Transcript Slide 1

Twentieth Century Drought in the Conterminous United States: An Application of Severity-Area-Duration Analysis
Konstantinos M. Andreadis1, Elizabeth A. Clark1, and Dennis P. Lettenmaier1
1. Department of Civil and Environmental Engineering, Box 352700, University of Washington, Seattle, WA 98195
AMS Annual Meeting, 19th Conference on Hydrology
9-13 Jan 2005, San Diego, CA
ABSTRACT
Drought characterization typically involves severity, frequency and duration; however, the often neglected spatial extent of a
drought also influences its impact on water resources management. In the past, station data have been used to calculate
drought severity for individual climate divisions across the United States, but a basis for the spatial characterization of
drought on a nationwide scale has been lacking. Spatially distributed hydrologic models provide a means for simulating both
agricultural drought (related to soil moisture) and hydrological drought (related to runoff) over a grid mesh. The output of
such models can be used to identify the spatial extent of drought. Depth-area-duration analysis, widely used in
characterization of precipitation extremes for specification so-called design storms, provides a basis for evaluation of drought
severity when storm depth is replaced by an appropriate measure of drought severity. Precipitation and temperature data
over the continental U.S. for the entire period of observational record are now available in electronic form from the National
Climatic Data Center, and these recently available extended data greatly facilitate the ability to reconstruct U.S. drought
history. We used these data, starting with 1920 (prior to which station density was too sparse to allow production of
meaningful simulations) as input to the physically-based Variable Infiltration Capacity (VIC) macroscale hydrology model,
which was used to simulate soil moisture and runoff over the conterminous United States. To standardize soil moisture and
runoff anomalies, we computed percentiles of each at a monthly timestep. We then used a clustering algorithm to identify
individual drought events in space and time. A series of severity-area-duration curves for all drought events were constructed,
to relate the spatial extent of each drought to its severity. From these curves, an envelope curve of the worst drought events in
the conterminous U.S. during the 20th century, was derived. These events included the 1930s, 1950s, late 1980s, and the
current western U.S. drought, all of which have been previously cited as extreme droughts.
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The overall impact of a drought event depends on several factors, including
severity, frequency, area, and duration (Dracup et al., 1980). Several drought
indices have been defined for the characterization of drought severity over time.
These indices typically describe one of four drought types: agricultural,
hydrologic, meteorological, and socioeconomic. Generally, agricultural drought
relates to soil moisture, hydrologic to runoff and streamflow, meteorologic to
precipitation and temperature, and socioeconomic to the disparity between
supply and demand for water-related goods (Wilhite and Glantz, 1985).
Severity
We use simulated monthly soil moisture anomalies as a measure of agricultural
drought and simulated monthly runoff anomalies as a measure of hydrologic
drought. Because the absolute magnitude of these departures varies with climate
region, we measure the departure from normal in terms of percentiles (Weibull
estimate) based on the 1920 to 2003 climatology.
Area
The algorithm used to identify areal
extent of droughts begins with spatial
smoothing using a 3-by-3 median
filter to minimize discontinuities in the
original data. Based on the threshold
level, pixels that are experiencing
drought at a given monthly time step
are identified and are classified using
a simple clustering algorithm. The
first pixel "under drought" is assigned
to the first class. Then the 3-by-3
neighborhood of this pixel is searched
for pixels "under drought" which are
classified in the same drought cluster.
This procedure is repeated until no
pixels in the neighboring pixels of the
current cluster are "under drought"
and a new cluster is created for the
next pixel below the drought
threshold. After the initial partitioning
step, a final classification step
excludes all clusters with areas below
10 half-degree pixels from subsequent
calculations. At the end of this step, Figure 4. Spatio-temporal drought
the remaining clusters are defined as identification: three consecutive
separate drought events for the current timesteps, with two drought areas
time step.
