Dampak Perubahan Curah Hujan Terhadap Tingkat Kerentanan Erosi Tanah Di Sub DAS Merawu, Jawa Tengah

Authors

  • Donnie Koes Nugraha Gadjah Mada University
  • Bayu Dwi Apri Nugroho Gadjah Mada University
  • Chandra Setyawan Gadjah Mada University

DOI:

https://doi.org/10.23960/jtep-l.v10i3.356-366

Abstract

This research was held to estimate rainfall and change in soil erosion vulnerability from 2020 to 2050 in Merawu Sub-Watershed, Banjanegara District with RCP 2.6, 4.5 and 8.5. The RCP is an overview of the concentration trends for greenhouse gases, aerosols and land use change created by the climate modeling community. Rainfall prediction was generated from SDSM Software and combined with USLE to predict soil erosion in ArcGIS 10.4. Changes in rainfall intensity are an important factor in changes of soil erosion rates because the kinetic energy of falling rainwater can cause soil erosion.The results showed rainfall in Banjarnegara Station at 2020-2050 with RCP 2.6,4.5 and 8.5 were increasing by +0,26%; +0,60%; +0,52%, while in Kalisapi Station were decreasing by -1,54%; -1,65% dan -2,20%. The change of soil erosion vulnerability prediction showed that soil erosion in Sub-DAS Merawu at 2020-2050 with RCP 2.6,4.5 and 8.5 in very light category were -0,02%;-0,02%;-0,03%, light category were -0,17%;-0,17%;-0,17%, moderate category -0,05%;-0,05%;-0,04%, heavy category -0,26%;-0,35%;-0,37%, and very heavy category were +1,46%;+1,88%;+1,95%. While the average soil erosion prediction at RCP 2.6, 4.5 and 8.5 were +0,86, +1,19% and +1,03%, respectively.

 

Keywords: soil erosion prediction, rainfall prediction, SDSM Software, Sub-DAS Merawu

References

Aiqiu, Lavia F., Mahendera, I Gede A., Mulsandi, A. 2017. Analisis Kondisi Atmosfer pada Kejadian Hujan Lebat Daerah Poso dan Sekitarnya (Studi Kasus: Kabupaten Poso Tanggal 17 Juli 2017). Seminar Nasional Penginderaan Jauh ke-4 Tahun 2017.

Asuero, A.G., Sayago, A. dan Gonzalez, A.G. 2006. The Correlation Coefficient: An Overview. Critical Reviews in Analytical Chemistry, 36:41–59.

Bappenas. 2018. Kaji Ulang RAN API: Kajian Basis Ilmiah Proyeksi Iklim Atmosferik. Bappenas, Jakarta, 51 hal.

Chai, T dan Draxler, R.R. 2014. Root mean square error (RMSE) or mean absolute error (MAE)? Arguments against avoiding RMSE in the literature. Geosci. Model Dev., 7: 1247–1250.

Duhan, D. dan Pandey,A. 2015. Statistical downscaling of temperature using three Techniques in the Tons River basin in Central India. Theoretical and Applied Climatology, 121: 605–622.

Julismin. 2013. Dampak dan Perubahan Iklim di Indonesia. Jurnal Geografi 5 (1): 39-46

Marhendi, T., 2011. Pengaruh Anomali Karakteristika Hujan Terhadap Erosi Lahan (Studi Kasus Das Merawu, Jawa Tengah). Techno, 12: 45-52.

Marhendi, T. dan Ningsih, D.L.S. 2018. Prediksi Peningkatan Sedimentasi Dengan Metode Angkutan Sedimen (Studi Kasus Sedimentasi Di Waduk Mrica). Techno 19 (2): 87 – 94.

Mawardi, I., 2010. Kerusakan Daerah Aliran Sungai Dan Penurunan Daya Dukung Sumberdaya Air Di Pulau Jawa Serta Upaya Penanganannya. Hidrosfir Indonesia, 5: 1-11.

Mekarsari, R. dan Utomo, P. 2019. Analisis Tingkat Bahaya Erosi pada Waduk Wadaslintang dengan Aplikasi Arcgis. Jurnal Geografi Gea, 19(2): 93-104

Moriasi, D.N., Arnold, J.G., Van Liew, M.W., Binger, R.L., Harmel, R.D. dan Veith, T.L. 2007. Model Evaluation Guidelines For Systematic Quantification Of Accuracy In Watershed Simulations. American Society of Agricultural and Biological Engineers, 50(3): 885−900.

Nearing, M.A., 2001. Potential changes in rainfall erosivity in the U.S. with climatechange during the 21st century. J. Soil Water Conserv, 56: 229–232.

Nugroho, B.D.A.2020. Fenomena Iklim Global, Perubahan Iklim dan Dampaknya di Indonesia. Gadjah Mada University Press.Yogyakarta.

Polade, S.D., Gershunov, A., Cayan, D.R., Dettinger, M.D., Pierce, D.W., 2017. Precipitation in a warming world: assessing projected hydro-climate changes in California and other Mediterranean climate regions. Sci. Rep., 7: 10783.

Poli, A.A dan Cirillo, M.C. 1993. On The Use Of The Normalized Mean Square Error In Evaluating Dispersion Model Performance. Atmospheric Environment 27A (15) : 2427-2434.

Ruminta, Handoko dan Nurmala, T. 2018. Indikasi perubahan iklim dan dampaknya terhadap produksi padi di Indonesia (Studi kasus : Sumatera Selatan dan Malang Raya). Jurnal Agro, 5(1): 48-60.

Sulistyo, B. 2011. Pengaruh Erosivitas Hujan Yang Diperoleh Dari Rumu Yang Berbeda Terhadap Pemodelan Erosi Berbasis Raster (Studi Kasus di Das Merawu, Banjarnegara, Jawa Tengah). AGRITECH, 31 (3): 250-259

Wischmeier, W.H dan D. D. Smith. 1978. Predicting Rainfall Erosion Losses A Guide to Conservation Planning. Washington DC: Goovernment Printing Office.

World Meteorological Organization. 1981. Measurement Of River Sediments. Secretariat of the World Meteorological Organization, Switzerland : Operational Hydrology Report No. 16.

Yang, D., Kanae, S., Oki, T., Koike, T., Musiake, K. 2003. Global potential soil erosion with reference to land use and climate changes. Hydrol. Process, 17: 2913–2928.

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2021-09-29

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