Foxton Wastewater Treatment Plant Flow Normalisation Modelling

Transcription

1 Foxton Wastewater Treatment Plant Flow Normalisation Modelling (LEI, 2015:B5) Prepared for Horowhenua District Council Prepared by August 2015

2 Foxton Wastewater Treatment Plant Flow Normalisation Modelling (LEI, 2015:B5) Horowhenua District Council This report has been prepared for the Horowhenua District Council by Lowe Environmental Impact (LEI). No liability is accepted by this company or any employee or sub-consultant of this company with respect to its use by any other parties. Quality Assurance Statement Task Responsibility Signature Project Manager: Prepared by: Reviewed by: Approved for Issue by: Status: Hamish Lowe Philip Lake Hamish Lowe Hamish Lowe Final Prepared by: Lowe Environmental Impact P O Box 4467 Palmerston North 4462 Ref: Foxton-B5-flow_normalisation-modelling- FINAL.docx T [+64] Job No.: E office@lei.co.nz W Date: August 2015 Revision Status Version Date Author What Changed and Why 3 20/08/15 N/A Approved by HDC as final version 2 16/08/15 HL Internal review 1 13/08/15 PL Original internal draft

3 TABLE OF CONTENTS 1 EXECUTIVE SUMMARY INTRODUCTION Background Purpose Scope SUMMARY OF NORMALISATION METHODOLOGY Information Sources Nature of Model Input Data Assessments Normalisation Modelling Process INPUT DATA INTEGRITY REVIEW OUTCOMES Climate Data FWWTP Wastewater Inflow Data Turks Trade Waste Data WASTEWATER FLOW NORMALISATION MODELLING RESULTS Inflow Data Trend Analysis Baseflow and Domestic Flow Modelling Total Daily Inflow Modelling Modelling Extrapolation CONCLUSIONS General Flows REFERENCES... 18

4 1 EXECUTIVE SUMMARY Horowhenua District Council (HDC) operate the Foxton municipal wastewater treatment plant (FWWTP) on Matakarapa which is surrounded by Foxton Loop and the Whirokino Cut of the Manawatu River. The FWWTP discharge requires re-consenting with a commitment by HDC to implement land discharge instead of the current discharge directly to the surface waters of Foxton Loop which flows into the Manawatu Estuary. In order to progress the conceptual design phase of the FWWTP consenting process, the wastewater flow rates through the current system need to be understood and able to be predicted with reasonable certainty based on rainfall events and seasonality. To satisfy this requirement, a long term (20 year minimum) dataset of daily total wastewater inflow needs to be generated from actual daily meteorological conditions that closely matches and extends the available actual daily total inflow records; this report fulfils that requirement. This report determines the relationships between rainfall events and wastewater inflow rates, and provides calculated predictions of daily wastewater inflow rates. The flow normalisation model s predictions are then validated against the actual inflow data. Statistics of the model s inflow predictions are compared with statistics of actual FWWTP inflow data. The actual FWWTP total inflow data has been unreliable or blank for some periods of time since 1 January 2004, but overall about 9 years of reliable inflow data is available for FWWTP. It therefore is acceptable for validating the flow normalisation modelling predictions. The statistics for the best fit inflows generated by the flow normalisation modelling process for the entire period are presented in Table 1.1. Table 1.1: Best Fit Predicted Flow Rates (m 3 /d) Total Flows Dry Weather Flows Wet Weather Flows Range Mean 95P Range Mean 95P Range Mean 95P 580 3,802 1,307 1, ,157 1,095 1, ,802 1,376 2,053 Note: 1 95P means 95 th Percentile The overall r 2 correlation between the predicted and actual total inflows throughout was The differences between the predicted and actual average daily flows and total monthly flows were between 5% underestimation and 9.6% overestimation when assessed on a monthly scale. The flow normalisation model overestimated the annual averages for daily, monthly, and annual flows by 1% or less. The values presented in this report for total daily wastewater flows are valid for minimal changes to the wastewater sources and population base of Foxton, but will require adjustment for forecasting and design review purposes if significant changes to Turks trade wastes or Foxton s population are to be accounted for. Any improvements to the reticulation system integrity to restrict stormwater inflow and groundwater infiltration (I & I) may also help to reduce the storm inflows and seasonally elevated winter inflows; the flow normalisation model would also require adjustment to match these reductions in I & I. The flow normalisation modelling predictions are suitable for use as the synthetic 20 + year dataset representing the FWWTP daily inflow component of the input data to be used for modelling the discharge and storage scenarios (see LIE, 2015:C1). The scenario modelling is necessary for Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 1