merging (A1 and A2); drought area B2
breaking up into two drought areas, B2
Duration
Drought events are assigned a and B3, with the latter merging with
temporal extent based on the another drought area (B1). The
continuation of drought conditions algorithm classifies each smaller
(20th percentile or for lower soil drought area to a larger drought event
(A and B).
moisture, 20th percentile or lower for
Background
Drought is among the most costly natural disasters in the United States. In 1995, the Federal Emergency Management
Agency (FEMA, 1995) estimated that the annual cost of U.S. droughts was in the range of $6-8B. To assess the potential
impacts of current and future drought, water managers often compare current or potential drought severity with historic
drought severities. This process, however, often overlooks the effects of areal extent on drought intensity. The purpose of
this study is to create a context for comparison of extreme drought events based not only on an event’s severity, but also
on its areal extent and duration.
NOAA's National Climate Data Center (NCDC) recently released digitized Cooperative Observer Network (Co-op) station
precipitation and temperature data for much of the 20th century. This data set makes the extension of model simulations of
hydrologic conditions over most of the 20th Century possible. Such simulations provide a spatially and temporally
continuous data set. They also allow us to investigate historical droughts in new ways.
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Hydrologic Model and Validation
The Variable Infiltration Capacity (VIC) macroscale hydrologic model (Liang et al., 1994) is
applied to a half degree resolution grid mesh across the conterminous United States for the
1920 to 2003 period. Soil properties for a 3-layer soil column are taken from Maurer et al.
(2002) and aggregated from 1/8o to 1/2o resolution. Vegetation fractions are based on the
University of Maryland's 1-km global land cover classification (Hansen et al., 2000). The
meteorological forcings used include observed precipitation and temperature from NCDC
Cooperative station data and wind from NCEP/NCAR reanalysis.
The VIC model essentially solves an energy and water balance, and accounts for sub-grid
scale variability in soil, vegetation, precipitation, and topography (Figure 1). The vertical
dimension of each cell is divided into three soil layers, in which the soil moisture storage
capacity is treated as a spatial probability distribution. Baseflow from deepest soil layer is
produced according to the Arno model nonlinear baseflow formulation (Francini and
Pacciani, 1996). Evapotranspiration, surface runoff and baseflow are calculated for each
Figure 1. Schematic
vegetation class, and the weighted sum of each, based on vegetation fraction, is assigned to
representation of VIC
the grid cell. Once generated, surface runoff and baseflow are released from the grid cell,
hydrologic model.
though they can be routed to simulate streamflow using the model developed by Lohmann et
al. (1998).
Validation
The VIC model has been tested at one-eighth degree over the continental U.S. for the period from 1950 to 2000 (Maurer
et al., 2002). Runoff was routed through a stream network to simulate streamflow for continental scale river basins with
reasonable results, showing good agreement of seasonal cycle, low flows, and peak flows between simulated streamflow
and USGS observed streamflow (Figure 2). Maurer et al. (2002) also compare VIC simulated soil moisture with Illinois
observed soil moisture (Figure 3). The seasonal variability of soil moisture flux (soil moisture storage change), and its
coefficient of variability and temporal persistence, were all reasonably well-simulated.
Figure 2. Six monthly hydrographs,
aggregated from daily flows.
Numbers correspond to location of
hydrograph flow. Observed flows
from USGS gaging stations.
Simulated flows from VIC model
(Maurer et al., 2002)
Obs.
Model
Figure 3. Comparison of soil
moisture at 19 observing stations in
Illinois and soil moisture from the
17 1/8º modeled grid cells that
contain the observation points.
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Drought Characterization
runoff) in at least one cell between monthly time steps. If multiple clusters merge
to form a larger drought in later time steps, or if a single drought splits into
multiple smaller droughts, the smaller droughts are considered part of the larger
drought. In these special cases, the spatial extents and severities are calculated
separately based on a contiguity constraint (Figure 4).
