M th
Mathematical
ti l Si
Simulation
l ti T
Tools
l
George Vellidis
Mathematical Simulation Tools
• Models DO NOT provide absolute results
Mathematical Simulation Tools
• Models DO NOT provide absolute results
• Models p
provide comparisons
p
between the
outcomes of different
►
management
g
scenarios
►
decisions
►
situations
►
conditions
Before Selecting
g a Model
• Original purpose
• Characteristics and operating principles
►
empirical, stochastic, mechanistic, multi-criteria, etc.
►
t
temporal
l and
d spatial
ti l scale
l
• Conditions under which the model will perform properly
• Data and calibration requirements
• Output produced by the model
• Model limitations
• User community and support network
Model Types
yp
• Empirical
►
equations
q
fitted to data
• Mechanistic (deterministic, process-based)
►
based on mathematically replicating physical processes
• Stochastic
►
use mathematical and statistical concepts to link a certain input
(rainfall) to the model output (runoff)
• Multi-Criteria
►
helps users make complex decisions among alternatives
involving multiple criteria
Why is Dissolved Oxygen an Issue?
• Coastal plain streams
have DO below standards
►
4 mg/L
►
Is this standard reasonable?
►
What is DO in minimally
impacted streams?
12
Dissolved Oxygen in the
Willacoochee Watershed
11
DO regulatory limit
D issolved Oxygen
n Concentration (mg/L)
10
Agricultural Watershed 1
Agricultural Watershed 2
Waste Water Treatment Watershed
Willacoochee River
9
8
7
6
5
4
3
2
1
0
Apr-02
Jun-02
Aug-02
Oct-02
Dec-02
Jan-03
Apr-03
Date
Jun-03
Aug-03
Oct-03
Dec-03
Feb-04
DO and TMDLs
Project
j
Objectives
j
• To determine the causes and effects of low
dissolved oxygen in the rivers, streams, and
wetlands of the Suwannee River Basin
• To train and educate stakeholders about these
issues and the effect that their actions have on
dissolved oxygen
Ecological
g
Processes
• Understand ecological processes governing
DO dynamics in coastal plain streams
►
nutrient enrichment / primary production
►
sediment oxygen demand (SOD)
►
role of in-stream
in stream wetlands and swamps
• Simulate DO dynamics
Simulate DO Dynamics
y
• Use the Georgia
g DO Sag
g Model
►
Developed by Georgia EPD
►
Used by EPD to develop DO TMDLs
►
Deterministic
►
Originally developed for use in
Piedmont waterways
DO (m
mg/l)
Disolved Oxygen Sag Curve
9
8
7
6
5
4
3
2
1
0
1
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18
Distance downstream
• Anna Cathey – former M.S. student
Cathey, A., G. Vellidis, M. Smith, R. Lowrance, and R. Burke. 2005. Modeling low dissolved oxygen in coastal plain streams. In A. Saleh (ed) Proceedings of the 3rd
Conference on Watershed Management to Meet Emerging TMDL Environmental Regulations, ASAE, St. Joseph, Michigan, pp 330-337.
Little River Experimental Watershed
(LREW)
M
J
K
I
F
G
N
Stream Gauging Station
Watershed Boundary
Floodplains / Swamps
O
Little River Experimental Watershed
M
J
• 334 km2 (82,500
(82 500 ac)
K
I
• USDA-ARS regional
experimental watershed
• Established in late 1960s
F
• 9 nested watersheds
G
• 5th order stream at outlet
N
Stream Gauging Station
Watershed Boundary
Floodplains / Swamps
O
Calibration
Calibration is the process of adjusting
parameters to make modeled DO match DO
values measured in the field.
Parameter Estimation
• DO sinks
►
CBOD
►
NBOD
►
SOD
• DO Sources
►
Reaeration
►
Ph t
Photosynthesis
th i
Sediment Oxygen
yg Demand – SOD
• The rate at which DO is removed from the water column
due to the decomposition of organic matter on the
bottom and within the bottom sediments
• SOD a combination of two processes:
►
►
biological respiration of benthic organisms residing on the
bottom or in the sediment
chemical oxidation of reduced substances found within the
sediment matrix
• Three methods: estimation, laboratory, and in situ
measurements
Parameter Estimation –
Sediment Oxygen Demand (SOD)
• Literature values for SOD rates for southeastern United
States rivers:
►
0.33 – 0.77 g O2 m-2 d-1 (Truax et al., 1995)
• Stream study in Suwannee River basin (Crompton, 2007):
►
0.6 – 1.4 g O2 m-2 d-1 in agricultural watersheds
►
0.9 – 2.5 g O2 m-2 d-1 in forested watersheds
• SOD needed to calibrate model:
►
6 gm-2d-1
Validation
Validation is the process of running a calibrated
model under different conditions than those used
for calibration to see if the model can still
represent the system.
