Assessing the performance of daily to subdaily temporal disaggregation methods for the IDF curve generation under climate change. Issue 4 (27th March 2023)
- Record Type:
- Journal Article
- Title:
- Assessing the performance of daily to subdaily temporal disaggregation methods for the IDF curve generation under climate change. Issue 4 (27th March 2023)
- Main Title:
- Assessing the performance of daily to subdaily temporal disaggregation methods for the IDF curve generation under climate change
- Authors:
- Alzahrani, Fahad
Seidou, Ousmane
Alodah, Abdullah - Abstract:
- Abstract: Given the short concentration time in urban watersheds, the design of municipal water infrastructures often requires knowledge of sub-daily precipitation intensity. Sub-daily time series can be directly used in a rainfall–runoff model or to derive intensity–duration–frequency (IDF) curves and calculate the design precipitation. Given that precipitation projections are typically at a daily time scale, temporal disaggregation using techniques of variable complexity is often needed to evaluate the risk/performance of urban infrastructure in the future. This paper proposes a simple steady-state stochastic disaggregation model that generates wet/dry day occurrence using a binomial distribution and precipitation intensity using an exponential distribution. Daily precipitation data from four regional climate models (RCMs) forced with the high-emission scenario representative concentration pathway (RCP 8.5) were downscaled using the quantile mapping (QM) method. The performance of the developed method is compared to widely used temporal disaggregation methods, namely, the multiplicative random cascade model (MRC), the Hurst–Kolmogorov process (HKP), and three versions of the K-nearest neighbour (KNN) model, using the Kolmogorov–Smirnov (KS) test. The six disaggregation techniques were assessed at four stations in the South Nation River Watershed in Eastern Ontario, Canada. Results indicate that, despite its simplicity, the proposed method performed well compared to otherAbstract: Given the short concentration time in urban watersheds, the design of municipal water infrastructures often requires knowledge of sub-daily precipitation intensity. Sub-daily time series can be directly used in a rainfall–runoff model or to derive intensity–duration–frequency (IDF) curves and calculate the design precipitation. Given that precipitation projections are typically at a daily time scale, temporal disaggregation using techniques of variable complexity is often needed to evaluate the risk/performance of urban infrastructure in the future. This paper proposes a simple steady-state stochastic disaggregation model that generates wet/dry day occurrence using a binomial distribution and precipitation intensity using an exponential distribution. Daily precipitation data from four regional climate models (RCMs) forced with the high-emission scenario representative concentration pathway (RCP 8.5) were downscaled using the quantile mapping (QM) method. The performance of the developed method is compared to widely used temporal disaggregation methods, namely, the multiplicative random cascade model (MRC), the Hurst–Kolmogorov process (HKP), and three versions of the K-nearest neighbour (KNN) model, using the Kolmogorov–Smirnov (KS) test. The six disaggregation techniques were assessed at four stations in the South Nation River Watershed in Eastern Ontario, Canada. Results indicate that, despite its simplicity, the proposed method performed well compared to other temporal disaggregation methods when resampling the observed extreme precipitation. HIGHLIGHTS: Climate change impacts on short-duration precipitation extreme events are investigated using different temporal disaggregation methods. A simple steady-state stochastic disaggregation model is introduced to generate future sub-daily precipitation intensities. The developed disaggregation method adequately resamples the observed short-duration extreme precipitation for application in municipal water infrastructures. Graphical Abstract … (more)
- Is Part Of:
- Journal of water and climate change. Volume 14:Issue 4(2023)
- Journal:
- Journal of water and climate change
- Issue:
- Volume 14:Issue 4(2023)
- Issue Display:
- Volume 14, Issue 4 (2023)
- Year:
- 2023
- Volume:
- 14
- Issue:
- 4
- Issue Sort Value:
- 2023-0014-0004-0000
- Page Start:
- 1339
- Page End:
- 1357
- Publication Date:
- 2023-03-27
- Subjects:
- climate change, FO method, IDF curves RCM, temporal disaggregation
Water -- Periodicals
Hydrology -- Periodicals
Climatic changes -- Periodicals
Climatic changes
Hydrology
Water
Electronic journals
Periodicals
333.9116 - Journal URLs:
- https://iwaponline.com/jwcc/issue/browse-by-year ↗
http://www.iwaponline.com/jwc/toc.htm ↗ - DOI:
- 10.2166/wcc.2023.507 ↗
- Languages:
- English
- ISSNs:
- 2040-2244
- Deposit Type:
- Legaldeposit
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- British Library HMNTS - ELD Digital store
- Ingest File:
- 26560.xml