PENGEMBANGAN MODEL CURAH HUJAN-RUN-OFF BERBASIS CLOUD MENGGUNAKAN GOOGLE EARTH ENGINE DI MUARA SUNGAI BANYUASIN, SUMATERA SELATAN

SARMILA, RIA and Surbakti, Heron (2024) PENGEMBANGAN MODEL CURAH HUJAN-RUN-OFF BERBASIS CLOUD MENGGUNAKAN GOOGLE EARTH ENGINE DI MUARA SUNGAI BANYUASIN, SUMATERA SELATAN. Undergraduate thesis, Sriwijaya University.

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Abstract

Run-off happens when the soil is unable to collect rainwater. It plays a significant role in transporting domestic waste, but there is limited data on run- off. The SCS-CN (Soil Conservation Services-Curve Number) method calculates run-off estimates by considering land characteristics like vegetation, soil, and land use. Google Earth Engine (GEE) is effective for analyzing extensive geographic data. This study aims to validate the accuracy of modeled rainfall data and analyze the impact of land use and land cover (LULC) on run-off in the Banyuasin River Estuary from 2018 to 2022. The study areas include Lalan River, Banyuasin River, and Banyuasin River Estuary. Data processing involves validating rainfall data (CHIRPS) using BMKG data and processing of soil maps, LULC maps, soil moisture maps, and CN maps. The results of this study show that the correlation of rainfall data of the Lalan River is 0.461 (medium), for the Banyuasin River is 0.642 (strong) and for the Banyuasin River Estuary is 0.710 (strong). Lalan River has two LULC classes, Banyuasin River has six LULC classes, and Banyuasin River Estuary has eight LULC classes. High CN values lead to increased run-off. The run-off forecast model shows that the highest run- off is in 2022, which is 3,446.97 mm for the Lalan River, 2,895.74 mm for the Banyuasin River, and 2,965.44 mm for the Banyuasin River Estuary. Further research could utilize weather radar data and add cross-sectional area data to produce discharge data, which can be used for flood mitigation.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Run-off, Curah hujan, Muara Sungai, Google Earth Engine, Land Use/Land Cover
Subjects:	G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography > GA125-155 Map drawing, modeling, printing, reading, etc. G Geography. Anthropology. Recreation > GB Physical geography
Divisions:	08-Faculty of Mathematics and Natural Science > 54241-Marine Science (S1)
Depositing User:	Ria Sarmila
Date Deposited:	18 Jul 2024 05:09
Last Modified:	18 Jul 2024 05:09
URI:	http://repository.unsri.ac.id/id/eprint/151391

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