The flood disaster is a severe threat in Indonesia due to the enormous impacts on environmental degradation, social and economic sectors. One flood event due to the overflow is the Badeng River's flooding in 2018 at Singojuruh Subdistrict, Banyuwangi Regency. The flood had a detrimental impact on the local community, especially on agricultural land and residential. Anticipatory steps need to be taken to minimize losses due to flooding in the future. Inundation modelling in this research is purposed to predict flood hazards. Hence it can have appropriate anticipatory steps in the future. The software used to model the inundation in this study was the HEC-RAS Program. Data needed in this study are river geometry, manning coefficient, and maximum daily rainfall from the year 2010 until 2019. The research e stages in this study consist of (1) Calculation of watershed morphometry, (2) Calculation of average regional rainfall, (3) Calculation of rainfall plan, (4) Rain Data Suitability Test, (5) Calculation of Rain Intensity, (6) Calculation of Flood Discharge Plan, (7) Geometry Modelling, (8) Extraction of Manning Coefficient, and (9) Inundation Simulation. The results of the Gama 1 method's peak discharge plan showed an increase in each return period. The area with the highest level of susceptibility around the Badeng River occurs in Alasmalang Village, Singojuruh Subdistrict. This area has the smallest river storage capacity than other river crossings. Hence it has the most significant potential for flooding.Keywords: inundation modelling, flood, HEC-RAS, Badeng RiverBencana banjir menjadi ancaman serius bagi negara Indonesia karena memberikan dampak yang besar terhadap kerusakan lingkungan, sosial maupun ekonomi. Salah satu kejadiannya adalah banjir yang terjadi akibat luapan sungai Badeng pada tahun 2018 di Kecamatan Singojuruh, Kabupaten Banyuwangi. Kejadian Banjir tersebut memberikan dampak yang merugikan bagi masyarakat setempat, terutama pada lahan pertanian dan permukiman. Langkah antisipasi perlu dilakukan untuk meminimalisir kerugian akibat bencana banjir di masa mendatang. Pemodelan genangan dalam penelitian ini dibuat bertujuan untuk  memprediksi bahaya banjir, sehingga dapat dilakukan langkah antisipasi yang tepat. Software yang digunakan untuk memodelkan genangan dalam penelitian ini adalah Program HEC-RAS. Data yang dibutuhkan berupa data geometri sungai, koefisien manning dan curah hujan harian maksimum selama periode tahun 2010 sampai 2019. Beberapa tahapan dalam penelitian ini meliputi (1) Perhitungan morfometri DAS, (2) Perhitungan hujan rerata wilayah, (3) Perhitungan curah hujan rencana, (4) Uji Kesesuaian Data Hujan, (5) Perhitungan Intensitas Hujan, (6) Perhitungan Debit banjir rencana, (7) Pemodelan geometri, (8) Ekstraksi angka kekasaran manning, dan (9) Simulasi Genangan. Hasil perhitungan debit puncak rencana metode Gama 1 menunjukkan peningkatan pada setiap periode ulang. Daerah yang mempunyai tingkat kerawanan paling besar adalah areal sekitar Sungai Badeng yang berada di Desa Alasmalang Kecamatan Singojuruh. Daerah ini memiliki kapasitas tampung sungai yang paling kecil daripada penampang sungai yang lainnya, sehingga memiliki potensi terjadinya banjir paling besar. Kata kunci: pemodelan genangan, banjir, HEC-RAS, Sungai Badeng

The Singojuruh flash flood incident have diverse effects on residential and agriculture areas. As result of the 2018 flood, two houses collapsed and there were severe also effects on agriculture. This paper focuses on understanding the river capacity (Badeng River) as well as the modeling to the next flood. We used Hydrological Engineering Center-River Analysis System (HEC-RAS) version 5.0.7 to analyze the river storage capacity. The factor in this analysis i.e. river morphometry (river length, river width, river depth and river slope) and manning coefficient. The sampling conducted in three point along the Badeng River. The result showed that each of point location have different characteristic hence influence its capacity. The smallest capacity has the biggest potential of flooding.

The salt pond ecosystem has a very important ecological function, especially for the coastal region of Madura. One of the ecological functions of the salt pond is supporting the economy of the community. The purposes of this study are: (1) To determine changes in salt ponds in Madura Island in the last 10 years (2009-2019) based on remote sensing data and Geographic Information System; (2) To make a simulation of structuring the Salt Pond area on Madura Island in the management of a sustainable coastal environment. This type of research is a descriptive-analytic survey method using remote sensing data and Geographic Information System. The object of the study is the Tambak Garam (salt pond) area in Madura Island focusing on Sampang Regency, Pamekasan Regency, and Sumenep Regency. Data collection techniques carried out by observation, interviews, and documentation. Changes in Salt Ponds data analysis were carried out using remote sensing data extraction method with true-color image input and NDVI. The results show that the area of salt ponds decreased from year to year in the district of Sampang, Pamekasan, and Sumenep. Management intensification using more modern technology is done to increase production in the declining salt pond areas. Salt production runs optimally if it is carried out in coastal areas with sloping morphology and soil that is not porous in the form of clay soil, which does not absorb seawater. Sloping morphology was chosen to support the entry of seawater into salt pond plots that use tidal power.

Land degradation have caused decline in land productivity and triggering landslide incident in Bendo Watershed. This area has been selected as study area which represent characteristic upland area of the region. The research examines land capability analysis in order to reduce land degradation and disaster incidents and for sustainable use of land resources. The geomorphology approach was used along with sixteen of landform unit as unit sample. Further, artificial neural network models were used to classify land capabilities. Network architecture 10-8-1 was used on classification process due to the lowest error value factors. The findings of the study present that 20, 46% of Bendo watershed are prone to land degradation. Physical characteristic within area are contributing increasing land degradation. The capability classes of Bendo watershed ranges from class II to class VII. The upstream areas have erosion and intensive landslides as its limited factors, hence tend to have poor land capability classes. While the middle to downstream areas of Bendo watershed have better land capability classes with more diverse land use recommendations.

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