SMART Watershed Network

SMART Watershed Network

SMART Watershed Network

About Us

The SMART Watershed Network maintained by several Lancaster University projects, in collaboration with numerous other institutions in the UK and overseas, is a platform for evaluating the latest hydrological, climatic and water quality sensors and in parallel evaluating the latest dynamic models of the resultant high frequency data. We wish to show how such a network not only delivers fundamental research in extreme tropical and temperate environments, but also research that has impact with the international water and forestry sectors.

Full details of our ongoing NERC-funded research projects, of which these SMART watersheds are a fundamental part, can be found at the following websites:

Some example Lancaster University publications using SMART sensors and/or SMART models:

Kretzschmar, A., Tych, W., Chappell, N.A. and Beven, K.J. 2016. Reversing hydrology: quantifying the temporal aggregation effect of catchment rainfall estimation using sub-hourly data. Hydrology Research, 47: in press. DOI: 10.2166/nh.2015.076 view online.

Ockenden, M.C., Deasy, C.E., Benskin, C.McW.H., Benskin, K.J., Beven, K.J. et al. 2016. Changing climate and nutrient transfers: Evidence from high temporal resolution concentration-flow dynamics in headwater catchments. Science of the Total Environment, 548: 325-339.view online.

Jones, T.D., Chappell, N.A. and Tych, W. 2014. First dynamic model of dissolved organic carbon derived directly from high frequency observations through contiguous storms. Environmental Science & Technology, 48: 13289-13297. view online.

Jones, T.D. and Chappell, N.A. 2014. Streamflow and hydrogen ion interrelationships identified using Data-Based Mechanistic modelling of high frequency observations through contiguous storms. Hydrology Research, 45(6): 868-892. view online.

Kretzschmar, A., Tych, W., and Chappell, N.A. 2014. Reversing Hydrology: estimation of sub-hourly rainfall time-series from streamflow. Environmental Modelling and Software, 60: 290-301. doi: 10.1016/j.envsoft.2014.06.017 view online.

Leedal, D., Weerts, A.H., Smith, P.J. and Beven, K.J. 2013. Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales). Hydrology and Earth System Sciences, 17: 177-185.view online.

Chappell, N.A., Bonell, M., Barnes, C.J., and Tych, W. 2012. Tropical cyclone effects on rapid runoff responses: quantifying with new continuous-time transfer function models. In: Revisiting Experimental Catchment Studies in Forest Hydrology, Webb, A.A., Bonell, M. Bren, L. Lane, P.N.J., McGuire, D., Neary, D.G., Nettles, J., Scott, D.F., Stednik J. & Wang, Y. (eds) IAHS Publication 353, Wallingford, IAHS Press. 82-93. view online.

Chappell, N.A., and Tych, W. 2012. Identifying step changes in single streamflow and evaporation records due to forest cover change. Hydrological Processes, 26, 100-116 doi:10.1002/hyp.8115. view online.

Ockenden M.C. and Chappell, N.A. 2011. Identification of the dominant runoff pathways from the data-based mechanistic modelling of nested catchments in temperate UK. Journal of Hydrology, 402, 71-79.view online.

Taylor, C.J., Pedregal, D.J., Young, P.C. and Tych, W. 2007. Environmental time series analysis and forecasting with the Captain Toolbox. Environmental Modelling and Software, 22: 797-814. view online.

Lancaster University conference/workshop outputs using SMART sensors and/or SMART models:

Chappell, N.A., Jones, T., Young, P., and Krishnaswamy, J. 2015. Demonstrating value of fine-resolution optical data for minimising aliasing impacts on biogeochemical models of surface waters. Presentation in session B14D of the American Geophysical Union meeting AGU Fall Meeting 2015 in San Francisco 14-18 December 2015.

Jones, T., Chappell, N.A., Tych, W., and Bhalla, R.S., 2015. Importance of high-frequency chemistry for resolving hot moments in headwaters: a combined optical sensor and time-series modelling approach. Presentation in session B53H of the American Geophysical Union meeting AGU Fall Meeting 2015 in San Francisco 14-18 December 2015.

Chappell, N.A., Jones, T. and White, L. 2014. Quantifying & interpreting DOC & fDOM dynamics in streams using the first model to be derived directly from sub-hourly monitoring through contiguous storms. Presentation to the Sensors for Water Interest Group (SWIG) meeting Monitoring Organics at Hilton Glasgow Grosvenor Hotel 24th Sept 2014.

Chappell, N.A. and Jones, T. 2013. Flow path functioning identified from fundamental dynamics in sub-hourly non-conservative stream chemistry. Presentation in session H44B of the American Geophysical Union meeting AGU Fall Meeting 2013 in San Francisco 9-13 December 2013.

Chappell, N.A. and Jones, T. 2013. New data-based mechanistic methodology to quantify hydrological & biogeochemical recovery following forest disturbance using observations monitored from sub-hourly to decadal time-scales. Poster presentation in session H11D of the American Geophysical Union meeting AGU Fall Meeting 2013 in San Francisco 9-13 December 2013.

Chappell, N.A. and Jones, T. 2013. Modelling streamflow & water quality within Dwr Cymru Welsh Water headwaters using DBM. Presentation to the British Hydrological Society meeting Data-based mechanistic methods for hydrological modelling & forecasting: research and practice at Lancaster University 11th July 2013.

Jones, T. and Chappell, N.A. 2013. Spectrophotometry within the DURESS project: Sensor maintenance for DOC, TOC, turbidity and nitrate, and preliminary modelling of Llyn Brianne data. Presentation at the Second International Workshop on In-Situ Spectrophotometry, 8 May 2013, Lancaster University, UK