Remote Sensing for Regional Assessment and Analysis of Minnesota Lake and River Water
Quality
Leif OlmansonMarvin Bauer
Patrick Brezonik
UNIVERSITY OF MINNESOTA
Areas of Research and Accomplishments
• Developed large Landsat water clarity database ~10,500 MN lakes
– Analyzed geospatial and temporal trends of water clarity in Minnesota
• Investigated and evaluated alternative remote sensing systems for regional water quality assessment
• Developed techniques for remote sensing of optically complex river waters using high spatial and spectral resolution airborne imagery
How clear is your Lake?
Lake Water Quality Monitoring: Summary
1. Citizens measure lake clarity
2. Near the same time, satellites collect imagery
4. Clarity of all lakes is classified
~1,000 Lakes monitored
Over 10,000 Lakes monitored
3. Build statistical models
y = -15.583x + 4.6742R2 = 0.84
-2
-1.5
-1
-0.5
0
0.5
1
1.5
2
0.15 0.2 0.25 0.3 0.35 0.4 0.45
TM3:TM1 Ratio
ln(S
DT) -
- met
ers
0
500
1000
1500
2000
2500
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3500
>4 3-4 2-3 1-2 0.5-1 <0.5
Water Clarity (m)
Num
ber o
f Lak
es
Minnesota Lake ClarityLake Level 2005
33‐year “Census” of Minnesota lake clarity with 7 assessments for 1975–2008
Over 10,000 lakes classified for each time periodAll lakes >8 hectares are includedDatabase includes 1‐ 4 measurements per time period
Used for statistical analysis of Lake water clarity
Water Clarity Trends by Ecoregion, 1985 − 2005
75%
15%
10%
93%
1%6%
95%
3%2%
85%
8%7%
68%
27%
5%
80%
12%8%
76%
19%
5%
NLF4,717 lakes
RRV184 lakes
NGP534 lakes
WCBP520 lakes
NMW155 lakes
NCHF3,496 lakes
DLA41 lakes
9,647 lakes assessed in 1985, 1990, 1995, 2000 and 2005
1,039 lakes (10.8%) had trend line change ≥ 10 TSI units
440 (4.6%) improved clarity 599 (6.2%) decreased clarity
0
50
100
150
200
250
<20 20-50 50-150 150-500 >500
Num
ber
of L
akes
Lake Area (acres)
Minnesota Lakes with Trends by Size
0
50
100
150
200
250
300
Type 5 Type 4 Type 3 Type 2 No ID
Num
ber o
f Lak
es
Wetland Type from Bulletin 25
Minnesota Lakes with Trends by Type
Land cover versuswater clarity by depth
within lake watershed
August 25, 2008Imagery
MODIS Terra 500 mCalibrated Radiance
• MODIS 250, 1000 m calibrated radiance• MODIS 8-day surface reflectance
MERIS L1 TOA Calibrated Radiance
• MERIS L2 Surface radiance/reflectance (Bright Pixel method)
• MERIS C2 Water leaving reflectance (radiative transfer simulations-NN method)
Landsat ETM+ SLC off
Comparison and Evaluation of Medium to Low Resolution Satellite Imagery for Regional Lake Water Quality Assessment
Objectives
• Develop the capability for frequent monitoring, of clarity and chlorophyll, in medium-to-large lakes using MODIS and MERIS data.
• Compare alternative sensors.
Landsat ETM+ 30mMERIS 300mMODIS 250 & 500mMODIS 1000m
Reflectance spectra of 15 Minnesota lakes with Landsat, MERIS and MODIS band locations indicated (Menken et al. 2006)
Landsat ETM+ 30mMERIS 300mMODIS 250 & 500mMODIS 1000m
Reflectance spectra of 15 Minnesota lakes with Landsat, MERIS and MODIS band locations indicated (Menken et al. 2006)
Image processing calibration fit and lakes assessed for Landsat, MERIS and MODIS (8/25/08)
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 ha
MERIS L2 140 0.77 56 0.76 300 m 471 300 ha
MERIS C2 186 0.50 75 0.41 300 m 664 250 ha
MODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 haMERIS L2 140 0.77 56 0.76 300 m 471 300 haMERIS C2 186 0.50 75 0.41 300 m 664 250 haMODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Secchi Disk Chl a
Image processing calibration fit and lakes assessed for Landsat, MERIS and MODIS (8/25/08)
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 ha
MERIS L2 140 0.77 56 0.76 300 m 471 300 ha
MERIS C2 186 0.50 75 0.41 300 m 664 250 ha
MODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 haMERIS L2 140 0.77 56 0.76 300 m 471 300 haMERIS C2 186 0.50 75 0.41 300 m 664 250 haMODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 ha
MODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Imagery Product N R2 N R2 Spatial MN lakes # Lake Size
Landsat 280 0.83 177 0.79 30 m 10,500 4 haMERIS L1 229 0.83 90 0.85 300 m 896 150 haMERIS L2 140 0.77 56 0.76 300 m 471 300 haMERIS C2 186 0.50 75 0.41 300 m 664 250 haMODIS L1B 305 0.65 123 0.57 250 m 1,257 125 ha
MODIS L1B 110 0.75 42 0.79 500 m 385 400 haMODIS L1B 7 0.77 6 0.61 1000 m 57 1000 ha
MODIS 8‐day 110 0.75 47 0.78 500 m 385 400 ha
Secchi Disk Chl a
Landsat TM 30 m MODIS 500 m
*14,528 acre lake
Lake Minnetonka* Water QualityAugust 25, 2008
MERIS water clarity MERIS chlorophyll a
Map LegendSD Chl a(m) (μg/L)
Hyperspectral Imagery for Water Quality Assessment of the Mississippi River and its
Major Tributaries in Minnesota
Mississippi River water
Minnesota River water
• Monitor the water quality of optically complex / dynamic rivers.
