Palmer Drought Severity Index (PDSI)
Index name: Palmer Drought Severity Index (PDSI).
Ease of use: Yellow.
Origins: Developed in the 1960s as one of the first attempts to identify droughts using more than just precipitation data. Palmer was tasked with developing a method to incorporate temperature and precipitation data with water balance information to identify droughts in crop-producing regions of the United States. For many years, PDSI was the only operational drought index, and it is still very popular around the world.
Characteristics: Calculated using monthly temperature and precipitation data along with information on the water-holding capacity of soils. It takes into account moisture received (precipitation) as well as moisture stored in the soil, accounting for the potential loss of moisture due to temperature influences.
Input parameters: Monthly temperature and precipitation data. Information on the water-holding capacity of soils can be used, but defaults are also available. A serially complete record of temperature and precipitation is required.
Applications: Developed mainly as a way to identify droughts affecting agriculture, it has also been used for identifying and monitoring droughts associated with other types of impacts. With the longevity of PDSI, there are numerous examples of its use over the years.
Strengths: Used around the world, and the code and output are widely available. Scientific literature contains numerous papers related to PSDI. The use of soil data and a total water balance methodology makes it quite robust for identifying drought.
Weaknesses: The need for serially complete data may cause problems. PDSI has a timescale of approximately nine months, which leads to a lag in identifying drought conditions based upon simplification of the soil moisture component within the calculations. This lag may be up to several months, which is a drawback when trying to identify a rapidly emerging drought situation. Seasonal issues also exist, as the PDSI does not handle frozen precipitation or frozen soils well.
Resource: Global PDSI by the Terrestrial Hydrology Research Group of Princeton University.
Alley, W.M., 1984: The Palmer Drought Severity Index: limitations and assumptions. Journal of Climate and Applied Meteorology, 23: 1100–1109. DOI: 10.1175/1520-0450(1984)023<1100:TPDSIL>2.0.CO;2.
Palmer, W.C., 1965: Meteorological Drought. Research Paper No. 45, US Weather Bureau, Washington, DC.
Currently used by: Bosnia and Herzegovina, Brazil, Bulgaria, Canada, Greece, Macedonia, Peru, Trinidad and Tobago, Turkey, USA.
I used the tool by Jacobi et al. 2013 to calculate the PDSI. I am not sure about the AWC as the manual says the input unit needs to be inches. For my study area I’ve got the AWC values in % which i could convert to mm/m or inch/foot but I would not end up with an absolute value in inches. So to do the calculation, would I also need to have an estimation of the soil profile thickness for each location or does the PDSI assume a certain (constant) thickness for the soil layer model? Thanks for your help.
Kindly tell me how to calculate the PDSI in MATLAB? Could you please give me an example of the code?
it will be appreciated.
There are several codes available for calculation of PDSI in MATLAB. Please find a method here: https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/wrcr.20342 and a freely available sample function here (needs your quality check): https://www.mathworks.com/matlabcentral/fileexchange/88962-pdsi?s_tid=FX_rc1_behav.
Could PDSI be used as a proxy for water shortage calculation? If so, what would be critical point or range for that?
Dear Maruf Morshed
The PDSI has been developed to monitor longer-term meteorological drought and it is standardized to range from -10 (dry) to +10 (wet). Indices like the PDSI can serve as triggers for action in a drought plan and will be most meaningful if they are connected to the respective impacts.
You can find more information on the PDSI here.
Can anyone send me the excel file of PDSI for the last 40-50 years (country-wise data) to firstname.lastname@example.org
Depending on which region or country you are looking for, there are gridded datasets available here: https://psl.noaa.gov/data/gridded/data.pdsi.html
Is there a way to tie drought severity indexes to percentages of normal precipitation?
Dear BJ Schellin
Thank you for your message. Could you please be more specific with your question? The percentage of normal precipitation is an index (https://www.droughtmanagement.info/percent-of-normal-precipitation/) that gives an indication of drought severity (as in deviation from the normal precipitation).
Estimado Robert: soy fitomejorador e investigador en el cultivo del frijol. Me llama la atencion la clasificacion de la sequia como ustedes las manejan….. consultando literatura ha visto diferentes clasificaciones de sequia, la pregunta es ¿ cual clasificacion recomiendas para el caso de america latina?
Estimada/o Aldemaro Clara
Gracias por su mensaje. Le hago referencia a algunos monitores de sequía en América Latina:
Sistema de Información sobre Sequías para el sur de Sudamérica
Monitoreo de sequías del CIIFEN
Monitoreo de sequías Mesoamérica
How can I calculate PDSI for India ?
There are several published studies on the application of the PDSI in India. Please find here some examples:
Please note that the PDSI was developed for use in the USA and default values for soil water holding capacity may not be transferable to other contexts.
A presentation of how the PDSI is calculated can be found here: https://drought.unl.edu/archive/Documents/NDMC/Workshops/136/Pres/Brian%20Fuchs–PDSI%20and%20scPDSI.pdf
think you for your article，could i calculate the PDSI using a special R software package？i kindly want to it
and looking forward to your early reply.
yes, you can calculate drought using scPDSI package in R which gives both PDSI and scPDSI.
i kindly request the equation for the PDSI
Could this method be useful for Nepal?
Thank you for your email. PDSI was developed in the USA for deep soils. The PDSI is also a bit difficult to program. The SPI is much simpler and user to use. However, the SPI only uses precipitation and the PDSI uses temperature. So the PDSI is better suited for climate change studies. What is the application that you are working on?
kindly send me fromula or equation of Palmer Drought Severity Index (PDSI)
it will be appreciated.
Please see the original paper by Palmer: