linking land-use and water quality - modelling results and ... · linking land-use and water...
TRANSCRIPT
Linking Land-Use and Water Quality -
Modelling Results and Discussion
Lisa Norton, Stephen Maberly, Linda May and
Alex Elliott
with help from John Rockliffe, Leslie Webb, farmers and householders
in the catchment
What is a model?
A model is a simulation of reality
which:
looks like the real thing
provides an opportunity to look at something in its
totality (which might be difficult to do in real life)
provides information on how different parts of an
object relate to one another
A model does not necessarily
function like the real thing it represents
contain all the detailed internal workings of the thing it
represents
Scientists use models to:
Represent reality
Understand how things work
Test how things might work under different (including future) conditions
(because it’s easier than doing it in reality)
What do we want the
Loweswater catchment
model to do?
What are the building blocks for a
Loweswater model?
Land cover information
Land management information and soil P
levels for farmed land
Numbers of people
Septic tank condition, use and
management
Rainfall
Lake discharge
Wind speed
Air temperature/humidity
Cloud cover
Lake data for validation
Tell us how what is done in the
catchment is related to the
algal blooms in the lake
Data/information that is likely to be important but which we don’t
have/ haven’t been able to incorporate
Slurry tank/midden stead condition
Yard water /waste arrangements
Connectivity between waste storage
and water bodies (under normal
conditions)
Connectivity between waste storage
and water bodies (under extreme
weather conditions)
Locations of animal feeders in relation
to water bodies
Animal access to water bodies in lake
feeder streams
Outline of modelling approach
Collect farm
data
Create farm
nutrient budget
(PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff
model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations
(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as
point or diffuse)
Create farm
management
scenario data
Status quo
Scenario testing
Local weather
Land cover
Land cover and land management
Each land cover type has an associated average nutrient
export value
Nutrient Exports on managed farmland depend heavily on
inputs and stocking levels
Hence specialist farmer nutrient budgeting software
was used to calculate nutrient exports from the farmland
using John Rockliffe’s information on farming practice and
soil nutrient status
Land cover type Area
(km2)
P
(mg P m-3)
Nitrate
(mg N m-3)
A High production grass 2.79 32 3,540
B Broadleaved woodland 0.65 10 190
C Coniferous woodland 0.35 10 190
D Natural grass 1.39 5 2,100
E Urban 0.12 56 0
F Arable 0.03 17 2,900
G Moors and heathland 2.29 7 190
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Calculate nutrient excess on each farm
1. Collect data from farmers
2. Enter data into PLANET
(Planning Land Application of
Nutrients for Efficiency and the
Environment)
3. Calculate phosphorus and
nitrogen balance for each farm,
based on ‘imports’ and ‘exports’
of :
1. Fertiliser
2. Livestock
3. Feedstuffs
4. Bedding
5. etc.
1. Predict nutrient excess on each
farm
1 & 2
3 & 4Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Example: predicting the P excess on each farm
Farm
5 kg P y-1 50 kg P y-1
N
U
T
R
I
E
N
T
S
O
U
T
N
U
T
R
I
E
N
T
S
I
N
NUTRIENT
EXCESS
IN – OUT = 400 – 250 =150 kg P y-1
Bedding/feed Bedding/feed
Fertiliser/manure/slurry
Sheep
Cattle
Fertiliser/manure/slurry
Sheep
Cattle
Revise annual net P surplus
1. P surplus for each farm minus soil P deficit
(calculated in PLANET) (as calculated from John Rockliffe’s soil sampling)
(calculated by farm – on the assumption that P deficit = capacity for P uptake by soil)
