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All issues Volume 483 (2024) E3S Web Conf., 483 (2024) 01014 References
Open Access
Issue
E3S Web Conf.
Volume 483, 2024
The 3rd International Seminar of Science and Technology (ISST 2023)
Article Number 01014
Number of page(s) 17
Section Collaborative Contribution to Sustainable Environment
DOI https://doi.org/10.1051/e3sconf/202448301014
Published online 31 January 2024
  1. WMO, Integrated flood management concept paper associated programme on flood management, World Meteorological Organization, (2009) [Google Scholar]
  2. E. Aldrian, D. Sein, D. Jacob, L. D. Gates, and R. Podzun, Modelling Indonesian rainfall with a coupled regional model, Clim Dyn, 25, 1, 1–17, (2005), doi: 10.1007/s00382-004-0483-0. [CrossRef] [Google Scholar]
  3. National Agency for Disaster Countermeasure, Disaster statisctic by time. Accessed: Aug. 19, 2023. [Online]. Available: https://dibi.bnpb.go.id/kwaktu2 [Google Scholar]
  4. D. R. Maidment, Handbook of hidrology, 1st ed. (McGRAW-Hill. Inc, New York 1992) [Google Scholar]
  5. R. Sørensen, U. Zinko, and J. Seibert, On the calculation of the topographic wetness index: Evaluation of different methods based on field observations, (2006). [Online]. Available: www.copernicus.org/EGU/hess/hess/10/101/ [Google Scholar]
  6. M. Diakakis, A method for flood hazard mapping based on basin morphometry: application in two catchments in Greece, Natural Hazards, 56, 3, 803–814, (2011). doi: 10.1007/s11069-010-9592-8. [CrossRef] [Google Scholar]
  7. S. H. Pourali, C. Arrowsmith, N. Chrisman, A. A. Matkan, and D. Mitchell, “Topography wetness index application in flood-risk-based land use planning, Appl Spat Anal Policy, 9, 1, 39–54, (2016). doi: 10.1007/s12061-014-9130-2. [CrossRef] [Google Scholar]
  8. C-Z. Qin, A-X Zhu, T. Pei, B-L. Lin, T. Scholten, T. Behrens and C-H Zhou, An approach to computing topographic wetness index based on maximum downslope gradient, Precis Agric, 12, 1, 32–43, (2011). doi: 10.1007/s11119-009-9152-y. [CrossRef] [Google Scholar]
  9. H. Aksoy, V. S. Ozgur Kirca, H. I. Burgan, and D. Kellecioglu, Hydrological and hydraulic models for determination of flood-prone and flood inundation areas, in IAHS-AISH Proceedings and Reports, Copernicus GmbH, May (2016), 137–141. doi: 10.5194/piahs-373-137-2016. [Google Scholar]
  10. I. W. Suarna, Aplikasi geografi dalam penanganan kebencanaan lingkungan di Indonesia [Application of geography in handling environmental disasters in Indonesia], Media Komunikasi Geografi, 14, 1, (2013). doi: https://doi.org/10.23887/mkg.v14i1.1748 [Google Scholar]
  11. S. A. Koriche and T. H. M. Rientjes, Application of satellite products and hydrological modelling for flood early warning, Physics and Chemistry of the Earth, Parts A/B/C, 93, 12–23, (Jun. 2016). doi: 10.1016/J.PCE.2016.03.007. [CrossRef] [Google Scholar]
  12. J. Haas, Soil moisture modelling using TWI and satellite imagery in the Stockholm region, Royal Institute of Technology (KTH), Stockholm, (2010). [Google Scholar]
  13. K. J. Beven and M. J. Kirkby, A physically based, variable contributing area model of basin hydrology, Hydrological Sciences Bulletin, 24, 1, 43–69, (1979). doi: 10.1080/02626667909491834. [CrossRef] [Google Scholar]
