Nutrient Pollution of Inland and Coastal Waters:

Science into Policy and Practice

Noctiluca tides Phaeocystis foam Microcystis bloom Caulerpa growth Green tides Fish kills Fishery closure NZ coast N Sea coast Baltic Sea Florida keys N Brittany Gulf of Mexico Chesapeake Bay

Algal bloom Fish Kill Hydrodictyon mats Cladophora mats Water closure Anabaena bloom Blue-green algae K&A Canal River Thames River Wye Bosherston Windsor Florida Everglades Lake Erie

• Nutrient enrichment of inland and coastal waters is a growing global problem with significant impacts on ecosystem and human health – a suite of UN and EU policies require that we reduce this loading

• Reducing nutrient loading to waters presents a significant challenge, raising complex questions about – the sources of enrichment within the landscape, – key priorities for effective policy and management

• Current policy relies on incomplete science evidence and is failing to address the problem, with substantial cost implications

The scale of the challenge in UK waters

Total N export (2000-2010) Total P export (2000-2010)

Typical riverine Typical riverine concentrations concentrations

1 – >20 mg N/l 0.01 – >2 mg P/l

2.17 TP kg / ha

2.10 TP kg / ha

1.67 TP kg / ha

2.16 TP kg / ha

1.67 TP kg / ha

TN (kg/ha) 0 – 2 3 – 4 5 – 8 9 – 16 17 – 32 33 – 64 65 – 128 > 128

0 – 0.1 0.1 – 0.2 0.2 – 0.4 0.4 – 0.8 0.8 – 1.6 3.2 – 6.4 6.4 – 12.8 > 12.8

TP (kg/ha)

The challenge for policy & practice

• Science evidence that informs process understanding is often: – generated at relatively small experimental scales,

– not directly scalable between systems or time periods.

• Stakeholders managing nutrient impacted systems have had to either: – fund the development of bespoke solutions for each catchment of interest

– use knowledge acquired from inadequate monitoring, or another catchment

– run models with conflicting outcomes, generating mistrust of the evidence

• To deliver effective support for policy and management we need to: – provide a holistic understanding of the nature, origins and scale of the problem

– develop physically-based models, transferable between systems and scales

– develop better mechanisms for KE between scientists and stakeholders

Developing a weight of evidence to underpin policy and management

• Improving the evidence base – High resolution monitoring of multiple stressors at

representative sites and scales: the UK research platform

• Targeting mitigation measures – Expert evaluation of the evidence base to target mitigation

• Implementing on-farm mitigation measures – Farmer engagement through workshops and

demonstrations – Advice delivery – Capital incentives

• Developing physically based modelling – Unravel complex responses to climate and land use change – Transfer understanding between systems and scales and

provide robust underpinning for policy and management

The UK Research Platform: Delivering science evidence for effective policy and management

High Res Research Catchments (9)

Demonstration Test Catchments (4)

CSF Enhanced Monitoring (8)

CSF Priority Catchments(71)

WCI Priority Catchments(6)

DP Priority Catchments (14)

The UK Research Platform: a tiered approach

15 min sensor data*, sub-daily, daily + storm sampling+ Source characterisation using novel approaches,

Targeted process based research

Monthly water chemistry*, Daily Q and routine

ecological monitoring

Weekly + storm sampling*, daily Q, sediment source fingerprinting, seasonal ecological monitoring

15 min sensor data*, daily + storm sampling+

Source characterisation, with ecological monitoring including structural and functional measures

71 CSF, 14 DPPC & 6 WCI Priority Catchments

Research catchments

4 DTC Catchments

8 Enhanced Monitoring Catchments

Targ

eted

ad

vice

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ap

ita

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ing

+ Complete range of chemical determinands * Limited range of chemical determinands

High resolution monitoring in the Research and DTC catchments

I. Quantitative measures of hydrological, hydrochemical and sedimentological flux using autosamplers, bankside analysers and novel telemetered sensor networks

II. Quantitative measures of ecological status in control vs. manipulated catchment

III. Hydrochemical and sedimentological

source characterisation using novel approaches

IV. In situ measurements of ecosystem functional responses to catchment manipulation

Photos credits: Reaney, Jones, Collins, Smith and Meteor Communications

Recognising sources of observational uncertainty in catchment research

• Spatial representativity – What is the appropriate scale at which to monitor? – Where should we sample within the water matrix? – How should we sample?

• Determinand representativity – Reliance on partial fraction data – Inferring ecosystem responses from physico-chemical data – Measuring ecosystem functional and structural responses

• Sample stability and representativity

• Data quality following sample storage and analysis

• Sensor network and remote monitoring representativity – Instrumental degradation – Sensor drift and re-calibration – Lack of technological capacity for non-solute parameters

• Temporal representativity – How frequently should we sample? – Is temporal representativity linked to spatial scale? – Using simple indices to generate high frequency data from low frequency observations – Using simple indices to generate total catchment response from partial fraction observational data

How reliable are sensors in action?

NH4-N (blue), Q (red) at Brixton Deverill, Hampshire Avon DTC

Sensor miscalibration, drift and drop outs

How reliable are sensors in action?

