Statistical modelling of suspended sediment off Stonehaven

Research output: Contribution to conferencePoster

Abstract

Changes in suspended sediment concentration (SSC)
are important for both the physical and ecological
environment. One of the main impacts is on the
attenuation of light intensity with depth, which
affects phytoplankton and macrophyte primary
production, and the environment for visual
predators. However, detailed data on SSC are
relatively scarce, so both dynamic and statistical
models which may predict SSC from more readily
available data are potentially valuable.
We analysed a dataset of >400 turbidity profiles
collected at weekly intervals during 2007-2011 at
the Marine Scotland Science sampling site off
Stonehaven on the east of Scotland. We sought to
establish a statistical General Additive Model
(GAM) of SSC at a given altitude above the seabed
with explanatory variables being seabed depth, tidal,
wind, wave, and river outflow data. Alternative
models were assessed with Akaike's Information
Criterion to choose between the fits offered by
different models.
Our final model provided a highly significant fit
to the observed data from the main sampling site.
We then tested the model by applying it to
independent data collected at secondary sampling
sites in both shallower and deeper water in the
vicinity and showed that the model provided as
significant account of the SSC dynamics at these site
also.

Conference

ConferenceMarine Alliance for Science and Technology for Scotland: Annual Science Meeting
CountryUnited Kingdom
CityEdinburgh
Period27/08/1329/08/13

Fingerprint

Suspended sediments
Statistical Modeling
Sediment
Sampling
Turbidity
Oceanography
Additive Models
Phytoplankton
Light Intensity
Model
Choose
Rivers
Modeling
Water
Predict
Interval

Keywords

  • statistical modelling
  • suspended sediment
  • stonehaven

Cite this

McCaig, C. (2013). Statistical modelling of suspended sediment off Stonehaven. 1. Poster session presented at Marine Alliance for Science and Technology for Scotland: Annual Science Meeting, Edinburgh, United Kingdom.
McCaig, Chris. / Statistical modelling of suspended sediment off Stonehaven. Poster session presented at Marine Alliance for Science and Technology for Scotland: Annual Science Meeting, Edinburgh, United Kingdom.
@conference{3125e036b26249f7b9c645c99396379e,
title = "Statistical modelling of suspended sediment off Stonehaven",
abstract = "Changes in suspended sediment concentration (SSC)are important for both the physical and ecologicalenvironment. One of the main impacts is on theattenuation of light intensity with depth, whichaffects phytoplankton and macrophyte primaryproduction, and the environment for visualpredators. However, detailed data on SSC arerelatively scarce, so both dynamic and statisticalmodels which may predict SSC from more readilyavailable data are potentially valuable.We analysed a dataset of >400 turbidity profilescollected at weekly intervals during 2007-2011 atthe Marine Scotland Science sampling site offStonehaven on the east of Scotland. We sought toestablish a statistical General Additive Model(GAM) of SSC at a given altitude above the seabedwith explanatory variables being seabed depth, tidal,wind, wave, and river outflow data. Alternativemodels were assessed with Akaike's InformationCriterion to choose between the fits offered bydifferent models.Our final model provided a highly significant fitto the observed data from the main sampling site.We then tested the model by applying it toindependent data collected at secondary samplingsites in both shallower and deeper water in thevicinity and showed that the model provided assignificant account of the SSC dynamics at these sitealso.",
keywords = "statistical modelling, suspended sediment, stonehaven",
author = "Chris McCaig",
year = "2013",
month = "8",
language = "English",
pages = "1",
note = "Marine Alliance for Science and Technology for Scotland: Annual Science Meeting ; Conference date: 27-08-2013 Through 29-08-2013",

}

McCaig, C 2013, 'Statistical modelling of suspended sediment off Stonehaven' Marine Alliance for Science and Technology for Scotland: Annual Science Meeting, Edinburgh, United Kingdom, 27/08/13 - 29/08/13, pp. 1.

Statistical modelling of suspended sediment off Stonehaven. / McCaig, Chris.

2013. 1 Poster session presented at Marine Alliance for Science and Technology for Scotland: Annual Science Meeting, Edinburgh, United Kingdom.

Research output: Contribution to conferencePoster

TY - CONF

T1 - Statistical modelling of suspended sediment off Stonehaven

AU - McCaig, Chris

PY - 2013/8

Y1 - 2013/8

N2 - Changes in suspended sediment concentration (SSC)are important for both the physical and ecologicalenvironment. One of the main impacts is on theattenuation of light intensity with depth, whichaffects phytoplankton and macrophyte primaryproduction, and the environment for visualpredators. However, detailed data on SSC arerelatively scarce, so both dynamic and statisticalmodels which may predict SSC from more readilyavailable data are potentially valuable.We analysed a dataset of >400 turbidity profilescollected at weekly intervals during 2007-2011 atthe Marine Scotland Science sampling site offStonehaven on the east of Scotland. We sought toestablish a statistical General Additive Model(GAM) of SSC at a given altitude above the seabedwith explanatory variables being seabed depth, tidal,wind, wave, and river outflow data. Alternativemodels were assessed with Akaike's InformationCriterion to choose between the fits offered bydifferent models.Our final model provided a highly significant fitto the observed data from the main sampling site.We then tested the model by applying it toindependent data collected at secondary samplingsites in both shallower and deeper water in thevicinity and showed that the model provided assignificant account of the SSC dynamics at these sitealso.

AB - Changes in suspended sediment concentration (SSC)are important for both the physical and ecologicalenvironment. One of the main impacts is on theattenuation of light intensity with depth, whichaffects phytoplankton and macrophyte primaryproduction, and the environment for visualpredators. However, detailed data on SSC arerelatively scarce, so both dynamic and statisticalmodels which may predict SSC from more readilyavailable data are potentially valuable.We analysed a dataset of >400 turbidity profilescollected at weekly intervals during 2007-2011 atthe Marine Scotland Science sampling site offStonehaven on the east of Scotland. We sought toestablish a statistical General Additive Model(GAM) of SSC at a given altitude above the seabedwith explanatory variables being seabed depth, tidal,wind, wave, and river outflow data. Alternativemodels were assessed with Akaike's InformationCriterion to choose between the fits offered bydifferent models.Our final model provided a highly significant fitto the observed data from the main sampling site.We then tested the model by applying it toindependent data collected at secondary samplingsites in both shallower and deeper water in thevicinity and showed that the model provided assignificant account of the SSC dynamics at these sitealso.

KW - statistical modelling

KW - suspended sediment

KW - stonehaven

UR - http://www.masts.ac.uk/annual-science-meeting/

UR - http://www.masts.ac.uk/

M3 - Poster

SP - 1

ER -

McCaig C. Statistical modelling of suspended sediment off Stonehaven. 2013. Poster session presented at Marine Alliance for Science and Technology for Scotland: Annual Science Meeting, Edinburgh, United Kingdom.