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Analysis of Spatial Interpolation Method for Rainfall Mapping of Hydrometeorological Disaster Mitigation Design in Denpasar, Bali Tri Hayatining Pamungkas; Gede Sumarda; I Gusti Made Sudika; I Gusti Ngurah Eka Partama; I Ketut Kembarajaya; Kadek Budhi Warsana
INERSIA lnformasi dan Ekspose Hasil Riset Teknik Sipil dan Arsitektur Vol. 22 No. 1 (2026): May
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/inersia.v22i1.90147

Abstract

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. 
RASIONALISASI JARINGAN STASIUN CURAH HUJAN PADA DAERAH ALIRAN SUNGAI TUKAD MATI Putu Doddy Heka Ardana; I Gusti Made Sudika; I Wayan Angga Hadinata
PADURAKSA: Jurnal Teknik Sipil Universitas Warmadewa Vol. 12 No. 1 (2023)
Publisher : Program Studi Teknik Sipil, Fakultas Teknik dan Perencanaan, Universitas Warmadewa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22225/pd.12.1.6212.85-96

Abstract

The hydrological component is the main component in planning water infrastructure. The quality and quantity of rainfall data recorded at each rain post is the most crucial component in hydrological analysis, so it is necessary to analyze the rationalization of the rain station network to obtain an effective and efficient one. This research was conducted in the Tukad Mati Watershed, which has an area of 44,667 km2, with the length of the main river reaching 22,429 km, and there are six rain stations spread across the watershed. Rationalization analysis was carried out using two methods, namely the WMO (World Meteorological Organization) and Kagan-Rodda methods. The analysis using the WMO standard found that all rain stations were less than the minimum density. Meanwhile, from the results of the analysis using the Kagan-Rodda method with a smoothing error (Z1) of 9.069% and an interpolation error (Z3) of 7.989%, it is recommended that four selected rain stations out of six rain stations, namely Ngurah rain station, Sanglah rain station, Sading rain station, and Kapal rain station.