The University of Mississippi Geoinformatics Center NASA RPC – March, 2 2009 Evaluation for the Integration of a Virtual Evapotranspiration Sensor Based.

Slides:



Advertisements
Similar presentations
Land Surface Evaporation 1. Key research issues 2. What we learnt from OASIS 3. Land surface evaporation using remote sensing 4. Data requirements Helen.
Advertisements

Scaling Biomass Measurements for Examining MODIS Derived Vegetation Products Matthew C. Reeves and Maosheng Zhao Numerical Terradynamic Simulation Group.
MONITORING EVAPOTRANSPIRATION USING REMOTELY SENSED DATA, CONSTRAINTS TO POSSIBLE APPLICATIONS IN AFRICA B Chipindu, Agricultural Meteorology Programme,
Land Use Change and Its Effect on Water Quality: A Watershed Level BASINS-SWAT Model in West Georgia Gandhi Raj Bhattarai Diane Hite Upton Hatch Prepared.
The University of Mississippi Geoinformatics Center NASA MRC RPC review meeting, April 2008 Use of NASA Assets for Predicting Wildfire Potential.
Remote Sensing of Hydrological Variables over the Red Arkansas Eric Wood Matthew McCabe Rafal Wojcik Hongbo Su Huilin Gao Justin Sheffield Princeton University.
Princeton University Global Evaluation of a MODIS based Evapotranspiration Product Eric Wood Hongbo Su Matthew McCabe.
1 Lake Eutrophication Change Detection for the Management of Water Resources Michelle L. Aten and Greg Easson University of Mississippi Geoinformatics.
Globally distributed evapotranspiration using remote sensing and CEOP data Eric Wood, Matthew McCabe and Hongbo Su Princeton University.
Remote Mapping of River Channel Morphology March 9, 2003 Carl J. Legleiter Geography Department University of California Santa Barbara.
CSIRO LAND and WATER Estimation of Spatial Actual Evapotranspiration to Close Water Balance in Irrigation Systems 1- Key Research Issues 2- Evapotranspiration.
Dr. Sarawut NINSAWAT GEO Grid Research Group/ITRI/AIST GEO Grid Research Group/ITRI/AIST Development of OGC Framework for Estimating Near Real-time Air.
Impact of Climate Change on Flow in the Upper Mississippi River Basin
Introduction Land surface temperature (LST) measurement is important for understanding climate change, modeling the hydrological and biogeochemical cycles,
Slide 1/32NOAA Soil Moisture/Soil Temperature Workshop, Oak Ridge, TN, 3-5 March, 2009 Value of Ground Network Observations in Development of Satellite.
The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: April, 2008 Evaluation for the Integration of a Virtual Evapotranspiration.
The University of Mississippi Geoinformatics Center NASA MRC RPC: April 2008 Greg Easson, Ph.D.- (PI) Robert Holt, Ph.D.- (Co-PI) A. K. M. Azad Hossain.
Ag. & Biological Engineering
The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: April 2008 Integration of NASA Global Precipitation Measurement.
AVHRR-NDVI satellite data is supplied by the Climate and Water Institute from the Argentinean Agriculture Research Institute (INTA). The NDVI is a normalized.
Scale Effect of Vegetation Index Based Thermal Sharpening: A Simulation Study Based on ASTER Data X.H. Chen a, Y. Yamaguchi a, J. Chen b, Y.S. Shi a a.
Recent advances in remote sensing in hydrology
1 AOD to PM2.5 to AQC – An excel sheet exercise ARSET Applied Remote Sensing Education and Training A project of NASA Applied Sciences Pawan Gupta Salt.
NWS Calibration Workshop, LMRFC March, 2009 Slide 1 Analysis of Evaporation Basic Calibration Workshop March 10-13, 2009 LMRFC.
Pang-Wei Liu 1, Roger De Roo 2, Anthony England 2,3, Jasmeet Judge 1 1. Center for Remote Sensing, Agri. and Bio. Engineering, U. of Florida 2. Atmosphere,
Preliminary Applications of the HL-RDHM within the Colorado Basin River Forecast Center Ed Clark, Hydrologist Presented July 26 th, 2007 as part of the.
1 Exploiting Multisensor Spectral Data to Improve Crop Residue Cover Estimates for Management of Agricultural Water Quality Magda S. Galloza 1, Melba M.
The University of Mississippi Geoinformatics Center NASA MRC RPC – 11 July 2007 Greg Easson, Ph.D. Robert Holt, Ph.D. A. K. M. Azad Hossain University.
Modeling experience of non- point pollution: CREAMS (R. Tumas) EPIC (A. Povilaitis and R.Tumas SWRRBWQ (A. Dumbrauskas and R. Tumas) AGNPS (Sileika and.
A detailed look at the MOD16 ET algorithm Natalie Schultz Heat budget group meeting 7/11/13.
Development and evaluation of Passive Microwave SWE retrieval equations for mountainous area Naoki Mizukami.
William Crosson, Ashutosh Limaye, Charles Laymon National Space Science and Technology Center Huntsville, Alabama, USA Soil Moisture Retrievals Using C-
