A United Kingdom Lake Ecological Observatory Network

Lead Research Organisation: Lancaster University
Department Name: Lancaster Environment Centre


Lake systems play a fundamental role in storing and providing freshwater and food, in supporting recreation and in protecting species diversity. However, the stability of these ecosystem services can be undermined by the increased demands society makes upon these systems and changes in atmospheric composition and lake water balance that arise through a societal-mediated changing climate. To safeguard against such loss of functioning there is in place legally-binding national and European directives that set stringent targets for water quality and biodiversity. Meeting these targets requires a detailed understanding of lake processes that in turn requires measurements at an appropriate temporal scale. Traditional monitoring, of at best weekly-fortnightly intervals, is sufficient to record seasonal change but cannot resolve the processes driving many aspects of lake function. To resolve these processes we need to 'hear every note in the full symphony of lake functioning', with such resolution only viable through semi-continuous measurement of parameters that are key reflectors of lake functioning. We are fortunate that deployed in eleven lakes across the UK, of different size, altitude, latitude and nutrient status, are basic systems automated to make such measurements, Automatic Water Quality Monitoring Stations (AWQMS). However at present, most buoys are restricted to a meteorological station and temperature measurements. A few have other probes to measure water quality, but these are subject to biofouling which could compromise the data. At present, the data are mainly downloaded by telemetry to the host-site via a range of procedures. Thus we are not utilising advances in data-logger-, computer- and sensor-technology to measure automatically at high frequency and 'hear the full symphony'. We propose to change this by installing stable, state-of-the-art sensor technology, with mechanical devices to minimise biofouling. Further, we will maximise the value of generating this high frequency data by linking together the lakes in a sensor network to deliver quality-controlled data onto the internet for analysis by project partners, the wider scientific community and the general public. Such infrastructure investment needs to reflect the need for high quality measurement from science-driven agendas. We will demonstrate such a network supports these agendas through the following projects: DST1: Real-time forecasting of lake behaviour: We will incorporate the real-time data available from the sensor network into a forecast system for lake phytoplankton behaviour and, in particular, to provide warning for the onset of phytoplankton blooms. DST2: The effect of meteorology on the fate of carbon within lakes: We will track pool and flux variability of dissolved carbon dioxide over daily to seasonal time scales. By relating these measurements to meteorological and within-lake physico-chemical measurements within and between sites we are better equipped to define critical controls on the lake carbon cycle. DST3: The level of regional coherence in sub-seasonal timescales: Lakes can show a regionally coherent response e.g. strong links exist between air and surface water temperature; large-scale weather patterns such as the position of north wall of the Gulf Stream have also been shown to influence directly the regional coherence of lakes. Use of high resolution data to examine coherence in lake temperatures has just begun but as yet no-one has investigated coherence of biological, chemical or wider physical variables on these short time-scales, an approach which is viable through this network. In summary, this sensor network of AWQMSs, offering detail of observation through high resolution data generation and the new instrumentation will demonstrate not only the value of observing the environment remotely and in detail, but the benefit from integration systems to offer real advances in environmental science.


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Description We have greatly improved the CEH Lake Ecology model PROTECH and have implemented a data assimilation framework for it that will allow it to be used for real time forecasting, for example to warn of potential algal bloom situations ahead of time. Initially this has been applied to the South Basin of Windermere and Esthwaite and should be later applied to other lakes in the Network
Exploitation Route This could become a routine forecasting tool for lakes, for example for use by the EA or SEPA.
Sectors Environment,Healthcare

Description Used in developing a Pathfinder project supported by Water Utilities
Sector Environment
Impact Types Policy & public services

Description Pathfinder Grant
Amount £17,042 (GBP)
Funding ID NE/N004817/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 06/2015 
End 07/2015
Title Lake Phytoplankton Forecasting Method 
Description Implementation of forecasting methodology based on an improved version of the PROTECH lake phytoplankton model 
Type Of Material Improvements to research infrastructure 
Year Produced 2018 
Provided To Others? Yes  
Impact Publication in Water Research (Page et al., 2018) 
Description Contact with Water Industry, Market Research for Forecasting Method funded by NERC Pathfinder Grant 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Industry/Business
Results and Impact Report provided for NERC Pathfinder Grant. Has potential to be developed into a marketable tool
Year(s) Of Engagement Activity 2017