Analisis Tingkat Bahaya Erosi di Sub DAS Manday
DOI:
https://doi.org/10.26418/jtllb.v14i1.95805Keywords:
Erosion, USLE, Manday Sub-watershed, ArcGIS, Erosion Hazard LevelAbstract
Erosion is the process by which soil particles are detached and transported from their original location to other areas, primarily driven by water and wind, through the breakdown of soil aggregates (dispersion) and surface runoff. Continuous erosion can lead to sedimentation in rivers, reducing their capacity to carry water and increasing the risk of flooding during periods of high rainfall. However, scientific studies on erosion in the Manday sub-watershed remain limited. This study aims to analyze the extent of erosion occurring in the Manday Sub-Watershed using the Universal Soil Loss Equation (USLE) method combined with Geographic Information Systems (GIS), classify the erosion hazard level (EHL) in the Manday Sub-Watershed, and produce a map of the distribution of erosion hazard levels (EHL) in the Manday Sub-Watershed. The parameters used include the erosivity factor (R), soil erodibility (K), slope length and gradient (LS), land cover (C), and land conservation measures (P). The results of the study show that erosion in the Manday Sub-Watershed amounts to 101,491.44 tons/ha/year, with five erosion hazard levels (EHL) classified: very low, low, moderate, high, and very high, with the very low category covering 176,966.41 ha (56.95%) and the low category covering 92. 773.49 ha (29.86%), while the moderate category accounted for 5.67% (17,618.21 ha), severe for 3.35% (10,397.92 ha), and very severe for 4.17% (12,971.30 ha). Mapping the distribution of erosion hazard levels (TBE) shows that areas with higher TBE are generally on steep slopes with minimal vegetation cover. This mapping underscores the need for targeted land management in high-risk areas to mitigate erosion impacts.References
Arega, E., & others. (2024). Assessment of soil erosion and prioritization of conservation and restoration measures using {RUSLE} and Geospatial techniques: the case of upper Bilate watershed. Geomatics, Natural Hazards and Risk, 15(1), 2336016. https://doi.org/10.1080/19475705.2024.2336016
Arsyad, S. (2010). Konservasi Tanah dan Air (2nd ed.). IPB Press.
Asdak, C. (2022). Hidrologi dan Pengelolaan Daerah Aliran Sungai (Cetakan Ke 8). Yogyakarta: Gadjah Mada Press.
Bezak, N., & others. (2022). Exploring the possible role of satellite-based rainfall data in estimating inter- and intra-annual global rainfall erosivity. Hydrology and Earth System Sciences, 26, 4935–4953. https://doi.org/10.5194/hess-26-4935-2022
Bols, P. (1978). The ISO--Erosion Model: Rainfall erosivity method for tropical regions.
BPBD Kapuas Hulu. (2022). 4 Kecamatan dan 19 Desa Terdampak Banjir di Kabupaten Kapuas Hulu. Info.Kapuashulukab.Go.Id.
Chen, C., & others. (2025). Applicability Evaluation and Correction of Cover and Management Factor Methods for Soil Erosion Models. Agriculture, 15(9), 941. https://doi.org/10.3390/agriculture15090941
Chen, H., & others. (2023). Soil Erosion in Taiwan. Agriculture, 13(10), 1945. https://doi.org/10.3390/agriculture13101945
Chidi, C. L., & others. (2021). Sensitivity Assessment and Uncertainty Evaluation of {RUSLE} for Soil Erosion Estimation Using {GIS} Techniques: A Case of Durame Watershed, Southern Ethiopia. ISPRS International Journal of Geo-Information, 10(1), 28. https://doi.org/10.3390/ijgi10010028
Emberson, R., & others. (2023). Dynamic rainfall erosivity estimates derived from {IMERG} data. Hydrology and Earth System Sciences, 27, 1565–1589. https://doi.org/10.5194/hess-27-1565-2023
Fadl, M. E., & others. (2025). Integrating {RUSLE}, {AHP}, {GIS}, and cloud-based geospatial analysis for soil erosion assessment under Mediterranean conditions. Scientific Reports, 15(1), 22503. https://doi.org/10.1038/s41598-025-22503-3
François, A. D., & others. (2024). Assessing the Global Sensitivity and Uncertainty of the {RUSLE} Model Using Sobol Indices. Soil Systems, 8(4), 125. https://doi.org/10.3390/soilsystems8040125
Guo, H., & others. (2024). Analysis of Spatial and Temporal Patterns of Soil Erosion in the {Yunnan--Guizhou} Plateau during 2000--2030. Sustainability, 16(17), 7769. https://doi.org/10.3390/su16177769
Hanggara, I., & Irvani, H. (2018). Analisa Erosi Embung Putukrejo Menggunakan Metode Usle. Prosiding Seminar Nasional Teknologi Industri, Lingkungan Dan Infrastruktur (SENTIKUIN), 1(September), 1–7.
Hemmler, S., & others. (2025). Social ecology of artisanal sand mining in the Niger River around Bamako, Mali. PLOS ONE, 20(1), e0318029. https://doi.org/10.1371/journal.pone.0318029
Kalbar.AntaraNews.com. (2024). BPBD: Banjir Melanda 11 Kecamatan di Kapuas Hulu Kalbar. Admin Antarakalbar.
