Robust environmental decision support tools are critical to maximise the ecological benefit of management decisions. However the models that underpin these rarely undergo rigorous evaluation. Here, we evaluated components of a scenario-based habitat suitability model, the Murray Flow Assessment Tool, by correlating model outputs against fish monitoring data collected since its development. Overall, we detected a low correlation between habitat suitability scores for fish and fish assemblages during low-flow conditions, including when lags in fish response to hydrological inputs were introduced. Scores specific to fish functional groups were also poorly correlated with data for those groups. Finally, model outcomes were highly sensitive to methods used to combine both individual indices and weightings for each component. Thus, we recommend using constant weightings, simple and consistent combination methods and reconsidering the number of fish functional groups as simplifications to this model and in the development of similar habitat suitability models elsewhere.

强大的环境决策支持工具对于最大化管理决策的生态效益至关重要。但是，支撑这些模型的模型很少经过严格的评估。在这里，我们通过将模型输出与自开发以来收集的鱼类监测数据进行关联，从而评估了基于情景的栖息地适应性模型（Murray Flow Assessment Tool）的组成部分。总体而言，在低流量条件下，包括引入水文输入对鱼类的响应出现滞后时，我们发现鱼类和鱼类组合的栖息地适宜性得分之间的相关性较低。特定于鱼类功能组的分数与这些组的数据也没有很好的相关性。最后，模型结果对用于组合各个组成部分的各个指标和权重的方法高度敏感。因此，