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Determining Water Quality Status and Assimilation Capacity of Pollutant Loads in West Lombok Regency M Said Ramdlan; Astrini Widiyanti; Hilman Rizkiadi; Muhamad Arif Sidiq; Khaerul Ihwan
Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Vol 21, No 2 (2024): July 2024
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/presipitasi.v21i2.419-432

Abstract

Babak watershed is one of the essential watersheds in Lombok Island providing water supply for irrigation, fish pool, drinking water supply, and micro-hydro power plant. Excessive human activities degrade the water quality of Babak watershed, and more pollutants are present in the water column. Thus, this study aims to determine Babak watershed's water quality status and assimilating capacity to plan effective and holistic mitigation measures properly. The study calculates the pollution index (PI) using a formula based on the Minister of Environment No.115/2003 Decree and assimilating capacity (AC) based on the Minister of Environment No.110/2003 Decree. The results found that Babak watershed is lightly polluted, defined by exceeding chemical parameters such as DO, total phosphate, nitrite, and dissolved iron (Fe). Similarly, these parameters (total phosphate, nitrite, and Dissolved iron (Fe) also reached the maximum assimilation capacity of Babak watershed to contain and self-purify these pollutants from the water column. Thus, planning mitigation and adaptation measures are required to prevent further contaminations in this watershed.
The Implementation of a spatial model for developing a flood early warning system in the Kelep River Basin, Lombok, Indonesia: Implementasi model spasial untuk pengembangan sistem peringatan dini banjir di Daerah Aliran Sungai Kelep, Lombok, Indonesia Lalu Ade Sugiarta; Arben Virgota; Baiq Farista; Astrini Widiyanti
Indonesian Journal of Tropical Biology Vol. 1 No. 2 (2025): August 2025
Publisher : Yayasan Siti Widhatul Faeha

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Abstract

Indonesia, including in the Kelep Watershed, Lombok Island, flood disasters frequently occur. Land use changes and climate variability make this area more vulnerable to floods. This study aims to analyze the distribution and level of flood vulnerability and the dominant factors causing flood vulnerability in the Kelep Watershed. The method used was the weighting of six parameters, namely slope, landform, soil type, rainfall, land use, and river buffer, which were then overlaid using ArcGIS 10.8 software. The results showed that the highly flood-prone areas were spread across all sub-districts in the Kelep watershed, with the highest concentration in Sekotong, Lembar and Southwest Praya sub-districts. The three villages with the highest flood-prone areas are Candi Manik, Sekotong Tengah and Taman Baru. These areas require special attention as they often experience serious impacts due to flooding. Based on the validation test, the RMSE value of 5.95% indicates acceptable accuracy. The resulting flood vulnerability classification map can be used as a flood early warning system or basis for flood risk mitigation and is proposed to be implemented through cross-sector collaboration to improve preparedness and reduce disaster impacts.
The Implementation of a spatial model for developing a flood early warning system in the Kelep River Basin, Lombok, Indonesia: Implementasi model spasial untuk pengembangan sistem peringatan dini banjir di Daerah Aliran Sungai Kelep, Lombok, Indonesia Lalu Ade Sugiarta; Arben Virgota; Baiq Farista; Astrini Widiyanti
Indonesian Journal of Tropical Biology Vol. 1 No. 2 (2025): August 2025
Publisher : Yayasan Siti Widhatul Faeha

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Indonesia, including in the Kelep Watershed, Lombok Island, flood disasters frequently occur. Land use changes and climate variability make this area more vulnerable to floods. This study aims to analyze the distribution and level of flood vulnerability and the dominant factors causing flood vulnerability in the Kelep Watershed. The method used was the weighting of six parameters, namely slope, landform, soil type, rainfall, land use, and river buffer, which were then overlaid using ArcGIS 10.8 software. The results showed that the highly flood-prone areas were spread across all sub-districts in the Kelep watershed, with the highest concentration in Sekotong, Lembar and Southwest Praya sub-districts. The three villages with the highest flood-prone areas are Candi Manik, Sekotong Tengah and Taman Baru. These areas require special attention as they often experience serious impacts due to flooding. Based on the validation test, the RMSE value of 5.95% indicates acceptable accuracy. The resulting flood vulnerability classification map can be used as a flood early warning system or basis for flood risk mitigation and is proposed to be implemented through cross-sector collaboration to improve preparedness and reduce disaster impacts.