Dear all,

A reminder that the RSS Environmental Section Meeting will be holding a
meeting on Water Quality, in collaboration with the University of
Greenwich, on

Friday 21st March, 13:30 – 18:00

at

Room 063, Queen Anne Court, Greenwich Campus, University of Greenwich, London

(for further directions please see:
http://www2.gre.ac.uk/about/travel/greenwich)

The event is free and open to all; in order to book your free place,
please go to:

http://www.eventbrite.co.uk/e/rss-environmental-section-meeting-on-water-quality-in-collaboration-with-the-university-of-greenwich-tickets-10734427963

For further information about the event please contact Jordan Drinan at
[log in to unmask] or Adam Butler at [log in to unmask]

Programme:

13:30        Registration & refreshments

14:00        Professor Marian Scott (University of Glasgow)
Statistics of the aquatic environment.  What is on the horizon?

14:40        Ed Bramley (Environment Manager, Yorkshire Water)
        River quality modelling using Monte Carlo techniques

15:20        Thames Water
        To be confirmed

16:00        Refreshments

16:30        Robert Pitchers (Senior Microbiologist, WRc plc, Swindon) New
directions in assuring the microbiological quality of drinking water

17:10        Dr. Luigi Spezia (Biomathematics & Statistics Scotland,
Aberdeen)
        Markov switching autoregressive models and stream isotope dynamics

17:50        Final summing up

Abstracts:

* Marian Scott

Traditionally much environmental regulation has been “silo-based”, with
regulations based on single issue, environmental media or legal regime
components, such as bathing water quality, without recognizing that to
manage bathing water, one might need to also consider diffuse pollution in
catchment.   More encompassing regulations such as the EU Water Framework
Directive, require evaluation and reporting of the ecological status of a
water body based on chemistry, morphology and biology.  Traditional
monitoring programmes have been sparse in space and time (eg monthly
monitoring), and focussed on a single aspect, eg biota but new sensor
technology is generating increasingly large volumes of earth observation
data and challenging more traditional statistical monitoring strategies in
space and time. These evolutions in environmental regulation and
environmental monitoring mean that interactions in our environment should
be more easily recognised, and data linkage across a number of
environmental, social and political domains will become essential to
deliver a more holistic ecosystem view. This presentation will consider a
number of case studies illustrating some of these points.

* Ed Bramley

Over the last two decades, the quality of many of England rivers has
improved dramatically, due to significant investment by water companies in
what was an aging sewage treatment infrastructure.  New European
legislation, specifically the Water Framework Directive, is currently
driving further improvements in the sewage treatment infrastructure, and
this will continue for at least the next decade.

As the causes of poor water quality are complex, the costs of sewage
treatment are potentially large, and the combinations of improvements
myriad, it is important that a structured approach is taken to evaluating
the improvements required.

This presentation will explore the use made of Monte Carlo modelling
techniques used in the evaluation of water quality improvements, and will
cover both the modelling techniques and uses made of them, as well as the
underlying sampling and monitoring regimes.  It will highlight some of the
statistical challenges that are faced in this work, how these have been
addressed to date, and where future challenges still lie.

* Robert Pitchers

Under normal conditions, the risks to health attributed to harmful
micro-organisms in public supplies of drinking water, whilst never zero,
are generally too low to establish by epidemiological investigations. This
lack of sensitivity has made it difficult to reach conclusions about the
level of public health protection provided by water treatment, and to
assess the benefits that could be achieved from improving operational
practices. Quantitative microbial risk assessment (QMRA) provides an
alternative approach for estimating the probability of illness associated
with exposure to pathogens through specific routes of transmission that
would otherwise be difficult to determine through conventional health
surveillance schemes. My presentation will explore how QMRA is now being
used to support development of standards and strategies to ensure the
continued supply of safe drinking water, rather than rely on compliance
monitoring for protecting public health.

* Luigi Spezia

Markov switching autoregressive models (MSARMs) have been applied to
analyse the temporal dynamics and statistical characteristics of the time
series of two conservative water isotopes, deuterium and oxygen-18, in
daily stream water samples over two years in a small catchment in eastern
Scotland. MSARMs enabled us to explicitly account for the identified
non-linear, non-Normal and non-stationary isotope dynamics of both time
series. The hidden states of the Markov chain could also be associated
with meteorological and hydrological drivers identifying the short (event)
and longer-term (inter-event) transport mechanisms for both isotopes.

Inference was based on the Bayesian approach performed through Markov
Chain Monte Carlo algorithms, which also allowed us to deal with a high
rate of missing values. Although it is usually assumed that both isotopes
are conservative and exhibit similar dynamics, oxygen-18 showed somewhat
different time series characteristics. Both isotopes were best modelled
with two hidden states, but oxygen-18 demanded autoregressions of the
first order, whereas deuterium of the second. Moreover, both the dynamics
of observations and the hidden states of the two isotopes were explained
by two different sets of covariates. Covariates have been selected
stochastically by a new method that will be presented. The talk is based
on a joint work with Christian Birkel, Sarah Dunn, Roberta Paroli, Chris
Soulsby, and Doerthe Tetzlaff.




-- 
Biomathematics and Statistics Scotland (BioSS) is formally part of The
James Hutton Institute (JHI), a registered Scottish charity No. SC041796
and a company limited by guarantee No. SC374831

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