Update P surplus values to take account of soil uptake and septic tank
discharges:
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
2a. Either- add P from septic tanks on farms into the above sum (data from Leslie
Webb)
(P from septic tanks is taken up the soil in the same way as farm nutrient surplus
– a diffuse source)
2b. Or add P from septic tanks in as a direct input to streams (a point source)
Farm no. Surplus P Soil P deficitP from septic
tanksNet P surplus
1134 375 3.1 0
2356 161 2.0 197
3. Summed to produce an annual P-load for all the farms
Outline of modelling approach
Collect farm
data
Create farm
nutrient budget
(PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff
model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations
(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as
point or diffuse)
Create farm
management
scenario data
Status quo
Scenario testing
Local weather
Land cover
•Last data available for Loweswater in 2001
• 2009 data reconstructed from adjacent gauging stations
y = 0.060x + 0.087
R2 = 0.843
0
0.5
1
1.5
2
2.5
3
0 20 40 60
Park Beck outflow to Crummock (m3 s-1)
Lo
we
sw
ate
r o
utflo
w (
m3
s-1
)
y = 0.076x + 0.094
R2 = 0.832
0
0.5
1
1.5
2
2.5
3
3.5
0 10 20 30 40
Scalehill outflow from Crummock (m3 s-1)
Lo
we
sw
ate
r o
utflo
w (
m3
s-1
)
Loweswater flow (discharge) for validation- 1
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
0
0.5
1
1.5
2
2.5
3
09/02/19
99
28/08/19
99
15/03/20
00
01/10/20
00
19/04/20
01
05/11/20
01
Dis
ch
arg
e (
m3 s
-1)
Loweswater
Lowes from Park Beck
Lowes from Scalehill
0
2
4
6
8
10
12
31/12/20
08
10/04/20
09
19/07/20
09
27/10/20
09
04/02/20
10
Dis
ch
arg
e (
m3 s
-1)
Scalehill simulation
Park Beck simulation
Loweswater flow (discharge) for validation- 2
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Predict streamflow from rainfall
1. Generate modelled streamflow
from rainfall (local rain gauge plus
Ken) and air temperature (buoy)
2. Values compared to simulated
discharge for Loweswater
0
0.5
1
1.5
2
2.5
Sep-99 Dec-99 Mar-00 Jun-00 Sep-00 Dec-00 Mar-01 Jun-01
Dail
y d
isch
arg
e (m
3s
-1)
Date
Modelled values
Measured values
Str
ea
mfl
ow
(m
3s
-1)
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Calculate daily nutrient runoff values for each scenario
1. Annual P-inputs from the farms
added to annual P-input from the
other land in the catchment (export
coefficient) to produce a total
annual load of P (kg y-1)
2. Different scenarios of possible land
management were investigated
(each with/without direct septic tank
input) and annual P-load calculated
3. GWLF hydrological model (daily
discharge) combined with these P-
loads to produce daily loads of P
(also using a similar approach
nitrogen and silica)
0
2
4
6
8
10
12
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Estim
ate
d P
load t
o la
ke (
kg P
d-1
)
2009
S1 S2 S3
S4 S5E
stim
ate
d P
in
pu
t to
lake
(kg P
d-1
)
Scenario Description
S1 Status quo
S2 All farmland to deciduous forest
S3 All improved grassland to natural grassland
S4 Remove cattle; double sheep
S5 Double cattle; halve sheep
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
0
100
200
300
400
S1
S1A
S2
S2A
S3
S3A
S4
S4A
S5
S5A
Phosphorus-load (kg y-1)
Scen
ario
P-loads predicted by the different scenarios
Scenario Description
S1Current land cover & stocking densities
(A = Septic tanks as point sources)
S2All farmland changed to deciduous forest
(A = Septic tanks as point sources)
S3
All improved grassland changed to natural
grassland
(A = Septic tanks as point sources)
S4No cattle; double sheep
(A = Septic tanks as point sources)
S5Double cattle; half sheep
(A = Septic tanks as point sources)
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Light
What controls phytoplankton growth?
