Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments
Identifieur interne : 002F95 ( Istex/Corpus ); précédent : 002F94; suivant : 002F96Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments
Auteurs : L. Coron ; V. Andréassian ; C. Perrin ; J. Lerat ; J. Vaze ; M. Bourqui ; F. HendrickxSource :
- Water Resources Research [ 0043-1397 ] ; 2012-05.
English descriptors
- KwdEn :
- Andreassian, Average conditions, Bias, Calibration, Calibration performance, Calibration period, Calibration periods, Catchment, Catchment scale, Chiew, Climate, Climate change, Climate change impact studies, Climate change impacts, Climate characteristics, Climate conditions, Climate difference, Climate differences, Climate variables, Climatic, Climatic characteristics, Climatic conditions, Climatic differences, Conceptual models, Coron, Csiro land, Daily data, Earth syst, Entire catchment, Free parameters, Further research, Generalized test, Gr4j, Gsst, Gsst procedure, Hydrol, Hydrological, Hydrological models, Interannual, Interannual variability, Large number, Mathevet, Median, Median bias, Merz, Methodology, Model calibration, Model error, Model parameters, Model performance, Model robustness, Mordor6, Ndings, Objective function, Optimized, Oudin, Overview, Parameter, Parameter dependency, Parameter sets, Parameter transfer, Parameter transferability, Parameter transfers, Parameter values, Percentile, Performance loss, Performance losses, Potential evapotranspiration, Rainfall, Resour, Rmse, Robustness, Robustness loss, Runoff, Simhyd, Simulation, Simulation bias, Subperiods, Teng, Testing hydrological models, Time series, Transferability, Validation, Validation bias, Validation periods, Variability, Various conditions, Vaze, Water budget, Water resour, Wetter, Wide range, Year periods.
- Teeft :
- Andreassian, Average conditions, Bias, Calibration, Calibration performance, Calibration period, Calibration periods, Catchment, Catchment scale, Chiew, Climate, Climate change, Climate change impact studies, Climate change impacts, Climate characteristics, Climate conditions, Climate difference, Climate differences, Climate variables, Climatic, Climatic characteristics, Climatic conditions, Climatic differences, Conceptual models, Coron, Csiro land, Daily data, Earth syst, Entire catchment, Free parameters, Further research, Generalized test, Gr4j, Gsst, Gsst procedure, Hydrol, Hydrological, Hydrological models, Interannual, Interannual variability, Large number, Mathevet, Median, Median bias, Merz, Methodology, Model calibration, Model error, Model parameters, Model performance, Model robustness, Mordor6, Ndings, Objective function, Optimized, Oudin, Overview, Parameter, Parameter dependency, Parameter sets, Parameter transfer, Parameter transferability, Parameter transfers, Parameter values, Percentile, Performance loss, Performance losses, Potential evapotranspiration, Rainfall, Resour, Rmse, Robustness, Robustness loss, Runoff, Simhyd, Simulation, Simulation bias, Subperiods, Teng, Testing hydrological models, Time series, Transferability, Validation, Validation bias, Validation periods, Variability, Various conditions, Vaze, Water budget, Water resour, Wetter, Wide range, Year periods.
Abstract
This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split‐sample tests, testing all possible combinations of calibration‐validation periods using a 10 year sliding window. This methodology, which we have called the generalized split‐sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall‐runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root‐mean‐square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties.
Url:
DOI: 10.1029/2011WR011721
Links to Exploration step
ISTEX:FE3762420A06B692D129FC1D9C60A0B546708DBALe document en format XML
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Coron</name><affiliation><mods:affiliation>LNHE, EDF R&D,Chatou,France</mods:affiliation></affiliation><affiliation><mods:affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: laurent.coron@edf.fr</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: laurent.coron@edf.fr</mods:affiliation></affiliation></author><author><name sortKey="Andreassian, V" sort="Andreassian, V" uniqKey="Andreassian V" first="V." last="Andréassian">V. Andréassian</name><affiliation><mods:affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</mods:affiliation></affiliation></author><author><name sortKey="Perrin, C" sort="Perrin, C" uniqKey="Perrin C" first="C." last="Perrin">C. Perrin</name><affiliation><mods:affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</mods:affiliation></affiliation></author><author><name sortKey="Lerat, J" sort="Lerat, J" uniqKey="Lerat J" first="J." last="Lerat">J. Lerat</name><affiliation><mods:affiliation>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia</mods:affiliation></affiliation></author><author><name sortKey="Vaze, J" sort="Vaze, J" uniqKey="Vaze J" first="J." last="Vaze">J. Vaze</name><affiliation><mods:affiliation>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia</mods:affiliation></affiliation></author><author><name sortKey="Bourqui, M" sort="Bourqui, M" uniqKey="Bourqui