Identification of changes in floods and flood regimes in Canada using a peaks over threshold approach

Abstract

Abstract:Recent flood events in Canada have led to speculation that changes in flood behaviour are occurring; these changes have often been attributed to climate change. This paper examines flood data for a collection of 132 gauging stations in Canada. All of these watersheds are part of the Canadian Reference Hydrometric Basin Network (RHBN), a group of gauging stations specifically assembled to assist in the identification of the impacts of climate change. The RHBN stations are considered to have good quality data and were screened to avoid the influences of regulation, diversions, or land use change. Daily flow data for each watershed are used to derive a peaks over threshold (POT) dataset. Several measures of flood behaviour are examined based on the POT data, which afford a more in-depth analysis of flood behaviour than can be obtained using annual maxima data. Analysis is conducted for four time periods ranging from 50 to 80 years in duration; the latter period results in a much smaller number of watersheds that have data for the period. The changes in flood responses of the watersheds are summarized by grouping the watersheds by size (small, medium, and large) and also by hydrologic regime (nival, mixed, and pluvial). The results provide important insights into the nature of the changes that are occurring in flood regimes of Canadian rivers, which include more flood exceedances, reduced maximum flood exceedance magnitudes for snowmelt events, and earlier flood events.

Comparison of automatic procedures for selecting flood peaks over threshold based on goodness‐of‐fit tests

“…Previous studies conducted by Burn et al () and MacDonald and Burn () used POT to investigate trends in timing and magnitude of flood peaks in Canada. Combining this previous work led to a database of 285 stations in which thresholds were selected manually following the same instructions and using graphical diagnostic tools other than the P value plot (see Lang et al, ; Burn et al, , for further details). Some of these stations were extracted from the Canadian Reference Hydrometric Basin Network (RHBN), whose stations have been screened for the influences of regulation, diversion, or land use changes.…”

“…Cunderlik and Ouarda () studied the timing and magnitude of flood peaks in Canada and showed that for several rivers seasonal snowmelt events are now occurring earlier during the year and that an increasing number of flood peaks are taking place in the fall. Burn, Whitfield, and Sharif () observed no significant trend in magnitude for rainfall floods but noticed a decrease in the magnitude of the snowmelt events. These studies illustrate the advantage of the use of POT in trend analysis of floods.…”

Climate Variability Alters Flood Timing Across Africa

“…Changes in the timing of the annual flood, for example, have widespread impacts on flood-based farming systems and therefore the livelihoods for populations who adapt their floodplain management and agricultural practices to the normally experienced rise and fall of the flood wave (Paul, 1984;van Steenbergen, 1997). Accordingly, research has been carried out to characterize the distribution of hydrological regimes globally (Dettinger & Diaz, 2000;Lee et al, 2015), to explain the largest seasonality gradients (Hastenrath, 1996), and to understand how hydrological regimes might be impacted by climate change (Blöschl et al, 2017;Burn et al, 2016;Cunderlik & Ouarda, 2009). The objective of this paper is to investigate whether there are significant differences in the timing of annual floods between different modes of climate variability across Africa, where there is a strong link between ©2019.…”

Comparison of estimation methods for a nonstationary index-flood model in flood frequency analysis using peaks over threshold

“…Notice that the criteria used for selecting 470 the stations creates a selection bias where stations located in the Prairies and the northern regions are relatively few. Burn et al (2016) investigated changes in peaks over threshold data in Canada using a classification based on three types of flood regimes. A similar approach is adopted herein, where hierarchical clustering (Ward, 1963) is applied to define seasonality regions using the seasonality 475 measure of Equation (9).…”