TP sensor (Blue) and lab (Green) at Brixton Deverill, Hampshire Avon DTC

Sensor drop outs, underestimation of peak concentrations

TP (

mg

/l)

TP

(m

g/l

)

TP

(m

g/l

)

How reliable are sensors in action?

Turbidity at Prior’s Farm, River Sem, Hampshire Avon DTC

Bubbles! 1200

1000

800

600

400

200

0 19/09/10 07/04/11 24/10/11 11/05/12 27/11/12 15/06/13 01/01/14

Turb

idity (

NTU

)

Science potential: investigating uncertainties using sensor data from the platform

Data from the Brixton Deverill high spec station, Wylye catchment, Hampshire Avon DTC, 2012-13

The way forward • Testing of emerging ‘smart’ wireless sensor technologies for river systems, with

application potential in

– Diffuse pollution research and management

– Water and wastewater discharge and water supply distribution networks

– Real time forecasting to support operational management decisions

• Development of novel wireless sensor technologies, with application potential in inaccessible research environments

– Wetlands and undisturbed soils

– Stream sediments and the hyporheos

– Sub-glacial environments and moving water parcels

• Numerical analysis to determine the scale of uncertainties associated with traditional low frequency routine monitoring data

• Development of analytical methods and tools for interpretation and analysis of sensor data for operational decision support

• Use sensor data to support the development of physically-based models, transferable between systems and scales

• Streaming sensor data to cloud-enabled virtual observatories to support modelling and provide targeted advice for policy and management

The Environmental Virtual Observatory (EVOp) programme

WP5: Enhancing national modelling and scenario testing capability

Jim Freer, Penny Johnes, Nick Odoni, University of Bristol;

Sheila Greene, CEH; John Bloomfield, BGS; Sim Reaney, University of Durham; Kit MacLeod, James Hutton Institute;

and the NERC EVOp team

Realising the potential of environmental data, models and tools

The challenge

• Science evidence that informs process understanding is often: – generated at relatively small experimental scales,

– not directly scalable between systems or time periods.

• Stakeholders managing nutrient impacted systems have had to either: – fund the development of bespoke solutions for each catchment of interest

– use knowledge acquired from inadequate monitoring, or another catchment

– run models with conflicting outcomes, generating mistrust of the evidence

• To deliver effective support for policy and management we need to: – provide a holistic understanding of the nature, origins and scale of the problem

– develop physically-based models, transferable between systems and scales

– develop better mechanisms for KE between scientists and stakeholders

Spatial distribution of nutrient export to waters, 2000-10 by sector Further breakdown by process, pathway or contributing source area can be generated

depending on the model(s) selected

2.17 TP kg / ha

2.10 TP kg / ha

1.67 TP kg / ha

2.16 TP kg / ha

1.67 TP kg / ha

Phosphorus Nitrogen

Point sources Diffuse sources Total export

+ ˭

+ ˭

TN Export kg/ha

TP Export kg/ha

Upscaling model outputs from 4km2 to policy reporting units

4 km2 grid Large River Catchment WFD RBD Coastal Drainage Unit OSPAR Zone

2.17 TP kg / ha

2.10 TP kg / ha

1.67 TP kg / ha

2.16 TP kg / ha

1.67 TP kg / ha

Phosphorus Nitrogen

TP Export kg/ha

TN Export kg/ha

TP Export kg/ha

2.17 TP kg / ha

2.10 TP kg / ha

1.67 TP kg / ha

2.16 TP kg / ha

1.67 TP kg / ha

Scenario testing within the cloud-enabled modelling framework

Phosphorus

Nitrogen

Current + Good Agricultural + Farming for WFD + UWwTD for all Conditions Practice Compliance point sources

10.3% decrease 24.7% decrease 29.1% decrease

TN Export kg/ha

TP Export kg/ha

5.73 % decrease 14.7% decrease 57.9% decrease 2.17 TP kg / ha

2.10 TP kg / ha

1.67 TP kg / ha

2.16 TP kg / ha

1.67 TP kg / ha

TOPMODEL PRMS

VIC SAC

Rainfall (mm)

Runoff (mm)

BFI

Developing national ensemble hydrological modelling capability (led by Jim Freer)

Multi-model evaluation against high resolution observational data

• Evaluation in 1100 UK instrumented catchments • Best model varies according to geoclimatic character • Model performance is weakest in regions with high BFI • Super-ensemble improves predictive capability

Scale: goodness of fit Red = good Blue = poor

Super-Ensemble

3500 3000 2500 2000 1500 1000 500 0

100 80 60 40 20 0

1.0 0.8 0.6 0.4 0.2 0

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0

TOPMODEL

Realising the potential of environmental data, models and tools

Website: http://www.evo-uk.org/

Pilot Virtual Observatory Tool….open for testing: http://www.resc.reading.ac.uk/evop/wp4stable/evo-welcome.html

Guest username: BRISTOL_guest

Guest password: silver_Pearl

Find out more…..

http://www.evo-uk.org/http://www.evo-uk.org/http://www.evo-uk.org/http://www.resc.reading.ac.uk/evop/wp4stable/evo-welcome.htmlhttp://www.resc.reading.ac.uk/evop/wp4stable/evo-welcome.htmlhttp://www.resc.reading.ac.uk/evop/wp4stable/evo-welcome.html