M" first="M." last="Bourqui">M. Bourqui</name><affiliation><mods:affiliation>LNHE, EDF R&D,Chatou,France</mods:affiliation></affiliation></author><author><name sortKey="Hendrickx, F" sort="Hendrickx, F" uniqKey="Hendrickx F" first="F." last="Hendrickx">F. Hendrickx</name><affiliation><mods:affiliation>LNHE, EDF R&D,Chatou,France</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="j" type="main">Water Resources Research</title><title level="j" type="alt">WATER RESOURCES RESEARCH</title><idno type="ISSN">0043-1397</idno><idno type="eISSN">1944-7973</idno><imprint><biblScope unit="vol">48</biblScope><biblScope unit="issue">5</biblScope><biblScope unit="page-count">17</biblScope><date type="published" when="2012-05">2012-05</date></imprint><idno type="ISSN">0043-1397</idno></series></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0043-1397</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Andreassian</term><term>Average conditions</term><term>Bias</term><term>Calibration</term><term>Calibration performance</term><term>Calibration period</term><term>Calibration periods</term><term>Catchment</term><term>Catchment scale</term><term>Chiew</term><term>Climate</term><term>Climate change</term><term>Climate change impact studies</term><term>Climate change impacts</term><term>Climate characteristics</term><term>Climate conditions</term><term>Climate difference</term><term>Climate differences</term><term>Climate variables</term><term>Climatic</term><term>Climatic characteristics</term><term>Climatic conditions</term><term>Climatic differences</term><term>Conceptual models</term><term>Coron</term><term>Csiro land</term><term>Daily data</term><term>Earth syst</term><term>Entire catchment</term><term>Free parameters</term><term>Further research</term><term>Generalized test</term><term>Gr4j</term><term>Gsst</term><term>Gsst procedure</term><term>Hydrol</term><term>Hydrological</term><term>Hydrological models</term><term>Interannual</term><term>Interannual variability</term><term>Large number</term><term>Mathevet</term><term>Median</term><term>Median bias</term><term>Merz</term><term>Methodology</term><term>Model calibration</term><term>Model error</term><term>Model parameters</term><term>Model performance</term><term>Model robustness</term><term>Mordor6</term><term>Ndings</term><term>Objective function</term><term>Optimized</term><term>Oudin</term><term>Overview</term><term>Parameter</term><term>Parameter dependency</term><term>Parameter sets</term><term>Parameter transfer</term><term>Parameter transferability</term><term>Parameter transfers</term><term>Parameter values</term><term>Percentile</term><term>Performance loss</term><term>Performance losses</term><term>Potential evapotranspiration</term><term>Rainfall</term><term>Resour</term><term>Rmse</term><term>Robustness</term><term>Robustness loss</term><term>Runoff</term><term>Simhyd</term><term>Simulation</term><term>Simulation bias</term><term>Subperiods</term><term>Teng</term><term>Testing hydrological models</term><term>Time series</term><term>Transferability</term><term>Validation</term><term>Validation bias</term><term>Validation periods</term><term>Variability</term><term>Various conditions</term><term>Vaze</term><term>Water budget</term><term>Water resour</term><term>Wetter</term><term>Wide range</term><term>Year periods</term></keywords><keywords scheme="Teeft" xml:lang="en"><term>Andreassian</term><term>Average conditions</term><term>Bias</term><term>Calibration</term><term>Calibration performance</term><term>Calibration period</term><term>Calibration periods</term><term>Catchment</term><term>Catchment scale</term><term>Chiew</term><term>Climate</term><term>Climate change</term><term>Climate change impact studies</term><term>Climate change impacts</term><term>Climate characteristics</term><term>Climate conditions</term><term>Climate difference</term><term>Climate differences</term><term>Climate variables</term><term>Climatic</term><term>Climatic characteristics</term><term>Climatic conditions</term><term>Climatic differences</term><term>Conceptual models</term><term>Coron</term><term>Csiro land</term><term>Daily data</term><term>Earth syst</term><term>Entire catchment</term><term>Free parameters</term><term>Further research</term><term>Generalized test</term><term>Gr4j</term><term>Gsst</term><term>Gsst procedure</term><term>Hydrol</term><term>Hydrological</term><term>Hydrological models</term><term>Interannual</term><term>Interannual variability</term><term>Large number</term><term>Mathevet</term><term>Median</term><term>Median bias</term><term>Merz</term><term>Methodology</term><term>Model calibration</term><term>Model error</term><term>Model parameters</term><term>Model performance</term><term>Model robustness</term><term>Mordor6</term><term>Ndings</term><term>Objective function</term><term>Optimized</term><term>Oudin</term><term>Overview</term><term>Parameter</term><term>Parameter dependency</term><term>Parameter sets</term><term>Parameter transfer</term><term>Parameter transferability</term><term>Parameter transfers</term><term>Parameter values</term><term>Percentile</term><term>Performance loss</term><term>Performance losses</term><term>Potential