Analysis of the relationship between land use change and potential inundation rob in The Cipunagara River Basin using machine learning algorithms on google earth engine

Abstract

Changes in land use in watersheds play a major role in the study of changes in tidal inundation. Land use is a form of human effort to change the environment into a stable environment such as agricultural land, roads, plantations, and settlements. The purpose of this study is the slope of the catchment area, changes in land use in 1996-2020, and the potential for tidal flooding due to changes in land use in the Cipunagara watershed. The method used is the analysis of satellite images available on the Google Earth Engine platform data cloud using machine learning algorithms. The results of the slope analysis in the Cipunagara watershed are divided into five classes, namely the flat category with an area of 52.67 km2, the sloping category covering an area of 823.98 km2, slightly steep covering an area of 226.79 km2, steep covering an area of 126.02 km2, and very steep covering an area of 74.96 km2. Spatial changes in land use from 1996 to 2020, namely for open land/settlements decreased by -15% (-196.92 km2), forest vegetation increased by +11% (+145.78 km2), waters/water decreased by -13% (-164.96 km2), and paddy fields/ponds increased by +17% (+216.11 km2). Analysis of the potential for tidal inundation (river runoff) downstream of the Cipunagara watershed correlates with changes in the use of open land, forest vegetation, and rice fields with an area of 1,982 ha (47%). Meanwhile, the potential for tidal inundation (tidal events) is correlated with changes in the use of paddy fields and waters/water with an area of 2,213.93 ha (53%). The results of the research can be utilized in the management of flood risk in the downstream area of the watershed.

Perubahan penggunaan lahan pada daerah aliran sungai memainkan peran utama dalam studi perubahan luasan genangan banjir rob. Tata guna lahan merupakan bentuk usaha manusia mengubah lingkungan menjadi lingkungan yang mapan seperti lahan pertanian, jalan, perkebunan dan pemukiman. Tujuan dari penelitian ini adalah identifikasi kelerengan catchment area, identifikasi perubahan spasial tataguna lahan tahun 1996-2020 dan memetakan potensi banjir rob akibat perubahan tataguna lahan di DAS Cipunagara. Metode yang digunakan adalah analisis citra satelit yang tersedia di cloud data platform Google Earth Engine dengan menggunakan algoritma machine learning. Hasil analisis kemiringan lereng pada DAS Cipunagara terbagi atas lima kelas yaitu kategori datar dengan luas 52.67 km2, kategori landai seluas 823.98 km2, agak curam seluas 226.79 km2, curam seluas 126.02 km2, dan sangat curam seluas 74.96 km2. Perubahan spasial tataguna lahan tahun 1996 sampai dengan 2020 yaitu untuk lahan terbuka/pemukiman mengalami pengurangan sebesar -15% (-196.92 km2), vegetasi hutan mengalami penambahan sebesar +11% (+145.78 km2), perairan/air terjadi pengurangan sebesar -13% (-164.96 km2), dan lahan sawah/tambak terjadi penambahan sebesar +17% (+216.11 km2). Analisis potensi genangan rob (kejadian limpasan sungai) di hilir DAS Cipunagara berkorelasi dengan perubahan tataguna lahan terbuka, vegetasi hutan, dan sawah dengan luas 1,982 ha (47%). Sementara potensi genangan rob (kejadian pasang surut) berkorelasi dengan perubahan tataguna lahan sawah dan perairan/air dengan luas 2,213.93 ha (53%). Hasil riset dapat dimanfaatkan dalam manajemen risiko banjir rob pada area hilir daerah aliran sungai.