• Both Phytoplankton or inorganic sediment are optically dominant.
Major Minnesota Rivers
September 5, 2003 Landsat TM imagery
Mississippi River40-45% of flow
20% of TSS load
Minnesota contributes2.9% of total nitrogen flux
2.0% of total phosphorus fluxdelivered to the Gulf of Mexico
St. Croix River25-30% of flow5% of TSS load
Minnesota River25-30% of flow
75% of TSS loadSpring Lake
Discharge (cfs) August 19, 2004 August 15, 2005 August 30, 2007River Site Mean 26,604 Discharge (cfs) 9,130 Discharge (cfs) 7,370 Discharge (cfs) 8,070
Minnesota Jordan 8810 - 33% 3190 - 35% 1840 - 25% 4160 - 52%Mississippi Anoka 11700 - 44% 2770 - 30% 4100 - 56% 1930 - 24%
St. Croix Stillwater 6094 - 23% 3170 - 35% 1430 - 19% 1980 - 24%
Major Minnesota Rivers
September 5, 2003 Landsat TM imagery
Mississippi River40-45% of flow
20% of TSS load
Minnesota contributes2.9% of total nitrogen flux
2.0% of total phosphorus fluxdelivered to the Gulf of Mexico
St. Croix River25-30% of flow5% of TSS load
Minnesota River25-30% of flow
75% of TSS loadSpring Lake
Discharge (cfs) August 19, 2004 August 15, 2005 August 30, 2007River Site Mean 26,604 Discharge (cfs) 9,130 Discharge (cfs) 7,370 Discharge (cfs) 8,070
Minnesota Jordan 8810 - 33% 3190 - 35% 1840 - 25% 4160 - 52%Mississippi Anoka 11700 - 44% 2770 - 30% 4100 - 56% 1930 - 24%
St. Croix Stillwater 6094 - 23% 3170 - 35% 1430 - 19% 1980 - 24%
LN of variable Bands r2
T Tube (cm) 705 0.77–0.91Turbidity (NTU) 705 0.77–0.93
TSS (mg/L) 705 0.77–0.93VSS (mg/L) 705/670 0.80–0.94Chl a (µg/L) 705/670 or 705/620 0.75–0.93
NVSS (mg/L) 705 & 705/670 0.85–0.97a
NVSS/TSS (%) 705 & 705/620 0.73–0.91a
aR2
River Water Quality Model Development *
Characteristic Reflectance Spectra * Used most consistent (2004, 2005 and 2007) best fit band or band combination model for each water quality variable
LN of variable Bands r2
T Tube (cm) 705 0.77–0.91Turbidity (NTU) 705 0.77–0.93
TSS (mg/L) 705 0.77–0.93VSS (mg/L) 705/670 0.80–0.94Chl a (µg/L) 705/670 or 705/620 0.75–0.93
NVSS (mg/L) 705 & 705/670 0.85–0.97a
NVSS/TSS (%) 705 & 705/620 0.73–0.91a
aR2
River Water Quality Model Development *
Characteristic Reflectance Spectra * Used most consistent (2004, 2005 and 2007) best fit band or band combination model for each water quality variable
LN of variable Bands r2
T Tube (cm) 705 0.77–0.91Turbidity (NTU) 705 0.77–0.93
TSS (mg/L) 705 0.77–0.93VSS (mg/L) 705/670 0.80–0.94Chl a (µg/L) 705/670 or 705/620 0.75–0.93
NVSS (mg/L) 705 & 705/670 0.85–0.97a
NVSS/TSS (%) 705 & 705/620 0.73–0.91a
aR2
River Water Quality Model Development *
Characteristic Reflectance Spectra * Used most consistent (2004, 2005 and 2007) best fit band or band combination model for each water quality variable
Pig’s Eye Lake and the Mississippi River at St. Paul showing the transition from
inorganic sediment dominated to phytoplankton dominated
conditions, August 30, 2007.
Turbidity Chlorophyll a NVSS:TSS
Pig’s Eye Lake
Pig’s Eye Lake and the Mississippi River at St. Paul showing the transition from
inorganic sediment dominated to phytoplankton dominated
conditions, August 30, 2007.
Turbidity Chlorophyll a NVSS:TSS
Pig’s Eye Lake