This study characterizes seasonal drought variability at nine synoptic stations spanning Burkina Faso’s climatic zones over 1981-2021, using the Standardized Precipitation Index (SPI-3) and the Standardized Precipitation Evapotranspiration Index (SPEI-3) computed at nine synoptic stations representative of the country’s three climatic zones—Sahelian, Sudano-Sahelian, and Sudanian. A multi-indicator approach combining non-parametric trend analysis (Hamed-Rao modified Mann-Kendall test, Sen’s slope) and structural change point detection (Pettitt test) is applied to two intra-seasonal windows: the early rainy season (MJJ: May-June-July) and the late rainy season (ASO: August-September-October). Results reveal three structurally distinct hydroclimatic phases. The period 1981-1990 was dominated by severe and extreme droughts, spatially coherent across all zones and concentrated in the Sahelian sector. A partial rainfall recovery emerged from 1991 onward, consistent with the documented Sahelian re-greening, with significant structural change points clustering in two windows: 1997 and 2007-2009. However, SPEI-3 systematically detects higher moderate and severe drought frequencies than SPI-3 after 2000, revealing an intensification of evapotranspiration-driven water stress decoupled from precipitation trends—particularly in the Sudano-Sahelian zone and at the late-season scale. SPI-3 retains superior sensitivity for extreme drought detection, driven by catastrophic rainfall deficits, while SPEI-3 better captures chronic, low-intensity stress with direct implications for rainfed agriculture. The early season (MJJ) constitutes the primary locus of monsoon onset vulnerability, while the late season (ASO) experiences increasing thermal amplification of drought, particularly in the Sudanian zone. These findings underscore the diagnostic necessity of jointly using SPI-3 and SPEI-3 for drought monitoring in semi-arid West Africa, and provide a spatially differentiated evidence base for climate adaptation strategies in a country where over 80% of the population depends on rainfed agriculture.
References
[1]
Mbaye, M.L., Bodian, A., Kimambo, O.N., Rouamba, F.I. and Gaveta, E. (2021) Analyses of Past Extremes Precipitation-Evapotranspiration Indices over Sub-Saharan Countries. JournalofExtremeEvents, 8, Article ID: 2250002. https://doi.org/10.1142/s2345737622500026
[2]
Peng, J., Dadson, S., Hirpa, F., Dyer, E., Lees, T., Miralles, D.G., et al. (2020) A Pan-African High-Resolution Drought Index Dataset. EarthSystemScienceData, 12, 753-769. https://doi.org/10.5194/essd-12-753-2020
[3]
Sarr, M., Moussa, A.M., Wade, M., Deme, E.H. and Diop, B. (2024) Regional Climate Models in the Simulation of the Drought of the 1970’s and 1980’s Years in Senegal (in West Africa). JournalofWaterResourceandProtection, 16, 585-604. https://doi.org/10.4236/jwarp.2024.169034
[4]
Taylor, R.G., Todd, M.C., Kongola, L., Maurice, L., Nahozya, E., Sanga, H., et al. (2013) Evidence of the Dependence of Groundwater Resources on Extreme Rainfall in East Africa. NatureClimateChange, 3, 374-378. https://doi.org/10.1038/nclimate1731
[5]
Sogno, P., Klein, I. and Kuenzer, C. (2022) Remote Sensing of Surface Water Dynamics in the Context of Global Change—A Review. RemoteSensing, 14, Article No. 2475. https://doi.org/10.3390/rs14102475
[6]
Kingsford, R.T., Bino, G., Finlayson, C.M., Falster, D., Fitzsimons, J.A., Gawlik, D.E., et al. (2021) Ramsar Wetlands of International Importance-improving Conservation Outcomes. FrontiersinEnvironmentalScience, 9, Article ID: 643367. https://doi.org/10.3389/fenvs.2021.643367
[7]
Fowé, T., Yonaba, R., Mounirou, L.A., Ouédraogo, E., Ibrahim, B., Niang, D., et al. (2023) From Meteorological to Hydrological Drought: A Case Study Using Standardized Indices in the Nakanbe River Basin, Burkina Faso. NaturalHazards, 119, 1941-1965. https://doi.org/10.1007/s11069-023-06194-5
[8]
Bambio, Y. (2013) Aid and Environment in Burkina Faso. WIDER Working Paper No. 2013/139, United Nations University World Institute for Development Eco-nomics Research (UNU-WIDER).
