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

2016 ◽  
Vol 20 (2) ◽  
pp. 859-874 ◽  
Author(s):  
Michal Jenicek ◽  
Jan Seibert ◽  
Massimiliano Zappa ◽  
Maria Staudinger ◽  
Tobias Jonas
Keyword(s):  
Snow Water Equivalent ◽  
Warm Season ◽  
Snow Accumulation ◽  
Low Flow ◽  
Annual Variations ◽  
Low Flows ◽  
Snow Storage ◽  
Winter Snow ◽  
Lower Elevation ◽  
Alpine 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 maximum 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.

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

2015 ◽  
Vol 12 (7) ◽  
pp. 7023-7056 ◽  
Author(s):  
M. Jenicek ◽  
J. Seibert ◽  
M. Zappa ◽  
M. Staudinger ◽  
T. Jonas
Keyword(s):  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Snow Accumulation ◽  
Low Flow ◽  
Annual Variations ◽  
Low Flows ◽  
Lower Elevation ◽  
Long Time ◽  
Snow Conditions ◽  
Alpine Catchments

Abstract. The expected increase of air temperature will increase the ratio of liquid to solid precipitation during winter and, thus decrease the amount of snow, especially in mid-elevation mountain ranges across Europe. The decrease of snow will affect groundwater recharge during spring and might cause low streamflow values in the subsequent summer period. To evaluate these potential climate change impacts, we investigated the effects of inter-annual variations in snow accumulation on summer low flow and addressed the following research questions: (1) how important is snow for summer low flows and how long is the "memory effect" in catchments with different elevations? (2) How sensitive are summer low flows to any change of winter 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. We assessed the sensitivity of individual catchments to the change of maximum snow water equivalent (SWEmax) using the non-parametric Theil–Sen approach as well as an elasticity index. In general, the results indicated that maximum winter snow accumulation influenced summer low flow, but could only partly explain the observed inter-annual variations. One other important factor was the precipitation between maximum snow accumulation and summer low flow. When only the years with below average precipitation amounts during this period were considered, the importance of snow accumulation as a predictor of low flows increased. The slope of the regression between SWEmax and summer low flow and the elasticity index both increased with increasing mean catchment elevation. This indicated a higher sensitivity of summer low flow to snow accumulation in alpine catchments compared to lower elevation catchments.

scholarly journals Importance of snowmelt contribution to seasonal runoff and summer low flows in Czechia

2020 ◽  
Vol 24 (7) ◽  
pp. 3475-3491 ◽  
Author(s):  
Michal Jenicek ◽  
Ondrej Ledvinka
Keyword(s):  
Groundwater Recharge ◽  
Snow Water Equivalent ◽  
Summer Precipitation ◽  
Annual Runoff ◽  
Annual Variations ◽  
Low Flows ◽  
Total Runoff ◽  
Snow Storage ◽  
The Future ◽  
Seasonal Runoff

Abstract. The streamflow seasonality in mountain catchments is often influenced by snow. However, a shift from snowfall to rain is expected in the future. Consequently, a decrease in snow storage and earlier snowmelt is predicted, which will cause changes not only in seasonal runoff distribution in snow-dominated catchments, but it may also affect the total annual runoff. The objectives of this study were to quantify (1) how inter-annual variations in snow storages affect spring and summer runoff, including summer low flows, and (2) the importance of snowmelt in generating runoff compared to rainfall. The snow storage, groundwater recharge and streamflow were simulated for 59 mountain catchments in Czechia in the period from 1980 to 2014 using a bucket-type catchment model. The model output was evaluated against observed daily runoff and snow water equivalent. Hypothetical scenarios were performed, which allowed for analysing the effect of inter-annual variations in snow storage on seasonal runoff separately from other components of the water balance. The results showed that 17 %–42 % (26 % on average) of the total runoff in the study catchments originates as snowmelt, despite the fact that only 12 %–37 % (20 % on average) of the precipitation falls as snow. This means that snow is more effective in generating catchment runoff compared to liquid precipitation. This was demonstrated by modelling experiments which showed that total annual runoff and groundwater recharge decrease in the case of a precipitation shift from snow to rain. In general, snow-poor years were clearly characterized by a lower snowmelt runoff contribution compared to snow-rich years in the analysed period. Additionally, snowmelt started earlier in these snow-poor years and caused lower groundwater recharge. This also affected summer baseflow. For most of the catchments, the lowest summer baseflow was reached in years with both relatively low summer precipitation and snow storage. This showed that summer low flows (directly related to baseflow) in our study catchments are not only a function of low precipitation and high evapotranspiration, but they are significantly affected by the previous winter snowpack. This effect might intensify drought periods in the future when generally less snow is expected.

