000055845 001__ 55845
000055845 005__ 20180127191221.0
000055845 02470 $$2DAR$$a7351
000055845 02470 $$2ISI$$a000232811300014
000055845 037__ $$aARTICLE 000055845 245__$$aStatistical performances of various deterministic and stochastic models for rainfall series disaggregation.
000055845 260__ $$c2005 000055845 269__$$a2005
000055845 336__ $$aJournal Articles 000055845 520__$$aThis paper compares the performance of seven disaggregation models, based on various approaches and/or concepts, for the generation of 10mn time step rainfall series from hourly rainfall series. The so-called constant disaggregation model and a linear model based on the external temporal pattern of rainfall are first considered. The other models are stochastic: the first ones are based on a given probability density function applying for the 10mn rainfall amounts of the hour to disaggregate. This probability density function is either uniform or derived from the external temporal pattern of rainfall. The other stochastic models are scaling models using canonical or microcanonical multiplicative random cascades. The comparison of the models is based on their ability to reproduce some important statistical characteristics of the observed time series: variance, skewness coefficient, wet/dry properties of 10mn rainfall amounts; rainfall amounts quantiles for different return periods; autocorrelation of 10mn rainfall amounts. A continuous hydrological simulation is next applied to produce for each generated rainfall series a continuous discharge series used afterwards for a retention design. The ability of the different disaggregation models to produce rainfall time series resulting in the same retention design than the one obtained with the observed rainfall series is finally analysed. Deterministic models as well as simpler stochastic models have rather bad performances when compared to the others. Because it is non-conservative, the model based on a microcanonical random cascade performs also very poorly. It significantly overestimates all studied statistics. Models based on microcanonical random cascades achieve the best performance. They perform reasonably well for the reproduction of rainfall statistics and almost perfectly for the reproduction of runoff and storage design variables. Results finally highlight the interest of including in the disaggregation scheme information related to the external temporal pattern of rainfall
000055845 6531_ $$arainfall disaggregation 000055845 6531_$$atemporal pattern
000055845 6531_ $$arainfall series 000055845 6531_$$aretention design
000055845 6531_ $$acontinuous hydrologic simulation 000055845 700__$$0240768$$aHingray, B.$$g130359
000055845 700__ $$aBen Haha, M. 000055845 773__$$j77$$q152-175$$tAtm. Res.
000055845 909C0 $$0252387$$pHYDRAM
000055845 909CO $$ooai:infoscience.tind.io:55845$$particle
000055845 937__ $$aHYDRAM-ARTICLE-2005-009 000055845 973__$$aEPFL$$rREVIEWED$$sPUBLISHED
000055845 980__ aARTICLE