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Impact-Based Forecasting (IBF) untuk Mendukung Manajemen Risiko Banjir di Kawasan Jabodetabek

Program Studi Meteorologi, Sekolah Tinggi Meteorologi Klimatologi dan Geofisika, Indonesia

Received: 20 Nov 2023; Revised: 22 Feb 2024; Accepted: 13 Mar 2024; Available online: 7 Aug 2024; Published: 12 Aug 2024.
Editor(s): Budi Warsito

Citation Format:
Abstract

Bencana Banjir menimbulkan dampak dan kerugian yang cukup besar pada berbagai sektor di Jabodetabek. Pengembangan informasi cuaca diperlukan untuk mengurangi dampak dan kerugian tersebut. Impact-based Forecasting (IBF) menjadi salah satu sistem yang bertujuan untuk meningkatkan informasi cuaca yang terintegrasi dengan prakiraan potensi dampak yang dapat terjadi. Penelitian ini menerapkan teknik Analytical Hierarchy Process (AHP) untuk memetakan tingkat risiko banjir di Jabodetabek dengan mempertimbangkan parameter curah hujan, kepadatan penduduk, jarak kerapatan jalan, jarak ke sungai, tata guna lahan, geologi, janis tanah, rata-rata banjir tahunan, kemiringan, dan drainage density. Hasil penelitian menunjukkan bahwa seluruh parameer mempunyai pengaruh terhadap bencana banjir, dimana curah hujan menjadi parameter yang paling berpengaruh sebesar 25%. Jarak kerapatan jalan menjadi parameter dengan pengaruh paling kecil, yakni hanya sebesar 2%. Nilai Consistency Ratio (CR) yang dihasilkan sebesar 0,04 sehingga menunjukkan hasil pemetaan risiko banjir yang relevan. Data model curah hujan Global Ensemble Forecast System (GEFS) diimplementasikan ke dalam pemetaan risiko banjir untuk menghasilkan sistem Impact-based Forecasting (IBF), yang memberikan kemungkinan terjadinya curah hujan. Berdasarkan verifikasi yang dilakukan, prakiraan dampak yang diberikan memberikan hasil yang selaras dengan kejadian sebenarnya. Hasil ini menunjukkan bahwa informasi prakiraan potensi dan dampak banjir yang diberikan memberikan hasil yang baik dan representatif.

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Keywords: Dampak; Banjir; Impact-based Foecasting (IBF); Analytical Hierarchy Process (AHP); Sistem Informasi Geografis (SIG)
Funding: Sekolah Tinggi Meteorologi Klimatologi dan Geofisika

Article Metrics:

  1. Aldimasqie, A. M., Hari Saputra, A., & Oktarina, S. (2022). Pemetaan Zona Rawan Banjir Di Jakarta Menggunakan Analytic Hierarchy Process (AHP). Jurnal Environmental Science, 5(1), 1–14. https://www.fao.org/soils-portal/data-hub/
  2. Ali, A., Deranadyan, G., & Sa’adah, U. (2021). Kajian awal pemanfaatan data pengindraan jauh dalam implementasi peringatan dini cuaca esktrem berbasis dampak. Prosiding WIN-ID, 27–36. https://www.researchgate.net/publication/357506257
  3. Ariyora, S., Budisusanto, Y., & Prasasti, I. (2015). Pemanfaatan data Penginderaan Jauh dan SIG untuk Analisa Banjir (Studi Kasus : Banjir Provinsi DKI Jakarta). GEOID, 10(2), 137–146
  4. Aziza, S. N., Somantri, L., & Setiawan, I. (2021). Analisis pemetaan tingkat rawan banjir dikecamatan bontang barat kota bontang berbasis SIG. Jurnal Pendidikan Geografi Undiksha, 9(2), 109–120
  5. Boult, V. L., Black, E., Saado Abdillahi, H., Bailey, M., Harris, C., Kilavi, M., Kniveton, D., MacLeod, D., Mwangi, E., Otieno, G., Rees, E., Rowhani, P., Taylor, O., & Todd, M. C. (2022). Towards drought impact-based forecasting in a multi-hazard context. Climate Risk Management, 35, 1–7. https://doi.org/10.1016/j.crm.2022.100402
  6. Budi Harsoyo. (2013). Mengulas penyebab banjir di wilayah dki jakarta dari sudut pandang geologi, geomorfologi dan morfometri sungai. Jurnal Sains & Teknologi Modifikasi Cuaca, 14(1), 37–43
  7. Chowdhuri, I., Pal, S. C., & Chakrabortty, R. (2020). Flood susceptibility mapping by ensemble evidential belief function and binomial logistic regression model on river basin of eastern India. Advances in Space Research, 65(5), 1466–1489
  8. Darmawan, K., Hani’ah, & Suprayogi, A. (2017). Analisis tingkat kerawanan banjir di kabupaten sampang menggunakan metode overlay dengan scoring berbasis sistem informasi geografis. Jurnal Geodesi Undip Januari, 6(1), 31–40
  9. Das, S. (2018). Geographic information system and AHP-based flood hazard zonation of Vaitarna basin, Maharashtra, India. Arabian Journal of Geosciences, 11(19), 1–13. https://doi.org/10.1007/s12517-018-3933-4
  10. Desalegn, H., & Mulu, A. (2021). Flood vulnerability assessment using GIS at Fetam watershed, upper Abbay basin, Ethiopia. Heliyon, 7(1). https://doi.org/10.1016/j.heliyon.2020.e05865
  11. ESCAP. (2021). Manual for Operationalizing Impact-based Forecasting and Warning Services (IBFWS)
  12. Ginting, A. M. (2020). Dampak ekonomi dan kebijakan mitigasi risiko banjir di dki jakarta dan sekitarnya tahun 2020. Info Singkat, XII(1), 19–24
  13. Hamdani, H., Permana, S., & Susetyaningsih, A. (2014). Analisa daerah rawan banjir menggunakan aplikasi sistem informasi geografis (studi kasus pulau bangka). Jurnalsttgarut, 12(1), 1–13. http://jurnal.sttgarut.ac.id
  14. Hammami, S., Zouhri, L., Souissi, D., Souei, A., Zghibi, A., Marzougui, A., & Dlala, M. (2019). Application of the GIS based multi-criteria decision analysis and analytical hierarchy process (AHP) in the flood susceptibility mapping (Tunisia). Dalam Arabian Journal of Geosciences (Vol. 12, Nomor 21). Springer Verlag. https://doi.org/10.1007/s12517-019-4754-9
  15. Hasanuzzaman, Md., Adhikary, P. P., Bera, B., & Shit, P. K. (2022). Flood Vulnerability Assessment Using AHP and Frequency Ratio Techniques. GIScience and Geo-environmental Modelling, 91–104. https://doi.org/10.1007/978-3-030-94544-2_6
  16. Hassan, Z., & Kamarudzaman, A. N. (2023). Development of Flood Hazard Index (FHI) of the Kelantan River Catchment Using Geographic Information System (GIS) Based Analytical Hierarchy Process (AHP). Pertanika Journal of Science and Technology, 31(1), 203–215. https://doi.org/10.47836/pjst.31.1.13
  17. Hutabarat, Y. M. (2020). Pengembangan sistem informasi prakiraan cuaca berbasis dampak menggunakan model prakiraan cuaca numerik untuk wilayah jakarta. Jurnal WIdya Climago, 2(2), 56–68
  18. Kourgialas, N. N., & Karatzas, G. P. (2013). A hydro-economic modelling framework for flood damage estimation and the role of riparian vegetation. Hydrological Processes, 27(4), 515–531. https://doi.org/10.1002/hyp.9256
  19. Kox, T., Lüder, C., & Gerhold, L. (2018). Anticipation and Response: Emergency Services in Severe Weather Situations in Germany. International Journal of Disaster Risk Science, 9(1), 116–128. https://doi.org/10.1007/s13753-018-0163-z
  20. Langkoke, R., & Nur, Z. A. (2022). Analisis Bahaya Banjir Sungai Bone-Bone dengan Metode Geographical Information System (GIS) pada daerah Bantimurung Kecamatan Bone-Bone Kabupaten Luwu Utara Provinsi Sulawesi Selatan. Jurnal Ecosolum, 11(2), 110–125. https://doi.org/10.20956/ecosolum.v11i2.23971
  21. Merz, B., Kuhlicke, C., Kunz, M., Pittore, M., Babeyko, A., Bresch, D. N., Domeisen, D. I. V., Feser, F., Koszalka, I., Kreibich, H., Pantillon, F., Parolai, S., Pinto, J. G., Punge, H. J., Rivalta, E., Schröter, K., Strehlow, K., Weisse, R., & Wurpts, A. (2020). Impact Forecasting to Support Emergency Management of Natural Hazards. Reviews of Geophysics, 58(4), 1–52. https://doi.org/10.1029/2020RG000704
  22. Mukherjee, F., & Singh, D. (2020). Detecting flood prone areas in Harris County: a GIS based analysis. GeoJournal, 85, 647–663
  23. Oikonomidis, D., Dimogianni, S., Kazakis, N., & Voudouris, K. (2015). A GIS/ remote sensing based methodology for groundwater potentiality assessment in Tirnavos area, Greece. Journal of Hydrology, 525, 197–208
  24. Pandega, A. K., & Hastuti, E. W. D. (2019). Analisis potensi banjir berdasarkan metode AHP daerah sumber jaya dan sekitarnya, kabupaten oku selatan, provinsi sumatera SELATAN. Seminar Nasional AVoER XI
  25. PP No. 60 Tahun 2020, (2020)
  26. Putra, H. M. M., & Karomah, A. (2022). Implementasi Sistem Informasi Geografis (SIG) Untuk Pemetaan Lokasi Rawan Banjir Di Kabupaten Kebumen. Prosiding SAINTEK: Sains dan Teknologi, 1(1), 437–444
  27. Rahman, M., Ningsheng, C., Mahmud, G. I., Islam, M. M., Pourghasemi, H. R., Ahmad, H., Habumugisha, J. M., Washakh, R. M. A., Alam, M., Liu, E., Han, Z., Ni, H., Shufeng, T., & Dewan, A. (2021). Flooding and its relationship with land cover change, population growth, and road density. Geoscience Frontiers, 12(6), 1–20. https://doi.org/10.1016/j.gsf.2021.101224
  28. Ramadhani, D., Hariyanto, T., & Nurwatik. (2021). Penerapan Metode Analytical Hierarchy Process (AHP) dalam Pemetaan Potensi Banjir Berbasis Sistem Informasi Geografis (Studi Kasus: Kota Malang, Jawa Timur) Application of the Analytical Hierarchy Process (AHP) Method in Mapping Flood Potentials Based on Geographic Information Systems (Study Case: Malang City, East Java). GEOID, 17(1), 72–80
  29. Rincón, D., Khan, U. T., & Armenakis, C. (2018). Flood risk mapping using GIS and multi-criteria analysis: A greater toronto area case study. Geosciences (Switzerland), 8(8), 1–27
  30. https://doi.org/10.3390/geosciences8080275
  31. Rözer, V., Peche, A., Berkhahn, S., Feng, Y., Fuchs, L., Graf, T., Haberlandt, U., Kreibich, H., Sämann, R., Sester, M., Shehu, B., Wahl, J., & Neuweiler, I. (2021). Impact-Based Forecasting for Pluvial Floods. Earth’s Future, 9(2), 1–18. https://doi.org/10.1029/2020EF001851
  32. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. Int. J. Services Sciences, 1(1), 83–98
  33. Sai, F., Cumiskey, L., Weerts, A., Bhattacharya, B., Khan, R. H., & Po, A. I. (2018). Towards impact-based flood forecasting and warning in Bangladesh: a case study at the local level in Sirajganj district. Natural Hazard and Earth System Sciences, 1–20. https://doi.org/10.5194/nhess-2018-26
  34. Sajedi-Hosseini, F., Choubin, B., Solaimani, K., Cerda, A., & Kavian, A. (2018). Spatial prediction of soil erosion susceptibility using a fuzzy analytical network process: Application of the fuzzy decision making trial and evaluation laboratory approach. LDD Land Degreadation & Development, 29(9), 3092–3103
  35. Saputra, N. A., Perwira, A., Tarigan, M., & Nusa, A. B. (2020). Penggunaan Metode AHP dan GIS Untuk Zonasi Daerah Rawan Banjir Rob di Wilayah Medan Utara. Media Komunikasi Teknik Sipil, 26(1), 73–82
  36. Saranya, T., & Saravanan, S. (2020). Groundwater potential zone mapping using analytical hierarchy process (AHP) and GIS for Kancheepuram District, Tamilnadu, India. Modeling Earth Systems and Environment, 6(2), 1105–1122. https://doi.org/10.1007/s40808-020-00744-7
  37. Seejata, K., Yodying, A., Wongthadam, T., Mahavik, N., & Tantanee, S. (2018). Assessment of flood hazard areas using Analytical Hierarchy Process over the Lower Yom Basin, Sukhothai Province. Procedia Engineering, 212, 340–347. https://doi.org/10.1016/j.proeng.2018.01.044
  38. Septian, A., Elvarani, A. Y., Putri, A. S., Maulia, I., Damayanti, L., Pahlevi, M. Z., & Aswad, F. H. (2020). Identifikasi Zona Potensi Banjir Berbasis Sistem Informasi Geografis Menggunakan Metode Overlay dengan Scoring di Kabupaten Agam, Sumatera Barat. Jurnal Geosains dan Remote Sensing, 1(1), 11–22. https://doi.org/10.23960/jgrs.2020.v1i1.25
  39. Setiawan, H., Jalil, M., Enggi, M., Purwadi, F., Adios, C., Brata, A. W., Syaful Jufda, A., Studi, P., Geografi, P., Keguruan, F., Pendidikan, I., & Mulawarman, U. (2020). ANALISIS PENYEBAB BANJIR DI KOTA SAMARINDA. Jurnal Geografi Gea, 20(1), 39–43. https://ejournal.upi.edu/index.php/gea
  40. Sidek, L. M., Basri, H., Mohammed, M. H., Marufuzzaman, M., Ishak, N. A., Ishak, A. M., Omar, B. Z. C., Osman, S., Ramly, S., & Hassan, M. H. (2021). Towards impact-based flood forecasting and warning in Malaysia: A case study at Kelantan river. IOP Conference Series: Earth and Environmental Science, 704(1). https://doi.org/10.1088/1755-1315/704/1/012001
  41. Singhal, A., Raman, A., & Jha, S. K. (2022). Potential Use of Extreme Rainfall Forecast and Socio-Economic Data for Impact-Based Forecasting at the District Level in Northern India. Frontiers in Earth Science, 10, 1–15. https://doi.org/10.3389/feart.2022.846113
  42. Swain, K. C., Singha, C., & Nayak, L. (2020). Flood susceptibility mapping through the GIS-AHP technique using the cloud. ISPRS International Journal of Geo-Information, 9(12), 1–23. https://doi.org/10.3390/ijgi9120720
  43. Taylor, A. L., Kause, A., & Harrowsmith, M. (2019). Preparing for Doris: Exploring Public Responses to Impact-Based Weather Warnings in the United Kingdom. WEATHER, CL IMATE , AND SOCIETY, 11, 713–729. https://doi.org/10.1175/WCAS-D-18
  44. Tehrany, M. S., Pradhan, B., & Jebur, M. N. (2015). Flood susceptibility analysis and its verification using a novel ensemble support vector machine and frequency ratio method. Stochastic Environmental Research and Risk Assessment, 29(4), 1149–1165. https://doi.org/10.1007/s00477-015-1021-9
  45. Tempa, K. (2022). District flood vulnerability assessment using analytic hierarchy process (AHP) with historical flood events in Bhutan. PLoS ONE, 17(6), 1–20. https://doi.org/10.1371/journal.pone.0270467
  46. UKMO. (2020). IMPACT-BASED FORECASTING FOR EARLY ACTION THE FUTURE OF FORECASTS. UK Met Office
  47. Umar, H., Dahlan Balfas, M., Amin Syam, M., Arum Pertiwi, D., & Iqbal, F. M. (2021). Geologi dan pemanfaatan sistem informasi geografis untuk daerah bahaya banjir dengan metode AHP di desa bangun rejo kecamatan tenggarong seberang, kutai kartanegara, kalimantan timur. Jurnal Teknik Geologi: Ilmu Pengetahuan dan Teknologi, 4(1), 7–17
  48. Velastegui-Montoya, A., Montalván-Burbano, N., Peña-Villacreses, G., de Lima, A., & Herrera-Franco, G. (2022). Land Use and Land Cover in Tropical Forest: Global Research. Forests, 13(10), 1–34. https://doi.org/10.3390/f13101709
  49. Vojtek, M., & Vojteková, J. (2019). Flood susceptibility mapping on a national scale in Slovakia using the analytical hierarchy process. Water (Switzerland), 11(2), 1–17. https://doi.org/10.3390/w11020364
  50. Weyrich, P., Scolobig, A., Bresch, D. N., & Patt, A. (2018). Effects of Impact-Based Warnings and Behavioral Recommendations for Extreme Weather Events. WEATHER, CLIMATE, AND SOCIETY, 10, 781–796. https://doi.org/10.1175/WCAS-D-18
  51. WMO. (2015). WMO Guidelines on Multi-hazard Impact-based Forecast and Warning Services (1 ed.)
  52. Yassar, M. F., Nurul, M., Nadhifah, N., Sekarsari, N. F., Dewi, R., Buana, R., Fernandez, S. N., & Rahmadhita,
  53. K. A. (2020). Penerapan Weighted Overlay Pada Pemetaan Tingkat Probabilitas Zona Rawan Longsor di Kabupaten Sumedang, Jawa Barat. Jurnal Geosains dan Remote Sensing, 1(1), 1–10. https://doi.org/10.23960/jgrs.2020.v1i1.13
  54. Yin, J., Yu, D., Yin, Z., Liu, M., & He, Qi. (2016). Evaluating the impact and risk of pluvial flash flood on intra-urban road network: A case study in the city center of Shanghai, China. Journal of Hydrology, 537, 138–145

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