Kementerian Kehutanan Republik Indonesia. (2009). Peraturan Menteri Kehutanan Nomor 32 Tahun 2009 tentang Tata Cara Penyusunan Rencana Teknik Rehabilitasi Hutan dan Lahan.
Kironoto, B. A., Yulistiyanto, B., & Olii, M. R. (2020). Erosi dan Konservasi Lahan (p. 278).
Kwon, H., & others. (2024). Applicability Comparison of {GIS}-Based {RUSLE} and {SEMMA} for Risk Assessment of Soil Erosion in Wildfire Watersheds. Remote Sensing, 16(5), 932. https://doi.org/10.3390/rs16050932
Michalopoulou, H., & others. (2022). Significance of Digital Elevation Model in the Calculation of {LS} Factor and Soil Erosion Estimation. Land, 11(9), 1592. https://doi.org/10.3390/land11091592
Mukharamova, S., & others. (2021). Estimating the Soil Erosion Cover-Management Factor at Multiple Spatial Scales. ISPRS International Journal of Geo-Information, 10(10), 645. https://doi.org/10.3390/ijgi10100645
Neolaka, E. Y., Tanesib, J. L., & Bernandus, B. (2022). Pemetaan Daerah Rawan Erosi Dengan Menngunakan Metode Universal Soil Loss Equation (Usle) Di Kota Kupang. Jurnal Fisika : Fisika Sains Dan Aplikasinya, 7(1), 29–36. https://doi.org/10.35508/fisa.v7i1.6081
Oleszczuk, R., & others. (2022). Measurements versus Estimates of Soil Subsidence and Mineralization Rates at Peatland over 50 Years (1966--2016). Sustainability, 14(24), 16459. https://doi.org/10.3390/su142416459
Oliveira, J. A. X. de, Almeida, F. T. de, Souza, A. P. de, Paulista, R. S. D., Zolin, C. A., & Hoshide, A. K. (2024). Determination of Soil Erodibility by Different Methodologies in the Renato and Caiabi River Sub-Basins in Brazil. Land, 13(9). https://doi.org/10.3390/land13091442
Portalanza, D., & others. (2025). Mapping Soil Erosion and Ecosystem Service Loss: Integrating {RUSLE} and {NDVI} Metrics to Support Conservation in El Cajas National Park, Ecuador. Hydrology, 12(11), 279. https://doi.org/10.3390/hydrology12110279
Putra, A. W., Nugroho, S., & Setiawan, B. (2021). Analisis bahaya erosi menggunakan {USLE} di {DAS} Mahakam. Jurnal Teknik Lingkungan, 27(2), 112–123.
Ridwan, M., & Sarjito, J. (2024). Studi Kajian Dampak Perubahan Tutupan Lahan terhadap Kejadian Banjir di Daerah Aliran Sungai. 26, 38–45.
Soefani, S. M. (2023). Analisis Tingkat Bahaya Erosi Di Desa Jeruju Besar Kecamatan Sungai Kakap Berbasis Sistem Informasi Geografis.
Soeryamassoeka, S. B., Gunarto, D., & Octaviana, Y. (2024a). Penentuan Indeks Bahaya Erosi di Bagian Hulu Wilayah Sungai (WS) Kapuas. Penelitian DIPA Fakultas Teknik Universitas Tanjungpura Pontianak Tahun 2024.
Soeryamassoeka, S. B., Gunarto, D., & Octaviana, Y. (2024b). Penentuan Indeks Bahaya Erosi di Bagian Hulu Wilayah Sungai (WS) Kapuas. Penelitian DIPA Fakultas Teknik Universitas Tanjungpura Pontianak Tahun 2024.
Sud, A., & others. (2024). Integrating {RUSLE} Model with Cloud-Based Geospatial Analysis: A Google Earth Engine Approach for Soil Erosion Assessment in the Satluj Watershed. Water, 16(8), 1073. https://doi.org/10.3390/w16081073
Susanto, R., Pranoto, T., & Nugraha, D. (2020). Pemetaan bahaya erosi menggunakan {USLE} dan {GIS} di {DAS} Brantas. Jurnal Tanah Dan Air Indonesia, 18(1), 45–56.
Tangkadas, C. G., Soeryamassoeka, S., & Nirmala, A. (2023). VALIDATION OF TROPICAL RAINFALL MEASURING MISSION (TRMM) RAINFALL DATA FOR THE KAPUAS HULU DISTRICT AREA. Jurnal Teknik Sipil, 23(3). https://doi.org/10.26418/jts.v23i3.66513
Taslim, & others. (2019). Artikel tentang pemodelan/pemetaan erosi berbasis USLE dengan dukungan GIS. Jurnal Ilmu Lingkungan, 17(2), 323–332.
Wang, H., & others. (2024). Evaluation of the {GPM IMERG-FR} Product for Computing Rainfall Erosivity for Mainland China. Remote Sensing, 16(7), 1186. https://doi.org/10.3390/rs16071186
Wijaya, A., Firmansyah, A., & Nurhadi, D. (2019). Analisis tingkat bahaya erosi menggunakan {USLE} di {DAS} Citarum. Jurnal Sumber Daya Alam Dan Lingkungan, 6(2), 77–88.
Wischmeier, W. H., & Smith, D. D. (1978). Predicting rainfall erosion losses: A guide to conservation planning (Number 537). U.S. Department of Agriculture.
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