5 informing the FWWTP discharge conceptual design (LEI, 2015:C7) and resource consenting; the discharge scenario outputs include the required land areas, application rates, application days per annum, and storage pond volumes. The flow normalisation data may also be useful as baseline flow data for the resource consent applications. Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 2

6 2 INTRODUCTION 2.1 Background Horowhenua District Council (HDC) operate the Foxton municipal wastewater treatment plant (FWWTP) on Matakarapa which is surrounded by Foxton Loop and the Whirokino Cut of the Manawatu River. A location figure is presented in Figure 2.1. Figure 2.1: Location Plan for FWWTP The FWWTP was originally constructed at this location in 1974, and it currently consists of three oxidation ponds with no mechanical assistance. Foxton s only trade waste customer is Turks Poultry (Turks); there are other commercial and small scale industrial sites within Foxton, but the remaining wastewater sources are primarily from the residential population of 2,643 according to the 2013 census, which has been slowly declining during previous census periods. The treated wastewater is currently discharged via a surface drain into the Foxton Loop to the west of the FWWTP. The FWWTP discharge requires re-consenting with a commitment by HDC to implement land discharge instead of the current discharge directly to the surface waters of Foxton Loop which flows into the Manawatu Estuary. In order to progress the conceptual design phase of the FWWTP consenting process, the wastewater flow rates through the current system need to be understood and able to be predicted Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 3

7 with reasonable certainty based on rainfall events and seasonality. To satisfy this requirement, a long term (20 year minimum) dataset of daily total wastewater inflow needs to be generated from actual daily meteorological conditions that closely matches and extends the available actual daily total inflow records; this report fulfils that requirement. 2.2 Purpose The purpose of this report is to generate a synthetic daily total wastewater inflow dataset for the FWWTP that covers a period of at least 20 years and closely matches the available actual total daily wastewater inflow data for FWWTP. The process of calculating synthetic inflow data from meteorological parameters is known as flow normalisation modelling. The outputs of the flow normalisation modelling are required to enable a series of discharge and storage scenarios to be reliably modelled for FWWTP. This report and the discharge scenarios inform the Conceptual Design (LEI, 2015:C7) report for the future land discharge system design and ultimately support the resource consent applications for the future of the FWWTP and its discharge systems. 2.3 Scope The scope of this report includes the following aspects of the FWWTP: Develop a mathematical model for predicting total daily wastewater inflows from relevant meteorological data; Quantify the stormwater inflow and groundwater infiltration (I & I) generated by rainfall events and seasonal changes in groundwater levels respectively; and Generate statistics of predicted inflow rates of wastewater received at FWWTP for at least a 20 year period. The general steps in the process of achieving this are as follows: Obtain actual daily rainfall, soil moisture deficit, and runoff data for the locality; Develop best fit mathematical relationships between historical FWWTP wastewater inflow data and meteorological data; Identify any uncertainties or clear outliers of historic FWWTP inflow monitoring data; Calculate daily wastewater base flow and total daily flow data for a 20 year period by developing a model that uses the established mathematical relationships; Prepare graphs of actual versus modelled data; Complete regression calculations of the matching rates between the predicted daily inflows and the actual flow data; Describe the methods used for determining the best fit relationships; Describe the calculations used to generate the 20 year predictions and their assumptions and/or rationale; and Generate statistics of the model s predicted inflows for comparison with the actual FWWTP inflow data statistics. Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 4

