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Inadmissible evidence: knowledge and prediction in land and riverscapes.

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Inadmissible evidence : knowledge and prediction in land and riverscapes. / Harris, Graham; Heathwaite, A. Louise.

In: Journal of Hydrology, Vol. 304, No. 1-4, 10.03.2005, p. 3-19.

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@article{75de6eedcf824b65a2152c10c8eb0b16,
title = "Inadmissible evidence: knowledge and prediction in land and riverscapes.",
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 non-linear 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.",
keywords = "Fractal, Catchments, Streams, Nutrients",
author = "Graham Harris and Heathwaite, {A. Louise}",
note = "Harris is external. Heathwaite collected data. Collaboration challenges way we handle 'noise' in water quality data and presents evidence to show these data have fractal properties demonstrating self-organisation in catchment processes RAE_import_type : Journal article RAE_uoa_type : Earth Systems and Environmental Sciences",
year = "2005",
month = mar,
day = "10",
doi = "10.1016/j.jhydrol.2004.07.020",
language = "English",
volume = "304",
pages = "3--19",
journal = "Journal of Hydrology",
issn = "0022-1694",
publisher = "Elsevier Science B.V.",
number = "1-4",

}

RIS

TY - JOUR

T1 - Inadmissible evidence

T2 - knowledge and prediction in land and riverscapes.

AU - Harris, Graham

AU - Heathwaite, A. Louise

N1 - Harris is external. Heathwaite collected data. Collaboration challenges way we handle 'noise' in water quality data and presents evidence to show these data have fractal properties demonstrating self-organisation in catchment processes RAE_import_type : Journal article RAE_uoa_type : Earth Systems and Environmental Sciences

PY - 2005/3/10

Y1 - 2005/3/10

N2 - 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 non-linear 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.

AB - 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 non-linear 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.

KW - Fractal

KW - Catchments

KW - Streams

KW - Nutrients

U2 - 10.1016/j.jhydrol.2004.07.020

DO - 10.1016/j.jhydrol.2004.07.020

M3 - Journal article

VL - 304

SP - 3

EP - 19

JO - Journal of Hydrology

JF - Journal of Hydrology

SN - 0022-1694

IS - 1-4

ER -