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Towards a methodology for testing models as hypotheses in the inexact sciences

机译:寻求一种在不精确的科学中作为假设检验模型的方法

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摘要

This paper reviews the issues involved in treating hydrology as an example of an inexact science faced with significant epistemic uncertainties. It proposes a novel method for developing limits of acceptability for testing hydrological models as hypotheses about how a catchment hydrological system might function. The approach is based only on an analysis of the available observations and the consideration of event mass balance for successive rainfall-runoff events. It is shown that there are many events that are subject to epistemic uncertainties in the input data so that mass balance is not satisfied. The proposed approach allows taking these epistemic uncertainties into account in a pragmatic way before any model runs are made. It is an approach that might be applicable in other areas of environmental science where similar basic principles are fundamental to models, but which might not be satisfied by the observations that are used for model evaluation.
机译:本文回顾了水文学中涉及的问题,将其作为一个面临重大认知不确定性的不精确科学的例子。它提出了一种新的方法来建立水文模型测试可接受性的极限,作为关于流域水文系统可能如何运作的假设。该方法仅基于对可用观测值的分析以及对连续降雨径流事件的事件质量平衡的考虑。结果表明,在输入数据中有许多事件受到认知不确定性的影响,因此无法满足质量平衡。所提出的方法允许在进行任何模型运行之前以务实的方式考虑这些认知不确定性。这种方法可能适用于环境科学的其他领域,在这些领域中,类似的基本原理是模型的基础,但是可能无法被用于模型评估的观察结果所满足。

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