Niyigena et al. (2025) Assessment of rainfall variability and trend using variational indices and modified Mann Kendell-Test in Gicumbi, Northern Province of Rwanda

Identification

• Journal: Discover Environment
• Year: 2025
• Date: 2025-09-12
• Authors: Bernard Niyigena, Jean Uwamahoro, Innocent Nkurikiyimfura, Joseph Ndakize Sebaziga, Jonah Kazora, Vedaste Iyakaremye, David Ukwishaka, Bernardin Bavuge, Aminadab Tuyisenge, Alexis Nizeyimana, Olive Byukusenge, William Mugabo, Godfrey Musafiri, Justin Munyaneza, Patrick Iradukunda Mugaragu
• DOI: 10.1007/s44274-025-00338-z

Research Groups

• Rwanda Meteorology Agency, Kigali, Rwanda
• College of Science and Technology, University of Rwanda, Kigali, Rwanda
• College of Education, University of Rwanda, Rwamagana, Rwanda
• Rwanda Environment Management Authority, Kigali, Rwanda
• University of Lay Adventists of Kigali, Kigali, Rwanda
• Climate and Clean Air Coalition Secretariat, Hosted By the United Nations Environment Program, Paris, France
• Rwanda Climate Change Development Network, Kigali, Rwanda
• Ministry of Environment, Kigali, Rwanda
• Rwanda Water Board, Kigali, Rwanda
• Ministry of Education, Kigali, Rwanda

Short Summary

This study assessed rainfall variability and trends in Rwanda's Gicumbi district (1983-2021), identifying three homogeneous climate zones and revealing high monthly/seasonal variability (especially in dry seasons) but no statistically significant trends in rainfall patterns.

Objective

• To assess rainfall variability and trends in Gicumbi district, Rwanda, using variational indices and the Modified Mann–Kendall test to inform sustainable agricultural planning and climate adaptation strategies.

Study Configuration

• Spatial Scale: Gicumbi district, Northern Province of Rwanda, spanning an area of 829 km². Gridded rainfall data at a spatial resolution of 0.0375 degrees (approximately 4 km).
• Temporal Scale: 1983 to 2021 (39 years), analyzed on monthly, seasonal (January–February, March–May, June–August, September–December), and annual scales.

Methodology and Data

• Models used:
  • k-means clustering (for delineating homogeneous climatic zones)
  • Coefficient of Variability (CV)
  • Precipitation Concentration Index (PCI)
  • Rainfall Anomaly Index (RAI)
  • Modified Mann–Kendall (MMK) trend test
  • Sen’s slope estimator
• Data sources: Daily gridded rainfall dataset from the Rwanda Meteorology Agency (Meteo Rwanda), developed in partnership with the International Research Institute for Climate and Society (IRI) at Columbia University’s Earth Institute through the Enhancing National Climate Services (ENACTS) initiative. Maximum and minimum temperature data were also used for clustering.

Main Results

• Gicumbi district was delineated into three nearly homogeneous climate zones: Southern Highland, Central Highland, and Northern Highland.
• Rainfall variability was significantly higher during dry seasons (June–August: 64%; January–February: 33%) compared to wet seasons (March–May: 21%; September–December: 20%).
• The annual average rainfall variability was 18%, indicating relatively low overall annual variability.
• No statistically significant trends were observed in monthly, seasonal, or annual rainfall patterns across any of the identified zones.
• Dry years were more frequent than wet years during the dry seasons, while the opposite was observed during the rainy seasons.
• The year 2017 was identified as the driest year throughout the entire study period across all zones.
• Intra-annual rainfall variability was found to be higher than inter-annual variability.

Contributions

• Provides the first specific assessment of rainfall variability and trends for the Gicumbi district, addressing a gap in previous studies that focused on national or provincial scales in Rwanda.
• Delineates specific, nearly homogeneous climatic zones within Gicumbi, offering localized insights for agricultural planning and water resource management.
• Offers valuable insights for improving seasonal forecasting, sustainable agricultural planning, and climate adaptation strategies tailored to the Gicumbi District's specific conditions.
• Utilizes a Modified Mann–Kendall test to account for autocorrelation, enhancing the reliability of trend analysis.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Citation

@article{Niyigena2025Assessment,
  author = {Niyigena, Bernard and Uwamahoro, Jean and Nkurikiyimfura, Innocent and Sebaziga, Joseph Ndakize and Kazora, Jonah and Iyakaremye, Vedaste and Ukwishaka, David and Bavuge, Bernardin and Tuyisenge, Aminadab and Nizeyimana, Alexis and Byukusenge, Olive and Mugabo, William and Musafiri, Godfrey and Munyaneza, Justin and Mugaragu, Patrick Iradukunda},
  title = {Assessment of rainfall variability and trend using variational indices and modified Mann Kendell-Test in Gicumbi, Northern Province of Rwanda},
  journal = {Discover Environment},
  year = {2025},
  doi = {10.1007/s44274-025-00338-z},
  url = {https://doi.org/10.1007/s44274-025-00338-z}
}