Estimation of Erosion Potentials through Utilization of Remote Sensing Data and The Universal Soil Loss Equation Model
DOI:
https://doi.org/10.23960/jtep-l.v12i1.223-235Abstract
Remote sensing data and USLE models have been used widely for erosion analysis. In Indonesia, the USLE model is a reference in erosion analysis to assess land suitability for agricultural crop development. Erosion analysis using remote sensing data provides various advantages, including good accuracy, lower costs, and can analyze erosion rates quickly compared to direct measurement methods. The aim of this study was to analyze the potential erosion in the Arui watershed - Manokwari Regency − West Papua Province using remote sensing data and USLE models. The research was conducted from April to July 2022, with three main stages i.e data inventory, data analysis, and erosion rate estimation. The research shows that the potential erosion rate in the Arui watershed is 15 tons/ha/year or 3.480 tons/year, thus exceeding the tolerable soil loss (TSL) erosion rate threshold of 9.6 tons/ha/year. Therefore, a conservation and restoration program is needed to control the erosion rate in the Arui watershed.
Keywords: Erosion rate, Remote sensing, Tolerable soil loss, USLE, Watershed
References
Agustina, H., & Dewi, V.A.K. (2020). Analisis erosi metode USLE pada lahan sawit Kabupaten Muara Enim, Jurnal Teknik Pertanian Lampung, 9(3), 157 - 162.
Arif, N., Danoedoro, P., & Hartono, H. (2017). Remote sensing and GIS approaches to a qualitative assessment of soil erosion risk in Serang watershed, Kulonprogo, Indonesia. Geoplanning: Journal of Geomatics and Planning, 4(2), 131–142. https://doi.org/10.14710/geoplanning.4.2.131-142
Arifin, H., Heatubun, C.H., & Wahyudi. (2019). Analisis kawasan hutan dan tutupan hutan pada tiga daerah aliran sungai di Kabupaten Manokwari. Cassowary, 2(1), 49-67. https://doi.org/10.30862/casssowary.cs.v2.i1.22
Arsyad, S. 1989. Konservasi Tanah dan Air. IPB Press. Bogor.
Arsyad, S. 2006. Konservasi Tanah dan Air. IPB Press. Bogor. 396 hal.
Avwunudiogba, A., & Hudson, P.F. (2014). A review of soil erosion models with special reference to the needs of humid tropical mountainous environments. European Journal of Sustainable Development, 3(4), 299–310. https://doi.org/10.14207/ejsd.2014.v3n4p299
Ransiki, R. (2017). Laporan Monitoring dan Evaluasi Pengelolaan DAS Wosi Tahun 2016. Kementerian Lingkungan Hidup dan Kehutanan. Jakarta
Bernoux, M., Arrouays, D., Cerri, C., Volkoff, B., & Jolivet, C. (1998). Bulk densities of Brazilian Amazon soils related to other soil properties. Soil Science Society of America Journal, 62(3), 743–749.
Djuwansah, M.R., & Mulyono, A. (2017). Assessment model for determining soil erodibility factor in Lombok Island. Riset Geologi dan Pertambangan, 27(2), 133–143. https://doi.org/10.14203/risetgeotam2017.v27.417
Durigon, V.L., Carvalho, D.F., Antunes, M.A.H., Oliveira, P.T.S., & Fernandes, M.M. (2014). NDVI time series for monitoring RUSLE cover management factor in a tropical watershed. International Journal of Remote Sensing, 35(2), 441–453. https://doi.org/10.1080/01431161.2013.871081
El Jazouli, A., Barakat, A., Ghafiri, A., El Moutaki, S., Ettaqy, A., & Khellouk, R. (2017). Soil erosion modeled with USLE, GIS, and remote sensing: A case study of Ikkour watershed in Middle Atlas (Morocco). Geoscience Letters, 4(1), 12p. https://doi.org/10.1186/s40562-017-0091-6
Gao, F., Wang, Y., & Yang, J. (2017). Assessing soil erosion using USLE model and MODIS data in the Guangdong, China. IOP Conference Series: Earth and Environmental Science, 74(1), 012007. https://doi.org/10.1088/1755-1315/74/1/012007
Kar, S.K., Kumar, S., Sankar, M., Patra, S., Singh, R.M., Shrimali, S.S., & Ojasvi, P.R. (2022). Process-based modelling of soil erosion : Scope and limitation in the Indian context. Current Science, 122(5), 533–541.
Karydas, C.G., Panagos, P., & Gitas, I.Z. (2014). A classification of water erosion models according to their geospatial characteristics. International Journal of Digital Earth, 7(3), 229–250. https://doi.org/10.1080/17538947.2012.671380
Kementerian Kehutanan. (2009). Keputusan Menteri Kehutanan Republik Indonesia Nomor: SK.328/Menhut-II/2009 Tentang Penetapan Daerah Aliran Sungai (DAS) Prioritas Dalam Rangka Rencana Pembangunan Jangka Menengah (RPJM) Tahun 2010 - 2014. Kementerian Kehutanan Republik Indonesia. Jakarta.
Kementerian Kehutanan. (2009). Peraturan Menteri Kehutanan Republik Indonesia Nomor: P.32/Menhut-II/2009 Tentang Tata Cara Penyusunan Rencana Teknik Rehabilitasi Hutan dan Lahan Daerah Aliran Sungai (RTkRHL-DAS). Kementerian Kehutanan Republik Indonesia. Jakarta.