8 3 SUMMARY OF NORMALISATION METHODOLOGY 3.1 Information Sources HDC records were the original source of FWWTP inflow data. The FWWTP inflow meter is mounted on the rising main pipeline near the Stewart Street pump station and designed for an accuracy of +5%. Flow meter calibration is checked annually. Turks Poultry supplied their daily trade waste flow records to HDC. Daily climate data (rainfall, soil moisture deficit, and runoff) for the Levin meteorological station was obtained from NIWA s on-line climate database. Levin was the closest current NIWA weather station to Foxton; it also provided the longest continuous meteorological dataset for a wide range of meteorological parameters including soil moisture deficit. Table summarises the extent and key parameters of the various datasets that were relied upon in this report for describing the actual daily wastewater flow rates of the FWWTP and for calculating or validating the synthetic wastewater daily flow dataset. Data Type Climate data for Levin Wastewater inflow rate to FWWTP Turks trade waste flow rate Table 3.1.1: Dataset Summary Dataset Data Parameters Source Duration Frequency 01/01/93 Daily Total rainfall, soil moisture NIWA 30/04/15 deficit, and runoff 01/01/00 Daily Total daily inflow HDC 31/03/15 telemetry 28/11/09 16/04/15 Daily Total daily flow Turks Poultry telemetry 3.2 Nature of Model Input Data Assessments All datasets were assessed for any gaps or errors (extreme outliers were scrutinised for their likelihood of being errors instead of true outliers). Where minor data gaps were found, they were filled where possible by estimating likely values from adjacent days of data within the datasets or from corresponding data in related datasets. LEI s Design Parameter Summary (LEI, 2015:B6) provides monthly and annual flow statistics for FWWTP, and also describes the correlations between daily Turks trade waste flows and daily total FWWTP wastewater inflows. 3.3 Normalisation Modelling Process The first step in the normalisation process was to subtract the Turks trade waste flows from each day s total wastewater inflows entering the FWWTP for the period of 1 January 2010 to 31 March This created a daily domestic wastewater inflow dataset for FWWTP. The next step was to generate calculations that reasonably closely resembled the base flow variations of the FWWTP domestic flow data for The flow normalisation model calculated the predicted base flow by adding an amount of additional inflow per mm of 30 day average rainfall to a set minimum total daily flow, and adding an amount of inflow per mm of 10-day average rainfall and 30-day average rainfall when soil moisture deficit was less than 15 mm to Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 5

9 reflect seasonal groundwater infiltration and stormwater runoff rates. The model s scaling factors were varied until the best visual match of daily base flow predictions to the lowest actual daily domestic flow rates was achieved. After obtaining the best fit domestic base flow predictions for , a second set of iterations was followed to select the best visual fit of graphed actual domestic total flow and modelled total domestic flow data. The total domestic flow modelling calculations added daily flow volumes to the base flows to account for the short-term rainfall effects. The scale of increases in the peak flow rates was controlled by the scaling factors applied to rainfall totals, and these scaling factors were adjusted until the best visual match to the actual daily domestic FWWTP inflow data was achieved. Next, in order to account for the Turks trade waste flows, a uniform increase on each working day s inflow was added to the best fit predicted daily domestic inflows; this increase was a uniform 420 m 3 /d increase was added to every working day (weekends and public holidays were excluded by the calculator) to reflect the average working day contribution from Turks trade wastes. This resulted in calculations of the total daily wastewater inflows for FWWTP. The predicted and actual daily total wastewater flows were visually and statistically assessed for their match rates for Where conflicting or unrealistic actual flow data became apparent during this process, they were excluded from the actual FWWTP flow data that was to be used for the modelling validation assessments. Regression calculations of the correlation between the modelling predictions for total daily flows and the actual flow data were used to measure how closely the modelling was matching the actual flow data. The total flow normalisation model was then refined by repeating several iterations of adjusting the flow adjustment scaling factors used by the model and recalculating the regression factors until the highest r 2 values and closest matching monthly and annual total flows were obtained for Finally, upon obtaining the best fit for the flow data, the flow normalisation calculations were applied to daily meteorological data covering 1 January 1993 to 31 March Statistics of daily, monthly and annual flows were generated for the actual FWWTP flow data and the flow normalisation model s predicted flow data. These statistics were compared for their match rates between 1 January 2000 and 31 March 2015 when actual FWWTP flow data was available. Further adjustments to the modelling calculation methods were made until the match between the modelling predictions and the actual FWWTP flow data was optimised for Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 6

