Water-Quality Modeling of Lake Garda › ... › 2018 › 05 › Chapra.pdfSteve Chapra GARDEN 2018...
Transcript of Water-Quality Modeling of Lake Garda › ... › 2018 › 05 › Chapra.pdfSteve Chapra GARDEN 2018...
Steve Chapra
GARDEN 2018
10 April 2018
“Building the Perfect Beast”
Water-Quality Modelingof Lake Garda
OUTLINE
Assumptions
Sediment-Water Interactions
HABs
Upper Food Web
Chemistry
The Po as a System
Conclusions
L2K: PHYSICAL MODEL
epi (1)
bottom
hypo
(4)
A0
A1
meta (2)
A3
top hypo (3)
A2H
H1
H2
H3
H4
Temp
cond
Qin
Qp Qe
Qout
STATE VARIABLES
(mass balances)Variable Units Variable Units
Temperature C Diatoms mgC/L
Specific conductance umhos Greens mgC/L
Inorganic suspended solids mgD/L Cyanobacteria fix mgC/L
Particulate organic carbon mgC/L Cyanobacteria-non fix mgC/L
Dissolved organic carbon mgC/L Nanoplankton mgC/L
Organic nitrogen mgN/L Herbivorous zooplankton mgC/L
Ammonia mgN/L Carnivorous zooplankton mgC/L
Nitrate mgN/L Dissolved methane mgCH4/L
Organic phosphorus mgP/L Sulfate mgSO4/L
Bioavailable phosphorus mgP/L Hydrogen Sulfide mgS/L
Detrital organic silica mgSi/L Calcium mgCa/L
Bioavailable available silica mgSi/L Total inorganic carbon
Dissolved oxygen mgO2/L Alkalinity mgCaCO3/L
mol/L
OTHER WATER-QUALITY
OUTPUTDerived variables Sediment-water fluxes Air-water gas fluxes
Carbonaceous BOD Oxygen Oxygen
Carbon dioxide Total inorganic carbon Carbon dioxide
Bicarbonate Bioavailable phosphorus Methane
Carbonate Ammonia Nitrous oxide
Total chlorophyll a Nitrate
Extinction coefficient Sulfate
Secchi depth Hydrogen sulfide
Turbidity Nitrogen gas
pH Nitrous oxide
Alkalinity Dissolved organic carbon
Specific conductance Dissolved methane
Total Kjeldahl N Methane gas
Total organic carbon
Particulate organic carbon
Hydrogen sulfide
WATER COLUMN KINETICS
ran
dn
s
mi
cd
h
hna
hpi
rnc
rpc
s
ap
s
nnn
rap
p
o
x
g
zc
o
sod
o
s
cp
no
s
po
s
zh
g
e
e
d
rca
r
r
r
rca
rpc
rnc
ASSUMPTIONSState of the art physics
Water motion
Heat budget & temperature
Boundary layers
State of the art biology & chemistry
Multiple algal groups (including HABs)
Upper food chain (grazers)
Macrochemistry (pH, major ions, calcite, etc.)
Sediment-water interactions
Gas transfer (SOD, methane flux, etc.)
Nutrient fluxes
Sediment chemistry (beyond nutrients)
MODELLING
Sediment/Water
Interactions in Lakes(SOD and Nutrient Fluxes)
sediments
epi
air
SEDIMENT-WATER PROCESSES“THE MISSING LINK OF WATER-QUALITY MODELLING”
Organic
Matter
SOD
Nutrients
N, P
Fluxes
SEWAGE,
RUNOFF PHOTOSYNTHESIS
hypo
Nutrients
Organic
Matter
Organic
Matter
Oxygen
Nutrients?
Short-term Effects:
O2 Depletion and
Internal Loading
Esthwaite Water, England
Mortimer (1971)
settling
p1
inflow outflow
SHAGAWA
LAKE,
MINNESOTA 0
20
40
60
1965 1967 1969 1971 1973 1975 1977 1979
NO RELEASE
RELEASE
burial
p2
release
WASTE TREATMENT
Long-term Effects:
Retarded Recovery
SOD
(g/m2/d)
0
4
8
0 100 200
COD (mgO/L)
THE “SQUARE-ROOT” RELATIONSHIP
OF SEDIMENT OXYGEN DEMAND
AND OVERENRICHMENT
SOD = a COD0.5
WHERE DOES NONLINEARITY
COME FROM?
