Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment
Testing hydrological models over different spatio‐temporal scales is important for both evaluating diagnostics and aiding process understanding. High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sa...
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| Veröffentlicht in: | Hydrological processes 2017-10, Vol.31 (22), p.3962-3978 |
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| creator | Tunaley, Claire Tetzlaff, Doerthe Birkel, Christian Soulsby, Chris |
| description | Testing hydrological models over different spatio‐temporal scales is important for both evaluating diagnostics and aiding process understanding. High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sampling in a 3.2‐km2 catchment in the Scottish Highlands. This was used to calibrate and test a tracer‐aided model to assess the (a) information content of high‐resolution data, (b) effect of different calibration strategies on simulations and inferred processes, and (c) model transferability to |
| doi_str_mv | 10.1002/hyp.11313 |
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High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sampling in a 3.2‐km2 catchment in the Scottish Highlands. This was used to calibrate and test a tracer‐aided model to assess the (a) information content of high‐resolution data, (b) effect of different calibration strategies on simulations and inferred processes, and (c) model transferability to <1‐km2 subcatchment. The 6‐hourly data were successfully incorporated without loss of model performance, improving the temporal resolution of the modelling, and making it more relevant to the time dynamics of the isotope and hydrometric response. However, this added little new information due to old‐water dominance and riparian mixing in this peatland catchment. Time variant results, from differential split sample testing, highlighted the importance of calibrating to a wide range of hydrological conditions. This also provided insights into the nonstationarity of catchment mixing processes, in relation to storage and water ages, which varied markedly depending on the calibration period. Application to the nested subcatchment produced equivalent parameterization and performance, highlighting similarity in dominant processes. The study highlighted the utility of high‐resolution data in combination with tracer‐aided models, applied at multiple spatial scales, as learning tools to enhance process understanding and evaluation of model behaviour across nonstationary conditions. This helps reveal more fully the catchment response in terms of the different mechanistic controls on both wave celerites and particle velocities.</description><identifier>ISSN: 0885-6087</identifier><identifier>EISSN: 1099-1085</identifier><identifier>DOI: 10.1002/hyp.11313</identifier><language>eng</language><publisher>Chichester: Wiley Subscription Services, Inc</publisher><subject>Age ; Calibration ; Catchment area ; Catchment areas ; catchment storage ; Catchments ; Computer simulation ; Data ; Data processing ; Dynamics ; Evaluation ; High resolution ; Highlands ; high‐resolution isotopes ; Hydrologic models ; Hydrology ; Isotopes ; Learning behaviour ; Mixing ; Mixing processes ; Modelling ; parameter transferability ; Parameterization ; Rain ; Rainfall ; Resolution ; Riparian environments ; Runoff ; runoff processes ; Sampling ; Spatial discrimination learning ; Stable isotopes ; Storage ; Temporal resolution ; Testing ; Tracers ; tracer‐aided modelling ; water age</subject><ispartof>Hydrological processes, 2017-10, Vol.31 (22), p.3962-3978</ispartof><rights>Copyright © 2017 John Wiley & Sons, Ltd.