Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations
Abstract
:1. Introduction
1.1. Heavy Rainfall Event in July 2018 in Western Japan
1.2. Recent Hydrological Studies on Heavy Rainfall Disasters
1.3. Objectives, Hypothesis and New Contributions of This Study
2. Materials and Methods
2.1. Study Sites
2.2. Materials and Datasets
2.3. Model Configurations
2.4. Model Calibration and Validation
3. Results
3.1. Classification of Historical Extreme Rainfall Events
3.2. Calibration and Validation of River Discharges
3.2.1. Ota River
3.2.2. Takahashi River
3.2.3. All Rivers Cumulatively
3.3. Cross-Validation of River Discharges
3.3.1. Ota River
3.3.2. Takahashi River
4. Discussion
4.1. Classification of Historical Extreme Rainfall Events
4.2. Calibration and Validation of River Discharges
4.3. Approach to Developing Flash Flood River Discharge Hydrograph Nowcasting Applications
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
5-CPM | 5 calibrated parameters method |
7-CPM | 7 calibrated parameters method |
CDRM | Cell Distributed Runoff Model version 3.1.1 |
EWS | Early warning system |
HRE18 | Heavy Rainfall Event of July 2018 |
KGE | Kling–Gupta efficiency |
NSE | Nash–Sutcliffe efficiency |
PE | Peak error |
Pt | Ensemble average at time t |
River mouth | Location of the closest upstream discharge station without a significant tidal effect, which was selected for the observation and simulation location |
RRI | Rainfall-Runoff-Inundation |
SCE-UA | Shuffled Complex Evolution optimization method developed at the University of Arizona |
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River/Mean Center | Elevation (m) | LAT (◦N) | LON (◦E) |
---|---|---|---|
Saba/Wada | 140 | 34.15 | 131.74 |
Oze/Hatsukaichi | 317 | 34.37 | 132.19 |
Ota/Addition | 210 | 34.61 | 132.32 |
Ashida/Fuchu | 70 | 34.56 | 133.23 |
Takahashi/Jinjyama | 529 | 34.83 | 133.52 |
Asahi/Kuze | 144 | 35.07 | 133.75 |
Yoshii/Akaiwa | 56 | 34.92 | 134.08 |
River | Date From | Date Until | Qmax (m³/s) | 5 Day | 3 Day | 2 Day | 1 Day | Max. Day |
---|---|---|---|---|---|---|---|---|
Saba | 10 Jul 2010 | 16 Jul 2010 | 1060 | 444 | 376 | 349 | 337 | 06 Sep 2005 |
21 Jul 2009 | 27 Jul 2009 | 1250 | 368 | 355 | 300 | 197.5 | 21 Jul 2009 | |
04 Sep 2005 | 10 Sep 2005 | 910 | 357 | 317 | 299 | 183.5 | 10 May 2011 | |
19 Jun 2016 | 25 Jun 2016 | 900 | 348.5 | 284 | 231.5 | 175 | 13 Jul 2010 | |
