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NOAA Regional Integrated Sciences and Assessments (RISA) Program Web Application Development for Dynamic Drought Index Mapping Jinyoung Rhee *, Ph.D. Candidate.

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Presentation on theme: "NOAA Regional Integrated Sciences and Assessments (RISA) Program Web Application Development for Dynamic Drought Index Mapping Jinyoung Rhee *, Ph.D. Candidate."— Presentation transcript:

1 NOAA Regional Integrated Sciences and Assessments (RISA) Program Web Application Development for Dynamic Drought Index Mapping Jinyoung Rhee *, Ph.D. Candidate Greg Carbone *, Hope Mizzell **, and Ryan Boyles *** * Department of Geography, University of South Carolina ** SC State Climatology Office, SC Department of Natural Resources *** State Climate Office of NC, North Carolina State University Palmetto Chapter of the American Meteorological Society 12 th Annual Mini-Technical Conference, 15 May 2006

2 Catawba-Wateree River Basin

3 Source: Duke Power (http://www.dukepower.com/community/lakes/cw/) Exceptional Drought Extreme Drought Severe Drought Moderate Drought Abnormally Dry

4 Objective To provide local scale drought monitoring tool that generates indices in various time scale Spatial scale (state, climate division, county, drought management area of SC, 2~8-digit HUC water basin) Time scale (short-term or long-term)

5 Structure Drought Indices StreamflowPrecipitation Raw Data and Percentiles Interpolation and Spatial Averaging Numerical models (Python) Database (MySQL) Graphical User Interface Client(JavaScript) Server(PHP) SVG embedded User Input Map Display PHP – PHP: Hypertext Preprocessor SVG – Scalable Vector Graphics

6 Calculating Percentiles Total 55 years (1950 ~ 2004) Palmer indices and SPI: all stations, all months Streamflow and precipitation: each station, each month Raw data: Percentile: 22.78

7 Interpolation (IDW) 6 nearest stations Search up to 12 nearest stations for data No data Next nearest station 4 km X 4 km grids

8 Spatial Averaging For each spatial scale (state, climate division, county, drought management area of SC, 2~8-digit HUC water basin)

9 Scalable Vector Graphics (SVG) SVG defines vector-based graphics in XML (eXtensible Markup Language) format for the Web Source: SVG Tutorial (http://www.w3schools.com/svg)

10 Shapefile to SVG Conversion of geometries and properties of ArcView Shapefiles into SVG elements using Visual Basic Application module (from Yahoo SVG developer Group; modified by Drs. Michael Hodgson and Edwin Chow)www.carto.nethttp://pilat.free.fr/ Communication between MySQL database and SVG elements using PHP and JavaScript Shapefile SVG element with an attribute ID=0 MySQL JavaScript files e.g. blend[SPI][0]=-4.29 PHP Classify and assign color Show value when mouseover, etc DOM Convert

11 User Input Display type Input PDSI, PHDI, Z Index SPI in several time scales Precipitation and streamflow in several time scales Raw data vs. percentile blend

12 Map User Input Classification method Equal interval Quantile Natural break U.S. Drought Monitor- comparable category For any percentile blend For PDSI For SPI For weekly streamflow percentile Exceptional Drought Extreme Drought Severe Drought Moderate Drought Abnormally Dry

13 Map Navigation Tools Full view New map extent Pan New map center Zoom in & out Zoom slide (JavaScript source code by Andreas Neumann; modified by Jinyoung Rhee)

14 Map Layers Visibility Choropleth map Boundary Stations used

15 4 km x 4 km grid No data

16 Map Layers Visibility Choropleth map Boundary Stations used

17 Layer Aggregation Selected features of the same layer have been aggregated Aggregation is based on the number of 4 km x 4 km grids with data used for spatial averaging of each feature Click create map again

18 Graph Create Graph Aggregated Features

19 Table Create Table

20 Comparison: spatial variability May % PDSI and 50% 1-month SPI Climate Division 8-digit HUC County Exceptional Drought Extreme Drought Severe Drought Moderate Drought Abnormally Dry

21 Comparison: spatial variability July % PDSI and 50% PHDI Climate Division 8-digit HUC County Exceptional Drought Extreme Drought Severe Drought Moderate Drought Abnormally Dry

22 Comparison: time scale variability January 1995 ~ December month SPI3-month SPI 6-month SPI12-month SPI

23 Long term, July 2002Long term, December 1965 Short term, December 1965Short term, July 2002 Exceptional Drought Extreme Drought Severe Drought Moderate Drought Abnormally Dry

24 Conclusion Customized functions have been extended gradually through the user feedback procedures: flexibility Use of open-source software and database: suitability for cost effective and tight budget projects


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