5. Validation

Almost always when measures are implemented to control cyanobacterial occurrence or cyanotoxin break-through there remains some degree of uncertainty whether or not they are adequately chosen and designed to achieve the target they are intended for. Validation is a periodic investigative activity to identify the effectiveness of a control measure. It is typically intensive when a system is initially constructed or rehabilitated and is not intended for day-to-day management.

Validation begins with considering data and information that already exist, e.g. from scientific literature, guidelines, regulations and their explanatory text, historical data, experience. Research on site, specific to the individual setting, is adequate for validation particularly where uncertainty is large as to whether or not a measure will “work” sufficiently well in this situation.

Examples for the validation of measures from catchment to drinking-water treatment are given below. They include limited and targeted specific experimental or monitoring programmes. These should be periodically repeated as adequate for each, but particularly after changes in the system were undertaken. Running intensified monitoring programmes during extreme blooms is particularly valuable for validation of the performance of control measures. Vice versa, follow-up investigations after an event such as a cyanobacterial bloom or occurrence of toxin in finished drinking-water will usually include validation of the whole system / Water Safety Plan.

Additional expertise may be necessary for some validation programmes. It may be useful to invite experts on board a Water Safety Plan team for such specific programmes.

An outcome of validation may be a change in a control measure or its monitoring system, or confirmation that it is (still) adequate to ensure safety from cyanotoxin occurrence.

Your validation activities should also be documented in your Water Safety Plan, i.e. in the worksheet for your entries provided by this decision support tool. With such documentation, you can demonstrate having observed your duties of due diligence towards the public surveillance agency responsible for your setting, and also towards journalists and the general public in case questions or incidents arise.

Measure or Method	Potential approach to its validation
Indicators for cyanobacterial occurrence – example
Turbidity or pigment fluorescence as indicators of cyanobacterial density	Validate whether signals reflect cyanobacterial occurrence sufficiently well in your specific setting by performing cell counts and/or biovolume determination. This may be different for different parts of the supply chain, e.g. for raw water and for filter outlets, and separate validation may be adequate.
Choice and efficacy of control measures in the catchment – example
Catchment management measures	Validate whether the measures implemented actually meet the targets set for phosphorus loading by running specific research programmes to determine the load, e.g. by sampling tributaries under normal conditions and during heavy precipitation or snowmelt events and modelling the P budget
Choice and efficacy of control measures in the waterbody – examples
Artificial mixing and/or biological measures to reduce cyanobacterial growth in a water-body	In situations where visual inspection indicates cyanobacteria might be increasing in spite of mixing, take a sample and determine their cell density and/or biovolume, e.g. through cell counting
Measures to control phosphorus release from water-body sediments	Monitor phosphorus concentrations over time to detect patterns that indicate the sediments to be the source and/or model the phosphorus budget to differentiate between internal and external loading
Choice and efficacy of control measures for offtake – examples
Minimum residence times in the underground	Validate assumptions made in planning and design through tracer test under the extremes of conditions expected
Choice of offtake depths to minimise intake of cyanobacteria	Measure depth profiles of cyanobacterial occurrence, e.g. by cell counts or in situ fluorescence probe, in a range of different situations of cyanobacterial occurrence and compare your plan for the selection of offtake depths to the findings
Scheme for clogging layer removal and pumping afterwards	Check redox conditions and cyanotoxin concentrations in water pumped from the artificial recharge system under selected extreme situations
Choice and efficacy of control measures in drinking-water treatment – examples
Pre-oxidation	evaluate amount of oxidant needed at minimum to ensure cyanotoxin released by cell lysis will be oxidised, even if the system is challenged by high levels of organic carbon, as is the case during a cyanobacterial bloom. For example, conduct jar tests with bloom material and the oxidising agent used in your treatment scheme, analysing dissolved cyanotoxin, or run a temporary sampling programme for the analysis of dissolved cyanotoxin when a heavy bloom occurs in your reservoir and challenges your system. Such data may result in a scheme for dosing oxidant in relation to some indicator of cyanobacterial cell density that proves most useful to you, e.g. pigment fluorescence, cell counts or chlorophyll-a concentration analysis in the raw water, or even visual inspection of the reservoir, and this indicator can then be used for operational monitoring in your system.
Filtration in drinking-water treatment	Evaluate situations of pronounced cell accumulation on filters for indication of cell lysis and break-through
Dosing of oxidant to remove or of powdered activated carbon (PAC) to bind dissolved cyanotoxins	evaluate amount needed at minimum to ensure cyanotoxin degradation / binding even in situations in which the system is challenged by high levels of competing organic carbon, as is the case during a cyanobacterial bloom. For example, conduct jar tests with bloom material and the oxidising agent or PAC used in your treatment scheme, analysing dissolved cyanotoxin, or run a temporary sampling programme for the analysis of dissolved cyanotoxin when a heavy bloom occurs in your reservoir and challenges your system. Such data may result in a scheme for dosing in relation to some indicator of cyanobacterial cell density that proves most useful to you, e.g. pigment fluorescence, cell counts or chlorophyll-a concentration analysis in the raw water, or even visual inspection of the reservoir, and this indicator can then be used for operational monitoring in your system.

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