Since the accuracy of the model calibration depends critically on the calibration data used, attention is given to some of the most common issues associated with data quality. For this reason, the paper does not address complex modelling issues around wave-driven currents, littoral drift, and shoreline evolution where specialist models (e.g., the nonhydrostatic version of XBeach and CFD) must be employed. In doing so, it acknowledges that some degree of compromise between the complexity of the natural system and the model representation must be reached. It is intended to provide guidance to the assessment and use of model calibration data and to offer procedural clarity and simplification to the model calibration and validation process. This paper provides an evidence-based review and presents examples of calibration data sources and of model calibration and validation practices for estuarine and shelf sea models. Without an agreed methodology and a performance standard for model calibration and validation, there is a risk that the quality of different approaches will vary, efforts will be wasted following inefficient or inappropriate calibration methods, and inconsistencies in methodologies will make model intercomparisons problematic. This can result in poor model performance and unreliable model predictions. A wide variety of different modelling practices are employed by consultants and academics, and frequently insufficient attention is given to the potential errors associated with the measured (and modelled) data used for model calibration and validation. IntroductionĪlthough a need to standardise model build, calibration, and validation processes around one agreed approach is widely acknowledged, only limited guidance is available (e.g., ) and often ambiguous and sometimes conflicting advice if offered in the grey literature (e.g., ). It is intended as a reference point both for numerical modellers and for specialists tasked with interpreting the accuracy and validity of results from hydrodynamic, wave, and sediment models. Specifically, it takes account of inherent modelling uncertainties and defines metrics of performance based on practical experience. It also looks at common assumptions, data input requirements, and statistical analyses that can be applied to assess the performance of models of estuaries and shelf seas. It addresses the common problems associated with data availability, errors, and uncertainty and examines the model build process, including calibration and validation. The paper is motivated by a present lack of clear model performance guidelines for shelf sea and estuarine modellers seeking to demonstrate to clients and end users that a model is fit for purpose.
0 kommentar(er)
