Inadmissible evidence: knowledge and prediction in land and riverscapes
Identifieur interne : 00A587 ( Main/Exploration ); précédent : 00A586; suivant : 00A588Inadmissible evidence: knowledge and prediction in land and riverscapes
Auteurs : Graham Harris [Australie] ; A. L. Heathwaite [Royaume-Uni]Source :
- Journal of hydrology : (Amsterdam) [ 0022-1694 ] ; 2005.
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English descriptors
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Abstract
Analyses of daily water quality data from two streams draining a pair of small coastal catchments in South Devon, England reveal that what conventionally would be thought to show random noise, has a discernable structure and is clear evidence of process. Catchment and aquatic systems are non-equilibrium systems and climate drivers cause fluctuations in water quality both in terms of the concentrations of individual parameters and in the correlations between parameters. The data reveal nonlinear coupling at small scales and show evidence of fractal properties both of which may be evidence of self-organised phenomena at small scales in catchments and streams. These data show that: (a) water quality and catchment nutrient export data may be strongly aliased, and (b) there is a fundamental degree of indeterminacy underlying the data we can collect and the knowledge we can generate from the data. New techniques of data based modelling that use the data itself to define more parsimonious predictive models are needed because such an approach recognises the partial nature of our knowledge and requires adequate monitoring and adaptive management programs.
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Heathwaite</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Centre for Sustainable Water Management, The Lancaster Environment Centre, Lancaster University</s1><s2>Lancaster LA1 4YQ</s2><s3>GBR</s3><sZ>2 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Lancaster LA1 4YQ</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">05-0170659</idno><date when="2005">2005</date><idno type="stanalyst">PASCAL 05-0170659 INIST</idno><idno type="RBID">Pascal:05-0170659</idno><idno type="wicri:Area/PascalFrancis/Corpus">004A24</idno><idno type="wicri:Area/PascalFrancis/Curation">001679</idno><idno type="wicri:Area/PascalFrancis/Checkpoint">004549</idno><idno type="wicri:explorRef" wicri:stream="PascalFrancis" wicri:step="Checkpoint">004549</idno><idno type="wicri:doubleKey">0022-1694:2005:Harris G:inadmissible:evidence:knowledge</idno><idno type="wicri:Area/Main/Merge">00B199</idno><idno type="wicri:Area/Main/Curation">00A587</idno><idno type="wicri:Area/Main/Exploration">00A587</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Inadmissible evidence: knowledge and prediction in land and riverscapes</title><author><name sortKey="Harris, Graham" sort="Harris, Graham" uniqKey="Harris G" first="Graham" last="Harris">Graham Harris</name><affiliation wicri:level="1"><inist:fA14 i1="01"><s1>University of Tasmania</s1><s2>Sandy Bay, Hobart, Tasmania 7005</s2><s3>AUS</s3><sZ>1 aut.</sZ></inist:fA14><country>Australie</country><wicri:noRegion>University of Tasmania</wicri:noRegion></affiliation></author><author><name sortKey="Heathwaite, A L" sort="Heathwaite, A L" uniqKey="Heathwaite A" first="A. L." last="Heathwaite">A. L. Heathwaite</name><affiliation wicri:level="1"><inist:fA14 i1="02"><s1>Centre for Sustainable Water Management, The Lancaster Environment Centre, Lancaster University</s1><s2>Lancaster LA1 4YQ</s2><s3>GBR</s3><sZ>2 aut.</sZ></inist:fA14><country>Royaume-Uni</country><wicri:noRegion>Lancaster LA1 4YQ</wicri:noRegion></affiliation></author></analytic><series><title level="j" type="main">Journal of hydrology : (Amsterdam)</title><title level="j" type="abbreviated">J. Hydrol. : (Amst.)</title><idno type="ISSN">0022-1694</idno><imprint><date when="2005">2005</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Journal of hydrology : (Amsterdam)</title><title level="j" type="abbreviated">J. Hydrol. : (Amst.)</title><idno type="ISSN">0022-1694</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Devonshire England</term><term>England</term><term>climate</term><term>concentration</term><term>drainage basins</term><term>fluctuations</term><term>fractals</term><term>management</term><term>models</term><term>nitrates</term><term>nutrients</term><term>phosphates</term><term>prediction</term><term>river discharge</term><term>stream transport</term><term>streams</term><term>water quality</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Angleterre</term><term>Devonshire</term><term>Prévision</term><term>Qualité eau</term><term>Cours eau</term><term>Bassin versant</term><term>Climat</term><term>Fluctuation</term><term>Concentration</term><term>Fractal</term><term>Elément nutritif</term><term>Modèle</term><term>Gestion</term><term>Transport fluviatile</term><term>Débit rivière</term><term>Nitrate</term><term>Phosphate</term></keywords><keywords scheme="Wicri" type="topic" xml:lang="fr"><term>Climat</term><term>Gestion</term><term>Phosphate</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Analyses of daily water quality data from two streams draining a pair of small coastal catchments in South Devon, England reveal that what conventionally would be thought to show random noise, has a discernable structure and is clear evidence of process. Catchment and aquatic systems are non-equilibrium systems and climate drivers cause fluctuations in water quality both in terms of the concentrations of individual parameters and in the correlations between parameters. The data reveal nonlinear coupling at small scales and show evidence of fractal properties both of which may be evidence of self-organised phenomena at small scales in catchments and streams. These data show that: (a) water quality and catchment nutrient export data may be strongly aliased, and (b) there is a fundamental degree of indeterminacy underlying the data we can collect and the knowledge we can generate from the data. New techniques of data based modelling that use the data itself to define more parsimonious predictive models are needed because such an approach recognises the partial nature of our knowledge and requires adequate monitoring and adaptive management programs.</div></front></TEI><affiliations><list><country><li>Australie</li><li>Royaume-Uni</li></country></list><tree><country name="Australie"><noRegion><name sortKey="Harris, Graham" sort="Harris, Graham" uniqKey="Harris G" first="Graham" last="Harris">Graham Harris</name></noRegion></country><country name="Royaume-Uni"><noRegion><name sortKey="Heathwaite, A L" sort="Heathwaite, A L" uniqKey="Heathwaite A" first="A. L." last="Heathwaite">A. L. Heathwaite</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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