Flood Management Based on The Potential Urban Catchments Case Study Padang City

  • Dwi Marsiska Driptufany Department of Geodetic Engineering, Institute of Padang Technology (ITP) – Indonesia
  • Quinoza Guvil Department of Geodetic Engineering, Institute of Padang Technology (ITP) – Indonesia
  • Desi Syafriani Department of Geodetic Engineering, Institute of Padang Technology (ITP) – Indonesia
  • Dwi Arini Department of Geodetic Engineering, Institute of Padang Technology (ITP) – Indonesia
Keywords: Water Catchment Area, Flood, Geographic Information System, Spatial

Abstract

The water catchment area also indirectly impacts on flood control for areas that are lower than it because rainwater does not fall to the lower areas but is absorbed as groundwater. Increased development of Padang City will be inversely proportional to the reduction in water catchment areas and become an area that is impermeable that makes rainwater stagnate on the surface and flood occurs. The development of remote sensing technology and geographic information systems has made it possible to study the spatial patterns of potential water catchment areas in a wide range, including mapping the potential of water catchment areas in Padang City. This study aims to analyze the condition of the availability of water catchment areas for controlling water management and flood disasters in Padang City based on data on spatial parameters such as rainfall data, slope, soil type maps, and land use obtained from Landsat 8 OLI imagery data. This study uses the scoring and overlay method with the Geographical Information System. The results show that the condition of the water catchment area in the western part of Padang City have been critical, reaching 18.29% of the total area of ​​Padang City, this is due to land use that has undergone a change of function. If the water infiltration condition worsens (critical), it gives more opportunities for flooding and inundation. Thus the areas with the potential for water absorption which are categorized as critical and very critical in the research location can be said to be areas that are potentially prone to flooding and inundation, because the ground surface is no longer able to absorb water. Monitoring the potential of water catchment areas is one form of flood mitigation efforts.

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References

[1] Putranto TT, Hadiyanto H, Hati AC. Study of Determination of Infiltration Wells as an Effort to Control Floods in Pekalongan City Based on Geographical Information Systems. Pekalongan City Research and Development Journal. 2021 Jan 8; 19
[2] Yulianto F, Suwarsono S, Maulana T, Khomarudin MR. Analysis of the dynamics of coastal landform change based on the integration of remote sensing and GIS techniques: Implications for tidal flooding impact in Pekalongan, Central Java, Indonesia. Quaestiones Geographicae. 2019 Sep 30;38(3):17-29.
[3] Zope PE, Eldho TI, Jothiprakash V. Impacts of urbanization on flooding of a coastal urban catchment: a case study of Mumbai City, India. Natural Hazards. 2015 Jan 1;75(1):887-908.
[4] Muliawati DN. Planning for the implementation of an environmentally sound drainage system (eco-drainage) using infiltration wells in the Rungkut area (Doctoral dissertation, Sepuluh Nopember Institute of Technology).
[5] Hermon, D. (2019). Mitigation and Adaptation:Disaster of Climate Change. Sara Book Publication. India.
[6] Hermon, D. (2019). Land Stability Model for Sustainable Spatial Planning in Padang City- Indonesia based on Landslide Disaster. Journal of Geography and Earth Sciences, 7(1), 19-26.
[7] Mitrović VL, O’Mathúna DP, Nola IA. Ethics and floods: a systematic review. Disaster medicine and public health preparedness. 2019 Aug;13(4):817-28.
[8] George P. Health impacts of floods. Prehospital and disaster medicine. 2011 Apr;26(2):137-.
[9] Parida Y. Economic impact of floods in the Indian states. Environment and Development Economics. 2020 Jun;25(3):267-90.
[10] Yoda T, Yokoyama K, Suzuki H, Hirao T. Relationship between long-term flooding and serious mental illness after the 2011 flood in Thailand. Disaster medicine and public health preparedness. 2017 Jun 1;11(3):300-4.
[11] Yang, G.; Bowling, L.C.; Cherkauer, K.A.; Pijanowski, B.C. The impact of urban development on hydrologic regime from catchment to basin scales. Landsc. Urban Plan. 2011, 103, 237–247.
[12] Dams, J.; Dujardin, J.; Reggers, R.; Bashir, I.; Canters, F.; Batelaan, O. Mapping impervious surface change from remote sensing for hydrological modeling. J. Hydrol. 2013, 485, 84–95.
[13] Faulkner, D.S.; Francis, O.; Lamb, R. Greenfield run off and flood estimation on small catchments. J. Flood Risk Manag. 2012, 5, 81–90.
[14] Grimaldi, S.; Petroselli, A.; Romano, N. Curve-Number/Green–Ampt mixed procedure for streamflow predictions in ungauged basins: Parameter sensitivity analysis. Hydrol. Processes 2013, 27, 1265–1275.
[15] Grimaldi, S.; Petroselli, A. Do we still need the Rational Formula? An alternative empirical procedure for peak discharge estimation in small and ungauged basins. Hydrol. Sci. J. 2014, 60, 67–77
[16] Zoppou, C. Review of urban storm water models. Environ. Model. Softw. 2001, 16, 195–231.
[17] Guvil Q, Driptufany DM, Ramadhan S. Analisis Potensi Daerah Resapan Air Kota Padang. InSeminar Nasional Geomatika 2019 Feb 15 (Vol. 3, pp. 671-680).
[18] Driptufany DM, Guvil Q, Ramadhan S. Aplikasi Sistem Informasi Geografis Untuk Estimasi Sebaran Daerah Potensi Resapan Air Kota Padang. Jurnal Momentum ISSN 1693-752X. 2019 Feb 1;21(1):8-14.
[19] Yao L, Chen L, Wei W. Exploring the linkage between urban flood risk and spatial patterns in small urbanized catchments of Beijing, China. International journal of environmental research and public health. 2017 Mar;14(3):239.
[20] Mather P, Tso B. Classification methods for remotely sensed data. CRC press; 2016 Apr 19.
[21] Sampurno RM, Thoriq A. Klasifikasi tutupan lahan menggunakan citra landsat 8 operational land imager (OLI) di Kabupaten Sumedang (land cover classification using landsat 8 operational land imager (OLI) data in Sumedang Regency). Jurnal Teknotan Vol. 2016 Nov;10(2).
[22] Matondang JP, Kahar S, Sasmito B. Analisis Zonasi Daerah Rentan Banjir Dengan Pemanfaatan Sistem Informasi Geografis (Studi Kasus: Kota Kendal dan Sekitarnya). Jurnal Geodesi Undip. 2013 Apr 15;2(2).
[23] Peraturan Menteri Kehutanan Republik Indonesia No: P.32/Menhut-II/2009 tentang Tata Cara Penyusunan Rencana Teknik Rehabilitasi Hutan dan Lahan Daerah Aliran Sungai (RTkRHL-DAS)
[24] Hendriana KI, Yasa IG, Kesiman MW, Sunarya IM. Sistem Informasi Geografis Penentuan Wilayah Rawan Banjir di Kabupaten Buleleng. KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika). 2013 Jul 31;2(5):608-16.
[25] Wahyuni W, Arsyad U, Bachtiar B, Irfan M. Identifikasi Daerah Resapan Air di Sub Daerah Aliran Sungai Malino Hulu Daerah Aliran Sungai Jeneberang Kabupaten Gowa. Jurnal Hutan dan Masyarakat. 2017 Dec 30;9(2):93-104.
[26] Wibowo M. Model Penetuan Kawasan Resapan Air untuk Perencanaan Tata Ruang Berwawasan Lingkungan. Jurnal Hidrosfir Indonesia. 2006;1(1).
[27] Hermon D. Climate Change Mitigation.Jakarta. 2017
Published
2021-06-24
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