Methods for Estimating Impacts of Rainfall on Bathing Water Quality Report on results for Saltcoats, Irvine, Fleetwood and Paignton

Methods for Estimating Impacts of Rainfall on Bathing Water Quality Report on results for Saltcoats, Irvine, Fleetwood and Paignton
UKLQ07
August 2008

EXECUTIVE SUMMARY
Introduction
Rainfall is acknowledged as having a primary influence in causing episodes of high faecal coliform concentration in bathing water, a principal indicator of poor water quality. This pollution occurs through two key pathways; increasing run-off from agricultural land and from combined sewer overflows (CSOs) spilling during times of heavy rainfall. This occurs throughout the UK, but in particular areas that experience higher rainfall, such as the west coast of Scotland, northwest England and Northern Ireland.

A revised Bathing Water Directive (2006/7/EC, repealing current Directive 76/160/EEC), came into force on 24 March 2006. With it comes new responsibilities from 2012 to provide bathers with information regarding potential risks to their health, including advance warnings of pollution incidents where practicable. As a result, interest is increasing throughout the UK in the development of techniques to predict poor bathing water quality to enable information to be provided to the public and therefore enhancing human health.

As a means of managing bathing beaches that are at risk of failing to meet the current EU Bathing Water Directive mandatory water quality standards, and in anticipation of the revised Directive, SEPA piloted a Scottish Government project to predict bathing water quality based on prior rainfall. These predictions are then displayed at electronic messaging signs at selected sites. Six sites in southwest Scotland were targeted in the 2003 bathing water season and ten from 2004 including two outwith the southwest area.

SNIFFER on behalf of SEPA and NIEA initiated this rain radar project on the premise that:

Existing rain-gauge prediction methods could potentially be improved by using rainfall radar data as an alternative or in addition to rain and river gauge data.
The revised Directive includes tighter faecal coliform standards, requiring increased accuracy of predictions.
Using rain radar may be more practical than installing telemetered rain and river gauges at new sites.
Using rain radar may be better for obtaining midday updates and projections than rain gauge networks

The aim of this study is to examine whether radar rainfall data can improve on rain-gauge methods of prediction of faecal coliform exceedances in bathing waters based on rain-gauge data. This research project is not aiming to compare and contrast radar and rain-gauge data directly, but to examine whether radar-derived thresholds could improve the prediction of faecal coliform concentration exceedances, which indicate poor bathing water quality.

Halcrow Group Limited was appointed by SNIFFER on 8 June 2007 to undertake this study. The original contract was to analyse two sites on the southwest coast of Scotland, Saltcoats and Irvine. Subsequently, this contract was extended to analyse two further sites in England, Fleetwood in the northwest and Paignton-Preston Sands in the southwest. This report is the culmination of the study and encompasses the findings of the complete project covering all four sites.

Methodology
Met Office radar data were obtained from three different radars to cover the four study areas. The radar data were provided in the format of rainfall intensities at a temporal resolution of 5 minutes and a spatial resolution, depending on site, of either one or two kilometres squared. A GIS software utility was developed for the project to construct the time-series of instantaneous rainfall values for each event and each catchment. This was used to evaluate the average rainfall over specified areas at a 5-minute intervals during multiple events. The end output was then a calculation of average rainfall across a number of grid cells within the areas specified in a shape file. Using this function, grid squares with centres located within the boundaries of a polygon area are included in the calculations.

The radar data were processed to derive rainfall averages over a variety of potential pollution source areas. In total, 11 pollution source areas were analysed for the 4 sites.

The rainfall depth data were distributed into different durations and plotted against faecal coliform count to identify thresholds. The thresholds of rainfall for a given duration were determined by fitting a best-fit line through the data. Where the best fit line crosses the 500 cfu/100 ml faecal coliform (FC) line a threshold rainfall depth is defined. This is referred to as an ‘optimising’ approach, which aims to achieve the maximum number of predictions of FC>500 and minimise ‘false alarms’ i.e. incorrect predictions of FC>500. This method differs from the method employed by SEPA using rain-gauge data, referred to as a ‘precautionary approach’ in which the principal aim is to correctly predict FC>500 events.

Revisions to the methodology made during the project included:

Improvements in the ascribed method of deriving the rainfall threshold from the data
Inclusion of a short duration to capture peak rainfall intensity and examine the influence this has on prediction. Hence for Paignton, where it was suspected that peak intensities might play a greater role due to the type of rainfall experienced, a 1-hour duration was incorporated as a ‘sliding’ duration – i.e. the peak 1-hour intensity in a given time period such as 24-hours.

