Pemanfaatan Model WRF-ARW Untuk Analisis Fenomena Atmosfer Borneo Vortex (Studi Kasus Tanggal 28 Desember 2014)

Penelitian ini memanfaatkan model WRF-ARW (Weather Research and Forcasting – Advanced Research WRF) untuk memberikan gambaran mengenai kondisi atmosfer saat kejadian Borneo Vortex. Hasil visualisasi model WRF-ARW pada tanggal 28 Desember 2014 menunjukkan adanya vortex, dimana hal ini menimbulkan belokan angin dan arus konvergen di Laut Cina Selatan, Selat Karimata, dan Kalimantan bagian selatan. Selain itu kondisi atmosfer yang labil dan kelembaban udara yang tinggi saat itu, memicu terbentuknya awan-awan konvektif pada ketiga wilayah tersebut. Uji kehandalan sederhana pada model menunjukkan bahwa secara spasial model mampu memetakan wilayah-wilayah yang terdapat hujan dengan baik namun dari segi intensitas hujan, angka yang dihasilkan oleh model tergolong underestimate jika dibandingkan dengan data TRMM 3B42.

PROGRAM PENDAMPINGAN LITERASI DAN NUMERASI DI SD NEGERI 1 DOMPYONGAN

Program Kampus Mengajar merupakan program yang dirancang oleh Kemendikbud Ristek yang memberikan kesempatan bagi mahasiswa untuk mengembangkan diri, melatih kemampuan menyelesaikan masalah dan menjadi mitra guru di sekolah penugasan untuk terus berinovasi dalam seluruh rangkaian kegiatan pembelajaran. Sasaran program Kampus Mengajar, yaitu sekolah-sekolah yang nilai literasi dan numerasinya masih berada dibawah rata-rata minimum sehingga memerlukan bantuan untuk meningkatkan kemampuan literasi dan numerasi pada siswa-siswinya. Salah satu sasaran Kampus Mengajar Angkatan 7 tahun 2024 adalah SD Negeri 1 Dompyongan. Program Kampus Mengajar Angkatan 7 dilaksanakan pada tanggal 26 Februari 2024 s.d. 15 Juni 2024. Tujuan dari program ini, yaitu untuk membantu meningkatkan kemampuan literasi dan numerasi sekolah sasaran, memperkenalkan teknologi kepada siswa, dan membantu administrasi sekolah sasaran. Program kerja yang disusun disesuaikan dengan keadaan siswa dan lingkungan sekolah. Program kerja yang berhasil dilaksanakan, yaitu Les Calistung, Les Literasi Numerasi, English Club, Pohon Literasi, Jam Kedatangan, Math Market, Pengenalan Microsoft Word, Eco Stars, Eco Champions, One Day Fun Learning, Ular Tangga Sains, Sosialisasi 3 Dosa Besar Pendidikan, penanaman tanaman obat-obatan, Kunjungan Museum dan pendampingan kegiatan pembelajaran. Kata kunci: Kampus Mengajar, Literasi, Numerasi, Teknologi, SD Negeri 1 Dompyonga

Pemanfaatan Model WRF-ARW Untuk Analisis Fenomena Atmosfer Borneo Vortex (Studi Kasus Tanggal 28 Desember 2014)

Penelitian ini memanfaatkan model WRF-ARW (Weather Research and Forcasting – Advanced Research WRF) untuk memberikan gambaran mengenai kondisi atmosfer saat kejadian Borneo Vortex. Hasil visualisasi model WRF-ARW pada tanggal 28 Desember 2014 menunjukkan adanya vortex, dimana hal ini menimbulkan belokan angin dan arus konvergen di Laut Cina Selatan, Selat Karimata, dan Kalimantan bagian selatan. Selain itu kondisi atmosfer yang labil dan kelembaban udara yang tinggi saat itu, memicu terbentuknya awan-awan konvektif pada ketiga wilayah tersebut. Uji kehandalan sederhana pada model menunjukkan bahwa secara spasial model mampu memetakan wilayah-wilayah yang terdapat hujan dengan baik namun dari segi intensitas hujan, angka yang dihasilkan oleh model tergolong underestimate jika dibandingkan dengan data TRMM 3B42

