Application of the distributed hydrology soil vegetation model to Redfish Creek, British Columbia: model evaluation using internal catchment data

Abstract

Abstract:The Distributed Hydrology Soil Vegetation Model is applied to the Redfish Creek catchment to investigate the suitability of this model for simulation of forested mountainous watersheds in interior British Columbia and other high-latitude and high-altitude areas. On-site meteorological data and GIS information on terrain parameters, forest cover, and soil cover are used to specify model input. A stepwise approach is taken in calibrating the model, in which snow accumulation and melt parameters for clear-cut and forested areas were optimized independent of runoff production parameters. The calibrated model performs well in reproducing year-to-year variability in the outflow hydrograph, including peak flows. In the subsequent model performance evaluation for simulation of catchment processes, emphasis is put on elevation and temporal differences in snow accumulation and melt, spatial patterns of snowline retreat, water table depth, and internal runoff generation, using internal catchment data as much as possible. Although the overall model performance based on these criteria is found to be good, some issues regarding the simulation of internal catchment processes remain. These issues are related to the distribution of meteorological variables over the catchment and a lack of information on spatial variability in soil properties and soil saturation patterns. Present data limitations for testing internal model accuracy serve to guide future data collection at Redfish Creek. This study also illustrates the challenges that need to be overcome before distributed physically based hydrologic models can be used for simulating catchments with fewer data resources.

A Model Approach for Estimating Colony Size, Trends, and Habitat Associations of Burrow-Nesting Seabirds

“…DHSVM has been recently modified to predict the hydrologic response of partially urbanized watersheds by altering the treatment of precipitation on impervious surfaces, adding water detention, and spatially varying the surface runoff depending on land cover (Cuo et al 2008. The model's output, which closely matches empirically observed trends in flux rates and volumes, illustrates important linkages between landscape pattern and hydrology, with more extreme, episodic flux rates and volumes in urbanizing, highly impervious landscapes (Bowling and Lettenmaier 2001;Lamarche and Lettenmaier 2001;Whitaker et al 2003;Cuo et al 2008.…”

“…DHSVM uses GIS-derived representations of elevation, soil type, soil thickness, vegetation, and meteorological data to simulate water and energy fluxes at and below the land surface. The model has been used to evaluate effects of forest management on land surface hydrologic response, especially flooding, of upland forested basins (e.g., Bowling and Lettenmaier 2001;Lamarche and Lettenmaier 2001;Whitaker et al 2003). The model represents the effects of topography on incident and reflected solar radiation, and on downslope redistribution of moisture in the saturated zone, which in turn controls both fast and slow runoff response.…”

Agricultural watershed modeling: a review for hydrology and soil erosion processes

“…Afterwards, other studies in USA have contributed for the consolidation of the model, highlighting Bowling and Lettenmaier (2001) and Doten et al (2006). After that, DHSVM has been applied in other countries, like Canada (Whitaker et al, 2003), northern Taiwan (Chu et al, 2010), Japan (Yoshitani et al, 2009) and Brazilian Amazon Forest (Cuartas et al, 2012). DHSVM was initially designed for mountainous regions and has been applied to different research purposes, such as:…”

Channel morphology and bed-load yield in fluvial, formerly-glaciated headwater streams of the Columbia Mountains, Canada

“…Both the 2006 and 2007 freshets included multiple sediment mobilizing peak flows. In particular, the structure of the 2007 hydrograph is regarded as typical of a spring freshet in the southern Columbia Mountains (i.e., Whitaker et al, 2003;Jordan, 2006). Maximum Q in 2006 was the largest recorded in the four study years and is estimated to be a 10-year flood based on the closest (50 km) long-term gauging site that displays similar physiographic characteristics and meteorology (Environment Canada Station 08NH016).…”