  14. P. Quinn, K. Beven, P. Chevallier, and O. Planchon, The prediction of hillslope flow paths for distributed hydrological modelling using digital terrain models, Hydrol Process, 5, 1, 59–79, (Jan. 1991). doi: https://doi.org/10.1002/hyp.3360050106. [CrossRef] [Google Scholar]
  15. J. Fitra, W. C. Huang, and Y. M. Purwana, Landslide analysis subject to geological uncertainty using Monte Carlo simulation (A study case in Taiwan), in Lecture Notes in Civil Engineering, Springer Science and Business Media Deutschland GmbH, 437–447, (2023). doi: 10.1007/978-981-16-9348-9_38. [CrossRef] [Google Scholar]
  16. B. Yong, L-L. Ren, Y. Hong, J. Gourley, X. Chen, Y-J. Zhang, X. Yang, Z-X Zhang and W. Wang, A novel multiple flow direction algorithm for computing the topographic wetness index, Hydrology Research, 43, 1–2, 135–145, (Feb. 2012). doi: 10.2166/nh.2011.115. [CrossRef] [Google Scholar]
  17. M. Kopecký and Š. Čížková, Using topographic wetness index in vegetation ecology: Does the algorithm matter?, Appl Veg Sci, 13, 4, 450–459, (Oct. 2010). doi: https://doi.org/10.1111/j.1654-109X.2010.01083.x [CrossRef] [Google Scholar]
  18. K. N. Hjerdt, J. J. McDonnell, J. Seibert, and A. Rodhe, A new topographic index to quantify downslope controls on local drainage, Water Resour Res, 40, 5, (2004), doi: 10.1029/2004WR003130. [CrossRef] [Google Scholar]
  19. A. L. Ruhoff, N. M. R. Castro, and A. Risso, Numerical modelling of the topographic wetness index: An analysis at different scales, International Journal of Geosciences, 2, 4, 476–483, ( Jan. 2011). doi: 10.4236/ijg.2011.24050 [CrossRef] [Google Scholar]
  20. T. Pei, C-Z Qin, A-X Zhu, L. Yang, M. Luo, B. Li and C. Zhou, Mapping soil organic matter using the topographic wetness index: A comparative study based on different flow-direction algorithms and kriging methods, Ecol Indic, 10, 3, 610–619, (May 2010). doi: 10.1016/j.ecolind.2009.10.005. [CrossRef] [Google Scholar]
  21. J. P. Wilson, Sensitivity of quasi-dynamic topographic wetness index to choice of DEM resolution, flow routing algorithm, and soil variability, (2010). [Online]. Available: https://www.researchgate.net/publication/307887571 [Google Scholar]
  22. T. Grabs, J. Seibert, K. Bishop, and H. Laudon, Modeling spatial patterns of saturated areas: A comparison of the topographic wetness index and a dynamic distributed model, J Hydrol (Amst), 373, 1–2, 15–23, (Jun. 2009). doi: 10.1016/j.jhydrol.2009.03.031 [CrossRef] [Google Scholar]
  23. S. K. Jenson, Applications of hydrologic information automatically extracted from digital elevation models, Hydrol Process, 5, 1, 31–44, (Jan. 1991). doi: https://doi.org/10.1002/hyp.3360050104 [CrossRef] [Google Scholar]
  24. J. Seibert, J. Stendahl, and R. Sørensen, Topographical influences on soil properties in boreal forests, Geoderma, 141, 1, 139–148, (2007). doi: https://doi.org/10.1016/j.geoderma.2007.05.013 [CrossRef] [Google Scholar]
  25. Geospatial Information Agency, DEMNAS. Accessed: Sep. 16, 2023. [Online]. Available: https://tanahair.indonesia.go.id/demnas/#/ [Google Scholar]
  26. Ministry of Energy and Mineral Resources, Geological map of Medan sheet. Accessed: Aug. 20, 2023. [Online]. Available: https://geologi.esdm.go.id/geomap/pages/preview/peta-geologi-lembar-medan-sumatera [Google Scholar]

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