Quantifying Uncertainty in Streamflow Records
Uncertainty in hydrometric data is a fact of life. Basic assumptions about the nature of this uncertainty are necessary in every analysis of hydrometric data, and an understanding of the variability of uncertainty can facilitate the effective use of hydrologic information. For most of the twentieth...
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| Veröffentlicht in: | Canadian water resources journal Jg. 37; H. 1; S. 3 - 21 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
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Taylor & Francis Group
22.03.2012
Taylor & Francis Group LLC Canadian Water Resources Assn |
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| ISSN: | 0701-1784, 1918-1817, 1918-1817 |
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| Abstract | Uncertainty in hydrometric data is a fact of life. Basic assumptions about the nature of this uncertainty are necessary in every analysis of hydrometric data, and an understanding of the variability of uncertainty can facilitate the effective use of hydrologic information. For most of the twentieth century there has been little change in hydrometric methods and many analysts explicitly or implicitly assume that the uncertainty has not changed over the period of record. We argue that there is substantial variability in the magnitude of uncertainty in published streamflow records that is not transparent to data users. Quantifying uncertainty is particularly important in the context of the current changes in hydrometric technology and in the increasing integration of data sets from multiple providers. We recommend best practices for identifying uncertainty in field notes and propagating that observational uncertainty through the data production process. We suggest both field and reanalysis studies that could be undertaken to improve understanding of hydrometric uncertainty. We also recommend improvements in management practices, including preservation of relevant metadata and a suitable period of overlap for new and old observing systems to allow assessment of the effects of changing technology. |
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| AbstractList | Uncertainty in hydrometric data is a fact of life. Basic assumptions about the nature of this uncertainty are necessary in every analysis of hydrometric data, and an understanding of the variability of uncertainty can facilitate the effective use of hydrologic information. For most of the twentieth century there has been little change in hydrometric methods and many analysts explicitly or implicitly assume that the uncertainty has not changed over the period of record. We argue that there is substantial variability in the magnitude of uncertainty in published streamflow records that is not transparent to data users. Quantifying uncertainty is particularly important in the context of the current changes in hydrometric technology and in the increasing integration of data sets from multiple providers. We recommend best practices for identifying uncertainty in field notes and propagating that observational uncertainty through the data production process. We suggest both field and reanalysis studies that could be undertaken to improve understanding of hydrometric uncertainty. We also recommend improvements in management practices, including preservation ofrelevant metadata and a suitable period of overlap for new and old observing systems to allow assessment of the effects of changing technology. Uncertainty in hydrometric data is a fact of life. Basic assumptions about the nature of this uncertainty are necessary in every analysis of hydrometric data, and an understanding of the variability of uncertainty can facilitate the effective use of hydrologic information. For most of the twentieth century there has been little change in hydrometric methods and many analysts explicitly or implicitly assume that the uncertainty has not changed over the period of record. We argue that there is substantial variability in the magnitude of uncertainty in published streamflow records that is not transparent to data users. Quantifying uncertainty is particularly important in the context of the current changes in hydrometric technology and in the increasing integration of data sets from multiple providers. We recommend best practices for identifying uncertainty in field notes and propagating that observational uncertainty through the data production process. We suggest both field and reanalysis studies that could be undertaken to improve understanding of hydrometric uncertainty. We also recommend improvements in management practices, including preservation ofrelevant metadata and a suitable period of overlap for new and old observing systems to allow assessment of the effects of changing technology. L'incertitude entourant les donnees hydrometriques est un fait concret. Les hypotheses de base quant a la nature de cette incertitude s'averent necessaires pour chaque analyse des donnees hydrometriques et une comprehension de la variabilite de l'incertitude peut faciliter l'utilisation efficace des donnees hydrologiques. Pendant la majeure partie du vingtieme siecle, ces methodes ont connu peu de changements et de nombreux analystes posent comme hypothese, de maniere explicite ou implicite, que l'incertitude n'a pas evolue au cours de la periode de releve. Nous faisons valoir qu'il existe une variabilite considerable dans l'ampleur de l'incertitude liee aux enregistrements des debits des cours d'eau publies, laquelle n'est pas transparente aux yeux des utilisateurs de donnees. Il est particulierement important de quantifier l'incertitude dans le contexte des changements actuels qui touchent les technologies hydrometriques et de l'integration croissante des ensembles de donnees provenant de fournisseurs multiples. Nous recommandons les pratiques exemplaires pour la determination de l'incertitude dans les notes de terrain et la diffusion de cette incertitude observationnelle par l'entremise du processus de production de donnees. Nous proposons la possibilite d'entreprendre ae la fois des etudes sur le terrain et de nouvelles analyses dans le but d'ameliorer la comprehension de l'incertitude hydrometrique. Nous recommandons egalement d'apporter des ameliorations aux pratiques de gestion, notamment la conservation des metadonnees pertinentes et le recours ae une periode appropriee de chevauchement des anciens et nouveaux systemes d'observation pour faciliter l'evaluation des effets de l'evolution de la technologie. Uncertainty in hydrometric data is a fact of life. Basic assumptions about the nature of this uncertainty are necessary in every analysis of hydrometric data, and an understanding of the variability of uncertainty can facilitate the effective use of hydrologic information. For most of the twentieth century there has been little change in hydrometric methods and many analysts explicitly or implicitly assume that the uncertainty has not changed over the period of record. We argue that there is substantial variability in the magnitude of uncertainty in published streamflow records that is not transparent to data users. Quantifying uncertainty is particularly important in the context of the current changes in hydrometric technology and in the increasing integration of data sets from multiple providers. We recommend best practices for identifying uncertainty in field notes and propagating that observational uncertainty through the data production process. We suggest both field and reanalysis studies that could be undertaken to improve understanding of hydrometric uncertainty. We also recommend improvements in management practices, including preservation of relevant metadata and a suitable period of overlap for new and old observing systems to allow assessment of the effects of changing technology. |
| Audience | Academic |
| Author | Moore, R.D. Hamilton, A.S. |
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| Title | Quantifying Uncertainty in Streamflow Records |
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