Greg Easson, H. G. Momm The University of Mississippi Ronald Bingner
description
Transcript of Greg Easson, H. G. Momm The University of Mississippi Ronald Bingner
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation for the Integration of a Virtual Evapotranspiration Sensor Based on VIIRS and Passive Microwave Sensors into the Annualized
Agricultural Non-Point Source (AnnAGNPS) Pollution Model
Greg Easson, H. G. MommThe University of Mississippi
Ronald BingnerUSDA – ARS – National Sedimentation Laboratory
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Project Objectives
• To investigate the feasibility of using existing NASA results as source of ET estimates for AnnAGNPS pollution model
• To evaluate the continuity of the NASA-based remotely sensed ET estimates by the future missions
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Project Rationale
• Evapotranspiration (ET) plays an important role for modeling surface-lower atmospheric flux processes
• ET estimates in a continuous and spatially distributed fashion represents a challenge for scientists
• Remote sensing-based techniques are sought as an possible alternative
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Background: AnnAGNPS
• The Annualized Agricultural Non-Point Source
• Pollution model is a continuous watershed-scale computer simulation tool used to generate loading estimates for some constituents of agricultural non-point source pollution
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Background: AnnAGNPS (continued)
• Developed by USDA-NRCS • Event driven model• Simulates
– Surface flow– Sediment– Nutrients– Pesticides
• Used to evaluate Best Management Practices
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Background: AnnAGNPS (continued)
• Watershed is divided into cells
• Each of these cells requires 22 parameters
• Climate data is derived from field weather stations located within or nearby the watershed
• Thiessen polygon method
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Background: AnnAGNPS (continued)
• Problem when field weather stations are sparse or even non-existing
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Project Objectives
• To investigate the feasibility of using existing NASA results as source of ET estimates for AnnAGNPS pollution model
• To evaluate the continuity of the NASA-based remotely sensed ET estimates by the future missions
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS
• Modifications to AnnAGNPS
• Concept of “Virtual” field weather stations
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• Modifications to AnnAGNPS
MODIS ET DATA
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• Study SiteLong history of hydrologic work
Extensive infrastructure
USDA-ARS NSL past and ongoing projects
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• MOD16 daily images for 2004
• Provided by scientists at The University of Montana (Nishida et al., 2003, Cleugh et al., 2007, and Mu et al., 2007).
• Ground sampling distance (GSD) of approximately 5,000 meters
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• Two AnnAGNPS simulations– ET computed using the Penman equation– ET provided proxy-MOD16
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• Results:– Average
watershed ET
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DAY OF YEAR
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AnnAGNPS ET
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• Results:– Daily runoff
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g)
M O D IS
AnnA G N PS
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• Results:– Spatial
distribution of the 2004 annual percent difference between ET from AnnAGNPS and from MODIS
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Evaluation of the Integration of NASA Results into AnnAGNPS (continued)
• Results:– Spatial
distribution of the 2004 annual percent difference between runoff from AnnAGNPS and from MODIS
