Muhammad Amar Sajali

This study evaluates the performance of Global Precipitation Measurement (GPM) satellite-based rainfall data in comparison to Automatic Rainfall Recorder (ARR) data in forming rainfall distribution patterns and assessing its impact on flood discharge simulation using the HEC-HMS model. Statistical validation was conducted using the Pearson Correlation Coefficient, the ratio of standard deviation of observations to RMSE (RSR), Percent Bias (PBIAS), and Mean Absolute Percentage Error (MAPE). The results show that GPM has a strong correlation with ARR (r = 0.875) and a low RSR value (RSR= 0.256), yet it exhibits a notable negative bias (PBIAS = –24.41%), indicating an underestimation of rainfall values. In contrast, simulations using ARR rainfall patterns produce peak discharges that closely match actual discharge records at the Jatigede Dam outlet, with an average deviation of less than 3% and a MAPE of 1.17%, categorized as very good. The GPM simulation produces peak discharges 13–16% higher than actual observations, with a MAPE of 14.53%, which still falls into the good category. These results suggest that while ARR provides higher accuracy, GPM remains a viable alternative source, especially in data-scarce areas, provided that appropriate calibration methods such as bias correction are applied. This study supports future research in satellite data calibration using machine learning and multivariate statistical approaches.

Accurate precipitation data is critical for hydrological modeling, flood forecasting, and water resources planning. This study evaluates the performance of satellite-based rainfall estimates from the Integrated Multi-satellite Retrievals for GPM (IMERG) Final Run Version 06 by comparing them with ground-based observations from six stations in the Jatigede Reservoir catchment, West Java, Indonesia. The analysis covers the 2014–2023 period, aligning with the reliable availability of IMERG Final Run products, and examines three temporal resolutions: monthly, daily, and hourly. Statistical evaluation employed Pearson correlation coefficient (r), the ratio of RMSE to observed standard deviation (RSR), and Percent Bias (PBIAS). Results show strong agreement at the monthly scale (r = 0.84, RSR = 0.34, PBIAS ≈ +24%), suggesting suitability for long-term water resource assessments. However, performance declines at shorter timescales. At the daily scale, IMERG underestimates rainfall (PBIAS ≈ -27%) with moderate correlation (r = 0.24). The hourly scale shows the poorest performance (r = 0.10, RSR > 3.0, PBIAS < -50%), indicating limitations in capturing short-duration, high-intensity rainfall typical in tropical regions. These findings underscore the importance of temporal aggregation and bias correction when applying IMERG data for operational hydrology and flood modeling

Bencana kekeringan menjadi perhatian bagi Badan Penanggulangan Bencana Daerah (BPBD) Kabupaten Bangkalan beberapa tahun terakhir. Studi ini bertujuan untuk menganalisis indeks kekeringan dan mengembangkan peta spasial kekeringan di Kabupaten Bangkalan khususnya di DAS Blega. Penelitian ini menggunakan konsep kekeringan meteorologis untuk menganalisa karakteristik kekeringan di lokasi penelitian. Data yang digunakan adalah data curah hujan bulanan, data curah hujan satelit, dan peta DAS Blega. Indeks kekeringan dianalisis menggunakan metode Standardised Precipitation Index (SPI). Peta spasial kekeringan diperoleh menggunakan metode Inverse Distance Weight (IDW) pada aplikasi ArcGIS 10.8. Hasil studi menunjukkan intensitas kekeringan terparah terjadi selama tujuh bulan (bulan Mei hingga November). Pola hubungan antara indeks kekeringan bulanan dengan tingkat kekeringan rentang 1992 - 2021 menunjukkan tingkat kekeringan "Amat Sangat Kering" terjadi secara berkala setiap empat tahun. Hasil perbandingan antara kejadian tahun kering dari hasil analisis metode SPI dan kejadian tahun EL Nino yang dikeluarkan BMKG menunjukkan terdapat kesesuaian antara kejadian tahun kering yang terjadi. Analisis kesesuaian menunjukkan persentase sebesar 75,97%, menunjukkan adanya kesamaan yang relatif baik antara kejadian kekeringan historis di daerah penelitian dengan kekeringan yang berasal dari metode SPI. Hasil studi memverifikasi bahwa metode SPI layak digunakan untuk menggambarkan karakteristik kekeringan di lokasi studi.

Banjir pada Sungai Kali Surabaya terjadi akibat kondisi cuaca ekstrem berupa hujan dan arus sungai yang deras dan menyebabkan sungai meluap. Fenomena meluapnya Sungai Kali Surabaya terjadi karena luapan air Sungai Brantas yang mengalir melalui Kali Surabaya. Tujuan dari penelitian ini adalah membuat model banjir di Sungai Kali Surabaya dan merancang jalur evakuasi di Sungai Kali Surabaya. Analisis hidrologi dilakukan untuk memperkirakan debit rencana dengan kala ulang 2 tahun sebesar 164.453 m3/detik, kala ulang 5 tahun sebesar 341.107 m3/detik, kala ulang 10 tahun sebesar 458.068 m3/detik, kala ulang 25 tahun sebesar 605.848 m3/s, dan kala ulang 50 tahun adalah 715,479 m3/detik. Pemodelan hidrolika dilakukan menggunakan 2D HEC-RAS. Luasan genangan banjir yang diperoleh dari rancangan debit kala ulang 2 tahun seluas 79 ha, debit kala ulang 5 tahun seluas 199 ha, debit kala ulang 10 tahun seluas 311 ha, debit kala ulang 25 tahun seluas 403 ha dan debit kala ulang 50 tahun adalah 478 hektar. Kajian mitigasi bencana berupa peta jalur evakuasi berdasarkan analisis sebaran banjir Sungai Surabaya di Kota Surabaya mengidentifikasi 8 titik kumpul dan 3 titik evakuasi akhir yang tersebar di tujuh wilayah kecamatan sepanjang Sungai Kali Surabaya.

In the past decade, the development of land retaining construction is growing rapidly as optimization of available land use. The purpose of this study is to hold the soil in order to avoid landslide due to the structural load other than the use of available space. The results of the sheet pile analysis at Pontianak Peaker PLTMG found that the SF number in the condition without earthquake (safe condition) is 2.00 and the number of SF in earthquake conditions is 1.40. Based on the results of sheet pile analysis at S-02 and S-03 points in conditions without earthquakes, low tide-without earthquakes, floods-without earthquakes, normal-earthquakes, receding earthquakes, and earthquake floods with earthquakes returning 500 years in analysis the structure and analysis of slope stability are said to be "safe" because the conditions without earthquakes SF values greater than 2.00 and earthquake conditions SF values greater than 1.40.