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Rasionalisasi Kerapatan Stasiun Hujan di Sub DAS Ngasinan Hulu Menggunakan Data Hujan Pengukuran dan Satelit Yumna Atika; Sri Wahyuni; Lily Montarcih Limantara
Jurnal Teknik Pengairan: Journal of Water Resources Engineering Vol. 13 No. 2 (2022)
Publisher : Fakultas Teknik, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.pengairan.2022.013.02.09

Abstract

Kesalahan dalam pemantauan data hidrologi pada sebuah DAS dapat menyebabkan data yang dihasilkan tidak akurat serta dapat menyebabkan hasil perencanaan dan pengelolaan sumber daya air yang tidak efisien. Permasalahan lain pada Sub DAS Ngasinan Hulu adalah ketersediaan data curah hujan yang minim, time series data hujan pendek dan tidak lengkap, kurangnya petugas pengamat, kesalahan pembacaan data, dan kesulitan dalam mendapatkan data curah hujan dengan cepat. Penelitian ini bertujuan untuk mendapatkan rekomendasi jaringan serta jumlah stasiun hujan yang efektif dan efisien pada Sub DAS Ngasinan Hulu menggunakan data pengukuran dan satelit CHIRPS. Metode yang digunakan dalam penelitian ini, yang pertama adalah melakukan uji kesesuaian antara data hujan pengukuran dengan satelit CHIRPS. Lalu mengevaluasi jaringan stasiun hujan eksisting berdasarkan standar WMO. Selanjutnya, melakukan rasionalisasi stasiun hujan menggunakan metode Kagan-Rodda dengan data pengukuran dan satelit CHIRPS. Hasil dari penelitian ini menunjukkan bahwa data hujan satelit CHIRPS sudah sesuai dengan data hujan pengukuran. Lalu, menurut standar WMO Sub DAS Ngasinan Hulu cukup diwakilkan oleh 6 stasiun hujan. Selanjutnya setelah dilakukan rasionalisasi menggunakan metode Kagan-Rodda dengan kesalahan perataan < 10% didapatkan luas pengaruh dan sebaran stasiunhujan yang sudah cukup merata dengan menggunakan 6 stasiun hujan.
Analisa Analisis korelasi antara kualitas air dan identifikasi mikroplastik di wilayah pesisir utara Situbondo. Arisda Maryama Santikanuri; Riyanto Haribowo; Sri Wahyuni
Jurnal Penelitian Pendidikan IPA Vol 11 No 5 (2025): May
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i5.10989

Abstract

Water pollution occurs when unwanted substances contaminate a body of water, affecting its quality. Rivers, as the main source of water, are particularly vulnerable to pollution from human activities. This study was located in the Situbondo North Coast Area with a focus on 15 sampling points. Water quality was assessed through several parameters. The abundance and characteristics of microplastics were analyzed, revealing the highest abundance at one point, with small fiber-shaped black particles predominant. Canonical Correspondence Analysis (CCA) identified microplastic characteristics, such as color and size, showed strong correlations with water quality. Green and large-sized microplastics were associated with increased ammonia and turbidity, while transparent and fragmentary microplastics correlated with decreased DO and increased BOD. Black microplastics were associated with a decrease in pH. These findings confirm the role of microplastics in worsening the chemical and biological conditions of waters. The study also found that Dissolved Oxygen (DO) and BOD had the strongest influence on the relationship between water quality and microplastics, highlighting the ecological significance of these findings.  
Utilization of CORDEX-SEA Rainfall Data for Rainfall Projections Using the RCP 4.5 Secenario in the Beringin Sila Dam Catchment Area Sumbawa Regency Iwin Satria; Sumiadi; Sri Wahyuni
Jurnal Penelitian Pendidikan IPA Vol 11 No 9 (2025): September
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v11i9.12744

Abstract

Climate change poses significant challenges to water resource management, particularly in regions dependent on reservoirs. This study evaluates the performance of CORDEX-SEA rainfall data in the Beringin Sila watershed and applies a bias correction using the Linear Scaling (LS) method. Historical analysis for 2001–2022 revealed that the raw CORDEX-SEA output overestimated rainfall, with a mean of 147.88 mm/month compared to 93.10 mm/month observed (PBIAS = 35.5%, Willmott’s d = 0.03). After applying LS, model accuracy improved substantially, yielding an adjusted mean of 100.30 mm/month, PBIAS of 3.07%, Willmott’s d of 0.748, and correlation coefficient of 0.580. These results confirm that LS effectively reduces systematic bias. The corrected dataset was then used to project rainfall for 2023–2050 under the RCP 4.5 scenario. Projections indicate an average of 98.49 mm/month, or 5.8% higher than the historical baseline, with considerable interannual variability ranging from less than 50 mm in dry years to more than 300 mm in wet years. Such findings highlight both the potential for modestly increased water availability and the need for adaptive reservoir operation to manage variability across wet and dry seasons. The results provide a valuable reference for future water balance studies and operational strategies in newly constructed reservoirs such as Beringin Sila.