Introducing Non-Stationarity into the Development of Intensity-Duration-Frequency Curves under a Changing Climate
| Autor: | Andre Schardong, Slobodan P. Simonovic, Daniele Feitoza Silva, Joel Avruch Goldenfum |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Return period
Canadá Matching (statistics) non-stationarity lcsh:Hydraulic engineering Geography Planning and Development Teoria dos valores extremos Climate change Aquatic Science Biochemistry lcsh:Water supply for domestic and industrial purposes intensity-duration-frequency curve lcsh:TC1-978 Covariate Econometrics Mudanças climáticas Duration (project management) Extreme value theory Chuva Water Science and Technology lcsh:TD201-500 Non-stationarity Rainfall intensities climate change rainfall intensities Curvas IDF Generalized extreme value distribution Intensity-duration-frequency curve Environmental science Quantile |
| Zdroj: | Water, Vol 13, Iss 1008, p 1008 (2021) Repositório Institucional da UFRGS Universidade Federal do Rio Grande do Sul (UFRGS) instacron:UFRGS Water Volume 13 Issue 8 |
| ISSN: | 2073-4441 |
| Popis: | Intensity-duration-frequency (IDF) relationships are traditional tools in water infrastructure planning and design. IDFs are developed under a stationarity assumption which may not be realistic, neither in the present nor in the future, under a changing climatic condition. This paper introduces a framework for generating non-stationary IDFs under climate change, assuming that probability of occurrence of quantiles changes over time. Using Extreme Value Theory, eight trend combinations in Generalized Extreme Value (GEV) parameters using time as covariate are compared with a stationary GEV, to identify the best alternative. Additionally, a modified Equidistance Quantile Matching (EQMNS) method is implemented to develop IDFs for future conditions, introducing non-stationarity where justified, based on the Global Climate Models (GCM). The methodology is applied for Moncton and Shearwater gauges in Northeast Canada. From the results, it is observed that EQMNS is able to capture the trends in the present and to translate them to estimated future rainfall intensities. Comparison of present and future IDFs strongly suggest that return period can be reduced by more than 50 years in the estimates of future rainfall intensities (e.g., historical 100-yr return period extreme rainfall may have frequency smaller than 50-yr under future conditions), raising attention to emerging risks to water infrastructure systems. |
| Databáze: | OpenAIRE |
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