Ecohydrological phenomena are o ften multiscale in nature, with behavioTur that emerges from the interaction of tightly coupled systems having characteristic timescales that differ by orders of magnitude. Models address these differences using timescale separation methods, where each system is held in psuedo‐steady state while the other evolves. When the computational demands of solving the ‘fast’ system are large, this strategy can become numerically intractable. Here, we use emulation modelling to accelerate the simulation of a computationally intensive ‘fast’ system: overland flow. We focus on dryland ecosystems in which storms generate overland flow, on timescales of 10^1 − 2 s. In these ecosystems, overland flow delivers crucial water inputs to vegetation, which grows and disperses ‘slowly’, on timescales of 10^7 − 9 s. Emulation allows for a physically realistic treatment of flow, advancing on phenomenological descriptions used in previous studies. Resolving the within‐storm processes reveals novel dynamics, including new transition pathways from patchy vegetation to desertification, that are specifically controlled by storm processes.

中文翻译：

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旱地植被格局对风暴特征的敏感性

生态水文学现象本质上是多尺度的，其行为来自紧密耦合的系统之间的相互作用，这些系统的特征时标相差一个数量级。模型使用时标分离方法解决了这些差异，其中每个系统都保持伪稳态，而另一个系统则不断演化。当解决“快速”系统的计算需求很大时，此策略在数值上会变得棘手。在这里，我们使用仿真模型来加速对计算密集型“快速”系统的仿真：陆上水流。我们专注于旱灾生态系统，其中风暴会产生陆地流动，时间尺度为10 ^{1 − 2}s。在这些生态系统中，陆流为植被提供了关键的水输入，植被在10 ^{7 − 9} s的时间内“缓慢地”生长和扩散。仿真可以对流动进行物理上的真实处理，并可以根据先前研究中使用的现象学描述进行处理。解决风暴内过程揭示了新的动力，包括由斑块状植被到荒漠化的新过渡路径，这些路径特别受风暴过程控制。