Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models
Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performa...
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| Autor*in: |
Fowler, Keirnan J. A [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016 |
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| Rechteinformationen: |
Nutzungsrecht: © 2016. American Geophysical Union. All Rights Reserved. |
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| Übergeordnetes Werk: |
Enthalten in: Water resources research - Hoboken, NJ : Wiley, 1965, 52(2016), 3, Seite 1820-1846 |
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| Übergeordnetes Werk: |
volume:52 ; year:2016 ; number:3 ; pages:1820-1846 |
| Links: |
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| DOI / URN: |
10.1002/2015WR018068 |
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| 520 | |a Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing | ||
| 540 | |a Nutzungsrecht: © 2016. American Geophysical Union. All Rights Reserved. | ||
| 650 | 4 | |a rainfall runoff modeling | |
| 650 | 4 | |a climate change | |
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| 650 | 4 | |a Runoff | |
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| 700 | 1 | |a Peel, Murray C |4 oth | |
| 700 | 1 | |a Western, Andrew W |4 oth | |
| 700 | 1 | |a Zhang, Lu |4 oth | |
| 700 | 1 | |a Peterson, Tim J |4 oth | |
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10.1002/2015WR018068 doi PQ20160430 (DE-627)OLC1972729810 (DE-599)GBVOLC1972729810 (PRQ)p960-ff9a66a5d1a6149497293d532d877cea97653ca73dea2050ab4ebf81b1a3b1360 (KEY)0046260820160000052000301820simulatingrunoffunderchangingclimaticconditionsrev DE-627 ger DE-627 rakwb eng 550 DNB 38.85 bkl Fowler, Keirnan J. A verfasserin aut Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing Nutzungsrecht: © 2016. American Geophysical Union. All Rights Reserved. rainfall runoff modeling climate change calibration Calibration Runoff Economic models Peel, Murray C oth Western, Andrew W oth Zhang, Lu oth Peterson, Tim J oth Enthalten in Water resources research Hoboken, NJ : Wiley, 1965 52(2016), 3, Seite 1820-1846 (DE-627)129088285 (DE-600)5564-5 (DE-576)014422980 0043-1397 nnns volume:52 year:2016 number:3 pages:1820-1846 http://dx.doi.org/10.1002/2015WR018068 Volltext http://onlinelibrary.wiley.com/doi/10.1002/2015WR018068/abstract http://search.proquest.com/docview/1782832125 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO GBV_ILN_4219 38.85 AVZ AR 52 2016 3 1820-1846 |
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10.1002/2015WR018068 doi PQ20160430 (DE-627)OLC1972729810 (DE-599)GBVOLC1972729810 (PRQ)p960-ff9a66a5d1a6149497293d532d877cea97653ca73dea2050ab4ebf81b1a3b1360 (KEY)0046260820160000052000301820simulatingrunoffunderchangingclimaticconditionsrev DE-627 ger DE-627 rakwb eng 550 DNB 38.85 bkl Fowler, Keirnan J. A verfasserin aut Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing Nutzungsrecht: © 2016. American Geophysical Union. All Rights Reserved. rainfall runoff modeling climate change calibration Calibration Runoff Economic models Peel, Murray C oth Western, Andrew W oth Zhang, Lu oth Peterson, Tim J oth Enthalten in Water resources research Hoboken, NJ : Wiley, 1965 52(2016), 3, Seite 1820-1846 (DE-627)129088285 (DE-600)5564-5 (DE-576)014422980 0043-1397 nnns volume:52 year:2016 number:3 pages:1820-1846 http://dx.doi.org/10.1002/2015WR018068 Volltext http://onlinelibrary.wiley.com/doi/10.1002/2015WR018068/abstract http://search.proquest.com/docview/1782832125 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO GBV_ILN_4219 38.85 AVZ AR 52 2016 3 1820-1846 |
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10.1002/2015WR018068 doi PQ20160430 (DE-627)OLC1972729810 (DE-599)GBVOLC1972729810 (PRQ)p960-ff9a66a5d1a6149497293d532d877cea97653ca73dea2050ab4ebf81b1a3b1360 (KEY)0046260820160000052000301820simulatingrunoffunderchangingclimaticconditionsrev DE-627 ger DE-627 rakwb eng 550 DNB 38.85 bkl Fowler, Keirnan J. A verfasserin aut Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing Nutzungsrecht: © 2016. American Geophysical Union. All Rights Reserved. rainfall runoff modeling climate change calibration Calibration Runoff Economic models Peel, Murray C oth Western, Andrew W oth Zhang, Lu oth Peterson, Tim J oth Enthalten in Water resources research Hoboken, NJ : Wiley, 1965 52(2016), 3, Seite 1820-1846 (DE-627)129088285 (DE-600)5564-5 (DE-576)014422980 0043-1397 nnns volume:52 year:2016 number:3 pages:1820-1846 http://dx.doi.org/10.1002/2015WR018068 Volltext http://onlinelibrary.wiley.com/doi/10.1002/2015WR018068/abstract http://search.proquest.com/docview/1782832125 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO GBV_ILN_4219 38.85 AVZ AR 52 2016 3 1820-1846 |
