applying new drought decision support tools mark svoboda national drought mitigation center...
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Applying New Drought Decision Support Tools
Mark SvobodaNational Drought Mitigation Center
International Drought Information CenterUniversity of Nebraska-Lincoln
Importance of Drought Indices
Simplify complex relationships and provide a
good communication tool for diverse audiences
Quantitative assessment of anomalous climatic conditions:* Intensity
* Duration
* Spatial Extent
Historical reference (probability of recurrence)
* Planning and design applications
Sample of Drought Indices
Percent of Normal Precipitation
Deciles
Aridity Index (AI)
Palmer Drought Index (PDI) suite of indices
Crop Moisture Index (CMI)
Surface Water Supply Index (SWSI)
Reclamation Drought Index (RDI)
Standardized Precipitation Index (SPI)
What is the SPI?
Developed in 1993 in the United States (McKee et al. 1993, CSU)
Being studied or applied in over 50 countries
Simple to use (precipitation only)
Temporal flexibility allows the user to look at and monitor all water resources in a region
How the SPI works
Need 30 years of continuous monthly precipitation dataSPI time scale intervals longer than 24 months may be unreliableIs spatially invariant in its interpretationProbability based (probability of observed precipitation transformed into an index) nature makes it well suited for risk management
How the SPI works
It is NOT simply the “difference of precipitation from the mean… divided by the standard deviation”Precipitation is normalized using a probability distribution so that values of SPI are actually seen as standard deviations from the medianNormal distribution allows for estimating both dry and wet periodsAccumulated values can be used to analyze drought severity
Hilo 6-Month SPI (1950-1998)
-3
-2
-1
0
1
2
3
Jan
-50
Jan
-55
Jan
-60
Jan
-65
Jan
-70
Jan
-75
Jan
-80
Jan
-85
Jan
-90
Jan
-95
Time
SP
I
Hilo 12-Month SPI (1950-1998)
-3
-2
-1
0
1
2
3
Jan
-50
Jan
-55
Jan
-60
Jan
-65
Jan
-70
Jan
-75
Jan
-80
Jan
-85
Jan
-90
Jan
-95
Time
SP
I
The SPI Program Monthly program w/ interface PC version is coded in C++ Easy to use interface compared to
original command-line UNIX version Distributed to over 60 countries
UNIX version also available (robust) Download PC code from the NDMC: http://www.drought.unl.edu/monitor/spi/program/spi_program.htm Weekly code available at: http://nadss.unl.edu/us/download/
National Agricultural Decision Support System
NSF 3-year project ($1M) Digital Gov.
Allows for weekly table/map output of the
SPI, PDSI and Newhall values
1948-present (base 61-90’ for distribution)
Leap years and missing/estimated data
HPRCC/UCAN SHEF real-time data from COOP and first order sites
1-m onth SPI through the end of April 2001
C opyright © 2001 N ational D rought M itigation C enter
+ 2.0 and above (extremely wet)
+ 1.50 to + 1.99 (very wet)
+ 1.0 to + 1.49 (moderately wet)
-0.99 to + 0.99 (near normal)
-1.00 to -1.49 (m oderately dry)
-1.50 to -1.99 (severely dry)
-2.0 and less (extremely dry)
3-m onth SPI through the end of April 2001
C opyright © 2001 N ational D rought M itigation C enter
+ 2.0 and above (extremely wet)
+ 1.50 to + 1.99 (very wet)
+ 1.0 to + 1.49 (moderately wet)
-0.99 to + 0.99 (near normal)
-1.00 to -1.49 (m oderately dry)
-1.50 to -1.99 (severely dry)
-2.0 and less (extremely dry)
6-m onth SPI through the end of April 2001
C opyright © 2001 N ational D rought M itigation C enter
+ 2.0 and above (extremely wet)
+ 1.50 to + 1.99 (very wet)
+ 1.0 to + 1.49 (moderately wet)
-0.99 to + 0.99 (near normal)
-1.00 to -1.49 (m oderately dry)
-1.50 to -1.99 (severely dry)
-2.0 and less (extremely dry)
12-m onth SPI through the end of April 2001
C opyright © 2001 N ational D rought M itigation C enter
+ 2.0 and above (extremely wet)
+ 1.50 to + 1.99 (very wet)
+ 1.0 to + 1.49 (moderately wet)
-0.99 to + 0.99 (near normal)
-1.00 to -1.49 (m oderately dry)
-1.50 to -1.99 (severely dry)
-2.0 and less (extremely dry)
Results
Increased spatial and temporalresolution of SPI/PDSI improves:
• Drought monitoring
• Vulnerability mapping
• Decision support
-exposure analyses
Next Steps
Incorporate elevation factor (SNOTEL)
Integrate TD3206 data for pre-1948 analysis
Incorporate projected SPI maps based on
.80/.50/.20 for decision makers
Implement Pearson III in the code
Extend out to 104 weeks (2 years)
More exposure analysis research
The UNIX version of the SPI can be found at:http://ulysses.atmos.colostate.edu/SPI.html
Additional copies of the PC version of the SPI can be obtained by emailing me at: msvoboda2@unl.edu
The weekly SPI code can be found at:http://nadss.unl.edu/
How to get the SPI Programs
http://nadss.unl.edu
A Case Study:A Case Study:
Monitoring Drought in Hungary with Monitoring Drought in Hungary with the Standardized Precipitation Indexthe Standardized Precipitation Index
A. Bussay1, M. Hayes2, Cs. Szinell1, and M. Svoboda2
1. Hungarian Meteorological Service2. National Drought Mitigation Center, University of Nebraska-Lincoln
Goals of the Study
One of the first applications of the SPI in Hungary and in EuropeTo identify the relationship of the SPI with streamflow, groundwater levels and
soil moisture valuesTo assess and compare the monitoring capabilities between the SPI and the Palmer Drought Severity Index
The Study AreaThe Study Area
Table 1. Classification scale for SPI values (after Edwards and McKee 1996)
SPI Values Category Time in Category (%)
+2.00 Extremely Wet 2.3 +1.50 to +1.99 Very Wet 4.4
+1.00 to +1.49 Moderately Wet 9.2
-0.99 to +0.99 Near Normal 68.2
-1.00 to -1.49 Moderately Dry 9.2
-1.50 to -1.99 Severely Dry 4.4 -2.00 Extremely Dry 2.3
Classification Scale for SPI Values
-3-2.5
-2-1.5
-1-0.5
00.5
11.5
2
1981 1982 1983 1984 1985
Years
SP
I
-6-5-4-3-2-101234
PD
SI
3-month SPI 18-month SPI PDSI
The course of 3-month SPI, 18-month SPI and PDSI during the 1983 drought in the southeast of Hungary
0
50
100
150
200
250
300
1981 1982 1983 1984 1985Years
Wat
er ta
ble
dept
h (c
m)
-2.5-2-1.5-1-0.500.511.5
SPI
Water Table 6-month SPI 12-month SPI
The course of the 6-month SPI, 12-monthSPI and water table depth during the 1983 drought in the southeast of Hungary
Findings
The SPI and PDSI showed the strongest relationship at around 6 or 7 months
Shorter time scales worked best with soil moisture and streamflow (2 to 3 months)
Longer time scales worked best with groundwater levels (12 to 24 months)
In all cases, the SPI captured tendencies and characteristics of these variables
http://nadss.unl.edu
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