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RASIONALISASI KERAPATAN POS HUJAN MENGGUNAKAN METODE KAGAN-RODDA DI SUB DAS LESTI Alfirman, Zulfikar R.; Limantara, Lily M.; Wahyuni, Sri
Jurnal Teknik Sipil Vol 8, No 2 (2019): Jurnal Teknik Sipil
Publisher : Jurnal Teknik Sipil

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.333 KB)

Ketelitian data hujan yang tidak akurat sering menyebabkan pengelolaan SDA (sumber daya air) tidak berjalan sesuai harapan. Mengingat pentingnya informasi data hujan maka diperlukan kajian rasionalisasi atau perencanaan jaringan stasiun hujan yang efektif dan efisien. Studi ini dilakukan di Sub DAS Lesti dengan luas 378,2 km2 menggunakan metode WMO (World Meteorogical Organization) dan Kagan-Rodda. Hasil analisa berdasarkan standar WMO 100-250 km2/stasiun hujan, hanya 2 dari 5 stasiun hujan yaitu Dampit dan Poncokusumo yang memenuhi standar. Hasil analisa Kagan-Rodda berdasarkan nilai kesalahan perataan 5% adalah Sub DAS Lesti cukup memiliki 3 stasiun hujan. Hasil rasionalisasi dengan titik stasiun acuan Poncokusumo, menghasilkan rekomendasi menggeser stasiun Dampit sejauh 5,9 km ke utara dan membentuk stasiun hujan baru (A) yang berlokasi di sebelah tenggara stasiun hujan Dampit. Hasil rekomendasi tersebut memiliki luas pengaruh yang sesuai standar WMO untuk masing-masing stasiun hujan, yaitu: Poncokusumo 110,8 km2, Dampit 156,5 km2, dan A 110,9 km2.Accuracy of inaccurate rainfall data often results in inefficient management of water resources. Considering the importance of rainfall data information, an effective and efficient rational study or planning of a rain gauge network is needed. This study was conducted in the Lesti Sub-Watershed with an area of 378,2 km2 using the WMO (World Meteorogical Organization) and Kagan-Rodda methods. The results of the analysis based on WMO standards 100-250 km2/rain gauge, only 2 out of 5 rain gauges which is Dampit and Poncokusumo are qualified. The results of the Kagan-Rodda analysis based on a 5% leveling error value are that Lesti Sub-Watershed has enough 3 rain gauges. The results of rationalization with the Poncokusumo reference station point resulted in a recommendation to shift the Dampit station as far as 5,9 km to the north and form a new rain station (A) located to the southeast of the Dampit rain station. The results of the recommendation have an area of influence in accordance with the WMO standard for each rain gauge, namely: Poncokusumo 110,8 km2, Dampit 156,5 km2, and A 110,9 km2.

RASIONALISASI KERAPATAN POS HUJAN MENGGUNAKAN METODE KAGAN-RODDA DI SUB DAS LESTI Alfirman, Zulfikar R.; Limantara, Lily M.; Wahyuni, Sri
Jurnal Teknik Sipil Vol 8, No 2 (2019): Jurnal Teknik Sipil
Publisher : Jurnal Teknik Sipil

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (486.333 KB)

Ketelitian data hujan yang tidak akurat sering menyebabkan pengelolaan SDA (sumber daya air) tidak berjalan sesuai harapan. Mengingat pentingnya informasi data hujan maka diperlukan kajian rasionalisasi atau perencanaan jaringan stasiun hujan yang efektif dan efisien. Studi ini dilakukan di Sub DAS Lesti dengan luas 378,2 km2 menggunakan metode WMO (World Meteorogical Organization) dan Kagan-Rodda. Hasil analisa berdasarkan standar WMO 100-250 km2/stasiun hujan, hanya 2 dari 5 stasiun hujan yaitu Dampit dan Poncokusumo yang memenuhi standar. Hasil analisa Kagan-Rodda berdasarkan nilai kesalahan perataan 5% adalah Sub DAS Lesti cukup memiliki 3 stasiun hujan. Hasil rasionalisasi dengan titik stasiun acuan Poncokusumo, menghasilkan rekomendasi menggeser stasiun Dampit sejauh 5,9 km ke utara dan membentuk stasiun hujan baru (A) yang berlokasi di sebelah tenggara stasiun hujan Dampit. Hasil rekomendasi tersebut memiliki luas pengaruh yang sesuai standar WMO untuk masing-masing stasiun hujan, yaitu: Poncokusumo 110,8 km2, Dampit 156,5 km2, dan A 110,9 km2.Accuracy of inaccurate rainfall data often results in inefficient management of water resources. Considering the importance of rainfall data information, an effective and efficient rational study or planning of a rain gauge network is needed. This study was conducted in the Lesti Sub-Watershed with an area of 378,2 km2 using the WMO (World Meteorogical Organization) and Kagan-Rodda methods. The results of the analysis based on WMO standards 100-250 km2/rain gauge, only 2 out of 5 rain gauges which is Dampit and Poncokusumo are qualified. The results of the Kagan-Rodda analysis based on a 5% leveling error value are that Lesti Sub-Watershed has enough 3 rain gauges. The results of rationalization with the Poncokusumo reference station point resulted in a recommendation to shift the Dampit station as far as 5,9 km to the north and form a new rain station (A) located to the southeast of the Dampit rain station. The results of the recommendation have an area of influence in accordance with the WMO standard for each rain gauge, namely: Poncokusumo 110,8 km2, Dampit 156,5 km2, and A 110,9 km2.