Snowmelt contribution to seasonal runoff: Lessons learned from using a bucket-type model on a large set of catchments

2020 ◽  
Author(s):  
Michal Jenicek ◽  
Ondrej Ledvinka
Keyword(s):  
Groundwater Recharge ◽  
Snow Water Equivalent ◽  
Large Set ◽  
Annual Variations ◽  
Low Flows ◽  
Snow Storage ◽  
The Future ◽  
Seasonal Runoff ◽  
The Impact ◽  
Catchment Runoff

<p>The streamflow seasonality in mountain catchments is largely influenced by snow. However, a shift from snowfall to rain is expected in the future. Consequently, a decrease in snow storage and earlier snowmelt is predicted, which will cause changes in spring and summer runoff. The objectives of this study were to quantify 1) how inter-annual variations in snow storages affect spring and summer runoff, including summer low flows and 2) the importance of snowmelt in generating runoff compared to rainfall. The snow storage, groundwater recharge and streamflow were simulated for 59 mountain catchments in Czechia in the period 1980–2014 using a bucket-type catchment model. The model performance was evaluated against observed daily runoff and snow water equivalent. Hypothetical simulations were performed, which allowed us to analyse the effect of inter-annual variations in snow storage on seasonal runoff separately from other components of the water balance. This was done in the HBV snow routine using the threshold temperature T<sub>T</sub> that differentiates between snow and rain and sets the air temperature of snowmelt onset. By changing the T<sub>T</sub>, we can control the amount of accumulated snow and snowmelt timing, while other variables remain unaffected.</p><p>The results showed that 17-42% (26% on average) of the total runoff in study catchments originates as snowmelt, despite the fact that only 12-37% (20% on average) of the precipitation falls as snow. This means that snow is more effective in generating catchment runoff compared to liquid precipitation. This was documented by modelling experiments which showed that total annual runoff and groundwater recharge decreases in the case of a precipitation shift from snow to rain. In general, snow-poor years are clearly characterized by a lower snowmelt runoff contribution compared to snow-rich years in the analysed period. Additionally, snowmelt started earlier in these snow-poor years and caused lower groundwater recharge. This also affected summer baseflow. For most of the catchments, the lowest summer baseflow was reached in years with both relatively low summer precipitation and snow storage. This showed that summer low flows (directly related to baseflow) in our study catchments are not only a function of low precipitation and high evapotranspiration, but they are significantly affected by previous winter snowpack. This effect might intensify the summer low flows in the future when generally less snow is expected.</p><p>Modelling experiments also opened further questions related to model structure and parameterization, specifically how individual model procedures and parameters represent the real natural processes. To understand potential model artefacts might be important when using HBV or similar bucket-type models for impact studies, such as modelling the impact of climate change on catchment runoff.</p>

scholarly journals Importance of snowmelt contribution to seasonal runoff and summer low flows in Czechia

2020 ◽  
Author(s):  
Michal Jenicek ◽  
Ondrej Ledvinka
Keyword(s):  
Groundwater Recharge ◽  
Snow Water Equivalent ◽  
Model Performance ◽  
Summer Precipitation ◽  
Annual Runoff ◽  
Annual Variations ◽  
Low Flows ◽  
Snow Storage ◽  
The Future ◽  
Seasonal Runoff

