Quantifying the Uncertainty Related to Climate Change in the Assessment of Urban Flooding—A Case Study
Abstract
1. Introduction
2. Materials and Methods
2.1. Case Study and Dataset
2.2. Estimation of DDF Curve Parameters in Climate Change Scenarios
- From the original dataset, several continuous sub-datasets with different ending years and lengths were extracted. Specifically, starting from a minimum of 15 years, the length of each sub-dataset was increased by one, up to a maximum of 35 years. This choice was based on the evidence that an intensification of the hydrological cycle occurred in the last 30–35 years [27]. Moreover, this assumption is furtherly supported by the evidence of a statistically significant increase of the average annual rainfall during the last 30 years in Sicily [28];
- The aT parameter was estimated for each of the above-mentioned sub-datasets;
- The likelihood function was used to evaluate the 95th, 50th, and 5th percentiles of each aT series.
2.3. The Hydraulic Model: FLO-2D
3. Results
3.1. DDF Curves Parameters
3.2. Maps of Maximum Flow Depths
4. Discussion
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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T (Years) | Scenario | nT | aT (mm) | ||
---|---|---|---|---|---|
95th Percentile | 50th Percentile | 5th Percentile | |||
2 | 2010 | 0.27 | 30.5 | 28.3 | 27.0 |
2025 | 0.27 | 34.0 | 31.3 | 29.7 | |
2050 | 0.27 | 39.7 | 36.2 | 34.1 | |
5 | 2010 | 0.32 | 41.7 | 38.4 | 37.0 |
2025 | 0.32 | 45.5 | 41.4 | 39.7 | |
2050 | 0.32 | 51.9 | 46.4 | 44.4 | |
10 | 2010 | 0.29 | 52.9 | 48.3 | 45.6 |
2025 | 0.29 | 58.1 | 52.2 | 48.5 | |
2050 | 0.29 | 66.6 | 58.8 | 53.2 | |
20 | 2010 | 0.29 | 68.0 | 61.1 | 56.3 |
2025 | 0.29 | 76.0 | 67.0 | 59.7 | |
2050 | 0.29 | 89.2 | 76.8 | 65.4 |
Scenario | Return Period (Years) | Flooded Area (km2) | ||
---|---|---|---|---|
95th Percentile | 50th Percentile | 5th Percentile | ||
2010 | 2 | 0.020 | 0.019 | 0.018 |
5 | 0.042 | 0.021 | 0.020 | |
10 | 0.274 | 0.034 | 0.025 | |
20 | 0.788 | 0.603 | 0.441 | |
2025 | 2 | 0.021 | 0.020 | 0.019 |
5 | 0.164 | 0.029 | 0.024 | |
10 | 0.507 | 0.243 | 0.094 | |
20 | 0.788 | 0.764 | 0.556 | |
2050 | 2 | 0.023 | 0.022 | 0.021 |
5 | 0.472 | 0.225 | 0.111 | |
10 | 0.750 | 0.523 | 0.276 | |
20 | 1.258 | 0.970 | 0.719 |
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Liuzzo, L.; Freni, G. Quantifying the Uncertainty Related to Climate Change in the Assessment of Urban Flooding—A Case Study. Water 2019, 11, 2072. https://doi.org/10.3390/w11102072
Liuzzo L, Freni G. Quantifying the Uncertainty Related to Climate Change in the Assessment of Urban Flooding—A Case Study. Water. 2019; 11(10):2072. https://doi.org/10.3390/w11102072
Chicago/Turabian StyleLiuzzo, Lorena, and Gabriele Freni. 2019. "Quantifying the Uncertainty Related to Climate Change in the Assessment of Urban Flooding—A Case Study" Water 11, no. 10: 2072. https://doi.org/10.3390/w11102072
APA StyleLiuzzo, L., & Freni, G. (2019). Quantifying the Uncertainty Related to Climate Change in the Assessment of Urban Flooding—A Case Study. Water, 11(10), 2072. https://doi.org/10.3390/w11102072