10 4 INPUT DATA INTEGRITY REVIEW OUTCOMES 4.1 Climate Data LEI s environmental data summary report (LEI, 2014:B1) found that NIWA s rainfall data for Levin was the best continuous up to date climate dataset for the Levin-Foxton area. There were no instances of missing daily rainfall, soil moisture deficit, or runoff data within the NIWA climate dataset for Levin from 1 January 1993 to 30 April FWWTP Wastewater Inflow Data A number of gaps were apparent in the HDC total daily wastewater inflow data where no daily total flow rate records were available. Some flow measurements immediately before or after these gaps were also clearly erroneous as they were well below 400 m 3 /day (the minimum was otherwise about 550 m 3 /day). In total, 301 days of total wastewater inflow data were blank or unrealistically low since 1 January 2000, but this reduced to 118 days after 11 October The date ranges for these wastewater inflow data gaps were as follows: 31 December 2002 to 12 January February 2003 to 24 February April 2003 to 21 April January 2004 to 7 February May 2004 to 11 May March 2005 to 8 April June 2005 to 11 October March 2010 to 28 March September 2010 to 1 November October 2011 to 17 November May 2012 to 7 June December 2012 to 2 January 2013 Figure presents a graph of the inflow data where the longest of these data gaps are obvious. Figure 4.2.1: Foxton WWTP Daily Inflow Data for Turks Trade Waste Data Occasional gaps are apparent in the daily Turks trade waste flow data where no daily total flow rate records were available. The clear regular cycle of increased flow rates during weekdays (and Saturdays during some months) enabled the identification of missed days. In total, 25 days of data were blank or unrealistically low, and were therefore filled or excluded from the dataset used for this project. These were as follows: 9 December June 2012 Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 7

11 14 and 23 September January May June September 2013 Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 8

12 5 WASTEWATER FLOW NORMALISATION MODELLING RESULTS 5.1 Inflow Data Trend Analysis Figure below presents wastewater inflow data for where the weekly and seasonal cycles are apparent for each of the total daily wastewater inflows to the FWWTP and the Turks trade waste flows. Figure 5.1.1: Daily Total FWWTP Inflows and Daily Total Turks Trade Waste Flows for Figure presents the daily domestic inflows to the FWWTP (calculated by subtracting the daily Turks trade waste flows from the FWWTP total daily wastewater inflows) and daily rainfall data for Levin for Figure 5.1.2: Daily Domestic FWWTP Inflows and Levin Rainfall for Rainfall does not appear to account for all peak domestic flows which can be up to 1-2,000 m 3 /d higher than adjacent days; some of these large inflow spikes might be caused by unusual commercial inputs from a contributor other than Turks Poultry. Clearances of reticulation blockages and erroneous readings may also be causing some of these unusually high peaks. Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 9

13 5.2 Baseflow and Domestic Flow Modelling Figure shows baseflow modelling predictions against actual daily domestic FWWTP inflows for The match rate of predicted base flow with the lowest actual domestic flows was generally good for January 2010 to June 2012 and since June Figure 5.2.1: Predicted Base Flow and Actual FWWTP Domestic Flow for The match between modelling of domestic flows and actual domestic flows during is shown in Figure below. The match rate of predicted and actual daily domestic flow was particularly good for January 2010 to June 2012 and June 2013 to October During November 2014 through to March 2015 the actual FWWTP total inflows remained higher than usual between storm events instead of decreasing in response to the seasonally drier conditions. Figure 5.2.2: Predicted and Actual FWWTP Daily Domestic Flows for Total Daily Inflow Modelling After factoring in the daily Turks trade waste flows, the match between modelling of total flows and actual total FWWTP wastewater inflows is shown in Figure below. The match rate appears to be good for most of the dataset except for November 2014 through to March 2015 when the actual FWWTP total inflows remained higher than usual instead of decreasing in response to the seasonally drier conditions. This discrepancy between the modelled and actual total daily inflows is largely a consequential carry-over from the poorer match rate of the domestic flow modelling predictions. Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 10

