Developing Intensity–Duration–Frequency (IDF) Curves under Climate Change Uncertainty: The Case of Bangkok, Thailand
Abstract
:1. Introduction
2. Use of Global Climate Models (GCMs) in Urban Scale Applications
3. Case Study Area
4. Methodology
4.1. Methodological Framework for the Spatial Downscaling-Temporal Disaggregation Method (DDM) Approach
4.2. Spatial Downscaling Using Long Ashton Research Station Weather Generator (LARS-WG)
4.3. Disaggregation to Hourly Time Scale Using Hyetos
4.4. Intensity–Duration–Frequency (IDF) Generation and Correction
5. Results and Discussion
5.1. Spatial Downscaling
5.2. Temporal Disaggregation
5.3. Generation of IDF Curves
6. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Model | Research Center | Grid Resolution | Scenarios |
---|---|---|---|
CNCM3 | Centre National de Recherches Meteorologiques, France | 1.9° × 1.9° | SRA1B, SRA2 |
GFCM21 | Geophysical Fluid Dynamics Laboratory, USA | 2.0° × 2.5° | SRA1B, SRB1, SRA2 |
HADCM3 | UK Meteorological Office, UK | 2.5° × 3.75° | SRA1B, SRB1, SRA2 |
HADGEM | UK Meteorological Office, UK | 1.3° × 1.9° | SRA1B, SRA2 |
INCM3 | Institute for Numerical Mathematics, Russia | 4.0° × 5.0° | SRA1B, SRB1, SRA2 |
IPCM4 | Institute Pierre Simon Laplace, France | 2.5° × 3.75° | SRA1B, SRB1, SRA2 |
MPEH5 | Max-Planck Institute for Meteorology, Germany | 1.9° × 1.9° | SRA1B, SRB1, SRA2 |
NCCCSM | National Centre for Atmospheric Research, USA | 1.4° × 1.4° | SRA1B, SRB1, SRA2 |
NCPCM | National Centre for Atmospheric Research, USA | 2.8° × 2.8° | SRA1B, SRA2 |
Month | λ (day−1) | Κ = β/η (−) | Φ = γ/η (−) | α (−) | ν (day) | μX (mm·day−1) | σX (mm·day−1) |
---|---|---|---|---|---|---|---|
January | 0.1190 | 0.0260 | 0.0227 | 69 | 1.500 | 70 | 70 |
February | 0.1200 | 0.2400 | 0.1500 | 69 | 2.300 | 70 | 70 |
March | 0.1150 | 0.1700 | 0.0900 | 86 | 3.200 | 85 | 85 |
April | 0.1900 | 0.1750 | 0.0910 | 65 | 3.690 | 90 | 90 |
May | 0.3000 | 0.2500 | 0.0910 | 40 | 3.770 | 90 | 90 |
June | 0.4100 | 0.4500 | 0.1250 | 69 | 2.600 | 70 | 70 |
July | 0.2900 | 0.1430 | 0.0330 | 69 | 2.450 | 90 | 90 |
August | 0.2350 | 0.1360 | 0.0150 | 69 | 2.300 | 90 | 90 |
September | 0.9000 | 0.6640 | 0.1150 | 90 | 2.500 | 70 | 70 |
