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Analisis Spasial Potensi Kekeringan di Daerah Aliran Sungai Kapuas, Kalimantan Barat

*Diah Auliyani  -  Balai Penelitian dan Pengembangan Teknologi Pengelolaan Daerah Aliran Sungai (KLHK) Surakarta, Indonesia
Muhammad Rekapermana  -  Balai Besar Taman Nasional Betung Kerihun dan Danau Sentarum (KLHK) Putussibau Kalimantan Barat, Indonesia

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Abstract

Kekeringan merupakan efek samping dari variabilitas iklim, yang dapat terjadi di daerah dengan curah hujan tinggi maupun rendah. Kekeringan dapat menjadi suatu bencana apabila terjadi secara terus menerus. Standardized Precipitation Index (SPI) memudahkan pemantauan kejadian kekeringan dengan memanfaatkan standar deviasi dari curah hujan. Penelitian ini bertujuan untuk menganalisis potensi kekeringan di Daerah Aliran Sungai (DAS) Kapuas. Lokasi penelitian merupakan DAS terbesar di Provinsi Kalimantan Barat. Dalam tulisan ini akan digunakan SPI periode kumulatif 1 bulan, 3 bulan, 6 bulan, dan 12 bulan untuk menentukan tingkat kekeringannya. Dengan menggunakan perangkat lunak Arc GIS, nilai rata-rata SPI setiap periode kumulatif kemudian diinterpolasikan untuk mendapatkan sebaran spasial potensi kekeringan di seluruh wilayah DAS Kapuas. Seri data curah hujan harian tahun 1995-2017 dari 5 stasiun hujan yang kelola oleh Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) Provinsi Kalimantan Barat digunakan dalam analisisnya. Kelima stasiun pengamatan hujan tersebut terletak di (1) Bandara Supadio Pontianak, (2) Pelabuhan Maritim Pontianak, (3) Bandara Susilo Sintang Kabupaten Sintang, (4) Bandara Nanga Pinoh Kabupaten Melawi, dan (5) Bandara Pangsuma Kabupaten Kapuas Hulu. Hasilpenelitian menunjukkan bahwa setiap lokasi pengamatan hujan mengalami kekeringan untuk setiap periode kumulatif dengan frekuensi 1 hingga 4 kali.Kekeringan tersebut memiliki durasi paling lama 2 bulan secara berturut-turut. Distribusi spasial SPI di DAS Kapuas memiliki nilai antara -0,1 hingga -0,07 yang termasuk dalam kategori normal. Secara keseluruhan, DAS Kapuas merupakan wilayah yang tidak berpotensi mengalami bencana kekeringan. 

Drought is a side effect of climate variability, which can occur in areas with high or low rainfall.  Drought will become a disaster if it happens continuously. Standardized Precipitation Index (SPI) facilitates the drought monitoring by utilizing standard deviation of its rainfall. This study aims to analyze the potential for drought in the Kapuas Watershed. Kapuas Watershed is the widest watershed located in West Kalimantan Province. In this paper, 1 month, 3 months, 6 months, and 12 months cumulative periods of SPI will be used to determine the level of drought.  Using Arc GIS software, the average SPI value for each cumulative period is then interpolated to obtain the spatial distribution of potential drought in the entire Kapuas Watershed area.The 1995-2017 daily rainfall data series from 5 rainfall stations managed by The West Kalimantan Province Meteorology, Climatology and Geophysics Agency (BMKG) were used in this analysis. The five rainfall stations are located at (1) Supadio Airport, Pontianak, (2) Pontianak Maritime Port, (3) Susilo Airport, Sintang Regency, (4) Nanga Pinoh Airport, Melawi Regency, and (5) Pangsuma Airport, Kapuas Hulu Regency.  The results showed that each rainfall station experienced drought for each cumulative period with a frequency of 1 to 4 times. Its duration was 2 months or less. The spatial distribution of SPI in Kapuas Watershed has a value between -0.1 to -0.07 which categorized as normal. Overall, Kapuas Watershed is an area that has no potential for drought.