01 Jul 2005 | 07 Jul 2005 | 470 | 341 | 262.5 | 230 | 166 | 03 Jul 2005 | |
03 Jul 2018 | 09 Jul 2018 | 920 | 331 | 257 | 227.5 | 151.5 | 06 Jul 2018 | |
09 May 2011 | 15 May 2011 | 490 | 317 | 251 | 160.5 | 104 | 22 Jun 2016 | |
Oze | 03 Jul 2018 | 09 Jul 2018 | 1240 | 425 | 387 | 375 | 346 | 06 Sep 2005 |
04 Sep 2005 | 10 Sep 2005 | 630 | 394 | 363 | 269 | 161 | 10 May 2006 | |
11 Jul 2010 | 17 Jul 2010 | 490 | 375 | 275 | 251.5 | 140 | 13 Jul 2010 | |
06 May 2006 | 12 May 2006 | 360 | 265 | 237 | 173 | 139 | 06 Jul 2018 | |
19 Jun 2016 | 25 Jun 2016 | 260 | 254.5 | 199 | 171 | 100 | 18 Jul 2003 | |
31 Jul 2004 | 06 Aug 2004 | 220 | 254 | 186 | 171 | 90 | 01 Aug 2004 | |
18 Jul 2003 | 24 Jul 2003 | 320 | 248 | 171 | 140.5 | 73.5 | 22 Jun 2016 | |
Ota | 11 Jul 2010 | 17 Jul 2010 | 4220 | 431.5 | 350.5 | 258 | 229 | 06 Sep 2005 |
03 Jul 2018 | 09 Jul 2018 | 4530 | 341 | 303 | 256 | 145 | 06 Jul 2018 | |
04 Sep 2005 | 10 Sep 2005 | 7080 | 313 | 277.5 | 221 | 132 | 14 Jul 2010 | |
07 Jul 1997 | 13 Jul 1997 | 1620 | 311 | 233 | 205 | 131 | 24 Sep 1999 | |
21 Sep 1999 | 27 Sep 1999 | 3890 | 280 | 221 | 176 | 118 | 20 Jul 2009 | |
17 Jul 2009 | 23 Jul 2009 | 2250 | 238.5 | 212.5 | 147 | 105 | 08 Jul 1997 | |
31 Jul 2004 | 06 Aug 2004 | 1110 | 236 | 149 | 140 | 91 | 02 Aug 2004 | |
Ashida | 03 Jul 2018 | 09 Jul 2018 | 2090 | 394.5 | 373.5 | 285 | 181.5 | 06 Jul 2018 |
31 Aug 2013 | 06 Sep 2013 | 920 | 232.5 | 189.5 | 162 | 110.5 | 04 Jul 2017 | |
19 Jun 2016 | 25 Jun 2016 | 990 | 211 | 185.5 | 134 | 90 | 20 Jun 2013 | |
01 Jul 2005 | 07 Jul 2005 | 300 | 198 | 163 | 132.5 | 83 | 02 Jul 2005 | |
19 Jun 2013 | 25 Jun 2013 | 460 | 190 | 161 | 120 | 78.5 | 04 Sep 2013 | |
11 Jul 2010 | 17 Jul 2010 | 1110 | 181 | 156 | 115.5 | 75.5 | 14 Jul 2010 | |
04 Jul 2017 | 10 Jul 2017 | 610 | 139 | 134 | 109 | 58 | 24 Jun 2016 | |
Takahashi | 03 Jul 2018 | 09 Jul 2018 | 7660 | 394.5 | 362 | 304.5 | 249.5 | 03 Sep 2011 |
02 Sep 2011 | 08 Sep 2011 | 5110 | 306.5 | 305.5 | 290.5 | 174 | 06 Jul 2018 | |
31 Aug 2013 | 06 Sep 2013 | 3810 | 242.5 | 204.5 | 182.5 | 151.5 | 30 Sep 2018 | |
11 Jul 2010 | 17 Jul 2010 | 2520 | 231 | 188.5 | 164.5 | 109 | 14 Jul 2010 | |
17 Jul 2006 | 23 Jul 2006 | 3980 | 221 | 182.5 | 134 | 109 | 04 Sep 2013 | |
03 Jul 2012 | 09 Jul 2012 | 3050 | 194 | 163 | 128 | 84 | 07 Jul 2012 | |
