Spatial and Temporal Analysis of Seasonal Rainfall on the East Coast of North Sumatra, Indonesia

https://doi.org/10.22146/ijg.56724

Nuzul Hijri Darlan(1*), Sigit Supadmo Arif(2), Putu Sudira(3), Bayu Dwi Apri Nugroho(4)

(1) Doctoral student of Department of Agricultural Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia and Indonesian Oil Palm Research Institute, North Sumatera, Indonesia.
(2) Department of Agricultural Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia Indonesian Oil Palm Research Institute
(3) Department of Agricultural Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia Indonesian Oil Palm Research Institute
(4) Department of Agricultural Engineering, Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia Indonesian Oil Palm Research Institute
(*) Corresponding Author

Abstract


The east coast of North Sumatra has lower rainfall than the central (Bukit Barisan) and the west coast. Meanwhile, the literature on the influence of climate phenomena, such as El Nino, La Nina, and positive/negative IOD, on the rainfall distribution in North Sumatra remains quite limited. This paper aims to describe the spatial distribution of seasonal rainfall on the east coast of North Sumatra and its correlation with ENSO and the IOD. Hopefully, the spatial analysis of seasonal rainfall and its correlation to ENSO and IOD can improve the understanding on rainfall distribution and the influenced factors in the study area. For 16 years (1999–2014), the monthly rainfall data at 52 rain gauge stations that passed the homogeneity test were divided into the seasonal 6-month and 4-month. Hereafter, the seasonal rainfall was spatially analyzed with the Inverse Distance Weighting (IDW) method using ArcMap software. The spatial analysis results can clearly describe the rainfall dynamics and its anomalies, therefore, can be more easily understood. The repetition of rainfall anomaly patterns can be seen in January to June (JFMAMJ), January to April (JFMA), and May to August (MJJA), which occurs in 3–4 years. Furthermore, the Pearson-correlation analysis shows that SOI has a strong positive correlation on JFMAMJ (0.529), JFMA (0.485), and MJJA (0.366), while IOD has a strong positive correlation on MJJA (0.512) and negative on September to December - SOND (-0.341).

 


Keywords


spatial; seasonal rainfall; North Sumatra; El Nino; IOD

Full Text:

PDF


References

Aldrian, E. (2002). Spatial Patterns of ENSO Impact on Indonesian Rainfall. Jurnal Sains & Teknologi Modifikasi Cuaca. 3(1). 5-15. https://doi.org/10.29122/jstmc.v3i1.2154.

Aldrian, E. and Susanto, D. (2003). Identification of Three Dominant Rainfall Regions Within Indonesia and Their Relationship to Sea Surface Temperature. Int. J. Climatol. 23. 1435-1452. http://doi.org/10.1002/joc.950.

Alemu, M. M. and Baweke, G. T. (2019). Analysis of Spatial Variability and Temporal Trends of Rainfall in Amhara Region, Ethiopia. Journal of Water and Climate Change. In press. http://doi.org/10.2166/wcc.2019.084.

Bhunia, G.S., Shit, P. K., and Maiti, R. (2016). Comparison of GIS-based interpolation methods for spatial distribution of soil organic carbon (SOC). Journal of the Saudi Society of Agricultural Sciences. 17(2). 114-126. https://doi.org/10.1016/j.jssas.2016.02.001.

Boer, R. and Faqih, M. (2004). Global Climate Forcing Factors and Rainfall Variability in West Java: Case Study in Bandung District. J. Agromet 18(2). 1-12. https://doi.org/10.29244/ j.agromet.18.2.1-12.

Brisson, E., Demuzere, M., Willems, P., van Lipzig, N. P. M. (2015). Assesment of Natural Climate Variability Using a Weather Generator. Clim Dyn. 44. 495-508. https://doi.org/10.1007/s00382-014-2122-8.

Chen, F-W. and Liu, C-W. (2012). Estimation of the spatial rainfall distribution using inverse distance weighting (IDW) in the middle of Taiwan. Paddy and Water Environment. 10(3). 209–222. https://doi.org/10.1007/s10333-012-0319-1.

Chiew, F. H. A., Piechota, T. C., Dracup, J. A., and McMahon, T. A. (1998). El Nino Southern Oscillation and Australian Rainfall, Streamflow, and Drought: Links and Potential for Forecasting. Journal of Hydrology. 204(1). 138-149. https://doi.org/10.1016/S0022-1694(97)00121-2.

Fadholi, A. (2013). Studi Dampak El Nino dan Indian Ocean Diole (IOD) Terhadap Curah Hujan di Pangkalpinang. Jurnal Ilmu Lingkungan. 11(1). 43-50. https://doi.org/10.14710/ jil.11.1.43-50.

Ghosh, K. G. (2018). Analysis of Rainfall Trends and its Spatial Patterns During the Last Century over the Gangetic West Bengal, Eastern India. Journal of Geovisualization and

Spatial Analysis. 2(15). http://doi.org/10/1007/s41651-018-0022-x.

He, X., Koch, J., Zheng, C., Bovith, T., and Jensen, K. H. (2018). Comparison of Simulated Spatial Patterns Using Rain Gauge and Polametric-Radar-Based Precipitation Data in Catchment Hydrological Modeling. Journal of Hydrometeorology. 19(August). 1273-1288. http://doi.org/10.1175/JHM-D-17-0235.1.

Hermawan, E. (2010). Pengelompokan Pola Curah Hujan yang Terjadi di Beberapa Kawasan P.Sumatra Berbasis Hasil Analisis Teknik Spetral. Jurnal Meteorologi dan Geofisika. 11(2). 75-85. http://doi.org/10.31172/jmg.v11i2.67.

Irwandi, H., Nasution, M. I., Kurniawan, E., and Megalina, Y. (2017). Pengaruh El Nino Terhadap Variabilitas Curah Hujan di Sumatra Utara. Fisitek: Jurnal Ilmu Fisika dan Teknologi. 1(2). 7-15. http://dx.doi.org/10.30821/fisitek.v1i2.1319.

Kang, H. M. and Yusof, F. (2012). Homogeneity Tests on Daily Rainfall Series in Peninsular Malaysia. Int. J. Contemp. Math. Sciences. 7(1).9-22. http://doi.org/10.9790/0990-0503025763.

Kisaka, M.O., Mucheru-Muna, M., Ngetich, F. K., Mugwe, J. N., Mugendi, D., and Mairura, F. (2014). Rainfall Variability, Drought Characterization, and Efficacy of Rainfall Data Reconstruction: Case of Eastern Kenya. Advances in Meteorology. 2015. 16 pages. https://doi.org/10.1155/2015/380404.

Lee, H. S. (2015). General Rainfall Patterns in Indoneisa and the Potential Impacts of Local Seas on Rainfall Intensity. Water. 7. 1751-1768. https://doi.org/10.3390/w7041751.

Lee, J. H., Yang, C-Y., Julien, P. Y. (2020). Taiwanese rainfall variability associated with large-scale climate phenomena. Journal Advances in Water Resources. 135. http://doi.org/10.1016/j.advwaters.2019.103462.

Lestari, D. O., E. Sutriyono, Sabaruddin, and Iskandar, I. (2018). Respective Influences of Indian Ocean Dipole and El Nino Southern Oscillation on Indonesian Precipitation. J. Math. Fund. Sci. 50(3). 257-272. https://doi.org/10.5614/j.math.fund.sci.2018.50.3.3.

Ly, S., Charles, C., and Degré, A. (2011). Geostatistical interpolation of daily rainfall at catchment scale: the use of several variogram models in the Ourthe and Ambleve catchments, Belgium. Hydrology and Earth System Sciences. 15(7). 2259–2274. https://doi.org/10.5194/ hess-15-2259-2011.

Mulyana, E (2002). Hubungan antara ENSO dengan variasi curah hujan di Indonesia. Jurnal Sains & Teknologi Modifikasi Cuaca. 3(1). 1-4.

Nasution, M. I. and Nuh, M. (2018). Kajian Iklim Berdasarkan Klasifikasi Oldeman di Kabupaten Langkat. JISTech. 3(2). 1-19. http://dx/doi.org/10.30829/jistech.v3i2.3157.

Nugroho, B. D. A. (2015). Relationship between Sea Surface Temperature (SST) and Rainfall Distribution Pattern in South-Central Java, Indonesia. Indonesian Journal of Geography. 47(1). 20-25. https://doi.org/10.22146/ijg.6742.

