Importance of maximum snow accumulation for summer low flows in humid catchments

Abstract

Winter snow accumulation obviously has an effect on the following catchment runoff. The question is, however, how long this effect lasts and how important it is compared to rainfall inputs. Here we investigate the relative importance of snow accumulation on one critical aspect of runoff, namely the summer low flow. This is especially relevant as the expected increase of air temperature might result in decreased snow storage. A decrease of snow will affect soil and groundwater storages during spring and might cause low streamflow values in the subsequent warm season. To understand these potential climate change impacts, a better evaluation of the effects of inter-annual variations in snow accumulation on summer low flow under current conditions is central. The objective in this study was (1) to quantify how long snowmelt affects runoff after melt-out and (2) to estimate the sensitivity of catchments with different elevation ranges to changes in snowpack. To find suitable predictors of summer low flow we used long time series from 14 Alpine and pre-Alpine catchments in Switzerland and computed different variables quantifying winter and spring snow conditions. In general, the results indicated that maximum winter snow water equivalent (SWE) influenced summer low flow, but could expectedly only partly explain the observed inter-annual variations. On average, a decrease of maximum SWE by 10 % caused a decrease of minimum discharge in July by 6-9 % in catchments higher than 2000 m a.s.l. This effect was smaller in middle-and lower-elevation catchments with a decrease of minimum discharge by 2-5 % per 10 % decrease of maxi-mum SWE. For higher-and middle-elevation catchments and years with below-average SWE maximum, the minimum discharge in July decreased to 70-90 % of its normal level. Additionally, a reduction in SWE resulted in earlier low-flow occurrence in some cases. One other important factor was the precipitation between maximum SWE and summer low flow. When only dry preceding conditions in this period were considered, the importance of maximum SWE as a predictor of low flows increased. We assessed the sensitivity of individual catchments to the change of maximum SWE using the non-parametric Theil-Sen approach as well as an elasticity index. Both sensitivity indicators increased with increasing mean catchment elevation, indicating a higher sensitivity of summer low flow to snow accumulation in Alpine catchments compared to lower-elevation pre-Alpine catchments.

Examining controls on peak annual streamflow and floods in the Fraser River Basin of British Columbia

“…Predictors were selected based on physical intuition, inspection of the relevant literature and initial exploratory data analysis. Prior studies that were particularly helpful in this regard were Gurrapu et al (2016), who examined the influence of the PDO on streamflow in western Canada, Jenicek et al (2016), who examined the influence of snow accumulation and other variables on summer low flows, Coles et al (2017), who studied snowmeltrunoff generation on Canadian prairie hillslopes, and Wever et al (2017), who conducted model simulations of the joint effect of snowmelt and soil moisture on streamflow in a Swiss Alpine catchment. The predictor variables chosen are listed in Table 2.…”

Beyond binary baseflow separation: delayed flow index as a fresh perspective on streamflow contributions

“…to consider differences in seasonal snowmelt and evaporative processes between the groups. The number of 270 classes and lower and upper elevation bounds are comparable to classifications used in other studies in the same region (Jenicek et al, 2015;Staudinger et al, 2017;2015;Viviroli and Weingartner, 2004). Our study catchments are uniformly distributed over the four classes allowing for a balanced statistical analysis across the four regime types ( Table 2).…”

Comparison of MODIS and Model-Derived Snow-Covered Areas: Impact of Land Use and Solar Illumination Conditions

“…In particular, estimating such variable is often uncertain due to the lack of snow-related ground measures across the catchment [46] and the high spatial variability of snow height [2]. This uncertainty, in turn, affects the correct estimation of snowmelt runoff [47] as well as summer low flows [48]. Thus, conditioning hydrological models using consistent satellite-derived products might be an appealing way to improve hydrological modeling reliability, as proven by [12,49,50] among others.…”