evapotranspiration</term><term>Rainfall</term><term>Resour</term><term>Rmse</term><term>Robustness</term><term>Robustness loss</term><term>Runoff</term><term>Simhyd</term><term>Simulation</term><term>Simulation bias</term><term>Subperiods</term><term>Teng</term><term>Testing hydrological models</term><term>Time series</term><term>Transferability</term><term>Validation</term><term>Validation bias</term><term>Validation periods</term><term>Variability</term><term>Various conditions</term><term>Vaze</term><term>Water budget</term><term>Water resour</term><term>Wetter</term><term>Wide range</term><term>Year periods</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract">This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split‐sample tests, testing all possible combinations of calibration‐validation periods using a 10 year sliding window. This methodology, which we have called the generalized split‐sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall‐runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root‐mean‐square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties.</div></front></TEI><istex><corpusName>wiley</corpusName><keywords><teeft><json:string>catchment</json:string><json:string>hydrological</json:string><json:string>climatic</json:string><json:string>hydrol</json:string><json:string>validation</json:string><json:string>coron</json:string><json:string>vaze</json:string><json:string>water resour</json:string><json:string>resour</json:string><json:string>testing hydrological models</json:string><json:string>hydrological models</json:string><json:string>chiew</json:string><json:string>transferability</json:string><json:string>rmse</json:string><json:string>parameter transfer</json:string><json:string>andreassian</json:string><json:string>climatic conditions</json:string><json:string>subperiods</json:string><json:string>gsst</json:string><json:string>calibration 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Coron</name><affiliations><json:string>LNHE, EDF R&D,Chatou,France</json:string><json:string>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</json:string><json:string>E-mail: laurent.coron@edf.fr</json:string><json:string>E-mail: laurent.coron@edf.fr</json:string></affiliations></json:item><json:item><name>V. Andréassian</name><affiliations><json:string>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</json:string></affiliations></json:item><json:item><name>C. Perrin</name><affiliations><json:string>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</json:string></affiliations></json:item><json:item><name>J. Lerat</name><affiliations><json:string>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia</json:string></affiliations></json:item><json:item><name>J. Vaze</name><affiliations><json:string>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia</json:string></affiliations></json:item><json:item><name>M. Bourqui</name><affiliations><json:string>LNHE, EDF R&D,Chatou,France</json:string></affiliations></json:item><json:item><name>F. Hendrickx</name><affiliations><json:string>LNHE, EDF R&D,Chatou,France</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>hydrological modeling</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>parameters transferability</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>model robustness</value></json:item></subject><articleId><json:string>2011WR011721</json:string></articleId><arkIstex>ark:/67375/WNG-QHL34K2D-0</arkIstex><language><json:string>eng</json:string></language><originalGenre><json:string>article</json:string></originalGenre><abstract>This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split‐sample tests, testing all possible combinations of calibration‐validation periods using a 10 year sliding window. This methodology, which we have called the generalized split‐sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall‐runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root‐mean‐square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties.</abstract><qualityIndicators><score>9.796</score><pdfWordCount>10841</pdfWordCount><pdfCharCount>66866</pdfCharCount><pdfVersion>1.4</pdfVersion><pdfPageCount>17</pdfPageCount><pdfPageSize>612 x 828 pts</pdfPageSize><refBibsNative>true</refBibsNative><abstractWordCount>233</abstractWordCount><abstractCharCount>1670</abstractCharCount><keywordCount>3</keywordCount></qualityIndicators><title>Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments</title><genre><json:string>article</json:string></genre><host><title>Water Resources Research</title><language><json:string>unknown</json:string></language><doi><json:string>10.1002/(ISSN)1944-7973</json:string></doi><issn><json:string>0043-1397</json:string></issn><eissn><json:string>1944-7973</json:string></eissn><publisherId><json:string>WRCR</json:string></publisherId><volume>48</volume><issue>5</issue><pages><first>n/a</first><last>n/a</last><total>17</total></pages><genre><json:string>journal</json:string></genre><subject><json:item><value>Hydrology</value></json:item><json:item><value>Hydrology: Climate impacts</value></json:item><json:item><value>Natural Hazards: Climate impact</value></json:item><json:item><value>Hydrology: Model