Pradiko, I., Darlan, N. H., dan Siregar, H. H. (2016). Kajian Anomali Iklim terhadap Penurunan Produksi Kelapa Sawit di Sumatra Utara. Warta PPKS, 21(1). 7-18. ISSN 0853-2141.

Prasetyo, B., Irwandi, H., and Pusparini, N. (2018). Variable Topography-Based Rainfall Characteristic in North Sumatra. Jurnal Sains & Teknolgi Modifikasi Cuaca. 19(1). 11-20. https://doi.org/10.31172/jmg.v10i1.31.

Qian, J-H. (2019). Multi-scale Climate Processes and Rainfall Variability in Sumatra and Malay Peninsula associated with ENSO in boreal fall and winter. Int. J. of Clymatol. 40. 4171-4188. http://doi.org/10.1002/joc/6450.

Ruigar, H. and Gulian, S. (2015). Assessing the Correlation Between Climate Signals and Monthly Mean and Extreme Precipitation and Discharge of Golestan Darm Watershed. Eart Sci. Res. J. 19(1). 65-72. http://dx.doi.org/10.15446/esrj.v19n1.40996.

Salhi, A., Martin-Vide, J., Benhamrouche, A., Benabdelouahab, S., Himi, M., Benabdelouahab, T., and Ponsati, A. C. (2019). Rainfall distribution and trends of the daily precipitation concentration index in northern Morocco: a need for an adaptive environmental policy. SN Applied Sciences. 1:277. https://doi.org/10.1007/s42452-019-0290-1.

Saunders, K., Stephenson, A. G., Taylor, P. G., and Karoly, D. (2017). The spatial distribution of rainfall extremes and the influence of El Nino Southern Oscillation. Journal Weather and Climate Extremes. 18. 17-28. http://doi.org/10.1016/j.wace.2017.10.001.

Sekaranom, A. B., Nurjani, E., Harini, R., and Muttaqin, A. S. (2020). Simulation of Daily Rainfall Data using Articulated Weather Generator Model for Seasonal Prediction of ENSO-Affected Zones in Indonesia. Indonesian Journal of Geography. 52(2). 143-153. http://dx.doi.org/10.22146/ijg.50862.

Sinambela, W., Dani, T., Rusnadi, I. E., dan Nugroho, J. T. (2008). Pengaruh Aktivitas Matahari pada Variasi Curah Hujan di Indonesia. Jurnal Sains Dirgantara. 5(2). 149-168.

Suhaila, J. and Jemain, A. A. (2012). Spatial Analysis of Daily Rainfall Intensity and Concentration Index in Peninsular Malaysia. Theor. Appl. Climatol. 108. 235-245. http://doi.org/10.1007/s00704-011-0529-2.

Tukidi (2010). Karakter curah hujan di Indonesia. Jurnal Geografi. 7(2). 136-145. Department of Geography Universitas Negeri Semarang. https://doi.org/10/15294/jg.v7i2.84.

Yang, X., Xie, X., Liu, D. L., Ji, F., and Wang, L. (2015). Spatial Interpolation of Daily Rainfall Data for Local Climate Impact Assessment over Greater Sydney Region. Advances in Meteorology. 2015. 12 pages. https://doi.org/10.1155/2015/563629.

Yuggotomo, M.E. dan Ihwan, A. (2014). Pengaruh fenomena El Niño Southern Oscillation dan Dipole Mode terhadap curah hujan di Kabupaten Ketapang. POSITRON. IV(2). 35 – 39. http://dx.doi.org/10.26418/positron.v4i2.7563.

Zeinivand, H. (2015). Comparison of Interpolation Methods for Precipitation Fields Using the Physically Based and Spatially Distributed Model of River Runoff on the Example of the Gharesou Basin, Iran. Russian Meteorology and Hydrology. 40(7). 480-488. https://doi.org/10.3103/S1068373915070079.



DOI: https://doi.org/10.22146/ijg.56724

Article Metrics

Abstract views : 3496 | views : 2796

Refbacks

  • There are currently no refbacks.


Bookmark and Share


Copyright (c) 2020 Nuzul Hijri Darlan, Sigit Supadmo Arif, Putu Sudira, Bayu Dwi Apri Nugroho

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)

ISSN 2354-9114 (online), ISSN 0024-9521 (print)

Web Analytics IJG STATISTIC