October | 0.1620 | 0.3150 | 0.0150 | 69 | 2.560 | 70 | 70 |
November | 0.1150 | 0.1900 | 0.0900 | 95 | 4.387 | 95 | 95 |
December | 0.0240 | 0.1826 | 0.1590 | 100 | 1.960 | 69 | 69 |
Duration | Distribution | Parameters | K-S Test | χ2 Test | Intensity (mm/h) at Return Periods: | ||||
---|---|---|---|---|---|---|---|---|---|
Statistic | p | Statistic | p | 2 Years | 5 Years | 20 Years | |||
3 h | GEV | k = 0.08325, µ = 20.652, σ = 76.138 | 0.098 | 0.899 | 2.013 | 0.570 | 27.86 | 35.09 | 43.49 |
Gamma | α = 13.698, β = 6.3132, γ = 0 | 0.102 | 0.869 | 1.383 | 0.709 | 28.13 | 35.09 | 42.72 | |
Gumbel | α = 18.218, µ = 75.962 | 0.119 | 0.725 | 3.739 | 0.291 | 27.55 | 34.43 | 43.36 | |
Log Pearson III | α = 1518.3, β = 0.00689, γ = −6.0309 | 0.106 | 0.842 | 2.206 | 0.531 | 27.78 | 35.05 | 43.69 | |
Log Normal | α = 0.26397, µ = 4.4251, γ = 0 | 0.110 | 0.807 | 2.226 | 0.527 | 27.84 | 34.77 | 42.98 | |
Standard Deviation | 0.21 | 0.29 | 0.39 | ||||||
6 h | GEV | k = 0.12065, µ = 22.557, σ = 83.159 | 0.079 | 0.982 | 0.358 | 0.949 | 15.27 | 20.04 | 27.29 |
Gamma | α = 8.8257, β = 11.241, γ = 0 | 0.116 | 0.751 | 1.297 | 0.730 | 15.92 | 20.95 | 26.63 | |
Gumbel | α = 26.039, µ = 84.183 | 0.093 | 0.926 | 0.119 | 0.998 | 15.62 | 20.54 | 26.92 | |
Log Pearson III | α = 11.027, β = 0.09135, γ = 3.5429 | 0.085 | 0.966 | 0.345 | 0.951 | 15.30 | 20.10 | 27.21 | |
Log Normal | α = 0.29842, µ = 4.5502, γ = 0 | 0.105 | 0.848 | 0.145 | 0.997 | 15.78 | 20.28 | 25.77 | |
Standard Deviation | 0.29 | 0.37 | 0.61 | ||||||
12 h | GEV | k = 0.20531, µ = 23.843, σ = 86.68 | 0.135 | 0.581 | 0.475 | 0.924 | 7.98 | 10.71 | 15.35 |
Gamma | α = 5.3666, β = 19.836, γ = 0 | 0.179 | 0.241 | 7.317 | 0.026 | 8.33 | 11.83 | 15.96 | |
Gumbel | α = 35.828, µ = 85.771 | 0.164 | 0.335 | 3.010 | 0.390 | 8.24 | 11.63 | 16.02 | |
Log Pearson III | α = 3.2755, β = 0.18536, γ = 3.9984 | 0.157 | 0.386 | 0.874 | 0.832 | 7.85 | 10.70 | 15.74 | |
Log Normal | α = 0.33002, µ = 4.6056, γ = 0 | 0.127 | 0.657 | 1.005 | 0.800 | 8.34 | 11.01 | 14.35 | |
Standard Deviation | 0.22 | 0.52 | 0.69 | ||||||
24 h | GEV | k = 0.28101, µ = 24.575, σ = 97.168 | 0.107 | 0.835 | 0.542 | 0.763 | 4.44 | 5.96 | 8.80 |
