Snowmelt Period Research Articles

GNSS-R-Based Snow Water Equivalent Estimation with Empirical Modeling and Enhanced SNR-Based Snow Depth Estimation

Snow depth and snow water equivalent (SWE) are two parameters for measuring snowfall. By exploiting the Global Navigation Satellite System reflectometry (GNSS-R) technique and thousands of existing GNSS Continuous Operating Reference Stations (CORS) deployed in the cryosphere, it is possible to improve the temporal and spatial resolutions of the SWE measurement. In this paper, a fusion model for combining multi-satellite SNR (Signal to Noise Ratio) snow depth estimations is proposed, which uses peak spectral powers associated with each of the snow depth estimations. To simplify the estimation of SWE, the complete snowfall period over a winter season is split into snow accumulation, transition, and melting period in accordance with the variation characteristics of snow depth and SWE. By extensively using in situ snow depth and SWE observations recorded by snow telemetry network (SNOTEL) and regression analysis, three empirical models are developed to describe the relationship between snow depth and SWE for the three periods, respectively. Based on the snow depth fusion model and the SWE empirical models, an SWE estimation algorithm is proposed. Three data sets recorded in different environments are used to test the proposed method. The results demonstrate that there exists good agreement between the in situ SWE measurements and the SWE estimates produced by the proposed method; the root-mean-square error of SWE estimations is smaller than 6 cm when the SWE is up to 80 cm.

Snowmelt periods as hot moments for soil N dynamics: a case study in Maine, USA.

The vernal transition represents the seasonal transition to spring, occurring as temperatures rise at the end of winter. With rapid snowmelt, microbial community turnover, and accelerated nutrient cycling, this is a critical but relatively under-studied period of ecosystem function. We conducted a study over two consecutive winters (2015-2016) at the Bear Brook Watershed in Maine to examine how changing winter conditions (warming winters, reduced snow accumulation) altered soil nitrogen availability and stream N export during winter and the vernal transition, and how these patterns were influenced by ecosystem N status (N-enriched vs. N-limited). Of the two study years, 2016 had a warmer winter with substantially less snow accumulation and a discontinuous snowpack-and as a result, had a longer vernal transition and a snowpack that thawed before the vernal transition began. Across both years, snowmelt triggered a transition, signaled by increased ammonium concentrations in soil, decreased soil nitrate concentrations due to flushing by meltwater, and increased stream nitrate exports. Despite the contrasting winter conditions, both years showed similar patterns in N availability and export, differing only in the timing of these transitions. The vernal transition has conventionally been considered a critical period for biogeochemical cycling, because the associated snowmelt event triggers physicochemical and biochemical changes in soil systems. This was consistent with our results in 2015, but our data for 2016 show that this may not always hold true, and instead, that warmer, low-snow winters may demonstrate a temporal asynchrony between snowmelt and the vernal transition. We also show that ecosystem N status is a strong driver of the seasonal N pattern, and the interaction of N status and changing climate must be further investigated to understand ecosystem function under our current predicted trajectory of warming winters, declining snowfall, and winter thaw events.

Seasonal snow cover decreases young water fractions in high Alpine catchments

AbstractEstimation of young water fractions (Fyw), defined as the fraction of water in a stream younger than approximately 2–3 months, provides key information for water resource management in catchments where runoff is dominated by snowmelt. Knowing the average dependence of summer flow on winter precipitation is an essential context for comparing regional drought severity and provides the hydrological template for downstream water users and ecosystems. However, Fyw estimation based on seasonal signals of stable isotopes of oxygen and hydrogen has not yet explicitly addressed how to parsimoniously include the seasonal shift of water input from snow. Using experimental data from three high‐elevation, Alpine catchments (one dominated by glacier and two by snow), we propose a framework to explicitly include the delays induced by snow storage into estimates of Fyw. Scrutinizing the key methodological choices when estimating Fyw from isotope data, we find that the methods used to construct precipitation input signals from sparse isotope samples can significantly impact Fyw. Given this sensitivity, our revised procedure estimates a distribution of Fyw values that incorporates a wide range of possible methodological choices and their uncertainties; it furthermore compares the commonly used amplitude ratio approach to a direct convolution approach, which circumvents the assumption that the isotopic signals have a sine curve shape, an assumption that is generally violated in snow‐dominated environments. Our new estimates confirm that high‐elevation Alpine catchments have low Fyw values, spanning from 8 to 11%. Such low values have previously been interpreted as the impact of seasonal snow storage alone, but our comparison of different Fyw estimation methods suggests that these low Fyw values result from a combination of both snow cover effects and longer storage in the subsurface. In contrast, in the highest elevation, glacier dominated catchment, Fyw is 3–4 times greater compared to the other two catchments, due to the lower storage and faster drainage processes. A future challenge, capturing spatio‐temporal snowmelt isotope signals during winter baseflow and the snowmelt period, remains to improve constraints on the Fyw estimation technique.

