干旱政权会发生变化吗?

Pallavi Goswami, T. Peterson, A. Mondal, C. Rüdiger
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引用次数: 0

摘要

集水区的水文变量及其相应的极端特征有可能改变状态,特别是当集水区经历长期干旱期时。这可能导致集水区经历流量异常,甚至比历史上认为的集水区极低流量事件更为极端。现有的研究表明,极端事件可能会随着时间而变化;因此,了解流中的极端是否也有可能存在于多个状态是很重要的。Goswami等人(2022)证实,低流量表现出由气候模式引起的非平稳性(即低流量中基于协变量的非平稳性)。我们目前的工作是调查低流量是否表现出更复杂的非平稳性形式,以状态(或制度)变化的形式超越Goswami等人(2022)所探索的常规的基于协变量的非平稳性。这项工作也是Peterson等人(2021)研究的延伸,该研究显示了澳大利亚东南部集水区的复杂动态。Peterson等人(2021)证实,一个集水区的年平均流量和季节平均流量可以切换到不同的稳定状态,导致给定降水下,集水区产生的流量低于正常水平。术语“状态切换”或“状态切换”与变量潜在概率分布的转移有关。我们的研究特别关注极端(低)流量,以调查它们是否经历了政权变化,并以更精细的时间分辨率。我们研究了澳大利亚东南部161个无管制集水区的低流量强度、持续时间和频率(IDF)。基于隐马尔可夫模型的方法用于检测低流量特性的移位。主要发现如下:
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Can drought regimes undergo shifts?
: Hydrological variables of a catchment and their corresponding extreme characteristics have a possibility of switching regimes, particularly when a catchment undergoes protracted dry periods. This can result in a catchment experiencing a flow anomaly that is even more extreme than what was historically considered an extreme low flow event for the catchment. Existing studies suggest that extreme events may be changing with time; it is thus important to understand whether extremes in flows also have the potential to exist in multiple states. Goswami et al. (2022) established that low flows exhibit non-stationarity induced by climate modes (i.e., covariate-based non-stationarity in low flows). Our present work investigates if low flows exhibit a more complex form of non-stationarity, in the form of state (or regime) changes beyond the routine covariate-based non-stationarity as explored in Goswami et al. (2022). This work is also an extension of the study by Peterson et al. (2021), which showed complex dynamics for flows in catchments in southeast Australia. Peterson et al. (2021) established that a catchment's annual and seasonal mean flows can switch into alternative stable states, resulting in a catchment producing less streamflow than normal for a given precipitation. The term ‘switching of states’ or ‘regime-switching’ relates to a shift in the underlying probability distribution of a variable. Our study looks specifically at extreme (low) flows to investigate if they undergo regime changes, and at a much finer temporal resolution. We studied intensity, duration, and frequency (IDF) of low flows for 161 unregulated catchments in southeast Australia. A Hidden Markov Model-based approach was used to examine shifts in the low flow characteristics. The key findings are:
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