Combine and Share Essential Knowledge for Sustainable Water Management

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Neil Williamson
Figure 2. Algal blooms in a pond beside an old watermill.

How can we better comprehend and respond to sustainability challenges in the water domain? Operational water analysts around the world face this question every day.

Per_Andersson_Figure1
Adapted from Arheimer & Lindström2
Figure 1. The 5,300 largest dams in Sweden.

In Sweden, a key sustainability challenge for national water managers is to improve ecosystem health. The aim is for all water bodies to obtain “good status” as stipulated by the European Union (EU) Water Framework Directive regarding their capacity to support natural life, biodiversity, and legitimate water uses.1

 

The most prevalent problem for Swedish inland waters is physical alteration of the natural flow regime as a consequence of drainage, dredging, regulation, and thousands of dams (Figure 1). On average, 19 percent of the total runoff from the land surface to the sea is redistributed due to these extensive physical alterations.3  Other major problems include eutrophication (overabundance of nutrients leading to algal blooms, see Figure 2) and invasive species (e.g. the Zebra mussel that came to Sweden in the 1920s through international shipping).

 

To identify knowledge gaps and information needed to better respond to these challenges, the Swedish Meteorological and Hydrological Institute (SMHI) has held regular meetings with key regional water managers across the country since 2011. The meetings have gradually become more frequent (currently held once every month) and more operative (i.e. focusing on the concrete needs of practitioners). As a general response to water managers’ needs, SMHI developed a high-resolution numeric model simulating water and nutrient cycles across Sweden.4

One specific need that water managers identified was to better comprehend, monitor, and characterize the ecological status of Sweden’s numerous water bodies. Meaningful sampling requires precise timing of hydrological monitoring (e.g. the onset of the annual flow peak), which is difficult given the resources and number of water bodies involved. As a solution, SMHI constructed a spatially explicit and openly accessible, tailored forecasting tool based on the numeric model (Figure 3).3 An essential component in the tool’s development was the combining of the expertise of hydrologists, who provided forecasts, with that of aquatic ecologists, who identified critical flow conditions and thresholds against which to relate the forecasts. The tool is now used by regional government boards to target monitoring toward desired flow conditions.

Per_Andersson_Figure2
Adapted from Arheimer & Lindström2
Figure 1. The impact of flow regulations on the seasonal distribution of runoff from Sweden to the surrounding seas.

The open sharing of this tool increased the resolution of Swedish hydrological forecasts available to the public by a factor of 36, from 1,001 catchments to 36,693 catchments. During 2014, the tool was used about 60 times per day during an average weekday. Given that there are only 20 Swedish regional water management bodies, it seems likely that the open sharing of this publicly financed tool provides added value beyond its core audience.

 

A second need identified by water managers was to improve the effectiveness of strategies to reduce the nutrient pollution that causes eutrophication. As budgets are always limited, it is essential to target regions and sectors with the highest potential for downstream impact. The SMHI solution was to develop a scenario tool to assess the potential impact of remediation measures in different sectors and locations (Figure 4).6 Here, the expertise of hydrologists, water chemists, and web developers are combined to simulate water, nitrogen, and phosphorous cycles and visualize them interactively online. The tool provides the estimated baseline nutrient loads and source distribution (sector, location, and hydrography), as well as a simple function to assess the downstream impact of altered loads. Around half of the Swedish regional government boards used the tool to assist with planning eutrophication remediation measures.

 

Implementation of eutrophication remediation measures is typically very sensitive since it involves top-down regulation of, for example, agricultural fertilization and private sewage treatment facilities. Making the scenario tool openly accessible is a way to increase transparency for all stakeholders regarding the knowledge foundation on which regulation is based. We hope the open access can contribute to an improved understanding and acceptance of remediation measures. There is, however, also a risk that an over-reliance on the tool—which has a number of uncertainties (e.g. nutrient states)—could backfire if implemented nutrient reductions do not lead to desired downstream results.

Per_Andersson_Figure4
SMHI Vattenwebb
Figure 3. The HydroNu forecasting tool.5

How can these solution examples be generalized and applied on larger scales and in other areas? We think a key component is to make knowledge more openly available, e.g. through open data, open software, and open publications. Open data has been a hallmark of the United States government for a number of years, and with the creation of the EU INSPIRE directive in 2007, which looks to create an EU-wide data infrastructure for the sharing of environmental information by 2019, European datasets are gradually opening up more and more, inspiring innovative applications. Open software is by no means new, but it is increasingly used by national agencies and companies alike, speeding up service delivery across the globe. At the same time, the open publication of synthesized knowledge has increased exponentially in the last decade.7

SMHI is currently leading the SWITCH-ON initiative, which seeks to improve water research and management practices by developing, testing, and utilizing the information offered by open knowledge. SWITCH-ON provides a metadata portal of open datasets, aiming to make open data less scattered and easier to find. The initiative also provides a virtual laboratory for collaborative water research, aiming to improve transparency, repeatability, and error detection by using common protocols (specifying experimental design and quality assurance), versioned datasets and algorithms, as well as regular interaction. In addition, SWITCH-ON explores the potential advantages of open data for commercial applications within water management.

Per_Andersson_Figure5
SMHI Vattenwebb
Figure 4. The scenario tool to study eutrophication remediation measures in Sweden.6

To better comprehend and respond to sustainability challenges in the water domain, our Swedish experience suggests that sustainability initiatives should focus on: (i) essential knowledge (not marginal details, but the core needs of society); (ii) combining knowledge across disciplines and other boundaries; and (iii) sharing knowledge, not just in open publications, but also through open data, software, web tools, mobile apps, machine-to-machine interfaces, etc. We believe this approach could also be beneficial in other locations and scientific domains.

 

Acknowledgements: We thank the Swedish Government for funding the water management tools and the European Union for funding the SWITCH-ON project (grant agreement No. 603587).

 

Acknowledgements

This contribution is based on deliberations in the session ‘Water for all’ at the IARU Sustainability Science Congress 2014.

 

References

  1. The European Parliament and the Council of the European Union. Directive 2000/60/EG Of The European Parliament And Of The Council Of 23 October 2000 Establishing A Framework For Community Action In The Field Of Water Policy (2000).
  2. Svarwebb – Dammregister [online] (2015) http://vattenwebb.smhi.se/svarwebb/.
  3. Arheimer, B. and G. Lindström. Electricity vs Ecosystems – understanding and predicting hydropower impact on Swedish river flow, in ICWRS2014 364 (IAHS Press, Bologna, Italy, 2014): 313–319.
  4. Lindström, G. et al. Development and testing of the HYPE (Hydrological Predictions for the Environment) water quality model for different spatial scales. Hydrology Research 41 (2010): 295–319.
  5. Vattenwebb – Hydrologiskt nuläge [online] (2015) http://vattenwebb.smhi.se/hydronu/.
  6. Vattenwebb – Analys- och scenarioverktyg för övergödning i sötvatten [online] (2015) http://vattenwebb.smhi.se/scenario/.
  7. Redhead, C. Growth of Fully OA Journals Using a CC-BY License – OASPA. Open Access Scholarly Publishers Association [online] (2014) http://oaspa.org/growth-of-fully-oa-journals-using-a-cc-by-license/.