The model was validated in both time and space
Modeled data from April 24, 2004
M
J
K
I
F
G
N
Stream Gauging Station
Watershed Boundary
Floodplains / Swamps
•
Using data from Little River watershed
•
Yellow marks indicate sampled DO
O
Sensitivityy Analysis
y
Sensitivity analysis is the process of varying
parameters within published or reasonable
ranges and observing how those changes
affects the model output.
Sensitivity Analysis
12
SOD
Net Photosynthesis
Rearationk
Temp
Depth
Velocity
Change
e in Dissolved Oxyg
gen (mg/l)
10
8
6
4
2
0
-100%
-75%
-50%
-25%
0%
25%
Percent Change of Parameter
50%
75%
100%
Hypotheses
yp
• SOD is the principal sink of
DO in these swamps
• Soil organic matter is a
driving factor of SOD
• Jason Todd – former
Ph.D. student
Calibration and Validation on
LRB
M
J
K
I
Flow Direction
F
G
N
Stream Gauging Station
Watershed Boundary
Floodplains / Swamps
O
SOD Conclusions
• Literature values for SOD rates for southeastern United States
rivers range between 0.33 – 0.77 g O2 m-2 d-1 (Truax et al., 1995).
• Stream study (Crompton, 2007):
►
0.6 – 1.4 g O2 m-2 d-1 in agricultural watersheds
►
0.9 – 2.5 g O2 m-2 d-1 in forested watersheds
• In the swamp: 1.3 – 14.2 g O2 m-2 d-1 (avg = 4.96 g O2 m-2 d-1 )
►
►
65% of swamp values above the highest value recorded in stream
channels
31/32 higher than literature values
Todd, M. J., G. Vellidis, R.R. Lowrance, and C.M. Pringle. 2009. High sediment oxygen demand within an instream swamp in southern
Georgia: Implications for low dissolved oxygen levels in coastal blackwater streams. Journal of the American Water Resources Association
45(6):1493 1507.
45(6):1493-1507
Georgia
g CEAP Project
j
• To evaluate the effects of past and potential
conservation practices on water quality in a
coastal plain watershed;
• To evaluate social and economic factors influencing
implementation and maintenance of these conservation
practices; and
• Train and educate stakeholders about these issues and
the effects that their actions have on watershed-scale
water quality.
LREW Cropping History
LREW Landcover
Urban
Pecan
Forested
Water/Wetland
Crop
Pasture
J K
[%
[%
I
[%
• Agricultural: 41%
►
F
[%
Pasture: 7%
• Forest: 47%
►
Forested wetland: 9%
• Urban:
Ub
3%
B
[%
[%O
• Water: 2%
USDA Conservation Practices
• By 2006
►
12 714 ac
12,714
►
38% of agricultural land
►
15% of total watershed
Water Quality Trends
Watershed B (LREW), 1978-2003
0.60
-1
FWM Total P Concentratiion (mg l )
Spring
Winter
0.50
Spring Trend
Winter Trend
0.40
0.30
0.20
0.10
0.00
1975
1980
1985
1990
winter trend significant
g
for a = 0.05
1995
2000
2005
Water Quality Trends
Annual flow-weighted mean concentrations – trends
between 1978-2003
Parameter
NO3-N
B
F
I
J
K
M
N
O
-
-
-
-
-
-
-
M
NH4-N
-
TKN
-
-
-
i
i
-
-
-
J
K
I
-
-
-
-
-
-
F
Total N
-
-
-
-
-
-
-
G
DMRP
-
-
-
-
-
-
-
-
Total P
d
D
d
D
-
-
-
D
Cl
-
-
-
I
-
-
I
I
N
Stream Gauging Station
Watershed Boundary
Floodplains / Swamps
“–” denotes not significant; D denotes significant decreasing trend and I denotes significant
increasing
g trend for a = 0.05. Non-capital
p
letters indicate significance
g
for a = 0.10.
