Challenges

While AQUASTAT is a key player in the world's understanding of water resources and uses, the work done is subject to quite some challenges.

Lack of complete time-series for the variables AQUASTAT holds makes it difficult to develop trends and increase the understanding of water in a socio-economic context. Data gaps in AQUASTAT are mainly attributable to the lack of information and capacity at national level and the lack of resources at all levels. While AQUASTAT performs some careful modelling to supplement country-level data, the team feels that it is important that most data continue to be directly reported by the country itself.

This lack of complete time series limits the interpretation possible from the AQUASTAT data holdings but—more maliciously—also leads to the recycling of data by other parties, sometimes attributing that same data to more recent years than the years the data is attributed to as reported by AQUASTAT. This often increases confusion, especially for national entities who think that this is a statistic modelled by AQUASTAT.

AQUASTAT prides itself in reporting the highest quality data possible. Unfortunately the best-quality data are frequently not satisfactory. AQUASTAT rejects a substantial amount of incoming data, and only accepts data that have passed several rounds of automated and manual quality assurance checks. And yet, regularly data updates invalidate prior series due to a methodology correction at a national level or due to the acknowledgement of a prior error, amongst others, thus reducing rather than increasing the amount of data available. This constant struggle requires endless revisiting of data and methodologies, of validation and calculation rules, of whatever knowledge has been inferred by data. This problem is exacerbated by the fact that countries use inconsistent terminology and different from international organizations, which in turn also have differences amongst them.

The problems of insufficient data and data of dubious accuracy paint a picture that, if interpreted as a final product, lead to incorrect assumptions, which is of course unacceptable. This is exacerbated by the impatience of those that rely on data updates in order to generate content, with apparent disregard as to the quality of the data itself. The perception of understanding is a malicious and pervasive situation that ultimately does substantial damage to the goal of all data dissemination exercises: clarification. Of course everybody has pressures and deadlines, which explains the behaviour of data-dependant entities. Since this situation is irresolvable, the only way to improve matters is to provide as good information as possible, and to be transparent about the limitations of how data can be interpreted. This is, of course, expensive. But while the cost of data gathering is substantial, the cost of policy derived from incorrect data is surely higher. This is why AQUASTAT always supports the intensification of data-strengthening initiatives within countries, even though it remains a drop in the ocean considering the data-related improvements needed globally.

Policy-makers need disagregated information to make scientifically justified decisions. However, the financial cost to provide substantially more information at disaggregated levels is something that requires investments of a different order of magnitude than what AQUASTAT currently counts on, and therefore national statistics continue to be the main focus. Unfortunately the national picture often hides problems occurring at sub-national units, and do not allow river-basin planning commissions to optimize the use of the resources available within their river basin. Therefore, AQUASTAT data remains a nesessary and important, but insufficient first step in the quantification of water management information.

Financial constraints are due to the global perception that "data are easy… just get them". This problem is shared by AQUASTAT's colleagues across the world, in national centres as well as other international agencies.

The problems associated with data collection and dissemination are systematic, no country is perfect, and neither is any international agency. It is only through frequent, honest, and timely two-way communication that data inaccuracies can be continuously identified and eliminated.