Michael Quinnell Senior Oceanographer 30 th June 2009 1
� Background to author � Introduction to review undertaken � Overview of numerical models � 5 identified points of concern � Summary � Any questions � Degree in Ocean Sciences � Post-graduate qualification in Coastal Engineering � 12yrs experience in commercial oceanography and marine geophysics � CMarSci, MIMarEST 2
� Review of Sewerage Scheme EIS Statements, 2006 & 2008, ‘Outfall Model Report’ sub-section � Review comments report submitted Dec 2008 � EIS presents a detailed investigation into a wide range of environmental impacts � Concern identified in 5 key study areas of Outfall Model Report affecting validity of predictions of effluent dispersion � Several numerical models used in EIS to simulate effluent dispersion 3
• • A computer program which gives a report of predicted A computer program which gives a report of predicted conditions, e.g. a conditions, e.g. a weather forecast weather forecast INPUT NUMERICAL MODEL OUTPUT > > > > > > > > (wind, temperature…) (software program) (weather forecast) • • Effluent dispersion models Effluent dispersion models • • Output: map of effluent dispersion Output: map of effluent dispersion • • Inputs: wind, current, effluent concentration, effluent volume Inputs: wind, current, effluent concentration, effluent volume • • Inputs and model therefore influence outputs Inputs and model therefore influence outputs • • Output of one model can be the input to another Output of one model can be the input to another • • IMPORTANT: Accuracy of model output IMPORTANT: Accuracy of model output is linked to accuracy of model is linked to accuracy of model inputs… inputs … 4
Point 1: Projected maximum outflow from the pipe Point 1: Projected maximum outflow from the pipe Average flow volumes v. Maximum flow volumes � 2008 report models used predicted average daily outflow volume from pipe (i.e. not max volume) � Models using average daily volume allow prediction during average pipe outflow conditions (i.e. an “average day”) � It would be more appropriate to model average & maximum outflow conditions � This could be more informative to determine if effluent would disperse onto bathing beaches when outflow volume is above average 5
Projected maximum outflow from the pipe Projected maximum outflow from the pipe “What if the plant fails scenario” � 2006 report undertook (at DCC’s request) modeling of effluent dispersion of plant failure event (i.e. maximum concentration of untreated effluent) � 2008 report omitted this modeling of plant failure event � How untreated effluent disperses during plant failure event not modeled therefore not known if would effluent disperse onto bathing beaches if plant fails 6
Projected maximum outflow from the pipe Projected maximum outflow from the pipe Remember: accuracy of output of a dispersion model is limited by accuracy of input… Conclusions: � EIS modeled average outflow volume � Therefore we cannot determine the impacts on beach, bathing area and shellfish area etc when above average outflow is experienced Recommendations: � Effluent dispersion modeling and particle tracking modeling should be re-run using maximum outflow volume and maximum concentration events (i.e. plant failure) and results re-assessed 7
Point 2: Plant design return period for extreme events Point 2: Plant design return period for extreme events How often is acceptable for effluent concentrations at a location to be surpassed?: Systems & structures are built with consideration to return period of � extreme conditions What are extreme conditions? When “the norm” is exceeded, maxima � What is the return period? 1yr, 10yrs, 25yrs? � What is the duration of the extreme? 1hr, 1day, 1week? � In context of effluent… � EIS report models used predicted and measured conditions, � e.g. currents, winds, rainfall, river outflow; plant operating efficiency, failure frequency, effluent volumes, concentrations But what return period does model dispersion results represent? 1yr, � 25yrs? Not stated in report 8
Plant design return period for extreme events Plant design return period for extreme events � How frequently effluent concentrations at a location are exceeded is important in determining acceptability of such extreme conditions � E.g. Qu. On how many occasions in a year is effluent disperse close to or on the bathing beaches? Ans. Not known Conclusions: � Return period of dispersion model results presented not known (to the reader) � Plant design return period for extreme events not known Recommendations: � Return period of dispersion model results presented and plant design return period for extreme events should be reported 9
Point 3: Calculation of projected flow volumes used in the Point 3: Calculation of projected flow volumes used in the models models Is the value of the maximum flow volume correct? � 1 (DWF) x 8800 (PE) x 0.225 (PE) = 1980m 3 /day � 1.5 (DWF) x 8800 (PE) x 0.225 (PE) = 2970m 3 /day � 3 (DWF) x 8800 (PE) x 0.225 (PE) = 5940m 3 /day 10
Calculation of projected flow volumes used in the models Calculation of projected flow volumes used in the models � 3DWF value was used in effluent dispersion and particle tracking models. If calculation is incorrect this represents under-estimation of 17% of projected flow � Remember: accuracy of output of a dispersion model is limited by accuracy of input… Conclusion: � Methodology of calculating 3DWF value is questioned Recommendation: � Accuracy of calculation of 3DWF value should be independently confirmed 11
Point 4: Determination of the T 90 coefficient used for bacterial Point 4: Determination of the T 90 coefficient used for bacterial dispersion in the effluent dispersion model dispersion in the effluent dispersion model What T 90 coefficient should be used?: � Recommended values of coefficient based on water clarity . � Outfall location categorized by general description - EIS report quotes coefficient used close to that recommended for “ coastal waters in the UK ” � Waters in Lough Foyle are shallow, surrounded by mud flats, frequently mod to high winds and waves. Dye detection survey report states “ very high ” concentrations � Therefore not considered representative of typical “ coastal waters in the UK ” >> a more conservative coefficient should be used 12
Determination of the T90 coefficient used for bacterial dispersion on Determination of the T90 coefficient used for bacterial dispersi in the effluent dispersion model in the effluent dispersion model � T 90 coefficient key in predicting extents of dispersion of effluent. If coefficient in model incorrect then effluent spreads further at high concentrations than presently predicted Remember: accuracy of output of a dispersion model is limited by accuracy of input… Conclusion: � Accuracy of T 90 coefficient for Lough is questioned Recommendation : � Accuracy of T 90 coefficient should be independently confirmed � Measured during current survey 13
Point 5: Interpretation of observed current, drogue, dye survey Point 5: Interpretation of observed current, drogue, dye survey data in validation of flow model data in validation of flow model Is current data input to effluent dispersion model accurate?: � Current flow directly affects where effluent is moved to >>directly affects accuracy of final effluent dispersion model � Methodology: (i) Obtain suitable current flow model (ii) Undertake current measurements (iii) Validate model by comparison and adjustment of results with current flow model (iv) Input current flow model results to effluent dispersion model (v) Obtain predicted movement of effluent 14
Interpretation of observed current, drogue, dye survey data in Interpretation of observed current, drogue, dye survey data in validation of flow model validation of flow model � EIS results of comparison reported “ very good correlation ” between measured and modeled current direction and duration data, and “ good correlation ” between measured and modeled current speed data during spring tides for all locations � Current flow model therefore not adjusted and input to final effluent dispersion model � Author believes poor correlation between measured data and model data � Author believes quality of current measurement program is poor (data quality, sampling rate, profiling) 15
� Tidal duration � Current speed � Current direction 16
� Tidal duration � Current speed � Current direction 17
� Tidal duration � Current speed � Current direction 18
� Tidal duration � Current speed � Current direction 19
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