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Transcript of Model-based and statistical methods for assessment of goal achievement EEA, Copenhagen 21-22...
Model-based and statistical methods for assessment of goal achievement
EEA, Copenhagen 21-22 February, 2005
Anders Grimvall
Department of Mathematics
Linköping University, Sweden
EEA, 21-22 Feb 2005
Outline of presentation
Statistical methods for separating human impact from natural fluctuations
Ensemble runs of process-based models
Validation of models for scenario analyses
EEA, 21-22 Feb 2005
Nitrogen load and water dischargeat Lobith on the Rhine
0
100
200
300
400
500
1988 1990 1992 1994 1996 1998 2000 2002 2004
Riv
eri
ne
loa
d o
f to
tal n
itro
ge
n (
10
00
to
n N
/yr)
0
20
40
60
80
100
Wa
ter
dis
ch
arg
e (
10
6 m3 /y
r)
Nitrogen load Water discharge
EEA, 21-22 Feb 2005
Observed and normalised nitrogen load at Lobith on the Rhine
0
100
200
300
400
500
1988 1990 1992 1994 1996 1998 2000 2002 2004
Riv
erin
e lo
ad o
f to
tal n
itro
gen
(10
00 t
on
N/y
r)
Normalised load Observed load
EEA, 21-22 Feb 2005
Simple flow-normalisation of the riverine load of phosphorus at Brunsbüttel on the Elbe River
0
5
10
15
20
1984 1988 1992 1996 2000
To
t-P
loa
d (
kto
n/y
r)
0
10
20
30
40
Wa
ter
dis
cha
rge
(1
09 m
3 /yr)
Tot-P load Water discharge
0
5
10
15
20
0 10 20 30 40
Water discharge (109 m3/yr)
To
t-P
loa
d (
kto
n/y
r)
0
5
10
15
20
1984 1988 1992 1996 2000
Flo
w-n
orm
alis
ed
To
t-P
loa
d (
kto
n/y
r)
EEA, 21-22 Feb 2005
Normalisation of the load of phosporuscarried by the Elbe River
0
5
10
15
1984 1986 1988 1990 1992 1994 1996 1998 2000 2002
No
rma
lise
d T
ot-
P lo
ad
(kt
on
/yr)
.
Schnackenburg Brunsbuettel Cuxhaven
Normalisation with respect to water discharge, salinity and load of suspended particulate matter
EEA, 21-22 Feb 2005
Conclusions- statistical normalisation
The combined effect of all past interventions in the drainage area can be clarified with a temporal resolution that is satisfactory for decision-making
The attribution of anthropogenic trends to specific interventions may require other tools
EEA, 21-22 Feb 2005
General structure of process-based models of the flow of water and substances through a catchment
The riverine load y at given time t and site z is a function
of all inputs at all occasions up to time t and all sites upstream of zz~)ofupstream~,);~,((),( zztszsfzt xy
Different types of model inputs:
• initial conditions (state of the system at the onset of the simulation)• anthropogenic forcing of the system• meteorological forcing of the system• model parameters
)~,( zsx
EEA, 21-22 Feb 2005
Ensemble runs for meteorological normalisationof riverine loads
20
40
60
80
100
120
1 11 2120
40
60
80
100
120
1 11 21
Physics-basedmodel
Anthropogenicforcing
Simulatedweather data 1
Step 2:
20
40
60
80
100
120
1 11 2120
40
60
80
100
120
1 11 21
Physics-basedmodel
Anthropogenicforcing
Simulatedweather data k Model output k
Model output 1
20
40
60
80
100
120
1 11 2120
40
60
80
100
120
1 11 21
Weathergenerator
Real weather dataSimulatedweather data
Step 1:
Average output for each time t
20
40
60
80
100
120
1 11 21
The natural variation is suppressed
EEA, 21-22 Feb 2005
Meteorologically normalised outputs of the Integrated Nitrogen in Catchments (INCA-N) model
A single sub-basin comprising only arable land and
receiving a constant level of ammonium and nitrate fertiliser
(combined total 156 kg N/ha/yr)
0
20
40
60
80
100
120
1 2 3 4 5 6 7Year
Nor
mal
ised
load
of
inor
gani
c N
(kg
/ha/
yr)
EEA, 21-22 Feb 2005
Ensemble runs clarifying the response to changes in the fertilisation scheme
Run the model with
(i) a given fertilisation scheme
(ii) a slightly adjusted scheme
and compute the difference between the two model runs.
