Quantifying the role of the snowpack in generating water available for run‐off during rain‐on‐snow events from snow pillow records

Rain‐on‐snow events have generated major floods around the world, particularly in coastal, mountainous regions. Most previous studies focused on a limited number of major rain‐on‐snow events or were based primarily on model results, largely due to a lack of long‐term records from lysimeters or other instrumentation for quantifying event water balances. In this analysis, we used records from five automated snow pillow sites in south coastal British Columbia, Canada, to reconstruct event water balances for 286 rain‐on‐snow events over a 10‐year period. For large rain‐on‐snow events (event rainfall >40 mm), snowmelt enhanced the production of water available for run‐off (WAR) by approximately 25% over rainfall alone. For smaller events, a range of antecedent and meteorological factors influenced WAR generation, particularly the antecedent liquid water content of the snowpack. Most large events were associated with atmospheric rivers. Rainfall dominated WAR generation during autumn and winter events, whereas snowmelt dominated during spring and summer events. In the majority of events, the sensible heat of rain contributed less than 10% of the total energy consumed by snowmelt. This analysis illustrated the importance of understanding the amount of rainfall occurring at high elevations during rain‐on‐snow events in mountainous regions.     

Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (T_B) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatio‐temporal controls of snowmelt and runoff generation during rain‐on‐snow events in a mid‐latitude mountain catchment

A network of 30 standalone snow monitoring stations was used to investigate the snow cover distribution, snowmelt dynamics, and runoff generation during two rain‐on‐snow (ROS) events in a 40 km² montane catchment in the Black Forest region of southwestern Germany. A multiple linear regression analysis using elevation, aspect, and land cover as predictors for the snow water equivalent (SWE) distribution within the catchment was applied on an hourly basis for two significant ROS flood events that occurred in December 2012. The available snowmelt water, liquid precipitation, as well as the total retention storage of the snow cover were considered in order to estimate the amount of water potentially available for the runoff generation. The study provides a spatially and temporally distributed picture of how the two observed ROS floods developed in the catchment. It became evident that the retention capacity of the snow cover is a crucial mechanism during ROS. It took several hours before water was released from the snowpack during the first ROS event, while retention storage was exceeded within 1 h from the start of the second event. Elevation was the most important terrain feature. South‐facing terrain contributed more water for runoff than north‐facing slopes, and only slightly more runoff was generated at open compared to forested areas. The results highlight the importance of snowmelt together with liquid precipitation for the generation of flood runoff during ROS and the large temporal and spatial variability of the relevant processes. Copyright © 2015 John Wiley & Sons, Ltd.     

Changes to flood peaks of a mountain river: implications for analysis of the 2013 flood in the Upper Bow River,Canada

The mountain headwater Bow River at Banff, Alberta, Canada, was subject to a large flood in June 2013, over which considerable debate has ensued regarding its probability of occurrence. It is therefore instructive to consider what information long‐term streamflow discharge records provide about environmental change in the Upper Bow River basin above Banff. Though protected as part of Banff National Park, since 1885, the basin has experienced considerable climate and land cover changes, each of which has the potential to impact observations, and hence the interpretations of flood probability. The Bow River at Banff hydrometric station is one of Canada's longest‐operating reference hydrological basin network stations and so has great value for assessing changes in flow regime over time. Furthermore, the station measures a river that provides an extremely important water supply for Calgary and irrigation district downstream and so is of great interest for assessing regional water security. These records were examined for changes in several flood attributes and to determine whether flow changes may have been related to landscape change within the basin as caused by forest fires, conversion from grasslands to forest with fire suppression, and regional climate variations and/or trends. Floods in the Upper Bow River are generated by both snowmelt and rain‐on‐snow (ROS) events, the latter type which include flood events generated by spatially and temporally large storms such as occurred in 2013. The two types of floods also have different frequency characteristics. Snowmelt and ROS flood attributes were not correlated significantly with any climate index or with burned area except that snowmelt event duration correlated negatively to the Pacific Decadal Oscillation. While there is a significant negative trend in all floods over the past 100 years, when separated based on generating process, neither snowmelt floods nor large ROS floods associated with mesoscale storms show any trends over time. Despite extensive changes to the landscape of the basin and in within the climate system, the flood regime remains unchanged, something identified at smaller scales in the region but never at larger scales. Copyright © 2016 John Wiley & Sons, Ltd.     