14 Figure 5.3.1: Predicted and Actual FWWTP Total Daily Flows for A closer view of the data is presented in Figure below. This clearly shows good matches of the model s predicted daily total flows with the actual FWWTP total daily inflow s weekly trade waste cycles, seasonal cycles, and peak inflows generated by rainfall events. Figure 5.3.2: Predicted and Actual FWWTP Total Daily Flows for The average r 2 correlation between the predicted and actual total inflows throughout was It was lowest at 0.33 for June to December 2012; for the remainder of the datasets the r 2 correlation was between 0.56 and 0.68, with an average of Table below presents the actual and predicted average total daily inflows for each month of Table 5.3.1: Predicted and Actual Mean FWWTP Wastewater Inflows for Mean Daily Inflow (m 3 /d) Difference Between Predictions & Actual Month Actual Predicted m 3 /d % January 1,125 1, % February 1,082 1, % March 1,101 1, % April 1,120 1, % May 1,263 1, % June 1,469 1, % July 1,498 1, % August 1,545 1, % September 1,627 1, % October 1,342 1, % November 1,198 1, % December 1,184 1, % Average 1,296 1, % Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 11

15 The monthly comparisons in Table demonstrate that overall the flow normalisation predictions were very close to the actual average inflows. The flow normalisation model s predictions were least accurate for September, and this was due mainly to a lack of actual inflow data for 2010 and 2011, as well as the occurrence of some very large peak inflows in the actual inflow dataset that do not reflect the scale and timing of rainfall events. Consequently, the actual inflow data s highest measurements for September appear to be unreliable and unrealistically high. October data was also missing for 2010 and 2011, which would have affected the statistics for the actual flow data for this month. The actual inflow data for the second half of May 2012 was also blank, and the wetter than usual conditions during this particular month may have increased the average inflows to better match the modelling predictions. 5.4 Modelling Extrapolation Extrapolation of the flow normalisation calculations to predict daily total inflows for 1993 to 2015 is shown against the actual total daily FWWTP inflows for in Figure below. Figure 5.4.1: Predicted and Actual FWWTP Total Daily Flows for It is clear from Figure that the seasonal cycles and peaks of the actual daily total inflows have been very consistent since July This suggests that there have been minimal changes to the wastewater inflow volumes including those attributable to Turks trade wastes and I & I during the last 12 years. The flow normalisation model did not allow for any changes in these flow profiles or the population base of Foxton, and this has been shown to be appropriate for predicting the actual daily total inflows. However, the flow normalisation model will require adjustment for forecasting and design review purposes if significant changes to Turks trade wastes, Foxton s reticulation I & I, or Foxton s population are to be accounted for. Figure also highlights that the actual FWWTP total daily wastewater inflows during much of 2002 to July 2003 were well above the modelling predictions, highly variable, and out of character from the normal seasonal cycles. These features indicate that this section of the actual inflow data was either erroneous or strongly affected by factors other than meteorological and Turks trade wastes. It is possible that Feltex trade wastes were dominating, but this seems unlikely given that Feltex were operating until 2008 yet other years of flow data do not exhibit such elevations and high variability of total daily inflows. Figure presents a more detailed view of the datasets. This highlights that the poorest correlation occurred during February to June 2002 and November 2002 to June It also highlights that the actual total daily inflows for 2000 and 2001 were less variable than more recent years; the weekly cycle of reduced weekend flows was absent from the actual inflow data. Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 12

