Water for people.pdf - WHO Thailand Digital Repository

5 4 / S E T T I N G T H E S C E N ESigning Process: Indicators Mark the Waya country scale and orange on a regional scale (WSI 50–75percent). The hot spot of red colour (WSI >75 percent) in the WestCoast of the United States in the figure on grid cell scale has turnedinto an orange colour in the figures on country and regional scales.Comparison of the four spatial scales leads to the conclusion thatlarge-scale aggregations of the WSI result in too much informationloss. The grid cell is the optimal scale to detect the areas of waterstress in the world because it allows more detailed data to beshown rather than grouping all data together to produce anaverage.Thirdly, selection of the right temporal scale is important forindicator aggregation and presentation as well. For example, theavailability of water depends strongly on the seasons. A mean valuecalculated over one year can hide a shortage of water in dry periodsand floods during wet times. In this case a seasonal-based mean ora minimum and maximum value over a year will provide morerelevant information. The temporal scale of an indicator is alsodependent on the point in time and the period of data collection.For example, water-quality monitoring is often based on ameasurement frequency of once a month. Consequently,information on the minimum oxygen concentration in a water bodywill not be provided accurately by this measurement frequency. Theminimum oxygen level is however important for the survival anddevelopment of aquatic fauna.The last scale-related discussion point is the level ofaggregation of the data. During the process of indicator or indexdevelopment a trade-off has to be made between aggregationversus loss of detail. Which trade-off is made in a certain situationdepends on the aim, the user, the system under consideration,knowledge of the system, data availability and the availablefinancial resources. Too much detail can even lead to informationloss, as the overall picture fades and becomes less clear. The initialselection of indicators is scientifically based, but if the need ispolicy-driven, a trade-off between scientific completeness andsimplification for management will be inevitable.Figure 3.8 provides an interesting example (EEA, 2001) basedon an extensive knowledge and information base encompassingdifferent institutes and scientists in countries bordering the RhineRiver. Scientists have carried out studies in different regions onvarious time scales, looking into patterns, trends and datadistribution profiles in order to understand and monitor theprocesses taking place. Other scientists are undoubtedly interestedin the detailed information and in data interpretation. All thisinformation has been aggregated into just two indicators,representing the entire river basin, completely discarding spatialfeatures. The figure provides, however, a clear message todecision-makers and the public: oxygen content and biodiversitywere poor in the 1970s, but have greatly improved since. Scientistshave responsibility to ensure that the conclusions drawn from thefigure are correct, despite the simplifications and need to provideadditional information (e.g. benchmarks) which enable both decisionmakersand the public to classify the present condition in terms of‘good’, ‘acceptable ’or ‘poor’. In general, the search for the rightbalance between the policy aim of indicators and their scientificfoundation requires an ongoing dialogue between scientists andpolicy-makers in order to improve and focus the indicator set. Properdocumentation of the aggregation procedure and the original dataenables retrospective testing, verification of the approach andincreased transparency. While aggregation aims to reducemultidimensional information to a single dimension, visualization maypresent multidimensional information at a glance. Depending onwhat is to be visualized a specific design can be chosen (e.g. tables,diagrams, line charts and maps). Visualization techniques offerpowerful means for knowledge transfer and communication.It is essential to note that scale is a critical issue but it is verymuch linked to the issue of boundaries. Discrepancies betweennatural and administrative boundaries make indicator interpretationdifficult, especially since rivers may often serve as administrativeboundaries between countries or between provinces/states withincountries. So collecting water-associated data in two administrativeareas separated by a river often covers up the impact of the aquaticenvironment on health and risks, unless the data collected aresegregated for respective distances from the river.Figure 3.8: A time series of the oxygen concentration and living organismsin the Rhine River since 1900Number of species Oxygen concentration %180101900-160 19201989- 91995Porifeta1408Tricladida712010080604020Oxygenconcentration1955197119781986-1988001900 1955 1965 1975 1985 1995654321HirudineaCrustaceaMolluscaInsectaBryozoaThis figure provides a clear message to policy-makers and to the public. Althoughoxygen content and biodiversity were poor in the 1970s, they have since thenstrongly improved. This conclusion has been drawn from extensive data, which werethen aggregated into easily understandable indicators.Source: EEA, 2001.