Evaluation of four hydrological models for operational flood forecasting in a Canadian Prairie watershed

Unduche, Fisaha; Tolossa, Habtamu G.; Senbeta, Degefa; Zhu, Eric Y.

doi:10.1080/02626667.2018.1474219

Cited by 62 publications

(46 citation statements)

References 33 publications

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“…Despite the larger computational demand, implementation of TVSA can be useful in model calibration by identifying event-based hydrological processes. This is particularly important for event-based calibration useful for flood forecasting in cold regions dominated by snowmelt runoff [67,75]. Furthermore, the choice of error metric has significant influence on the rankings and selection of parameter sensitivity.…”

Section: Discussionmentioning

confidence: 99%

“…The runoff process in cold regions such as NCRB is governed by snowmelt during spring season, as the snowmelt alone accounts for more than 80% of annual local runoff in this region [66]. Hydrological models used for flood forecasting requires reliable simulation of high flows and runoff generated from snowmelt [67]. Therefore, it is essential to consider event based parameters contributing to high flows and snowmelt such as rivvel and fpsno parameters in model calibration.…”

Section: Time Variant Sensitivity Analysismentioning

confidence: 99%

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Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures

Bajracharya

Awoye

Stadnyk

et al. 2020

Water

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The complex terrain, seasonality, and cold region hydrology of the Nelson Churchill River Basin (NCRB) presents a formidable challenge for hydrological modeling, which complicates the calibration of model parameters. Seasonality leads to different hydrological processes dominating at different times of the year, which translates to time variant sensitivity in model parameters. In this study, Hydrological Predictions for the Environment model (HYPE) is set up in the NCRB to analyze the time variant sensitivity analysis (TVSA) of model parameters using a Global Sensitivity Analysis technique known as Variogram Analysis of Response Surfaces (VARS). TVSA can identify parameters that are highly influential in a short period but relatively uninfluential over the whole simulation period. TVSA is generally effective in identifying model’s sensitivity to event-based parameters related to cold region processes such as snowmelt and frozen soil. This can guide event-based calibration, useful for operational flood forecasting. In contrast to residual based metrics, flow signatures, specifically the slope of the mid-segment of the flow duration curve, allows VARS to detect the influential parameters throughout the timescale of analysis. The results are beneficial for the calibration process in complex and multi-dimensional models by targeting the informative parameters, which are associated with the cold region hydrological processes.

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Section: Discussionmentioning

confidence: 99%

Section: Time Variant Sensitivity Analysismentioning

confidence: 99%

Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures

Bajracharya

Awoye

Stadnyk

et al. 2020

Water

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“…Inflow into the reservoir is generated from three major upstream tributaries: the Whitesand River, the Shell Rivers and the main stream of the Assiniboine River. This Prairie watershed, which is known to have a complex hydrology is characterized by abundant potholes and wetlands, poorly interconnected streams and non-contributing areas, long and cold winter periods, deep-frozen soils and rapid infiltration, high spring snowmelt contribution to annual runoff, intense rainfall in spring and early summer, lower soil moisture and evaporation from summer to fall [1,39]. The basin's topography ranges from 250 m a.s.l.…”

Section: Study Areamentioning

confidence: 99%

“…For this study, a calibrated and operational WATFLOOD model was obtained from the Manitoba Infrastructure, Hydrological Forecasting Centre. The model has been used by the center to provide operational flood forecasting using real-time weather forecast data to issue short-and medium-range river forecasts in the Upper Assiniboine River basin and other nearby watersheds [39]. WATFLOOD is a Canadian Hydrological model specifically developed for flood forecasting and watershed simulation.…”

