Pemodelan Sistem Dinamik untuk Prediksi Intensitas Hujan Harian di Kota Malang
DOI:
https://doi.org/10.32815/jitika.v12i2.272Keywords:
Modelling, System Dynamics, Rain Intensity, Malang CityAbstract
Malang city located in the highlands that is not spared from the flood disaster which the number of events is increasing every year. This is due to many factors, such as the high intensity of daily rainfall coupled with less optimal infrastructure development. In this case, to mitigate the number of flood events, an easy first step is to predict the daily rain intensity. So that the prediction result can be used by the stakeholders to mitigate flood incident in Malang City in the following years. This study aims to create a simple model in predicting rain intensity over a three year period of 2018-2020. Modeling and simulation are done by using a system dynamics approach that can model the system with complex dynamics. The developed model of rain intensity integrates influencing factors such as humidity and temperature. The rainfall intensity model has validated with the error of E1 value is 3.86% and E2 is 4.13% and with RMSE result indicates the number of 8.4452.
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References
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Adhi, A. (2014, Agustus 12). Hasil Survei, Kota Malang Nyaman tetapi Sering Banjir. Surya Online. Diambil dari http://surabaya.tribunnews.com/2014/08/12/hasil-survei-kota-malang-nyaman-tetapi-sering-banjir
Allan, R. P., Lavers, D. A., & Champion, A. J. (2016). Diagnosing links between atmospheric moisture and extreme daily precipitation over the UK. International Journal of Climatology, 36(9), 3191–3206. https://doi.org/10.1002/joc.4547
Barlas, Y. (1996). Formal aspects of model validity and validation in system dynamics. System dynamics review, 12(3), 183–210.
BPS Kota Malang. (2016). Kota Malang dalam Angka 2016 (Malang Municipality in Figures 2016). Malang: CV. Bima Media Mandiri.
Buishand, T. A., & Brandsma, T. (1999). Dependence of precipitation on temperature at Florence and Livorno (Italy). Climate Research, 12(1), 53–63. https://doi.org/10.3354/cr012053
Chang, H.-K., Tan, Y.-C., Lai, J.-S., Pan, T.-Y., Liu, T.-M., & Tung, C.-P. (2013). Improvement of a drainage system for flood management with assessment of the potential effects of climate change. Hydrological Sciences Journal, 58(8), 1581–1597. https://doi.org/10.1080/02626667.2013.836276
Cong, R. G., & Brady, M. (2012). The interdependence between rainfall and temperature: Copula analyses. The Scientific World Journal, 2012(3). https://doi.org/10.1100/2012/405675
Cooley, A., & Chang, H. (2017). Precipitation Intensity Trend Detection using Hourly and Daily Observations in Portland, Oregon. Climate, 5(1), 10. https://doi.org/10.3390/cli5010010
Dube, A., Ashrit, R., Ashish, A., Sharma, K., Iyengar, G. R., Rajagopal, E. N., & Basu, S. (2014). Forecasting the heavy rainfall during Himalayan flooding—June 2013. Weather and Climate Extremes, 4, 22–34. https://doi.org/https://doi.org/10.1016/j.wace.2014.03.004
Fadli, M. (2012). Prediksi (Nowcasting) Curah Hujan Pagi dan Siang Hari di Wilayah Jakarta dengan Model ANFIS (Prediction (Nowcasting) Rainfall Morning and Daylight in Jakarta Region with ANFIS Model). Megasains, 3(2), 61–76.
Frei, C., Schär, C., Lüthi, D., & Davies, H. C. (1998). Heavy precipitation processes in a warmer climate. Geophysical Research Letters, 25(9), 1431–1434. https://doi.org/10.1029/98GL51099
Hayat. (2014). Implementasi Kebijakan Penataan Ruang Terbuka Hijau. Jurnal Ilmu Administrasi Negara, 13(1), 43–56. Diambil dari http://ejournal.unri.ac.id/index.php/JIANA/article/view/2366
Hiteshri, S., Subimal, G., & Subhankar, K. (2017). Improving Global Forecast System of extreme precipitation events with regional statistical model: Application of quantile‐based probabilistic forecasts. Journal of Geophysical Research: Atmospheres, 122(3), 1617–1634. https://doi.org/10.1002/2016JD025489
Khedhiri, S. (2015). Artificial neural network for forecasting rainfall pattern in Prince Edward Island, Canada. International Journal of Environmental Studies, 72(2), 331–340. https://doi.org/10.1080/00207233.2014.961311
Khidir, A. M., Adlan, H. H. A., & Basheir, I. A. (2013). Neural Networks forecasting architectures for rainfall in the rain-fed Sectors in Sudan. In International Conference on Computing, Electrical and Electronics Engineering (ICCEEE) (hal. 700–707). Khartoum, Sudan.