29 Sep 2018 | 05 Oct 2018 | 4870 | 182.5 | 161 | 125.5 | 74 | 19 Jul 2006 | |
Asahi | 03 Jul 2018 | 09 Jul 2018 | 5330 | 435 | 415.5 | 325.5 | 178.5 | 06 Jul 2018 |
16 Jul 2006 | 22 Jul 2006 | 2650 | 240 | 220.5 | 216.5 | 170 | 03 Sep 2011 | |
31 Aug 2013 | 06 Sep 2013 | 2030 | 230 | 206 | 161 | 123 | 09 Sep 2018 | |
01 Sep 2011 | 07 Sep 2011 | 3230 | 222 | 165 | 158 | 114 | 30 Sep 2018 | |
07 Sep 2018 | 13 Sep 2018 | 1070 | 177.5 | 163 | 146 | 109 | 20 Oct 2004 | |
19 Oct 2004 | 25 Oct 2004 | 2800 | 165 | 161 | 145 | 93 | 04 Sep 2013 | |
29 Sep 2018 | 05 Oct 2018 | 1870 | 161 | 145.5 | 118 | 76 | 17 Jul 2006 | |
Yoshii | 03 Jul 2018 | 09 Jul 2018 | 6700 | 314.5 | 280 | 213.5 | 170.5 | 03 Sep 2011 |
31 Aug 2013 | 06 Sep 2013 | 4010 | 272.5 | 226.5 | 210 | 161 | 29 Sep 2004 | |
01 Sep 2011 | 07 Sep 2011 | 3750 | 218.5 | 216 | 183 | 146 | 06 Jul 2018 | |
17 Jul 2006 | 23 Jul 2006 | 4150 | 207 | 187 | 175 | 137 | 04 Sep 2013 | |
26 Sep 2004 | 02 Oct 2004 | 5740 | 191 | 183.5 | 175 | 136 | 09Aug 2009 | |
08 Aug 2009 | 14 Aug 2009 | 3170 | 183.5 | 176 | 165 | 120 | 20 Oct 2004 | |
19 Oct 2004 | 25 Oct 2004 | 3580 | 176 | 168 | 119 | 83 | 19 Jul 2006 |
River/Event | 2010 (a) | 2018 | 2005 (e) | 1997 (f) | 1999 (b) | 2009 (d) | 2004 (c) | Event/Day |
---|---|---|---|---|---|---|---|---|
Ota | 81 | 63.5 | 10 | 90 | 131 | 26 | 3 | 3rd–5th days |
94.5 | 56.5 | 45 | 45 | 9 | 7.5 | 86 | 2nd–3rd days | |
124 | 76 | 29 | 71 | 9 | 87 | 56 | 1st–2nd days | |
132 | 145 | 229 | 105 | 131 | 118 | 91 | 1st day | |
River/Event | 2018-7 | 2011 (a) | 2013 (c) | 2010 (d) | 2006 (b) | 2012 (f) | 2018-10 (e) | Event/Day |
Takahashi | 32.5 | 1 | 54 | 26.5 | 60 | 31 | 0 | 3rd–5th days |
71.5 | 1 | 63 | 40 | 33 | 29 | 0 | 2nd–3rd days | |
116.5 | 55 | 16.5 | 55.5 | 54 | 50 | 31 | 1st–2nd days | |
174 | 249.5 | 109 | 109 | 74 | 84 | 151.5 | 1st day |
Calibrated Parameter | Case | River (left—7 Parameters Method/Right—5 Parameters Method) | ||||||
---|---|---|---|---|---|---|---|---|
Saba | Oze | Ota | Ashida | Takahashi | Asahi | Yoshii | ||
Soil roughness coefficient N_slo [m−1/3s] | Cal | 0.10/0.10 | 0.97/0.10 | 0.12/0.10 | 1.00/0.33 | 1.00/0.10 | 0.93/0.10 | 0.46/0.18 |
Val (1) | 0.75/0.10 | 0.59/0.10 | 0.56/0.10 | 1.00/0.70 | 0.68/0.10 | 0.97/0.10 | 0.62/0.15 | |
Val (2) | 0.88/0.12 | 0.78/0.35 | 0.76/0.10 | 1.00/0.44 | 0.81/0.10 | 0.93/0.10 | 0.95/0.10 | |
