Correlation Analysis Between Measured Rain Data with Satellite at Rainfall Station in Merapi
DOI:
https://doi.org/10.18196/st.v27i1.22180Keywords:
rainfall, correlation coefficient, satellite, GPM, PERSIANNAbstract
Manual and automatic rain gauges often need to be revised in measuring rainfall due to various constraints. Therefore, using rain data from satellites will be a promising alternative. The rain data used is measured hourly rainfall data >20mm in 2012, 2017, and 2022. In addition, rain data from the PERSIANN and GPM satellites were also used. The analysis was carried out using the correlation coefficient (r) method, which aims to find the correlation between measured rain data and satellite rain data. The results show that the PERSIANN satellite has the highest correlation value in rain duration in two years, while the GPM satellite has the highest total depth and intensity correlation value in two years. Therefore, it can be concluded that the GPM satellite has better accuracy than the PERSIANN satellite in monitoring rain.References
Adib Azka, M., Kadar Dzikiro, T., Kusuma Wardani, U., & Fadlan, A. (2018). Uji akurasi data model estimasi curah hujan satelit TRMM, GSMAP, dan GPM selama periode siklon tropis Cempaka dan Dahlia di wilayah Jawa validation of TRMM, GSMAP, and GPM Modeling Data Accuracy during tropical cyclone event in Java region. Seminar Nasional Penginderaan Jauh, July 2018, 983–991.
Anonim. (2019). Banjir. Badan Penanggulangan Bencana Daerah (BPBD) Daerah Intimewa Yogyakarta (DIY). http://bpbd.jogjaprov.go.id/banjir (Accessed 24 February 2024)
Anonim. (2022). Modul 1 Analisis Curah Hujan. Direktorat Jenderal Sumber Daya Air. Jakarta.
Aristizabal, E., Garcia, E. F., Marin, R. J., Gomez, F., & JuanGuzman-Martinez. (2022). Rainfall-intensity effect on landslide hazard assessment due to climate change in north-western Colombian Andes. Revista Facultad de Ingenieria, 103. https://doi.org/10.17533/udea.redin.20201215
Badri, R., & Yerizon. (2021). Development of the learning instruction based on problem based learning models oriented with mitigation of mount eruption and lava floods on the mathematical reasoning ability of class VIII students of SMP / MTs. Journal of Physics: Conference Series, 1742(1). https://doi.org/10.1088/1742-6596/1742/1/012001
BMKG ( METEOROLOGICAL, CLIMATOLOGICAL, AND GEOPHYSICAL AGENCY). (2024). Probabilistik Curah Hujan 20 mm. https://www.bmkg.go.id/cuaca/probabilistik-curah-hujan.bmkg?mm=20&hour=24&gen=yeyoybj0smcr31fx1l (accessed 24 April 2024)
BSN. (2016). SNI 2415:2016. Tata Cara Perhitungan Debit Banjir Rencana. 1–4.
Chapman, S., Birch, C. E., Galdos, M. V., Pope, E., Davie, J., Bradshaw, C., Eze, S., & Marsham, J. H. (2021). Assessing the impact of climate change on soil erosion in East Africa using a convection-permitting climate model. Environmental Research Letters, 16(8). https://doi.org/10.1088/1748-9326/ac10e1
Fakhruddin, I., & Elmada, M. A. G. (2022). Local wisdom as a part of disaster communication: a study on the local storytelling in disaster mitigation. ETNOSIA : Jurnal Etnografi Indonesia. https://doi.org/10.31947/etnosia.v7i2.22145
Ginting, J. M., Sujono, J., & Jayadi, R. (2019). Analisis Hubungan Data Hujan Satelit dengan Hujan Terukur ARR Kalibawang. Prociding Konferensi Nasional Pascasarjana Teknik Sipil (KNPTS) X 2019, November, 89–102.