Abstract. The streamflow seasonality in mountain catchments is largely influenced by snow. However, a shift from snowfall to rain is expected in the future. Consequently, a decrease in snow storage and earlier snowmelt is predicted, which will cause changes in spring and summer runoff. The objectives of this study were to quantify 1) how inter-annual variations in snow storages affect spring and summer runoff, including summer low flows and 2) the importance of snowmelt in generating runoff compared to rainfall. The snow storage, groundwater recharge and streamflow were simulated for 59 mountain catchments in Czechia in the period 1980–2014 using a bucket-type catchment model. The model performance was evaluated against observed daily runoff and snow water equivalent. Hypothetical simulations were performed, which allowed us to analyse the effect of inter-annual variations in snow storage on seasonal runoff separately from other components of the water balance. The results showed that 17–42 % (26 % on average) of the total runoff in study catchments originates as snowmelt, despite the fact that only 12–37 % (20 % on average) of the precipitation falls as snow. This means that snow is more effective in generating catchment runoff compared to liquid precipitation. This was documented by modelling experiments which showed that total annual runoff and groundwater recharge decreases in the case of a precipitation shift from snow to rain. In general, snow-poor years are clearly characterized by a lower snowmelt runoff contribution compared to snow-rich years in the analysed period. Additionally, snowmelt started earlier in these snow-poor years and caused lower groundwater recharge. This also affected summer baseflow. For most of the catchments, the lowest summer baseflow was reached in years with both relatively low summer precipitation and snow storage. This showed that summer low flows (directly related to baseflow) in our study catchments are not only a function of low precipitation and high evapotranspiration, but they are significantly affected by previous winter snowpack. This effect might intensify the summer low flows in the future when generally less snow is expected.

scholarly journals Effects of climate anomalies on warm-season low flows in Switzerland

2020 ◽  
Vol 24 (11) ◽  
pp. 5423-5438
Author(s):  
Marius G. Floriancic ◽  
Wouter R. Berghuijs ◽  
Tobias Jonas ◽  
James W. Kirchner ◽  
Peter Molnar
Keyword(s):  
Snow Water Equivalent ◽  
Potential Evapotranspiration ◽  
Warm Season ◽  
Winter Precipitation ◽  
Low Flow ◽  
Climate Conditions ◽  
Environmental Consequences ◽  
Climate Anomalies ◽  
Low Flows ◽  
The Individual

Abstract. Switzerland has faced extended periods of low river flows in recent years (2003, 2011, 2015 and 2018), with major economic and environmental consequences. Understanding the origins of events like these is important for water resources management. In this work, we provide data illustrating the individual and joint contributions of precipitation and evapotranspiration to low flows in both typical and dry years. To quantify how weather drives low flows, we explore how deviations from mean seasonal climate conditions (i.e., climate anomalies) of precipitation and potential evapotranspiration correlate with the occurrence and magnitude of annual 7 d lowest flows (Qmin) during the warm season (May through November) across 380 Swiss catchments from 2000 through 2018. Most warm-season low flows followed periods of below-average precipitation and above-average potential evapotranspiration, and the lowest low flows resulted from both of these drivers acting together. Low-flow timing was spatially variable across Switzerland in all years, including the driest (2003, 2011, 2015 and 2018). Low flows in these driest years were associated with much longer-lasting climate anomalies than the ≤2 month anomalies which preceded typical warm-season low flows in other years. We found that snow water equivalent and winter precipitation totals only slightly influenced the magnitude and timing of warm-season low flows in low-elevation catchments across Switzerland. Our results provide insight into how precipitation and potential evapotranspiration jointly shape warm-season low flows across Switzerland and potentially aid in assessing low-flow risks in similar mountain regions using seasonal weather forecasts.

scholarly journals Simulation of snow accumulation and melting in the Kama river basin using data from global prognostic models

2019 ◽  
Vol 59 (4) ◽  
pp. 494-508 ◽  
Author(s):  
S. V. Pyankov ◽  
A. N. Shikhov ◽  
P. G. Mikhaylyukova
Keyword(s):  
Snow Cover ◽  
Mean Square Error ◽  
River Basin ◽  
Snow Water Equivalent ◽  
Numerical Models ◽  
Snow Accumulation ◽  
Mean Square ◽  
Snow Storage ◽  
The Mean ◽  
Weather Stations

