Temporal Disaggregation of Daily Precipitation Data in a Changing Climate
Models for spatially interpolating hourly precipitation data and temporally disaggregating daily precipitation to hourly data are developed for application to multisite scenarios at the watershed scale. The intent is to create models to produce data which are valid input for a hydrologic rainfall-runoff model, from daily data produced by a stochastic weather generator. These models will be used to determine the potential effects of climate change on local precipitation events. A case study is presented applying these models to the Upper Thames River basin in Ontario, Canada; however, these models are generic and applicable to any watershed with few changes. <br /><br /> Some hourly precipitation data were required to calibrate the temporal disaggregation model. Spatial interpolation of this hourly precipitation data was required before temporal disaggregation could be completed. Spatial interpolation methods were investigated and an inverse distance method was applied to the data. Analysis of the output from this model confirms that isotropy is a valid assumption for this application and illustrates that the model is robust. The results for this model show that further study is required for accurate spatial interpolation of hourly precipitation data at the watershed scale. <br /><br /> An improved method of fragments is used to perform temporal disaggregation on daily precipitation data. A parsimonious approach to multisite fragment calculation is introduced within this model as well as other improvements upon the methods presented in the literature. The output from this model clearly indicates that spatial and temporal variations are maintained throughout the disaggregation process. Analysis of the results indicates that the model creates plausible precipitation events. <br /><br /> The models presented here were run for multiple climate scenarios to determine which GCM scenario has the most potential to affect precipitation. Discussion on the potential impacts of climate change on the region of study is provided. Selected events are examined in detail to give a representation of extreme precipitation events which may be experienced in the study area due to climate change.