AustralieFrV1, PascalFrancis, Curation, bibRecord, 001679

Inadmissible evidence: knowledge and prediction in land and riverscapes

Identifieur interne : 001679 ( PascalFrancis/Curation ); précédent : 001678; suivant : 001680

Inadmissible 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.

RBID : Pascal:05-0170659

Descripteurs français

Pascal (Inist)
- Angleterre, Devonshire, Prévision, Qualité eau, Cours eau, Bassin versant, Climat, Fluctuation, Concentration, Fractal, Elément nutritif, Modèle, Gestion, Transport fluviatile, Débit rivière, Nitrate, Phosphate.
Wicri :
- topic : Climat, Gestion, Phosphate.

English descriptors

KwdEn :
- Devonshire England, England, climate, concentration, drainage basins, fluctuations, fractals, management, models, nitrates, nutrients, phosphates, prediction, river discharge, stream transport, streams, water quality.

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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A08	`01`	`1`	`ENG`	`@1 Inadmissible evidence: knowledge and prediction in land and riverscapes`
A09	`01`	`1`	`ENG`	`@1 Nutrient mobility within river basins: a European perspective`
A11	`01`	`1`		`@1 HARRIS (Graham)`
A11	`02`	`1`		`@1 HEATHWAITE (A. L.)`
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A14	`01`			`@1 University of Tasmania @2 Sandy Bay, Hobart, Tasmania 7005 @3 AUS @Z 1 aut.`
A14	`02`			`@1 Centre for Sustainable Water Management, The Lancaster Environment Centre, Lancaster University @2 Lancaster LA1 4YQ @3 GBR @Z 2 aut.`
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C01	`01`		`ENG`	@0 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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C03	`11`	`2`	`SPA`	`@0 Nutriente @5 18`
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C03	`14`	`2`	`ENG`	`@0 stream transport @5 24`
C03	`14`	`2`	`SPA`	`@0 Transporte fluvial @5 24`
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Le document en format XML