Gamma | α = 4.7342, β = 25.493, γ = 0 | 0.192 | 0.180 | 8.616 | 0.035 | 4.68 | 6.80 | 9.33 | |
Gumbel | α = 43.249, µ = 95.726 | 0.183 | 0.224 | 5.639 | 0.131 | 4.65 | 6.69 | 9.34 | |
Log Pearson III | α = 2.0027, β = 0.23836, γ = 4.2507 | 0.126 | 0.661 | 3.161 | 0.293 | 4.36 | 5.97 | 9.07 | |
Log Normal | α = 0.33184, µ = 4.7281, γ = 0 | 0.121 | 0.707 | 1.205 | 0.752 | 4.71 | 6.23 | 8.13 | |
Standard Deviation | 0.16 | 0.40 | 0.50 |
Duration | Comparison * | Return Period | |||||
---|---|---|---|---|---|---|---|
2 Years | 5 Years | 10 Years | 20 Years | 50 Years | 100 Years | ||
3 h | Ratio = O/M | 1.426 | 1.426 | 1.406 | 1.377 | 1.332 | 1.295 |
Difference (mm/h) = O − M | 8.327 | 10.483 | 11.399 | 11.908 | 12.050 | 11.783 | |
6 h | Ratio = O/M | 1.047 | 1.093 | 1.159 | 1.242 | 1.373 | 1.489 |
Difference (mm/h) = O − M | 0.684 | 1.705 | 3.235 | 5.310 | 8.858 | 12.147 | |
12 h | Ratio = O/M | 1.007 | 1.020 | 1.036 | 1.057 | 1.090 | 1.119 |
Difference (mm/h) = O − M | 0.058 | 0.208 | 0.453 | 0.832 | 1.585 | 2.393 | |
24 h | Ratio = O/M | 1.013 | 1.025 | 1.035 | 1.045 | 1.060 | 1.072 |
Difference (mm/h) = O − M | 0.055 | 0.144 | 0.243 | 0.380 | 0.642 | 0.922 |
GCMs | Future Period | Scenario | Return Period 2 Years Duration (h) | Return Period 5 Years Duration (h) | Return Period 20 Years Duration (h) | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | 3 | 6 | 12 | 24 | 1 | 3 | 6 | 12 | 24 | 1 | 3 | 6 | 12 | 24 | |||
CNCM3 | I | SRA2 | 4.9 | 8.9 | 19.0 | 11.3 | 10.3 | 5.6 | 9.6 | 23.0 | 19.8 | 20.2 | 8.5 | 15.2 | 34.6 | 37.8 | 31.2 |
SRA1B | 9.0 | 9.4 | 18.2 | 11.9 | 7.5 | 6.9 | 11.1 | 22.2 | 24.8 | 17.9 | 0.1 | 11.3 | 34.7 | 52.7 | 32.9 | ||
II | SRA2 | 9.0 | 15.4 | 28.7 | 16.6 | 11.4 | 6.9 | 16.6 | 34.0 | 27.6 | 21.9 | 0.8 | 21.4 | 49.6 | 54.9 | 37.9 | |
SRA1B | 7.3 | 5.4 | 16.9 | 6.7 | 7.7 | 8.2 | 9.6 | 18.0 | 17.1 | 16.7 | 6.0 | 18.9 | 30.2 | 45.8 | 31.9 | ||
GFCM21 | I | SRA2 | 6.9 | 10.4 | 24.9 | 13.7 | 6.3 | 1.6 | 9.4 | 27.6 | 26.5 | 14.7 | −10.1 | 1.3 | 25.0 | 39.8 | 22.7 |
SRA1B | 0.8 | 12.6 | 24.4 | 12.5 | 5.7 | −0.2 | 17.2 | 29.8 | 21.3 | 14.1 | 3.7 | 18.4 | 32.8 | 33.1 | 23.1 | ||
II | SRA2 | 12.0 | 17.6 | 30.6 | 16.3 | 10.5 | 13.2 | 26.7 | 41.7 | 30.6 | 20.4 | 6.0 | 28.9 | 51.2 | 49.2 | 29.3 | |