16 Figure 5.4.2: Predicted and Actual FWWTP Total Daily Flows for The closest match between predicted and actual total daily inflows occurred during ; the annual total flow difference was less than 1% (as shown in Table below), and the daily data generally matched well. Figure below presents a more detailed view of this timeframe. Figure 5.4.3: Predicted and Actual FWWTP Total Daily Flows for The actual FWWTP total inflow data has been unreliable or blank for some periods of time since 1 January 2004, but overall about 9 years of reliable inflow data is available for FWWTP. It therefore is acceptable for validating the flow normalisation modelling predictions. The overall r 2 correlation between the predicted and actual total inflows throughout was The differences between the predicted and actual average daily flows and total monthly flows were between 5% underestimation and 9.6% overestimation. The flow normalisation model overestimated the annual average for daily inflows by 1%. Table below presents the actual and predicted average total daily inflows for each month of Table 5.4.1: Mean FWWTP Wastewater Inflows ( flow data) Mean Daily Inflow (m 3 /d) Difference Between Predictions and Actual Total Inflows Month Actual Predicted m 3 /d % January 1,095 1, % February 1,128 1, % March 1,071 1, % April 1,042 1, % May 1,146 1, % June 1,342 1, % July 1,543 1, % August 1,638 1, % September 1,522 1, % Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 13

17 October 1,517 1, % November 1,259 1, % December 1,217 1, % Average 1,293 1, % Table below presents the actual and predicted average monthly total inflows for , while Table presents the actual and predicted annual total inflows for Table 5.4.2: Mean FWWTP Wastewater Inflows ( flow data) Mean Monthly Inflow (m 3 /month) Difference Between Predictions and Actual Total Inflows Month Actual Predicted m 3 /month % January 33,940 35,497 1, % February 31,875 32, % March 33,214 34,634 1, % April 31,253 32, % May 35,511 38,929 3, % June 40,249 42,532 2, % July 47,825 47, % August 50,767 48,096-2, % September 45,657 43,345-2, % October 47,015 45,848-1, % November 37,772 38, % December 37,738 37, % Average 39,401 39, % Table 5.4.3: Annual Total FWWTP Wastewater Inflows ( flow data) Difference Between Predictions and Annual Total Inflow (m 3 /y) Actual Total Inflows Year Actual Predicted m 3 /y % , ,124-23, % , ,146-36, % , , ,147-33% , , ,018-22% , ,870 3, % , ,460 56,897 15% , ,310 2, % , ,606-5, % , ,900 4, % , ,244 57,156 13% , ,502 14, % , ,541 20, % , ,155-30, % , ,053 26, % , ,595-28, % 2015 (Jan-Mar) 116,329 90,625-25,704-22% Annual Average 487, ,234-18, % Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 14

18 The worst matches between modelling predictions and actual annual total inflows occurred for the years of 2002, 2003, 2005, 2009, and The poor correlations for 2002 and 2003 annual total inflows were expected due to the visually poor match with the highly variable elevated actual inflow data. The model s apparent overestimation of the inflows for 2005 is primarily the consequence of the actual 2005 inflow dataset having no readings during 118 days of the wetter months of June to September. The model s apparent overestimation of the inflows for 2009 reflects the actual inflow dataset s notable lack of significant seasonal inflow increases during the wetter months of The reasons for this change of trend during 2009 are unknown; this particular year s trends did not occur during any other years of actual inflow data. The model s apparent underestimation of the inflows for 2015 was expected due to the visually poor match with the elevated and less variable actual inflow data. After excluding all comparisons of annual total inflows for the worst matching years of 2002, 2003, 2005, 2009, and 2015 as well as which were previously noted as less variable than subsequent years, the difference between the average annual predicted and actual total inflows reduced to 902 m 3 /y or 0.2% overestimation. For comparison, the difference between the average annual predicted and actual total inflows for all of was 11,100 m 3 /y or 2.4% overestimation. This is almost the opposite of the difference when data is included. Table below presents the flow normalisation model s predicted average daily, monthly, and annual total inflows for the FWWTP during the entire meteorological dataset of 1 January 1993 to 31 March Table 5.4.4: Mean Predicted FWWTP Wastewater Inflows ( flow data) Month Mean Daily Inflow (m 3 /d) Mean Monthly Inflow Totals (m 3 /month) January 1,114 34,791 February 1,105 31,265 March 1,102 34,242 April 1,101 33,031 May 1,254 38,880 June 1,435 43,064 July 1,539 47,724 August 1,516 46,990 September 1,458 43,729 October 1,497 46,397 November 1,321 39,626 December 1,251 38,767 Annual Average 1,307 39,875 m 3 /month (478,500 m 3 /y) The statistics for the best fit inflows generated by the flow normalisation modelling process for the entire period are presented in Table Table 5.4.4: Best Fit Predicted Flow Rates (m 3 /d) Total Flows Dry Weather Flows Wet Weather Flows Range Mean 95P Range Mean 95P Range Mean 95P 580 3,802 1,307 1, ,157 1,095 1, ,802 1,376 2,053 Note: 1 95P means 95 th Percentile Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 15