Role of water percolation in reproductive physiology of hazelnut (Corylus spp.)

Hazelnut (Corylus spp.) flowering occurs during late winters and early spring which coincides with erratic fluctuating weather patterns. Irregular and reduced precipitation, especially in the form of snow, is assumed to dictate poor flowering and enhanced injury to catkins, especially in the sourced cultivars of interest to growers. We investigated the effect of water (precipitation received as rain and or snow) percolation during snowmelt period using phenological endpoints such as female flower ratio, bud position of female flower occurrence, and catkin dehiscence in sourced and locally adapted cultivars. These reproductive events were also analyzed for biochemical endpoints such as the concentrations of tryptophan, serotonin and melatonin in temporally collected bud or catkin samples. In addition, the yield responses of the tagged twigs were tracked and analyzed. When snow was consistently removed from the root zone (NS) or when a prior placed plastic sheet (P) disallowed water percolation, the percentage of female flowers and apical dominance declined in the sourced cultivars suggesting an erratic gradient between aerial and belowground temperature. The presence of snow cover resulted in increased probability of female flowers from dormant buds in sourced cultivars. Tryptophan was found to accumulate in the dormant buds of sourced cultivars where snow was not disturbed, while serotonin concentrations were significantly higher in NS and P treatments. Melatonin concentrations were notably high in dormant flower and vegetative buds of locally adapted cultivars especially subjected to P treatment. The biochemical markers may not only assist in identifying cold tolerance but also reveal abiotic stress negating responses modulated by relative concentrations of these molecules. Our results demonstrate that ideal conditions of good precipitation, especially as snow, would not only blanket to provide thermoregulation but also maintain the sensitive gradient on which temperate trees rely to break dormancy and initiate flower development. These findings also suggest that the use of horticultural alternatives such as thermal mulch could be an option for mitigating adverse conditions of reduced water percolation which affect reproductive physiology of hazelnut.

Response of carbon and microbial properties to risk elements pollution in arctic soils

A 180-day incubation study was conducted to evaluate the effects of risk elements (REs) on organic carbon use and microbial activities in organic soils in the Arctic during the summer snowmelt period. Soils were artificially spiked with Cd, Pb, Cr, Ni, Cu, As, and a combination of these REs according to the levels measured in Arctic soils from REs-polluted industrial sites. During the incubation period, microbial activities and microbial biomass carbon (MBC) formation were inhibited, and microbial quotient (qCO2) values were relatively high in the spiked soils indicating that more energy was used by microbes for maintenance under REs stress. Meanwhile, microbial metabolism was significantly restrained. Microbial Specific phospholipid fatty acids (PLFAs) were reduced in RE spiked soils relative to the control, especially in the As- and multi-RE-spiked soils. The abundance of both fungi and bacteria was reduced in response to RE amendments by 14–24% and 1–55%, respectively. PLFA biomarkers indicated a shift in soil microbial community structure and activities influenced by REs, consequently having a negative effect on soil organic carbon degradation. This study addresses the knowledge gap regarding the alternation of biochemical reactions in Arctic soils under anthropogenic REs with relevant contamination levels.

Quantitative Soil Wind Erosion Potential Mapping for Central Asia Using the Google Earth Engine Platform

A lack of long-term soil wind erosion data impedes sustainable land management in developing regions, especially in Central Asia (CA). Compared with large-scale field measurements, wind erosion modeling based on geospatial data is an efficient and effective method for quantitative soil wind erosion mapping. However, conventional local-based wind erosion modeling is time-consuming and labor-intensive, especially when processing large amounts of geospatial data. To address this issue, we developed a Google Earth Engine-based Revised Wind Erosion Equation (RWEQ) model, named GEE-RWEQ, to delineate the Soil Wind Erosion Potential (SWEP). Based on the GEE-RWEQ model, terabytes of Remote Sensing (RS) data, climate assimilation data, and some other geospatial data were applied to produce monthly SWEP with a high spatial resolution (500 m) across CA between 2000 and 2019. The results show that the mean SWEP is in good agreement with the ground observation-based dust storm index (DSI), satellite-based Aerosol Optical Depth (AOD), and Absorbing Aerosol Index (AAI), confirming that GEE-RWEQ is a robust wind erosion prediction model. Wind speed factors primarily determined the wind erosion in CA (r = 0.7, p < 0.001), and the SWEP has significantly increased since 2011 because of the reversal of global terrestrial stilling in recent years. The Aral Sea Dry Lakebed (ASDLB), formed by shrinkage of the Aral Sea, is the most severe wind erosion area in CA (47.29 kg/m2/y). Temporally, the wind erosion dominated by wind speed has the largest spatial extent of wind erosion in Spring (MAM). Meanwhile, affected by the spatial difference of the snowmelt period in CA, the wind erosion hazard center moved from the southwest (Karakum Desert) to the middle of CA (Kyzylkum Desert and Muyunkum Desert) during spring. According to the impacts of land cover change on the spatial dynamic of wind erosion, the SWEP of bareland was the highest, while that of forestland was the lowest.

Long-term forecast of changes in soil erosion losses during spring snowmelt caused by climate within the plain part of Ukraine

The paper deals with the forecast of changes in erosion soil losses during the spring snowmelt due to climate change in the regions of Ukraine in the middle of the 21st century (during 2031–2050) and at its end (during 2081–2100) compared with the values of the baseline period (1961–1990). The forecast is based on the use of the so-called “hydrometeorological factor of spring soil loss”. This factor is a part of the physical-statistical mathematical model of soil erosion lossduring spring snowmelt, developed at the Department of Physical Geography of Odesa I. I. Mechnikov State (since 2000 — National) University during the 1980s – 1990s. The long-term average value of the hydrometeorological factor is linearly related to the long-term average value of spring erosion soil loss. Therefore, the relative change in the hydrometeorological factor corresponds to the relative change in soil erosion losses. The developed methodology for assessing climate-induced changes in soil erosion losses in five regions of Ukraine (North, West, Center, East and South) takes into account the change in water equivalent of snow cover at the beginning of snow melting, the change in surface runoff and its turbidity, and changes in soil erodibility. The forecast of changes in erosion soil loss was carried out using projections of annual and monthly average air temperatures and precipitation for 2031–2050 and 2081–2100 in accordance with scenario A1B from AR4 of the IPCC. As a result of the research, it was found that both in the middle and at the end of the 21st century a decrease in the rate of soil erosion during the period of spring snowmelt is expected. During 2031–2050, the expected soil losses will be less than corresponding baseline period values within the West region by 79%, within the North and East regions by 81%, and within the Center region by 85%. In the South region, the spring soil losses will be zero due to the lack of snow cover. During 2081–2100 snow cover will be absent not only in the South region, but also in the Center and East regions. In the regions North and West snow cover will remain, but the spring soil erosion losses will decrease by dozens of times and will be so small that they can also be ignored.

Estimation of snow meltwater based on the energy and mass processes during the soil thawing period in seasonally frozen soil areas

In seasonally frozen soil areas, voluminous meltwater forms during the melting period with frequent winds. Research on the energy and mass processes during this snow-melting period and on methods for estimating the amount of meltwater needs to be further improved. In this paper, a real-time snow melt detector (RSMD) was developed to monitor the amount of meltwater and water vapor (the sum of snow sublimation and meltwater evaporation(SVS)) simultaneously at constant wind speeds of 3.2 m/s and 0 m/s. Based on the monitoring results, we use the snow-blown energy coefficient (EC) to describe the effect of wind on snow ablation and the mass coefficient (MC) to describe the meltwater proportion. Based on the law of mass conservation, a formula for estimating meltwater was established with the occurrence probability of different wind speeds as the main variable. The local meltwater ratio of this study was 0.726. Higher ambient temperatures inhibit SVS. Wind greatly increases SVS. In most cases, wind can reduce the amount of meltwater. The EC under a 3.2 m/s wind speed was 50~150%. These research results have important significance for understanding the snow melting process and efficiently guiding agricultural irrigation and water resource development.

