![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/map2-e1457458793978.jpg?resize=652%2C800\")
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Site map (from Jones et al., 2014, Hydrol Res, 45.6, 868<\/a>)<\/p>\n Llyn Brianne dam and spillway<\/p>\n \/* INLINE WIDGET CSS *\/ LI3 – Nant-y-Craflwyn LI6 – Nant Esgair Garn LI7 – Nant Rhesfa LI8 – Trawsnant \/* INLINE WIDGET CSS *\/ Publications using SMART sensors\/models from Llyn Brianne watersheds: \/* INLINE WIDGET CSS *\/ Our Infrastructure and SMART Sensor Deployment Water quality box to house and protect equipment (e.g. autosampler, dataloggers, batteries) – LI8<\/p>\n Water samples collected using an ISCO autosampler to allow calibration of water quality sensors to laboratory measured values<\/p>\n Manifold to hold and protect water quality sensors in the stream – LI8<\/p>\n Trapezoidal flume (for accurate measurement of stream discharge), raingauge and tripod-mounted datalogger with solar panel – LI6<\/p>\n \/* INLINE WIDGET CSS *\/ S::CAN spectro::lyser smart sensor removed from\u00a0housing for cleaning – LI3<\/p>\n Automatic Weather Station – LI6<\/p>\n EXO2 multiparameter sonde removed from housing for cleaning – LI8<\/p>\n Dataloggers and sensor interfaces housed on water quality box door – LI8<\/p>\n \/* INLINE WIDGET CSS *\/ Data <\/p>\n The datasets for these four sites currently include:January 2013 – present: rainfall, streamflow, stream temperature, electrical conductivity, plus all AWS variables.January 2013 – August 2014: turbidity, nitrate-N, DOC, TOC, apparent & true colour, pH.Example data (right): First 6 months of 15-min sampled & calibrated DOC (mg\/L) from watersheds LI3-8 (8 Jan \u2013 25 Jun 13). Collected using the S::CAN spectro::lyser and con:nect interface with twice weekly manual cleaning of instrument lenses with 10% HCl. Rainfall for the period also shown in blue.Please contact us <\/a>if you are interested in using our datasets.<\/p>\n \/* INLINE WIDGET CSS *\/ Example Research Summary: \/* INLINE WIDGET CSS *\/ SMART Models at Llyn Brianne Rainfall time-series (blue) plus observed DOC (black) and simulated DOC (red) for all four basins for a period of three contiguous storms in 2013 <\/p>\n \/* INLINE WIDGET CSS *\/ The model identification routine, known as the Refined Instrumental Variable in Continuous Time, (RIVC) algorithm <\/a>is based on transfer functions, and gives high simulation efficiencies for these analyses with constrained uncertainty. The modelled water chemistry response and the hydrometric response display two separate response components, i.e. second-order dynamics, with a fast pathway (e.g. soil-water) and slow pathway (e.g. movement through underlying drift strata). The similarity of the model structures enables preliminary physical interpretation of the dynamic responses. For example, most DOC export at these sites was through the faster hydrometric pathway and was exhausted in the slower pathway, while as temperature increased from winter to spring there was increased delay between the initial hydrometric response and the response of the DOC load. This work has highlighted the critical need for high-frequency (sub-hourly) monitoring of water quality variables in order to avoid distortion of the true dynamics by models (‘temporal aliasing’).Full details of the modelling results and implications are given in Jones and Chappell (2014)<\/a> and Jones et al. (2014)<\/a>. <\/p>\n DOC load simulated from rainfall at LI3 shows a second-order response, with 56% of DOC delivery following a fast pathway, and 44% of response following a slow pathway.