Loss of carbon as methane
gas in anaerobic sediments
Competition between reaction
and diffusion in aerobic
surface sediment
LOSS OF CARBON AS METHANE GAS
IN ANAEROBIC SEDIMENTSA
CT
IVE
SE
DIM
EN
T L
AY
ER
WA
TE
R C
OL
UM
N
ANAEROBIC ZONE
AEROBIC ZONE
PRODUCTION OF
CH4(aq) CH4(aq) CH4(g)
If saturation exceeded
CH4(aq)
SOD
POC FLUX
POC
CO2
0
2
2 D
d c
dzSC
2 c JD s CCSODmax *
CSODmax
0
5
10
0 20 40 60
SOD
(g/m2/d)
Jc* (g/m2/d)
SOD = Jc*
SQUARE-ROOT EFFECT DUE
TO BUBBLE FORMATION
Mass Balance:
Flux
Mass Balance
COMPETITION BETWEEN REACTION AND
DIFFUSION IN AEROBIC SURFACE SEDIMENT
Flux Balance (divide by A):
1110
1
1 ckVAcvAcvdt
dcV b -- 1110
1
1 ckVAcvAcvdt
dcV b -- 1110
1
1 ckVAcvAcvdt
dcV b -- 1110s
1
1 ckVAcvAcvdt
dcV b --
10
1
1 cvcvdt
dcH b
--10s
1
1 kH1c1cvcvdt
dcH b
--
Jn = rnavaa + vonno
no1
no2 na2
na1
o
nn2
nn1 N2
N2
N2
aerobic
anaerobic
overlying water
deep sediments
ac
tive
sed
ime
nts
O2
overlying water
deep sediments
ac
tiv
e s
ed
imen
ts
NH4+
anaerobic
JN JNH 4
+
NO3–
aerobic
DIFFUSION/REACTION COMPETITION
IN THE AEROBIC LAYER
Diffusion
Reaction
water
aerobic
anaerobic
0 1 2 3 40
5
10
15
20
0
5
10
15
20
0 1 2 3 4
SOD
JN
SOD = 2.77 Jn
0.6Jn
0.6
R2
= 0.9827R2
= 0.9827
TOTAL SOD = CSOD + NSOD
1
22
2
'
1
22
2*SOD
1
1
SOD1
12SOD
nwo
n
C*noon
cwo
c
CsD
koD
DJar
koD
DJc
CSOD NSOD
0
5
10
0 20 40 60
Jc* (gO/m2/d)
SO
D
(gO
/m2/d
)
TOTAL SOD = CSOD + NSOD
SOD = Jc*
SODmax
SOD
o(0) = 10
o(0) = 4
OXIDATION-REDUCTION
Oxidation:
“REDOX”
Loss of electrons (energy)
Reduction:
Gain of electrons (energy)
Charge is “reduced”
[CH2O] + O2 CO2 + H2O
[CH2O] O2
e–
Oxidized
Reductant
Electron
donor
Reduced
Oxidant
Electron
acceptor
energy
“Aerobic respiration”
REDOX SEQUENCECH2O O2+ CO2
Aerobic respiration
Denitrification
Manganese
reduction
Iron reduction
Sulfate reduction
Methane formation
“methanogenesis”
NO3– N2 + CO2+
CH2O CH4 + CO2+
SO42– HS– + CO2+
FeOOH(s) Fe2+ + CO2+
MnO2(s) Mn2+ + CO2+
PON2
JN
JC
POC2
Aerobic
sediment
Anaerobic
sediment
Deep
sediment
Water
Atmosphere
LOW SULFATE SYSTEMS
(Most lakes)
O2,0
CH4,0
CH4,2
CO2,1
CO2,0
CO2,2
CH4,g
DOC2
DOC1 CH4,1
NH4,2
NH4,0
N2O
N2
NO3,1
NO3,1
O2,0
NH4,1
NH4,2
NH4,0
N2O
N2
NO3,1
NO3,1
O2,0
NH4,1
SO4,1
SO4,2HS2
HS0
HS1
O2,0 SO4,0
HIGH SULFATE SYSTEMS
(Estuaries)
O2,0
NH4,2
NH4,0
N2O
N2
CO2,1
CO2,0 NO3,1
NO3,1
O2,0
NH4,1
POC2
DOC1
CO2,2
JC
JN
PON2DOC2
O2,0
NH4,2
NH4,0
N2O
N2
CO2,1
CO2,0 NO3,1
NO3,1
O2,0
NH4,1
POC2
DOC1 SO4,1
SO4,2HS2
HS0
HS1
O2,0
CO2,2
SO4,0
JC
JN
CH4,0
CH4,2
CH4,1
PON2DOC2
CH4,g
SOME “SIGNIFICANT” LAKES(Iseo)
LAKE ISEO EXAMPLE
High (Present) Sulfate
SO4 = 48.4 mgSO4 L–1
SOD = 7.6285 gO2 m–2 d–1
NSOD = 0.4670 gO2 m–2 d–1
CSOD = 0.0023 gO2 m–2 d–1
SSOD = 7.1591 gO2 m–2 d–1
No Sulfate
SO4 = 0 mgSO4 L–1
SOD = 1.2069 gO2 m–2 d–1
NSOD = 1.1144 gO2 m–2 d–1
CSOD = 0.0926 gO2 m–2 d–1
SSOD = 0 gO2 m–2 d–1
Hypo O2 = 10 mg/L
JC* = 10 gO2 m–2 d–1
Temp = 6.3 oC
Depth = 150 m
Presence of SO4
Bad for lake
Increases SOD
Good for climate
Decreases loss of
methane to atmosphere
Further Research
Effect of meromixis on
sediment mixing
Effect of water motion on
sediment-water exchange
Incorporation of full
chemistry into sediment
models
Harmful Algal Blooms
(HABs)
(a) Diatoms (b) Greens
(d) non-N-fixing Bluegreens
“Microcystis”
(c) N-fixing Bluegreens
“Oscillatoria”
“Good Algae”(i.e., nontoxic,
edible phytoplankton)
Functional Groups
Cyanobacteria
(HABs)(AKA Blue Green Algae)
“The cockroaches
of the water”
Cyanobacteria
Greens
Diatoms
Seasonal Succession of Phytoplankton in Lakes
100
Percent
biomass
(b) Hypereutrophic
0M A M J J A S O N D
Cyano
Greens
Diatoms
0
100
Percent
biomass
(a) Oligotrophic
Temperature
Nutrient limitation
Grazing
Settling/buoyancy
Principal Components Governing
Seasonal Succession Patterns
Why do cyanobacteria win?
