Rohmah, Nabila Asyiqotur (2018) Estimasi Curah Hujan Berdasarkan Model TFR Menggunakan Metode Ensemble Kalman Filter. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Fluktuasi curah hujan dapat mempengaruhi kondisi lingkungan yang berhubungan dengan aktivitas ekonomi dan kesehatan masyarakat. Peningkatan temperatur rata-rata global dipengaruhi oleh kenaikan CO2 di atmosfer, sehingga terjadi perubahan iklim. Hutan sebagai penampung karbon terbesar membantu menjaga daur karbon dan mengurangi perubahan iklim. Perubahan iklim yang menyebabkan penyimpangan intensitas hujan dapat mempengaruhi perekonomian suatu daerah, bahkan negara. Hal ini mendorong penelitian mengenai curah hujan yang berkaitan dengan luas hutan dan temperatur. Pada penelitian ini model matematika yang digunakan adalah model TFR (temperature, forest cover, and rainfall). Terlebih dahulu model dipelajari kestabilan dan keteramatannya, kemudian model didiskritkan. Setelah itu dilakukan estimasi terhadap model menggunakan metode Ensemble Kalman Filter (EnKF). Jumlah ensemble yang digunakan pada penelitian ini adalah 100, 200, dan 300 ensemble. Hasil menunjukkan bahwa semakin banyak variabel yang digunakan sebagai variabel pengukuran, hasil estimasi terhadap curah hujan akan semakin akurat. Akurasi hasil simulasi dapat dilihat dari nilai RMSE state variable tersebut dan persentase nilai RMSE-nya terhadap nilai real. =========== Fluctuations in rainfall may influence other environmental conditions that correlated with economic activity and public health. The increasing of global average temperature is influenced by the increasing of CO2 in the atmosphere, causing climate change. The forest as carbon sinks that help to keep the carbon cycle and climate change mitigation. Climate change is causing rainfall intensity deviations can affect the economy of a region, and even a country. It encourages research on rainfall associated with an area of forest. In this study the mathematics model that used is a model which describes the rainfall, global temperatures, forest cover, and rainfall change called the TFR (temperature, forest cover, and rainfall) model. At the beginning, the stability of equibrium points is studied, then model will be discritized. Next step the model will be estimated by the method of Ensemble Kalman Filter (EnKF). The numbers of ensembles used for this study are 100, 200, and 300 ensembles. The result shows that the more state variable used as measured variable, the better estimation of rainfall result will do. The accurateness of simulation result can be examined from RMSE value of state variable and its RMSE value percentage to its real value.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTMa 518.1 Roh e |
| Uncontrolled Keywords: | Ensemble Kalman Filter; Model TFR; Estimasi Curah Hujan; rainfall estimation; TFR model; rainfall estimation; TFR model |
| Subjects: | Q Science > QA Mathematics > QA402.3 Kalman filtering. |
| Divisions: | Faculty of Mathematics, Computation, and Data Science > Mathematics > 44101-(S2) Master Thesis |
| Depositing User: | Rohmah Nabila Asyiqotur |
| Date Deposited: | 29 Jan 2018 04:50 |
| Last Modified: | 18 Sep 2020 07:01 |
| URI: | http://repository.its.ac.id/id/eprint/50875 |
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