Evaluasi Pemantauan Kekeringan Multi-Skala Standardized Precipitation Index (SPI) Berbasis Produk Curah Hujan Satelit di Wilayah Jambi, Riau, dan Sumatera Selatan
Keywords:
Kekeringan Meteorologis; Produk Curah Hujan Satelit; SPI Multi-SkalaAbstract
Kekeringan adalah bencana hidrometeorologis bergradasi lambat yang berdampak luas, di mana pemantauannya di Indonesia terkendala oleh terbatasnya kerapatan stasiun observasi curah hujan permukaan. Keterbatasan data ini menyebabkan pemetaan di kawasan rawan kebakaran lahan, seperti Sumatera Bagian Tengah, menjadi kurang akurat. Oleh karena itu, penelitian ini bertujuan mengevaluasi keandalan lima produk estimasi curah hujan satelit (CHIRPS, PERSIANN, MSWEP, GSMaP, dan CMORPH) berbasis Standardized Precipitation Index (SPI) multi-skala di Jambi, Riau, dan Sumatera Selatan periode 2001-2020. Kinerja satelit divalidasi terhadap data stasiun BMKG menggunakan metrik statistik (Korelasi Pearson dan Root Mean Square Error) serta metrik kontingensi (Accuracy, Probability of Detection, False Alarm Ratio, dan Critical Success Index). Hasil analisis menunjukkan akurasi satelit bervariasi secara spasial dan temporal. Pada Sumatera Selatan dan Jambi, MSWEP paling akurat pada skala waktu pendek, sedangkan GSMaP mendominasi pada skala menengah hingga panjang, karena kemampuannya mereduksi bias orografis. Sebaliknya, CMORPH dan PERSIANN menunjukkan performa terbaik di Riau berkat keunggulan algoritmanya dalam menangkap dinamika konvektif ekuatorial, sementara CHIRPS secara konsisten menghasilkan tingkat galat tertinggi. Kesimpulannya, MSWEP, GSMaP, dan CMORPH direkomendasikan sebagai alternatif data terbaik untuk mendukung sistem peringatan dini kekeringan dan kebakaran lahan di Sumatera Bagian Tengah.
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Song, Z., Xia, J., She, D., Zhang, L., Hu, C., & Zhao, L. (2020). The Development of a Nonstationary Standardized Precipitation Index Using Climate Covariates: A Case Study in The Middle and Lower Reaches of Yangtze River Basin, China. Journal of Hydrology, 588. https://doi.org/10.1016/j.jhydrol.2020.125115
Sorooshian, S., Hsu, K.-L., Gao, X., Gupta, H. V, & Braithwaite, D. (2000). Evaluation of PERSIANN System Satellite-Based Estimates of Tropical Rainfall.
Surmaini, E., & Faqih, D. A. (2016). Kejadian Iklim Ekstrem dan Dampaknya Terhadap Pertanian Tanaman Pangan di Indonesia Extreme Climate Events and their Impacts on Food Crop in Indonesia.
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Tsesmelis, D. E., Leveidioti, I., Karavitis, C. A., Kalogeropoulos, K., Vasilakou, C. G., Tsatsaris, A., & Zervas, E. (2023). Spatiotemporal Application of the Standardized Precipitation Index (SPI) in the Eastern Mediterranean. Climate, 11(5). https://doi.org/10.3390/cli11050095
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Wagan, B., Zhang, Z., Baopeing, F., Wagan, H., Han, S., Ahmad, I., & Kabo-Bah, A. T. (2015). Using the SPI to Interpret Spatial and Temporal Conditions of Drought in China. Outlook on Agriculture, 44(3), 235–241. https://doi.org/10.5367/oa.2015.0217
Wang, F., Yang, H., Wang, Z., Zhang, Z., & Li, Z. (2019). Drought evaluation with CMORPH satellite precipitation data in the Yellow River basin by using Gridded Standardized Precipitation Evapotranspiration Index. Remote Sensing, 11(5). https://doi.org/10.3390/rs11050485
Wanisakdiah, S., Sutikno, S., & Handayani, Y. L. (2017). Analisis Indeks Kekeringan Meteorologis Lahan Gambut di Pulau Tebing Tinggi Provinsi Riau Menggunakan Data Satelit Tropical Rainfall Measuring Mission (TRMM). Jom FTEKNIK, 4(2).
WMO. (2012). Standardized Precipitation Index User Guide. World Meteorological Organization. https://www.droughtmanagement.info/literature/WMO_standardized_precipitation_index_user_guide_en_2012.pdf
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Zhao, H., & Ma, Y. (2019). Evaluating the Drought-Monitoring Utility of Four Satellite-Based Quantitative Precipitation Estimation Products at Global Scale. Remote Sensing, 11(17). https://doi.org/10.3390/rs11172010
Bankar, A., Venkatesan, P., Chopra, G., & Sujith, R. I. (2025). Evaluation of High-Resolution Gridded Precipitation Datasets Against a Dense Rain Gauge Network During the Indian Summer Monsoon.