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Envelope Curves
Soil Moisture
Runoff
This envelope curve represents four major hydrologic
From the envelope curve, we can see that there were
drought events between 1920 and 2003. These include
four major agricultural drought events between 1920
1932 to 1938, 1950 to1957, 1975 to 1978, and 1999 to
and 2003. These occurred from 1928 to 1932, 1932 to
2003 (current). The 1970s drought was most severe
1938, 1950 to 1957, and 1998 to 2003 (current). The
over the 3-month duration at very small areas. The
current drought dominates at smaller areas for durations
current drought dominates over a greater range of areas
from 3 months to 2 years. As expected, the 1930s
for durations from 3-months to 2-years when defined by
drought was most severe at large spatial extents for
runoff shortages. As we can see in the accompanying
short durations. During the “Dust Bowl” severe drought
spatial maps, the current drought effectively covers the
covered areas larger than 5 million km2 for durations
entire western U.S., suggesting that there were minimal
from 3-months to 1-year. the 1950s drought appears to
recovery periods for the entire region, amplifying
be the most severe at an increasing number of area
severity in terms of drought impacts. The 1930s drought
values as durations become longer, especially for 1was most severe for the 3-month duration over areas
year durations and longer covering the entire envelope
from 2 million km2 to 6 million km2. The 1950s drought
curve for the 6-year duration. Our analysis technique
was most severe for larger areas and longer durations;
prevented the 30s drought from continuing during
in fact, it is always the most severe drought for the 61932, due to a one month recovery and subsequent
year duration. However, if the current drought, which
relocation, the drought was split into two events, one in
has a maximum duration of 4 years in this analysis,
1928-1932 and one in 1932-1938. The effect of this is
continues, it could surpass the 1950s drought in severity
most evident in the longest duration results.
at the 6-year duration.
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Soil Moisture and Runoff Drought Differences
Even though the current drought has a relatively high soil moisturebased severity, it occupies a much larger portion of the runoff-based
envelope curve. If we examine the spatially averaged correlation
coefficient between soil moisture and runoff for the periods of the
three major drought events (1930s, 1950s and current), we find that
precipitation has a much higher correlation with runoff than with soil
moisture. The autocorrelation is higher for the current drought, which
suggests that dry (or wet) spells during the current drought were
longer than during the other two droughts. Because runoff responds
faster to precipitation, parts of the areas under hydrological drought
in the 30s and 50s recovered, thus decreasing the average severity.
Severity-Area-Duration Analysis
Depth-area-duration analysis, widely used in characterization of precipitation extremes for specification of so-called design storms,
provides a basis for evaluation of drought severity when storm depth is replaced by an appropriate measure of drought severity. For
the purposes of this paper, drought severity (S) is defined as S=(1-ΣP/t), where ΣP is the percentile of soil moisture or runoff summed
over duration t (in months). We adapted the computational method of WMO (1960) to calculate the average severity corresponding
to each standard area for each drought identified. In this study, we examine durations of 3, 6, 9, 12, 24, 36, 48, and 72 months and
areas from 10 grid cells, or approximately 25,000 km2, to the maximum drought extent, in increments of 20 grid cells, or
approximately 50,000 km2. Figure 6 shows a flow diagram of the entire methodology.
Threshold
VIC model
output
Total column
soil moisture
Runoff
20th
Weibull
percentiles
percentile
and lower soil
moisture
30th percentile
and lower
runoff
Spatial
contiguity
Initial
Temporal
drought
contiguity
classification
Final drought
and
subdrought
classification
Severity-AreaDuration
SAD
curves
for each
event
Highest
severities
Figure 6. Overview of methodology from initial input to envelope curves.
Envelope
curve for
each
duration
Construction of SAD Curves:
1. Rank cells by severity & identify
potential drought centers
2. Search 3x3 neighborhood of
drought center
3. Average severities & add areas
4. Output severity and area at
specified area intervals
Figure 5. Process of computing area and area-averaged severities
for SAD analysis. (1) Start with maximum severity grid cell, or
“drought center”. (2) Add area and average severity with most
severe grid cell that is contiguous with drought center. (3)
Continue adding next most severe grid cells until prescribed areal
extent is reached.