Spatiotemporal Dynamics of Rainfall Variability, Trends and Extreme Events in Hargeisa, Somaliland: A Google Earth Engine-Based Analysis

Rainfall variability strongly influences water availability, runoff generation, drought risk, and urban stormwater conditions in arid and semi-arid environments. Hargeisa, Somaliland, experiences pronounced seasonality and substantial year-to-year rainfall variability, but an integrated assessment across temporal scales, anomalies, spatial patterns, trends, and daily extremes remains limited. This study evaluates the recent rainfall regime of Hargeisa using daily Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS) and Google Earth Engine (GEE) for 2010–2025. Rainfall was processed within the study boundary and aggregated to monthly, seasonal, and annual scales.

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Publication Details

Journal
International Journal of Innovative Science and Research Technology (IJISRT)
Published
2026-10-28
DOI
https://doi.org/10.38124/ijisrt/26oct957
Primary Topic
Climate variability and models
Type
article
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article

Spatiotemporal Dynamics of Rainfall Variability, Trends and Extreme Events in Hargeisa, Somaliland: A Google Earth Engine-Based Analysis

Ahmed Abshir Ahmed
1 links
International Journal of Innovative Science and Research Technology (IJISRT)
Climate variability and models
article

Spatiotemporal Dynamics of Rainfall Variability, Trends and Extreme Events in Hargeisa, Somaliland: A Google Earth Engine-Based Analysis

Ahmed Abshir Ahmed
article en

Abstract

Rainfall variability strongly influences water availability, runoff generation, drought risk, and urban stormwater conditions in arid and semi-arid environments. Hargeisa, Somaliland, experiences pronounced seasonality and substantial year-to-year rainfall variability, but an integrated assessment across temporal scales, anomalies, spatial patterns, trends, and daily extremes remains limited. This study evaluates the recent rainfall regime of Hargeisa using daily Climate Hazards Center InfraRed Precipitation with Station data (CHIRPS) and Google Earth Engine (GEE) for 2010–2025. Rainfall was processed within the study boundary and aggregated to monthly, seasonal, and annual scales.

International Journal of Innovative Science and Research Technology (IJISRT)Vol. 11(10)
Climate action, Clean water and sanitation, Sustainable cities and communities
Openalex Percentile: Top 17%
Climate variability and models
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