Drought

1. Drought in Travis County
Chris Shaw
CE394K.2
Spring 2007

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Outline of Presentation
 Introduction/Objective
 Drought
 Indices
 Methods
 Results
 Summary

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Introduction
 Water is important
– Transportation
– Agriculture
– Domestic Use
– Commercial and Industrial Use
– Recreation
 Drought negatively impacts these uses
 Tools needed to predict and classify drought

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Objective
 I approached this project as an opportunity
to:
– Learn more about drought
– Learn more about tools available to classify and
forecast drought.
– As an exercise in determining drought
conditions for a local area, in this case Travis
County.

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What is Drought
 The immediate cause of drought is the
predominant sinking motion of air
(subsidence) that results in compressional
warming or high pressure, which inhibits
cloud formation and results in lower relative
humidity and less precipitation.

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Definitions
 Conceptual vs. Operational
 Conceptual definitions, help people understand the
concept of drought.
 Example: Drought is a protracted period of
deficient precipitation resulting in extensive
damage to crops, resulting in loss of yield.
 Operational definitions help people identify the
beginning, end, and degree of severity of a
drought.

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Meteorological/Agricultural
 Meteorological-usually an expression of
precipitation’s departure from normal over time.
 Agricultural-Links various characteristics of
meteorological or hydrological drought to
agricultural impacts.
– precipitation shortages
– differences between actual and potential
evapotranspiration
– soil water deficits,
– reduced ground water or reservoir levels.

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Hydrological
• Hydrological drought refers to deficiencies in surface and
subsurface water supplies. It is measured as streamflow
and as lake, reservoir, and groundwater levels. There is a
time lag between lack of rain and less water in streams,
rivers, lakes, and reservoirs, so hydrological measurements
are not the earliest indicators of drought.
• Although climate is a primary contributor to hydrological
drought, other factors such as changes in land use
(deforestation), land degradation, and dam construction
also contribute.

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Socioeconomic
• Socioeconomic- associates the supply and demand
of some economic good with elements of
meteorological, hydrological, and agricultural
drought.
• occurs when the demand for an economic good
exceeds supply as a result of a weather-related
shortfall in water supply.
• occurs when physical water shortage starts to
affect people, individually and collectively.

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How is drought measured and
represented?
 No single operational definition of drought works
in all circumstances, and this is a big part of why
policy makers, resource planners, and others have
more trouble recognizing and planning for drought
than they do for other natural disasters. In fact,
most drought planners now rely on mathematic
indices to decide when to start implementing
water conservation or drought response measures.

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Drought models or indices
 Percent of Normal
 Standardized Precipitation Index (SPI)
 Surface Water Supply Index (SWSI)
 Reclamation Drought Index (RDI)
 Deciles
 Crop Moisture Index (CMI)
 Palmer Drought Severity Index (PDSI)

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Indices
 Percent of Normal - a simple calculation suited to
the needs of TV weathercasters and general
audiences.
 SPI - The SPI is an index based on the probability
of precipitation for any time scale.
 SWSI - designed to complement the Palmer in the
state of Colorado
 RDI - calculated at the river basin level

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Indices
 Deciles - Groups monthly precipitation into
deciles, used in Australia
 CMI – Palmer derivative, reflects short term
moisture supply across major crop-producing
regions, not intended to assess long-term droughts
 PDSI - Soil moisture algorithm calibrated for
relatively homogeneous regions. U.S. government
agencies and states rely on the Palmer.
 Chose PDSI
 30 years data required

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PDSI Calculation
 Inputs: Temperature, Precipitation, Normal Temperatures,
Latitude, and Available Water Holding Capacity (AWC) of
the soil.
 The temperature values are the average daily temperature
for each time period (month/week).
 Precipitation the total amount received over each time
period.
 Normal temperatures are long-term average temperature
for each period.
 Latitude used to approximate the amount of sunlight the
location receives, which is part of Thornthwaite's
calculation of PET.

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PDSI Calculation
 For each period, the following values must be
calculated
o Potential Evapotranspiration
o Potential Recharge
o Potential Runoff
o Potential Loss
o Actual Evapotranspiration
o Recharge
o Runoff
o Loss

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PDSI Calculation
 Calculate the moisture departure for each period
 The moisture anomaly is calculated
 To calibrate the PDSI, values of the duration
factors and the climate characteristic must be
determined
 To determine the value of the duration factors p
and q, the linear relationship between the length of
extreme dry spells and the value of the
accumulated Z-index over those spells is
determined using the least-squares method.

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PDSI Calculation
 The PDSI is calculated for each period using the
moisture anomaly that was approximated. Then
each value of the Z-index is weighted according to
where the 2nd and 98th percentiles of the PDSI fall
compared with the expected -4.00 and +4.00.
 The PDSI values are calculated iteratively using
the Z-index and the duration factors. Each of the
intermediate indices X1, X2, and X3 are calculated
as necessary for each period in order. The
probability of the current spell ending is also
calculated.

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Study Area Considerations
 County chosen over HUC or watershed/basin
 Location of measurement sites and length of
records required for some data, most notably
precipitation and soil moisture, limited the site
data available.
 Site location is relatively central to the county
extents. Site moved to Camp Mabry in early part
of this decade.

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Site Location

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PDSI Calculator
 Fortunately I discovered a site that would
do the calculation for me.
 http://nadss.unl.edu/PDSIReport/index.jsp
 SPI calculator available as well, but does
not appear to work at this time.
 Shortcomings – outputs, limited sites

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Results
Station ID 410428 1990 -3.5 1996 -1.08 2002 1.9
Station NameAustin Mueller Muni AP 1991 0.94 1997 0.52 2003 1.83
Latitude 30.321 1992 2.89 1998 2.82 2004 0.13
Longitude -97.76 1993 3.7 1999 1.35 2005 2.28
Index Self Calibrated PDSI 1994 -1.89 2000 -1.74 2006 -2.48
1995 1.83 2001 1.39

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Travis County, 1990-1997

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Travis County 1998-2006

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Summary
 An abundance of indices available
 Need to match the model to the job
 As with most climate models there is a fair
amount of uncertainty
 Increasing availability of products like I
used
 Need more sites to support these kinds of
efforts.

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Questions?