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Effects of Nonpoint Source
Marsh Loading on Complex
Estuaries
Edwin A. Roehl, Jr.
John B. Cook, PE
Advanced Data Mining Intl
Greenville, SC
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South Carolina coastal estuaries
Myrtle Beach
Charleston
Beaufort
Savannah
Georgetown
Grand Strand
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A brief review of tidal dynamics
Freshwater
Saltwater
Saltwater-FreshwaterInterface
RiverineInputs
Coastal Inputs
“…estuaries may never really be steady-state
systems; they may be trying to reach a balance
they never achieve.”
Keith Dyer, from Estuaries – A Physical Introduction (1997)
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Difficult to wrestle down nonpoint
source effects
Difficult to measure and predict NPS impacts on
upland areas
Data sets sparse as compared to point source data
Equations and models to estimate loads can have large
prediction errors (50-100%)
NPS problem compounded on the coast
Low-gradient system with little or no slope
Tidal complexities of receiving stream
Poorly defined drainage areas
Limited understanding of runoff process along the coast
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Complex forces on a tidal river
Overland flow
from watershed
Tidal forcing
from ocean
connection
•Small contributing watershed
•Little freshwater inflow
•Tidally dominated
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Consider alternative approach to
NPS modeling
Data mining Transforming data into information
Amalgamation of techniques from various
disciplines: information theory, signal processing,
statistics, machine learning, chaos theory,
advanced visualization
The physics is manifested in the data
Need to extract the information from large
data sets of continuous monitoring w/in
estuary
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Artificial Neural Networks (ANN) models
Mathematical representation of the brain
provides complicated behaviors from “simple” components
- neurons and synapses
models created by training the ANN to learn relationships
between variables in example data
form of machine learning from Artificial Intelligence (AI)
x1
x2
x3
x4
x5
y1
y2
inputs outputs
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3D response surfaces for SC, WL, Q
Surface created by ANN model
“Unseen” variables set to constant value
Manifestation of historical behavior of system
Provides insight into the process dynamics or physics
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ANN model performance for
hydrodynamic behavior
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Data mining NPS – Consider Cooper
River Estuary case study
Sensitivity of DO to rainfall, water
tidal-level flushing action and tidal
range determined
Model able to simulate rainfall
effects/amounts
System had long-term data bases
>3 years of 15-minute WL, DO, SC,
WT
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Cooper River
Estuary
Area of no
development
Little impact
from all point
sources
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Signal decomposition of water level
Periodic component
– Tidal range
Chaotic component –
Filtered water level
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Dissolved oxygen (DO) dynamics
Measured DO time
series
Dissolved-oxygen deficit
= difference b/w saturation
and measured
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Or, in equation form:
DO deficit (DOD) =
DO [saturated f(T and salinity)]
- DO (measured)
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Effects of rainfall
on Cooper RiverZ-axis – DOD
X & Y axis – 1- and 3-day
rainfalls
∆2 mg/L
The sensitivity of DOD
to rainfall :
DOD/inch ≈ 2 mg/L/ 8 in.
of rainfall over 2 days
= 0.25 mg/L per inch of
rainfall.
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Cooper River measured and predicted
DO-deficit (DOD) as result of rainfall only
RAINAA=2-day moving window average
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In addition to rainfall effects, response
surfaces show effects of WLs on DOD
1st response surface shows “Low WL” = higher DOD
(range of 3.0 to 4.5 mg/L)
2nd response surface shows “High WL” = lower DOD
(range of 1.5 to 2.8 mg/L)
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Data-Driven model’s accuracy, Cooper R.
3
4
5
6
7
8
9
10
8/21/93 0:30 8/22/93 0:30 8/23/93 0:30 8/24/93 0:30
Date and time
Dis
so
lve
d o
xy
ge
n (
mg
/L)
16
18
20
22
24
26
28
30
32
Te
mp
era
ture
(de
gre
e C
els
ius
)
Measured Neural Network BRANCH/BLTM
Water temperature
Dissolved oxygen
• Mixing - Tides, Flows from 3 Rivers
• Weather (T, P Dew Point)
• Point Discharge Wastewater
Treatment Plants
• Non-Point Discharges - rainfall,
50% overbank storage
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Beaufort River
Estuary
Complex tidal system
>9 foot tide range
Net flow to the north
Model developed for
TMDL and NPDES permits
Model simulates 3.5 years
of historical conditions
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Decision Support Systems make “what-ifs”
easy for Beaufort River TMDL
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Savannah Harbor deepening
Model hydrodynamics
How far does salinity intrude when Harbor is deepened?
What happens when fresh water flows are low?
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Accuracy insights: EFDC vs. ANN model
for Savannah River, GA
EFDC R2=0.10M2M R2=0.90
Salin
ity,
Pra
ctic
al S
alin
ity
Un
its
Stre
amfl
ow
(cf
s)
EFDC unable to
predict peaksSource: Conrads, P., and Greenfield, J., (2008)
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Simulate reduced freshwater flows with
EFDC and ANN model and compare
EFDC R2=0.10M2M R2=0.90
Salin
ity,
Pra
ctic
al S
alin
ity
Un
its
Stre
amfl
ow
(cf
s)
Source: Conrads, P., and Greenfield, J., (2008)
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Summary for NPS Estuary Modeling
Stormwater and tidal effects (as well as point
source impacts) can be quantified using Data
Mining techniques
3D visualization gives valuable insight into
process physics of the system
Data Mining can be used with traditional
approaches to minimize errors in load
estimates from NPS
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Questions
Contact:
John B. Cook
Advanced Data Mining
Intl; Greenville, SC
843.513.2130
www.advdmi.com