SPEI
Calculate and visualize some popular drought indices such as the SPI, SPEI and SGI.
https://github.com/martinvonk/SPEI
Category: Natural Resources
Sub Category: Water Supply and Quality
Keywords
drought drought-index drought-indices groundwater hydrology python sgi spei spi timeseries
Last synced: about 8 hours ago
JSON representation
Repository metadata
A Python package for calculating and visualizing drought indices such as the SPI, SPEI and SGI.
- Host: GitHub
- URL: https://github.com/martinvonk/SPEI
- Owner: martinvonk
- License: mit
- Created: 2022-07-28T09:49:22.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2025-09-09T09:12:51.000Z (4 months ago)
- Last Synced: 2025-10-26T06:44:35.279Z (2 months ago)
- Topics: drought, drought-index, drought-indices, groundwater, hydrology, python, sgi, spei, spi, timeseries
- Language: Python
- Homepage: https://martinvonk.github.io/SPEI/
- Size: 40.9 MB
- Stars: 97
- Watchers: 2
- Forks: 12
- Open Issues: 4
- Releases: 27
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
README.md
SPEI
SPEI is a simple Python package to calculate drought indices for hydrological time series. This package uses popular Python packages such as Pandas and Scipy to make it easy and versatile 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. Different popular drought indices are supported such as the SPI (Standardized Precipitation Index), SPEI (Standardized Precipitation Evaporation Index), and SGI (Standardized Groundwater Index).
If you use this software for either the visualization and/or analysis, please cite this package via our article in the Journal of Open Source Software:
Vonk, M. A. (2025). SPEI: A Python package for calculating and visualizing drought indices. Journal of Open Source Software, 10(111), 8454. doi.org/10.21105/joss.08454.
Or cite a specific version in the Zenodo archive:
Vonk, M. A. (XXXX). SPEI: A simple Python package to calculate and visualize drought indices (vX.X.X). Zenodo. doi.org/10.5281/zenodo.10816740.
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 | 5,6 |
| Standardized Soil Moisture Index | SSMI | 7 |
The package is not limited to only these five drought indices. If any of the distributions in the Scipy library is valid on the observed hydrological series, the drought index can be calculated.
*For the calculation of potential evaporation, take a look at pyet. This is another great package that also uses pandas Series to calculate different kinds of potential evaporation time series.
Installation
To get the latest stable version install using:
pip install spei
To get the development version download or clone the GitHub repository to your local device. Install using:
pip install -e <download_directory>
Literature
This list of scientific literature is helpful as a reference to understand the context and application of drought indices.
- Lloyd-Hughes, B. and M.A. Saunders (2002) - A Drought Climatology for Europe. DOI: 10.1002/joc.846
- Vicente-Serrano, S.M., 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
- Bloomfield, J.P. and B.P. Marchant (2013) - Analysis of groundwater drought building on the standardised precipitation index approach. DOI: 10.5194/hess-17-4769-2013
- Babre, A., 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
- Vicente-Serrano, S. M., J. I. López-Moreno, S. Beguería, J. Lorenzo-Lacruz, C. Azorin-Molina, and E. Morán-Tejeda (2012). Accurate Computation of a Streamflow Drought Index. Journal of Hydrologic Engineering. American Society of Civil Engineers. DOI: 10.1061/(asce)he.1943-5584.0000433
- Tijdeman, E., 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
- Carrão. H., Russo, S., Sepulcre-Canto, G., Barbosa, P.: An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data. DOI: 10.1016/j.jag.2015.06.011s
Publications
These are scientific publications that use and cite this Python package:
van Mourik, J., Ruijsch, D., van der Wiel, K., Hazeleger, W., & Wanders, N. (2025). Regional drivers and characteristics of multi-year droughts. Weather and Climate Extremes, 48, 100748. https://doi.org/10.1016/j.wace.2025.100748
Segura-Barrero, R., Lauvaux, T., Lian, J., Ciais, P., Badia, A., Ventura, S., Bazzi, H., Abbessi, E., Fu, Z., Xiao, J., Li, X., & Villalba, G. (2025). Heat and Drought Events Alter Biogenic Capacity to Balance CO2 Budget in South-Western Europe. Global biogeochemical cycles, 39(1), e2024GB008163. https://doi.org/10.1029/2024GB008163
Adla, S., Šaponjić, A., Tyagi, A., Nagi, A., Pastore, P., & Pande, S. (2024). Steering agricultural interventions towards sustained irrigation adoption by farmers: socio-psychological analysis of irrigation practices in Maharashtra, India. Hydrological Sciences Journal, 69(12), 1586–1603. https://doi.org/10.1080/02626667.2024.2376709
Panigrahi, S., Vidyarthi, V.K. (2025). Assessing the Suitability of SPI and SPEI in Steppe Hot and Arid Climatic Zones in India. In: Sefelnasr, A., Sherif, M., Singh, V.P. (eds) Water Resources Management and Sustainability. Water Science and Technology Library, vol 114. Springer, Cham. https://doi.org/10.1007/978-3-031-80520-2_12
Citation (CITATION.cff)
cff-version: "1.2.0"
authors:
- family-names: Vonk
given-names: M. A.