Observed characteristics of the water and heat transfer of the soil–snow–atmosphere system through the snowpack in the eastern Tibetan Plateau

Snow cover on the Tibetan Plateau (TP) affects the surface heating in spring and then modulates the Asian summer monsoon. The snow of the TP is known for the thin thickness and rapid change, different from that in high-latitude areas. However, many reanalysis data and model products cannot well capture the variation of the TP snow, partly related to poorly understanding of water and heat transfer through the snowpack. Using the observation data, this study documents the characteristics of water-heat transfer and effective thermal conductivity of a snowpack that lasted more than five months in the eastern TP. The main results are as follows: The negative sensible heat flux (H) prevailed during the snow cover period and nearly half energy of latent heat flux (LE) was derived from H. With the melting of snow, H and LE increased rapidly, and strong LE persisted for more than a month. Diurnal snow albedo presented an asymmetric U-shaped pattern, with the minimum value at 13:00–16:00. The snow albedo around noon mostly ranged from 0.6 to 0.8 and can reach 0.95 for the fresh snow. Frequency of strong temperature gradients was significantly higher in the upper and bottom snowpack than in the middle, in which the largest gradient (151.8 °C m−1) appeared in November. The proportion of weak gradients was much less than that in other areas. Duration of isothermal snowpack is transient during the snow melting period. The soil heat flux at −0.05 m increased almost linearly throughout the snow cover period, and the turning point from negative to positive appeared in late March. Around noon in late March, the upper snow layer was warmer than the bottom layer, and the snow temperature increased gradually from bottom to top in afternoon, opposite to the previous pattern. The effective thermal conductivity of snow slowly increased from November to mid-February and increased dramatically in late March, whose average values were 0.075 ± 0.02 W m−1 K−1 for the bottom snow (0.01–0.08 m) and 0.04 ± 0.013 W m−1 K−1 for 0.01–0.15 m. This study will bring to light the verification and simulation of the TP snow.

Soil erosion and radiocesium migration during the snowmelt period in grasslands and forested areas of Miyagi prefecture, Japan.

This study aimed to examine the influence of snowmelt on soil erosion processes in mountainous landscapes in the Miyagi prefecture of Japan. The investigated slopes had different expositions and were covered with grasslands and forests. The snowpack thickness, soil frost depth, volume of surface runoff, physicochemical properties of the soil and sediments, cesium composition of the snow and meltwater, and air dose rate were determined. In mid-February, snow cover reached its maximum thickness (100-179cm). In the forest, the snow depth was always lower by 15-20cm. The soil did not freeze in winter in any of the plots. Surface runoff was observed only in the grassland plots and depended on the slope aspect. The total volume of surface runoff ranged from 31 to 52mm and snowmelt soil losses ranged from 2 to 9kgha-1 DM. Radiocesium concentrations in runoff samples ranged from 0.1 to 8.4BqL-1, below the standard limit for drinking water in Japan (10BqL-1). The average organic matter content of the sampled sediments was 0.4%, higher than that in the surface soil. The silt fraction in sediments became dominant for particle size distribution, and the activity concentration of total radiocesium was, on average, 250Bqkg-1. The air dose rate was always lower than the maximum permissible level (0.2μSvh-1) and varied from 0.02 to 0.09μSvh-1 in winter, and from 0.08 to 0.13μSvh-1 at times of the year without snow.

Snow melt stimulates ecosystem respiration in Arctic ecosystems.

Cold seasons in Arctic ecosystems are increasingly important to the annual carbon balance of these vulnerable ecosystems. Arctic winters are largely harsh and inaccessible leading historic data gaps during that time. Until recently, cold seasons have been assumed to have negligible impacts on the annual carbon balance but as data coverage increases and the Arctic warms, the cold season has been shown to account for over half of annual methane (CH4 ) emissions and can offset summer photosynthetic carbon dioxide (CO2 ) uptake. Freeze-thaw cycle dynamics play a critical role in controlling cold season CO2 and CH4 loss, but the relationship has not been extensively studied. Here, we analyze freeze-thaw processes through in situ CO2 and CH4 fluxes in conjunction with soil cores for physical structure and porewater samples for redox biogeochemistry. We find a movement of water toward freezing fronts in soil cores, leaving air spaces in soils, which allows for rapid infiltration of oxygen-rich snow melt in spring as shown by oxidized iron in porewater. The snow melt period coincides with rising ecosystem respiration and can offset up to 41% of the summer CO2 uptake. Our study highlights this important seasonal process and shows spring greenhouse gas emissions are largely due to production from respiration instead of only bursts of stored gases. Further warming is projected to result in increases of snowpack and deeper thaws, which could increase this ecosystem respiration dominate snow melt period causing larger greenhouse gas losses during spring.

