For simulating reactive transport on aquifer scale, various modeling approaches have been proposed. They vary considerably in their computational demands and in the amount of data needed for their calibration. Typically, the more complex a model is, the more data are required to sufficiently constrain its parameters. In this study, we assess a set of five models that simulate aerobic respiration and denitrification in a heterogeneous aquifer at quasi steady state. In a probabilistic framework, we test whether simplified approaches can be used as alternatives to the most detailed model. The simplifications are achieved by neglecting processes such as dispersion or biomass dynamics, or by replacing spatial discretization with travel‐time‐based coordinates. We use the model justifiability analysis proposed by Schöniger, Illman, et al. (2015, https://doi.org/10.1016/j.jhydrol.2015.07.047) to determine how similar the simplified models are to the reference model. This analysis rests on the principles of Bayesian model selection and performs a tradeoff between goodness‐of‐fit to reference data and model complexity, which is important for the reliability of predictions. Results show that, in principle, the simplified models are able to reproduce the predictions of the reference model in the considered scenario. Yet, it became evident that it can be challenging to define appropriate ranges for effective parameters of simplified models. This issue can lead to overly wide predictive distributions, which counteract the apparent simplicity of the models. We found that performing the justifiability analysis on the case of model simplification is an objective and comprehensive approach to assess the suitability of candidate models with different levels of detail.

中文翻译：

---

简化反应性运输模型的策略：贝叶斯模型比较

为了模拟含水层尺度上的反应输运，已经提出了各种建模方法。它们的计算需求和校准所需的数据量差异很大。通常，模型越复杂，就需要更多的数据来充分约束其参数。在这项研究中，我们评估了一组五个模型，这些模型在准稳态下模拟非均质含水层中的有氧呼吸和反硝化作用。在概率框架中，我们测试简化方法是否可以用作最详细模型的替代方法。可以通过忽略诸如分散或生物量动力学之类的过程来实现简化，或者通过用基于行进时间的坐标来代替空间离散化来实现。我们使用Schöniger，Illman等人提出的模型合理性分析。（2015，https：//doi.org/10.1016/j.jhydrol.2015.07.047），以确定简化模型与参考模型的相似程度。该分析基于贝叶斯模型选择的原理，并在参考数据的拟合优度和模型复杂度之间进行权衡，这对于预测的可靠性至关重要。结果表明，从原理上讲，简化模型能够在所考虑的场景中重现参考模型的预测。然而，显而易见的是，为简化模型的有效参数定义合适的范围可能具有挑战性。这个问题可能导致预测分布过宽，从而抵消了模型的明显简化。