Coupling physical understanding and statistical modeling to estimate ice jam flood frequency in the northern Peace-Athabasca Delta under climate change

TL;DR

This study combines physical and statistical modeling to predict how climate change may alter ice jam flood frequency in the Peace River, revealing a likely decrease in flood events under future climate scenarios.

Contribution

It introduces a physically-based conceptual model integrated with logistic regression and climate projections to assess future ice jam flood frequency in the Peace River.

Findings

Winter precipitation and temperature are key predictors of ice jam floods.

Projected flood frequency is likely to decrease under climate change scenarios.

Average waiting times between floods are expected to increase significantly.

Abstract

The Peace-Athabasca Delta (PAD) of northwestern Alberta is one of the largest inland freshwater deltas in the world, laying at the confluence of the Peace and Athabasca Rivers. The PAD is recognized as a having unique ecological significance and periodic ice jam flooding from both rivers is an important feature of its current ecology. Past studies have debated whether a change in ice jam flood (IJF) frequency on the Peace River has recently occurred, and what factors might be driving any perceived changes. This study contributes to this debate by addressing two questions: (1) what factors are most predictive of Peace River IJFs, and (2) how might climate change impact IJF frequency? This work starts with a physically-based conceptual model of the necessary conditions for a large Peace River IJF, and the factors that indicate whether those conditions are met. Logistic regression is applied to the historical flood record to determine which combination of hydroclimatic and riverine factors best predict IJFs and the uncertainty in those relationships given the available data. Winter precipitation and temperature are most predictive of Peace River IJFs, while freeze-up elevation contains little predictive power and is not closely related to IJF occurrence. The best logistic regression model is forced with downscaled climate change scenarios from multiple climate models to project IJF frequency for a variety of plausible futures. Parametric uncertainty in the best logistic regression model is propagated into the projections using a parametric bootstrap to sample many plausible statistical models. Although there is variability across emissions scenarios and climate models, all projections indicate that the frequency of Peace River IJFs is likely to decrease substantially in the coming decades, and that average waiting times between future IJFs will likely surpass recent experience.