19 6 CONCLUSIONS 6.1 General The actual FWWTP total inflow data has been unreliable or blank for some periods of time since 1 January 2004, but overall about 9 years of reliable inflow data is available for FWWTP. It therefore is acceptable for validating the flow normalisation modelling predictions. The flow normalisation modelling predictions are suitable for use as the synthetic 20 + year dataset representing the FWWTP daily inflow component of the input data to be used for modelling the discharge and storage scenarios (see LEI, 2015:C1). The scenario modelling is necessary for informing the FWWTP discharge conceptual design (LEI, 2015:C7) and resource consenting; the discharge scenario outputs include the required land areas, application rates, application days per annum, and storage pond volumes. The flow normalisation data may also be useful as baseline flow data for the resource consent applications. The values presented in this report for total daily wastewater flows are valid for minimal changes to the wastewater sources and population base of Foxton, but will require adjustment for forecasting and design review purposes if significant changes to Turks trade wastes or Foxton s population are to be accounted for. Any improvements to the reticulation system integrity to restrict I & I may also help to reduce the storm inflows and seasonally elevated winter inflows; the flow normalisation model would also require adjustment to match these reductions in I & I. 6.2 Flows Table below presents the mean daily, monthly and annual inflow values for the best-fit predicted inflow data set generated by the flow normalisation modelling for the period of 1 January 1993 to 31 March Table 6.2.1: Mean Normalised FWWTP Wastewater Inflows ( flow data) Month Mean Daily Inflow (m 3 /d) Mean Monthly Inflow Totals (m 3 /month) January 1,114 34,791 February 1,105 31,265 March 1,102 34,242 April 1,101 33,031 May 1,254 38,880 June 1,435 43,064 July 1,539 47,724 August 1,516 46,990 September 1,458 43,729 October 1,497 46,397 November 1,321 39,626 December 1,251 38,767 Average 1,307 39,875 m 3 /month (478,500 m 3 /y) The statistics for the best fit inflows generated by the flow normalisation modelling process for the entire period are presented in Table Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 16

20 Table 6.2.2: Best Fit Predicted Flow Rates (m 3 /d) Total Flows Dry Weather Flows Wet Weather Flows Range Mean 95P Range Mean 95P Range Mean 95P 580 3,802 1,307 1, ,157 1,095 1, ,802 1,376 2,053 Note: 1 95P means 95 th Percentile Historic flow data has been unreliable or blank for some periods of time, but overall about 9 years of reliable inflow data is available for FWWTP. It therefore is acceptable for validating the flow normalisation modelling predictions. The overall r 2 correlation between the predicted and actual total inflows throughout was The differences between the predicted and actual average daily flows and total monthly flows were between 5% underestimation and 9.6% overestimation when assessed on a monthly scale. The normalisation model overestimated the annual averages for daily, monthly, and annual flows by 1% or less. Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 17

21 7 REFERENCES Lowe Environmental Impact (2014:B1) Summary of Existing Environmental Data for Foxton WWTP Lowe Environmental Impact (2015:B6) Foxton WWTP Design Parameter Summary Lowe Environmental Impact (2015:C1) Foxton WWTP Discharge and Storage Scenarios Lowe Environmental Impact (2015:C7) Foxton WWTP Discharge Conceptual Design Horowhenua District Council - Foxton WWTP Flow Normalisation Modelling P a g e 18

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