Flood and drought hydrologic monitoring: the role of model parameter uncertainty

Chaney, N. W.; Herman, J. D.; Reed, P. M.; Wood, E. F.

doi:10.5194/hess-19-3239-2015

Articles | Volume 19, issue 7

https://doi.org/10.5194/hess-19-3239-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/hess-19-3239-2015

© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 19, issue 7

Research article

|

24 Jul 2015

Research article |

| 24 Jul 2015

Flood and drought hydrologic monitoring: the role of model parameter uncertainty

N. W. Chaney, J. D. Herman, P. M. Reed, and E. F. Wood

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Month	HTML	PDF	XML	Total
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Mar 2015	31	20	1	52
Apr 2015	36	22	3	61
May 2015	13	19	0	32
Jun 2015	31	20	0	51
Jul 2015	121	119	4	244
Aug 2015	56	94	0	150
Sep 2015	18	52	7	77
Oct 2015	51	66	0	117
Nov 2015	46	34	4	84
Dec 2015	25	30	0	55
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Feb 2016	23	38	1	62
Mar 2016	21	29	17	67
Apr 2016	11	16	0	27
May 2016	12	8	4	24
Jun 2016	9	8	2	19
Jul 2016	12	14	2	28
Aug 2016	16	16	0	32
Sep 2016	15	15	0	30
Oct 2016	21	27	6	54
Nov 2016	15	12	7	34
Dec 2016	6	10	0	16
Jan 2017	16	11	1	28
Feb 2017	10	5	1	16
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May 2020	8	7	0	15
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Aug 2020	10	14	6	30
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Dec 2023	14	20	2	36
Jan 2024	26	13	1	40
Feb 2024	16	18	1	35
Mar 2024	19	18	1	38
Apr 2024	23	9	3	35
May 2024	23	13	8	44
Jun 2024	30	14	2	46
Jul 2024	37	9	4	50
Aug 2024	42	11	4	57
Sep 2024	12	4	0	16
Oct 2024	31	8	0	39
Nov 2024	15	6	0	21
Dec 2024	14	12	4	30
Jan 2025	18	11	0	29
Feb 2025	26	12	1	39
Mar 2025	33	16	1	50
Apr 2025	34	17	1	52
May 2025	35	6	1	42
Jun 2025	42	18	0	60
Jul 2025	42	21	2	65
Aug 2025	45	19	2	66
Sep 2025	69	28	3	100
Oct 2025	41	25	1	67
Nov 2025	41	46	3	90
Dec 2025	39	49	5	93
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Cumulative views and downloads (calculated since 04 Feb 2015)

Month	HTML	PDF	XML	Total
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Mar 2015	31	20	1	52
Apr 2015	36	22	3	61
May 2015	13	19	0	32
Jun 2015	31	20	0	51
Jul 2015	121	119	4	244
Aug 2015	56	94	0	150
Sep 2015	18	52	7	77
Oct 2015	51	66	0	117
Nov 2015	46	34	4	84
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Jan 2016	30	45	0	75
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Apr 2016	11	16	0	27
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Jan 2024	26	13	1	40
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Jun 2024	30	14	2	46
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Dec 2024	14	12	4	30
Jan 2025	18	11	0	29
Feb 2025	26	12	1	39
Mar 2025	33	16	1	50
Apr 2025	34	17	1	52
May 2025	35	6	1	42
Jun 2025	42	18	0	60
Jul 2025	42	21	2	65
Aug 2025	45	19	2	66
Sep 2025	69	28	3	100
Oct 2025	41	25	1	67
Nov 2025	41	46	3	90
Dec 2025	39	49	5	93
Jan 2026	4	0	4

Latest update: 03 Jan 2026

Short summary

Land surface modeling is playing an increasing role in global monitoring and prediction of extreme hydrologic events. However, uncertainties in parameter identifiability limit the reliability of model predictions. This study makes use of petascale computing to perform a comprehensive evaluation of land surface modeling for global flood and drought monitoring and suggests paths forward to overcome the challenges posed by parameter uncertainty.