Currently, the improvement of numerical models of weather forecasting allows using them for hydrological problems, including calculations of snow water equivalent  (SWE) or snow storage. In this paper, we discuss the applicability of daily precipitation forecasts for three global atmospheric models: GFS (USA), GEM (Canada) and PL-AV (Russia) for calculating snow storage (SWE) in the Kama river basin for the cold season of 2017–2018. As the main components of the balance of snow storages the following parameters were taken into account: precipitation (with regard for the phase); snow melting during thaws; evaporation from the surface of the snow cover; interception of solid precipitation by forest vegetation. The calculation of snow accumulation and melting was based on empirical methods and performed with the GIS technologies. The degree-day factor was used to calculate snowmelt intensity, and snow sublimation was estimated by P.P. Kuz’min formula. The accuracy of numerical precipitation forecasts was estimated by comparing the results with the data of 101 weather stations. Materials of 40 field and 27 forest snow-measuring routes were taken into account to assess the reliability of the calculation of snow storages (SWE). During the snowmelt period, the part of the snow-covered area of the basin was also calculated using satellite images of Terra/Aqua MODIS on the basis of the NDFSI index. The most important result is that under conditions of 2017/18 the mean square error of calculating the maximum snow storage by the GFS, GEM and PL-AB models was less than 25% of its measured values. It is difficult to determine which model provides the maximum accuracy of the snow storage calculation since each one has individual limitations. According to the PL-AV model, the mean square error of snow storage calculation was minimal, but there was a significant underestimation of snow accumulation in the mountainous part of the basin. According to the GEM model, snow storages were overestimated by 10–25%. When calculating with use of the GFS model data, a lot of local maximums and minimums are detected in the field of snow storages, which are not confirmed by the data of weather stations. The main sources of uncertainty in the calculation are possible systematic errors in the numerical forecasts of precipitation, as well as the empirical coefficients used in the calculation of the intensity of snowmelt and evaporation from the snow cover surface.

scholarly journals Snow Distribution and Melt Modeling for Mittivakkat Glacier, Ammassalik Island, Southeast Greenland

2006 ◽  
Vol 7 (4) ◽  
pp. 808-824 ◽  
Author(s):  
Sebastian H. Mernild ◽  
Glen E. Liston ◽  
Bent Hasholt ◽  
Niels T. Knudsen
Keyword(s):  
Mass Balance ◽  
Snow Water Equivalent ◽  
Snow Accumulation ◽  
Equilibrium Line Altitude ◽  
Ice Melt ◽  
Solid Precipitation ◽  
Glacier Terminus ◽  
Winter Snow ◽  
Glacier Ice ◽  
Surface Melt

Abstract A physically based snow-evolution modeling system (SnowModel) that includes four submodels—the Micrometeorological Model (MicroMet), EnBal, SnowPack, and SnowTran-3D—was used to simulate five full-year evolutions of snow accumulation, distribution, sublimation, and surface melt on the Mittivakkat Glacier, in southeast Greenland. Model modifications were implemented and used 1) to adjust underestimated observed meteorological station solid precipitation until the model matched the observed Mittivakkat Glacier winter mass balance, and 2) to simulate glacier-ice melt after the winter snow accumulation had ablated. Meteorological observations from two meteorological stations were used as model inputs, and glaciological mass balance observations were used for model calibration and testing of solid precipitation observations. The modeled end-of-winter snow-water equivalent (w.eq.) accumulation increased with elevation from 200 to 700 m above sea level (ASL) in response to both elevation and topographic influences, and the simulated end-of-summer location of the glacier equilibrium line altitude was confirmed by glaciological observations and digital images. The modeled test-period-averaged annual mass balance was 150 mm w.eq. yr−1, or ∼15%, less than the observed. Approximately 12% of the precipitation was returned to the atmosphere by sublimation. Glacier-averaged mean annual modeled surface melt ranged from 1272 to 2221 mm w.eq. yr−1, of which snowmelt contributed from 610 to 1040 mm w.eq. yr−1. The surface-melt period started between mid-May and the beginning of June, and lasted until mid-September; there were as many as 120 melt days at the glacier terminus. The model simulated a Mittivakkat Glacier recession averaging −616 mm w.eq. yr−1, almost equal to the observed −600 mm w.eq. yr−1.

