Uncertainty analysis and detection of structural changes in environmental systems dynamics for a better understanding of climatic and anthropogenic risks

数字技术的进步，以及更快的处理速度，促使复杂的环境模型用于研究、设计和规划目的。如今，功能强大的计算机代码几乎可以描述任何令人感兴趣的环境过程。由于全球变暖的灾难性影响的证据以惊人的速度增长，目前的做法是使用这些模型在使用观测数据校准后进行影响估计。然而，一致性问题很少被考虑：在当前气候中表现相对良好的模型在变化的气候中是否提供值得信赖的结果？在水文学方面，几乎使用了所有类型的模式，不幸的是，很少注意所选环境模式在未来气候条件下的适用性。对于此类研究，应谨慎使用黑箱模型，因为众所周知，黑箱模型的参数捕获了大量与校准条件相关的信息。在这种情况下，流域对气候反应一致性的隐含假设是不成立的。后一种说法原则上在较小程度上适用于物理驱动的和概念模型，这些模型总是涉及一些参数化和校准。由于全球变暖正以一种前所未有的方式驱动着地球的气候，我们需要了解一个特定的模型如何在未来的气候中发挥作用。

Progress in numerical technologies, as well as greater processing speed, has prompted the use of complex environmental models for research, design and planning purposes. Nowadays, powerful computer codes are available to describe nearly any environmental process of interest. As evidence for catastrophic impact of global warming grows at an alarming rate, the current practice is to use these models for impacts estimation after calibration using observed data. However, the issue of consistency is rarely considered: will a model that is performing relatively well in the current climate provide trustworthy results in a changed climate? In hydrology, nearly all categories of models have been used, unfortunately with very little attention if any to the suitability of the chosen environmental model under future climatic conditions. Black-box models should be used with extreme caution for such studies, since it is well known that the parameters of black-box models capture a lot of information related to the calibration conditions. In this case, the implicit assumption of consistency in a watershed's response to climate does not hold. The latter statement applies, in principle at a lesser extent, to physics-driven and conceptual models, which always involve some parameterisation and calibration. Since global warming is driving earth's climate in an unprecedented manner, insight is needed as to how a particular model can be expected to perform in the future climate.