Web-Based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate at Gauged and Ungauged Locations

Abstract

Rainfall Intensity–Duration–Frequency (IDF) curves are among the most essential datasets used in water resources management across the globe. Traditionally, they are derived from observations of historical rainfall, under the assumption of stationarity. Change of climatic conditions makes use of historical data for development of IDFs for the future unreliable, and in some cases, may lead to underestimated infrastructure designs. The IDF_CC tool is designed to assist water professionals and engineers in producing IDF estimates under changing climatic conditions. The latest version of the tool (Version 4) provides updated IDF curve estimates for gauged locations (rainfall monitoring stations) and ungauged sites using a new gridded dataset of IDF curves for the land mass of Canada. The tool has been developed using web-based technologies and takes the form of a decision support system (DSS). The main modifications and improvements between version 1 and the latest version of the IDF_CC tool include: (i) introduction of the Generalized Extreme value (GEV) distribution; (ii) updated equidistant matching algorithm (QM); (iii) gridded IDF curves dataset for ungauged location and (iv) updated Climate Models.

Nitrogen dynamics and nitrogen‐to‐phosphorus stoichiometry in cold region agricultural streams

“…In 2014, there was an extreme rainfall‐runoff event at all three streams, attributed to a heavy rainstorm (124.4 mm in 3 d [data retrieved from the “BRANDON A” historical weather station data from https://climate.weather.gc.ca]) in combination with very wet antecedent conditions (Ahmari et al., 2016; Wilson et al., 2019). Based on intensity–duration–frequency curves for the Brandon A weather station, a 100‐yr event has a magnitude of 109 mm over 24 h, while a 25‐yr event has a magnitude of 84 mm over 24 h (Schardong et al., 2020). Pre‐snowmelt precipitation (1 November to 30 April) ranged from 145 to 200 mm, and the total rainfall in May and June that contributed to the extreme rainfall‐runoff event ranged from 249 to 268 mm at these sites (Wilson et al., 2019).…”

Using the present to estimate the future: A simplified approach for the quantification of climate change effects on urban flooding by scenario analysis

“…This is not possible when using more common top-down approaches (i.e., Felder et al, 2018;Gusain et al, 2020;Padulano et al, 2021). It should be noted that no consolidated method to update IDF curves is available, but a large number exist (e.g., Hosseinzadehtalaei et al, 2020;Requena et al, 2021;Schardong et al, 2020;Schardong & Simonovic, 2019) that are also F I G U R E 1 0 Flooded area for the Scenario D under peak conditions highly sensitive to the adopted downscaling technique and to the ensemble size.…”

Sponge City: Using the “One Water” Concept to Improve Understanding of Flood Management Effectiveness

“…As an example, using the IDF CC Tool 3.5 developed by the University of Western Ontario, Canada, to demonstrate climate change trends [43] for London, Ontario, Canada with the GCM prediction, the IDF (Intensity-Duration-Frequency) partial results for major storm events (25-, 50-, and 100-year) are shown in Figure 6. Projecting from years 2020 to 2070 (based on historical data), the intensities of a 100-year storm are expected to increase by 0.23%/year.…”