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Project Objectives
• To investigate the feasibility of using existing NASA results as source of ET estimates for AnnAGNPS pollution model
• To evaluate the continuity of the NASA-based remotely sensed ET estimates by the future missions
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results
• Due to the lack of published methodology describing the generation of ET estimates from VIIRS data, a different approach was considered
• Using the relationship between ET, VI, and LST, daily ET maps were generated from models created using multivariate linear regression techniques
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Lambin and Ehrlich’s feature space
Vegetation Index-1.0 1.0
Surf
ace
Tem
per
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eNo Evapotranspiration
Max Evapotranspiration
SoilMoistureAvailability
-0.2
No Evapotranspiration
Max Evapotranspiration
SurfaceResistance
Baresoil
PartialCover
Fullcover
Source: simplified from Lambin and Ehrlich (1996)
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Daily images from April 01, 2004 to July 31, 2004
• Re-sampled to 5,000 GSD
250 meter MODIS NDVI
pixels
400 meter proxy-VIIRS NDVI
pixels
1,000 meter MODIS LST
pixels
750 meter proxy-VIIRS LST pixels
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• “Virtual” stations
Field
“Virtual”
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Simplified representation
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1 2
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The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Simplified representation
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The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Model development– Stations 127 to 136 (physical stations)– Stepwise backward elimination (P-value
associated with Pearson’s Chi-Squared). – One model per day for each of the
sensors considered
542
32
210 LSTNDVILSTNDVILSTNDVIPET
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Adjusted R2 > 0.25 DOY 0 1 2 3 4 5 R2 ADJ-R2
F-STA 0 1 2 3 4 5 R2 ADJ-R2F-STA
93 0.13381 - - -0.05460 0.00000 - 0.25 0.04 1.18 1.07148 -2.21991 -0.00360 -0.35179 - 0.00874 0.99 0.98 118.4994 -239.47100 -65.53352 1.73094 - -0.00312 0.22224 0.29 -0.28 0.50 2.94757 1.90864 -0.02281 0.40994 0.00005 -0.00782 0.98 0.96 48.3495 2261.17000 -311.90640 -14.90215 10.04561 0.02455 1.03056 0.51 -0.11 0.82 2.80584 - -0.01849 -0.29084 0.00003 0.00097 0.94 0.90 20.6397 -18.18050 -2.25278 0.13212 -1.31309 -0.00024 0.01132 0.81 0.48 2.49 -14.26829 2.60058 0.09567 - -0.00016 -0.00907 0.95 0.89 15.1099 27.47680 15.58459 -0.22177 - 0.00044 -0.05232 0.72 0.50 3.26 0.11438 - - 0.55804 0.00000 -0.00190 0.21 -0.19 0.52
100 -0.04064 - - - 0.00000 -0.00118 0.40 0.23 2.33 -28.11020 -5.30128 0.21000 - -0.00039 0.01811 0.90 0.82 11.32105 30.69027 -45.16900 -0.10381 0.28977 - 0.15251 0.60 0.28 1.86 41.46143 -41.50556 -0.19602 0.65262 0.00019 0.13874 0.81 0.58 3.49106 15.03754 - -0.04998 - - -0.00060 0.52 0.39 3.83 -459.58120 452.38270 2.15650 2.27818 -0.00204 -1.53276 0.72 0.37 2.04107 7.02129 -1.94150 -0.04333 -1.79491 0.00006 0.01385 0.79 0.44 2.27 0.34512 -0.76174 - 0.68378 - - 0.20 -0.20 0.50108 282.44890 66.48745 -2.03904 6.05547 0.00369 -0.24735 0.55 -0.01 0.98 -5.25506 -2.63875 0.04317 - -0.00008 0.00888 0.60 0.29 1.91109 -21.58239 1.18308 0.15420 - -0.00027 -0.00359 0.75 0.56 3.81 28.23039 -11.26670 -0.17415 - 0.00027 0.03752 0.97 0.92 21.41117 40.03078 - -0.27486 -0.19439 0.00047 0.00077 0.71 0.49 3.13 7.28120 -3.62520 -0.04139 - 0.00006 0.01225 0.78 0.60 4.32118 0.21730 -1.19297 - 0.53574 - 0.00201 0.17 -0.25 0.40 3.93203 2.98366 -0.03465 0.17984 0.00007 -0.01079 0.95 0.89 16.06119 1.19290 - - - -0.00001 0.00074 0.32 0.12 1.63 0.03484 1.19512 - 0.32776 0.00000 -0.00536 0.98 0.97 77.90123 -8.17487 0.38236 0.05918 -0.33611 -0.00011 - 0.77 0.46 2.52 0.81756 0.68723 -0.00680 - 0.00002 -0.00261 0.83 0.61 3.76124 -0.02989 0.22271 0.00023 -0.20614 - - 0.63 0.45 3.44 0.22753 - -0.00112 -0.29643 0.00000 0.00122 0.63 0.25 1.67125 -68.55057 -9.43470 0.49616 -1.04590 -0.00090 0.03671 0.79 0.54 3.09 -9.72302 1.23866 0.06844 - -0.00012 -0.00422 0.96 0.93 29.13126 -20.51270 1.42738 0.14354 -1.06332 -0.00025 - 0.94 0.89 19.28 0.29080 - - -0.50434 0.00000 0.00229 0.94 0.91 27.66127 0.23051 -0.30620 - 0.27479 - - 0.06 -0.21 0.21 23.32905 -9.48630 -0.14532 -0.39403 0.00023 0.03309 0.93 0.85 10.95128 198.54200 -12.47922 -1.27313 - 0.00204 0.04087 0.38 -0.12 0.77 0.63347 - -0.00374 - 0.00001 - 0.10 -0.15 0.41131 7.25279 - -0.04959 0.54734 0.00009 -0.00174 0.71 0.12 1.20 -3.53358 -6.10091 0.03994 1.46324 -0.00009 0.01519 0.98 0.89 10.96132 20.14604 - -0.13932 -2.15005 0.00024 0.00752 0.94 0.85 11.21 -1.17814 -3.58840 0.01818 1.04150 -0.00004 0.00836 0.87 0.54 2.62141 -12.59578 -6.90655 0.10069 -1.97638 -0.00020 0.03050 0.94 0.86 12.48 -1.19733 - 0.00929 - -0.00002 - 0.18 -0.06 0.76142 -8.17611 -1.07132 0.06055 - -0.00011 0.00386 0.69 0.43 2.73 0.14048 - - 0.94713 0.00000 -0.00413 0.34 -0.06 0.85143 -10.12211 -12.99157 0.09306 -2.51812 -0.00020 0.05240 0.26 -0.66 0.28 1.19588 0.80528 -0.00965 - 0.00002 -0.00323 0.91 0.72 4.82144 -0.34563 0.91042 0.00214 0.36996 - -0.00441 0.82 0.67 5.58 0.17637 - - 0.69858 0.00000 -0.00273 0.88 0.82 14.89152 104.16520 -22.61602 -0.68461 - 0.00113 0.07589 0.92 0.76 5.75 -19.06033 17.55679 0.09959 - -0.00011 -0.06106 0.90 0.69 4.34154 30.10675 18.96722 -0.23230 -2.14792 0.00043 -0.05536 0.74 0.31 1.72 -291.20190 84.01778 1.76257 -4.44252 -0.00266 -0.26168 0.86 0.50 2.42156 -0.92031 -1.63420 0.01142 2.16361 -0.00002 - 0.61 0.29 1.93 2.82017 -8.38684 -0.00535 5.29105 - 0.01217 0.94 0.83 8.10160 0.01534 0.66372 - 0.36638 0.00000 -0.00362 0.62 0.12 1.24 0.34938 0.17215 -0.00183 - 0.00000 -0.00070 0.96 0.89 12.68163 -2.87473 5.56757 0.01151 1.21802 - -0.02323 0.59 0.26 1.80 -0.00020 -0.82422 0.00287 0.95587 0.00000 -0.00078 0.95 0.89 16.21164 0.11022 0.69198 - -0.29946 - -0.00144 0.59 0.38 2.84 -1.65313 -1.15712 0.01531 - -0.00003 0.00374 0.49 -0.01 0.98170 -0.40824 1.04074 0.00317 -0.23398 0.00000 -0.00299 0.91 0.75 5.72 -0.53358 0.04167 0.00563 - -0.00001 - 0.57 0.14 1.32171 -1.53995 3.16980 0.00817 - -0.00001 -0.01081 0.59 0.19 1.46 1.97895 -1.95457 -0.01188 -0.18245 0.00002 0.00744 0.97 0.91 14.39184 -1.00342 3.35560 0.00515 1.88495 - -0.01726 0.95 0.89 15.24 9.35118 -6.06995 -0.06120 1.73237 0.00011 0.01452 1.00 0.99 124.77186 0.14622 - - -1.36564 0.00000 0.00383 0.36 0.04 1.11 -0.95869 1.84131 0.00519 -0.58123 -0.00001 -0.00509 0.96 0.89 13.88187 -9.26065 0.10186 0.06233 -0.23920 -0.00010 - 0.66 0.39 2.41 -0.17414 0.82210 0.00066 -0.43834 - -0.00124 0.55 0.19 1.54188 -3.14018 16.77496 - 15.40937 0.00008 -0.10720 0.57 0.23 1.68 -0.81386 5.38148 -0.00229 -6.45199 - 0.00418 1.00 0.99 184.00192 16.24589 38.55536 -0.19375 -8.56135 0.00043 -0.09389 0.59 0.08 1.16 1.29579 -3.99527 - 3.34977 - - 0.52 0.38 3.80193 0.81794 -2.16803 - 0.50127 -0.00001 0.00547 0.63 0.34 2.14 -0.27020 0.66701 0.00151 -0.52171 0.00000 - 0.59 0.26 1.80194 0.02522 - - 9.71569 0.00005 -0.04153 0.31 -0.03 0.92 -3.40011 11.50713 - -17.17810 -0.00005 0.03979 0.96 0.90 17.46196 -3.92925 13.31728 - - 0.00005 -0.04527 0.63 0.40 2.81 -5.24323 110.89420 -0.23284 84.27215 0.00133 -0.77803 0.74 0.08 1.13197 0.74048 -2.06183 - 1.64597 - - 0.38 0.21 2.17 1.43652 -1.00395 -0.00759 - 0.00001 0.00359 0.46 0.04 1.08200 0.17025 0.04323 - - 0.00000 - 0.08 -0.23 0.25 0.49038 -1.13324 - - 0.00000 0.00386 0.96 0.91 21.59201 0.11276 -0.20308 0.00023 0.19229 - - 0.73 0.60 5.41 0.90810 -2.16446 - 1.16962 0.00000 0.00205 0.77 0.59 4.22202 15.46965 - -0.10437 - 0.00018 - 0.35 0.17 1.92 -0.81103 0.89861 0.00412 - 0.00000 -0.00292 0.66 0.39 2.41203 6.74516 - -0.04538 - 0.00008 - 0.24 0.02 1.09 4.96079 0.61399 -0.03511 0.25224 0.00006 -0.00314 0.94 0.87 12.71204 8.65474 8.65207 -0.07974 - 0.00017 -0.02934 0.39 -0.10 0.79 -0.26944 1.77669 -0.00183 -0.85492 0.00001 -0.00252 0.82 0.60 3.71206 -6.18092 -10.20331 0.07000 -6.64358 -0.00020 0.06723 0.62 0.15 1.33 0.11327 - - - 0.00000 -0.00017 0.07 -0.30 0.19210 -5.06153 13.93010 - - 0.00006 -0.04661 0.11 -0.34 0.24 18.83512 -41.19674 -0.02939 20.73188 - 0.04186 0.45 0.01 1.02