[9]
Le, P.V.V., Phan‐Van, T., Mai, K.V. and Tran, D.Q. (2019) Space-Time Variability of Drought over Vietnam. InternationalJournalofClimatology, 39, 5437-5451. https://doi.org/10.1002/joc.6164
[10]
Li, J., Wang, Y., Li, Y., Ming, W., Long, Y. and Zhang, M. (2022) Relationship between Meteorological and Hydrological Droughts in the Upstream Regions of the Lancang-Mekong River. JournalofWaterandClimateChange, 13, 421-433. https://doi.org/10.2166/wcc.2021.445
[11]
Zhou, Z., Shi, H., Fu, Q., Ding, Y., Li, T. and Liu, S. (2021) Investigating the Propagation from Meteorological to Hydrological Drought by Introducing the Nonlinear Dependence with Directed Information Transfer Index. WaterResourcesResearch, 57, e2021WR030028. https://doi.org/10.1029/2021wr030028
[12]
Hasan, H.H., Mohd Razali, S.F., Muhammad, N.S. and Ahmad, A. (2021) Hydrological Drought across Peninsular Malaysia: Implication of Drought Index. Natural Hazards and Earth System Sciences Discussions. https://doi.org/10.5194/nhess-2021-249
[13]
Morid, S., Smakhtin, V. and Moghaddasi, M. (2006) Comparison of Seven Meteorological Indices for Drought Monitoring in Iran. InternationalJournalofClimatology, 26, 971-985. https://doi.org/10.1002/joc.1264
[14]
Zargar, A., Sadiq, R., Naser, B. and Khan, F.I. (2011) A Review of Drought Indices. EnvironmentalReviews, 19, 333-349. https://doi.org/10.1139/a11-013
[15]
McKee, T.B., Doesken, N.J. and Kleist, J. (1993) The Relationship of Drought Frequency and Duration to Time Scales. Proceedings of the 8th Conference on Ap-plied Climatology, Anaheim, 17-22 January 1993, 179-183.
[16]
Vicente-Serrano, S.M., Beguería, S. and López-Moreno, J.I. (2010) A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. JournalofClimate, 23, 1696-1718. https://doi.org/10.1175/2009jcli2909.1
[17]
Beguería, S., Vicente-Serrano, S.M., Reig, F. and Latorre, B. (2014) Standardized Precipitation Evapotranspiration Index (SPEI) Revisited: Parameter Fitting, Evapotranspiration Models, Tools, Datasets and Drought Monitoring. InternationalJournalofClimatology, 34, 3001-3023. https://doi.org/10.1002/joc.3887
[18]
Yameogo, W.V.M., Kabore, O., Sanon, Z., Akpa, Y.L., Traore, F., Tankoano, B., et al. (2023) Dynamique spatio-temporelle des surfaces en eau du bassin du Nakanbé-Mané au Burkina Faso. InternationalJournalofBiologicalandChemicalSciences, 17, 233-246. https://doi.org/10.4314/ijbcs.v17i1.17
[19]
Gbohoui, Y.P., Paturel, J., Fowe, T., Karambiri, H. and Yacouba, H. (2021) Impacts des changements climatique et environnemental sur la réponse hydrologique du bassin du Nakanbé à Wayen (Burkina Faso) à travers le cadre de budyko. ProceedingsoftheInternationalAssociationofHydrologicalSciences, 384, 269-273. https://doi.org/10.5194/piahs-384-269-2021
[20]
Yonaba, R., Biaou, A.C., Ko？ta, M., Tazen, F., Mounirou, L.A., Zouré, C.O., et al. (2021) A Dynamic Land Use/Land Cover Input Helps in Picturing the Sahelian Paradox: Assessing Variability and Attribution of Changes in Surface Runoff in a Sahelian Watershed. ScienceoftheTotalEnvironment, 757, Article ID: 143792. https://doi.org/10.1016/j.scitotenv.2020.143792
[21]
Yonaba, R., Mounirou, L.A., Tazen, F., Ko？ta, M., Biaou, A.C., Zouré, C.O., et al. (2024) Future Climate or Land Use? Attribution of Changes in Surface Runoff in a Typical Sahelian Landscape. ComptesRendus.Géoscience, 355, 411-438. https://doi.org/10.5802/crgeos.179
[22]
Di Nunno, F., Yildiz, M.B. and Granata, F. (2025) Decoding the Architecture of Drought: SHAP-Enhanced Insights into the Climate Forces Reshaping the Sahel. Copernicus GmbH.
[23]
Millogo, Z.N., Okogbue, E.C., Diasso, J.U., Ochei, M.C. and Sawadogo, W. (2025) Projection of Heatwave Characteristics over Burkina Faso under the Shared Socioeconomic Pathways Scenarios—SSP2-4.5 and SSP5-8.5. TheoreticalandAppliedClimatology, 156, Article No. 461. https://doi.org/10.1007/s00704-025-05676-9
[24]
Ki, G.Z., Kébré, M.B., Somda, W., Gandema, S. and Dabilgou, F. (2026) Exploratory Data Analysis of Burkina Faso’s Raw Daily Meteorological Records (1981-2021): Data Quality Insights and Potential Outlier Screening. Environmental Research: Climate, 8, Article ID: 051012.
[25]
Abramowitz, M. and Stegun, I.A. (1964) Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Applied Mathematics Series 55, National Bureau of Standards, Washington DC.