Regional variability in dust‐on‐snow processes and impacts in the Upper Colorado River Basin

Dust deposition onto mountain snow cover in the Upper Colorado River Basin frequently occurs in the spring when wind speeds and dust emission peaks on the nearby Colorado Plateau. Dust loading has increased since the intensive settlement in the western USA in the mid 1880s. The effects of dust‐on‐snow have been well studied at Senator Beck Basin Study Area (SBBSA) in the San Juan Mountains, CO, the first high‐altitude area of contact for predominantly southwesterly winds transporting dust from the southern Colorado Plateau. To capture variability in dust transport from the broader Colorado Plateau and dust deposition across a larger area of the Colorado River water sources, an additional study plot was established in 2009 on Grand Mesa, 150 km to the north of SBBSA in west central, CO. Here, we compare the 4‐year (2010–2013) dust source, deposition, and radiative forcing records at Grand Mesa Study Plot (GMSP) and Swamp Angel Study Plot (SASP), SBBSA's subalpine study plot. The study plots have similar site elevations/environments and differ mainly in the amount of dust deposited and ensuing impacts. At SASP, end of year dust concentrations ranged from 0.83 mg g^?1 to 4.80 mg g^?1, and daily mean spring dust radiative forcing ranged from 50–65 W m^?2, advancing melt by 24–49 days. At GMSP, which received 1.0 mg g^?1 less dust per season on average, spring radiative forcings of 32–50 W m^?2 advanced melt by 15–30 days. Remote sensing imagery showed that observed dust events were frequently associated with dust emission from the southern Colorado Plateau. Dust from these sources generally passed south of GMSP, and back trajectory footprints modelled for observed dust events were commonly more westerly and northerly for GMSP relative to SASP. These factors suggest that although the southern Colorado Plateau contains important dust sources, dust contributions from other dust sources contribute to dust loading in this region, and likely account for the majority of dust loading at GMSP. Copyright © 2015 John Wiley & Sons, Ltd.     

The June 2013 Alberta Catastrophic Flooding Event: Part 1—Climatological aspects and hydrometeorological features

In June 2013, excessive rainfall associated with an intense weather system triggered severe flooding in southern Alberta, which became the costliest natural disaster in Canadian history. This article provides an overview of the climatological aspects and large‐scale hydrometeorological features associated with the flooding event based upon information from a variety of sources, including satellite data, upper air soundings, surface observations and operational model analyses. The results show that multiple factors combined to create this unusually severe event. The event was characterized by a slow‐moving upper level low pressure system west of Alberta, blocked by an upper level ridge, while an associated well‐organized surface low pressure system kept southern Alberta, especially the eastern slopes of the Rocky Mountains, in continuous precipitation for up to two days. Results from air parcel trajectory analysis show that a significant amount of the moisture originated from the central Great Plains, transported into Alberta by a southeasterly low level jet. The event was first dominated by significant thunderstorm activity, and then evolved into continuous precipitation supported by the synoptic‐scale low pressure system. Both the thunderstorm activity and upslope winds associated with the low pressure system produced large rainfall amounts. A comparison with previous similar events occurring in the same region suggests that the synoptic‐scale features associated with the 2013 rainfall event were not particularly intense; however, its storm environment was the most convectively unstable. The system also exhibited a relatively high freezing level, which resulted in rain, rather than snow, mainly falling over the still snow‐covered mountainous areas. Melting associated with this rain‐on‐snow scenario likely contributed to downstream flooding. Furthermore, above‐normal snowfall in the preceding spring helped to maintain snow in the high‐elevation areas, which facilitated the rain‐on‐snow event. Copyright © 2016 John Wiley & Sons, Ltd.     