<\/p>\n \/* INLINE WIDGET CSS *\/ SMART Watersheds: Llyn Brianne SMART Watersheds: Llyn Brianne SMART Watersheds: Llyn Brianne SMART Watersheds: Llyn Brianne \/* INLINE WIDGET CSS *\/ #layers-widget-slide-23-408 { background-color: #444; background-repeat: no-repeat;background-position: center;background-image: url(‘http:\/\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/DSC_0416-e1457454761810.jpg’);} #layers-widget-slide-23-204 { background-color: #444; background-repeat: no-repeat;background-position: center;background-image: url(‘http:\/\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/DSC_0384-e1457454689668.jpg’);} #layers-widget-slide-23-726 { background-color: #444; background-repeat: no-repeat;background-position: center;background-image: url(‘http:\/\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/DSC_0552-e1457454865808.jpg’);} #layers-widget-slide-23-637 { background-color: #444; background-repeat: no-repeat;background-position: center;background-image: url(‘http:\/\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/DSC_9553-e1457454938162.jpg’);} Llyn Brianne […]<\/p>\n","protected":false},"author":479,"featured_media":0,"parent":34,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"builder.php","meta":{"footnotes":""},"class_list":["post-79","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/P9rr27-1h","jetpack_likes_enabled":true,"jetpack-related-posts":[],"_links":{"self":[{"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/pages\/79","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/users\/479"}],"replies":[{"embeddable":true,"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/comments?post=79"}],"version-history":[{"count":41,"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/pages\/79\/revisions"}],"predecessor-version":[{"id":2185,"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/pages\/79\/revisions\/2185"}],"up":[{"embeddable":true,"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/pages\/34"}],"wp:attachment":[{"href":"http:\/\/wp.lancs.ac.uk\/basin-network\/wp-json\/wp\/v2\/media?parent=79"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/DSCF2831.jpg?resize=1080%2C810\")
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\n #layers-widget-column-38-583 h5.heading a,#layers-widget-column-38-583h5.heading,#layers-widget-column-38-583div.excerpt,#layers-widget-column-38-583div.excerpt p{ color: #000000;}
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\n #layers-widget-column-38-350 h5.heading a,#layers-widget-column-38-350h5.heading,#layers-widget-column-38-350div.excerpt,#layers-widget-column-38-350div.excerpt p{ color: #000000;}<\/p>\n![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/conifer.jpg?resize=300%2C274\")
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tCoordinates: N 52\u00b0 08′ 32.0″, W 003\u00b0 44′ 02.0″Area: 81 haLand Cover: Coniferous plantation (Sitka Spruce dominant)Geology: Lower Palaeozoic shales, mudstones, greywackes and grits.Soils: 47% podzol, 48% gleysol,\u00a0 5% histosolMean Annual Precip: 2,100 mm (8 yr average, 2002-2010)SMART sensors: Campbell Scientific CR1000 with temperature, water level, turbidity, electrical conductivity and\u00a0pH sensors. S::CAN spectro::lyser\u00a0measuring turbidity, nitrate-N, DOC, TOC, apparent colour, true colour.SMART models: RIVC algorithm (Rainfall-hydrogen ion; Rainfall-DOC).Landowner: Natural Resources Wales<\/p>\n![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/grassland.jpg?resize=300%2C274\")
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tCoordinates:\u00a0N 52\u00b0 07\u2032 57.2\u2033, W 003\u00b0 43\u2032 19.8\u2033Area:\u00a069 haLand Cover:\u00a0GrasslandGeology:\u00a0Lower Palaeozoic shales, mudstones, greywackes and grits.Soils:\u00a045% podzol, 15% gleysol,\u00a0 40% histosolMean Annual Precip:\u00a02,100 mm (8 yr average, 2002-2010)SMART sensors:\u00a0Campbell Scientific CR1000\u00a0with temperature, water level, turbidity, electrical conductivity and\u00a0pH sensors.S::CAN spectro::lyser\u00a0measuring turbidity, nitrate-N, DOC, TOC, apparent colour, true colour. Automatic Weather Station (CR1000) measuring rainfall, temperature, incoming solar radiation, photosynthetically active radiation, relative humidity, wind speed, wind direction.SMART models: RIVC algorithm (Rainfall-hydrogen ion; Rainfall-DOC).Landowner: Mr Roger Davies<\/p>\n![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/LI7_square2.jpg?resize=300%2C282\")