scholarly journals Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

2018 ◽  
Vol 22 (2) ◽  
pp. 1017-1032 ◽  
Author(s):  
Andreas Marx ◽  
Rohini Kumar ◽  
Stephan Thober ◽  
Oldrich Rakovec ◽  
Niko Wanders ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
General Circulation ◽  
Snow Accumulation ◽  
Low Flow ◽  
Model Ensemble ◽  
Daily Streamflow ◽  
Low Flows ◽  
Future Global Warming ◽  
The Mediterranean

Abstract. There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000 km2. The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-the-art hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5 km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90 % of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from −12 % under 1.5 K, compared to the baseline period 1971–2000, to −35 % under global warming of 3 K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5 K) to +45 % (3 K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2 K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of period-averaged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multi-model ensemble as well as its single members in the adaptation process.

scholarly journals Effects of Forest Harvesting on Warm-Season Low Flows in the Pacific Northwest: A Review

2020 ◽  
Vol 4 (1) ◽  
pp. 29
Author(s):  
R.D. (Dan) Moore ◽  
Stefan Gronsdahl ◽  
Richard McCleary
Keyword(s):  
Pacific Northwest ◽  
Forest Disturbance ◽  
Fish Habitat ◽  
Warm Season ◽  
Forest Harvesting ◽  
Low Flow ◽  
Post Harvest ◽  
Low Flows ◽  
The Pacific ◽  
Paired Catchment

Paired-catchment studies conducted on small (< 10 km2) rain-dominated catchments revealed that forest harvesting resulted in a period of increased warm-season low flows ranging from less than five years to more than two decades, consistent with the results of stand-level studies and process considerations. Of the five paired-catchment studies in snow-dominated regions, none revealed a statistically significant change in warm-season low flows in the first decade following harvest, although two exhibited non-significant higher flows in August and September and one had lower flows. Two studies, one of rain-dominated catchments and one of snow-dominated catchments, found that summer low flows became more severe (i.e., lower) about two decades or so following harvest. These longer-term results indicate that indices such as equivalent clearcut area, as currently calculated using monotonic recovery curves, may not accurately reflect the nature of post-harvest changes in low flows. Studies focussed on medium to large catchments (tens to thousands of km2 in area) found either no statistically significant relations between warm-season low flows and forest disturbance, or inconsistent responses. Attempts to synthesize existing studies are hampered by the lack of a common low-flow metric among studies, as well as detailed information on post-harvest vegetation changes. Further fieldresearch and process-based modelling is required to help elucidate the underlying processes leading to the results from these paired-catchment studies and to enhance the ability to predict streamflow responses to forest harvesting, especially in the context of a changing climate. KEYWORDS: streamflow; forestry; low flows; fish habitat; hydrologic recovery

scholarly journals Altitudinal dependency of snow amounts in two small alpine catchments: can catchment-wide snow amounts be estimated via single snow or precipitation stations?

2011 ◽  
Vol 52 (58) ◽  
pp. 153-158 ◽  
Author(s):  
Thomas Grünewald ◽  
Michael Lehning
Keyword(s):  
Laser Scanning ◽  
Snow Water Equivalent ◽  
Altitudinal Gradients ◽  
Mountainous Regions ◽  
Winter Snow ◽  
Catchment Areas ◽  
Scale Models ◽  
Snow Water ◽  
Snow Distribution ◽  
Alpine Catchments

AbstarctThe spatial distribution and the local amount of snow in mountainous regions strongly depend on the spatial characteristics of snowfall, snow deposition and snow redistribution. Uniform altitudinal gradients can only represent a part of these influences but are without alternative for use in larger-scale models. How well altitudinal gradients represent the true snow distribution has not been assessed. We analyse altitudinal characteristics of snow stored in two high-alpine catchments in Switzerland. Peak winter snow depths were monitored using high-resolution airborne laser scanning technology. These snow depths were transferred to snow water equivalent by applying simple density estimations. From these data, altitudinal gradients were calculated for the total catchment areas and for selected subareas characterized by different accumulation patterns. These gradients were then compared with gradients resulting from automated snow depth measurements obtained from several snow stations on different height levels located in the catchments, and with estimations from climatological precipitation gradients. The analysis showed that neither precipitation gradients nor flat-field stations estimate catchment-wide snow amounts accurately. While the climatological gradient showed different trends for different areas and years, the snow stations tended to overestimate mean snow amounts.

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