Val (3) | 1.00/1.00 | 0.83/0.39 | 0.51/0.10 | 0.95/0.10 | 0.94/0.10 | 0.99/0.14 | 0.51/0.10 | |
Val (4) | 0.46/1.00 | 0.36/0.10 | 0.98/0.11 | 0.98/0.26 | 0.84/0.10 | 0.91/0.10 | 0.96/0.30 | |
Val (5) | 1.00/1.00 | 0.29/0.99 | 0.10/0.53 | 0.57/0.10 | 0.80/0.10 | 0.32/0.10 | 0.73/0.10 | |
Val (6) | 0.34/0.12 | 0.27/0.10 | 0.45/0.10 | 0.75/0.67 | 0.34/0.10 | 0.10/0.10 | 0.65/0.10 | |
River roughness coefficient N_riv [m−1/3s] | Cal | 0.03/0.04 | 0.03/0.04 | 0.06/0.04 | 0.03/0.04 | 0.06/0.07 | 0.05/0.06 | 0.05/0.05 |
Val (1) | 0.03/0.03 | 0.04/0.04 | 0.05/0.05 | 0.03/0.03 | 0.06/0.07 | 0.06/0.06 | 0.05/0.05 | |
Val (2) | 0.04/0.04 | 0.03/0.04 | 0.04/0.04 | 0.04/0.04 | 0.05/0.06 | 0.03/0.03 | 0.03/0.04 | |
Val (3) | 0.04/0.02 | 0.01/0.01 | 0.04/0.04 | 0.05/0.05 | 0.06/0.06 | 0.05/0.06 | 0.05/0.04 | |
Val (4) | 0.02/0.02 | 0.04/0.01 | 0.02/0.02 | 0.04/0.05 | 0.07/0.07 | 0.04/0.01 | 0.03/0.03 | |
Val (5) | 0.01/0.01 | 0.02/0.02 | 0.04/0.05 | 0.05/0.04 | 0.05/0.06 | 0.02/0.02 | 0.05/0.05 | |
Val (6) | 0.04/0.01 | 0.02/0.03 | 0.05/0.03 | 0.05/0.04 | 0.06/0.05 | 0.02/0.02 | 0.02/0.03 | |
Effective porosity of non-capillary subsurface layer θa [/] | Cal | 0.47/0.31 | 0.27/0.32 | 0.37/0.23 | 0.22/0.22 | 0.10/0.20 | 0.23/0.26 | 0.18/0.16 |
Val (1) | 0.53/0.45 | 0.37/0.31 | 0.22/0.15 | 0.13/0.10 | 0.21/0.23 | 0.19/0.30 | 0.13/0.10 | |
Val (2) | 0.46/0.70 | 0.15/0.10 | 0.58/0.57 | 0.23/0.25 | 0.14/0.19 | 0.24/0.23 | 0.15/0.27 | |
Val (3) | 0.44/0.14 | 0.25/0.52 | 0.39/0.50 | 0.16/0.17 | 0.22/0.30 | 0.20/0.27 | 0.20/0.14 | |
Val (4) | 0.32/0.11 | 0.22/0.41 | 0.26/0.44 | 0.45/0.32 | 0.14/0.22 | 0.49/0.47 | 0.10/0.13 | |
Val (5) | 0.25/0.21 | 0.25/0.54 | 0.70/0.70 | 0.16/0.22 | 0.10/0.16 | 0.21/0.26 | 0.20/0.13 | |
Val (6) | 0.62/0.43 | 0.34/0.18 | 0.40/0.48 | 0.38/0.34 | 0.13/0.14 | 0.33/0.42 | 0.13/0.20 | |
Saturated hydraulic conductivity ka [ms—1] | Cal | 0.50/0.19 | 0.41/0.18 | 0.07/0.50 | 0.31/0.24 | 0.48/0.40 | 0.35/0.50 | 0.37/0.43 |
Val (1) | 0.25/0.18 | 0.43/0.14 | 0.07/0.50 | 0.10/0.18 | 0.03/0.50 | 0.04/0.50 | 0.44/0.50 | |
Val (2) | 0.39/0.44 | 0.18/0.04 | 0.04/0.50 | 0.35/0.37 | 0.10/0.50 | 0.21/0.42 | 0.49/0.50 | |
Val (3) | 0.005/0.005 | 0.12/0.42 | 0.04/0.50 | 0.35/0.50 | 0.06/0.39 | 0.36/0.37 | 0.23/0.50 | |
Val (4) | 0.44/0.005 | 0.12/0.50 | 0.43/0.18 | 0.006/0.005 | 0.04/0.50 | 0.005/0.26 | 0.09/0.50 | |
Val (5) | 0.18/0.14 | 0.48/0.32 | 0.34/0.34 | 0.05/0.36 | 0.34/0.50 | 0.41/0.50 | 0.01/0.50 | |
