Analysis of the Likelihood Function and Cutoff Threshold in the GLUE Procedure for Calibration of the Resistance Parameters of Mountain Rivers
Generalized Likelihood Uncertainty Estimation (GLUE) is a widely used methodology for propagating uncertainty through models. However, GLUE has been criticized because of the random selection of two components: i) the likelihood function, which is used to determine the probability that a given set o...
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| Veröffentlicht in: | Water resources management 2024-09, Vol.38 (11), p.4361-4377 |
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| description | Generalized Likelihood Uncertainty Estimation (GLUE) is a widely used methodology for propagating uncertainty through models. However, GLUE has been criticized because of the random selection of two components: i) the likelihood function, which is used to determine the probability that a given set of parameters reflects the observed data, and ii) the cutoff threshold, which is used to divide models into behavioral and nonbehavioral groups. In this research, a GLUE procedure is implemented based on three mountain river morphologies (cascade, step-pool, and plane bed) with different flow characteristics (high, moderate and low flow) located in the Quinuas River basin. Geometry, flow, bed material, and field roughness data are available for the studied reaches. The simple Fuzzy-rule provides different results than metric-based likelihood functions, so a modification of the simple fuzzy-rule is suggested. The metric-based-likelihood functions influence likelihood curve shape and uncertainty values for a certain threshold when the system under study do not meet the model simplifications. The cutoff threshold is proven necessary for reducing uncertainty; however, this value cannot be too stringently set because there are many cases in which observations fall outside the 5% and 95% confidence intervals, producing outliers. A reasonable cutoff threshold seems to be 12%, which is the uncertainty in the water depth estimated with the continuity equation. |
| doi_str_mv | 10.1007/s11269-024-03869-x |
| format | Article |
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However, GLUE has been criticized because of the random selection of two components: i) the likelihood function, which is used to determine the probability that a given set of parameters reflects the observed data, and ii) the cutoff threshold, which is used to divide models into behavioral and nonbehavioral groups. In this research, a GLUE procedure is implemented based on three mountain river morphologies (cascade, step-pool, and plane bed) with different flow characteristics (high, moderate and low flow) located in the Quinuas River basin. Geometry, flow, bed material, and field roughness data are available for the studied reaches. The simple Fuzzy-rule provides different results than metric-based likelihood functions, so a modification of the simple fuzzy-rule is suggested. The metric-based-likelihood functions influence likelihood curve shape and uncertainty values for a certain threshold when the system under study do not meet the model simplifications. The cutoff threshold is proven necessary for reducing uncertainty; however, this value cannot be too stringently set because there are many cases in which observations fall outside the 5% and 95% confidence intervals, producing outliers. A reasonable cutoff threshold seems to be 12%, which is the uncertainty in the water depth estimated with the continuity equation.</description><identifier>ISSN: 0920-4741</identifier><identifier>EISSN: 1573-1650</identifier><identifier>DOI: 10.1007/s11269-024-03869-x</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Atmospheric Sciences ; Bed material ; Calibration ; Civil Engineering ; Confidence intervals ; Continuity equation ; Earth and Environmental Science ; Earth Sciences ; Environment ; equations ; Floods ; Flow characteristics ; geometry ; Geotechnical Engineering & Applied Earth Sciences ; Hydrogeology ; Hydrology/Water Resources ; Low flow ; Mountains ; Outliers (statistics) ; Parameter estimation ; Parameter uncertainty ; Parameters ; River basins ; Rivers ; roughness ; Statistical analysis ; Stormwater management ; Uncertainty ; Uncertainty analysis ; water ; Water depth ; watersheds</subject><ispartof>Water resources management, 2024-09, Vol.38 (11), p.4361-4377</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c303t-222e1246197a6ef8992d2f15fee868886c91361b5f37af8146487bbbc100e9e83</cites><orcidid>0000-0001-6866-8937</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11269-024-03869-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11269-024-03869-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Cedillo, Sebastián</creatorcontrib><creatorcontrib>Sánchez-Cordero, Esteban</creatorcontrib><creatorcontrib>Duque-Sarango, Paola</creatorcontrib><creatorcontrib>Timbe, Luis</creatorcontrib><creatorcontrib>Veintimilla-Reyes, Jaime</creatorcontrib><creatorcontrib>Samaniego, Esteban</creatorcontrib><creatorcontrib>Alvarado, Andrés</creatorcontrib><title>Analysis of the Likelihood Function and Cutoff Threshold in the GLUE Procedure for Calibration of the Resistance Parameters of Mountain Rivers</title><title>Water resources management</title><addtitle>Water Resour Manage</addtitle><description>Generalized Likelihood Uncertainty Estimation (GLUE) is a widely used methodology for propagating uncertainty through models. However, GLUE has been criticized because of the random selection of two components: i) the likelihood function, which is used to determine the probability that a given set of parameters reflects the observed data, and ii) the cutoff threshold, which is used to divide models into behavioral and nonbehavioral groups. In this research, a GLUE procedure is implemented based on three mountain river morphologies (cascade, step-pool, and plane bed) with different flow characteristics (high, moderate and low flow) located in the Quinuas River basin. Geometry, flow, bed material, and field roughness data are available for the studied reaches. The simple Fuzzy-rule provides different results than metric-based likelihood functions, so a modification of the simple fuzzy-rule is suggested. The metric-based-likelihood functions influence likelihood curve shape and uncertainty values for a certain threshold when the system under study do not meet the model simplifications. The cutoff threshold is proven necessary for reducing uncertainty; however, this value cannot be too stringently set because there are many cases in which observations fall outside the 5% and 95% confidence intervals, producing outliers. 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| subjects | Atmospheric Sciences Bed material Calibration Civil Engineering Confidence intervals Continuity equation Earth and Environmental Science Earth Sciences Environment equations Floods Flow characteristics geometry Geotechnical Engineering & Applied Earth Sciences Hydrogeology Hydrology/Water Resources Low flow Mountains Outliers (statistics) Parameter estimation Parameter uncertainty Parameters River basins Rivers roughness Statistical analysis Stormwater management Uncertainty Uncertainty analysis water Water depth watersheds |
| title | Analysis of the Likelihood Function and Cutoff Threshold in the GLUE Procedure for Calibration of the Resistance Parameters of Mountain Rivers |
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