How to cite the IDF_CC Tool?

About the IDF_CC tool

Description of the tool

Read more/About the IDF_CC tool

Municipal water management in Canada is heavily dependent on the use of Intensity-Duration-Frequency (IDF) curves for planning, design, and operation of municipal water infrastructure. Many watershed management activities also rely on the use of IDF curves, including those related to water supply, water quality management and flood control. This web-based tool provides an approach for updating IDF curves under a changing climate and is available to anyone interested in developing IDF curves that incorporate projected climate change impacts.

While there is a need in almost every Canadian municipality to adapt to changing climatic conditions, there is a lack of necessary expertise within municipalities for implementing current research related to the impact of climatic change on IDF curves (Sandink et al, 2016). Thus, one of the primary aims of the tool is to standardize the IDF update process and make the results of current research on climate change impacts on IDF curves accessible to everyone (Simonovic et al., 2016; Sandink et al., 2016 and Schardong et al., 2020). The developers and supporting agencies believe that a freely available, computerized IDF update tool will aid in the selection of effective climate change adaptation options at the local level, advancing the decision-making capabilities of municipalities, watershed management authorities and other key stakeholders. The tool also provides a direct link between Canadian municipalities and the research community, creating opportunities for further research and innovation.

The IDF_CC tool is designed as a simple and generic decision support system to generate local IDF curve information that accounts for the possible impacts of climate change. It applies a user-friendly GIS interface and provides precipitation accumulation depths for a variety of return periods (2, 5, 10, 25, 50 and 100 years) and durations (5, 10, 15 and 30 minutes and 1, 2, 6, 12 and 24 hours), and allows users to generate IDF curve information based on historical data, as well as future climate conditions that can inform infrastructure decisions.

The IDF_CC tool stores data associated with 8986 Environment and Climate Change Canada operated rain stations from across Canada (ECCC, 2023). Roughly 700 of these stations have 10 years of data – the minimum time series used by Environment Canada to develop IDF curves for a specific location. Users can also create and share their own rain station information. Version 7.0 of the tool uses version 3.30 of the Environment Canada IDF dataset, released in October, 2023 (Environment and Climate Change Canada, 2022). This dataset is available through the Gauged locations module accessible from the main menu of the tool.

The latest version of the IDF_CC tool also uncludes the module for Ungauged locations. The ungauged IDF curve estimates, for all durations (5, 10, 15, 30 min, 1, 2, 6, 12 and 24 hrs) and return periods (2, 5, 10, 25, 50 and 100 years), are extracted directly from the gridded dataset produced for the IDF_CC tool and described in detail in Gaur et al., (2020) and in the Technical and User's Manuals (available from the Help menu).

The IDF_CC tool allows users to select from three sets of climate data for the development of IDF relationships under future conditions:
  • CMIP6 – 30 Global Circulation Models (GCMs) from the CMIP6 driven by a new set of Shared Socioeconomic Pathway (SSP) scenarios representing different socioeconomic assumptions. Specifically, a set of scenarios were chosen to provide a range of distinct end-of-century climate change outcomes. Earlier, the CMIP5 featured four Representative Concentration Pathways (RCPs) that examined different possible future greenhouse gas emissions. These scenarios - RCP2.6, RCP4.5, RCP6.0, and RCP8.5 – have been updated for CMIP6. These updated scenarios are called SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, each of which result in similar 2100 radiative forcing levels as their predecessor in CMIP5. Data for CMIP6 climate models are available from Lawrence Livermore National Laboratory (2021a)
  • CMIP5 – 24 Global Circulation Models from the CMIP5 driven by 3 Representative Concentration Pathways (RCPs). These models are adopted based on the availability of complete sets of future greenhouse gas concentration scenarios, also known as Representative Concentration Pathways (RCPs), which are described in detail in the Technical and User’s Manuals. Datasets for these models are available from Department of Energy, Lawrence Livermore National Laboratory (2021b).
  • PCIC bias corrected models (CMIP6) – 26 downscaled Global Circulation Models (GCMs) from the CMIP6 driven by a new set of Shared Socioeconomic Pathway (SSP) scenarios representing different socioeconomic assumptions. Specifically, a set of scenarios were chosen to provide a range of distinct end-of-century climate change outcomes. Earlier, the CMIP5 featured four Representative Concentration Pathways (RCPs) that examined different possible future greenhouse gas emissions. These scenarios - RCP2.6, RCP4.5, RCP6.0, and RCP8.5 – have been updated for CMIP6. These updated scenarios are called SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, each of which result in similar 2100 radiative forcing levels as their predecessor in CMIP5. Data for CMIP6 climate models are available from Lawrence Livermore National Laboratory (2021a)
  • PCIC bias corrected models (CMIP5) - 24 downscaled GCMs that simulate various climate conditions to local rainfall data. The models were selected based on the availability of projections (RCP 2.6, 4.5 and 8.5). For each model, two bias corrected diverted datasets are available from PCIC (2021). To access functionalities and explore advanced options (for example, provide your own data/stations and carry out analysis for future scenarios using Global Circulations Models), please create your account or login if you have an account already.