Kigawa, S. (2014). Techniques of Precipitation Analysis and Prediction for High-resolution Precipitation Nowcasts. The Japan Meteorological Agency, 1–15. Diambil dari https://www.jma.go.jp/jma/en/Activities/Techniques_of_Precipitation_Analysis_and_Prediction_developed_for_HRPNs.pdf
Lepore, C., Veneziano, D., & Molini, A. (2015). Temperature and CAPE dependence of rainfall extremes in the eastern United States. Geophysical Research Letters, 42(1), 74–83. https://doi.org/10.1002/2014GL062247
Lyneis, J. M. (2000). System dynamics for market forecasting and structural analysis. System Dynamics Review, 16(1), 3–25.
Morin, E., Krajewski, W. F., Goodrich, D. C., Gao, X., & Sorooshian, S. (2003). Estimating Rainfall Intensities from Weather Radar Data: The Scale-Dependency Problem. Journal of Hydrometeorology, 4(5), 782–797. https://doi.org/10.1175/1525-7541(2003)004<0782:ERIFWR>2.0.CO;2
Pabalik, I., Ihsan, N., & Arsyad, M. (2015). Analisis Fenomena Perubahan Iklim dan Karakteristik Curah Hujan Ekstrim di Kota Makassar. Jurnal Sains dan Pendidikan Fisika (JSPF), 11(1), 88–92.
Pielke, R. A., Bluestein, H. B., Enfield, D. B., Wells, N. C., Cenedese, C., Davies, R., … Loewe, F. P. (2018). Climate - Meteorology. Diambil 26 Juni 2018, dari https://www.britannica.com/science/climate-meteorology/Atmospheric-humidity-and-precipitation
Rajasekaram, V., McBean, G. A., & Simonovic, S. P. (2010). A systems dynamic modelling approach to assessing elements of a weather forecasting system. Atmosphere - Ocean, 48(1), 1–9. https://doi.org/10.3137/AO931.2010
Richardson, G. P. (2013). System Dynamics. In S. I. Gass & M. C. Fu (Ed.), Encyclopedia of Operations Research and Management Science (3 ed., hal. 1519–1521). New York: Springer. https://doi.org/10.1007/978-1-4419-1153-7
Sasongko, D. (2017, Oktober 2). Sektor Pariwisata Berperan Penting Mendongkrak Sektor Ekonomi. Merdeka.com. Diambil dari https://malang.merdeka.com/kabar-malang/sektor-pariwisata-berperan-penting-mendongkrak-sektor-ekonomi-171002f.html
Schumacher, R. S. (2016). Heavy Rainfall and Flash Flooding (Vol. 1). New York: Oxford University Press. https://doi.org/10.1093/acrefore/9780199389407.013.132
Tekeli, A. E. (2017). Exploring Jeddah floods by tropical rainfall measuring mission analysis. Water (Switzerland), 9(8), 612. https://doi.org/10.3390/w9080612
Trenberth, K. E. (2005). The Impact of Climate Change and Variability on Heavy Precipitation, Floods, and Droughts. Encyclopedia of Hydrological Sciences, 1–11. https://doi.org/10.1002/0470848944.hsa211
Wahyuni, I., Adipraja, P. F. E., & Mahmudy, W. F. (2018). Determining Growing Season of Potatoes Based on Rainfall Prediction Results Using System Dynamics. Indonesian Journal of Electrical Engineering and Informatics (IJEEI), 6(2).
Zhou, Q., Leng, G., & Huang, M. (2018). Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations. Hydrology and Earth System Sciences, 22(1), 305–316. https://doi.org/10.5194/hess-22-305-2018
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Published
23-10-2018
How to Cite
Adipraja, P. F. E., & Sulistyo, D. A. (2018). Pemodelan Sistem Dinamik untuk Prediksi Intensitas Hujan Harian di Kota Malang. Jurnal Ilmiah Teknologi Informasi Asia, 12(2), 137–146. https://doi.org/10.32815/jitika.v12i2.272
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