calibration</value></json:item><json:item><value>Atmospheric Processes: Model calibration</value></json:item><json:item><value>Hydrology: Modeling</value></json:item><json:item><value>Informatics: Modeling</value></json:item><json:item><value>Natural Hazards: Physical modeling</value></json:item><json:item><value>Regular Article</value></json:item></subject></host><namedEntities><unitex><date><json:string>1974</json:string><json:string>2012</json:string><json:string>1978</json:string><json:string>1980s</json:string></date><geogName></geogName><orgName><json:string>Black Mountain Laboratories</json:string><json:string>Bioprocesses Research Unit, Irstea, Antony, France</json:string><json:string>American Geophysical Union</json:string></orgName><orgName_funder></orgName_funder><orgName_provider></orgName_provider><persName><json:string>R. Provided</json:string><json:string>Klemes</json:string><json:string>A. Efstratiadis</json:string><json:string>Knudsen</json:string><json:string>Wilby</json:string><json:string>J. C. Refsgaard</json:string><json:string>M. Bourqui</json:string><json:string>Moore</json:string><json:string>Xu</json:string><json:string>J. Lerat</json:string><json:string>L. Coron</json:string><json:string>Donnelly-Makowecki</json:string><json:string>C. Perrin</json:string><json:string>Rose River</json:string><json:string>Seibert</json:string><json:string>J. Vaze</json:string><json:string>F. Hendrickx</json:string><json:string>Refsgaard</json:string></persName><placeName><json:string>Australia</json:string><json:string>Austria</json:string><json:string>Victoria</json:string><json:string>Wales</json:string><json:string>France</json:string><json:string>Capacity</json:string></placeName><ref_url><json:string>http://www.seaci.org/</json:string></ref_url><ref_bibl><json:string>Bastola et al. [2011]</json:string><json:string>Tan et al. [2005]</json:string><json:string>Thyer et al. [2009]</json:string><json:string>Coron et al. [2011]</json:string><json:string>Merz et al. [2011]</json:string><json:string>[2010]</json:string><json:string>Perrin et al. [2003]</json:string><json:string>Anctil et al. [2004]</json:string><json:string>Wagener et al. [2003]</json:string><json:string>[1986]</json:string><json:string>Oudin et al.</json:string><json:string>[6]</json:string><json:string>Vaze et al., 2010a</json:string><json:string>Vaze and Teng, 2011</json:string><json:string>Chiew et al. [2002]</json:string><json:string>[8]</json:string><json:string>Caballero et al., 2007</json:string><json:string>[1996]</json:string><json:string>Görgen et al., 2010</json:string><json:string>SteeleDunne et al., 2008</json:string><json:string>Andreassian et al. [2009]</json:string><json:string>Vicuna and Dracup, 2007</json:string><json:string>[54]</json:string><json:string>McMillan et al., 2011</json:string><json:string>Viney et al. [2009]</json:string><json:string>Potter and Chiew, 2011</json:string><json:string>Edijatno et al., 1999</json:string><json:string>Lerat et al., 2012</json:string><json:string>[16]</json:string><json:string>Murphy et al., 2006</json:string><json:string>Niel et al. [2003]</json:string><json:string>Prudhomme and Davies, 2009</json:string><json:string>[3]</json:string><json:string>de Vos et al. [2010]</json:string><json:string>Perrin et al., 2008</json:string><json:string>Merz et al., 2011</json:string><json:string>Oudin et al., 2008</json:string><json:string>Le Moine et al., 2007</json:string><json:string>[37]</json:string><json:string>Chiew et al. [2009]</json:string><json:string>[1999]</json:string><json:string>Rosero et al. [2010]</json:string><json:string>[52]</json:string><json:string>Nash and Sutcliffe, 1970</json:string><json:string>[36]</json:string><json:string>Wilby and Harris, 2006</json:string><json:string>Chiew et al., 2009</json:string><json:string>Yapo et al. [1996]</json:string><json:string>Oudin et al., 2006a</json:string><json:string>[2011]</json:string><json:string>Harman et al., 2011</json:string><json:string>Chahinian et al., 2006</json:string><json:string>Vaze et al.</json:string><json:string>[2]</json:string><json:string>[57]</json:string><json:string>Teng et al., 2011</json:string><json:string>Vaze et al., 2010b</json:string><json:string>Chiew et al., 2008</json:string><json:string>Singh et al. [2011]</json:string></ref_bibl><bibl></bibl></unitex></namedEntities><ark><json:string>ark:/67375/WNG-QHL34K2D-0</json:string></ark><categories><wos><json:string>1 - science</json:string><json:string>2 - water resources</json:string><json:string>2 - limnology</json:string><json:string>2 - environmental sciences</json:string></wos><scienceMetrix><json:string>1 - applied sciences</json:string><json:string>2 - engineering</json:string><json:string>3 - environmental engineering</json:string></scienceMetrix><scopus><json:string>1 - Physical Sciences</json:string><json:string>2 - Environmental Science</json:string><json:string>3 - Water Science and