SRA1B | 14.6 | 18.4 | 25.1 | 17.1 | 15.4 | 6.9 | 18.1 | 29.0 | 26.2 | 24.7 | −4.8 | 14.9 | 41.3 | 43.6 | 29.7 | ||
HADCM3 | I | SRA2 | 13.2 | 16.5 | 18.9 | 12.1 | 10.7 | 14.3 | 20.5 | 27.0 | 27.2 | 25.4 | 14.5 | 30.4 | 47.9 | 62.5 | 47.5 |
SRA1B | 10.1 | 15.4 | 22.9 | 16.8 | 13.0 | 6.9 | 20.4 | 35.2 | 30.9 | 26.4 | −1.5 | 21.9 | 58.1 | 59.8 | 46.3 | ||
II | SRA2 | 13.2 | 16.5 | 18.9 | 12.1 | 10.7 | 14.3 | 20.5 | 27.0 | 27.2 | 25.4 | 14.5 | 30.4 | 47.9 | 62.5 | 47.5 | |
SRA1B | 13.6 | 20.8 | 29.9 | 19.2 | 16.6 | 4.6 | 17.0 | 34.0 | 36.1 | 30.8 | −10.2 | 8.5 | 42.5 | 69.8 | 51.2 | ||
HADGEM | I | SRA2 | 1.8 | -0.1 | 11.4 | 1.1 | 1.6 | 0.0 | 2.2 | 17.6 | 8.9 | 12.3 | 1.3 | 18.9 | 34.9 | 27.8 | 28.4 |
SRA1B | 7.5 | 2.4 | 10.2 | 9.1 | 5.9 | 1.6 | 3.6 | 19.8 | 19.4 | 16.2 | −4.4 | 11.0 | 39.9 | 42.8 | 29.0 | ||
II | SRA2 | 4.5 | 11.1 | 26.0 | 11.9 | 9.9 | −2.3 | 5.9 | 26.4 | 23.6 | 21.4 | −18.3 | −7.0 | 19.7 | 41.7 | 31.1 | |
SRA1B | 12.0 | 27.0 | 47.5 | 33.3 | 22.5 | 7.9 | 24.7 | 43.0 | 45.6 | 34.9 | −1.4 | 18.8 | 28.0 | 50.9 | 40.6 | ||
IMCM3 | I | SRA2 | 20.4 | 21.2 | 23.1 | 11.7 | 3.8 | 18.7 | 22.9 | 24.7 | 22.0 | 12.6 | 14.8 | 23.6 | 42.0 | 51.9 | 32.1 |
SRA1B | 10.1 | 15.4 | 22.9 | 16.8 | 13.0 | 6.9 | 20.4 | 35.2 | 30.9 | 26.4 | −1.5 | 21.9 | 58.1 | 59.8 | 46.3 | ||
II | SRA2 | 15.7 | 17.6 | 20.0 | 12.6 | 9.6 | 5.1 | 9.3 | 20.4 | 19.3 | 17.5 | −10.5 | −3.2 | 25.0 | 40.7 | 30.1 | |
SRA1B | 13.6 | 20.8 | 29.9 | 19.2 | 16.6 | 4.6 | 17.0 | 34.0 | 36.1 | 30.8 | −10.2 | 8.5 | 42.5 | 69.8 | 51.2 | ||
IPCM4 | I | SRA2 | 7.2 | 10.4 | 14.3 | 4.1 | 2.2 | 7.4 | 9.6 | 15.1 | 13.0 | 11.2 | 3.3 | 7.1 | 20.0 | 34.3 | 26.7 |
SRA1B | 2.2 | 5.5 | 14.6 | 13.7 | 10.9 | −0.5 | 0.8 | 9.8 | 16.0 | 16.7 | −5.2 | −3.0 | 2.1 | 14.0 | 16.2 | ||
II | SRA2 | 8.4 | 14.9 | 20.8 | 10.0 | 5.8 | 1.4 | 11.2 | 24.9 | 21.0 | 14.7 | −10.0 | 7.3 | 32.7 | 48.0 | 31.2 | |
SRA1B | 2.2 | 15.2 | 28.4 | 24.1 | 16.5 | 4.4 | 24.1 | 40.3 | 34.8 | 26.2 | 10.2 | 41.2 | 75.3 | 56.4 | 37.9 | ||
MPEH5 | I | SRA2 | 10.1 | 12.6 | 15.5 | 4.1 | 3.9 | 7.7 | 15.3 | 21.0 | 16.6 | 18.1 | 0.9 | 18.7 | 36.8 | 43.2 | 40.1 |
SRA1B | 11.6 | 12.1 | 13.5 | 6.0 | 3.8 | 8.8 | 16.5 | 21.3 | 18.4 | 17.4 | 0.0 | 20.3 | 44.4 | 45.0 | 39.6 | ||
