PENGUKURAN KINERJA DATA HUJAN CHIRPS DALAM PENILAIAN KEKERINGAN DI LOMBOK TENGAH

HUMAIRO SAIDAH, I WAYAN YASA, HERI SULISTIYONO

Abstract


Drought index analysis requires long data requirements. However, the complete and long recording periods of rainfall data are still the main obstacles to meeting rainfall data needs. Apart from that, there are still many areas that do not have adequate and evenly distributed rain recording stations. This research aims to see if the use of CHIRPS (Climate Hazard Group Independent Precipitation with Station Data) satellite rainfall data can be used to calculate the drought index using the SPI (Standardized Precipitation Index) method. The research began with collecting rain data from ARR measurements and downloading CHIRPS satellite rain data. CHIRPS data is corrected first by reducing the correction factor using simple regression where CHIPS data is the independent variable and ARR data is the dependent variable. CHIRPS data was then corrected and used in calculating the drought index using the SPI method. The results of the SPI calculation from the corrected CHIRPS rainfall data were then compared with the drought index resulting from analysis using ARR data. The results obtained show that both CHIRPS data and ARR data produce the highest drought index with the Normal severity category. The drought index resulting from CHIRPS data analysis is stated to be quite good and corresponds to a suitability level of 60%. So the CHIRPS data is declared good and can be used for drought analysis in this region.


Keywords


CHIRPS, SPI, Drought Index, Regression, Correction Factor

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References


Agustina, L. (2023). Analisis Indeks Kekeringan Menggunakan Data Hujan Climate Hazards Group Infrared Precipitation With Station Data (Chirps) Di Kabupaten Lombok Tengah (Universitas Mataram). Universitas Mataram, Mataram. Retrieved from http://eprints.unram.ac.id/35563/

Ali, S. M., Khalid, B., Akhter, A., Islam, A., & Adnan, S. (2020). Analyzing the occurrence of floods and droughts in connection with climate change in Punjab province, Pakistan. Natural Hazards, 103(2), 2533–2559. https://doi.org/10.1007/s11069-020-04095-5

Amanullah, A., Dananjaya, R. H., & Chrismaningwang, G. (2023). Analisis regresi dengan metode support vector machine IMERG downscaled di Karanganyar. 3(1).

Azizah, M., Subiyanto, A., Triutomo, S., & Wahyuni, D. (2022). Pengaruh Perubahan Iklim Terhadap Bencana Hidrometeorologi di Kecamatan Cisarua—Kabupaten Bogor. PENDIPA Journal of Science Education, 6(2), 541–546. https://doi.org/10.33369/pendipa.6.2.541-546

BNPB. (2022). Buku Indek Risiko Bencana Indonesia 2022. Jakarta. Retrieved from https://inarisk.bnpb.go.id/pdf/BUKU%20IRBI%202022.pdf

Krisnayanti, D. S., Welkis, D. F. B., Hepy, F. M., & Legono, D. (2020). Evaluasi Kesesuaian Data Tropical Rainfall Measuring Mission (TRMM) dengan Data Pos Hujan Pada Das Temef di Kabupaten Timor Tengah Selatan. JURNAL SUMBER DAYA AIR, 16(1), 51–62. https://doi.org/10.32679/jsda.v16i1.646

Lehner, B., Döll, P., Alcamo, J., Henrichs, T., & Kaspar, F. (2006). Estimating the impact of global change on flood and drought risks in Europe: A continental, integrated analysis. Climatic Change, 75, 273–299.

Mamenun, M., Pawitan, H., & Sopaheluwakan, A. (2014). VALIDASI DAN KOREKSI DATA SATELIT TRMM PADA TIGA POLA HUJAN DI INDONESIA. Jurnal Meteorologi dan Geofisika, 15(1). https://doi.org/10.31172/jmg.v15i1.169

McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Proceedings of the 8th Conference on Applied Climatology, 17(22), 179–183. Boston. Retrieved from https://climate.colostate.edu/pdfs/relationshipofdroughtfrequency.pdf

Nelvi, A., & Srigutomo, W. (2016). PROSIDING SNIPS 2016 Identifikasi Tingkat Kekeringan dan Kebasahan dengan Menggunakan Standardized Precipitation Index ( SPI ) PROSIDING SNIPS 2016. 36–43.

Pratama, A. W., Buono, A., Hidayat, R., & Harsa, H. (2018). Bias correction of daily satellite precipitation data using genetic algorithm. IOP Conference Series: Earth and Environmental Science, 149(1), 012071. https://doi.org/10.1088/1755-1315/149/1/012071

Saidah, H., Budianto, M. B., & Hanifah, L. (2017). ANALISA INDEKS DAN SEBARAN KEKERINGAN MENGGUNAKAN METODE STANDARDIZED PRECIPITATION INDEX (SPI) DAN GEOGRAPHICAL INFORMATION SYSTEM (GIS) UNTUK PULAU LOMBOK. JURNAL SPEKTRAN, 5(2). Retrieved from https://ojs.unud.ac.id/index.php/jsn/article/view/32940

Tabari, H. (2020). Climate change impact on flood and extreme precipitation increases with water availability. Scientific Reports, 10(1), 13768. https://doi.org/10.1038/s41598-020-70816-2

Trenberth, K. E. (2005). The impact of climate change and variability on heavy precipitation, floods, and droughts. Encyclopedia of Hydrological Sciences, 17, 1–11.

Whetton, P., Fowler, A., Haylock, M., & Pittock, A. (1993). Implications of climate change due to the enhanced greenhouse effect on floods and droughts in Australia. Climatic Change, 25(3–4), 289–317.

Yang, C., Yu, Z., Hao, Z., Zhang, J., & Zhu, J. (2012). Impact of climate change on flood and drought events in Huaihe River Basin, China. Hydrology Research, 43(1–2), 14–22.




DOI: https://doi.org/10.35327/gara.v18i1.790

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