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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Integration of NASA Global Precipitation Measurement Mission Data into the SERVIR Flood Decision Support System for Mesoamerica Greg Easson Joel Kuszmaul Elizabeth Johnson
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Goals To test and validate GPM Mission data to 1.enhance the current satellite-based inputs into SERVIR, 2.replace AMSR-E data used for SERVIR’s flood Decision Support System (DSS) for floods and 3.calibrate flood extent information generated from AMSR-E data with gauging data in Central America
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Project Team Faisal Hossain - Tennessee Tech University (TTU) Robert Brakenridge - Dartmouth Flood Observatory (DFO). Timothy Gubbels – SSAI – GSFC Dan Irwin – NASA – MSFC Emil Cherrington – CATHALAC
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Background - SERVIR DSS SERVIR is a Mesoamerican – focused decision support system that integrates satellite and geospatial data disasters ecosystems biodiversity weather water climate oceans health agriculture energy
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 SERVIR - Flood DSS AMSR-E - passive microwave instrument measures surface water condition changes in watersheds in Central America
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Objectives 1.Generation of discharge estimator from AMSR- E data under the guidance of Dartmouth Flood Observatory Compare existing AMSR-E 36 GHz Microwave with TRMM 37 GHz 2.Simulated GPM precipitation estimates by Tennessee Technological University Evaluation of results of discharge estimator from GPM with gauge and ASMR-E measurements for calibration.
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Study Site and Timing Hurricane Stan Over Central America Oct 1-10, 2005 Up to 500 mm rain (200 inches) Loss of life between 1600 and 2000 people Most lives lost in Guatemala Damages greater than $1billion USD
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Hurricane Stan Panabaj – city lost to mudslides in Guatemala Rainfall Accumulation map
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Satellite Data For Project TRMM Products 3D42 RT 3D42 RT V6 TMI 37 GHz AMSR-E 36.5 GHz Simulated GPM Precipitation product AMSR-E imagery of Hurricane Stan
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a passive-microwave radiometer system. It measures horizontally and vertically polarized brightness temperatures at 6.9 GHz, 10.7 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz, and 89.0 GHz. Spatial resolution of the individual measurements varies from 5.4 km at 89 GHz to 56 km at 6.9 GHz. AMSR-E was developed by the Japan Aerospace Exploration Agency (JAXA) and launched by the U.S. aboard Aqua in mid-2002. AMSR-E on Aqua
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Simulated GPM Data TRMM data to be used to simulate GPM data rainfall for discharge estimation ~36Ghz microwave channel that duplicates AMSR-E ~5km spatial resolution at nadir
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Example: Wabash River near Mount Carmel, Indiana, USA Black square shows measurement pixel White square is calibration pixel Ratio C/M Higher ratios = higher discharge, more land flooded MC Objective 1:Comparison of 36Ghz Response
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Objective 1 – M/C Ratio
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Dartmouth Flood Observatory flood maps from MODIS and AMSR-E imagery data Objective 1 – Flood Map
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Objective 1 – Kappa Statistic Dartmouth Flood Algorithm on 36 GHz response from AMSR-E versus TRMM Comparison region by region each zone classified as flooded or not flooded Use Kappa Statistic corrects for chance agreement Kappa calculated in the general case as: = 0 chance agreement 0 better than chance
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Objective 2: Comparison of Discharge Volumes DFO will use ground data for calibration of daily AMSR-E-based discharge volumes TT will use ground data and rating curves for calibration of Simulated GPM precipitation-based discharge volumes Regression analysis 9 watersheds
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Usumacinta River Watershed area 59,902 km 2 Estimated discharge (m 3 /s) Hurricane Stan Comparison of discharge as estimated by DFO with discharge as estimated by simulated GPM GPM provides Precipitation Convert precipitation to discharge using watershed data and rating curves
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Ground Data Gage height data Hourly rain data Watershed morphometric data Currently trying to acquire rating curves
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Rating Curve Relates discharge to stream stage depth stage Datum Stage Rating Curve Discharge Discharge= velocity x depth x width Gage height
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 From Gage To Discharge (via a rating curve)
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Kirpich equation Tc = 0.02 L 0.77 S – 0.385 Tc is the collection time for precipitation L is the maximum length of flow (m); S is the watershed gradient (m/m).
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The University of Mississippi Geoinformatics Center NASA MRC RPC Review Meeting: 14-15 April 2008 Rational Formula q p = (C*I*A)/360 where q p is the peak flow C is dimensionless runoff coefficient I is the intensity of a storm duration (Tc) for a given return period (worst case of runoff) A is the area of catchment
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Timeline
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Questions? For more information please contact: Elizabeth Johnson University of Mississippi Geoinformatics Center (662) 915-7651 egj@olemiss.edu
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