from real to virtual observatories: sustaining and improving water and soil science
DESCRIPTION
From real to virtual observatories: sustaining and improving water and soil science. Doerthe Tetzlaff. Northern Rivers Institute, Aberdeen www.abdn.ac.uk/nri. Real observatories at different scales. Catchment scale. Hillslope scale. Reach scale. - PowerPoint PPT PresentationTRANSCRIPT
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From real to virtual observatories: From real to virtual observatories: sustaining and improving water and sustaining and improving water and
soil sciencesoil science
Doerthe Tetzlaff
Northern Rivers Institute, Aberdeenwww.abdn.ac.uk/nri
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Real observatories at different scales
Catchment scale Hillslope scale Reach scale
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Conceptualization – capturing connections at different scales
How can we capture environmental variability (water flow paths, storage, transit times…) in the landscape?
1st order streams
2nd order streams 3rd order streams
zero order streams
Different scales, geographical environments… Different approaches: mapping tool, qualitative conceptual
model, physical model…
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Cross-regional observatories – Contextualisation of insights
Girnock (30 km2)
Dee (2000 km2)Allt a’ Mharcaidh
Feshie Aberdeen
North Esk (800 km2)
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Towards an integrated process understanding
2. Runoff sources / Mean transit times
3. Towards prediction / Upscaling / Connection
1. Landscape composition / configuration
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Soils and hydrological response in a typical upland catchments
“Responsive”
Peat / Peaty GleySaturation overland flow
Shallow sub-surface storm flow
“Freely draining” Humus Iron Podzol
Deep sub-surface storm flow
Groundwater recharge
Soulsby et al. (2006a). J. of Hydrol. 325, 197-221.Soulsby et al. (2006b). Hydrol. Proc. 20, 2461-2465. Tetzlaff et al. (2007a). Hydrol. Proc. 21, 1289-1307.
30 km2 Girnock Burn catchment
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Saturation area: Importance for non-linear hydrological response
The Girnock catchment (30 km2)
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Hydrology Of Soil Types (HOST) - digital data base
- 29 classes which integrate:• Geology• Topography• Climate• Vegetation
- Infer hydrological pathways from soil properties
http://www.macaulay.ac.uk/host/hostdist.htm
Tetzlaff et al. (2007a) Hydrol. Proc. 21, 1289-1307: Conceptualisation of runoff processes using GIS and tracers in a nested mesoscale catchment.
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Conservative tracers for rainfall-runoff dynamics
McGuire and McDonnell, 2006 JoH
Streamwater
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01/01/95 01/01/97 01/01/99 01/01/01 01/01/03 Con
cent
ratio
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PrecipitationStreamwaterModelled
01/01/88 01/01/90 01/01/92 01/01/94 01/01/96 Con
cent
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g l-1
)
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PrecipitationStreamwaterModelled
Conservative tracers
Response of catchments: Short TT (rapid connection) / Longer TT (slower connections)
Fast responding catchment Deep-subsurface flow dominated catchment
Tetzlaff et al (2007b) J. of Hydrol. 346, 93-111.
Hrachowitz et al (2009) J. of Hydrol. 367, 237-248.
50%
Cu
m.
de
nsi
ties
fu
nct
ion
50%
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Incorporation of non-linearity in catchment response
Dry
Wet
Saturation area extent =
f (API, ET, Soils)
5-30% of catchment area
Birkel et al., 2010, Towards simple dynamic process conceptualization in rainfall runoff models using multi-criteria calibration and tracers in temperate, upland catchments. Hydrological Processes.
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Improved representation of system behaviour
Means of constraining models
C. Birkel et al., Water Resources Research, in press: Using time domain and geographic source areas tracers to conceptualize streamflow generation processes in rainfall-runoff models.
Non-linearity + high resolution tracers as objective measures
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Some problems with real observatories
• Fragmentation at all levels:• Spatial, temporal gaps in data• Individual and unlinked models• Limited linkages between disciplines, institutes,
agencies, countries (within and outwith UK)
Environmental community does not embrace new information technologies / is poorly equipped to exploit those
Need for consistency in approaches
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EVOp Vision
Pilot:
proof of concept project to demonstrate that linking data, models and expert knowledge will provide cost effective answers to wide-ranging environmental issues (initially soil - water system)
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The team
• Leadership and Management team– Adrian McDonald (Leeds)– Robert Gurney (Reading)– Bridget Emmett (CEH)
• WP leaders– Phil Haygarth (Lancaster)– Jim Freer (Bristol)– Wouter Buytaert (Imperial)– Gordon Blair (Lancaster) &
Gwyn Rees (CEH)– Doerthe Tetzlaff (Aberdeen)
Full team• Keith Beven (Lancaster)• Gordon Blair (Lancaster)• John Bloomfield (BGS)• Roland Bol (Rothamsted)• Wouter Buytaert (Imperial)• Bridget Emmett (CEH)• Jim Freer (Bristol)• Robert Gurney (Reading)• Phil Haygarth (Lancaster)• Penny Johnes (Reading)• Paul Quinn (Newcastle)• Mark Macklin (Abserystwyth)• Christopher Macleod (Macaulay)• Adrian McDonald (Leeds)• Sim Reaney (Durham)• Gwyn Rees (CEH)• Marc Stutter (Macaulay)• Doerthe Tetzlaff (Aberdeen)
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Objectives
(i) To make environmental data more visible / accessible to wide range of potential users and free to use for public;
(ii) To provide tools to facilitate integrated analysis of data, greater access to added knowledge and expert analysis, and visualisation of results;
(iii) To develop new, added-value knowledge from public and private sector data to help tackle environmental challenges.
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Soiltrec
Hydronet
Expeer
EU /Global observatories
Sensors
UK observatories
National Capability
Earth Observation Framework
Demonstration test Catchments
Data/portals
Dedicated data centres
GMES
Inspire
Models
Transparency
Environmental issue
FloodingDiffuse pollutionWater resources
EXEMPLARS
Decision support tools
Alternet
Strategy for the Pilot (£2M)Start with mature community which has good stakeholder engagement (i.e. soils and water) and build on various ongoing initiatives:
Environmental issue
Environmental issue
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Project structure
• 2 WPs to develop cyber infrastructure: data and modelling tools.
• These will underpin development of 2 exemplars based on soil and water questions framed in local and national context
• Internationalisation
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An environmental cloud
A space for:• Exploring data• Linking models• Accessing added knowledge• Visualisation tools
To deliver more:• Efficient, effective and
transparent use of environmental data, models and knowledge
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Questions the EVO could help answer
ScientistsHow do we define which model
is better to select from our model ensemble?
What kind of language/tools to use to make models “talk” to
each other.
Water IndustryWhat is the whole impact of
future flooding?How can water security be
assured?How can the industry carbon
impact be reduced?
PublicWill my town run out of
water?What is the state of the
local river? What are the options to protect us from future
flooding?
RegulatorsHow can we reduce monitoring for same
information? Credible apportioning of pollutant load between
industry, water, agriculture, other.
Government Agencies
What models work?What policy works?
How do I do it for less money?
EVO cloud
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What is benefit for scientists?
• Currently: many wheels constantly re-invented– Re-implementing models, file import and export routines etc. – Tools and models library will stop this re-invention
• Fewer wheels, more environmental science.
• Models to be tested as hypotheses about system functioning
• Longer term: understanding gained will be used in extending the VO within and outside UK.
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Many thanks for your attention!!!
”The more closely we search, the more elusive the edge becomes” (K. Dean Moore)
Check out for papers and posters: www.abdn.ac.uk/nri