CIES Projects & Publications from 2001
Projects
Project
Identifying Risks to Good Ecological Status
Sponsor
Environment
Agency
Environment
Agency
Date
2009-2010
Total
£37,929
2008-2009
£45,000
Extension to Development of an Integrated
Classification, Diagnosis and Prediction System
relating pressures and ecological monitoring
elements based on Pattern Recognition and
Plausible Reasoning
Environment
Agency
2008
£30,000
Water Framework Directive River Basin
Planning Project
Environment
Agency
2008
£15,000
SNIFFER
2006-2007
£39,285
Development of an Integrated Classification
System for Rivers and Canals. Environment
Agency, R&D Project
Environment
Agency
2004-2007
£199,247
Scoping Study to Examine the Potential Use of
Artificial Intelligence Systems for the
Classification and Predictive Modelling of
Surface Freshwaters in Ecoregion 17 for the EC
Water Framewater Directive.
Joint EHS (N
Ireland) and
EPA (Rep of
Ireland)
2003
£27,550
Characterisation of Reference Conditions and
Testing of Topology of Rivers
EPA (Rep of
Ireland)
2003
£10,000
Application of Artificial Intelligence Techniques
for the Water Framework Directive
Environment
Agency
2003
£24,000
An Assessment of the Role of Mathematical
Modelling in the Implementation of the Water
Framework Directive in Ireland
EPA (Rep of
Ireland)
2003
£2,500
Analysis of Environmental Stress Data recorded
at River Quality Sites in England and Wales
during the 2000 Survey
Environment
Agency
2001-2003
£23,345
Development of a System for the Identification
of Source of Oil Spills on Inland Waters
Environment
Agency
2001-2003
£90,000
Assessment
of
river
nutrient
and
macroinvertebrate quality correlation in England
and Wales using artificial intelligence
techniques
Environment
Agency
2002
£4,830,
Further Development of an Integrated
Classification, Diagnostic & Prediction System.
Revision of BMWP scores
Refereed Journal Papers
Paisley M.F., Trigg D.J. & Walley W.J. (2010). Revision of the BMWP Score
System: Derivation of Present-only and Abundance-related WHPT Scores from Field
Data. In preparation.
MF Paisley, DJ Trigg & WJ Walley (2010). Revision of the BMWP Score System:
Site Type Variations and Scores for New Taxa. In preparation.
Paisley M.F. & Walley W.J. (2009). Identification of Macro-Invertebrate Taxa as
Indicators of Nutrient Enrichment in Rivers. Submitted to Ecological Informatics.
Dodkins I., Harrington T.J., Rippey B., Bradley C., Ni Chathian B., Kelly-Quinn M.,
McCarrigle M. and Trigg D.J. (2005). Developing an optimal river typology for
biological elements within the Water Framework Directive, Water Research 39. pp.
3479-3486. Elsevier.
O’Connor M.A. & Walley W.J. (2002). River Pollution Diagnostic System (RPDS) –
Computer-based Analysis and Visualisation for Bio-Monitoring Data. Water Science
and Technology 46, no 6, pp17-23.
Walley, W. J. & O’Connor, M. A. (2001). Unsupervised pattern recognition for the
interpretation of ecological data. Ecological Modelling 146, pp219-230.
Walley, W.J., Grbovic J., & Dzeroski S. (2001). A reappraisal of saprobic values and
indicator weights based on Slovenian river quality data. Water Research 35, no. 18,
pp4285-4292.
Technical Reports
Trigg D.J. & Paisley M.F. (2010). Identifying Risks to Good Ecological Status.
Environment Agency Technical Report. In preparation.
Paisley M.F., Trigg D.J., Martin R., Walley W.J., Andriaenssens V., Buxton R. and
O’Connor M. (2008) Refinement of AI-Based Systems for Diagnosing and Predicting
River Health. Technical Report EMC/WP06 077. Environment Agency, Bristol.
Paisley, M.F., D.J. Trigg & W.J. Walley (2007) Revision and Testing of BMWP
scores. Final report SNIFFER Project WFD72a. Edinburgh, SNIFFER. Available
from http://www.sniffer.org.uk/search.asp by searching under ‘WFD72A’.
Kelly-Quinn M., Bradley C., Dodkins I., Harrington T.J., Ni Chathian B., O'Connor
M.A., Rippey B. and Trigg D.J.
(2005) Water Framework Directive Characterisation of Reference conditions and Testing of Typology of Rivers.
Environmental Protection Agency Project 2002-W-LS-7 Final Report. ISBN 1 84095
162 1.
O’Connor M.A., Paisley M.F., Trigg D.J. and Walley W.J. (2005). Further
Development and Testing of Artificial Intelligence Systems for the Classification and
Diagnosis of River Quality Based on Biological and Environmental Data. Science
Report E1-056/S2, Environment Agency. ISBN 1 84432 368 4.
Martin RW, O’Connor MA and Walley WJ (2005). The Collection and Analysis of
Environmental Stresses Influencing Biological General Quality Assessment in 2000.
Science Report E1-114/TR, Environment Agency. ISBN 1 84432 340 4.
Buxton R & O’Connor MA (2003). Use of Pattern Recognition to Identify the Source
of an Oil Spill on an Inland Water, R&D Technical Report (E1-109/TR).