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<term>fluctuations</term>
<term>fractals</term>
<term>management</term>
<term>models</term>
<term>nitrates</term>
<term>nutrients</term>
<term>phosphates</term>
<term>prediction</term>
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<term>Bassin versant</term>
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<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>
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<fC01 i1="01" l="ENG"><s0>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.</s0>
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<s5>08</s5>
</fC03>
<fC03 i1="05" i2="2" l="SPA"><s0>Curso agua</s0>
<s5>08</s5>
</fC03>
<fC03 i1="06" i2="2" l="FRE"><s0>Bassin versant</s0>
<s5>09</s5>
</fC03>
<fC03 i1="06" i2="2" l="ENG"><s0>drainage basins</s0>
<s5>09</s5>
</fC03>
<fC03 i1="06" i2="2" l="SPA"><s0>Cuenca</s0>
<s5>09</s5>
</fC03>
<fC03 i1="07" i2="2" l="FRE"><s0>Climat</s0>
<s5>12</s5>
</fC03>
<fC03 i1="07" i2="2" l="ENG"><s0>climate</s0>
<s5>12</s5>
</fC03>
<fC03 i1="07" i2="2" l="SPA"><s0>Clima</s0>
<s5>12</s5>
</fC03>
<fC03 i1="08" i2="2" l="FRE"><s0>Fluctuation</s0>
<s5>13</s5>
</fC03>
<fC03 i1="08" i2="2" l="ENG"><s0>fluctuations</s0>
<s5>13</s5>
</fC03>
<fC03 i1="08" i2="2" l="SPA"><s0>Fluctuación</s0>
<s5>13</s5>
</fC03>
<fC03 i1="09" i2="2" l="FRE"><s0>Concentration</s0>
<s5>14</s5>
</fC03>
<fC03 i1="09" i2="2" l="ENG"><s0>concentration</s0>
<s5>14</s5>
</fC03>
<fC03 i1="09" i2="2" l="SPA"><s0>Concentración</s0>
<s5>14</s5>
</fC03>
<fC03 i1="10" i2="2" l="FRE"><s0>Fractal</s0>
<s5>17</s5>
</fC03>
<fC03 i1="10" i2="2" l="ENG"><s0>fractals</s0>
<s5>17</s5>
</fC03>
<fC03 i1="10" i2="2" l="SPA"><s0>Fractal</s0>
<s5>17</s5>
</fC03>
<fC03 i1="11" i2="2" l="FRE"><s0>Elément nutritif</s0>
<s5>18</s5>
</fC03>
<fC03 i1="11" i2="2" l="ENG"><s0>nutrients</s0>
<s5>18</s5>
</fC03>
<fC03 i1="11" i2="2" l="SPA"><s0>Nutriente</s0>
<s5>18</s5>
</fC03>
<fC03 i1="12" i2="2" l="FRE"><s0>Modèle</s0>
<s5>20</s5>
</fC03>
<fC03 i1="12" i2="2" l="ENG"><s0>models</s0>
<s5>20</s5>
</fC03>
<fC03 i1="12" i2="2" l="SPA"><s0>Modelo</s0>
<s5>20</s5>
</fC03>
<fC03 i1="13" i2="2" l="FRE"><s0>Gestion</s0>
<s5>21</s5>
</fC03>
<fC03 i1="13" i2="2" l="ENG"><s0>management</s0>
<s5>21</s5>
</fC03>
<fC03 i1="13" i2="2" l="SPA"><s0>Gestión</s0>
<s5>21</s5>
</fC03>
<fC03 i1="14" i2="2" l="FRE"><s0>Transport fluviatile</s0>
<s5>24</s5>
</fC03>
<fC03 i1="14" i2="2" l="ENG"><s0>stream transport</s0>
<s5>24</s5>
</fC03>
<fC03 i1="14" i2="2" l="SPA"><s0>Transporte fluvial</s0>
<s5>24</s5>
</fC03>
<fC03 i1="15" i2="2" l="FRE"><s0>Débit rivière</s0>
<s5>25</s5>
</fC03>
<fC03 i1="15" i2="2" l="ENG"><s0>river discharge</s0>
<s5>25</s5>
</fC03>
<fC03 i1="15" i2="2" l="SPA"><s0>Caudal río</s0>
<s5>25</s5>
</fC03>
<fC03 i1="16" i2="2" l="FRE"><s0>Nitrate</s0>
<s5>61</s5>
</fC03>
<fC03 i1="16" i2="2" l="ENG"><s0>nitrates</s0>
<s5>61</s5>
</fC03>
<fC03 i1="16" i2="2" l="SPA"><s0>Nitrato</s0>
<s5>61</s5>
</fC03>
<fC03 i1="17" i2="2" l="FRE"><s0>Phosphate</s0>
<s5>62</s5>
</fC03>
<fC03 i1="17" i2="2" l="ENG"><s0>phosphates</s0>
<s5>62</s5>
</fC03>
<fC03 i1="17" i2="2" l="SPA"><s0>Fosfato</s0>
<s5>62</s5>
</fC03>
<fC06><s0>ILS</s0>
</fC06>
<fC07 i1="01" i2="2" l="FRE"><s0>Grande Bretagne</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="2" l="ENG"><s0>Great Britain</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="2" l="SPA"><s0>Gran Bretaña</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="02" i2="2" l="FRE"><s0>Royaume Uni</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="02" i2="2" l="ENG"><s0>United Kingdom</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="02" i2="2" l="SPA"><s0>Reino Unido</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="03" i2="2" l="FRE"><s0>Europe Ouest</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="03" i2="2" l="ENG"><s0>Western Europe</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="03" i2="2" l="SPA"><s0>Europa del Oeste</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="04" i2="2" l="FRE"><s0>Europe</s0>
</fC07>
<fC07 i1="04" i2="2" l="ENG"><s0>Europe</s0>
</fC07>
<fC07 i1="04" i2="2" l="SPA"><s0>Europa</s0>
</fC07>
<fN21><s1>115</s1>
</fN21>
<fN44 i1="01"><s1>PSI</s1>
</fN44>
<fN82><s1>PSI</s1>
</fN82>
</pA>
</standard>
</inist>
</record>

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   |texte=   Inadmissible evidence: knowledge and prediction in land and riverscapes
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	Serveur d'exploration sur les relations entre la France et l'Australie
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Serveur d'exploration sur les relations entre la France et l'Australie

Inadmissible evidence: knowledge and prediction in land and riverscapes

Inadmissible evidence: knowledge and prediction in land and riverscapes

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