Variability in spatial–temporal recharge under the observed and projected climate: A site-specific simulation in the black soil region of Russia

The main purpose of this work is to evaluate diffuse groundwater recharge and its temporal dynamics at sites with different landscapes and soil profiles under observed and projected climate variability. Three typical sites with different landscapes and topsoil profiles were chosen for the field study. Field work consisted of pit development and soil sample collection for laboratory study using the centrifuge method. Soil hydraulic parameters were obtained by the RETC code using the observed values of volumetric water content vs. pressure head. HYDRUS-1D code was used to estimate groundwater recharge based on a 70-year (1945–2015) meteorological dataset with daily resolution (including values of precipitation, air temperature, wind speed, and humidity). This dataset was preprocessed using our SURFBAL code to calculate the surface and topsoil water and energy balance. Retrospective historical simulation results showed that there was a considerable variation in the mean annual groundwater recharge values (49–104 mm/year) for the three studied profiles. The temporal change in groundwater recharge occurred relatively synchronously at all sites and was governed by the change in the current annual aridity index. The results of this historical simulation did not reveal any traces of climate change in the groundwater recharge of the studied region in the last 30–40 years. To predict the recharge variations in the second half of the 21st century, the LARSWG forecast weather generator with the climate projections of the 5th General Circulation Models (GCMs) from the Coupled Model Intercomparison Project 5 (CMIP5) family was used. On average in the case of climate development under the maximum greenhouse gas emissions RCP8.5 scenario, there will be a reduction in groundwater recharge in the studied region in 2060–2080, caused by two factors: change of aridity index, which determines evapotranspiration during a warm season and the accumulation of snow and subsequent meltwater infiltration during the snowmelt periods.

Assessment of soil loss by water erosion in small river basins in Russia

Prolonged and intensive agricultural exploitation in the European territory of Russia has resulted in extensive soil erosion, which has led to anthropogenically induced degradation of arable land. The extensive agricultural development of the region stems from the presence of plains suitable for plowing, which feature fertile chernozem (Luvic Chernozems) and grey forest (Luvisols) soils. The majority of the land in the small river basins (70–80%) are plowed. In addition, this macroregion of Russia is the main agricultural territory that provides food for the entire country. The total arable area comprises approximately 600,000 km2. Approximately 95 million people, the majority of the population of Russia, live in this region. This research aims to provide a quantitative assessment of the soil lost by erosion in the arable lands of the macroregion using an USLE empirical mathematical model modified to suit the harsh climatic conditions of Russia. The calculation was performed using a raster model of the data that includes a model of the slope angle, slope length, soil erodibility, rainfall erosivity factor, water content of the snow, annual distribution of precipitation, and types of land use. The location of arable lands of the territory were determined by remote sensing measurements and the TerraNorteRLCv.3 (2014) map compiled by the Space Research Institute of the Russian Academy of Science. For the first time, the intensity of soil erosion over periods of snowmelt and storm runoff, as well as the total annual soil loss, were determined for this territory at a regional scale (1:500,000). The results of these calculations were generalized for small river basins. For this generalization, we used a grid we had previously designed that features over 50,000 river basins.. The average soil erosion in the territory studied amounts to 4.04 t ha−1 year−1, considering the soil-protective coefficients of agricultural vegetation. In the annual soil loss by erosion, storm runoff erosion prevails at 3.78 t ha−1 year−1 and the erosion by snowmelt is considerably lower at only 0.26 t ha−1 year−1.As expected, due to the higher values of the relief (length-slope) factor, soil erosion increases from the lowland plains (3.65 t ha−1 year−1) to the high plains (5.38 t ha−1 year−1), peaking in the mountains (12.88 t ha−1 year−1). The rate of soil erosion of arable lands consistently decreases from the taiga and forest landscape subzone to the steppes. An east–west trending zone featuring the highest soil erosion was distinguished. This zone of high soil erosion coincides with the mixed and broad-leaved forests subzone, which is highly used for plowing. Moreover, a western longitudinal sector of high soil erosion that includes the forest and forest-steppe landscape zones was also determined.