Evaluation of Flood Inundation Image Detection Performance Using Deep Learning Soebroto, Arief A.; Limantara, Lily M.; Suhartanto, Ery; Moh. Sholichin; Ramdani, Fatwa; Rachmawati, Turniningtyas A.
Civil Engineering Journal Vol. 11 No. 11 (2025): November
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-11-08

Floods are the most frequently occurring natural disasters, significantly impacting the environment and society. As part of natural disaster mitigation, the impacts could be reduced through predictive techniques using deep learning for semantic segmentation of inundation images. Therefore, this research aims to evaluate the performance of deep learning architectures in segmenting inundation images using the Flood Segmentation dataset, which comprised 290 aerial images. The following segmentation architectures, U-Net, SegNet, and LinkNet, were compared using backbones such as MobileNet, ResNet, EfficientNet, and VGG, as well as optimizers including Adam, SGD, AdaDelta, and RMSProp. Performance was assessed using Intersection over Union (IoU) score, precision, F1-score, recall, and accuracy metrics. The results showed that U-Net achieved the highest performance with IoU, precision, F1-score, recall, and accuracy of 0.767, 0.862, 0.866, 0.876, and 0.899, respectively. Regarding the backbones, MobileNet excelled with IoU, precision, F1-score, recall, and accuracy of 0.764, 0.866, 0.865, 0.869, and 0.898, respectively. The Adam optimizer outperformed others, yielding IoU, precision, F1-score, recall, and accuracy of 0.712, 0.807, 0.824, 0.873, and 0.843. In conclusion, the combination of U-Net with MobileNet backbone and Adam optimizer was the most effective architecture for flood inundation image segmentation, offering a robust foundation for prediction systems.

A Model for the Reduction of Flood Peak Discharge (ΔQp) Due to the Retarding Basin Yuwono, Hari; Limantara, Lily M.; Sholichin, Moh.; Siswoyo, Hari
Civil Engineering Journal Vol. 11 No. 12 (2025): December
Publisher : Salehan Institute of Higher Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/CEJ-2025-011-12-012

This research aims to develop a model for flood peak discharge reduction (ΔQp) through the placement of retarding basins within a watershed system, represented by the area ratio of the controlled watershed (RAk) and the maximum storage capacity of the retarding basin (Vk). The area ratio of the controlled watershed (RAk) is defined as the ratio between the catchment area of the retarding basin and the total watershed area (Ak/A). The methodology involves simulating various retarding basin placements (RAk) and different maximum storage capacities (Vk) for several flood return periods (QT). This study was conducted in the urban agglomeration area of Wonosari, Gunungkidul Regency, Special Region of Yogyakarta, Indonesia. The placement and utilization of retarding basins result in varying levels of flood peak discharge reduction (ΔQp) at the downstream control point (Taman Pancuran), depending on the maximum storage capacity of the retarding basin (Vk) and its placement within the watershed (RAk). The resulting empirical equations for flood peak discharge reduction (ΔQp) using the retarding basin method are as follows: ΔQp = 0.105654 − 0.014593 Vk − 0.029251 RAk + 0.011089 QT for Vk values in the range (V1–V4) = 36.4–208.8 × 10³ m³, and ΔQp = 1.374989 − 0.003702 Vk − 0.338381 RAk + 0.004773 QT for Vk values in the range (V4–V200) = 136.2–7039.1 × 10³ m³. An observed anomaly was identified, where ΔQp became positive at small values of Vk and RAk, indicating an increase in peak discharge (Qp).

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