Role of temporal resolution of meteorological inputs for process‐based snow modelling

Accurate snow accumulation and melt simulations are crucial for understanding and predicting hydrological dynamics in mountainous settings. As snow models require temporally varying meteorological inputs, time resolution of these inputs is likely to play an important role on the model accuracy. Because meteorological data at a fine temporal resolution (~1 hr) are generally not available in many snow‐dominated settings, it is important to evaluate the role of meteorological inputs temporal resolution on the performance of process‐based snow models. The objective of this work is to assess the loss in model accuracy with temporal resolution of meteorological inputs, for a range of climatic conditions and topographic elevations. To this end, a process‐based snow model was run using 1‐, 3‐, and 6‐hourly inputs for wet, average, and dry years over Boise River Basin (6,963 km²), which spans rain dominated (≤1,400 m), rain–snow transition (>1,400 and ≤1,900 m), snow dominated below tree line (>1,900 and ≤2,400 m), and above tree line (>2,400 m) elevations. The results show that sensitivity of the model accuracy to the inputs time step generally decreases with increasing elevation from rain dominated to snow dominated above tree line. Using longer than hourly inputs causes substantial underestimation of snow cover area (SCA) and snow water equivalent (SWE) in rain‐dominated and rain–snow transition elevations, due to the precipitation phase mischaracterization. In snow‐dominated elevations, the melt rate is underestimated due to errors in estimation of net snow cover energy input. In addition, the errors in SCA and SWE estimates generally decrease toward years with low snow mass, that is, dry years. The results indicate significant increases in errors in estimates of SCA and SWE as the temporal resolution of meteorological inputs becomes coarser than an hour. However, use of 3‐hourly inputs can provide accurate estimates at snow‐dominated elevations. The study underscores the need to record meteorological variables at an hourly time step for accurate process‐based snow modelling.     

Spatial and temporal diversity for debris‐flow meteorological control in subarctic oceanic periglacial environments in Iceland

Slopes in fjord environments of Iceland are prone to debris‐flow initiation, responding to a wide variety of meteorological triggering factors, such as rain on snow, rapid snowmelt, long‐lasting rainfall or intense rainfall. If all fjord regions have similar debris flows with regards to their magnitude, their meteorological control is diverse both in space and in time. Debris flows in Northwest Iceland are triggered mostly by rain‐on‐snow and long‐lasting rainfall, while snowmelt is more characteristic in North Iceland, and rainfall has a clear impact in East Iceland. Most debris‐flow events occur on a single slope, and only a few are recorded at the same time in different regions. Observations of the threshold values underline the diversity of debris‐flow initiation, occurring with huge amounts of sudden water supply as well as with very moderate ones. Copyright © 2007 John Wiley & Sons, Ltd.     

Response of snow processes to climate change: spatial variability in a small basin in the Spanish Pyrenees

In this study, the Cold Regions Hydrological Modelling platform was used to create an alpine snow model including wind redistribution of snow and energy balance snowmelt to simulate the snowpack over the period 1996–2009 in a small (33 ha) snow‐dominated basin in the Spanish Pyrenees. The basin was divided into three hydrological response units (HRUs), based on contrasting physiographic and aerodynamic characteristics. A sensitivity analysis was conducted to calculate the snow water equivalent regime for various combinations of temperature and precipitation that differed from observed conditions. The results show that there was large inter‐annual variability in the snowpack in this region of the Pyrenees because of its marked sensitivity to climatic conditions. Although the basin is small and quite homogeneous, snowpack seasonality and inter‐annual evolution of the snowpack varied in each HRU. Snow accumulation change in relation to temperature change was approximately 20% for every 1 °C, and the duration of the snowpack was reduced by 20–30 days per °C. Melting rates decreased with increased temperature, and wind redistribution of snow was higher with decreased temperature. The magnitude and sign of changes in precipitation may markedly affect the response of the snowpack to changes in temperature. There was a non‐linear response of snow to individual and combined changes in temperature and precipitation, with respect to both the magnitude and sign of the change. This was a consequence of the complex interactions among climate, topography and blowing snow in the study basin. Copyright © 2012 John Wiley & Sons, Ltd.     