Beck, H. E., Van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., & De Roo, A. (2017). MSWEP: 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data. Hydrology and Earth System Sciences, 21(1), 589–615. https://doi.org/10.5194/hess-21-589-2017
BMKG. (2024, April 17). (Analisis-Bulanan) Indeks Kekeringan dan Kebasahan Meteorologis 3 Bulanan Untuk Bulan Januari - Februari - Maret Tahun 2024 di Provinsi Jawa Timur. Badan Meteorologi Klimatologi dan Geofisika. https://staklim-jatim.bmkg.go.id/index.php/indeks-presipitasi-terstandarisasi-spi-3-bulanan-di-propinsi-jawa-timur/4231-analisis-bulanan-indeks-kekeringan-dan-kebasahan-meteorologis-3-bulanan-di-provinsi-jawa-timur-tahun-2024/555560865-analisis-bulanan-indeks-kekeringan-dan-kebasahan-meteorologis-3-bulanan-untuk-bulan-januari-februari-maret-tahun-2024-di-provinsi-jawa-timur
BNPB. (2026). Data Informasi Bencana Indonesia (DIBI). Badan Nasional Penanggulangan Bencana. https://data.bnpb.go.id/
Dandridge, C., Lakshmi, V., Bolten, J., & Srinivasan, R. (2019). Evaluation of Satellite-Based Rainfall Estimates in the Lower Mekong River Basin (Southeast Asia). Remote Sensing, 11(22). https://doi.org/10.3390/rs11222709
Edwards, D. C., & McKee, T. B. (1997). Characteristic of 20th Century Drought in The United States at Multiple Time Scales.
Ferijal, T., Mechram, S., Fauzi, A., & Ferdiansyah, T. (2025). Performance Analysis of Satellite-Derived Precipitation Data in Aceh, Indonesia. International Journal of Geoinformatics, 21(7), 1–15. https://doi.org/10.52939/ijg.v21i7.4311
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S., Husak, G., Rowland, J., Harrison, L., Hoell, A., & Michaelsen, J. (2015). The climate hazards infrared precipitation with stations - A new environmental record for monitoring extremes. Scientific Data, 2. https://doi.org/10.1038/sdata.2015.66
Giarno, Pramono Hadi, M., Suprayogi, S., & Heru Murti, S. (2018). Distribution of Accuracy of TRMM Daily Rainfall in Makassar Strait. Forum Geografi: Indonesian Journal of Spatial and Regional Analysis, 32, 38–52.
Guo, H., Bao, A., Liu, T., Chen, S., & Ndayisaba, F. (2016). Evaluation of PERSIANN-CDR for meteorological drought monitoring over China. Remote Sensing, 8(5). https://doi.org/10.3390/rs8050379
Hayes, M., Svoboda, M., Wall, N., & Widhalm, M. (2011). The lincoln declaration on drought indices: Universal meteorological drought index recommended. Bulletin of the American Meteorological Society, 92(4), 485–488. https://doi.org/10.1175/2010BAMS3103.1
Herwanto, H. W., Widiyaningtyas, T., & Indriana, P. (2019). Penerapan Algoritme Linear Regression untuk Prediksi Hasil Panen Tanaman Padi. Dalam JNTETI (Vol. 8, Nomor 4).
Huang, P., Huang, M., Feng, A., Li, Y., Yu, K., Guo, Y., Yu, W., & Yang, K. (2025). Performance of remotely sensed precipitation products in capturing meteorological drought over typical agricultural planting area. Environmental Earth Sciences, 84(13). https://doi.org/10.1007/s12665-025-12258-5
Joyce, R. J., Janowiak, J. E., Arkin, P. A., & Xie, P. (2004). CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution.
Kubota, T., Shige, S., Hashizume, H., Aonashi, K., Takahashi, N., Seto, S., Hirose, M., Takayabu, Y. N., Ushio, T., Nakagawa, K., Iwanami, K., Kachi, M., & Okamoto, K. (2007). Global Precipitation Map Using Satellite-Borne Microwave Radiometers by the GSMaP Project: Production and Validation. IEEE Transactions on Geoscience and Remote Sensing, 45(7), 2259–2275. https://doi.org/10.1109/TGRS.2007.895337
Le, M. H., Lakshmi, V., Bolten, J., & Bui, D. Du. (2020). Adequacy of Satellite-derived Precipitation Estimate for Hydrological Modeling in Vietnam Basins. Journal of Hydrology, 586. https://doi.org/10.1016/j.jhydrol.2020.124820
Mashuri, Karlina, & Sujono, J. (2025). Assessment of satellite-based rainfall products for drought monitoring in the Siak Watershed, Indonesia. Environmental Challenges, 19. https://doi.org/10.1016/j.envc.2025.101134
Mckee, T. B., Doesken, N. J., & Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17–22.
Rahmalina, W., & Novreta. (2020). Peramalan Indeks Kekeringan Kelayang Menggunakan Metode Sarima dan SPI. Potensi: Jurnal Sipil Politeknik.
Roy, D., & Banu, S. (2021). Comparison of Satellite Derived Rainfall Estimations: CMORPH, IMERG and GSMaP with Observed Precipitation. American Journal of Climate Change, 10(04), 407–421. https://doi.org/10.4236/ajcc.2021.104021
Schober, P., & Schwarte, L. A. (2018). Correlation coefficients: Appropriate use and interpretation. Anesthesia and Analgesia, 126(5), 1763–1768. https://doi.org/10.1213/ANE.0000000000002864
Song, Z., Xia, J., She, D., Zhang, L., Hu, C., & Zhao, L. (2020). The Development of a Nonstationary Standardized Precipitation Index Using Climate Covariates: A Case Study in The Middle and Lower Reaches of Yangtze River Basin, China. Journal of Hydrology, 588. https://doi.org/10.1016/j.jhydrol.2020.125115
Sorooshian, S., Hsu, K.-L., Gao, X., Gupta, H. V, & Braithwaite, D. (2000). Evaluation of PERSIANN System Satellite-Based Estimates of Tropical Rainfall.
Surmaini, E., & Faqih, D. A. (2016). Kejadian Iklim Ekstrem dan Dampaknya Terhadap Pertanian Tanaman Pangan di Indonesia Extreme Climate Events and their Impacts on Food Crop in Indonesia.
Tjasyono, B. (2004). Klimatologi (2nd ed.). Institut Teknologi Bandung. https://perpustakaan.bmkg.go.id/
Tsesmelis, D. E., Leveidioti, I., Karavitis, C. A., Kalogeropoulos, K., Vasilakou, C. G., Tsatsaris, A., & Zervas, E. (2023). Spatiotemporal Application of the Standardized Precipitation Index (SPI) in the Eastern Mediterranean. Climate, 11(5). https://doi.org/10.3390/cli11050095
Ushio, T., Sasashige, K., Kubota, T., Shige, S., Okamoto, K., Aonashi, K., Inoue, T., Takahashi, N., Iguchi, T., Kachi, M., Oki, R., Morimoto, T., & Kawasaki, Z. I. (2009). A Kalman Filter Approach to The Global Satellite Mapping of Precipitation (GSMaP) from Combined Passive Microwave and Infrared Radiometric Data. Journal of the Meteorological Society of Japan, 87 A, 137–151. https://doi.org/10.2151/jmsj.87A.137
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
Wagan, B., Zhang, Z., Baopeing, F., Wagan, H., Han, S., Ahmad, I., & Kabo-Bah, A. T. (2015). Using the SPI to Interpret Spatial and Temporal Conditions of Drought in China. Outlook on Agriculture, 44(3), 235–241. https://doi.org/10.5367/oa.2015.0217
Wang, F., Yang, H., Wang, Z., Zhang, Z., & Li, Z. (2019). Drought evaluation with CMORPH satellite precipitation data in the Yellow River basin by using Gridded Standardized Precipitation Evapotranspiration Index. Remote Sensing, 11(5). https://doi.org/10.3390/rs11050485
Wanisakdiah, S., Sutikno, S., & Handayani, Y. L. (2017). Analisis Indeks Kekeringan Meteorologis Lahan Gambut di Pulau Tebing Tinggi Provinsi Riau Menggunakan Data Satelit Tropical Rainfall Measuring Mission (TRMM). Jom FTEKNIK, 4(2).
WMO. (2012). Standardized Precipitation Index User Guide. World Meteorological Organization. https://www.droughtmanagement.info/literature/WMO_standardized_precipitation_index_user_guide_en_2012.pdf
Wu, W., Li, Y., Luo, X., Zhang, Y., Ji, X., & Li, X. (2019). Performance evaluation of the CHIRPS precipitation dataset and its utility in drought monitoring over Yunnan Province, China. Geomatics, Natural Hazards and Risk, 10(1), 2145–2162. https://doi.org/10.1080/19475705.2019.1683082
Zhao, H., & Ma, Y. (2019). Evaluating the Drought-Monitoring Utility of Four Satellite-Based Quantitative Precipitation Estimation Products at Global Scale. Remote Sensing, 11(17). https://doi.org/10.3390/rs11172010
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2026-11-05
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