O
SWAT Modeling
(Soil Water Assessment Tool)
• Evaluate the effects of past and potential
conservation practices in the nested
watersheds
►
►
►
Evaluate model accuracy, establish confidence
bounds
Evaluate long-term impacts of installing
conservation practices
Evaluate potential impacts of alternative scenarios
Evaluating Current CPs
• Select parameters to appropriately
represent hydrology and pollutant
transport during calibration and
validation
• Compare simulation results
USDA Conservation Practices
M
J
K
I
F
G
2006
12,714 ac
38% of ag
15% of total
N
Stream Gauging Station
Watershed Boundary
Floodplains / Swamps
O
Water Quality Effects of Current CPs
Load at HRU Outlets
5.5 %
21 9 %
21.9
21.6 %
Sediment
20.1 %
TN
3.8 %
Reductions at B
TP
17.6 %
Alternative CP Scenarios
• Calibration and validation
• Impacts of riparian forest buffers (RFB)
• Impacts
I
t off conservation
ti practices
ti
(CPs)
(CP )
Conventional Conservation Practices
• Crop management practice (CMP)
►
grassed
d waterways,
t
tterraces, contour
t
farming,
f
i
and
d
conservation tillage
• Nutrient
N t i t managementt practice
ti (NMP)
►
whole-farm plans to reduce both nitrogen and
phosphorus application rates by 30%
• From 11% of the watershed (current condition)
to 41% of the watershed (maximum
implementation)
Effect of Conventional CPs
Cho, J., G. Vellidis, D.D. Bosch, R. Lowrance, and T. Strickland. 2010. Water quality effects of simulated conservation
practice scenarios in the Little River Experimental Watershed. Journal of Soil and Water Conservation (in press).
Effect of Riparian Forest Buffers (RFB)
• 0 m constant FILTERW
►
No RFB (Min.)
• 14 m variable FILTERW
►
Current distribution of RFB
►
Current – 88% of streams with RFB
• 14 m constant FILTERW
►
100% of streams with RFB (Max.)
NMP
Effect of Riparian Forest Buffers
Load at HRU Outlets
120
14
75%
80%
8
6
4
21%
Tota l Nitrogen Load (kg/ha)
Se diment Load (ton
n/ha)
100
80
32%
37%
7%
60
40
20
2
Total P
Phosphorus Load
d (kg/ha)
16
12
10
18
14
12
8
6
4
Sediment
20%
NMP
0
0
No RFB (0 m Current RFB Maximum RFB
FILTERW)
(14 m variable (14 m constant
FILTERW)
FILTERW)
80%
10
2
0
76%
No RFB (0 m Current RFB Maximum RFB
FILTERW) (14 m variable (14 m constant
FILTERW)
FILTERW)
Total Nitrogen
No RFB (0 m Current RFB Maximum RFB
FILTERW)
(14 m variable (14 m constant
FILTERW)
FILTERW)
Total Phosphorus
Effect of Riparian Forest Buffers
25
Reduction Rates
Sediment
21.6%
Current RFB
4
Sediment
20
Total nitrogen
Maximum RFB
21.7%
3
Total phosphorus
Reductio
on Rate (%)
Sedim
ment Load from HRU to Stream
m (ton/ha)
5
2
15
10
3.8%
1.0%
1
5
0.1%
0
0
1st
2nd
3rd
Stream Order
4th
5th
1st
2nd
3rd
4th
Stream order
Cho, J., G. Vellidis, D.D. Bosch, R. Lowrance, and T. Strickland. 2010. Water quality effects of simulated conservation
practice scenarios in the Little River Experimental Watershed. Journal of Soil and Water Conservation (in press).
5th
Conclusions
• Not able to see CP effects in water quality record
• LREW features ((flood p
plains,, RFBs)) make SWAT
modeling difficult
• Modeling shows the current CPs have positive
water quality effects
Conclusions
• RFBs have the greatest positive effect on water
quality
• Restoring RFBs on all stream segments (from
88% to 100%), but especially low order streams
has almost the same effect as putting all ag land
into conventional CPs (from 11% to 41% of
LREW)
Objectives
j
• To evaluate the effects of past and potential
conservation practices on water quality in a coastal
plain watershed;
• To evaluate social and economic factors influencing
implementation and maintenance of these
conservation practices; and
• Train and educate stakeholders about these issues
and the effects that their actions have on watershed
watershedscale water quality.