Estimating the distribution of snow water equivalent and snow extent beneath cloud cover in the Salt–Verde River basin,Arizona

The temporal and spatial continuity of spatially distributed estimates of snow‐covered area (SCA) are limited by the availability of cloud‐free satellite imagery; this also affects spatial estimates of snow water equivalent (SWE), as SCA can be used to define the extent of snow telemetry (SNOTEL) point SWE interpolation. In order to extend the continuity of these estimates in time and space to areas beneath the cloud cover, gridded temperature data were used to define the spatial domain of SWE interpolation in the Salt–Verde watershed of Arizona. Gridded positive accumulated degree‐days (ADD) and binary SCA (derived from the Advanced Very High Resolution Radiometer (AVHRR)) were used to define a threshold ADD to define the area of snow cover. The optimized threshold ADD increased during snow accumulation periods, reaching a peak at maximum snow extent. The threshold then decreased dramatically during the first time period after peak snow extent owing to the low amount of energy required to melt the thin snow cover at lower elevations. The area having snow cover at this later time was then used to define the area for which SWE interpolation was done. The area simulated to have snow was compared with observed SCA from AVHRR to assess the simulated snow map accuracy. During periods without precipitation, the average commission and omission errors of the optimal technique were 7% and 11% respectively, with a map accuracy of 82%. Average map accuracy decreased to 75% during storm periods, with commission and omission errors equal to 11% and 12% respectively. The analysis shows that temperature data can be used to help estimate the snow extent beneath clouds and therefore improve the spatial and temporal continuity of SCA and SWE products. Copyright © 2004 John Wiley & Sons, Ltd.     

The June 2013 Alberta catastrophic flooding event – part 2: fine‐scale precipitation and associated features

Data obtained from a variety of sources including the Canadian Lightning Detection Network, weather radars, weather stations and operational numerical weather model analyses were used to address the evolution of precipitation during the June 2013 southern Alberta flood. The event was linked to a mid‐level closed low pressure system to the west of the region and a surface low pressure region initially to its south. This configuration brought warm, moist unstable air into the region that led to dramatic, organized convection with an abundance of lightning and some hail. Such conditions occurred in the southern parts of the region whereas the northern parts were devoid of lightning. Initially, precipitation rates were high (extreme 15‐min rainfall rates up to 102 mm h^?1 were measured) but decreased to lower values as the precipitation shifted to long‐lived stratiform conditions. Both the convective and stratiform precipitation components were affected by the topography. Similar flooding events, such as June 2002, have occurred over this region although the 2002 event was colder and precipitation was not associated with substantial convection over southwest Alberta. Copyright © 2016 Her Majesty the Queen in Right of Canada. Hydrological Processes. © John Wiley & Sons, Ltd.     

On the role of spatial resolution on snow estimates using a process‐based snow model across a range of climatology and elevation

Hydrological processes in mountainous settings depend on snow distribution, whose prediction accuracy is a function of model spatial scale. Although model accuracy is expected to improve with finer spatial resolution, an increase in resolution comes with modelling costs related to increased computational time and greater input data and parameter information. This computational and data collection expense is still a limiting factor for many large watersheds. Thus, this work's main objective is to question which physical processes lead to loss in model accuracy with regard to input spatial resolution under different climatic conditions and elevation ranges. To address this objective, a spatially distributed snow model, iSnobal, was run with inputs distributed at 50‐m—our benchmark for comparison—and 100‐m resolutions and with aggregated (averaged from the fine to the large resolution) inputs from the 50‐m model to 100‐, 250‐, 500‐, and 750‐m resolution for wet, average, and dry years over the Upper Boise River Basin (6,963 km²), which spans four elevation bands: rain dominated, rain–snow transition, and snow dominated below treeline and above treeline. Residuals, defined as differences between values quantified with high resolution (>50 m) models minus the benchmark model (50 m), of simulated snow‐covered area (SCA) and snow water equivalent (SWE) were generally slight in the aggregated scenarios. This was due to transferring the effects of topography on meteorological variables from the 50‐m model to the coarser scales through aggregation. Residuals in SCA and SWE in the distributed 100‐m simulation were greater than those of the aggregated 750 m. Topographic features such as slope and aspect were simplified, and their gradient was reduced due to coarsening the topography from the 50‐ to 100‐m resolution. Therefore, solar radiation was overestimated, and snow drifting was modified and caused substantial SCA and SWE underestimation in the distributed 100‐m model relative to the 50‐m model. Large residuals were observed in the wet year and at the highest elevation band when and where snow mass was large. These results support that model accuracy is substantially reduced with model scales coarser than 50 m.     

