Estimation of the Impacts of Climate Change on the Design, Risk and Performance of Urban Water Infrastructure - Alzahrani, Fahad (Université d'Ottawa / University of Ottawa, 2023)
Changes in the temporal variability of precipitation at all timescales are expected due to global warming. Such changes affect urban water infrastructure by potentially influencing their performance and risk of failure. Unfortunately, there is considerable uncertainty about how hydrological variables will change in the future. While uncertainty is present at all timescales, the climate signal in the daily time series simulated by climate models, for instance, can be estimated with much greater certainty than in the simulated hourly time series. That is problematic as sub-daily precipitation time series are essential to solving specific water resource engineering problems, especially in urban hydrology, where times of concentrations are typically less than a day. For instance, hourly or sub-hourly precipitation time series are routinely used to design stormwater and road drainage systems. Rainfall variability at sub-daily time steps is often represented as Intensity-Duration-Frequency (IDF) curves, relating precipitation duration (of basin time of concentration) to return period and average precipitation intensity. Naturally, several researchers investigated the integration of climate change in IDF curves, leading to methods of variable complexity and variable performance. This thesis aims to a) make a critical analysis of the most commonly used methods for IDF curves under climate change in Canada and b) identify the methods with optimal performance for a set of stations located in the South Nation watershed in Ottawa, Ontario, and c) perform a case study highlighting the effect of the choice of the temporal disaggregation method on the estimated risk of failure/performance of an urban water system. The first part of the thesis examines Equidistant Quantile Mapping (EQM) used in the IDF_CC tool developed for the Canadian Water Network project. Two conceptual flaws in the method that led to a systematic underestimation of extreme events were discovered. Two corrections are proposed to the EQM, leading to the development of two new methods for IDF generation. The output of EQM and its improved version is a time series of annual maximum precipitation intensity for different durations that can be used to derive IDF curves. These time series generated using the above approach are not appropriate for rainfall-runoff models for which continuous time series of precipitation (not only maximums) are required. The second part of the thesis tackles the issue, which examines a different approach to evaluating the risk of failure/performance of urban water systems under a changing climate. This second approach yields continuous time series of precipitation that can be fed in rainfall-runoff models used for IDF curve generation. The proposed method is applied in three steps: i) projections of future daily precipitation are generated by downscaling the output of climate models; ii) the downscaled daily precipitation time series are temporally disaggregated to an hourly time step using various techniques; iii) finally, the disaggregated future precipitation time series are used as inputs to rainfall-runoff models or used to generate IDF curves. This approach relaxes several strong assumptions made to develop the EQM approach, such as the implicit (and strong) assumption that the annual maximum precipitation at two different time steps occurs during the same event. That assumption is not necessarily valid and can affect the realism of the generated IDF curves. The method's performance is obviously dependent on the temporal disaggregation technique used in step 3. In this thesis, a simple steady-state stochastic disaggregation model that generates wet/dry day occurrence using a binomial distribution and precipitation intensity using an exponential distribution is proposed and compared to widely used temporal disaggregation methods: the multiplicative random cascade model (MRC), the Hurst-Kolmogorov process (HKP), and three versions of the K-nearest neighbor model (KNN) using the nonparametric Kolmogorov- Smirnov (KS) test. The six disaggregation techniques were assessed at four stations located in South Nation River Watershed located in Eastern Ontario, Canada. The third part of the thesis is a case study of the impact of climate change on stormwater management. First, a stormwater management model (SWMM) of St. Catharines, Ontario, developed in a previous study, was selected to simulate its stormwater and sanitary system. The model was forced with downscaled and temporally disaggregated precipitation outputs of the Canadian Regional Climate Model at the Port Dalhousie station, simulated under emission scenario RCP8.5. The temporal disaggregation was done using the Fahad-Ousmane and the KNN (30) methods developed in the previous chapter. The impact of climate change on the frequency, volume, and quality of combined sewer overflows and other hydraulic parameters is examined. Results suggest an increase in the total volume, flow frequency percentage, maximum flow, and average flow in the stormwater system due to climate change. Therefore, adaptation measures should be implemented for the distribution network and wastewater treatment plant to convey and treat the wastewater resulting from wet and dry events.
Keywords: Equidistant Quantile Mapping; RCM; KNN; FO