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3323-5cfa878e14485c5e72b3d82f8e56f2722617357c59b86de3abad3a9b6631f4823</citedby><cites>FETCH-LOGICAL-c3323-5cfa878e14485c5e72b3d82f8e56f2722617357c59b86de3abad3a9b6631f4823</cites><orcidid>0000-0002-2958-0366 ; 0000-0002-7183-8674 ; 0000-0001-6910-2118</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fhyp.11313$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fhyp.11313$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Tunaley, Claire</creatorcontrib><creatorcontrib>Tetzlaff, Doerthe</creatorcontrib><creatorcontrib>Birkel, Christian</creatorcontrib><creatorcontrib>Soulsby, Chris</creatorcontrib><title>Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment</title><title>Hydrological processes</title><description>Testing hydrological models over different spatio‐temporal scales is important for both evaluating diagnostics and aiding process understanding. High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sampling in a 3.2‐km2 catchment in the Scottish Highlands. This was used to calibrate and test a tracer‐aided model to assess the (a) information content of high‐resolution data, (b) effect of different calibration strategies on simulations and inferred processes, and (c) model transferability to <1‐km2 subcatchment. The 6‐hourly data were successfully incorporated without loss of model performance, improving the temporal resolution of the modelling, and making it more relevant to the time dynamics of the isotope and hydrometric response. However, this added little new information due to old‐water dominance and riparian mixing in this peatland catchment. Time variant results, from differential split sample testing, highlighted the importance of calibrating to a wide range of hydrological conditions. This also provided insights into the nonstationarity of catchment mixing processes, in relation to storage and water ages, which varied markedly depending on the calibration period. Application to the nested subcatchment produced equivalent parameterization and performance, highlighting similarity in dominant processes. The study highlighted the utility of high‐resolution data in combination with tracer‐aided models, applied at multiple spatial scales, as learning tools to enhance process understanding and evaluation of model behaviour across nonstationary conditions. This helps reveal more fully the catchment response in terms of the different mechanistic controls on both wave celerites and particle velocities.</description><subject>Age</subject><subject>Calibration</subject><subject>Catchment area</subject><subject>Catchment areas</subject><subject>catchment storage</subject><subject>Catchments</subject><subject>Computer simulation</subject><subject>Data</subject><subject>Data processing</subject><subject>Dynamics</subject><subject>Evaluation</subject><subject>High resolution</subject><subject>Highlands</subject><subject>high‐resolution isotopes</subject><subject>Hydrologic models</subject><subject>Hydrology</subject><subject>Isotopes</subject><subject>Learning behaviour</subject><subject>Mixing</subject><subject>Mixing processes</subject><subject>Modelling</subject><subject>parameter transferability</subject><subject>Parameterization</subject><subject>Rain</subject><subject>Rainfall</subject><subject>Resolution</subject><subject>Riparian environments</subject><subject>Runoff</subject><subject>runoff processes</subject><subject>Sampling</subject><subject>Spatial discrimination learning</subject><subject>Stable isotopes</subject><subject>Storage</subject><subject>Temporal resolution</subject><subject>Testing</subject><subject>Tracers</subject><subject>tracer‐aided modelling</subject><subject>water age</subject><issn>0885-6087</issn><issn>1099-1085</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><recordid>eNp1kL9OwzAQxi0EEqUw8AaWmBjS-k-dOCOqgCJVgoEOTJHjnFtXaVxsF9QNiRfgGXkSTMPKdHe633367kPokpIRJYSNV_vtiFJO-REaUFKWGSVSHKMBkVJkOZHFKToLYU0ImRBJBuhzEWy3xCu7XH1_fHkIrt1F6zpsg4tuC7hRUWHVNVi1EXynon0DrFVra68OYIipgaWFgI3zWOE0a_BJTdkGGux3nTMGb1wDLbZdAjoIMS20inq1gS6eoxOj2gAXf3WIFne3z9NZNn-8f5jezDPNOeOZ0EbJQgKdTKTQAgpW80YyI0HkhhWM5bTgotCirGXeAFe1argq6zzn1Ewk40N01etuvXvdJRPV2u3SS22oaCkYZ5ISkajrntLeheDBVFtvN8rvK0qq34yrlHF1yDix4559ty3s_wer2ctTf_ED6yGBnA</recordid><startdate>20171030</startdate><enddate>20171030</enddate><creator>Tunaley, Claire</creator><creator>Tetzlaff, Doerthe</creator><creator>Birkel, Christian</creator><creator>Soulsby, Chris</creator><general>Wiley Subscription Services, Inc</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>SOI</scope><orcidid>https://orcid.org/0000-0002-2958-0366</orcidid><orcidid>https://orcid.org/0000-0002-7183-8674</orcidid><orcidid>https://orcid.org/0000-0001-6910-2118</orcidid></search><sort><creationdate>20171030</creationdate><title>Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment</title><author>Tunaley, Claire ; Tetzlaff, Doerthe ; Birkel, Christian ; Soulsby, Chris</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3323-5cfa878e14485c5e72b3d82f8e56f2722617357c59b86de3abad3a9b6631f4823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Age</topic><topic>Calibration</topic><topic>Catchment area</topic><topic>Catchment areas</topic><topic>catchment storage</topic><topic>Catchments</topic><topic>Computer simulation</topic><topic>Data</topic><topic>Data processing</topic><topic>Dynamics</topic><topic>Evaluation</topic><topic>High resolution</topic><topic>Highlands</topic><topic>high‐resolution isotopes</topic><topic>Hydrologic models</topic><topic>Hydrology</topic><topic>Isotopes</topic><topic>Learning behaviour</topic><topic>Mixing</topic><topic>Mixing processes</topic><topic>Modelling</topic><topic>parameter transferability</topic><topic>Parameterization</topic><topic>Rain</topic><topic>Rainfall</topic><topic>Resolution</topic><topic>Riparian environments</topic><topic>Runoff</topic><topic>runoff processes</topic><topic>Sampling</topic><topic>Spatial discrimination learning</topic><topic>Stable isotopes</topic><topic>Storage</topic><topic>Temporal resolution</topic><topic>Testing</topic><topic>Tracers</topic><topic>tracer‐aided modelling</topic><topic>water age</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tunaley, Claire</creatorcontrib><creatorcontrib>Tetzlaff, Doerthe</creatorcontrib><creatorcontrib>Birkel, Christian</creatorcontrib><creatorcontrib>Soulsby, Chris</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><jtitle>Hydrological processes</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tunaley, Claire</au><au>Tetzlaff, Doerthe</au><au>Birkel, Christian</au><au>Soulsby, Chris</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment</atitle><jtitle>Hydrological processes</jtitle><date>2017-10-30</date><risdate>2017</risdate><volume>31</volume><issue>22</issue><spage>3962</spage><epage>3978</epage><pages>3962-3978</pages><issn>0885-6087</issn><eissn>1099-1085</eissn><abstract>Testing hydrological models over different spatio‐temporal scales is important for both evaluating diagnostics and aiding process understanding. High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sampling in a 3.2‐km2 catchment in the Scottish Highlands. This was used to calibrate and test a tracer‐aided model to assess the (a) information content of high‐resolution data, (b) effect of different calibration strategies on simulations and inferred processes, and (c) model transferability to <1‐km2 subcatchment. The 6‐hourly data were successfully incorporated without loss of model performance, improving the temporal resolution of the modelling, and making it more relevant to the time dynamics of the isotope and hydrometric response. However, this added little new information due to old‐water dominance and riparian mixing in this peatland catchment. Time variant results, from differential split sample testing, highlighted the importance of calibrating to a wide range of hydrological conditions. This also provided insights into the nonstationarity of catchment mixing processes, in relation to storage and water ages, which varied markedly depending on the calibration period. Application to the nested subcatchment produced equivalent parameterization and performance, highlighting similarity in dominant processes. The study highlighted the utility of high‐resolution data in combination with tracer‐aided models, applied at multiple spatial scales, as learning tools to enhance process understanding and evaluation of model behaviour across nonstationary conditions. 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| ispartof | Hydrological processes, 2017-10, Vol.31 (22), p.3962-3978 |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Age Calibration Catchment area Catchment areas catchment storage Catchments Computer simulation Data Data processing Dynamics Evaluation High resolution Highlands high‐resolution isotopes Hydrologic models Hydrology Isotopes Learning behaviour Mixing Mixing processes Modelling parameter transferability Parameterization Rain Rainfall Resolution Riparian environments Runoff runoff processes Sampling Spatial discrimination learning Stable isotopes Storage Temporal resolution Testing Tracers tracer‐aided modelling water age |
| title | Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment |
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