| description abstract | Spatially distributed numerical hydrologic models are useful tools for examining the long-term impact of forest harvesting in mountainous basins on streamflow regime properties. Such models require the input of long-duration subdaily meteorological time series data that are not routinely available in mountainous headwater basins. A relatively simple method is presented for extending short-duration records by using a combined stochastic?empirical technique, and the approach is demonstrated using the Redfish Creek in British Columbia, Canada. Synthetic hourly precipitation, precipitation gradient, air temperature, temperature lapse rate, wind speed, relative humidity, solar beam and diffuse irradiance, and downward longwave irradiance for two station locations are generated in a three-step process: 1) hourly precipitation is generated using a clustered rectangular pulse point process, 2) daily meteorology is generated using a multivariate first-order autoregressive process, and 3) final hourly nonprecipitation meteorology is derived by disaggregating daily meteorology. Seasonal and annual precipitation means are reproduced to within 10% of observed. The skill of the generated nonprecipitation meteorological data to reproduce the statistical properties and diurnal structure of the observed data ranged from good to poor, with bias ranging from 0% to 500% and efficiency ranging from ?76 to 0.93. Despite discrepancies in the generated meteorology, a comparison of annual hydrologic fluxes, spatial distribution of winter snow accumulation, flow duration, and average hydrographs, simulated using the Distributed Hydrology Soil Vegetation Model (DHSVM), indicates that model skill shows negligible response to the use of the generated subdaily meteorology. | |
