scholarly journals Evaluating uncertainties in modelling the snow hydrology of the Fraser River Basin, British Columbia, Canada

2016 ◽  
Author(s):  
Siraj Ul Islam ◽  
Stephen J. Déry
Keyword(s):  
British Columbia ◽  
River Basin ◽  
Air Temperature ◽  
Rocky Mountains ◽  
Climate Impacts ◽  
Model Parameters ◽  
Fraser River ◽  
Hydrological Response ◽  
Snow Hydrology ◽  
Calibration Process

Abstract. This study evaluates predictive uncertainties in the snow hydrology of the Fraser River Basin (FRB) of British Columbia (BC), Canada, using the Variable Infiltration Capacity (VIC) model forced with several high-resolution gridded climate datasets. These datasets include the Canadian Precipitation Analysis and the thin-plate smoothing splines (ANUSPLIN), the North American Regional Reanalysis (NARR), University of Washington (UW) and Pacific Climate Impacts Consortium (PCIC) gridded products. Uncertainties are evaluated at different stages of the VIC implementation starting with the driving datasets, optimization of model parameters, and model calibration during cool and warm phases of the Pacific Decadal Oscillation (PDO). The inter-comparison of the forcing datasets (precipitation and air temperature) and their VIC simulations (snow water equivalent (SWE) and runoff) reveal widespread differences over the FRB especially in mountainous regions. The ANUSPLIN precipitation shows a considerable dry bias in the Rocky Mountains whereas the NARR winter air temperature is 2 °C warmer than the other datasets over most of the FRB. In the VIC simulations, the elevation-dependent changes in the maximum SWE (maxSWE) are more prominent at higher elevations of the Rocky Mountains where PCIC-VIC simulation accumulates too much SWE and ANUSPLIN-VIC yields an underestimation. Additionally, at each elevation range, the day of maxSWE varies 10 to 20 days between the VIC simulations. The snow melting season begins early in NARR-VIC simulation whereas PCIC-VIC simulation delays the melting indicating seasonal uncertainty in SWE simulations. When compared with the observed runoff for the Fraser River main stem at Hope, BC, the ANUSPLIN-VIC simulation shows considerable underestimation of runoff throughout the water year owing to reduced precipitation in the ANUSPLIN forcing dataset. The NARR-VIC simulation yields more winter and spring runoff and earlier decline of flows in summer due to a nearly 15-day earlier onset of the FRB springtime snowmelt. Analysis of the parametric uncertainty in the VIC calibration process shows that the choice of the initial parameter range plays a crucial role in defining the model hydrological response for the FRB. Furthermore, the VIC calibration process is biased toward cool and warm phases of the PDO and the choice of proper calibration and validation time periods is important for the experimental setup. Overall the VIC hydrological response is prominently influenced by the uncertainties involved in the forcing datasets rather than those in its parameters optimization and experimental setups.

scholarly journals Evaluating uncertainties in modelling the snow hydrology of the Fraser River Basin, British Columbia, Canada

2017 ◽  
Vol 21 (3) ◽  
pp. 1827-1847 ◽  
Author(s):  
Siraj Ul Islam ◽  
Stephen J. Déry
Keyword(s):  
British Columbia ◽  
River Basin ◽  
Air Temperature ◽  
Rocky Mountains ◽  
Climate Impacts ◽  
Model Parameters ◽  
Fraser River ◽  
Hydrological Response ◽  
Snow Hydrology ◽  
Calibration Process

Abstract. This study evaluates predictive uncertainties in the snow hydrology of the Fraser River Basin (FRB) of British Columbia (BC), Canada, using the Variable Infiltration Capacity (VIC) model forced with several high-resolution gridded climate datasets. These datasets include the Canadian Precipitation Analysis and the thin-plate smoothing splines (ANUSPLIN), North American Regional Reanalysis (NARR), University of Washington (UW) and Pacific Climate Impacts Consortium (PCIC) gridded products. Uncertainties are evaluated at different stages of the VIC implementation, starting with the driving datasets, optimization of model parameters, and model calibration during cool and warm phases of the Pacific Decadal Oscillation (PDO). The inter-comparison of the forcing datasets (precipitation and air temperature) and their VIC simulations (snow water equivalent – SWE – and runoff) reveals widespread differences over the FRB, especially in mountainous regions. The ANUSPLIN precipitation shows a considerable dry bias in the Rocky Mountains, whereas the NARR winter air temperature is 2 °C warmer than the other datasets over most of the FRB. In the VIC simulations, the elevation-dependent changes in the maximum SWE (maxSWE) are more prominent at higher elevations of the Rocky Mountains, where the PCIC-VIC simulation accumulates too much SWE and ANUSPLIN-VIC yields an underestimation. Additionally, at each elevation range, the day of maxSWE varies from 10 to 20 days between the VIC simulations. The snow melting season begins early in the NARR-VIC simulation, whereas the PCIC-VIC simulation delays the melting, indicating seasonal uncertainty in SWE simulations. When compared with the observed runoff for the Fraser River main stem at Hope, BC, the ANUSPLIN-VIC simulation shows considerable underestimation of runoff throughout the water year owing to reduced precipitation in the ANUSPLIN forcing dataset. The NARR-VIC simulation yields more winter and spring runoff and earlier decline of flows in summer due to a nearly 15-day earlier onset of the FRB springtime snowmelt. Analysis of the parametric uncertainty in the VIC calibration process shows that the choice of the initial parameter range plays a crucial role in defining the model hydrological response for the FRB. Furthermore, the VIC calibration process is biased toward cool and warm phases of the PDO and the choice of proper calibration and validation time periods is important for the experimental setup. Overall the VIC hydrological response is prominently influenced by the uncertainties involved in the forcing datasets rather than those in its parameter optimization and experimental setups.

