Pallavi Goswami, T. Peterson, A. Mondal, C. Rüdiger
{"title":"Can drought regimes undergo shifts?","authors":"Pallavi Goswami, T. Peterson, A. Mondal, C. Rüdiger","doi":"10.36334/modsim.2023.goswami501","DOIUrl":null,"url":null,"abstract":": 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:","PeriodicalId":390064,"journal":{"name":"MODSIM2023, 25th International Congress on Modelling and Simulation.","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"MODSIM2023, 25th International Congress on Modelling and Simulation.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36334/modsim.2023.goswami501","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
: 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: