The need to carry out monitoring = collecting data - is emphasised both in the legal text of the WFD and in the supporting Guidance Documents. Existing data are needed to characterise and assess status of water bodies and new data are needed to verify or to follow the development in that water body. Thus a lot of data collection is carried out to fulfil the requirements of the WFD – but how accessible are these data in practise and are there enough data to support modelling?
The question on how much data are required for modelling is classical. In the modelling community lack of data is often used as an ‘excuse’ for poor model performance. Similarly, lack of data is often by water managers used as a reason for not applying models. On the other hand, it is always possible to set up a model with whatever sparse available data, but the uncertainty of the model result might easily be far too high. Therefore, the question should be rephrased as: “Is the model prediction uncertainty small enough to be of any practical use in a water management context?” This question cannot be answered without considering the socio-economic context – that is how much is at stake economically and politically for stakeholders and decision makers. And this answer will vary from case to case.
There is a large diversity of data availability in river basins across Europe. For some data types like meteorological and river discharge data the coverage only varies moderately among river basins. When it comes to data on surface water quality and biology and on groundwater quality there are, however, very large differences. This difference appears to a large extent to reflect the seriousness of the pressures (population density, pollution, etc.); however, the water management traditions and the socio-economic policy priorities may also be important factors.
The level of complexity of modelling carried out in river basins appears in general to be proportional to the amount of data available. This may be because both the amount of data and the need for modelling to a large extent is driven by the level of pressure on the water resources, i.e. on the perceived water management problems. So maybe, at least in areas and domains with severe problems, the interaction between data and modelling is in fact larger than we think even if it many times may not be explicitly recognised by all involved actors.
The analysis therefore suggests that the larger problems at hand, the more data are available, and the more modelling studies have typically been carried out. It can therefore be concluded that data availability is seldom the largest constraint for not doing modelling. Analysis of Article 5 reports suggests that data availability in many cases may not be sufficient for all aspects of the coming WFD implementation. This implies that the level of modelling required to support the WFD implementation will be somewhat higher than what can be performed with the present data availability. So, although the present data availability appears to be adequate for some level of modelling, it may in many cases not be sufficient for the level of modelling required from a socio-economic (water management/WFD) point of view.
One question is whether data are actually being collected – the next crucial question is whether the collected data are stored efficiently and are easily accessible to all potential users.
Several European and International conventions such as the Aarhus Convention and the Inspire Directive prescribe free data accessibility. Besides the EC has developed a web portal ”WISE” for data collected in connection with the WFD. However, in addition to the data collected specifically for the WFD much more data are being collected in the river basins. These data that are useful for water management purpose can be difficult to access. The most important constraints in this respect are:
These bottlenecks represent considerable constraints in daily water management. But also in research the problems in getting data that are collected but not easily accessible – often requires a lot of effort both in terms of costs and hard work. In conclusion there still seems to be a large need for pan-European policies on making data collected for public funds free for all.
In addition to the availability and the accessibility of the data, the quality of the data is crucial. If data are not trustworthy they are not useful. Understanding the uncertainty in environmental data and systems is essential for making robust and wise water management decisions. Therefore, there is a need to characterise the data quality in terms of uncertainty and store such information as part of the data documentation.
Data requirement for research purposes vary tremendously depending on the objective of the research study. As the nature of research is to gain new knowledge, there will seldom be sufficient existing data on the particular research topic. If for instance the objective is to improve the understanding of water flow and reactive transport processes at a certain scale in a given area then it will most often be required to design a dedicated field monitoring programme just for the research project. If, on the other hand the research is focussing on water management issues and decision making there will often be sufficient data on the hydrological system, but instead it may be required to collect information on e.g. stakeholder views and behaviour.
In research many resources go into acquiring data for specific research projects – data that may only be available for individual projects. Thus there is a need to establish networks of representative river basins and hydrological observatories with data freely available for research purposes.