A multi‐scale study of the dominant catchment characteristics impacting low‐flow metrics

Abstract

Low flows can impact water use and instream ecology. Therefore, reliable predictions of low-flow metrics are crucial. In this study, we assess which catchment characteristics (climate, topography, geology and landcover) can explain the spatial variability of lowflow metrics at two different scales: the regional scale and the small headwater catchment scale. For the regional-scale analysis, we calculated the mean 7-day annual minimum flow (q min ), the mean of the flow that is exceeded 95% of the year (q 95 ), and the master recession constant (C) for 280 independent gauging stations across the Swiss Plateau and the Swiss Alps for the 2000-2018 period. We assessed the relation between 44 catchment characteristics and the three low-flow metrics based on correlation analysis and a random forest model. Low-flow magnitudes across the Swiss Plateau were positively correlated with the fraction of the area covered by sandstone bedrock or alluvium, and with the area that has a slope between 10 and 30 . Across the Swiss Alps, low-flow magnitudes were positively correlated with the fraction of area with slopes between 30 and 60 , and the area with glacial deposits and debris cover. There was good agreement between observations and predictions by the random forest regression model with the top 11 catchment characteristics for both regions: for 80% of the Swiss Plateau catchments and 60% of the Swiss Alpine catchments, we could predict the three low-flow metrics within an error of 30%. The residuals of the regression model, however, varied across short distances, suggesting that local catchment characteristics affect the variability of low-flow metrics. For the local-scale headwater catchments, we conducted 1-day snapshot field campaigns in 16 catchments during low-flow periods in 2015 and 2016. The measurements in these sub-catchments also showed that areas with sandstone bedrock and a good storage-to-river connectivity had above average low-flow magnitudes. Including knowledge on local catchment characteristics may help to improve regional low-flow predictions, however, not all local catchment characteristics were useful descriptors at larger scales.

Hillslope-scale exploration of the relative contribution of base flow, seepage flow and overland flow to streamflow dynamics

“…Previous studies have explored the control of geology on hydrological behaviors, revealing strong differences among classes of lithologies categorized as crystalline, carbonates, fine and coarse sedimentary rock (e.g. Carlier et al, 2018;Floriancic et al, 2022;Gleeson et al, 2011b). In the present case, the region is mostly composed of crystalline aquifer with only a few percent of the area covered by sedimentary aquifers.…”

Regional Low Flow Hydrology: Model Development and Evaluation

“…It can be considered a surrogate for groundwater pathways and their connectivity degrees, reflecting whether groundwater moves mainly through pores (unconsolidated sediments), a combination of pores and fractures (siliciclastic sedimentary), fractures with high connectivity potential (metamorphic and plutonic rocks), or fractures with generally low connectivity (volcanic rocks). Bedrock type can explain why, for instance, increased low flows are linked with the fraction of sandstones (Carlier et al., 2018; Floriancic et al., 2022) or colluvium (Price et al., 2011), both with high porosities and water storage capacities.…”

“…These studies argue that the unexplained variability is associated with physiography. On the other hand, small‐scale studies that show the predominant control of catchment characteristics on low flows (e.g., Bloomfield et al., 2009; Carlier et al., 2018; Floriancic et al., 2022; Pfister et al., 2017; Price et al., 2011) complement large‐scale studies by examining low flow generating mechanisms and identifying specific catchment characteristics linked with low flows in each location.…”

“…At continental and global scales, low flows are generally linked with climate rather than catchment characteristics (Addor et al., 2018; Apurv & Cai, 2020; Beck et al., 2013, 2015; Peña‐Arancibia et al., 2010), with few exceptions (e.g., Van Lanen et al., 2013). At smaller scales, in contrast, low flows are typically associated with catchment characteristics (Bloomfield et al., 2009; Carlier et al., 2018; Floriancic et al., 2022; Pfister et al., 2017; Price et al., 2011; Sayama et al., 2011). This scaling property is related to the fact that hydrological processes linked with catchment characteristics occur at local to continental scales, while processes linked with the climate occur mostly at large scales (Blöschl & Sivapalan, 1995; Western et al., 2002).…”

Time variable effectiveness and cost-benefits of different nature-based solution types and design for drought and flood management

“…Although the model and CBA method (Q 95 _7day index) were sitespecific, both could be scaled up and applied across multiple catchments contributing to major rivers on which industry abstraction limits are based, especially given the Q 95 is a widely used index for low flows [110][111][112]. This would aid determination of optimal locations and required scales of NBS for river basin-wide challenges.…”