Skip to main content

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 www.droughtmanagement.info)which 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 
Mrinmoy


All the income generated from this blog is deposited to NGOs after the deduction of honorariums and hosting costs.

Popular posts from this blog

M.Tech in Hydroinformatics Engineering at NIT Agartala: Building the Next Generation of Water Intelligence Specialists

Why Hydroinformatics — and Why Now India is facing a water crisis of compounding proportions. Erratic monsoons, receding groundwater tables, increasingly severe floods, and the pressures of rapid urbanisation have made water resource management one of the most urgent engineering challenges of our time. At the same time, the arrival of machine learning, big data, IoT sensor networks, and geospatial intelligence has created an entirely new toolkit for tackling these problems — if only enough engineers know how to use it. That is the promise of Hydroinformatics Engineering: a discipline that fuses hydrological science with the power of modern computation, data science, and artificial intelligence to model, predict, and manage water systems with a precision that was simply not possible a decade ago. NIT Agartala, an Institute of National Importance under the Government of India, has launched a 2-year full-time M.Tech programme in Hydroinformatics Engineering to train exactly these speciali...

“Lighting the Countryside: A Review of Electricity for the Farm”

“Lighting the Countryside: A Review of Electricity for the Farm” is a clear, engaging reflection on how a 1915 manual about farm electrification still speaks to today’s distributed energy and rural development debates. hydrogeek.substack +1 Core focus of the review The review introduces Frederick Irving Anderson’s “Electricity for the Farm: Light, Heat and Power by Inexpensive Methods from the Water Wheel or Farm Engine” as a practical, narrative-style manual aimed at early‑20th‑century farmers with curiosity but little formal training. hydrogeek.substack +1 It highlights how the book shows farmers using small streams or farm engines to generate electricity for lighting, heating, and power, replacing smoky lamps and manual drudgery with safer, cleaner energy services. hydrogeek.substack +1 Strengths highlighted The review praises the structure : an opening narrative centered on “Perkins” and his neighbor demonstrates, almost like a case study, how an idle water wheel becomes a 24‑hour ...

Call for Submissions to Publish in Conservation Geek

I invite all my subscribers, readers, and visitors to submit an article for publication(if selected after review) in the latest edition of Conservation Geek. The first edition has already been published; you can find a screenshot at the beginning of this post. We plan to publish four editions per year, so we are now looking for new articles, case studies, technical notes, reviews, “news and views”, etc from the relevant domain that comes under “Water, Energy or Both Conservation”. If you want to submit an article, please leave a comment on this post or email me at editor.at.baipatra.ws. We will review it and publish it if it is selected. Relevant topics of the article will be but not limited to : 1)Water Conservation 2)Energy Conservation 3)Water-Energy Nexus 4)Water-Energy-Food Nexus 5)Green Economy 6)Carbon Credits and Carbon Economy 7)Circular Economy 8)Desertification 9)Conservation Policies 10)Climate Change 11)Conservation Strategies involving the use of data science, AI, ML and ...