Jarwanti, D. P., Suhartanto, E., & Fidari, J. S. (2021). Validasi Data Curah Hujan Satelit TRMM (Tropical Rainfall Measuring Mission) dengan Data Pos Penakar Hujan di DAS Grindulu, Kabupaten Pacitan, Jawa Timur. Jurnal Teknologi Dan Rekayasa Sumber Daya Air, 1(2), 772–785. https://doi.org/10.21776/ub.jtresda.2021.001.02.36
Maharani, S. A., Romadhona, M., & Masnuna, M. (2023). Perancangan picture storybook berbasis augmented reality (AR) tentang edukasi sigap bencana alam untuk anak usia 9-12 tahun. SYNAKARYA Visual Communication Design Student Journal, 4(2). https://doi.org/10.33005/synakarya.v4i2.89
Mamenun, Pawitan, H., & Sophaheluwakan, A. (2014). Validasi dan koreksi data satelit TRMM pada tiga pola hujan di Indonesia (Validation and correction of TRMM satellite data on three rainfall patterns in Indonesia). Jurnal Meteorologi Dan Geofisika, 15(1), 13–23. http://202.90.199.54/jmg/index.php/jmg/article/view/169/155
Munir, M. D. (2019). Bangunan sabodam, fungsi dan potensinya sebagai bagian dari geowisata gunung api Merapi. Jurnal Lingkungan Dan Bencana Geologi, 10(2), 15–26. https://doi.org/10.34126/jlbg.v10i2.202
Nguyen, P., Ombadi, M., Sorooshian, S., Hsu, K., AghaKouchak, A., Braithwaite, D., Ashouri, H., & Rose Thorstensen, A. (2018). The PERSIANN family of global satellite precipitation data: A review and evaluation of products. Hydrology and Earth System Sciences, 22(11), 5801–5816. https://doi.org/10.5194/hess-22-5801-2018
Otto, F. E. L., Zachariah, M., Saeed, F., Siddiqi, A., Kamil, S., Mushtaq, H., Arulalan, T., AchutaRao, K., Chaithra, S. T., Barnes, C., Philip, S., Kew, S., Vautard, R., Koren, G., Pinto, I., Wolski, P., Vahlberg, M., Singh, R., Arrighi, J., … Clarke, B. (2023). Climate change increased extreme monsoon rainfall, flooding highly vulnerable communities in Pakistan. Environmental Research: Climate, 2(2). https://doi.org/10.1088/2752-5295/acbfd5
Sorooshian, S. (2020). UCI CHRS Data Portal - PERSIANN. Accesed (12 Febuary 2024), http://chrsdata.eng.uci.edu
Sugiyono. (2013). Statika untuk Penelitian. Bandung: Alfabeta.
Syaifullah, M. D. (2014). Validasi data TRMM terhadap data curah hujan aktual di tiga DAS di Indonesia. Jurnal Meteorologi Dan Geofisika, 15(2), 109–118. https://doi.org/10.31172/jmg.v15i2.180
Tan, M. L., & Duan, Z. (2017). Assessment of GPM and TRMM precipitation products over Singapore. Remote Sensing, 9(7), 1–16. https://doi.org/10.3390/rs9070720
Tradowsky, J. S., Philip, S. Y., Kreienkamp, F., Kew, S. F., Lorenz, P., Arrighi, J., Bettmann, T., Caluwaerts, S., Chan, S. C., De Cruz, L., de Vries, H., Demuth, N., Ferrone, A., Fischer, E. M., Fowler, H. J., Goergen, K., Heinrich, D., Henrichs, Y., Kaspar, F., … Wanders, N. (2023). Attribution of the heavy rainfall events leading to severe flooding in Western Europe during July 2021. Climatic Change, 176(7). https://doi.org/10.1007/s10584-023-03502-7
Vernimmen, R. R. E., Hooijer, A., Mamenun, Aldrian, E., & Van Dijk, A. I. J. M. (2012). Evaluation and bias correction of satellite rainfall data for drought monitoring in Indonesia. Hydrology and Earth System Sciences, 16(1), 133–146. https://doi.org/10.5194/hess-16-133-2012
Zhang, C., Chen, X., Shao, H., Chen, S., Liu, T., Chen, C., Ding, Q., & Du, H. (2018). Evaluation and intercomparison of high-resolution satellite precipitation estimates-GPM, TRMM, and CMORPH in the Tianshan Mountain Area. Remote Sensing, 10(10). https://doi.org/10.3390/rs10101543
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