Algae
Wind
Heat flux
Nutrients
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
The phytoplankton used in this PROTECH simulation
Asterionella
Aulacoseira
Chlorella
Plagioselmis
Dinobryon
Anabaena
Planktothrix
Aphanizomenon
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
-5.0
0.0
5.0
10.0
15.0
20.0
25.0
30.0
31
-Dec-0
81
4-J
an
-09
28
-Ja
n-0
91
1-F
eb
-09
25
-Feb
-09
11
-Ma
r-0
92
5-M
ar-0
90
8-A
pr-0
92
2-A
pr-0
90
6-M
ay
-09
20
-Ma
y-0
90
3-J
un
-09
17
-Ju
n-0
90
1-J
ul-
09
15
-Ju
l-0
92
9-J
ul-
09
12
-Au
g-0
92
6-A
ug
-09
09
-Sep
-09
23
-Sep
-09
07
-Oct-
09
21
-Oct-
09
04
-No
v-0
91
8-N
ov
-09
02
-Dec-0
91
6-D
ec-0
93
0-D
ec-0
9
T (
°C)
Loweswater, 2009
A…
0
4
8
12
16
20
31
-Dec-0
81
4-J
an
-09
28
-Ja
n-0
91
1-F
eb
-09
25
-Feb
-09
11
-Ma
r-0
92
5-M
ar-0
90
8-A
pr-0
92
2-A
pr-0
90
6-M
ay
-09
20
-Ma
y-0
90
3-J
un
-09
17
-Ju
n-0
90
1-J
ul-
09
15
-Ju
l-0
92
9-J
ul-
09
12
-Au
g-0
92
6-A
ug
-09
09
-Sep
-09
23
-Sep
-09
07
-Oct-
09
21
-Oct-
09
04
-No
v-0
91
8-N
ov
-09
02
-Dec-0
91
6-D
ec-0
93
0-D
ec-0
9
mea
n w
ind
sp
(m
/s)
Loweswater windspeed, 2009
Meteorological data from buoy input into PROTECH
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Loweswater, 2009
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
31
-De
c-0
8
14
-Ja
n-0
9
28
-Ja
n-0
9
11
-Fe
b-0
9
25
-Fe
b-0
9
11
-Ma
r-0
9
25
-Ma
r-0
9
08
-Ap
r-0
9
22
-Ap
r-0
9
06
-Ma
y-0
9
20
-Ma
y-0
9
03
-Ju
n-0
9
17
-Ju
n-0
9
01
-Ju
l-0
9
15
-Ju
l-0
9
29
-Ju
l-0
9
12
-Au
g-0
9
26
-Au
g-0
9
09
-Se
p-0
9
23
-Se
p-0
9
07
-Oc
t-0
9
21
-Oc
t-0
9
04
-No
v-0
9
18
-No
v-0
9
02
-De
c-0
9
16
-De
c-0
9
30
-De
c-0
9
Su
rf P
FD
um
ol
m-2
s-1
surf PFD surf PFD after 16Jan09
Surface lightAir temperature
Windspeed
In-lake temperatures for PROTECH validation
Loweswater, 2009
0
5
10
15
20
25
30
31-D
ec-0
8
14-J
an
-09
28-J
an
-09
11-F
eb
-09
25-F
eb
-09
11-M
ar-
09
25-M
ar-
09
08-A
pr-
09
22-A
pr-
09
06-M
ay-0
9
20-M
ay-0
9
03-J
un
-09
17-J
un
-09
01-J
ul-
09
15-J
ul-
09
29-J
ul-
09
12-A
ug
-09
26-A
ug
-09
09-S
ep
-09
23-S
ep
-09
07-O
ct-
09
21-O
ct-
09
04-N
ov
-09
18-N
ov
-09
02-D
ec-0
9
16-D
ec-0
9
30-D
ec-0
9
T (
°C)
0.1m 1m 2m 3m 4m 5m 6m 7m 9m 11m 13m 15mCollect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Met data inputs
0
5
10
15
20
25
0 50 100 150 200 250 300 350 400
Tem
per
atu
re in
to
p 5
m (
oC
)
Day of year
Buoy data
Series2PROTECH
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
0
5
10
15
20
25
1 31 61 91 121 151 181 211 241 271 301 331 361
Ch
loro
ph
yll a
(m
g m
-3)
Day of year
Total
Chlorella
Plagioselmis
Asterionella
Aulacoseira
Anabaena
Aphanizomenon
Planktothrix
Dinobryon
PROTECH output for S1 scenario
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
0
5
10
15
20
25
1 31 61 91 121 151 181 211 241 271 301 331 361
Ch
loro
ph
yll a
(m
g m
-3)
Day of year
Total
Chlorella
Plagioselmis
Asterionella
Aulacoseira
Anabaena
Aphanizomenon
Planktothrix
Dinobryon
0
5
10
15
20
25
1 31 61 91 121 151 181 211 241 271 301 331 361
Ch
loro
ph
yll a
(m
g m
-3)
Day of year
Total
Chlorella
Plagioselmis
Asterionella
Aulacoseira
Anabaena
Aphanizomenon
Planktothrix
Dinobryon
PROTECH output for S3 (low P load) & S5 (high P load) scenarios