Walley WJ, Trigg DJ, Martin RW, Nikhade J, O’Connor MA and Paisley MF (2002).
Assessment of River Phosphorus and Nitrogen from Macroinvertebrate Data using
Artificial Intelligence Techniques. Technical Report to the Environment Agency.
Walley W.J., O'Connor M.A., Trigg D.J. and Martin R.W. (2002). Diagnosing and
Predicting River Health from Biological Survey Data using Pattern Recognition and
Plausible Reasoning. Environment Agency Technical Report E1-056/TR2, Water
Research Centre. ISBN 1 85705 816 X
Martin R.W. and Walley W.J. (2001). Distribution of Perceived Stresses in English
and Welsh Rivers based on the 1995 Survey: the quality of a preliminary data set.
Environment Agency Technical Report E126.
Conference Papers
Paisley M.F., Trigg DJ & Walley W.J. (2007). Application of Artificial Intelligence
Methods to Natural Resource Management. Presented at International Symposium
for Environmental Software Systems at IST-Africa (Information Society
Technologies – Africa) Conference, Maputo, Mozambique, 7-9 May.
Paisley MF & Trigg DJ. (2005). The Application of Artificial Intelligence to the
Diagnosis, Prediction and Classification of River Health from Biological and
Environmental Data.
Invited Talk, UK/Ireland Workshop on Ecological
Classification Systems, Belfast, January.
Paisley M.F., Walley W.J., Nikhade J. & Dils R. (2003). Identification of the Key
Biological Iindicators of Nutrient Enrichment in Rivers for use in
Predictive/Diagnostic Models. Proc 7th IWA Conf on Diffuse Pollution and Basin
Management, Dublin.
O'Connor, M. A. & Walley W. J. (2002). "A framework for computer-based data
analysis and visualisation by pattern recognition". 3rd Conference of the International
Society for Ecological Informatics, Rome, 2002.
Trigg, D. J. & Walley, W. J. (2002). "RPBBN: A Bayesian Belief Network for
Diagnosis and Prognosis of River Health". 3rd Conference of the International
Society for Ecological Informatics, Rome, 2002.
Buxton R & O’Connor MA (2002). A Comparison of three Prototype Expert
Systems, two using Information Theoretic techniques, the other using Bayesian
techniques, in the domain of Petrochemical Pollution Classification in Fresh Water
Courses. Accepted for presentation but not given.
O’Connor, M. A. & Walley, W. J. (2001) River Pollution Diagnostic System (RPDS)
– Computer-based Analysis and Visualisation for Bio-Monitoring Data. In: Conf.
Proc. Of the International Water Association 2nd World Water Congress, Berlin.
O’Connor, M. A. & Walley, W. J. (2001) A River Pollution Diagnostic System
(RPDS) for England and Wales. Int. Symp. On Environmental Software Systems,
Banff, Canada, May 2001.
Martin R.W. and Walley W.J. (2001) A River Biology Monitoring System (RBMS)
for English and Welsh Rivers. In Environmental Software Systems / Environmental
Informatics, Vol 4. ISBN 3-901882-14-6.
PhD Theses
Trigg D.J. (2004). The Development of an Expert System using Plausible Reasoning
for the Diagnosis and Prognosis of River Quality. PhD. Thesis, Staffordshire
University
O’Connor MA (2004). The Development of a Pattern Recognition and Data
Visualisation System for the Diagnosis of River Health from Biological and
Environmental Data. PhD. Thesis, Staffordshire University
Other Data Tasks
We have over 10 years’ experience of projects requiring large national river survey
datasets (EA, SEPA, NIEA, EPA (Ireland)). Frequently used by the EA and others
(eg Catchment Science Centre, University of Sheffield) to extract and manipulate data
for use in other projects – see references below. Typical tasks:
 Management, handling and manipulation of large datasets
 Collating data from a variety of sources
 Validation of biological, chemical and environmental parameters
 Validation of sampling site coordinates via GIS
 Spatial matching of biological and chemical sampling sites
 Database construction and design
Comber S, and Georges K. (2007) Tiered approach to the assessment of metal
compliance in surface waters: Extension report: Nickel.
Science Report
SC050054/SR1. Environment Agency, Bristol.
De Zwart D., Pemberton E., Posthuma L., Veal A., Wells C.. (2008). Understanding
ecological impacts in rivers in England and Wales and identifying their possible
causes: part 1, the effect and probable cause (EPC) method. Environment Agency
Science Report - SC030189/SR5.
Holzkämper A., Surridge B., Paetzold A., Kumar V., Lerner D.N., Maltby L.,
Wainwright J., Anderson C.W. and Harris R. (2008). A consistent framework for
knowledge integration to support integrated catchment management. Proceedings of
the 4th International Congress on Environmental Modelling and Software 7-10 July
2008.
Kapo K.E., Burton G.A., Pemberton E.. (2008). Understanding ecological impacts in
rivers in England and Wales and identifying their possible causes: part 2, the GIS
based weights of evidence/weighted logistic regression method. Environment Agency
Science Report - SC030189/SR6.
Kumar V., Holzkämper A., Surridge B., Rockett P.I., Niranjan M., Lerner D.N.
(2008). Bayesian challenges in integrated catchment modelling. Proceedings of the
4th International Congress on Environmental Modelling and Software 7-10 July 2008.