0
20
40
60
80
100
0
20
40
60
80
100
0
20
40
60
80
100
0 2010 30 40
oTemperature ( C)
Paerl & Otten 2012
Diatoms
Greens
Bluegreens
sy/x = 6.11
r2 = 0.974
sy/x = 4.44
r2 = 0.986
sy/x = 8.55
r2 = 0.940
NUTRIENT LIMITATION,
SETTLING & GRAZING
Total phytoplankton chlorophyll
DiatomsBluegreens
(Non N-fix)
Greens/
Others
Zooplankton
Bluegreens
(N-fix)
Nitrogen PhosphorusSilica
2050
2090
Critical HABs blooms in USA
High temperature kinetics
Scum formation
Research Issues
High Temperature Growth
Plateau
High-Growth
Temperatureinhibition
0 10 20 30 40
Temperature (oC)
0
0.5
1
1.5
kg,max
(/d)
SEDIMENTS SEDIMENTSSEDIMENTS
WIND
SCUM FORMATION
WIND
Upper Food Chain
FIRST FOOD CHAIN
Herbivorous Zooplankton
Phytoplankton
Carnivorous Zooplankton
SIMPLE HABs MODEL
DiatomsBlue
greens
Others
(Greens)
NitrogenPhosphorus Silica
Herbivorous Zooplankton
Carnivorous Zooplankton
UPPER TROPHIC LEVEL
Bottom-up versus top-down
Where did the zooplankton go?
Invasive species
WQ modeling’s dirty little secret
NITROGEN
SMALL
HERBIVOROUS
CLADOCERANS
LARGE
HERBIVOROUS
CLADOCERANS
SMALL
OMNIVORES
SMALL
HERBIVOROUS
COPEPODS
GREENSBLUE
GREENS
LARGE
DIATOMSSMALL
DIATOMS
PHOSPHORUSSILICON
NAUPLII
PREDATORS LARGE
OMNIVORES
ALEWIFE
NITROGEN
SMALL
HERBIVOROUS
CLADOCERANS
LARGE
HERBIVOROUS
CLADOCERANS
SMALL
OMNIVORES
SMALL
HERBIVOROUS
COPEPODS
GREENSBLUE
GREENS
LARGE
DIATOMSSMALL
DIATOMS
PHOSPHORUSSILICON
NAUPLII
PREDATORS LARGE
OMNIVORES
ALEWIFE
GENERAL, ISSUES, QUESTIONS
AND CHALLENGES(Please indulge me)
Data stewardship
Watershed modeling
Interdisciplinary cooperation
Systems approach
GREAT LAKES TP MODELLoading
Model
TP
Load
WQ
Model
TP
Conc
population,
land useCorrelations
Chla/SD
Conc
DECISION-SUPPORT MODEL
HURON
SUPERIOR
W
W
W
W W W
W
S
SSS
S
S
S
WEST ERIE CENT ERIE EAST ERIE
ONTARIO
MICHIGAN
TP CONCENTRATIONS
50
40
30
20
10
0
10
0
1800 1850 1900 19500
1800 1850 1900 1950
1800 1850 1900 1950
30
20
10
01800 1850 1900 1950
30
20
10
0
1800 1850 1900 1950
30
20
10
01800 1850 1900 1950
10
0
1800 1850 1900 1950
10
0
CENTRAL
ERIE
HURON
MICHIGAN
ONTARIO
EASTERN
ERIE
WESTERN
ERIE
SUPERIOR
eutrophic
nonpoint
point
oligotrophic
0
10
20
1800 1850 1900 1950 2000
TP
(mgP/L)
LAKE ONTARIO
Much better than expected!
(and maybe too much)
The Pre Alpine Italian “Great Lakes”
N
50 km
Garda
Gulf of Genoa
Torino
Pavia
Milano
Cremona
Parma Ferrara
Mantova
Brescia
Como Iseo
Maggiore
SWITZERLAND
FRANCE
PoPo
Po
Po
Lugano
Garda