orcid: "https://orcid.org/0009-0007-3528-2991"
doi: 10.5281/zenodo.16441123
message: If you use this software, please cite our article in the
Journal of Open Source Software.
preferred-citation:
authors:
- family-names: Vonk
given-names: M. A.
orcid: "https://orcid.org/0009-0007-3528-2991"
date-published: 2025-07-29
doi: 10.21105/joss.08454
issn: 2475-9066
issue: 111
journal: Journal of Open Source Software
publisher:
name: Open Journals
start: 8454
title: "SPEI: A Python package for calculating and visualizing drought
indices"
type: article
url: "https://joss.theoj.org/papers/10.21105/joss.08454"
volume: 10
title: "SPEI: A Python package for calculating and visualizing drought
indices"
Owner metadata
- Name: Martin Vonk
- Login: martinvonk
- Email:
- Kind: user
- Description:
- Website:
- Location: Netherlands
- Twitter:
- Company: @tudelft, @ArtesiaWater
- Icon url: https://avatars.githubusercontent.com/u/66305055?u=4efe8c41f36e521d2727a5febf8c0c6f2b22c8de&v=4
- Repositories: 7
- Last ynced at: 2024-06-11T15:40:53.519Z
- Profile URL: https://github.com/martinvonk
GitHub Events
Total
- Create event: 13
- Release event: 4
- Issues event: 26
- Watch event: 19
- Delete event: 7
- Issue comment event: 23
- Push event: 223
- Pull request review comment event: 12
- Pull request review event: 8
- Pull request event: 22
- Fork event: 6
Last Year
- Create event: 11
- Release event: 3
- Issues event: 24
- Watch event: 13
- Delete event: 6
- Issue comment event: 22
- Push event: 212
- Pull request review comment event: 12
- Pull request review event: 8
- Pull request event: 18
- Fork event: 4
Committers metadata
Last synced: 15 days ago
Total Commits: 570
Total Committers: 1
Avg Commits per committer: 570.0
Development Distribution Score (DDS): 0.0
Commits in past year: 316
Committers in past year: 1
Avg Commits per committer in past year: 316.0
Development Distribution Score (DDS) in past year: 0.0
| Name | Commits | |
|---|---|---|
| martinvonk | v****t@g****m | 570 |
Issue and Pull Request metadata
Last synced: 14 days ago
Total issues: 26
Total pull requests: 60
Average time to close issues: 17 days
Average time to close pull requests: about 9 hours
Total issue authors: 16
Total pull request authors: 1
Average comments per issue: 1.5
Average comments per pull request: 0.05
Merged pull request: 56
Bot issues: 0
Bot pull requests: 0
Past year issues: 16
Past year pull requests: 16
Past year average time to close issues: 23 days
Past year average time to close pull requests: about 7 hours
Past year issue authors: 9
Past year pull request authors: 1
Past year average comments per issue: 1.44
Past year average comments per pull request: 0.0
Past year merged pull request: 13
Past year bot issues: 0
Past year bot pull requests: 0
Top Issue Authors
- martinvonk (10)
- filipematos95 (2)
- cherryleh (1)
- luizfiscina (1)
- Appleweier (1)
- 1JunGu (1)
- simoonoses1 (1)
- xiaoqi1010 (1)
- Mahsabzg (1)
- shirazi25 (1)
- agnespeltan (1)
- mengqi-z (1)
- mahronid (1)
- juliammassing (1)
- njdepsky (1)
Top Pull Request Authors
- martinvonk (60)
Top Issue Labels
- question (6)
- documentation (4)
- code quality (1)
Top Pull Request Labels
- enhancement (20)
- code quality (18)
- documentation (15)
- bug (3)
Package metadata
- Total packages: 1
-
Total downloads:
- pypi: 1,491 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 25
- Total maintainers: 1
pypi.org: spei
A simple Python package to calculate drought indices for time series such as the SPI, SPEI and SGI.
- Homepage:
- Documentation: https://spei.readthedocs.io/
- Licenses: MIT License Copyright (c) 2022 Martin Vonk Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
- Latest release: 0.8.0 (published 5 months ago)
- Last Synced: 2025-12-13T06:08:08.883Z (14 days ago)
- Versions: 25
- Dependent Packages: 0
- Dependent Repositories: 1
- Downloads: 1,491 Last month
-
Rankings:
- Dependent packages count: 10.038%
- Downloads: 12.513%
- Average: 14.736%
- Dependent repos count: 21.657%
- Maintainers (1)
Dependencies
- actions/checkout v3 composite
- actions/setup-python v4 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- matplotlib *
- numpy *
- pandas *
- scipy *
- toshimaru/auto-author-assign v1.6.2 composite
Score: 11.92366331438045