References:

  • Environment and Climate Change Canada (2023) Engineering Climate Datasets, available at http://climate.weather.gc.ca/prods_servs/engineering_e.html, last accessed July 2021.
  • Department of Energy Lawrence Livermore National Laboratory (2021a) CMIP6 - Coupled Model Intercomparison Project Phase 6, https://pcmdi.llnl.gov/CMIP6/, last accessed July 2021.
  • Department of Energy Lawrence Livermore National Laboratory (2021b) Earth System Grid Federation, https://esgf-node.llnl.gov/projects/esgf-llnl/, last accessed July 2021.
  • Pacific Climate Impacts Consortium (PCIC) (2021) Statistically downscaled climate scenarios, https://pacificclimate.org/data/statistically-downscaled-climate-scenarios last accessed July 2021.
  • Schardong, A., S. P. Simonovic, A. Gaur, and D. Sandink (2020) Web-based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate at Gauged and Ungauged Locations, Water, Special Issue Extreme Value Analysis of Short-Duration Rainfall and Intensity–Duration–Frequency Models, 12, 1243; doi:10.3390/w12051243, open access, https://www.mdpi.com/2073-4441/12/5/1243/pdf .
  • Gaur, A., Schardong, A., Simonovic, S.P. (2020) Gridded extreme precipitation Intensity—Duration-Frequency estimates for the Canadian landmass. J. Hydrol. Eng. 2020, 25.
  • Environment Canada (2020): Engineering Climate Datasets, available at http://climate.weather.gc.ca/prods_servs/engineering_e.html, last accessed July 2017.
  • Sandink, D., S.P. Simonovic, A. Schardong, and R. Srivastav, (2016) “A Decision Support System for Updating and Incorporating Climate Change Impacts into Rainfall Intensity-Duration-Frequency Curves: Review of the Stakeholder Involvement Process”, Environmental Modelling & Software Journal, 84:193-209.
  • Simonovic, S.P., A. Schardong, D. Sandink, and R. Srivastav, (2016) “A Web-based Tool for the Development of Intensity Duration Frequency Curves under Changing Climate”, Environmental Modelling & Software Journal, 81:136-153.
  • Srivastav, R.K., A. Schardong and S.P. Simonovic, (2014) “Equidistance Quantile Matching Method for Updating IDF Curves Under Climate Change”, Water Resources Management: An International Journal, 28(9): 2539-2562.

Acknowledgements and Financial Support

We would like to acknowledge financial support by the Canadian Water Network Project under the Evolving Opportunities for Knowledge Application Grant to Prof. S.P. Simonovic for the initial phase of the project, and the Institute for Catastrophic Loss Reduction for continuous support of this project.

 

 

Research and Development Team

Slobodan P. Simonovic, Professor Emeritus, Western University

Andre Schardong, Western University

Abhishek Gaur, Western University

Dan Sandink, Institute for Catastrophic Loss Reduction

IDF_CC Tool 7.0