Quantifying flood model accuracy under varying surface complexities
Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used d...
Ausführliche Beschreibung
Autor*in: |
Addison-Atkinson, W. [verfasserIn] Chen, A.S. [verfasserIn] Rubinato, M. [verfasserIn] Memon, F.A. [verfasserIn] Shucksmith, J.D. [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2023 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Journal of hydrology - Amsterdam [u.a.] : Elsevier, 1963, 620 |
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Übergeordnetes Werk: |
volume:620 |
DOI / URN: |
10.1016/j.jhydrol.2023.129511 |
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Katalog-ID: |
ELV063126168 |
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245 | 1 | 0 | |a Quantifying flood model accuracy under varying surface complexities |
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520 | |a Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. | ||
650 | 4 | |a Dual drainage | |
650 | 4 | |a Flow exchange | |
650 | 4 | |a Model validation | |
650 | 4 | |a Surface flow | |
700 | 1 | |a Chen, A.S. |e verfasserin |0 (orcid)0000-0003-3708-3332 |4 aut | |
700 | 1 | |a Rubinato, M. |e verfasserin |0 (orcid)0000-0002-8446-4448 |4 aut | |
700 | 1 | |a Memon, F.A. |e verfasserin |4 aut | |
700 | 1 | |a Shucksmith, J.D. |e verfasserin |0 (orcid)0000-0001-5497-0051 |4 aut | |
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10.1016/j.jhydrol.2023.129511 doi (DE-627)ELV063126168 (ELSEVIER)S0022-1694(23)00453-5 DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Addison-Atkinson, W. verfasserin (orcid)0000-0002-6776-4908 aut Quantifying flood model accuracy under varying surface complexities 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. Dual drainage Flow exchange Model validation Surface flow Chen, A.S. verfasserin (orcid)0000-0003-3708-3332 aut Rubinato, M. verfasserin (orcid)0000-0002-8446-4448 aut Memon, F.A. verfasserin aut Shucksmith, J.D. verfasserin (orcid)0000-0001-5497-0051 aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 620 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:620 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.85 Hydrologie: Allgemeines VZ AR 620 |
spelling |
10.1016/j.jhydrol.2023.129511 doi (DE-627)ELV063126168 (ELSEVIER)S0022-1694(23)00453-5 DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Addison-Atkinson, W. verfasserin (orcid)0000-0002-6776-4908 aut Quantifying flood model accuracy under varying surface complexities 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. Dual drainage Flow exchange Model validation Surface flow Chen, A.S. verfasserin (orcid)0000-0003-3708-3332 aut Rubinato, M. verfasserin (orcid)0000-0002-8446-4448 aut Memon, F.A. verfasserin aut Shucksmith, J.D. verfasserin (orcid)0000-0001-5497-0051 aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 620 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:620 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.85 Hydrologie: Allgemeines VZ AR 620 |
allfields_unstemmed |
10.1016/j.jhydrol.2023.129511 doi (DE-627)ELV063126168 (ELSEVIER)S0022-1694(23)00453-5 DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Addison-Atkinson, W. verfasserin (orcid)0000-0002-6776-4908 aut Quantifying flood model accuracy under varying surface complexities 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. Dual drainage Flow exchange Model validation Surface flow Chen, A.S. verfasserin (orcid)0000-0003-3708-3332 aut Rubinato, M. verfasserin (orcid)0000-0002-8446-4448 aut Memon, F.A. verfasserin aut Shucksmith, J.D. verfasserin (orcid)0000-0001-5497-0051 aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 620 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:620 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.85 Hydrologie: Allgemeines VZ AR 620 |
allfieldsGer |
10.1016/j.jhydrol.2023.129511 doi (DE-627)ELV063126168 (ELSEVIER)S0022-1694(23)00453-5 DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Addison-Atkinson, W. verfasserin (orcid)0000-0002-6776-4908 aut Quantifying flood model accuracy under varying surface complexities 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. Dual drainage Flow exchange Model validation Surface flow Chen, A.S. verfasserin (orcid)0000-0003-3708-3332 aut Rubinato, M. verfasserin (orcid)0000-0002-8446-4448 aut Memon, F.A. verfasserin aut Shucksmith, J.D. verfasserin (orcid)0000-0001-5497-0051 aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 620 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:620 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.85 Hydrologie: Allgemeines VZ AR 620 |
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10.1016/j.jhydrol.2023.129511 doi (DE-627)ELV063126168 (ELSEVIER)S0022-1694(23)00453-5 DE-627 ger DE-627 rda eng 690 VZ 38.85 bkl Addison-Atkinson, W. verfasserin (orcid)0000-0002-6776-4908 aut Quantifying flood model accuracy under varying surface complexities 2023 nicht spezifiziert zzz rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. Dual drainage Flow exchange Model validation Surface flow Chen, A.S. verfasserin (orcid)0000-0003-3708-3332 aut Rubinato, M. verfasserin (orcid)0000-0002-8446-4448 aut Memon, F.A. verfasserin aut Shucksmith, J.D. verfasserin (orcid)0000-0001-5497-0051 aut Enthalten in Journal of hydrology Amsterdam [u.a.] : Elsevier, 1963 620 Online-Ressource (DE-627)268761817 (DE-600)1473173-3 (DE-576)077610628 1879-2707 nnns volume:620 GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OPC-GGO GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_150 GBV_ILN_151 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2034 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2106 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2470 GBV_ILN_2507 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4242 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 38.85 Hydrologie: Allgemeines VZ AR 620 |
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Quantifying flood model accuracy under varying surface complexities |
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Quantifying flood model accuracy under varying surface complexities |
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Addison-Atkinson, W. |
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Addison-Atkinson, W. Chen, A.S. Rubinato, M. Memon, F.A. Shucksmith, J.D. |
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quantifying flood model accuracy under varying surface complexities |
title_auth |
Quantifying flood model accuracy under varying surface complexities |
abstract |
Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. |
abstractGer |
Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. |
abstract_unstemmed |
Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration. |
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Quantifying flood model accuracy under varying surface complexities |
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Chen, A.S. Rubinato, M. Memon, F.A. Shucksmith, J.D. |
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