Long‐term investigations of the snow cover in a subalpine semi‐forested catchment

To improve spring runoff forecasts from subalpine catchments, detailed spatial simulations of the snow cover in this landscape is obligatory. For more than 30 years, the Swiss Federal Research Institute WSL has been conducting extensive snow cover observations in the subalpine watershed Alptal (central Switzerland). This paper summarizes the conclusions from past snow studies in the Alptal valley and presents an analysis of 14 snow courses located at different exposures and altitudes, partly in open areas and partly in forest. The long‐term performance of a physically based numerical snow–vegetation–atmosphere model (COUP) was tested with these snow‐course measurements. One single parameter set with meteorological input variables corrected to the prevailing local conditions resulted in a convincing snow water equivalent (SWE) simulation at most sites and for various winters with a wide range of snow conditions. The snow interception approach used in this study was able to explain the forest effect on the SWE as observed on paired snow courses. Finally, we demonstrated for a meadow and a forest site that a successful simulation of the snowpack yields appropriate melt rates. Copyright © 2006 John Wiley & Sons, Ltd.     

Influences of forest on MODIS snow cover mapping and snow variations in the Amur River basin in Northeast Asia during 2000–2014

The study applies the improved cloud‐free moderate resolution imaging spectral radiometer daily snow cover product (MODMYD_MC) to investigate the snow cover variations from snow hydrologic year (HY) HY2000 to HY2013 in the Amur River basin (ARB), Northeast Asia. The fractions of forest cover were 38%, 63%, and 47% in 2009 in China (the southern ARB), Russia (the northern ARB), and ARB, respectively. Validation results show that MODMYD_MC has a snow agreement of 88% against in situ snow depth (SD) observations (SD ≥ 4 cm). The agreement is about 10% lower at the forested stations than at the nonforested stations. Snow cover durations (SCDs) from MODMYD_MC are 20 days shorter than ground observations (SD ≥ 1 cm) at the forested stations, whereas they are just 8 days shorter than ground observations (SD ≥ 1 cm) at the nonforested stations. Annual mean SCDs from MODMYD_MC in the forested areas are 21 days shorter than those in the nearby farmland in the Sanjiang Plain. This indicates forest has a complex influence on the snow accumulation and melting processes and even on optical satellite snow cover mapping. Meanwhile, SCD and mean snow cover are negatively correlated with air temperature in ARB, especially in the snow melting season, when mean air temperature in March and April can explain 86% and 74% of the mean snow cover variations in China ARB and Russia ARB, respectively. From 1961 to 2015, the annual mean air temperature presented an increased trend by 0.33 °C/decade in both China ARB and Russia ARB, whereas it had a decrease trend from HY2000 to HY2013. The decrease of air temperature led to an increase of snow cover, which is different from the global decrease trend of snow cover variations. SCD and snow cover had larger increase rates in China ARB than in Russia ARB, and they were larger in the forested areas than in the nearby farmland in the Sanjiang Plain.     