II | SRA2 | 10.6 | 19.1 | 19.6 | 3.4 | −1.0 | 10.8 | 21.7 | 30.5 | 14.5 | 7.1 | 11.1 | 16.6 | 43.1 | 46.4 | 28.2 | |
SRA1B | 12.4 | 14.7 | 29.0 | 25.8 | 21.5 | 6.9 | 18.3 | 34.5 | 39.2 | 37.8 | −2.7 | 18.0 | 51.0 | 68.4 | 65.0 | ||
NCCCSM | I | SRA2 | 11.9 | 8.8 | 16.4 | 13.7 | 10.7 | 15.6 | 15.6 | 23.3 | 27.1 | 24.3 | 25.9 | 25.6 | 43.1 | 56.4 | 42.1 |
SRA1B | 20.4 | 15.1 | 22.1 | 15.5 | 11.7 | 13.9 | 14.0 | 24.9 | 25.3 | 22.9 | −1.6 | 8.6 | 32.9 | 42.7 | 36.9 | ||
II | SRA2 | 1.3 | 8.1 | 18.6 | 14.9 | 13.9 | 0.6 | 7.9 | 22.0 | 25.5 | 24.8 | −4.3 | 1.0 | 24.0 | 46.6 | 35.6 | |
SRA1B | 25.6 | 26.0 | 29.5 | 19.9 | 11.6 | 18.7 | 28.8 | 37.8 | 33.1 | 22.6 | 1.5 | 26.3 | 48.1 | 54.4 | 36.8 | ||
NCPCM | I | SRA2 | 19.9 | 27.8 | 30.9 | 14.8 | 7.2 | 12.8 | 24.4 | 33.0 | 21.9 | 13.6 | 2.3 | 16.6 | 34.3 | 36.2 | 22.7 |
SRA1B | 7.4 | 14.6 | 16.5 | 12.9 | 9.0 | 2.5 | 16.0 | 15.6 | 19.8 | 15.1 | −7.8 | 12.3 | 20.9 | 34.7 | 19.0 | ||
II | SRA2 | 8.5 | 13.6 | 23.4 | 12.0 | 9.1 | 1.9 | 6.0 | 19.4 | 15.3 | 13.1 | −13.0 | −4.6 | 19.7 | 23.0 | 12.1 | |
SRA1B | 15.6 | 19.0 | 21.7 | 10.2 | 7.2 | 13.4 | 19.1 | 25.2 | 15.4 | 11.6 | 3.6 | 11.6 | 28.6 | 27.0 | 14.2 |
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Shrestha, A.; Babel, M.S.; Weesakul, S.; Vojinovic, Z. Developing Intensity–Duration–Frequency (IDF) Curves under Climate Change Uncertainty: The Case of Bangkok, Thailand. Water 2017, 9, 145. https://doi.org/10.3390/w9020145
Shrestha A, Babel MS, Weesakul S, Vojinovic Z. Developing Intensity–Duration–Frequency (IDF) Curves under Climate Change Uncertainty: The Case of Bangkok, Thailand. Water. 2017; 9(2):145. https://doi.org/10.3390/w9020145
Chicago/Turabian StyleShrestha, Ashish, Mukand Singh Babel, Sutat Weesakul, and Zoran Vojinovic. 2017. "Developing Intensity–Duration–Frequency (IDF) Curves under Climate Change Uncertainty: The Case of Bangkok, Thailand" Water 9, no. 2: 145. https://doi.org/10.3390/w9020145
APA StyleShrestha, A., Babel, M. S., Weesakul, S., & Vojinovic, Z. (2017). Developing Intensity–Duration–Frequency (IDF) Curves under Climate Change Uncertainty: The Case of Bangkok, Thailand. Water, 9(2), 145. https://doi.org/10.3390/w9020145