Hybrid state-space model and adjusting procedure based on Bayesian approaches for spatio-temporal rainfall disaggregation

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Suci Astutik, Nur Iriawan, Suhartono, Sutikno

2012 ICSSBE 2012 - Proceedings, 2012 International Conference on Statistics in Science, Business and Engineering: "Empowering Decision Making with Statistical Sciences" Conference paper Cited by 2

Abstract

Disaggregation is the transforming process from highlevel scale data into low-level which preserves the consistency of the high-level statistic characteristics. This process, considering the dependence between spatial and temporal, is known as the spatio-temporal disaggregation. In general, this method is divided into two stages, namely the data modeling and preserving of consistency the high level scale statistic characteristics. This study proposes a hybrid model that combines a state-space model and adjusting procedure to disaggregate spatio-temporal rainfall through Bayesian approach using WinBUGS. The results show that the generated hourly rainfall data are consistent with the observed daily rainfall data at some locations which have only the daily rainfall data in the watershed Sampean, Bondowoso, Indonesia. © 2012 IEEE.

Affiliations

Statistics Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia; Mathematics Department, Brawijaya University, Malang, Indonesia