Repeat such pairs of runs for a representative distribution of meteorological forcings and compute the mean output for each time t.
If the adjustment is zero for the second year and onwards, we can summarise the results in impulse response functions for the impact of fertiliser application.
EEA, 21-22 Feb 2005
Predicted response of riverine loads of inorganic nitrogen to an impulse in fertiliser application
A single sub-basin comprising only arable landBase-flow index 0
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7Year
Cu
mu
late
d r
esp
on
se
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7Year
Re
lativ
e f
req
ue
ncy
Travel time of the extra nitrogen added Ratio of the cumulated increase in
riverine loads to the increase in fertiliser application
EEA, 21-22 Feb 2005
Predicted response of riverine loads of inorganic nitrogen to an impulse in fertiliser application
A single sub-basin comprising only arable landBase-flow index 1
0.0
0.2
0.4
0.6
0.8
1.0
1 4 7 10 13 16 19 22 25 28Year
Cu
mu
late
d r
esp
on
se .
0.00
0.05
0.10
0.15
0.20
1 4 7 10
13
16
19
22
25
28
Year
Re
lativ
e f
req
ue
ncy
Ratio of the cumulated increase in riverine loads to the increase in
fertiliser applicationTravel time of the extra nitrogen added
EEA, 21-22 Feb 2005
Ensemble runs clarifying water travel times
The response to changes in the input of an inert substance can be clarified by performing ensemble runs in which:
all processes involving transformation or immobilisation
of nitrogen are switched off
An inert substance moves like the water in which it is
dissolved
EEA, 21-22 Feb 2005
Distributions of travel times for inorganic nitrogen and water
Base-flow index 0
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7
Year
Rel
ativ
e fr
eque
ncy
Water Inorg. N
0.00
0.05
0.10
0.15
0.20
1 3 5 7 9 11 13 15 17 19 21
Year
Rel
ativ
e fr
eque
ncy
Water Inorg. N
Base-flow index 1
Preferential removal of nitrogen taking long pathways
EEA, 21-22 Feb 2005
Conclusions- ensemble runs
Ensemble runs involving artificially generated meteorological inputs can be employed to:
Extract model features that might otherwise be hidden by the total variation in the model output
Compute meteorologically normalised model outputs for retrospective or scenario analyses of riverine loads
EEA, 21-22 Feb 2005
Conventional model validation
0
50
100
150
200
250
300
350
400
450
500
1991-01-01 1992-01-01 1992-12-31 1993-12-31 1994-12-31
Nitr
ate
tra
nsp
ort
(g
N/s
)
Observed transport Modelled transport
Proper validation requires data sets having a
substantial variation in the input under consideration
EEA, 21-22 Feb 2005
Conclusions- validation of process-based models
Proper validation of models for scenario analyses can only be done in catchments where substantial interventions have been undertaken
It can be questioned whether the INCA-N model, and many other models, are able to predict long lags in the water quality response to interventions in the drainage area
EEA, 21-22 Feb 2005
Overall conclusions
Statistical normalisation can give added value to observed data
Ensemble runs can give added value to process-based models
The currently used model validation techniques can be questioned
EEA, 21-22 Feb 2005
Further reading
Hussian, M., Grimvall, A., and Petersen, W. 2004. Estimation of the human impact on nutrient loads carried by the Elbe River. Environmental Monitoring and Assessment 96:15-33.
Wahlin, K., Shahsavani, D., Grimvall, A., Wade, A. and Butterfield, D. 2004. Reduced models of the retention of nitrogen in catchments. In C. Pahl-Wostl, S. Schmidt, A.E. Rizzoli, and A. J. Jakeman (eds.) Complexity and Integrated Resources Management, Transactions of the 2nd Biennial Meeting of the International Environmental Modelling and Software Society, iEMSs: Manno, Switzerland, 2004.
EEA, 21-22 Feb 2005
Flow normalisation of the nitrogen load carried by the Göta River - data from Trollhättan
Normalisation with respect to water discharge
0
5000
10000
15000
20000
25000
1975 1980 1985 1990 1995 2000 2005
Tot-N load (ton N/yr) Normalised Tot-N load (ton N/yr)