Skip to main content

A simple Python package to calculate drought indices for time series such as the SPI, SPEI and SGI.

Project description

SPEI

PyPI PyPi Supported Python Versions Code Size PyPi Downloads License

Tests CodacyGrade CodacyCoverage MyPy Black

SPEI is a simple Python package to calculate drought indices for time series such as the SPI (Standardized Precipitation Index), SPEI (Standardized Precipitation Evaporation Index) and SGI (Standardized Groundwater Index). This package uses popular Python packages such as Pandas and Scipy to make it easy and versitile for the user to calculate the drought indices. Pandas Series are great for dealing with time series; providing interpolation, rolling average and other manipulation options. SciPy enables us to use all different kinds of distributions to fit the data.

For the calculation of potential evaporation, take a look at pyet. This is another great package that uses pandas Series to calculate different kinds of potential evaporation time series.

Please feel free to contribute or ask questions!

Available Drought Indices

Drought Index Abbreviation Literature
Standardized Precipitation Index SPI 1
Standardized Precipitation Evaporation Index SPEI 2
Standardized Groundwater Index SGI 3,4
Standardized Streamflow Index SSFI 5

The package is not limited to only these four drought indices. If any of the distributions in the Scipy library is valid, the drought index can be calculated.

Installation

To get the latest stable version install using:

pip install spei

To get the development version download the GitHub code to your computer. Use cd to get to the download directory and install using:

pip install -e .

Literature

  1. B. Lloyd-Hughes and M.A. Saunders (2002) - A Drought Climatology for Europe. DOI: 10.1002/joc.846
  2. S.M. Vicente-Serrano, S. Beguería and J.I. López-Moreno (2010) - A Multi-scalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. DOI: 10.1175/2009JCLI2909.1
  3. J.P.Bloomfield and B.P. Marchant, B. P. (2013) - Analysis of groundwater drought building on the standardised precipitation index approach. DOI: 10.5194/hess-17-4769-2013
  4. A. Babre, A. Kalvāns, Z. Avotniece, I. Retiķe, J. Bikše, K.P.M. Jemeljanova, A. Zelenkevičs and A. Dēliņa (2022) - The use of predefined drought indices for the assessment of groundwater drought episodes in the Baltic States over the period 1989–2018. DOI: 10.1016/j.ejrh.2022.101049
  5. E. Tijdeman, K. Stahl and L.M. Tallaksen (2020) - Drought characteristics derived based on the Standardized Streamflow Index: A large sample comparison for parametric and nonparametric methods. DOI: 10.1029/2019WR026315

Note that the method for calculating the drought indices does not come from these articles and SciPy is used for deriving the distribution. However the literature is helpful as a reference to understand the context and application of drought indices.

Alternatives

There are other great packages available to calculate these indices. However, they are either written in R such as SPEI or don't have the Standardized Groundwater Index such as climate_indices. Additionaly, these packages provide ways to analyse spatial data and calculate potential evaporation. This makes these packages complex, because it is easier to only deal with time series.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

spei-0.3.2.tar.gz (13.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

spei-0.3.2-py3-none-any.whl (11.4 kB view details)

Uploaded Python 3

File details

Details for the file spei-0.3.2.tar.gz.

File metadata

  • Download URL: spei-0.3.2.tar.gz
  • Upload date:
  • Size: 13.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for spei-0.3.2.tar.gz
Algorithm Hash digest
SHA256 e0ed7e6b88948102316730ec845dd718abfd1642bcf127447812832ef73e3bd4
MD5 4e08e8b27f9eb18eda6b96bf419c8ff5
BLAKE2b-256 baae9e66f214e810298b3c613a02ea38175a91c81dded926243657e1b657b196

See more details on using hashes here.

File details

Details for the file spei-0.3.2-py3-none-any.whl.

File metadata

  • Download URL: spei-0.3.2-py3-none-any.whl
  • Upload date:
  • Size: 11.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.2

File hashes

Hashes for spei-0.3.2-py3-none-any.whl
Algorithm Hash digest
SHA256 c1d223078429f0f3e6ecedc0a6bb5939d1a30b8129719d6e5294fba9285d21a0
MD5 335e234bde538ad5595ade511dc34267
BLAKE2b-256 b537a74e249e35936b0c1afdc87024ef18e6d237494d194f1e431fcdc4a7ef3c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page