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Keywords: drought; rainfall; SPI; Kapuas

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  1. Adiningsih, S. E. (2014). Tinjauan metode deteksi parameter kekeringan berbasis data penginderaan jauh. In Prosiding Seminar Nasional Penginderaan Jauh 2014 (pp. 210–220). Bogor: LAPAN
  2. Amri, M. R., Yulianti, G., Yunus, R., Wiguna, S., Adi, A. ., Ichwana, A. ., … Septian, R. . (2016). Risiko bencana Indonesia. (R. Jati & M. . Amri, Eds.). Jakarta: Badan Nasional Penanggulangan Bencana
  3. Arismaya, J. (2016). Analisis potensi kekeringan menggunakan theory of run (Studi kasus Sub DAS Bengawan Solo Hulu). Skripsi. Fakultas Teknologi Pertanian. IPB
  4. Cancelliere, A., Mauro, G. Di, Bonaccorso, B., & Rossi, G. (2007). Drought forecasting using the standardized precipitation index. Water Resources Management, 21, 801–819. https://doi.org/10.1007/s11269-006-9062-y
  5. Guenang, G. M., & Mkankam Kamga, F. (2014). Computation of the standardized precipitation index (SPI) and its use to assess drought occurrences in Cameroon over recent decades. Journal of Applied Meteorology and Climatology, 53, 2310–2324. https://doi.org/10.1175/JAMC-D-14-0032.1
  6. Hayes, M. J., Svoboda, M. D., Wilhite, D. A., & Vanyarkho, O. V. (1999). Monitoring the 1996 drought using the standardized precipitation index. Bulletin of The American Meteorological Society, 80(3), 429–438. Retrieved from http://enso.unl.edu/ndmc/watch/
  7. Kayoman, L. (2010). Pemodelan spasial resiko kebakaran hutan dan lahan di Provinsi Kalimantan Barat. Tesis. Sekolah Pascasarjana. IPB
  8. Okpara, J. N., Afiesimama, E. A., Anuforom, A. C., Owino, A., & Ogunjobi, K. O. (2017). The applicability of standardized precipitation index: Drought characterization for early warning system and weather index insurance in West Africa. Natural Hazards, 89(2), 555–583. https://doi.org/10.1007/s11069-017-2980-6
  9. Setiawan, O. (2012). Analisis variabilitas curah hujan dan suhu di Bali. Jurnal Analisis Kebijakan Kehutanan, 9(1), 66–79
  10. Smakhtin, V. U., & Hughes, D. A. (2004). Review, automated estimation and analyses of drought indices in South Asia (No. 83). Colombo, Sri Lanka. Retrieved from http://www.iwmi.org
  11. Sönmez, F. K., Kömüscü, A. Ü., Erkan, A., & Turgu, E. (2005). An analysis of spatial and temporal dimension of drought vulnerability in Turkey using the standardized precipitation index. Natural Hazards, 35, 243–264. https://doi.org/10.1007/s11069-004-5704-7
  12. Spinoni, J., Naumann, G., Carrao, H., Barbosa, P., & Vogt, J. (2014). World drought frequency, duration, and severity for 1951-2010. International Journal of Climatology, 34, 2792–2804. https://doi.org/10.1002/joc.3875
  13. Sukmawati, A. (2006). Hubungan antara curah hujan dengan ttik panas (hotspot) sebagai indikator terjadinya kebakaran hutan dan lahan di Kabupaten Pontianak Propinsi Kalimantan Barat. Skripsi Fakultas Kehutanan IPB
  14. Utami, D., Hadiani, R. R., & Susilowati. (2013). Prediksi kekeringan berdasarkan standardized precipitation index pada Daerah Aliran Sungai Keduang di Kabupaten Wonogiri. MATRIKS TEKNIK SIPIL, September, 221–226
  15. Wahyu, A., Kuntoro, A. A., & Yamashita, T. (2010). Annual and seasonal discharge responses to forest / land cover changes and climate variations in Kapuas River Basin, Indonesia. Journal of International Development and Cooperation, 16(2), 81–100. https://doi.org/10.15027/29807
  16. Walsh, R. P. D. (1996). Drought frequency changes in Sabah and adjacent parts of northern Borneo since the late nineteenth century and possible implications for tropical rain forest dynamics. Journal of Tropical Ecology, 12(3), 382–407. https://doi.org/10.1017/S0266467400009585
  17. Wilhite, D. A. (2000). Drought as a natural hazard: Concepts and definitions. Drought: A Global Assessment, 1, 3–18. Retrieved from http://digitalcommons.unl.edu/droughtfacpubhttp://digitalcommons.unl.edu/droughtfacpub/69
  18. Wilhite, D. A., & Glantz, M. H. (1985). Understanding: The drought phenomenon: The role of definitions. Water International, 10(3), 111–120. https://doi.org/10.1080/02508068508686328

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