LREW Conceptual
p
Model
LREW Conceptual Model
MCDA
SWAT
Multi-Criteria Decision Analysis
y ((MCDA))
• Criterium DecisionPlus 3.0
►
►
►
helps users make complex decisions among
alternatives involving multiple criteria
calculates which alternative best meets the decisiondecision
maker's criteria
how likely that alternative is to be truly the best choice
in the face of uncertainty
NRCS Conservation Practices Used
Code
Conservation Practices (All possible in LREW)
Code
Conservation Practices (All possible in LREW)
1
Conservation Cover
18
Pond
2
Contour Farming
19
Prescribed Grazing
3
Cover & Green Manure Crop
20
Residue Management, No-Till & Strip-Till
4
Field Border
21
Residue Management, Seasonal
5
Filter Strips
22
Riparian Forest Buffer
6
Forest Site Preparation
23
Silvopasture Establishment
7
Forest Stand Improvement
24
Stream Crossing
8
Grassed Waterways
25
Streambank & Shoreline Protection
9
Grazing Management
26
Strip Cropping (contour)
10
Heavy Use Area Protection
27
Terrace
11
Irrigation Storage Reservoir
28
Tree Planting
12
Irrigation Water Management
29
Tree/Shrub Establishment
13
Nutrient Management
30
Trees - Already Established
14
Pasture & Hayland Management
31
Use Exclusion
15
Pasture & Hayland Planting
32
Waste Storage Facility
16
Pest Management
33
Water & Sediment Control Basin
17
Pest Management
Refined
f
Model
• 100 “serious”
farmers in LREW
• Weights
collected from
personal
interviews with
25 farmers
• Weights are
averages of 25
interviews
Model Farm
(142 ha)
Results
Results
Vellidis, G, S. Crow Lowrance, J. Mullen, P. Murphy, A. Smith, R. Lowrance, and D. Bosch. 2009. A multi-criteria decision model
for assessing conservation practice adoption. In: Bregt, A., S. Wolfert, J.E. Wien, and C. Lokhorst (Eds.), Proceedings of the EFITA
Conference ‘09, Wageningen, the Netherlands, pp. 319-327.
Modeling the Impact of RKN on Cotton
Biomass and Yield
• To adapt CSM-CROPGRO-Cotton for simulating
growth and yield of cotton plants infected with
RKN
• To study the study the potential impact of the
interaction RKN population-drought stress
through simulations of growth and yield
• Brenda Ortiz – former Ph.D. student
Experimental Data (2007)
DP 458 BG/RR cultivar
Control treatment (1+)
Model Calibration
Cultivar
coefficients
Soil water holding
characteristics
Nonfumigated treatments
Modeling RKN damage
Hyp.2:
H
2 Root
R t length
l
th per
unit root weight
Hyp.1:
H
1 Assimilate
A i il t
consumption by RKN
Modeling Evaluation
Experimental field (2001)
Producer’s field (2006)
Model Calibration
• Soil water content
• Leaf area index (LAI)
Ortiz, B.V., G. Hoogenboom, G. Vellidis, K. Boote, R.F. Davis,
C. Perry. 2009. Adapting the CROPGRO-cotton model to
simulate cotton biomass and yield under southern root-knot
root knot
nematode parasitism. Transactions of ASABE 52(6):2129-2140.
• Leaf weight
• Stem and petiole weight
• Boll weight
• Number of bolls per area
• Total biomass weight
• Seed cotton weight
Results
Management
Zones
Zone 1
Zone 2
3000
Zone 3
2000
22% (793 kg/ha) less
seed cotton in Zone 3
compared
d to
t Z
Zone 1
0
0
30
60
90
120
150
DAP
[a]
Zone
1
2
3
Seed cotton weight (kg ha-1)
Simulated
16% 3566
7.5% 2998
22% 2773
Observed
PD (%)
3316 12%
70
7.0
2909 19%
3.0
2354
[b]
29% 15.1
400000
Zone 1
Zone 2
Zone 3
RKN-Zone 1
RKN-Zone 2
RKN-Zone 3
5
4
350000
300000
250000
3
200000
150000
2
100000
1
0
50000
0
30
60
90
DAP
120
150
0
RKN-J2 150000 cm-3 of soil
1000
Assimilate rreduction [g(CH2O) m-2 d-1]
Seed cotton weight (kg ha-1)
4000
Thank you for your attention !!
For more information:
Dr. George Vellidis
Bi l i l & Agricultural
Biological
A i lt l E
Engineering
i
i D
Dept.
t
University of Georgia
USA
voice: 229.386.7274
e-mail: yiorgos@uga.edu
fax: 229.386.3958