Regional analysis of drought risks in South West Asia

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Regional analysis of drought risks in South West
Asia
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Introduction
Droughts often hit southwest Asia bringing
economic loss and political tension. To mitigate
the effects of the recurring droughts in the
region and develop the effective long-term
drought management policies, the frequency and
magnitude of drought occurrence should be
evaluated. Assessment of such drought risks is
one of the key elements of drought preparedness.
Drought Risk may be evaluated using various
Drought characteristics - Indices
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Drought Indices
A drought index is usually a single number,
derived form rainfall, snow pack, stream flow and
other water supply indicators, which is more
useful than raw data for decision making.
Drought indices provide decision makers with an
opportunity to place the current drought
conditions into historical perspective.
Allows quantitative assessment of intensity,
duration, spatial extent of anomalous climatic
conditions.
Can be used to trigger certain anti-drought
actions.
A communication tool for diverse audience to
better explain the complex relationships.
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Drought Indices
Palmer Drought Severity Index (PDSI)
Complex function of rainfall and evaporation.
Better for large areas of uniform topography.
Deciles
Based entirely on rainfall data. Level of dryness
is expressed in scores related to cumulative
statistical distribution of rainfall.
Based on rainfall. Most straightforward.
Region-specific.
Percent of normal
Many more exist. New indices continue to emerge.
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Need for a Software

• Calculation of drought indices requires, as a
  minimum, long term observed rainfall time series.
  
• No index is ideal for all regions or tasks. It is
  useful to consider several indices, examine the
  sensitivity and accuracy of indices, the
  correlation between them, and explore how well
  they compliment each other in the context of
  specific research or management objective.
• The number of calculations increases enormously
  when the analysis of drought of different
  duration is required and the area of interest
  increases, with corresponding increase in a
  number of rainfall stations.
• Plotting facilities are required to analyze the
  spatial variations of indices generated, and for
  their comparison with each other.
• The above goals were achieved by adding the
  Drought Indices Calculation Procedures to SPATSIM
  - software package with powerful spatial and
  temporal data analysis plotting capabilities.

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Drought Software
Main SPATSIM screen showing a coverage of SW
Asia and rainfall stations locations
Part of the SPATSIM package - SPAtial and Time
Series Information Modeling.
SPATSIM is developed by the Institute for Water
Research (IWR), South Africa. It is
permanently expanding to include more options for
various water resources analyses.
Drought software is developed jointly by IWMI and
IWR.
It calculates, displays, spatially plots,
exports/imports areal rainfall and variety of
drought indices from rainfall time series data.
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Drought Software
Read Step by Step Manual
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Drought Software
Generates areal rainfall data from observed
(point) rainfall time series with spatial
interpolation methods. Enables patching the
missing data periods.
Allows to plot rainfall and drought indices time
series data.
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Drought Software
Rendering the spatial variation of drought
indices across various geographical or political
boundaries - Provinces, districts, tehsils etc.
Allows to monitor the spatial extent of a
drought, and the dynamics of its expansion and
recession over time.
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Rainfall Data in South West Asia
INDIA
PAKISTAN
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Rainfall Data in South West Asia
AFGHANISTAN
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Rainfall Data in South West Asia
AFGHANISTAN
Only 5 stations with long term (gt25 yrs.)
rainfall time series data.
Stations with short term time series data, were
extended where possible - using highly correlated
data form neighboring long-term stations.
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Rainfall Data in South West Asia
IRAN
AFGHANISTAN
BALUCHISTAN
RAJASTHAN
SIND
GUJARAT
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Drought Indices Time Series Analysis
Areal Rainfall from 1984 to 1990 (inclusive) for
Jodhpur, Rajasthan
Indices calculated over different time steps
allow droughts of different durations to be
detected and to assess, for example, whether a
long-term drought is over or not.
Standardized Precipitation Index (SPI) Time
Series from 1984 to 1990 (inclusive) for
Jodhpur, Rajasthan
3m SPI
24m SPI
Running means
6m SPI
12m SPI
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Drought Indices Spatial Analysis
SPI running means for 1, 3, 6 ,12 months (up to
June 1988) Rajasthan Gujarat
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Drought Frequency Analysis
Different thresholds of drought indices are used
to calculate different drought extremity. By
calculating the number of cases of extreme,
severe and moderate droughts over a long period
for each tehsil, district, Province etc, drought
frequency can be calculated. This can be done
for a year, for a cropping season, for a month,
etc.
District-wise Distribution of Moderate, Severe
Extreme Drought Years in Rajasthan over 35 years
(1965 1999).
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Drought Frequency Analysis
District-wise Distribution of Moderate, Severe
Extreme Drought Years in Rajasthan over 35 years
(1965 1999).
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Drought Frequency Analysis
District-wise Distribution of Moderate, Severe
Extreme Drought Years in Gujarat over 35 years
(1965 1999).
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Drought Frequency Analysis
AFGHANISTAN
District-wise Distribution of Moderate, Severe
Extreme Drought Years in AFGHANISTAN over 31
years (1960 1990). (selected districts only)
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Conclusions

• Drought software is envisaged to become a useful
  addition to the drought assessment tool box. It
  can be used by relevant organizations at
  different locations in the region - results can
  be exported imported and reproduced. Software is
  available from IWR and from IWMI. Both institutes
  are committed to improvement/ extension of its
  functionality.
• Quantification of drought risks is important for
  drought preparedness plans. The higher the
  probability of drought occurrence the more
  focus should be on this area when planning
  drought mitigation measures
• Rainfall and other climate data availability in
  the region is the primary factor limiting the
  accuracy of drought risk assessments,
  particularly in Afghanistan. Linking readily
  available remote sensing data with limited
  climate data from ground observations may result
  in finding effective alternative ways for drought
  risk assessment.

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details http//www.iwmi.cgiar.org/droughtassessme
nt/index.asp
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