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tCoordinates: N 52\u00b0 07′ 44.8″, W 003\u00b0 43′ 39.7″Area:\u00a069 haLand Cover: GrasslandGeology: Lower Palaeozoic shales, mudstones, greywackes and grits.Soils: 33% podzol, 18% gleysol,\u00a0 49% histosolMean Annual Precip: 2,100 mm (8 yr average, 2002-2010)SMART sensors: Campbell Scientific CR1000 with temperature, water level, turbidity, electrical conductivity and\u00a0pH sensors.S::CAN spectro::lyser\u00a0measuring turbidity, nitrate-N, DOC, TOC, apparent colour, true colour.EXO1 sonde measuring borehole pH, temperature, electrical conductivity, DO.SMART models: RIVC algorithm (Rainfall-hydrogen ion; Rainfall-DOC).Landowner: Mr Roger Davies<\/p>\n![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/04\/LI8-.jpg?resize=300%2C283\")
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tCoordinates:\u00a0N 52\u00b0 07\u2032 32.0\u2033, W 003\u00b0 44\u2032 50.7\u2033Area:\u00a0121 haLand Cover:\u00a0Coniferous plantation (Sitka Spruce dominant)Geology:\u00a0Lower Palaeozoic shales, mudstones, greywackes and grits.Soils:\u00a044% podzol, 9% gleysol,\u00a0 48% histosolMean Annual Precip:\u00a02,100 mm (8 yr average, 2002-2010)SMART sensors:\u00a0Campbell Scientific CR1000\u00a0with temperature, water level, turbidity, electrical conductivity and\u00a0pH sensors.S::CAN spectro::lyser\u00a0measuring turbidity, nitrate-N, DOC, TOC, apparent colour, true colour. EXO2 sonde measuring fluorescent dissolved organic matter (fDOM), blue-green algae, chlorophyll-a, dissolved oxygen, pH, turbidity, and oxidation reduction potential (ORP)SMART models: RIVC algorithm (Rainfall-hydrogen ion; Rainfall-DOC).Landowner: Mr Roger Davies<\/p>\n
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tJones, 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<\/a>.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<\/a>.Littlewood, L.G. 1989. The Dynamics of Acid Runoff from Moorland and Conifer Afforested Catchments Draining into Llyn Brianne, Wales. PhD Thesis, University of Wales.<\/p>\n
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tThe four sites have identical instrumentation housed in water quality boxes with in-stream protective manifolds. The following images show the infrastructure and sensor system set up:<\/p>\n![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/WQ-box2.jpg?resize=201%2C300\")
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tThe deployment of SMART sensors and subsequent SMART modelling at the Llyn Brianne sites has been an important aspect of the NERC-funded DURESS<\/a> project. This project brings together many institutions and disciplines to assess how biodiversity provides the ecosystem services on which people depend.The Lancaster University team are quantifying the link between distributed changes in catchment land-use and management, climate, river ecological variables and river biota for a range of physical characters, and at a range of scales.Three key questions are being addressed by the team using data obtained from SMART sensors and using SMART models:What are the causes of the long and short-term dynamics in water quality and biodiversity in upland rivers and how can they be quantified?What time-scales (minutes, days, seasons and decades) dominate the dynamics of river biodiversity and water quality for upland Welsh rivers, and what are the implications for sampling ecosystem services. What is the relative impact of climate characteristics (extremes, seasons etc) versus land-use characteristics on status and change in biodiversity, resilience and ecosystem services in upland rivers?<\/p>\n
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\tSMART model identification routines have been\u00a0applied to the high-frequency observations (recorded through contiguous storms)\u00a0from these four watersheds. The models\u00a0are able\u00a0to simulate the rapid dynamics observed in the\u00a0hydrometric\u00a0behaviour (rainfall-streamflow)\u00a0and in the water quality\u00a0behaviour (e.g. rainfall-H+ load and rainfall-DOC load). The latter\u00a0is the first\u00a0dynamic model of\u00a0stream DOC export from such high-frequency observations.\u00a0<\/p>\n![](\"https:\/\/i0.wp.com\/wp.lancs.ac.uk\/basin-network\/files\/2016\/03\/Model.jpg?resize=1080%2C578\")
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