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10.1002/2015WR018068 doi PQ20160430 (DE-627)OLC1972729810 (DE-599)GBVOLC1972729810 (PRQ)p960-ff9a66a5d1a6149497293d532d877cea97653ca73dea2050ab4ebf81b1a3b1360 (KEY)0046260820160000052000301820simulatingrunoffunderchangingclimaticconditionsrev DE-627 ger DE-627 rakwb eng 550 DNB 38.85 bkl Fowler, Keirnan J. A verfasserin aut Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models 2016 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing Nutzungsrecht: © 2016. American Geophysical Union. All Rights Reserved. rainfall runoff modeling climate change calibration Calibration Runoff Economic models Peel, Murray C oth Western, Andrew W oth Zhang, Lu oth Peterson, Tim J oth Enthalten in Water resources research Hoboken, NJ : Wiley, 1965 52(2016), 3, Seite 1820-1846 (DE-627)129088285 (DE-600)5564-5 (DE-576)014422980 0043-1397 nnns volume:52 year:2016 number:3 pages:1820-1846 http://dx.doi.org/10.1002/2015WR018068 Volltext http://onlinelibrary.wiley.com/doi/10.1002/2015WR018068/abstract http://search.proquest.com/docview/1782832125 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OLC-FOR SSG-OPC-GGO GBV_ILN_4219 38.85 AVZ AR 52 2016 3 1820-1846 |
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simulating runoff under changing climatic conditions: revisiting an apparent deficiency of conceptual rainfall‐runoff models |
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Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models |
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Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing |
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Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing |
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Hydrologic models have potential to be useful tools in planning for future climate variability. However, recent literature suggests that the current generation of conceptual rainfall runoff models tend to underestimate the sensitivity of runoff to a given change in rainfall, leading to poor performance when evaluated over multiyear droughts. This research revisited this conclusion, investigating whether the observed poor performance could be due to insufficient model calibration and evaluation techniques. We applied an approach based on Pareto optimality to explore trade‐offs between model performance in different climatic conditions. Five conceptual rainfall runoff model structures were tested in 86 catchments in Australia, for a total of 430 Pareto analyses. The Pareto results were then compared with results from a commonly used model calibration and evaluation method, the Differential Split Sample Test. We found that the latter often missed potentially promising parameter sets within a given model structure, giving a false negative impression of the capabilities of the model. This suggests that models may be more capable under changing climatic conditions than previously thought. Of the 282[347] cases of apparent model failure under the split sample test using the lower [higher] of two model performance criteria trialed, 155[120] were false negatives. We discuss potential causes of remaining model failures, including the role of data errors. Although the Pareto approach proved useful, our aim was not to suggest an alternative calibration strategy, but to critically assess existing methods of model calibration and evaluation. We recommend caution when interpreting split sample results. Models may be more capable under changing climatic conditions than previously thought Common calibration methods often fail to identify parameter sets that are robust Caution is needed when interpreting the results of split sample testing |
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Simulating runoff under changing climatic conditions: Revisiting an apparent deficiency of conceptual rainfall‐runoff models |
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