Val (6) | 0.09/0.50 | 0.14/0.09 | 0.07/0.50 | 0.007/0.005 | 0.28/0.49 | 0.50/0.50 | 0.37/0.50 | |
Canopy | Cal | 0.79/0.81 | 0.70/0.70 | 0.68/0.66 | 0.61/0.63 | 0.66/0.67 | 0.79/0.79 | 0.71/0.72 |
interception | Val (1) | 0.77/0.76 | 0.67/0.68 | 0.69/0.60 | 0.60/0.60 | 0.64/0.60 | 0.75/0.71 | 0.71/0.69 |
and | Val (2) | 0.94/0.90 | 0.60/0.60 | 0.74/0.71 | 0.69/0.71 | 0.60/0.60 | 0.70/0.60 | 0.67/0.65 |
evaporation | Val (3) | 0.84/0.60 | 0.60/0.60 | 0.64/0.60 | 0.62/0.60 | 0.72/0.68 | 0.69/0.67 | 0.70/0.63 |
factor | Val (4) | 0.60/0.60 | 0.62/0.60 | 0.60/0.60 | 0.79/1.00 | 0.72/0.72 | 0.97/0.60 | 0.60/0.60 |
F1 [/] | Val (5) | 0.60/0.60 | 0.60/0.60 | 0.79/0.80 | 0.77/0.77 | 0.77/0.60 | 0.60/0.60 | 0.73/0.68 |
Val (6) | 0.64/0.62 | 0.74/0.75 | 0.83/0.82 | 0.88/1.00 | 0.65/0.60 | 0.60/0.60 | 0.69/0.67 | |
Effective | Cal | 0.27 | 0.28 | 0.37 | 0.10 | 0.11 | 0.24 | 0.10 |
porosity of | Val (1) | 0.53 | 0.39 | 0.24 | 0.10 | 0.22 | 0.22 | 0.15 |
capillary | Val (2) | 0.48 | 0.17 | 0.58 | 0.10 | 0.16 | 0.27 | 0.17 |
subsurface | Val (3) | 0.44 | 0.10 | 0.39 | 0.18 | 0.25 | 0.22 | 0.24 |
layer | Val (4) | 0.33 | 0.24 | 0.28 | 0.46 | 0.16 | 0.51 | 0.11 |
θm [/] | Val (5) | 0.10 | 0.26 | 0.10 | 0.10 | 0.15 | 0.23 | 0.19 |
Val (6) | 0.62 | 0.32 | 0.42 | 0.39 | 0.16 | 0.30 | 0.15 | |
Cal | 9.64 | 5.12 | 10.00 | 10.00 | 4.38 | 9.84 | 10.00 | |
Permeability | Val (1) | 10.00 | 9.43 | 6.74 | 10.00 | 7.26 | 4.94 | 9.52 |
reduction | Val (2) | 9.23 | 4.92 | 9.97 | 10.00 | 7.08 | 9.09 | 5.83 |
degree | Val (3) | 3.66 | 10.00 | 9.19 | 9.24 | 6.95 | 6.53 | 9.92 |
β [/] | Val (4) | 9.66 | 6.39 | 8.22 | 6.81 | 5.13 | 2.48 | 9.43 |
Val (5) | 9.90 | 7.93 | 10.00 | 9.93 | 2.59 | 8.10 | 3.19 | |
Val (6) | 10.00 | 8.05 | 9.93 | 4.70 | 6.68 | 10.00 | 6.07 |
7 Parameters Method | Saba | Oze | Ota | Ashida | Takahashi | Asahi | Yoshii | All | Average | |
---|---|---|---|---|---|---|---|---|---|---|
NSE | Calibration | 0.98 | 0.98 | 0.98 | 0.95 | 0.98 | 0.98 | 0.98 | 0.99 | 0.98 |
Ensemble average validation | 0.95 | 0.95 | 0.97 | 0.84 | 0.96 | 0.90 | 0.95 | 0.98 | 0.93 | |
KGE | Calibration | 0.94 | 0.98 | 0.98 | 0.91 | 0.99 | 0.98 | 0.93 | 0.98 | 0.96 |
Ensemble average validation | 0.85 | 0.90 | 0.95 | 0.70 | 0.92 | 0.69 | 0.85 | 0.91 | 0.84 | |
PE | Calibration | 0.93 | 1.09 | 0.96 | 0.97 | 1.01 | 0.96 | 0.98 | 1.00 | 0.99 |
