Model-Model Pembangkitan Data Sintetis Untuk Curah Hujan Harian Di Wilayah Brantas Tengah
Abstract
This research is for finding the suitable the synthetic data generating model for daily rainfall in the region of Middle Brantas River Basin in the East Java Province. There are 7 models being considered, 4 models for single-site generation, (1) the two-part, model group, (2) the transition probability matrix model group, (3) the resampling model group, and (4) the time series model group, and 3 models for multisite generation, (5) the conditional, model group, (6) the extension of single site Markov chain model group, and (7) the random cascade model group. All of the time-series produced by the daily rainfall synthetic data generation are then tested statistically. The results show that statistically the differences between the historical time series and the synthetically time series are not too significant. It turn out that the multisite model have produced better synthetic time series compared to those which have been produced by the single-site models.
Keywords: generating model, synthetic data, daily rainfall.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2013 Widandi Soetopo, Lily Montarcih Limantara, Rini Wahyu Sayekti, Endang Purwati, Dian Chandrasasi, Muhammad Ilham, Agung Rahmadi

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).