Results
In order to best compare the rain-gauge results with the radar results a like-for-like comparison was made by comparing the data from both sources using the thresholds determined by the radar data (optimising) method. An overview of results is shown in the table below:

Site	Data Source	Number of correct predictions (rain gauge predictions use radar derived thresholds)	Percentage correct (%)
Saltcoats	Ashgrove rain gauge Saltcoats Rural Radar Saltcoats Urban Radar Saltcoats Radar aggregated	13/23 16/23 15/23 15/23	57% 70% 65% 65%
Irvine	Rain gauges (aggregated) Irvine Urban Radar Kilmarnock Urban Area Irvine Rural Area Irvine Radar aggregated	17/26 9/26 9/26 12/26 10/26	74% 35% 35% 46% 38%
Fleetwood	Rain gauges (aggregated) Wyre Urban Radar Wyre Rural Radar Lune Rural Radar Fleetwood radar aggregated	25/40 23/40 27/40 22/40 27/40	63% 58% 68% 68% 68%
Paignton	Rain gauges (aggregated) Torbay Radar Okham Radar Paignton radar aggregated	6/11 9/11 9/11 9/11	55% 82% 82% 82%

We wish to emphasise that the method employed in this project is relatively simplistic and purposefully aims to determine whether a ‘black box’ method in which rainfall is the only input and faecal coliform exceedance the only output is adequate for poor bathing water quality predictions. The results presented in this report can be improved by the use of more event data, including for example river flow, tide and wind and, therefore, opportunities exist to improve the results further in the future.

An analysis of radar data values against rain-gauge data for the Irvine urban area in which there is rain-gauge showed that the two measurement techniques gave similar results but that radar consistently recorded slightly higher rainfall than the Irvine rain-gauge. This finding is useful as we can state with confidence that radar is measuring rainfall quantities well and may be recording some events that the rain-gauge is missing.

Conclusions
Overall this study concludes that the rain radar performs well, particularly for smaller catchments in which it is shown to improve on the SEPA and Environment Agency methods using rain-gauges. The radar performs slightly less well for larger catchments. This is likely to be due to factors including peak intensities in radar data being ‘smoothed’ due to spatial averaging and additional complexities in catchment processes affecting the results rather than the quality of the radar data.

The fact that radar data has been shown to be at least as good as rain-gauges in predicting exceedances of faecal coliform concentrations means that a radar-based system could operate where no rain-gauges exist and may be preferable for cost and practicality reasons (a cost benefit analysis is a recommendation of the project). Furthermore, the ability to use forecast rainfall products from the Met Office Nimrod system up to 6-hours ahead mean that increased lead time can be achieved, provided the forecast quantities are reasonable predictions of actual quantities.

A further benefit of radar is that it can measure localised, convective rainfall which may occur in individual events or within frontal systems as ‘embedded convection’. At sites at which localised, high intensity rainfall is known to result in FC exceedances, the ability to analyse the peak intensity using radar, and have data available throughout the day, is an added advantage.

Other key conclusions from the study are as follows:

Where radar data can excel is during highly localised, convective rainfall events (for example, thunderstorms), or frontal events with embedded convective rainfall, which are missed by rain-gauges unless these are installed in a very dense network. At the Paignton site there was evidence that radar had measured a localised event that rain-gauges had missed.
For the Scottish sites, it appeared that that the rainfall events were predominantly widespread frontal systems crossing the western coast of the UK from the south-west or west resulting in relatively uniform rainfall, with the exception of orographic enhancement (rainfall totals increasing with ground altitude). For this reason the radar data did not manage to explain the rain-gauge method’s ‘misses’ at the Scottish sites. Similarly, the results at Fleetwood from the like-for-like comparison do not indicate that radar data have improved in identifying localised intense rainfall missed by rain-gauges.
Spatial averaging of radar rainfall data, where the radar pixels are averaged over polygon pollution-source areas, may result in ‘smoothing’ of localised intense rainfall events (for example, from convective rainfall). Spatial ‘smoothing’ is likely to be particularly significant for the larger pollution-source areas of Irvine rural, Wyre urban and rural and Lune rural. In general, the rain radar time-series for each of the pollution-source areas shown in Appendix 3, 4, 5 and 6 are fairly similar for each of the pollution-source areas.
Once the pollution-source area radar time series has been obtained this is accumulated into rain radar totals for different durations. This is effectively ‘temporal smoothing’. This ‘temporal smoothing’ results in a further loss of resolution in the data as the rainfall peaks shown in the radar time-series (Appendix 3, 4, 5 and 6) are accumulated into rain radar total depths for different durations. In an effort to assess the impact of this at the Paignton site, where peak intensities are likely to be influential in predicting FC levels, peak 1-hour rainfall was selected for analysis, having a sliding duration over a 24-hour period. In this case, no exceedances resulted from the hourly maxima that did not result in an exceedance of a longer duration, though up to 13mm in an hour were measured, indicating that this duration could be useful with a greater number of events to analyse.

Recommendations
Recommendations for improving the results and for further study are made at the end of this report. They are detailed under the following headings:

Number of events analysed
Use of further study areas
Radar data – spatial averaging
Radar data – fixed or ‘sliding’ duration
Radar quality
Forecast rainfall
‘Optimising’ versus ‘Precautionary’ approach
Data variability (Noise):

Antecedent wetness conditions;
Water quality samples – spatial variation;
Water quality samples – temporal resolution;
Water quality – relationship with river flows

Cost-benefit of implementing a radar-based operational system

Copies of this report are available from the Foundation, in electronic format on CDRom at £20.00 + VAT or hard copy at £50.00, less 20% to FWR members.

N.B. The report is available for download from the SNIFFER Website