Abstract Human activities have extensively altered landscapes throughout the world and further changes are expected in the future. Anthropogenic impacts such as land use change, groundwater extraction and dam construction, along with the effects of climate change, interact with natural factors including soil weathering and erosion. Together, these processes create a constantly shifting, dynamic terrestrial environment that violates the assumption of stationarity commonly applied in hydrology. Consequently, hydrologists need to rethink both statistical and calibrated models to account for complex environmental processes. We review the literature on human-landscape-hydrological interactions to identify processes and feedbacks that influence water balances. Most of the papers covered consider only a few of these processes at a time and focus on structural attributes of the interactions rather than the short and long-term dynamics. We identify challenges in representing the scale-dependence, environmental connectivity and human-water interactions that characterize complex, dynamic landscapes. A synthesis of the findings posits connections between different landscape changes, as well as the associated timescales and level of certainty. A case study explores how different processes could combine to drive long-term shifts in catchment behavior. Recognizing that some important questions remain unaddressed by traditional approaches, we suggest the concept of ‘big laboratories’ in which multifaceted experiments are conducted in the environment by artificially inducing landscape change. These experiments would be accompanied by mechanistic modeling to both untangle experimental results and improve the theoretical basis of environmental models. An ambitious program of physical and virtual experimentation is needed to progress hydrologic prediction for dynamic landscapes. Plain language summary The Earth’s surface is constantly changing due to human-driven and natural processes. Shifts may be driven by humans directly (e.g. via land use change) or indirectly (e.g. by driving climate change that causes shifts in ecological communities). Other changes are natural, such as certain soil processes that lead to shifts in texture and properties over time. In many places, landscape change is now occurring at unprecedented rates. This impacts the water cycle, creating a need for models that are robust under changing conditions. Our paper synthesizes a wide range of literature on key aspects of landscape change that have wide-ranging implications for hydrology. We focus on the impacts of processes at different spatial and temporal scales, along with feedbacks between various environmental and anthropogenic shifts. We discuss connections between different landscape changes and the timescales over which they each affect the water cycle. A case study is presented to highlight the potential for cascading landscape disturbances that could alter long-term catchment response. Recognizing limitations in traditional data collection and modeling, we introduce the concept of ‘big laboratories’ to conduct environmental experiments under landscape change, providing an avenue for addressing the complex questions around hydrology in a changing world.

中文翻译：

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景观变化及其水文效应：跨尺度的相互作用和反馈

摘要 人类活动已经广泛地改变了世界各地的景观，预计未来还会发生进一步的变化。土地利用变化、地下水开采和大坝建设等人为影响，以及气候变化的影响，与土壤风化和侵蚀等自然因素相互作用。这些过程共同创造了一个不断变化的动态陆地环境，违反了水文学中普遍应用的平稳性假设。因此，水文学家需要重新考虑统计模型和校准模型，以解释复杂的环境过程。我们回顾了人类-景观-水文相互作用的文献，以确定影响水平衡的过程和反馈。所涉及的大多数论文一次只考虑其中的几个过程，并且侧重于相互作用的结构属性，而不是短期和长期动态。我们确定了表征复杂动态景观的尺度依赖性、环境连通性和人水相互作用方面的挑战。研究结果的综合假设了不同景观变化之间的联系，以及相关的时间尺度和确定性水平。一个案例研究探讨了不同的过程如何结合起来推动流域行为的长期转变。认识到传统方法仍未解决一些重要问题，我们提出了“大实验室”的概念，其中通过人为诱导景观变化在环境中进行多方面的实验。这些实验将伴随着机械建模，以解开实验结果并改进环境模型的理论基础。需要一个雄心勃勃的物理和虚拟实验计划来推进动态景观的水文预测。简单的语言总结 由于人类驱动和自然过程，地球表面在不断变化。变化可能是由人类直接（例如通过土地利用变化）或间接（例如通过推动导致生态群落变化的气候变化）驱动的。其他变化是自然的，例如某些土壤过程会导致质地和特性随时间发生变化。在许多地方，景观变化正以前所未有的速度发生。这会影响水循环，因此需要在不断变化的条件下保持稳健的模型。我们的论文综合了大量关于景观变化关键方面的文献，这些文献对水文具有广泛的影响。我们关注不同时空尺度的过程的影响，以及各种环境和人为变化之间的反馈。我们讨论了不同景观变化与它们各自影响水循环的时间尺度之间的联系。提出了一个案例研究，以强调可能改变流域长期响应的级联景观干扰的潜力。认识到传统数据收集和建模的局限性，我们引入了“大实验室”的概念，以在景观变化下进行环境实验，为解决不断变化的世界中与水文学相关的复杂问题提供了途径。