Coupling of a simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

Snow and frozen soil prevail in cold regions worldwide, and the integration of these processes is crucial in hydrological models. In this study, a combined model was developed by fully coupling a simultaneous heat and water model with a geomorphologically based distributed hydrological model. The combined model simulates vertical and lateral water transfer as well as vertical heat fluxes and is capable of representing the effects of frozen soil and snowmelt on hydrological processes in cold regions. This model was evaluated by using in situ observations in the Binggou watershed, an experimental watershed for cold region hydrology of the Watershed Allied Telemetry Experimental Research Project. Results showed that the model was able to predict soil freezing and thawing, unfrozen soil water content, and snow depth reasonably well. The simulated hydrograph was in good agreement with the in situ observation. The Nash–Sutcliffe coefficient of daily discharge was 0.744 for the entire simulation period, 0.472 from April to June, and 0.711 from June to November. This model can improve our understanding of hydrological processes in cold regions and assess the impacts of global warming on hydrological cycles and water resources. Copyright © 2012 John Wiley & Sons, Ltd.     

Changes in seasonality and timing of peak streamflow in snow and semi‐arid climates of the north‐central United States, 1910–2012

Changes in the seasonality and timing of annual peak streamflow in the north‐central USA are likely because of changes in precipitation and temperature regimes. A source of long‐term information about flood events across the study area is the U.S. Geological Survey peak streamflow database. However, one challenge of answering climate‐related questions with this dataset is that even in snowmelt‐dominated areas, it is a mixed population of snowmelt/spring rain generated peaks and summer/fall rain generated peaks. Therefore, a process was developed to divide the annual peaks into two populations, or seasons, snowmelt/spring, and summer/fall. The two series were then tested for the hypotheses that because of changes in precipitation regimes, the odds of summer/fall peaks have increased and, because of temperature changes, snowmelt/spring peaks happen earlier. Over climatologically and geographically similar regions in the north‐central USA, logistic regression was used to model the odds of getting a summer/fall peak. When controlling for antecedent wet and dry conditions and geographical differences, the odds of summer/fall peaks occurring have increased across the study area. With respect to timing within the seasons, trend analysis showed that in northern portions of the study region, snowmelt/spring peaks are occurring earlier. The timing of snowmelt/spring peaks in three regions in the northern part of the study area is earlier by 8.7– 14.3 days. These changes have implications for water interests, such as potential changes in lead‐time for flood forecasting or changes in the operation of flood‐control dams. Copyright © 2015 John Wiley & Sons, Ltd.     

First‐year sea ice spring melt transitions in the Canadian Arctic Archipelago from time‐series synthetic aperture radar data, 1992–2002

This paper synthesizes 10‐years' worth of interannual time‐series space‐borne ERS‐1 and RADARSAT‐1 synthetic aperture radar (SAR) data collected coincident with daily measurement of snow‐covered, land‐fast first‐year sea ice (FYI) geophysical and surface radiation data collected from the Seasonal Sea Ice Monitoring and Modeling Site, Collaborative‐Interdisciplinary Cryospheric Experiment and 1998 North Water Polynya study over the period 1992 to 2002. The objectives are to investigate the seasonal co‐relationship of the SAR time‐series dataset with selected surface mass (bulk snow thickness) and climate state variables (surface temperature and albedo) measured in situ for the purpose of measuring the interannual variability of sea ice spring melt transitions and validating a time‐series SAR methodology for sea ice surface mass and climate state parameter estimation. We begin with a review of the salient processes required for our interpretation of time‐series microwave backscatter from land‐fast FYI. Our results suggest that time‐series SAR data can reliably measure the timing and duration of surface albedo transitions at daily to weekly time‐scales and at a spatial scales that are on the order of hundreds of metres. Snow thickness on FYI immediately prior to melt onset explains a statistically significant portion of the variability in timing of SAR‐detected melt onset to pond onset for SAR time‐series that are made up of more than 25 images. Our results also show that the funicular regime of snowmelt, resolved in time‐series SAR data at a temporal resolution of approximately 2·5 images per week, is not detectable for snow covers less than 25 cm in thickness. Copyright © 2007 John Wiley & Sons, Ltd.     

