimum values. We set up a
  modeling framework by coupling glacier melt, surface mass balance, and spline-based volume-area scaling (called evolution hereafter), denoted as CGME model for Coupled Glacier Mass-balance Evolution model, to predict glacier melt runoff. Within the CGME model, we evaluate
  two temperature-index melt modeling approaches: the Classical Temperature Index Model
  (CTIM), which uses a degree-day approach, and the Pellicciotti Temperature-Index Model
  (PTIM), which incorporates radiative melt factors. Our study area is the Athabasca River Basin in
  Alberta, Canada, which contains 258 glaciers.
  After calibration and optimization, we find that both of the melt models used in our CGME
  model predicted similar ranges of uncertainty (i.e., 95 Percent Prediction Uncertainty, 95PPU) in
  melt runoff, but the CTIM-based model reproduced more observed data points within its prediction
  uncertainty range (71% of observed data were captured within the predicted 95PPU) whereas the
  PTIM-based model reproduced 31% of the observed data.
  Second, we applied these optimized parameter ranges at the regional scale for the period
  1984-2007. Approximately 63% of the glaciers in the region had a normalized uncertainty value
  of greater than 0.5 for melt runoff, indicating that the parameter range transferability is not
  appropriate for the majority of glaciers in the region and that small glaciers are especially sensitive
  to input parameter variability. The framework developed here assesses the parameter
  transferability issue, especially in catchments where small-sized glaciers are dominant contributors
  to downstream water-ways that may have a cumulative ecological impact.
  Further, we explore the impact of potential future change. The glacier model is forced using
  4 CMIP6 GCMs under two shared socioeconomic pathways scenarios (SSP126 and SSP585) for
  the 258 glaciers for the period 1980-2100. From the maximum physically meaningful range for
  each parameter, 100 sets of model input parameters are sampled using Latin Hypercube Sampling
  technique. The 100 sets of sampled parameters are used with the future projected and downscaled
  climate data to force 100 simulations using CGME model for each glacier. This allows us to assess
  the projections’ ranges of uncertainty (using the 95PPU) stemming from input parameterization.
  Glacier changes are assessed based on two categorizations: glacier initial area and glacier
  initial elevation. Our results, based on size, show that glaciers are predicted to decrease in volume
  75-80%, decrease in area 72-78%, and discharge 70-80% of their potential melt runoff in the first
  forty years of the simulation period (1980-2019, the historical period). Monthly predicted flow
  regimes not only indicate greatly reduced melt runoff as the century progresses, but also the loss
  of late spring and early fall melt runoff. Assessing potential changes by glacier initial elevation
  indicated similar trends, though low elevation glaciers are predicted to be especially responsive,
  discharging ~95% of their melt runoff during the historical period. Monthly melt runoff reflects
  similar trends to those found during size analysis, though low elevation glaciers have the most
  extreme response. These assessments show the potential range of glacier changes under various
  future climate scenarios and the uncertainty stemming from model parameterizations. This can
  assist with freshwater resource management as well as adaptation and mitigation planning and
  implementation.

• Subjects / Keywords

  • melt runoff modeling
  • temperature index
  • mass balance modeling
  • glacier area
  • glacier model uncertainty
  • CMIP 6
  • glacier volume

• Graduation date

  Spring 2023

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/r3-bgax-hd61

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.