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Five indices that you can use along with GIS to identify Drought

Drought can not be defined as Flood. No single definition is available for drought. The beginning and end of drought are difficult to identify. 

Drought can be, however, identified through various indicators such as rainfall, snowpack, streamflow, and more, and these indicators can be used to monitor drought.

Different scientists and researchers have developed various indices to help determine the onset, severity, and end of droughts. Drought indices are multiparameter and based on long or short duration observation of data for such parameters which help them create a comprehensible big picture.

A drought index value is typically a single number that is calculated based on the data of input parameters generally rainfall, snowpack, evapotranspiration, etc., and is interpreted on a scale of abnormally wet, average, and abnormally dry.(Reference)

The video below elaborates the concept :

Although drought is very difficult to determine the significance of drought in agriculture, water resource development, hydrological science is immense. The policymakers and urban planners also consider droughts before sanctioning water-dependent projects or future budgets etc. The power sector is also dependent on drought information as it also impacts the demand for electricity. Stock markets, banks, financial institutions also require the data of drought for future planning on investments. The entire socio-economical status of a region can be changed due to the onset of drought. That is why knowledge about the identification of drought conditions is essential for each citizen of a country. After going through the past literature about drought, it can be concluded that there are more than hundreds of indices(a comprehensive list of Drought indices can be found at is used for the identification of drought however, among all these indexes the following five indices are widely used:

1. The Standard Precipitation Index (SPI)
This index shows the actual precipitation compared to the probability of precipitation for various time frames. It is useful for both short and long-duration hydrological applications.

For each month drought is identified based on the intensity of precipitation and is demarcated by a start and end time.  

"A drought event occurs any time the SPI is continuously negative and reaches an intensity of -1.0 or less. The event ends when the SPI becomes positive."

2. The Palmer Drought Severity Index (PDSI)
This index has been used the longest for monitoring drought.

The PDSI considers precipitation, temperature, and soil moisture to determine drought. However, this index is not suited for mountainous regions and areas with frequent extreme events. Palmer values may lag emerging droughts by several months. It has no defined start and ends time.

3. Crop Moisture Index (CMI)
CMIS uses soil moisture to identify droughts.CMI was designed to evaluate short-term moisture conditions across major crop-producing regions.

Because it is designed to monitor short-term moisture conditions affecting a developing crop, the CMI is not a good long-term drought monitoring tool. The disadvantage of CMI is it may consider the soil moisture after an occasional rainfall during a drought and indicate a non-drought condition while the long-term drought at that location still persists.

For a more detailed explanation about the above three indices click here.

4. Integrated Drought Index (IDI)

IDI combines the response of meteorological, hydrological, and agricultural droughts and accounts for groundwater storage. It integrates the 12-month Standardized Precipitation Index (SPI), 4-month Standardized Runoff Index (SRI), 1-month Standardized Soil Moisture Index (SSI), and 1-month Standardized Groundwater Index (SGI) to develop IDI.

Hydrologic variables like total runoff, soil moisture, and groundwater are the input parameters of IDI. It can avoid the uncertainty due to rainfall data and provide a comprehensive picture of all three types of drought. However, the requirement of calculating so many indices can create data inconsistency as groundwater data is inaccessible in many places of the World.

To know more about this index click here.

5. Aridity Anomaly Index (AAI)

A real-time drought index developed by Indian Meteorological Department(IMD) considers water balance to identify droughts. "The Aridity Index (AI) is computed for weekly or two-weekly periods. For each period, the actual aridity for the period is compared to the normal aridity for that period. Negative values indicate a surplus of moisture while positive values indicate moisture stress."

Actual evapotranspiration and calculated potential evapotranspiration are the input parameters

AAI can identify the agriculture drought, especially in the tropics where defined wet and dry seasons are part of the climate regime. The winter and summer cropping seasons can be evaluated using this method.

Although the calculations are simple, based on the comparison of actual and normal conditions. and have a weekly time step, but it is applicable only for the identification of agriculture drought and for short-term events.

For more info about AAI click here.

There are other indices for the identification of droughts however, based on the popularity, ease of use, and less data requirement the above five indices were selected. The limitations of the indices were also discussed. Now advanced technologies like Multi-Criteria Decision Making, Artificial Intelligence,  Geographical Information Systems, etc can be used to optimize the applicability of such indices for a more accurate and adaptive prediction of drought.

Signing off 

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