Spatio‐temporal variability in contributions to low flows in the high Alpine Poschiavino catchment

Abstract

In order to predict streamflow accurately during extended dry periods, we need to understand the spatial variability of low flows and the extent to which it is affected by the spatial organization and drainage of catchment subsurface storage areas. This is especially true in Alpine catchments with widely varying topography, lithology, sediment deposits, and soil properties. Field measurements in the Poschiavino catchment in southern Switzerland, during a winter recession period without recharge, provided a unique opportunity to demonstrate the connections between subsurface storage areas, low flows, and their variability. We measured discharge in four nested sub‐catchments during seven field campaigns in the winter of 2013–2014. We analysed stream water electrical conductivity (EC) and water chemistry to identify the areas contributing to low‐flow discharge and estimated their contributions. Sediment cover type and thickness were mapped using a recently developed tool for geomorphology‐based storage classification of mountainous terrain, to determine the physical properties of the subsurface storage areas contributing to low‐flow discharge. Recession analyses combined with water chemistry data allowed the detection of different drainage timescales and the estimation of storage potential of the unconsolidated (Quaternary) deposits. We found substantial spatial variation in storage depletion between the sub‐catchments, ranging from 54 mm to 200 mm for the four‐month monitoring period. Variability in low‐flow contributions from different catchments and different recession behavior could be related to the differences in the estimated storage potential. For some point sources, we could quantify the contributing area and thus quantify low flows at the hillslope scale. Overall, the low‐flow variability is mostly related to the fraction of precipitation that recharges subsurface storage areas and to the properties influencing their drainage. To capture these processes, we suggest low‐flow geomorphological mapping approaches that consider not only morphometric (shape of the landscape) and geologic (properties of the bedrock) controls but also the water storage potential of debris cover and weathered rock.

Spatial variability in specific discharge and streamwater chemistry during low flows: Results from snapshot sampling campaigns in eleven Swiss catchments

“…The spatial variability in ion concentrations was especially high in catchments with complex geology, like P4, which had high Ca 2+ concentrations (and EC) in areas underlain by the karstified Jurassic limestones and high SO 4 2 − concentrations (and also EC) in other parts due to flow from gypsum layers. Such small‐scale differences in lithology can likely explain a large part of the variability in water chemistry in some of the other catchments as well (e.g., in the Poschiavino headwater catchment; see Floriancic et al, ). Unfortunately, we could not statistically quantify these relations based on the available larger scale geodata (Figure ).…”

“…Streamflow was measured using the salt dilution method (c.f. Moore, , ; Day, ; see Floriancic et al, , for a detailed description of the salt dilution protocol). We tried to minimize bias and measurement uncertainties by a careful preselection of the sampling locations, for example, we avoided sampling too close to the confluence of tributaries because this might lead to sampling in locations where the stream is not completely mixed.…”

“…Streamflow during low-flow periods largely originates from groundwater (e.g., Costelloe, Peterson, Halbert, Western, & McDonnell, 2015;Soulsby et al, 2007), including bedrock groundwater (e.g., Oda, Suzuki, Egusa, & Uchiyama, 2013;Sayama, McDonnell, Dhakal, & Sullivan, 2011;Tague & Grant, 2004). The properties of these groundwater stores, and thus their responses to extended dry periods, vary markedly from place to place, so that the magnitude of low flows can also be highly variable in space (e.g., Floriancic et al, 2018;Smakhtin, 2001;Sun, Kasahara, Otsuki, Saito, & Onda, 2017). Previous studies have shown that landscape characteristics, like topography (Kroll, Luz, Allen, & Vogel, 2004;Kuentz, Arheimer, Hundecha, & Wagener, 2017;Li et al, 2018;Sayama et al, 2011;Staudinger, Weiler, & Seibert, 2015), geology (Tague & Grant, 2004), land use (Ahn & Merwade, 2017;Smakhtin, 2001), or the extent of quaternary deposits and unconsolidated layers (Roy & Hayashi, 2009;Winkler et al, 2016) can affect the magnitude of low flows.…”

Seasonally varied hillslope and groundwater contributions to streamflow in a glacial till and fractured sedimentary bedrock dominated Rocky Mountain watershed

“…Similarly, Liu et al (2004) showed that the recession 45 limb of the annual hydrograph in the Colorado front range Rocky Mountains was driven by baseflow released from fractured bedrock. Deep soils and till deposits with large storage capacities have also been shown to sustain baseflows during drier periods (Floriancic et al, 2018;Shanley et al, 2015). Deep sediment deposits in the Poschiavino watershed, in Switzerland, were associated with larger storage capacity and higher winter baseflows compared to watersheds with shallow sediment deposits (Floriancic et al, 2018).…”

Saturated areas through the lens: 2. Spatio‐temporal variability of streamflow generation and its relationship with surface saturation

“…These studies helped to clarify the relative role of different landscape units as spatial sources of run-off and the importance of riparian zones in regulating the portion of "new" and "old" water in stormflow (McGlynn et al, 2004;McGlynn & McDonnell, 2003). Other studies have focused on characterizing spatial and temporal variability of run-off by measuring discharge along continuous stream reaches (Anderson & Burt, 1978;Bergstrom, Jencso, et al, 2016;Floriancic et al, 2018;Genereux, Hemond, & Mulholland, 1993;Huff, O'Neill, Emanuel, Elwood, & Newbold, 1982;Kura s, Weiler, & Alila, 2008;Payn, Gooseff, McGlynn, Bencala, & Wondzell, 2012;Shaw, Bonville, & Chandler, 2017). Unlike the studies employing catchment discretization, these studies take into account the dynamics of surface water (cf.…”