Johns, Newfoundland, Canada Author links open overlay panel Dayal Buddika Wijayarathne a Paulin Coulibaly b Show more Share Cite Get rights and content Under a Creative Commons license open access Highlights Five hydrological models were set-up, calibrated and validated for comparison.The best hydrological model(s) were chosen by comparison of performance criteria.
Hec Hms License Open AccessDeterministic hydrologic forecasts were performed using three selected models. Recommendations for enhanced flood forecasting were provided. Study focus This study investigates five hydrological models to identify adequate model(s) for operational flood forecasting at Waterford River watershed. These models included three lumped conceptual models (SAC-SMA: Sacramento Soil Moisture Accounting, GR4J: modle du Gnie Rural 4 paramtres Journalier, and MAC-HBV: McMaster University Hydrologiska Byrns Vattenbalansavdelning), a semi-distributed model (HEC-HMS: Hydrologic Engineering Centers Hydrologic Modeling System) and a fully distributed physically-based model (WATFLOOD: University of Waterloo Flood Forecasting System). The best model(s) were chosen by comparison of performance criteria. ![]() New hydrological insights for the region All five models are capable of simulating streamflow reasonably well in both calibration and validation periods. The SAC-SMA and GR4J models perform equally well and perform better than the other three models for all low, medium, and peak flows. The SAC-SMA and GR4J models generally perform better for peak flows, followed by HEC-HMS. Streamflow forecast experiment using deterministic weather prediction shows that SAC-SMA, GR4J, and HEC-HMS models perform well for up to 13 days ahead forecasts and are recommended for operational use. However, due to the good performance of all five models, an ensemble forecasting using continuous, multiple hydrological models is also recommended. Previous article in issue Next article in issue Keywords Waterford River watershed Flood forecasting Hydrological models Deterministic forecast Recommended articles Citing articles (0) View Abstract 2019 The Authors. Published by Elsevier B.V. Recommended articles No articles found. Citing articles Article Metrics View article metrics About ScienceDirect Remote access Shopping cart Advertise Contact and support Terms and conditions Privacy policy We use cookies to help provide and enhance our service and tailor content and ads. Copyright 2020 Elsevier B.V. ScienceDirect is a registered trademark of Elsevier B.V.
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