Improving Hydrodynamic Modelling: an Analytical Framework for Assessment of Two‐Dimensional Hydrodynamic Models

Abstract

Two-dimensional hydrodynamic models are increasingly common in riverine research and management. However, input data are not standardized among studies, and assessments of model performance are uncommon, which hinder interpretation of model results and comparisons among studies. Herein, we describe a framework for two-dimensional hydrodynamic model input data collection, model calibration and validation to evaluate model predictions. We present a logical process for the validation of depth and velocity that recognizes the inherent spatial uncertainty in the field measurements and modelling results. The hydrodynamic model we present as an example shows agreement between predicted and observed water surface elevation, area of inundation and spatial distributions of depth and velocity at calibration and independent validation discharges. If this model development and assessment framework was adopted by others, it would allow comparison between studies and provide a foundation for establishing model performance standards. Figure 6. Longitudinal water surface elevation plot comparing predicted (open circles) with observed (filled circles) values at T1 study site at a discharge of 58.1 m 3 s À1 (n = 719, RMSE = 0.0346).This was a discharge used for calibration K. A. WRIGHT ET AL.

River‐valley morphology, basin size, and flow‐event magnitude interact to produce wide variation in flooding dynamics

“…Maps of hydraulic model outputs such as flood depth, duration, and shear stress can provide other important descriptors of flooding dynamics that are comparable across reaches when the models have similar error levels (Wright et al. ) and can be useful for ecological investigations. Previous studies using 2D model output to characterize physical constraints on floodplain forests have successfully described linkages between river hydrology, lateral hydrologic connectivity, and forest composition (Meitzen , Kupfer et al.…”

“…The resulting maps offer a standardized method of hydrologic comparison that is meaningful within and across study sites and, when combined with other summaries of flooding patterns (e.g., duration, depth, shear stress), allow for a comprehensive understanding of inundation regimes. Maps of hydraulic model outputs such as flood depth, duration, and shear stress can provide other important descriptors of flooding dynamics that are comparable across reaches when the models have similar error levels (Wright et al 2016) and can be useful for ecological investigations. Previous studies using 2D model output to characterize physical constraints on floodplain forests have successfully described linkages between river hydrology, lateral hydrologic connectivity, and forest composition (Meitzen 2011, Kupfer et al 2015, Meitzen and and predicted forest succession processes in response to physical gradients associated with flooding such as flooding depth, duration, and shear stress (Benjankar et al 2012, Garci a-Arias et al 2013, Rivaes et al 2013.…”

Increasing the availability and spatial variation of spawning habitats through ascending baseflows

“…Substrate size (d84) was surveyed and georeferenced following methods presented by Latulippe, LaPointe, and Talbot (). The models were developed, calibrated, and validated using methods described in Wright et al (). Terrestrial LiDAR was the primary source of topographic data and was supplemented with survey grade GPS surveys and total station survey data, primarily along the river banks.…”

River Model Calibration Based on Design of Experiments Theory. A Case Study: Meta River, Colombia

“…In general, river models consist of a combination of two or three of the following components: hydrodynamics, sediments and morphology. A river model calibration is usually focused on the hydrodynamic component, whose usual indicators are water surface levels and discharge under steady flow conditions [19]. The most common indicator for sedimentological calibration is the sediment transport rate [20,21]; however, this information is not always available and, furthermore, it may include high levels of uncertainty depending on the measuring or estimation techniques employed to obtain the data.…”