Ensemble average validation | 0.82 | 1.15 | 0.90 | 1.26 | 1.14 | 0.74 | 0.97 | 1.03 | 1.00 | |
5 Parameters Method | Saba | Oze | Ota | Ashida | Takahashi | Asahi | Yoshii | All | Average | |
NSE | Calibration | 0.98 | 0.98 | 0.96 | 0.96 | 0.98 | 0.97 | 0.98 | 0.99 | 0.97 |
Ensemble average validation | 0.91 | 0.95 | 0.93 | 0.94 | 0.98 | 0.85 | 0.96 | 0.98 | 0.93 | |
KGE | Calibration | 0.94 | 0.98 | 0.97 | 0.93 | 0.98 | 0.96 | 0.94 | 0.99 | 0.96 |
Ensemble average validation | 0.75 | 0.86 | 0.88 | 0.92 | 0.93 | 0.64 | 0.85 | 0.87 | 0.83 | |
PE | Calibration | 0.90 | 1.07 | 0.88 | 0.97 | 0.99 | 0.92 | 0.97 | 0.99 | 0.96 |
Ensemble average validation | 0.74 | 1.01 | 0.76 | 1.10 | 0.96 | 0.62 | 0.89 | 0.89 | 0.87 |
River | Event | Qmax (m³ /s) | NSE (7-CPM) | NSE (5-CPM) | KGE (7-CPM) | KGE (5-CPM) | PE (7-CPM) | PE (5-CPM) |
---|---|---|---|---|---|---|---|---|
Saba | 2018 | 920 | 0.95 | 0.91 | 0.85 | 0.75 | 0.82 | 0.74 |
2010 | 1060 | 0.97 | 0.95 | 0.94 | 0.87 | 0.95 | 0.87 | |
2016 | 900 | 0.75 | 0.75 | 0.55 | 0.57 | 0.64 | 0.63 | |
2005-9 | 910 | 0.69 | 0.16 | 0.35 | −0.09 | 1.54 | 1.85 | |
2005-7 | 470 | 0.84 | 0.31 | 0.83 | 0.26 | 0.94 | 1.35 | |
2011 | 490 | 0.87 | 0.91 | 0.80 | 0.90 | 0.93 | 1.13 | |
2009 | 1250 | 0.68 | 0.89 | 0.50 | 0.80 | 1.40 | 1.02 | |
Oze | 2018 | 1240 | 0.95 | 0.95 | 0.90 | 0.86 | 1.15 | 1.01 |
2010 | 490 | 0.94 | 0.92 | 0.93 | 0.92 | 0.97 | 0.87 | |
2016 | 260 | 0.87 | 0.78 | 0.84 | 0.74 | 1.11 | 0.98 | |
2005 | 630 | 0.87 | 0.94 | 0.83 | 0.85 | 1.21 | 1.06 | |
2006 | 360 | 0.93 | 0.80 | 0.83 | 0.63 | 0.89 | 0.76 | |
2004 | 220 | 0.91 | 0.68 | 0.86 | 0.58 | 0.85 | 0.91 | |
2003 | 320 | 0.84 | 0.75 | 0.77 | 0.67 | 0.82 | 0.67 | |
Ota | 2018 | 4530 | 0.97 | 0.93 | 0.95 | 0.88 | 0.90 | 0.76 |
2005 | 7080 | 0.93 | 0.90 | 0.78 | 0.81 | 0.74 | 0.69 | |
2010 | 4220 | 0.98 | 0.94 | 0.97 | 0.91 | 0.96 | 0.77 | |
2009 | 2250 | 0.92 | 0.82 | 0.75 | 0.67 | 1.06 | 0.91 | |
2004 | 1110 | 0.78 | 0.42 | 0.72 | 0.32 | 1.30 | 1.35 | |
1997 | 1620 | 0.85 | 0.77 | 0.90 | 0.83 | 1.02 | 0.94 | |
1999 | 3890 | 0.75 | 0.73 | 0.56 | 0.61 | 0.54 | 0.48 | |
Ashida | 2018 | 2090 | 0.84 | 0.94 | 0.70 | 0.92 | 1.26 | 1.10 |
2017 | 610 | 0.95 | 0.92 | 0.88 | 0.80 | 0.99 | 0.95 | |
2010 | 1110 | 0.93 | 0.90 | 0.88 | 0.73 | 1.14 | 0.88 | |
2013-9 | 920 | 0.93 | 0.93 | 0.79 | 0.82 | 1.13 | 0.86 | |
2013-6 | 460 | −0.19 | −0.44 | −0.10 | −0.28 | 1.40 | 1.59 | |
