ScoRE—A Simple Approach to Select a Water Quality Model

Abstract

Over the past decades, water quality models have become unique tools in the management of aquatic resources. A consequence of their widespread application is the significant number of models now available. Available methodologies to compare models provide limited support for their choice in the first place, especially to end-users or modelers with limited experience. Here we propose a method to assist in the selection of a particular model from a set of apparently similar models. The method is termed ScoRE, as it grades models according to three main aspects: Scope (aim, simulated processes, constituents, etc.), Record (reference to the model in publications, its range of applications, etc.), and the Experience of using the model from the user perspective (support material, graphical user interface, etc.). End-users define the criteria to be evaluated and their relative importance, as well as the conditions for model exclusion. The evaluation of models is still performed by the modelers, in open discussion with end-users. ScoRE is a complete approach, as it provides guidance not only to exclude models but also to select the most appropriate model for a particular situation. An application of this method is provided to illustrate its use in the choice of a model. The application resulted in the definition of 18 criteria, where 6 of these were defined exclusively by the end-users. Based on these and the relative importance of each criterion, ScoRE produced a ranking of models, facilitating model selection. The results illustrate how the contributions from modelers and end-users are integrated to select a model for a particular task.

Overview of water quality modeling

“…Phase IV is the last phase of the model selection process, and it needed for advanced ranking of models based on relevant processes including accuracy (numerical stability, model representation, and dispersion), the competence of available model certification, ease of modification, data input design, and output form and content (Grimsrud et al, 1976). Similarly, models can be selected with simple approaches (Marcos et al, 2018). In general, before performing water quality simulation, suitable models should be selected.…”

Modeling Water Quality in Watersheds: From Here to the Next Generation

“…The choice of software tools needs to be improved to meet operational goals of decision making and to bridge the gap between science and management ( Argent et al, 2016 ). If existing models or tools are to be used, Van Voorn et al (2016) provide a checklist for assessing model credibility, salience, and legitimacy, and Mateus et al (2018) guide model managers in selecting tools and models that meet expectations in scope and experience. Real-time monitoring and analysis frameworks ( Wong & Kerkez, 2016 ) and spatial workflow environments ( Nielsen et al, 2017 ; Zhang, Bu, et al, 2017 ) demonstrate technical innovations that still need to be operationalized by agencies.…”

Water Quality Simulation in the Bois River, Goiás, Central Brazil

“…They allow for the simulation of water usage situations, defining the ability of assimilation through the limits of disposal of finding sources or for the extractions of certain outflows, in a manner that implies calculated risk about the deterioration of water quality according to legal standards [14]. There also exist methods to help choose a more proper model for a determined situation, such as ScoRE (Scope, Record and Experience), which also gives orientation for excluding models [15]. One of the requisites for modeling water quality is to find its adequation for the intended use.…”