Technology</json:string></scopus></categories><publicationDate>2012</publicationDate><copyrightDate>2012</copyrightDate><doi><json:string>10.1029/2011WR011721</json:string></doi><id>FE3762420A06B692D129FC1D9C60A0B546708DBA</id><score>1</score><fulltext><json:item><extension>pdf</extension><original>true</original><mimetype>application/pdf</mimetype><uri>https://api.istex.fr/document/FE3762420A06B692D129FC1D9C60A0B546708DBA/fulltext/pdf</uri></json:item><json:item><extension>zip</extension><original>false</original><mimetype>application/zip</mimetype><uri>https://api.istex.fr/document/FE3762420A06B692D129FC1D9C60A0B546708DBA/fulltext/zip</uri></json:item><istex:fulltextTEI uri="https://api.istex.fr/document/FE3762420A06B692D129FC1D9C60A0B546708DBA/fulltext/tei"><teiHeader><fileDesc><titleStmt><title level="a" type="main">Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments</title></titleStmt><publicationStmt><authority>ISTEX</authority><publisher>Wiley Publishing Ltd</publisher><availability><licence>Copyright2012 American Geophysical Union. All Rights Reserved.</licence></availability><date type="published" when="2012-05"></date></publicationStmt><notesStmt><note type="content-type" subtype="article" source="article" scheme="https://content-type.data.istex.fr/ark:/67375/XTP-6N5SZHKN-D">article</note><note type="publication-type" subtype="journal" scheme="https://publication-type.data.istex.fr/ark:/67375/JMC-0GLKJH51-B">journal</note></notesStmt><sourceDesc><biblStruct type="article"><analytic><title level="a" type="main">Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments</title><title level="a" type="short">TESTING HYDROLOGICAL MODELS IN CONTRASTED CLIMATE</title><author xml:id="author-0000" role="corresp"><persName><forename type="first">L.</forename><surname>Coron</surname></persName><email>laurent.coron@edf.fr</email><affiliation>LNHE, EDF R&D,Chatou,France<address><country key="FR"></country></address></affiliation><affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France<address><country key="FR"></country></address></affiliation><affiliation>Corresponding author: L. Coron, LNHE, EDF R&D, 6 quai Watier, F‐78401 Chatou CEDEX, France. (laurent.coron@edf.fr)</affiliation></author><author xml:id="author-0001"><persName><forename type="first">V.</forename><surname>Andréassian</surname></persName><affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France<address><country key="FR"></country></address></affiliation></author><author xml:id="author-0002"><persName><forename type="first">C.</forename><surname>Perrin</surname></persName><affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France<address><country key="FR"></country></address></affiliation></author><author xml:id="author-0003"><persName><forename type="first">J.</forename><surname>Lerat</surname></persName><affiliation>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia<address><country key="AU"></country></address></affiliation></author><author xml:id="author-0004"><persName><forename type="first">J.</forename><surname>Vaze</surname></persName><affiliation>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia<address><country key="AU"></country></address></affiliation></author><author xml:id="author-0005"><persName><forename type="first">M.</forename><surname>Bourqui</surname></persName><affiliation>LNHE, EDF R&D,Chatou,France<address><country key="FR"></country></address></affiliation></author><author xml:id="author-0006"><persName><forename type="first">F.</forename><surname>Hendrickx</surname></persName><affiliation>LNHE, EDF R&D,Chatou,France<address><country key="FR"></country></address></affiliation></author><idno type="istex">FE3762420A06B692D129FC1D9C60A0B546708DBA</idno><idno type="ark">ark:/67375/WNG-QHL34K2D-0</idno><idno type="DOI">10.1029/2011WR011721</idno><idno type="editorialOffice">2011WR011721</idno><idno type="society">W05552</idno><idno type="unit">WRCR13439</idno><idno type="toTypesetVersion">file:WRCR.WRCR13439.pdf</idno></analytic><monogr><title level="j" type="main">Water Resources Research</title><title level="j" type="alt">WATER RESOURCES RESEARCH</title><idno type="pISSN">0043-1397</idno><idno type="eISSN">1944-7973</idno><idno type="book-DOI">10.1002/(ISSN)1944-7973</idno><idno type="book-part-DOI">10.1002/wrcr.v48.5</idno><idno type="product">WRCR</idno><idno type="coden">WRERAQ</idno><imprint><biblScope unit="vol">48</biblScope><biblScope unit="issue">5</biblScope><biblScope unit="page-count">17</biblScope><date type="published" when="2012-05"></date></imprint></monogr></biblStruct></sourceDesc></fileDesc><profileDesc><abstract style="main"><p xml:id="wrcr13439-para-0001">This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split‐sample tests, testing all possible combinations of calibration‐validation periods using a 10 year sliding window. This methodology, which we have called the generalized split‐sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall‐runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root‐mean‐square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties.</p></abstract><abstract style="short"><head>Key Points</head><p xml:id="wrcr13439-para-0002"><list style="bulleted"><item>Proposing methods to analyse model robustness in contrasted climate conditions</item><item>Quantifying robustness losses due to climate change in parameters transfer</item><item>Estimating homogeneity of results over a large number of catchments</item></list></p></abstract><textClass><keywords><term xml:id="wrcr13439-kwd-0001">hydrological modeling</term><term xml:id="wrcr13439-kwd-0002">parameters transferability</term><term xml:id="wrcr13439-kwd-0003">model robustness</term></keywords><classCode scheme="http://psi.agu.org/taxonomy5/1800">Hydrology</classCode><keywords rend="articleCategory"><term>Regular Article</term></keywords><keywords rend="tocHeading1"><term>Regular Article</term></keywords></textClass><langUsage><language ident="en"></language></langUsage></profileDesc></teiHeader></istex:fulltextTEI><json:item><extension>txt</extension><original>false</original><mimetype>text/plain</mimetype><uri>https://api.istex.fr/document/FE3762420A06B692D129FC1D9C60A0B546708DBA/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Wiley, elements deleted: body"><istex:xmlDeclaration>version="1.0" encoding="UTF-8" standalone="yes"</istex:xmlDeclaration><istex:document><component type="serialArticle" version="2.0" xml:lang="en" xml:id="wrcr13439"><header><publicationMeta level="product"><doi>10.1002/(ISSN)1944-7973</doi><issn type="print">0043-1397</issn><issn type="electronic">1944-7973</issn><idGroup><id type="product" value="WRCR"></id><id type="coden" value="WRERAQ"></id></idGroup><titleGroup><title type="main" xml:lang="en" sort="WATER RESOURCES RESEARCH">Water Resources Research</title><title type="short">Water Resour. Res.</title></titleGroup></publicationMeta><publicationMeta level="part" position="50"><doi>10.1002/wrcr.v48.5</doi><numberingGroup><numbering type="journalVolume" number="48">48</numbering><numbering type="journalIssue">5</numbering></numberingGroup><coverDate startDate="2012-05">May 2012</coverDate></publicationMeta><publicationMeta level="unit" type="article" position="80" status="forIssue"><doi>10.1029/2011WR011721</doi><idGroup><id type="editorialOffice" value="2011WR011721"></id><id type="society" value="W05552"></id><id type="unit" value="WRCR13439"></id></idGroup><countGroup><count type="pageTotal" number="17"></count></countGroup><titleGroup><title type="articleCategory">Regular Article</title><title type="tocHeading1">Regular Article</title></titleGroup><copyright ownership="thirdParty">Copyright2012 American Geophysical Union. All Rights Reserved.</copyright><eventGroup><event type="manuscriptReceived" date="2011-12-07"></event><event type="manuscriptRevised" date="2012-03-26"></event><event type="manuscriptAccepted" date="2012-04-15"></event><event type="firstOnline" date="2012-05-26"></event><event type="publishedOnlineFinalForm" date="2012-05-26"></event><event type="xmlConverted" agent="SPi Global Converter:AGUv5.2_TO_WileyML3Gv1.0.3 version:1.1; WileyML 3G Packaging Tool v1.0" date="2012-12-14"></event><event type="xmlConverted" agent="Converter:WILEY_ML3G_TO_WILEY_ML3GV2 version:4.0.1" date="2014-03-21"></event><event type="xmlConverted" agent="Converter:WML3G_To_WML3G version:4.3.4 mode:FullText" date="2015-02-24"></event></eventGroup><numberingGroup><numbering type="pageFirst">n/a</numbering><numbering type="pageLast">n/a</numbering></numberingGroup><correspondenceTo>Corresponding author: L. Coron, LNHE, EDF R&D, 6 quai Watier, F‐78401 Chatou CEDEX, France. (<email>laurent.coron@edf.fr</email>)</correspondenceTo><subjectInfo><subject href="http://psi.agu.org/taxonomy5/1800">Hydrology</subject><subjectInfo><subject href="http://psi.agu.org/taxonomy5/1807">Hydrology: Climate impacts</subject><subjectInfo><subject href="http://psi.agu.org/taxonomy5/4321">Natural Hazards: Climate impact</subject></subjectInfo><subject href="http://psi.agu.org/taxonomy5/1846">Hydrology: Model calibration</subject><subjectInfo><subject href="http://psi.agu.org/taxonomy5/3333">Atmospheric Processes: Model calibration</subject></subjectInfo><subject href="http://psi.agu.org/taxonomy5/1847">Hydrology: Modeling</subject><subjectInfo><subject href="http://psi.agu.org/taxonomy5/1952">Informatics: Modeling</subject><subject href="http://psi.agu.org/taxonomy5/4316">Natural Hazards: Physical modeling</subject></subjectInfo></subjectInfo></subjectInfo><selfCitationGroup><citation xml:id="wrcr13439-cit-0000" type="self"><author><familyName>Coron</familyName>, <givenNames>L.</givenNames></author>, <author><givenNames>V.</givenNames><familyName>Andréassian</familyName></author>, <author><givenNames>C.</givenNames><familyName>Perrin</familyName></author>, <author><givenNames>J.</givenNames><familyName>Lerat</familyName></author>, <author><givenNames>J.</givenNames><familyName>Vaze</familyName></author>, <author><givenNames>M.</givenNames><familyName>Bourqui</familyName></author>, and <author><givenNames>F.</givenNames><familyName>Hendrickx</familyName></author> (<pubYear year="2012">2012</pubYear>), <articleTitle>Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments</articleTitle>, <journalTitle>Water Resour. Res.</journalTitle>, <vol>48</vol>, W05552, doi:<accessionId ref="info:doi/10.1029/2011WR011721">10.1029/2011WR011721</accessionId>.</citation></selfCitationGroup><linkGroup><link type="toTypesetVersion" href="file:WRCR.WRCR13439.pdf"></link></linkGroup></publicationMeta><contentMeta><countGroup><count type="wordTotal" number="11700"></count><count type="figureTotal" number="10"></count><count type="tableTotal" number="2"></count></countGroup><titleGroup><title type="main">Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments</title><title type="shortAuthors">CORON ET AL.