The goal of this commentary is to critically evaluate the use of popular performance metrics in hydrologic modeling. We focus on the Nash-Sutcliffe Efficiency (NSE) and the Kling-Gupta Efficiency (KGE) metrics, which are both widely used in hydrologic research and practice around the world. Our specific objectives are: (1) to provide tools that quantify the sampling uncertainty in popular performance metrics; (2) to quantify sampling uncertainty in popular performance metrics across a large sample of catchments; and (3) to prescribe the further research that is needed to improve the estimation, interpretation, and use of popular performance metrics in hydrologic modeling. Our large-sample analysis demonstrates that there is substantial sampling uncertainty in the NSE and KGE estimators. This occurs because the probability distribution of squared errors between model simulations and observations has heavy tails, meaning that performance metrics can be heavily influenced by just a few data points. Our results highlight obvious (yet ignored) abuses of performance metrics that contaminate the conclusions of many hydrologic modeling studies: It is essential to quantify the sampling uncertainty in performance metrics when justifying the use of a model for a specific purpose and when comparing the performance of competing models.

This paper provides an overview of the key processes that generate floods in Canada, and a context for the other papers in this special issue – papers that provide detailed examinations of specific floods and flood-generating processes. The historical context of flooding in Canada is outlined, followed by a summary of regional aspects of floods in Canada and descriptions of the processes that generate floods in these regions, including floods generated by snowmelt, rain-on-snow and rainfall. Some flood processes that are particularly relevant, or which have been less well studied in Canada, are described: groundwater, storm surges, ice-jams and urban flooding. The issue of climate change-related trends in floods in Canada is examined, and suggested research needs regarding flood-generating processes are identified.

In late June 2013, heavy rainfall and rapidly melting alpine snow triggered flooding throughout much of the southern half of Alberta. Heavy rainfall commenced on 19 June and continued for 3 days. When the event was over, more than 200 mm and as much as 350 mm of precipitation had fallen over the Front Ranges of the Canadian Rocky Mountains. Tributaries to the Bow River including the Ghost, Kananaskis, Elbow, Sheep and Highwood, and many of their tributaries, all reached flood levels. The storm had a large spatial extent causing flooding to the north and south in the Red Deer and Oldman Basins, and also to the west in the Elk River in British Columbia. Convergence of the nearly synchronous floodwaters downstream in the South Saskatchewan River system caused record high releases from Lake Diefenbaker through Gardiner Dam. Dam releases in Alberta and Saskatchewan attenuated the downstream flood peak such that only moderate flooding occurred in Saskatchewan and Manitoba. More than a dozen municipalities declared local states of emergency; numerous communities were placed under evacuation order in Alberta and Saskatchewan. The media reported that more than 100,000 people needed to evacuate their homes, and five people died. At CAD$6 billion, the Province of Alberta estimated that it was the costliest natural disaster in Canadian history. At their peak, the water levels were the highest in the past 60 years, and nearing those of historic events of the late 1800s and early 1900s where records exist. There was major damage to infrastructure roads, bridges and culverts. Downtown Calgary was inundated, as were many communities such as High River and Bragg Creek. Debris flows and debris torrents affected communities such as Canmore and Exshaw, and isolated many mountain communities including closing the TransCanada Highway for several days. Environment Canada called it the “Flood of Floods.” Insured losses of CAD$2 billion included thousands of cars and homes demolished and damaged by backed-up sewers. Flood damage losses and recovery costs from the flood are projected to exceed CAD$6 billion.