Section: Hydrological Modelsmentioning

confidence: 99%

“…Abaza et al [32], compared currently available Canadian meteorological forecasts and concluded that streamflow forecasting fed by Regional ensemble prediction systems (EPS) provided higher reliability than the Global EPS followed by their deterministic counterparts, as also supported by Fan et al [30]. The use of multiple models with the global, regional, and local ensemble and deterministic inputs has also been implemented in several operational flood forecasting centers across the globe [33][34][35][36][37][38][39].The main challenge in getting accurate and reliable short-and medium-range flood forecasts in large complex watersheds arises from the type of hydrological models, and the quality of weather forecast inputs applied. The choice of the models to be implemented for flood and streamflow forecasting depends on the intended purpose, the type of forecast inputs, and the complexity and scale of the study area [40].…”

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confidence: 94%

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Identification of Hydrological Models for Enhanced Ensemble Reservoir Inflow Forecasting in a Large Complex Prairie Watershed

Awol

Coulibaly

Tsanis

et al. 2019

Water

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Accurate and reliable flow forecasting in complex Canadian prairie watersheds has been one of the major challenges faced by hydrologists. In an attempt to improve the accuracy and reliability of a reservoir inflow forecast, this study investigates structurally different hydrological models along with ensemble precipitation forecasts to identify the most skillful and reliable model. The key goal is to assess whether short-and medium-range ensemble flood forecasting in large complex basins can be accurately achieved by simple conceptual lumped models (e.g., SACSMA with SNOW17 and MACHBV with SNOW17) or it requires a medium level distributed model (e.g., WATFLOOD) or an advanced macroscale land-surface based model (VIC coupled with routing module (RVIC)). Eleven (11)-member precipitation forecasts from second-generation Global Ensemble Forecast System reforecast (GEFSv2) were used as inputs. Each of the ensemble members was bias-corrected by Empirical Quantile Mapping method using the Canadian Precipitation Analysis (CaPA) as a training/verification dataset. Forecast evaluation is performed for 1-day up to 8-days forecast lead times in a 6-month hindcast period. Results indicate that bias-correcting precipitation forecasts using verifying datasets (such as CaPA) for a training period of at least two years before the forecast time, produces skillful ensemble hydrological forecasts. A comparison of models in forecast mode shows that the two lumped models (SACSMA and MACHBV) can provide better overall forecast performance than the benchmark WATFLOOD and the macroscale Variable Infiltration Capacity (VIC) model. However, for shorter lead-times, particularly up to day 3, the benchmark distributed model provides competitive reliability, as compared to the lumped models. In general, the SACSMA model provided better forecast quality, reliability and differentiation skill than other considered models at all lead times.2 of 27 soil moisture, and evaporation from summer to fall [1]. Relevant methodologies were proposed to assess several aspects of the hydrological cycle such as snowpack, spring melt, soil moisture, rainfall frequency, and evaporation, in the Canadian Prairie regions [2][3][4][5]. The effect of climate, land use, and ecosystem change on the hydrological processes of cold and wetland regions were also studied [6][7][8]. Even though some efforts were made to formulate the realistic representation of wetland processes in hydrological models [9][10][11][12][13], challenges of hydrological forecasting and flood predictions in such complex watersheds remain at large.Several important works have already been performed for enhancing flood prediction in several watersheds: for example, using single or multiple hydrological models [14-22], or feeding ensemble numerical weather products to models [23][24][25][26][27][28][29]. Velázquez et al. [18], for example, analyzed 16 lumped hydrological models with 50-member ensemble weather inputs. They detected that the multi-model approach of a grand member ensemble provided more...

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Hydrologic models coupled with 2D hydrodynamic model for high-resolution urban flood simulation

2021

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Evaluation of four hydrological models for operational flood forecasting in a Canadian Prairie watershed

Cited by 62 publications

References 33 publications

Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures

Time Variant Sensitivity Analysis of Hydrological Model Parameters in a Cold Region Using Flow Signatures

Identification of Hydrological Models for Enhanced Ensemble Reservoir Inflow Forecasting in a Large Complex Prairie Watershed

Hydrologic models coupled with 2D hydrodynamic model for high-resolution urban flood simulation

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