[26]
Vonk, M.A. (2025) SPEI: A Python Package for Calculating and Visualizing Drought Indices. JournalofOpenSourceSoftware, 10, Article No. 8454. https://doi.org/10.21105/joss.08454
[27]
Xiong, X., Zhou, J., Liu, X. and Cui, Y. (2022). The Potential of Using Dynamic Surface Water Products for Drought Monitoring. IGARSS 2022-2022 IEEE International Geoscience and Remote Sensing Symposium, Kuala Lumpur, 17-22 July 2022, 6308-6311. https://doi.org/10.1109/igarss46834.2022.9884112
[28]
Hamed, K.H. and Ramachandra Rao, A. (1998) A Modified Mann-Kendall Trend Test for Autocorrelated Data. JournalofHydrology, 204, 182-196. https://doi.org/10.1016/s0022-1694(97)00125-x
Kendall, M.G. (1975) Rank Correlation Methods. 4th Edition, Charles Griffin.
[31]
Sen, P.K. (1968) Estimates of the Regression Coefficient Based on Kendall’s Tau. JournaloftheAmericanStatisticalAssociation, 63, 1379-1389. https://doi.org/10.1080/01621459.1968.10480934
[32]
Pettitt, A.N. (1979) A Non-Parametric Approach to the Change-Point Problem. AppliedStatistics, 28, 126-135. https://doi.org/10.2307/2346729
[33]
Hussain, M. and Mahmud, I. (2019) pyMannKendall: A Python Package for Non Parametric Mann Kendall Family of Trend Tests. JournalofOpenSourceSoftware, 4, Article No. 1556. https://doi.org/10.21105/joss.01556
[34]
Pohlert, T. (2023) trend: Non-Parametric Trend Tests and Change-Point Detection. R Package Version 1.1.6. https://CRAN.R-project.org/package=trend
[35]
Militino, A.F., Moradi, M. and Ugarte, M.D. (2020) On the Performances of Trend and Change-Point Detection Methods for Remote Sensing Data. RemoteSensing, 12, Article No. 1008. https://doi.org/10.3390/rs12061008
[36]
Nicholson, S. (2005) On the Question of the “Recovery” of the Rains in the West African Sahel. JournalofAridEnvironments, 63, 615-641. https://doi.org/10.1016/j.jaridenv.2005.03.004
[37]
Biasutti, M. (2019) Rainfall Trends in the African Sahel: Characteristics, Processes, and Causes. WIREsClimateChange, 10, e591. https://doi.org/10.1002/wcc.591
[38]
Sylla, M.B., Nikiema, P.M., Gibba, P., Kebe, I. and Klutse, N.A.B. (2016) Climate Change over West Africa: Recent Trends and Future Projections. In: Yaro, J.A. and Hesselberg, J., Eds., AdaptationtoClimateChangeandVariabilityinRuralWestAfrica, Springer International Publishing, 25-40. https://doi.org/10.1007/978-3-319-31499-0_3
[39]
Fontaine, B., Gaetani, M., Ullmann, A. and Roucou, P. (2011) Time Evolution of Observed July-September Sea Surface Temperature-Sahel Climate Teleconnection with Removed Quasi-Global Effect (1900-2008). JournalofGeophysicalResearch, 116, D04105. https://doi.org/10.1029/2010jd014843
[40]
Stagge, J.H., Tallaksen, L.M., Gudmundsson, L., Van Loon, A.F. and Stahl, K. (2015) Candidate Distributions for Climatological Drought Indices (SPI and SPEI). InternationalJournalofClimatology, 35, 4027-4040. https://doi.org/10.1002/joc.4267
[41]
Salack, S., Sarr, B., Sangare, S.K., Ly, M., Sanda, I.S. and Kunstmann, H. (2015) Crop-climate Ensemble Scenarios to Improve Risk Assessment and Resilience in the Semi-Arid Regions of West Africa. ClimateResearch, 65, 107-121. https://doi.org/10.3354/cr01282
[42]
Sivakumar, M.V.K. (1992) Empirical Analysis of Dry Spells for Agricultural Applications in West Africa. JournalofClimate, 5, 532-539. https://doi.org/10.1175/1520-0442(1992)005<0532:eaodsf>2.0.co;2
[43]
Zhao, T. and Dai, A. (2015) The Magnitude and Causes of Global Drought Changes in the Twenty-First Century under a Low-Moderate Emissions Scenario. JournalofClimate, 28, 4490-4512. https://doi.org/10.1175/jcli-d-14-00363.1
[44]
Lebel, T. and Ali, A. (2009) Recent Trends in the Central and Western Sahel Rainfall Regime (1990-2007). JournalofHydrology, 375, 52-64. https://doi.org/10.1016/j.jhydrol.2008.11.030
[45]
Panthou, G., Lebel, T., Vischel, T., Quantin, G., Sane, Y., Ba, A., et al. (2018) Rainfall Intensification in Tropical Semi-Arid Regions: The Sahelian Case. EnvironmentalResearchLetters, 13, Article ID: 064013. https://doi.org/10.1088/1748-9326/aac334
