Abstract
Abstract. Climate change affects natural streamflow regimes globally. To assess alterations in streamflow regimes, typically temporal variations in one or a few streamflow characteristics are taken into account. This approach, however, cannot see simultaneous changes in multiple streamflow characteristics, does not utilize all the available information contained in a streamflow hydrograph, and cannot describe how and to what extent streamflow regimes evolve from one to another. To address these gaps, we conceptualize streamflow regimes as intersecting spectrums that are formed by multiple streamflow characteristics. Accordingly, the changes in a streamflow regime should be diagnosed through gradual, yet continuous changes in an ensemble of streamflow characteristics. To incorporate these key considerations, we propose a generic algorithm to first classify streams into a finite set of intersecting fuzzy clusters. Accordingly, by analyzing how the degrees of membership to each cluster change in a given stream, we quantify shifts from one regime to another. We apply this approach to the data, obtained from 105 natural Canadian streams, during the period of 1966 to 2010. We show that natural streamflow in Canada can be categorized into six regime types, with clear hydrological and geographical distinctions. Analyses of trends in membership values show that alterations in natural streamflow regimes vary among different regions. Having said that, we show that in more than 80 % of considered streams, there is a dominant regime shift that can be attributed to simultaneous changes in streamflow characteristics, some of which have remained previously unknown. Our study not only introduces a new globally relevant algorithm for identifying changing streamflow regimes but also provides a fresh look at streamflow alterations in Canada, highlighting complex and multifaceted impacts of climate change on streamflow regimes in cold regions.
Highlights
Natural characteristics of streamflow are critical to ecosystem livelihood and human settlements around river systems (Poff et al, 2010; Nazemi and Wheater, 2014; Hassanzadeh et al, 2017)
We consider a multi-year timeframe for clustering and assigning initial membership values. The length of this timeframe should be chosen in a way that (1) provides a notion for streamflow regime and (2) provides enough timeframes to assess evolution in membership values
This study presents an attempt toward providing a globally relevant algorithm for identifying changing streamflow regimes
Summary
Natural characteristics of streamflow are critical to ecosystem livelihood and human settlements around river systems (Poff et al, 2010; Nazemi and Wheater, 2014; Hassanzadeh et al, 2017). Humans have considered the seasonality, variability, and magnitude of natural streamflow as key factors for determining potentials for socio-economic developments (Knouft and Ficklin, 2017). Streamflow regimes have been considered stationary in time (Milly et al, 2008). The looming effects of climate change along with human interventions through land and water management have raised fundamental questions regarding the stationarity of streamflow regimes during the current “Anthropocene” (Arnell and Gosling, 2013; Nazemi and Wheater, 2015a, b). Recent literature is full of evidence indicating major alterations in-
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