Reducing Canada's vulnerability to climate change - ESS J28 Earth Science for National Action on Climate Change Canada Water Accounts AET estimates for.
Land Surface Hydrology Research Group Civil and Environmental Engineering University of Washington Land Surface Hydrology Research Group Civil and Environmental.
Canada Centre for Remote Sensing Field measurements and remote sensing-derived maps of vegetation around two arctic communities in Nunavut F. Zhou, W.
Problems Associated with Comparing In Situ Water Quality Measurements to Pollution Model Output for Geographic Analyses Presentation to the Annual Meeting.
Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:
Remote sensing for surface water hydrology RS applications for assessment of hydrometeorological states and fluxes –Soil moisture, snow cover, snow water.
Understanding hydrologic changes: application of the VIC model Vimal Mishra Assistant Professor Indian Institute of Technology (IIT), Gandhinagar
Flux observation: Integrating fluxes derived from ground station and satellite remote sensing 王鹤松 Hesong Wang Institute of atmospheric physics, Chinese.
The University of Mississippi Geoinformatics Center NASA MRC RPC – 11 July 2007 Modeling Non-Point Source Pollution and Erosion into Gulf Coast Bays and.
The University of Mississippi Geoinformatics Center NASA MRC RPC – 11 July 2007 Rapid Prototyping of NASA Next Generation Sensors for the SERVIR System.
The University of Mississippi Geoinformatics Center May 17, 2006 Rapid Prototyping of New NASA Sensor Data into the SERVIR System.
Validation of MODIS Snow Mapping Algorithm Jiancheng Shi Institute for Computational Earth System Science University of California, Santa Barbara.
Hydrological evaluation of satellite precipitation products in La Plata basin 1 Fengge Su, 2 Yang Hong, 3 William L. Crosson, and 4 Dennis P. Lettenmaier.
The University of Mississippi Geoinformatics Center NASA MRC RPC – 11 July 2007 Evaluating the Integration of a Virtual ET Sensor into AnnGNPS Model Rapid.
Surface conductance and evaporation from 1- km to continental scales using remote sensing Ray Leuning, Yonqiang Zhang, Amelie Rajaud, Helen Cleugh, Francis.
Evapotranspiration Estimates over Canada based on Observed, GR2 and NARR forcings Korolevich, V., Fernandes, R., Wang, S., Simic, A., Gong, F. Natural.
1. Analysis and Reanalysis Products Adrian M Tompkins, ICTP picture from Nasa.
Hydrologic Data Assimilation with a Representer-Based Variational Algorithm Dennis McLaughlin, Parsons Lab., Civil & Environmental Engineering, MIT Dara.
A Remote Sensing Approach for Estimating Regional Scale Surface Moisture Luke J. Marzen Associate Professor of Geography Auburn University Co-Director.
ASSESSMENT OF THE ANNUAL VARIATION OF MALARIA AND THE CLIMATE EFFECT BASED ON KAHNOOJ DATA BETWEEN 1994 AND 2001 Conclusions 1. One month lag between predictors.
Satellites Storm “Since the early 1960s, virtually all areas of the atmospheric sciences have been revolutionized by the development and application of.
ESTIMATION OF RIVER DISCHARGE WITH MODIS IMAGES The University of Tokyo, Institute of Industrial Science (IIS) Kohei Hashimoto and Kazuo Oki.
Data Processing Flow Chart Start NDVI, EVI2 are calculated and Rank SDS are incorporated Integrity Data Check: Is the data correct? Data: Download a) AVHRR.
EVALUATION OF A GLOBAL PREDICTION SYSTEM: THE MISSISSIPPI RIVER BASIN AS A TEST CASE Nathalie Voisin, Andy W. Wood and Dennis P. Lettenmaier Civil and.
References: 1)Ganguly, S., Samanta, A., Schull, M. A., Shabanov, N. V., Milesi, C., Nemani, R. R., Knyazikhin, Y., and Myneni, R. B., Generating vegetation.
Autonomous site-specific irrigation control: engineering a future irrigation management system Dr Alison McCarthy, Professor Rod Smith and Dr Malcolm Gillies.
1. Титульный..
Alexander Loew1, Mike Schwank2
VegDRI History, Current Status, and Related Activities
Kostas Andreadis and Dennis Lettenmaier
Space-Time in Hydrology How to define the GIS of the Future?
Meng Lu and Edzer Pebesma
Jili Qu Department of Environmental and Architectural College
Image courtesy of NASA/GSFC
Analysis of influencing factors on Budyko parameter and the application of Budyko framework in future runoff change projection EGU Weiguang Wang.
Statistical Applications of Physical Hydrologic Models and Satellite Snow Cover Observations to Seasonal Water Supply Forecasts Eric Rosenberg1, Qiuhong.
EC Workshop on European Water Scenarios Brussels 30 June 2003
Igor Appel Alexander Kokhanovsky
Presentation transcript:

The University of Mississippi Geoinformatics Center NASA RPC – March, 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. Momm The University of Mississippi Ronald Bingner USDA – ARS – National Sedimentation Laboratory

The University of Mississippi Geoinformatics Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, Background: AnnAGNPS (continued) Problem when field weather stations are sparse or even non-existing

The University of Mississippi Geoinformatics Center NASA RPC – March, 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 Center NASA RPC – March, Evaluation of the Integration of NASA Results into AnnAGNPS Modifications to AnnAGNPS Concept of “Virtual” field weather stations

The University of Mississippi Geoinformatics Center NASA RPC – March, Evaluation of the Integration of NASA Results into AnnAGNPS (continued) Modifications to AnnAGNPS

The University of Mississippi Geoinformatics Center NASA RPC – March, Evaluation of the Integration of NASA Results into AnnAGNPS (continued) Study Site Long history of hydrologic work Extensive infrastructure USDA-ARS NSL past and ongoing projects

The University of Mississippi Geoinformatics Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, Evaluation of the Integration of NASA Results into AnnAGNPS (continued) Results: –Average watershed ET

The University of Mississippi Geoinformatics Center NASA RPC – March, Evaluation of the Integration of NASA Results into AnnAGNPS (continued) Results: –Daily runoff

The University of Mississippi Geoinformatics Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued) Lambin and Ehrlich’s feature space

The University of Mississippi Geoinformatics Center NASA RPC – March, 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 Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued) “Virtual” stations Field “Virtual”

The University of Mississippi Geoinformatics Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued) Simplified representation DOY DOY DOY DOY 4 Stations DOY

The University of Mississippi Geoinformatics Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued) Simplified representation

The University of Mississippi Geoinformatics Center NASA RPC – March, 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

The University of Mississippi Geoinformatics Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued) Adjusted R 2 > 0.25

The University of Mississippi Geoinformatics Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued) Results –Variability of models performance –Adjusted R 2 –Predictors

The University of Mississippi Geoinformatics Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued)

The University of Mississippi Geoinformatics Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued) Simplified representation

The University of Mississippi Geoinformatics Center NASA RPC – March, Comparison of Existing and Future NASA Results (continued)

The University of Mississippi Geoinformatics Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, 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 Center NASA RPC – March, Acknowledgements Institute for Technology Development National Sedimentation Laboratory The University of Montana NASA and the University of Southern Mississippi