Potensi Terjadinya Banjir Rob Akibat Penurunan Muka Tanah dan Kenaikan Muka Air Laut di Kabupaten Badung, Bali

Frans Elvansha, I. Hendrawan, Ida Bagus Mandhara Brasika
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Abstract

Badung Regency is one of the tourist areas crowded with visitors, so that development continues to be developed as a support for tourist areas, one of which is a hotel. Hotel construction can cause building loads in a certain period; it can cause land subsidence. Land subsidence that co-occurs with sea-level rise can potentially be a tidal flood in the future. This study aimed to determine the rate of land subsidence in Badung Regency and the potential for tidal flooding due to land subsidence and sea-level rise in Badung Regency. The method used to calculate the rate of land subsidence is Small Baseline Subset Differential Interferometric Synthetic Aperture Radar (SBAS-DInSAR), which utilizes radar satellite imagery data Sentinel-1a IW level 1.1 images and Sentinel-1b IW level 1.1 images. The image data used in the SBAS-DInSAR method consists of 166 image data and Digital Elevation Model (DEM) data with a spatial resolution of 30 m which is used for the topographic phase removal phase. Meanwhile, land subsidence data is used to determine the potential for tidal flooding, and it is predicted using regression; then, an overlay is carried out with the highest tide data along with the value of sea-level rise every year. To facilitate the observation of land subsidence, the daily image data obtained are then averaged into monthly data in each village. The fastest land subsidence rate from 2014 to 2020 occurred in Tuban Village. The prediction of the most significant tidal flood in 2030 to 2040 will occur in Tuban Village due to the influence of rapid land subsidence in the village.
巴东摄政区是旅游区之一,游客络绎不绝,使发展成为支撑旅游区不断发展的地方,其中之一就是酒店。酒店建设在一定时期内会引起建筑荷载;它会导致地面下沉。与海平面上升同时发生的地面沉降在未来可能会引发潮汐洪水。本研究旨在确定巴东县的地面沉降率,以及巴东县由于地面沉降和海平面上升而发生潮汐洪水的可能性。计算地表沉降速率的方法是小基线子集差分干涉合成孔径雷达(SBAS-DInSAR),该方法利用雷达卫星图像数据Sentinel-1a IW 1.1级图像和Sentinel-1b IW 1.1级图像。SBAS-DInSAR方法使用的图像数据包括166幅图像数据和用于地形相位去除阶段的空间分辨率为30 m的数字高程模型(DEM)数据。同时,利用地面沉降数据确定潮汐洪水发生的可能性,并进行回归预测;然后,将每年的最高潮位数据与海平面上升值进行叠加。为了便于观测地表沉降,将获得的每日图像数据平均为每个村庄的月度数据。2014 - 2020年地表沉降速度最快的是土班村。预计2030 ~ 2040年最显著的潮汐洪水将发生在土班村,受该村地面快速沉降的影响。
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