Event-scale hysteresis metrics to reveal processes and mechanisms controlling constituent export from watersheds: A review
[Review of ]. WATER RESEARCH, 200.
• A six-step workflow was proposed to conduct hysteresis analyses. • We provided practical recommendations on the metrics to quantify hysteresis loops. • A standardized method to delineate events is needed to reduce uncertainties. • Machine-learning techniques are promising in future hysteresis analysis studies. Due to the increased availability of high-frequency measurements of stream chemistry provided by in situ sensors, researchers have gained more access to relationships between stream discharge and constituent concentrations (C-Q relationships) at event-scales. Existing studies reveal that event-scale C-Q relationships are mostly non-linear and exhibit temporal lags between peaks (or troughs) of hydrographs and chemographs, resulting in apparent hysteresis effects. In this paper, we summarize and introduce tools and methods in hysteresis analysis, especially the history and progresses of metrics to quantify hysteresis patterns. In addition, this paper provides a typical workflow to conduct event-scale hysteresis analysis, such as how to obtain the access to high-frequency measurements, existing methods to delineate storm events, approaches to classify and quantify hysteresis patterns, possible features/properties controlling hysteresis patterns, statistical methods to identify features at play, and strategies to deliver the inferences from hysteresis analysis. Lastly, we discuss some potential limitations that arise in the workflow and possible future work to address the challenges, including the development of advanced quantitative hysteresis metrics, generalized and standardized tools to delineate events and the integration of hysteresis analysis with numerical modeling. This paper aims to provide a critical overview of technical approaches for hysteresis analysis for researchers and hopefully foster their interests to advance our understanding of complex mechanisms in event-scale hydro-biogeochemical processes.