2016 | 990 | 0.90 | 0.79 | 0.76 | 0.59 | 0.77 | 0.63 | |
2005 | 300 | −2.63 | −4.28 | −0.35 | −0.78 | 1.10 | 1.50 | |
Takahashi | 2018-7 | 7660 | 0.96 | 0.98 | 0.92 | 0.93 | 1.14 | 0.96 |
2011 | 5110 | 0.97 | 0.93 | 0.84 | 0.78 | 1.05 | 1.00 | |
2018-10 | 4870 | 0.97 | 0.96 | 0.84 | 0.81 | 1.13 | 1.01 | |
2010 | 2520 | 0.96 | 0.92 | 0.93 | 0.87 | 0.89 | 0.84 | |
2006 | 3980 | 0.93 | 0.89 | 0.81 | 0.75 | 0.80 | 0.71 | |
2013 | 3810 | 0.96 | 0.93 | 0.82 | 0.78 | 1.05 | 0.91 | |
2012 | 3050 | 0.96 | 0.90 | 0.92 | 0.82 | 0.92 | 0.81 | |
Asahi | 2018-7 | 5330 | 0.90 | 0.85 | 0.69 | 0.64 | 0.74 | 0.62 |
2006 | 2650 | 0.88 | 0.83 | 0.77 | 0.75 | 0.77 | 0.70 | |
2013 | 2030 | 0.97 | 0.90 | 0.90 | 0.79 | 0.90 | 0.79 | |
2011 | 3230 | 0.94 | 0.94 | 0.92 | 0.92 | 0.97 | 0.91 | |
2018-9 | 1070 | 0.25 | -0.05 | 0.25 | 0.01 | 1.28 | 1.49 | |
2004 | 2800 | 0.84 | 0.82 | 0.88 | 0.81 | 0.86 | 0.77 | |
2018-10 | 1870 | 0.84 | 0.84 | 0.71 | 0.65 | 1.17 | 1.09 | |
Yoshii | 2018 | 6700 | 0.95 | 0.96 | 0.85 | 0.85 | 0.97 | 0.89 |
2004 | 5740 | 0.94 | 0.93 | 0.78 | 0.80 | 0.75 | 0.75 | |
2011 | 3750 | 0.94 | 0.88 | 0.88 | 0.81 | 1.05 | 1.03 | |
2013 | 4010 | 0.97 | 0.94 | 0.88 | 0.79 | 0.89 | 0.86 | |
2009 | 3170 | 0.94 | 0.97 | 0.92 | 0.78 | 0.95 | 1.09 | |
2006 | 4150 | 0.95 | 0.94 | 0.93 | 0.88 | 0.87 | 0.79 | |
2004 | 3580 | 0.91 | 0.91 | 0.88 | 0.89 | 0.84 | 0.87 | |
Average (all) | 2485 | 0.79 | 0.70 | 0.76 | 0.68 | 0.99 | 0.94 | |
Average (top 94%) | 2608 | 0.90 | 0.85 | 0.82 | 0.75 | 0.97 | 0.90 |
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Trošelj, J.; Lee, H.S.; Hobohm, L. Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations. Sustainability 2023, 15, 13897. https://doi.org/10.3390/su151813897
Trošelj J, Lee HS, Hobohm L. Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations. Sustainability. 2023; 15(18):13897. https://doi.org/10.3390/su151813897
Chicago/Turabian StyleTrošelj, Joško, Han Soo Lee, and Lena Hobohm. 2023. "Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations" Sustainability 15, no. 18: 13897. https://doi.org/10.3390/su151813897
APA StyleTrošelj, J., Lee, H. S., & Hobohm, L. (2023). Enhancing a Real-Time Flash Flood Predictive Accuracy Approach for the Development of Early Warning Systems: Hydrological Ensemble Hindcasts and Parameterizations. Sustainability, 15(18), 13897. https://doi.org/10.3390/su151813897