Simple Kriging for Rainfall Mapping: A Geostatistical Analysis of North East Amhara (Wollo), Ethiopia Using ArcMap Pro.

Abstract Background: Accurate spatial estimation of rainfall is essential for informed agricultural planning, sustainable water resource use, and climate resilience, particularly in data-scarce regions like North East Amhara (Wollo), Ethiopia.. In North East Amhara (Wollo), Ethiopia, rainfall data is often sparse and unevenly distributed, making it necessary to evaluate the spatial pattern of available rainfall gauge data for accurate interpolation and analysis. Method: This study compiled rainfall data from 55 meteorological stations, incorporating geographic and climatic variables such as mean annual rainfall, elevation, latitude, and longitude. Missing data were addressed to ensure completeness. Spatial distribution was visualized using ArcMap Pro, and Exploratory Spatial Data Analysis (ESDA) was conducted through histogram and Normal QQ plot analysis. To generate continuous rainfall surfaces, three interpolation methods Simple Kriging, Ordinary Kriging, and Universal Kriging were applied and evaluated using cross-validation metrics. Result: Simple Kriging emerged as the most accurate interpolation method. The spatial analysis revealed heterogeneous rainfall distribution, with low rainfall in the eastern and northern zones, high rainfall in the southwest, and moderate rainfall in the north-central region. A classification system was applied to categorize rainfall into low, medium, and high ranges, aiding in regional planning. Conclusion: The findings offer critical insights into the spatial rainfall patterns of North East Amhara and support the development of adaptive strategies such as drought-resistant crops, water-saving techniques, water storage infrastructure, and early warning systems. Long-term rainfall analysis is recommended to strengthen future planning and climate resilience efforts.