Mofu, Y., Lindongi, LE., Tukayo, R.K., & Suparno, A. (2019). Analisis daya dukung lahan pertanian di Kampung Susweni Distrik Manokwari Timur. Agrotek, 7(2), 24 - 32.
Liu, J.G., & Mason, P.J. (2009). Essential Image Processing and GIS for Remote Sensing (1st ed.). Wiley & Sons, Ltd.
Márquez, A.M., & Guevara-Pérez, E. (2010). Comparative analysis of erosion modeling techniques in a basin of Venezuela. Journal of Urban and Environmental Engineering, 4(2), 81–104. https://doi.org/10.4090/juee.2010.v4n2.081104
Meinen, B.U., & Robinson, D.T. (2021). Agricultural erosion modelling: Evaluating USLE and WEPP field-scale erosion estimates using UAV time-series data. Environmental Modelling and Software, 137(January), 10 p. https://doi.org/10.1016/j.envsoft.2021.104962
Novitasari, Rohman, M.H., Ambarwati, A.A., & Indarto, I. (2019). Aplikasi USLE dan GIS untuk prediksi laju erosi di wilayah DAS Brantas. Jurnal Teknik Pertanian Lampung, 8(2), 76 - 84.
Panagos, P., Karydas, C., Borrelli, P., Ballabio, C., & Meusburger, K. (2014). Advances in soil erosion modelling through remote sensing data availability at European scale. Second International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2014), 9229(September), 10 p. https://doi.org/10.1117/12.2066383
Raza, A., Ahrends, H., Habib-Ur-rahman, M., & Gaiser, T. (2021). Modeling approaches to assess soil erosion by water at the field scale with special emphasis on heterogeneity of soils and crops. Land, 10(4), 35 p. https://doi.org/10.3390/land10040422
Ritung, S., Nugroho, K., Mulyani, A., & Suryani, E. (2011). Petunjuk Teknis Evaluasi Lahan untuk Komoditas Pertanian (2nd ed.). Balai Besar Penelitian dan Pengembangan Sumberdaya Lahan Pertanian.
Senanayake, S., Pradhan, B., Huete, A., & Brennan, J. (2020). A Review on assessing and mapping soil erosion hazard using geo-informatics technology for farming system management. Remote Sensing, 12(24), 1–25. https://doi.org/10.3390/rs12244063
Sepuru, T. K., & Dube, T. (2018). An appraisal on the progress of remote sensing applications in soil erosion mapping and monitoring. Remote Sensing Applications: Society and Environment, 9, 9 p. https://doi.org/https://doi.org/10.1016/j.rsase.2017.10.005
Sharpley, A.N., & Williams, J.R. (1990). EPIC: The erosion-productivity impact calculator. In U.S. Department of Agriculture Technical Bulletin (Issue 1768). http://agris.fao.org/agris-search/search.do?recordID=US9403696
Sotiropoulou, A.M., Alexandridis, T., Bilas, G., Karapetsas, N., Tzellou, A., Silleos, N., & Misopolinos, N. (2011). A user friendly GIS model for the estimation of erosion risk in agricultural land using USLE. Proceedings of The International Conference on Information and Communication Technologies, 795–801
Srinivasan, R., Singh, S.K., Nayak, D.C., Hegde, R., & Ramesh, M. (2019). Estimation of soil loss by USLE model using remote sensing and GIS Techniques - A case study of coastal Odisha, India. Eurasian Journal of Soil Science, 8(4), 321–328. https://doi.org/10.18393/ejss.598120
Suharyanto, A., Suhartanto, E., & Pudyono. (2013). The use of satellite remote sensing data and geographic information systems on critical land analysis. Agrivita, 35(2), 119–126. https://doi.org/10.17503/Agrivita-2013-35-2-p119-126
The European Space Agency. (2018). Level-2A Algorithm Overview. https://sentinels.copernicus.eu/web/sentinel/technical-guides/sentinel-2-msi/level-2a/algorithm
USDA (United States Department of Agriculture). (1978). Predicting rainfall erosion losses - A guide to conservation planing. In USDA Agricultural Handbook 537 (1st ed., Vol. 1, Issue 1). United States Department of Agriculture.
Wang, L., Huang, J., Du, Y., Hu, Y., & Han, P. (2013). Dynamic assessment of soil erosion risk using landsat TM and HJ satellite data in Danjiangkou Reservoir Area, China. Remote Sensing, 5(8), 3826–3848. https://doi.org/10.3390/rs5083826
Wischmeier, W.H., & Smith, D.D. (1978). Predicting Rainfall Erosion Losses. In USDA (Vol. 1, Issue 1).
Yanti, D.F., Mansur, I., Rusdiana, O., & Kirmi, H. (2020). Pendugaan laju erosi tanaman serai wangi (Cymbopogon nardus L.) pada lahan pasca tambang. Jurnal Teknik Pertanian Lampung, 9(1), 55 - 62.
Xu, H., Hu, X., Guan, H., Zhang, B., Wang, M., Chen, S., & Chen, M. (2019). A remote sensing based method to detect soil erosion in forests. Remote Sensing, 11(5), 19 p. https://doi.org/10.3390/rs11050513
Životić, L., Perović, V., Jaramaz, D., Dordević, A., Petrović, R., & Todorović, M. (2012). Application of USLE, GIS, and Remote sensing in the assessment of soil erosion rates in Southeastern Serbia. Polish Journal of Environmental Studies, 21(6), 405–4011.
Downloads
Published
Issue
Section
License
- Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International Lice that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Jurnal Teknik Pertanian Lampung
JTEPL is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.