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
0
5
10
15
20
1 31 61 91 121 151 181 211 241 271 301 331 361
SRP
(m
g m
-3)
Day of year
S5
S3
S1
PROTECH output of SRP concentration for scenarios S1, S3 and S5
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Validation against monthly data: Total Chlorophyll
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Validation against monthly data: Cyanobacteria
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
0
2
4
6
8
10
12
14
0 100 200 300 400
An
nu
al m
ea
n c
hlo
rop
hy
ll a
(mg
m-3
)
Phosphorus load (kg SRP y-1)
H:G
G:M
M:P
Chlorophyll production vs SRP load for the scenarios
0
2
4
6
8
10
12
14
0 100 200 300 400
An
nu
al m
ea
n c
hlo
rop
hy
ll a
(mg
m-3
)
Phosphorus load (kg SRP y-1)
H:G
G:M
M:P
S3
S2
S3A
S2A
S1
S1AS5
S4
S5AS4A
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
0
2
4
6
8
10
12
0 100 200 300 400
An
nu
al m
ea
n c
hlo
rop
hy
ll a
(mg
m-3
)
Phosphorus load (kg SRP y-1)
Cyanobacterial Chlorophyll vs SRP load
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
y = 0.16x + 30.75R² = 0.98
0
20
40
60
80
100
0 100 200 300 400
% tim
e o
r %
Ch
la
Phosphorus load (kg SRP y-1)
Percent cyanobacteria Percent of year> 10 mg Chl a m-3
Cyanobacterial Chl as % of total and % of year chlorophyll > 10 mg m-3
Collect farm
data
Create farm
nutrient budget (PLANET)
Calculate farm
nutrient excess
Collect rainfall
& flow data
Calibrate
rainfall/runoff model (GWLF)
Generate daily
runoff values
Calculate nutrient
runoff concentrations(= nutrient excess/flow)
Generate daily nutrient
inputs to lake (GWLF)
Predict lake response
(PROTECH)
Adjust for soil P
deficit
Add P losses from
septic tank (as point or diffuse)
Create farm
management scenario data
Status quo
Scenario testingLocal weather
Land cover
Conclusions
• All models are simplifications of reality but,
despite the simplifying assumptions and inevitable
non-perfect data, the three models, PLANET,
GWLF and PROTECH were successfully linked to
produce a reasonable simulation of the effect of
the land on the lake
• Currently, observations and models suggest that
the lake is at moderate ecological status for WFD
with a total annual load of about 200 kg P y-1.
• The models suggests that if the load was halved,
the lake could be brought to good ecological status
(time……). The model could be used as a tool to
inform future land-management decisions.
• Septic tanks have a relatively small effect on P
and phytoplankton today, but- they can be
improved without major changes to way of life and
would become increasingly important if P-losses
from the land were reduced.
Discussion
• Discuss these and other scenarios
• Are their any actions that LCP could instigate following on from the modelling?
• Sources of funding for further improvements (septic tanks, slurry/ waste
management)
• Known unknowns
• Can it help with the ‘tension’ between economy and ecology?
•
0
5
10
15
20
25
1980 1990 2000 2010
To
tal p
ho
sp
horu
s (u
g L
-1)
W Sp
Su A
0
5
10
15
20
25
1990 1995 2000 2005 2010P
hyto
pla
nkto
n C
hl a
(µg
L-1
)
W Sp Su A
Long-term trends