The droughts of 1996–1997 and 2004–2005 in Amazonia: hydrological response in the river main‐stem

Severe hydrological droughts in the Amazon have generally been associated with strong El Niño events. More than 100 years of stage record at Manaus harbour confirms that minimum water levels generally coincide with intense warming in the tropical Pacific sea waters. During 2005, however, the Amazon experienced a severe drought which was not associated with an El Niño event. Unless what usually occurs during strong El Niño events, when negative rainfall anomalies usually affect central and eastern Amazon drainage basin; rainfall deficiencies in the drought of 2005 were spatially constrained to the west and southwest of the basin. In spite of this, discharge stations at the main‐stem recorded minimum water levels as low as those observed during the basin‐wide 1996–1997 El Niño‐related drought. The analysis of river discharges along the main‐stem and major tributaries during the drought of 2004–2005 revealed that the recession on major tributaries began almost simultaneously. This was not the case in the 1996–1997 drought, when above‐normal contribution of some tributaries for a short period during high water was crucial to partially counterbalance high discharge deficits of the other tributaries. Since time‐lagged contributions of major tributaries are fundamental to damp the extremes in the main‐stem, an almost coincident recession in almost all tributaries caused a rapid decrease in water discharges during the 2005 event. Copyright © 2010 John Wiley & Sons, Ltd.     

Variability and trends in the annual snow‐cover cycle in Northern Hemisphere land areas, 1972–2000

This study investigated variability and trends in the annual snow‐cover cycle in regions covering high‐latitude and high‐elevation land areas in the Northern Hemisphere. The annual snow‐cover cycle was examined with respect to the week of the last‐observed snow cover in spring (WLS), the week of the first‐observed snow cover in autumn (WFS), and the duration of the snow‐free period (DSF). The analysis used a 29‐year time‐series (1972–2000) of weekly, visible‐band satellite observations of Northern Hemisphere snow cover from NOAA with corrections applied by D. Robinson of Rutgers University Climate Laboratory. Substantial interannual variability was observed in WLS, WFS and DSF (standard deviations of 0·8–1·1, 0·7–0·9 and 1·0–1·4 weeks, respectively), which is related directly to interannual variability in snow‐cover area in the regions and time periods of snow‐cover transition. Over the nearly three‐decade study period, WLS shifted earlier by 3–5 days/decade as determined by linear regression analysis. The observed shifts in the annual snow‐cover cycle underlie a significant trend toward a longer annual snow‐free period. The DSF increased by 5–6 days/decade over the study period, primarily as a result of earlier snow cover disappearance in spring. The observed trends are consistent with reported trends in the timing and length of the active growing season as determined from satellite observations of vegetation greenness and the atmospheric CO₂ record. Copyright © 2002 John Wiley & Sons, Ltd.     

Influence of species and rain event characteristics on stemflow volume in a temperate mixed oak–beech stand

This study aimed at analysing the effects of biological and meteorological factors on stemflow generation in a temperate mixed oak (Quercus petraea Liebl.) and beech (Fagus sylvatica L.) stand. A statistical model was developed to predict single‐event individual stemflow volume from trunk circumference and rainfall depth allowing mechanistic stemflow parameters to be deduced from the model, namely stemflow rates (SF_rate), storage of water on tree organs (S_t) and rainfall thresholds for stemflow (RF_min). SF_rate and S_t increased with increasing trunk circumference while RF_min was not significantly influenced by tree size. RF_min and, for a given tree size, S_t were higher for oak than for beech, and inversely for SF_rate. For each species, RF_min was higher for the leaved season than for the leafless period, while the opposite was found for SF_rate, and S_t was not significantly affected by the season. Increasing wind speed during rain increased SF_rate, lowered RF_min and did not influence S_t. In contrast, S_t and RF_min tended, respectively, to decrease and to increase with increasing values of the ratio between the cumulated potential evaporation during the dry period preceding the rain event and the volume of the preceding rainfall (Eva p_ADP/R_previous). Stemflow volume, which results from the combined effects of the previous parameters, was higher for beech than for oak and also higher during the leafless period than during the leaved period; these differences were large for the smallest events but decreased rapidly as rainfall depth increased. In addition, an enhancing and a depressing effect on stemflow volume were shown for the average wind speed during rain and for the ratio Eva p_ADP/R_previous, respectively. Copyright © 2008 John Wiley & Sons, Ltd.