Multivariate rainfall disaggregation at a fine timescale

D. Koutsoyiannis, C. Onof, and H. S. Wheater, Multivariate rainfall disaggregation at a fine timescale, Water Resources Research, 39 (7), 1173, doi:10.1029/2002WR001600, 2003.



A methodology for spatial-temporal disaggregation of rainfall is proposed. The methodology involves the combination of several univariate and multivariate rainfall models operating at different time scales, in a disaggregation framework that can appropriately modify outputs of finer time scale models so as to become consistent with given coarser time scale series. Potential hydrologic applications include enhancement of historical data series and generation of simulated data series. Specifically, the methodology can be applied to derive spatially consistent hourly rainfall series in raingages where only daily data are available. In addition, in a simulation framework, the methodology provides a way to take simulations of multivariate daily rainfall (incorporating spatial and temporal non-stationarity) and generate multivariate fields at fine temporal resolution. The methodology is tested via a case study dealing with the disaggregation of daily historical data of five raingages into hourly series. Comparisons show that the methodology results in good preservation of important properties of the hourly rainfall process such as marginal moments, temporal and spatial correlations, and proportions and lengths of dry intervals, and in addition, a good reproduction of the actual hyetographs.

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Our works referenced by this work:

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Our works that reference this work:

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8. F. Lombardo, E. Volpi, D. Koutsoyiannis, and F. Serinaldi, A theoretically consistent stochastic cascade for temporal disaggregation of intermittent rainfall, Water Resources Research, 53 (6), 4586–4605, doi:10.1002/2017WR020529, 2017.
9. P. Kossieris, C. Makropoulos, C. Onof, and D. Koutsoyiannis, A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures, Journal of Hydrology, 556, 980–992, doi:10.1016/j.jhydrol.2016.07.015, 2018.
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12. I. Tsoukalas, A. Efstratiadis, and C. Makropoulos, Building a puzzle to solve a riddle: A multi-scale disaggregation approach for multivariate stochastic processes with any marginal distribution and correlation structure, Journal of Hydrology, 575, 354–380, doi:10.1016/j.jhydrol.2019.05.017, 2019.
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Tagged under: Stochastic disaggregation, Rainfall models, Stochastics