Estimating extreme avalanche runout for the Columbia Mountains and Fernie area Rocky Mountains of British Columbia, Canada

2012 ◽  
Vol 49 (11) ◽  
pp. 1309-1318 ◽  
Author(s):  
Katherine S. Johnston ◽  
Bruce Jamieson ◽  
Alan Jones
Keyword(s):  
British Columbia ◽  
Rocky Mountains ◽  
Statistical Models ◽  
Dynamic Models ◽  
Path Model ◽  
Model Parameters ◽  
Mountain Range ◽  
Coast Mountains ◽  
Runout Distance ◽  
Columbia Mountains

Extreme snow avalanche runout is typically estimated using a combination of historical and vegetation records as well as statistical and dynamic models. The two classes of statistical models (α–β and runout ratio) are based on estimating runout distance past the β-point, which is typically defined as the point where the avalanche slope incline first decreases to 10°. The parameters for these models vary from mountain range to mountain range. In Canada, α–β and runout ratio parameters have been published for the combined Rocky and Purcell Mountains and for the British Columbia Coast Mountains. Despite active development, no suitable tall avalanche path model parameters have been published for the Columbia Mountains or for the Lizard Range area around Fernie, B.C. Using a dataset of 65 avalanche paths, statistical model parameters have been derived for these regions.

scholarly journals Examining controls on peak annual streamflow and floods in the Fraser River Basin of British Columbia

2017 ◽  
Author(s):  
Charles L. Curry ◽  
Francis W. Zwiers
Keyword(s):  
British Columbia ◽  
Soil Moisture ◽  
River Basin ◽  
Snow Water Equivalent ◽  
Southern Oscillation ◽  
Snow Accumulation ◽  
Fraser River ◽  
Annual Maximum ◽  
Daily Streamflow ◽  
Annual Peak

Abstract. The Fraser River basin (FRB) of British Columbia is one of the largest and most important watersheds in Western North America, and is home to a rich diversity of biological species and economic assets that depend implicitly upon its extensive riverine habitats. The hydrology of the FRB is dominated by snow accumulation and melt processes, leading to a prominent annual peak streamflow invariably occurring in June–July. However, while annual peak daily streamflow (APF) during the spring freshet in the FRB is historically well correlated with basin-averaged, April 1 snow water equivalent (SWE), there are numerous occurrences of anomalously large APF in below- or near-normal SWE years, some of which have resulted in damaging floods in the region. An imperfect understanding of which other climatic factors contribute to these anomalously large APFs hinders robust projections of their magnitude and frequency. We employ the Variable Infiltration Capacity (VIC) process-based hydrological model driven by gridded observations to investigate the key controlling factors of anomalous APF events in the FRB and four of its subbasins that contribute more than 70 % of the annual flow at Fraser-Hope. The relative influence of a set of predictors characterizing the interannual variability of rainfall, snowfall, snowpack (characterized by the annual maximum value, SWEmax), soil moisture and temperature on simulated APF at Hope (the main outlet of the FRB) and at the subbasin outlets is examined within a regression framework. The influence of large-scale climate modes of variability (the Pacific Decadal Oscillation (PDO) and the El Niño-Southern Oscillation (ENSO)) on APF magnitude is also assessed, and placed in context with these more localized controls. The results indicate that next to SWEmax (which strongly controls the annual maximum of soil moisture), the snowmelt rate, the ENSO and PDO indices, and rate of warming subsequent to the date of SWEmax are the most influential predictors of APF magnitude in the FRB and its subbasins. The identification of these controls on annual peak flows in the region may be of use in the context of seasonal prediction or future projected streamflow behaviour.

scholarly journals Mathematical Model of Hydrological Processes METQ98 and its Applications

1999 ◽  
Vol 30 (2) ◽  
pp. 109-128 ◽  
Author(s):  
A. Ziverts ◽  
I. Jauja
Keyword(s):  
Mathematical Model ◽  
River Basin ◽  
Input Data ◽  
Meteorological Data ◽  
Vapour Pressure Deficit ◽  
Model Parameters ◽  
Hydrological Response ◽  
Runoff Simulation ◽  
Mean Values ◽  
The Mathematical Model

The mathematical model METQ98 for runoff simulation is described. The METQ98 is developed from the model METUL (Krams and Ziverts 1993). Input data for the model are daily mean values of air temperature, precipitation and vapour pressure deficit. The spatial variability of surface processes is represented by dividing the river basin into hydrological response units (HRUs) depending on the land cover. The analysis of the model parameters is based on hydrological and meteorological data of the Vienziemite Brook basin. Also the influence of drainage on the model parameters is analysed. The results of application of the model to the Daugava River basin are presented.

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