MODIS VIIRS
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Results– Variability of models performance– Adjusted R2 – Predictors
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
R2 = 0.0018
0.00
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MODIS Derived PET (inches)
VII
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PE
T (i
nche
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R2 = 0.9749
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MODIS Derived PET (inches)
VII
RS
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PE
T (i
nche
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R2 = 0.4154
0.00
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MODIS Derived PET (inches)
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ived
PE
T (i
nche
s)
DOY 105 DOY 154 All DOY considered
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
• Simplified representation
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The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Comparison of Existing and Future NASA Results (continued)
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions
• Linking MODIS ET with AnnAGNPS was successfully performed.
•
• The use of MODIS ET can reduce the need to collect/generate dew point, wind speed, and cloud coverage.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions (continued)
• Reducing uncertainty in input parameters will reduce the uncertainty in the model results.
• In addition, these values usually have temporal and spatial variability that are not easily taken into consideration when computing ET values.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions (continued)
• MODIS-ET produced 35% less ET then AnnAGNPS-ET and resulted in a 10% increase in runoff.
• Large watershed system, climate parameters can be highly variable.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions (continued)
• MODIS-ET provided a more comprehensive spatial variability capability than is not often available from measured climate stations.
• Additional remotely sensed data: precipitation and temperature.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions (continued)
• The second objective of this research project was to investigate the continuity of future NASA missions in providing ET estimates to AnnAGNPS simulation model.
• Daily NDVI and LST maps from MODIS and proxy-VIIRS data were used to create two sets of daily ET maps.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions (continued)
• Direct comparison between these two sets of daily ET maps indicates that the next generation of moderate resolution sensor will continue to be a potential source of ET estimates to simulation models such as AnnAGNPS.
• The VIIRS’s physical design features, such as improved signal to noise ratio and the attenuation of the “bowtie-shaped” footprint at large scan angles were not considered.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions (continued)
• The spatial variability demonstrated by the VIIRS-based LST map can be in part attributed to the downscaling technique used in the simulation process.
• Further investigation should be conducted to estimate ET for different land use/land cover classes.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Conclusions (continued)
• There are situations were the ET maps generated from VIIRS and from MODIS agreed.
• This demonstrates the potential of VIIRS to be used as the continuity mission, in providing ET estimates for AnnAGNPS pollution model.
The University of Mississippi Geoinformatics CenterNASA RPC – March, 2 2009
Acknowledgements
• Institute for Technology Development
• National Sedimentation Laboratory
• The University of Montana
• NASA and the University of Southern Mississippi