</title><title type="short">TESTING HYDROLOGICAL MODELS IN CONTRASTED CLIMATE</title></titleGroup><creators><creator xml:id="wrcr13439-cr-0001" creatorRole="author" affiliationRef="#wrcr13439-aff-0001 #wrcr13439-aff-0002" corresponding="yes"><personName><givenNames>L.</givenNames><familyName>Coron</familyName></personName><contactDetails><email>laurent.coron@edf.fr</email></contactDetails></creator><creator xml:id="wrcr13439-cr-0002" creatorRole="author" affiliationRef="#wrcr13439-aff-0002"><personName><givenNames>V.</givenNames><familyName>Andréassian</familyName></personName></creator><creator xml:id="wrcr13439-cr-0003" creatorRole="author" affiliationRef="#wrcr13439-aff-0002"><personName><givenNames>C.</givenNames><familyName>Perrin</familyName></personName></creator><creator xml:id="wrcr13439-cr-0004" creatorRole="author" affiliationRef="#wrcr13439-aff-0003"><personName><givenNames>J.</givenNames><familyName>Lerat</familyName></personName></creator><creator xml:id="wrcr13439-cr-0005" creatorRole="author" affiliationRef="#wrcr13439-aff-0003"><personName><givenNames>J.</givenNames><familyName>Vaze</familyName></personName></creator><creator xml:id="wrcr13439-cr-0006" creatorRole="author" affiliationRef="#wrcr13439-aff-0001"><personName><givenNames>M.</givenNames><familyName>Bourqui</familyName></personName></creator><creator xml:id="wrcr13439-cr-0007" creatorRole="author" affiliationRef="#wrcr13439-aff-0001"><personName><givenNames>F.</givenNames><familyName>Hendrickx</familyName></personName></creator></creators><affiliationGroup><affiliation xml:id="wrcr13439-aff-0001" countryCode="FR" type="organization"><unparsedAffiliation>LNHE, EDF R&D,Chatou,France</unparsedAffiliation></affiliation><affiliation xml:id="wrcr13439-aff-0002" countryCode="FR" type="organization"><unparsedAffiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</unparsedAffiliation></affiliation><affiliation xml:id="wrcr13439-aff-0003" countryCode="AU" type="organization"><unparsedAffiliation>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup type="author"><keyword xml:id="wrcr13439-kwd-0001">hydrological modeling</keyword><keyword xml:id="wrcr13439-kwd-0002">parameters transferability</keyword><keyword xml:id="wrcr13439-kwd-0003">model robustness</keyword></keywordGroup><supportingInformation><supportingInfoItem><mediaResource alt="supplementary data" mimeType="text/plain" href="urn-x:wiley:00431397:media:wrcr13439:wrcr13439-sup-0001-t01"></mediaResource><caption>Tab‐delimited Table 1.</caption></supportingInfoItem><supportingInfoItem><mediaResource alt="supplementary data" mimeType="text/plain" href="urn-x:wiley:00431397:media:wrcr13439:wrcr13439-sup-0002-t02"></mediaResource><caption>Tab‐delimited Table 2.</caption></supportingInfoItem></supportingInformation><abstractGroup><abstract type="main"><p xml:id="wrcr13439-para-0001" label="1">This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split‐sample tests, testing all possible combinations of calibration‐validation periods using a 10 year sliding window. This methodology, which we have called the generalized split‐sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall‐runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root‐mean‐square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties.</p></abstract><abstract type="short"><title type="main">Key Points</title><p xml:id="wrcr13439-para-0002"><list style="bulleted"><listItem>Proposing methods to analyse model robustness in contrasted climate conditions</listItem><listItem>Quantifying robustness losses due to climate change in parameters transfer</listItem><listItem>Estimating homogeneity of results over a large number of catchments</listItem></list></p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>TESTING HYDROLOGICAL MODELS IN CONTRASTED CLIMATE</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments</title></titleInfo><name type="personal"><namePart type="given">L.</namePart><namePart type="family">Coron</namePart><affiliation>LNHE, EDF R&D,Chatou,France</affiliation><affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</affiliation><affiliation>E-mail: laurent.coron@edf.fr</affiliation><affiliation>E-mail: laurent.coron@edf.fr</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">V.</namePart><namePart type="family">Andréassian</namePart><affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">C.</namePart><namePart type="family">Perrin</namePart><affiliation>Hydrosystems and Bioprocesses Research Unit,Irstea, Antony,France</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">Lerat</namePart><affiliation>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">J.</namePart><namePart type="family">Vaze</namePart><affiliation>Black Mountain Laboratories, CSIRO Land and Water,Acton, ACT,Australia</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">M.</namePart><namePart type="family">Bourqui</namePart><affiliation>LNHE, EDF R&D,Chatou,France</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">F.