Skip to main content

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

Project description

PyPI

SPEI

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). 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 since it is easier to only deal with time series. Therefore, this package uses the popular Python packages such as Pandas and Scipy to make it easy but versitile for the user to calculate the drought indices. With the use of Scipy all distributions available in the library can be used to fit the data. However, there are general recommendations for distributions when calculating the SPEI, SPI an SGI.

Note that, all time series have to be calculated in advance and be provided as a pandas Series. For the calculation of potential evaporation, we refer to pyet.

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 .

Nice to haves in the future:

  • Add way to identify best distribution on time series (with Scipy, Fitter or distfit)

  • Check SGI for other distributions

Feel free to contribute!

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

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-0.1.8.tar.gz (8.6 kB view details)

Uploaded Source

Built Distribution

spei-0.1.8-py3-none-any.whl (8.2 kB view details)

Uploaded Python 3

File details

Details for the file spei-0.1.8.tar.gz.

File metadata

  • Download URL: spei-0.1.8.tar.gz
  • Upload date:
  • Size: 8.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.6

File hashes

Hashes for spei-0.1.8.tar.gz
Algorithm Hash digest
SHA256 5988266dffea8b711bf45393d98b6be123ecac2a0eeca6da2617fed45a9a5b8d
MD5 1543b9934e6ea3a16da2de650ecf2e8f
BLAKE2b-256 c025dfa9183f5d84aab1a28813dd69b0cf753a8c59eb1df6d99522e42f59870f

See more details on using hashes here.

File details

Details for the file spei-0.1.8-py3-none-any.whl.

File metadata

  • Download URL: spei-0.1.8-py3-none-any.whl
  • Upload date:
  • Size: 8.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.6

File hashes

Hashes for spei-0.1.8-py3-none-any.whl
Algorithm Hash digest
SHA256 053ca7acdf969abe31c252f864b55ae4491d3014c11b6746ab4e8aae509e0026
MD5 f798c01d3809ee43308b74d58ed6b081
BLAKE2b-256 b070f75078689b16ff24aafd1e37251c4ce3df3846dec989ec6288759fd321cc

See more details on using hashes here.

Supported by

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