Conventional water quality or effluent monitoring can generate enormous amounts of data. But that isn’t the desired end product, and this can lead to the “Data Rich but Information Poor” (DRIP) syndrome. What’s really required is the information that’s locked inside the data. To get this, organisations need expertise in statistics to identify appropriate data analysis methods. Unfortunately these skills may not be available, which means that costly data is not fully utilised, and new monitoring programmes may well be inefficient.
WRc’s Aardvark software (Analyse Any Routine Data; Visually Acquire Real Knowledge) is specifically designed to meet the needs of the non-statistician fulfilling a data analysis role. It provides easy access to a variety of statistical methods, and its graphical analyses can help answer many of the most common questions asked of routine environmental quality monitoring data, such as:
Is the quality getting better?…or worse?…or more variable?
Are changes gradual…or sudden?
Are we doing enough sampling…or too much?
If you would like to see a demonstration of the types of analyses that Aardvark can do then please take a look at either:
“ Riv_demo' uses examples from river monitoring and focuses mainly on time trends in data.
“ Eff_demo” uses effluent data and focuses on types of analysis particularly suited to compliance with specific environmental targets.