<![CDATA[Climate change and rapid urbanization are increasing the intensity and uncertainty of rainfall in urban areas, including Denpasar City. The transition from the dry season to the rainy season is often followed by extreme rainfall that triggers floods, disrupts community activities, damages infrastructure, and significantly hinders economic activities. This condition is exacerbated by massive land conversion and the accumulation of waste that clogs drainage systems, leading to a drastic decrease in surface water holding capacity. Therefore, hydrometeorological disaster mitigation has become an urgent need, which must be supported by accurate and reliable spatial rainfall information to identify vulnerable areas and design more effective flood control strategies. This study evaluates and compares the spatial interpolation methods of Inverse Distance Weighting (IDW), Kriging, and Spline in mapping the distribution of design rainfall in Denpasar City. Data were obtained from six stations over the period 2013–2022 and analyzed based on various return periods, namely 2, 5, 10, 15, 20, 25, and 50 year. To comprehensively assess the performance of interpolation methods, statistical indicators such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²) were used. The results show that IDW is most accurate for short return periods, particularly 2 year, with low MAE, MAPE, and RMSE and high R². Kriging excels for medium to long return periods (5–50 years), producing stable predictions that closely match the observed data, while Spline tends to have higher errors and low R², especially for long return periods. This result confirms that IDW and Kriging are the most reliable and accurate methods for mapping the distribution of design rainfall in Denpasar City. ]]>