</namePart><namePart type="family">Hendrickx</namePart><affiliation>LNHE, EDF R&D,Chatou,France</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="article" displayLabel="article" authority="ISTEX" authorityURI="https://content-type.data.istex.fr" valueURI="https://content-type.data.istex.fr/ark:/67375/XTP-6N5SZHKN-D">article</genre><originInfo><publisher>Blackwell Publishing Ltd</publisher><dateIssued encoding="w3cdtf">2012-05</dateIssued><dateCaptured encoding="w3cdtf">2011-12-07</dateCaptured><dateValid encoding="w3cdtf">2012-04-15</dateValid><edition>Coron, L., V.Andréassian, C.Perrin, J.Lerat, J.Vaze, M.Bourqui, and F.Hendrickx (2012), Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48, W05552, doi:10.1029/2011WR011721.</edition><copyrightDate encoding="w3cdtf">2012</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><extent unit="figures">10</extent><extent unit="tables">2</extent><extent unit="words">11700</extent></physicalDescription><abstract>This paper investigates the actual extrapolation capacity of three hydrological models in differing climate conditions. We propose a general testing framework, in which we perform series of split‐sample tests, testing all possible combinations of calibration‐validation periods using a 10 year sliding window. This methodology, which we have called the generalized split‐sample test (GSST), provides insights into the model's transposability over time under various climatic conditions. The three conceptual rainfall‐runoff models yielded similar results over a set of 216 catchments in southeast Australia. First, we assessed the model's efficiency in validation using a criterion combining the root‐mean‐square error and bias. A relation was found between this efficiency and the changes in mean rainfall (P) but not with changes in mean potential evapotranspiration (PE) or air temperature (T). Second, we focused on average runoff volumes and found that simulation biases are greatly affected by changes in P. Calibration over a wetter (drier) climate than the validation climate leads to an overestimation (underestimation) of the mean simulated runoff. We observed different magnitudes of these models deficiencies depending on the catchment considered. Results indicate that the transfer of model parameters in time may introduce a significant level of errors in simulations, meaning increased uncertainty in the various practical applications of these models (flow simulation, forecasting, design, reservoir management, climate change impact assessments, etc.). Testing model robustness with respect to this issue should help better quantify these uncertainties.</abstract><abstract type="short">Proposing methods to analyse model robustness in contrasted climate conditions Quantifying robustness losses due to climate change in parameters transfer Estimating homogeneity of results over a large number of catchments</abstract><note type="additional physical form">Tab‐delimited Table 1.Tab‐delimited Table 2.</note><subject><genre>keywords</genre><topic>hydrological modeling</topic><topic>parameters transferability</topic><topic>model robustness</topic></subject><relatedItem type="host"><titleInfo><title>Water Resources Research</title></titleInfo><titleInfo type="abbreviated"><title>Water Resour. Res.</title></titleInfo><genre type="journal" authority="ISTEX" authorityURI="https://publication-type.data.istex.fr" valueURI="https://publication-type.data.istex.fr/ark:/67375/JMC-0GLKJH51-B">journal</genre><subject><genre>index-terms</genre><topic authorityURI="http://psi.agu.org/taxonomy5/1800">Hydrology</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1807">Hydrology: Climate impacts</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4321">Natural Hazards: Climate impact</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1846">Hydrology: Model calibration</topic><topic authorityURI="http://psi.agu.org/taxonomy5/3333">Atmospheric Processes: Model calibration</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1847">Hydrology: Modeling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/1952">Informatics: Modeling</topic><topic authorityURI="http://psi.agu.org/taxonomy5/4316">Natural Hazards: Physical modeling</topic></subject><subject><genre>article-category</genre><topic>Regular Article</topic></subject><identifier type="ISSN">0043-1397</identifier><identifier type="eISSN">1944-7973</identifier><identifier type="DOI">10.1002/(ISSN)1944-7973</identifier><identifier type="CODEN">WRERAQ</identifier><identifier type="PublisherID">WRCR</identifier><part><date>2012</date><detail type="volume"><caption>vol.</caption><number>48</number></detail><detail type="issue"><caption>no.</caption><number>5</number></detail><extent unit="pages"><start>n/a</start><end>n/a</end><total>17</total></extent></part></relatedItem><identifier type="istex">FE3762420A06B692D129FC1D9C60A0B546708DBA</identifier><identifier type="ark">ark:/67375/WNG-QHL34K2D-0</identifier><identifier type="DOI">10.1029/2011WR011721</identifier><identifier type="ArticleID">2011WR011721</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright2012 American Geophysical Union. 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