Integrated machine learning and GIS-based bathtub models to assess the future flood risk in the Kapuas River Delta, Indonesia

As more and more people live near the sea, future flood risk must be properly assessed for sustainable urban planning and coastal protection. However, this is rarely the case in developing countries where there is a lack of both in-situ data collection and forecasting tools. Here, we consider the case of the Kapuas River Delta (KRD), a data-scarce delta on the west coast of Borneo Island, Indonesia. We assessed future flood risk under three climate change scenarios (RCP2.6, RCP4.5, and RCP8.5). We combined the multiple linear regression and the GIS-based bathtub inundation models to assess the future flood risk. The former model was implemented to model the river’s water-level dynamics in the KRD, particularly in Pontianak, under the influence of rainfall changes, surface wind changes, and sea-level rise. The later model created flood maps with inundated areas under a 100-year flood scenario, representing Pontianak’s current and future flood extent. We found that about 6.4%–11.9% more buildings and about 6.8%–12.7% more roads will be impacted by a 100-year flood in 2100. Our assessment guides the local water manager in preparing adequate flood mitigation strategies

Integrated hydrodynamic and machine learning models for compound flooding prediction in a data-scarce estuarine delta

Flood forecasting based on hydrodynamic modeling is an essential non-structural measure against compound flooding across the globe. With the risk increasing under climate change, all coastal areas are now in need of flood risk management strategies. Unfortunately, for local water management agencies in developing countries, building such a model is challenging due to the limited computational resources and the scarcity of observational data. We attempt to solve this issue by proposing an integrated hydrodynamic and machine learning (ML) approach to predict water level dynamics as a proxy for the risk of compound flooding in a data-scarce delta. As a case study, this integrated approach is implemented in Pontianak, the densest coastal urban area over the Kapuas River delta, Indonesia. Firstly, we build a hydrodynamic model to simulate several compound flooding scenarios. The outputs are then used to train the ML model. To obtain a robust ML model, we consider three ML algorithms, i.e., random forest (RF), multiple linear regression (MLR), and support vector machine (SVM). Our results show that the integrated scheme works well. The RF is the most accurate algorithm to model water level dynamics in the study area. Meanwhile, the ML model using the RF algorithm can predict 11 out of 17 compound flooding events during the implementation phase. It could be concluded that RF is the most appropriate algorithm to build a reliable ML model capable of estimating the river's water level dynamics within Pontianak, whose output can be used as a proxy for predicting compound flooding events in the city

Modeling interactions between tides, storm surges, and river discharges in the Kapuas River delta

The Kapuas River delta is a unique estuary system on the western coast of the island of Borneo, Indonesia. Its hydrodynamics are driven by an interplay between storm surges, tides, and river discharges. These interactions are likely to be exacerbated by global warming, leading to more frequent compound flooding in the area. The mechanisms driving compound flooding events in the Kapuas River delta remain, however, poorly known. Here we attempt to fill this gap by assessing the interactions between river discharges, tides, and storm surges and how they can drive a compound inundation over the riverbanks, particularly within Pontianak, the main city along the Kapuas River. We simulated these interactions using the multi-scale hydrodynamic model SLIM (Second-generation Louvain-la-Neuve Ice-ocean Model). Our model correctly reproduces the Kapuas River's hydrodynamics and its interactions with tides and storm surge from the Karimata Strait. We considered several extreme-scenario test cases to evaluate the impact of tide–storm–discharge interactions on the maximum water level profile from the river mouth to the upstream part of the river. Based on the maximum water level profiles, we divide the Kapuas River's stream into three zones, i.e., the tidally dominated region (from the river mouth to about 30 km upstream), the transition region (from about 30 km to about 150 km upstream), and the river-dominated region (beyond 150 km upstream). Thus, the local water management can define proper mitigation for handling compound flooding hazards along the riverbanks by using this zoning category. The model also successfully reproduced a compound flooding event in Pontianak, which occurred on 29 December 2018. For this event, the wind-generated surge appeared to be the dominant trigger