Analysis of changes in hydrological cycle of a pristine mountain catchment. 1. Water balance components and snow cover

Abstract We analyse water balance, hydrological response, runoff and snow cover characteristics in the Jalovecký Creek catchment (area 22 km2, mean elevation 1500 m a.s.l.), Slovakia, in hydrological years 1989–2018 to search for changes in hydrological cycle of a mountain catchment representing hydrology of the highest part of the Western Carpathians. Daily air temperature data from two meteorological stations located in the studied mountain range (the Tatra Mountains) at higher elevations show that the study period is 0.1°C to 2.4°C warmer than the climatic standard period 1951–1980. Precipitation and snow depth data from the same stations do not allow to conclude if the study period is wetter/drier or has a decreasing snow cover. Clear trends or abrupt changes in the analysed multivariate hydrometric data time series are not obvious and the oscillations found in catchment runoff are not coherent to those found in catchment precipitation and air temperature. Several time series (flashiness index, number of flow reversals, annual and seasonal discharge maxima, runoff coefficients) indicate that hydrological cycle is more dynamic in the last years of the study period and more precipitation runs off since 2014. The snow cover characteristics and climatic conditions during the snow accumulation and melting period do not indicate pronounced changes (except the number of days with snowfall at the Kasprowy Wierch station since 2011). However, some data series (e.g. flow characteristics in March and June, annual versus summer runoff coefficients since 2014) suggest the changes in the cold period of the year.

Loss of total phenols from leaf litter of two shrub species: dual responses to alpine forest gap disturbance during winter and the growing season

AbstractAimsAlpine forest gaps can control understory ecosystem processes by manipulating hydrothermal dynamics. Here, we aimed to test the role of alpine forest gap disturbance on total phenol loss (TPL) from the decomposing litter of two typical shrub species (willow, Salix paraplesia Schneid., and bamboo, Fargesia nitida (Mitford) Keng f.).MethodsWe conducted a field litterbag experiment within a representative fir (Abies faxoniana Rehd.) forest based on ‘gap openness treatments’ (plot positions in the gap included the gap center south, gap center north, canopy edge, expanded edge and closed canopy). The TPL rate and litter surface microbial abundance (fungi and bacteria) of the two shrub species were measured during the following periods over 2 years: snow formation (SF), snow cover (SC), snow melting (ST), the early growing season (EG) and the late growing season (LG).Important FindingsAt the end of the study, we found that snow cover depth, freeze–thaw cycle frequency and the fungal copies g−1 to bacterial copies g−1 ratio had significant effects on litter TPL. The abundances of fungi and bacteria decreased from the gap center to the closed canopy during the SF, SC, ST and LG periods and showed the opposite trend during the EG periods. The rate of TPL among plot positions closely followed the same trend as microbial abundance during the first year of incubation. In addition, both species had higher rates of TPL in the gap center than at other positions during the first winter, first year and entire 2-year period. These findings suggest that alpine forest gap formation accelerates litter TPL, although litter TPL exhibits dual responses to gap disturbance during specific critical periods. In conclusion, reduced snow cover depth and duration during winter warming under projected climate change scenarios or as gaps vanish may slow litter TPL in alpine biomes.

Sensitivity of 21st century simulated ecosystem indicators to model parameters, prescribed climate drivers, RCP scenarios and forest management actions for two Finnish boreal forest sites

Abstract. Forest ecosystems are already responding to changing environmental conditions that are driven by increased atmospheric CO2 concentrations. These developments affect how societies can utilise and benefit from the woodland areas in the future, be it for example climate change mitigation as carbon sinks, lumber for wood industry, or preserved for nature tourism and recreational activities. We assess the effect and the relative magnitude of different uncertainty sources in ecosystem model simulations from the year 1980 to 2100 for two Finnish boreal forest sites. The models used in this study are the land ecosystem model JSBACH and the forest growth model PREBAS. The considered uncertainty sources for both models are model parameters and four prescribed climates with two RCP (representative concentration pathway) scenarios. Usually, model parameter uncertainty is not included in these types of uncertainty studies. PREBAS simulations also include two forest management scenarios. We assess the effect of these sources of variation at four different points in time on several ecosystem indicators, e.g. gross primary production (GPP), ecosystem respiration, soil moisture, recurrence of drought, length of the vegetation active period (VAP), length of the snow melting period and the stand volume. The uncertainty induced by the climate models remains roughly the same throughout the simulations and is overtaken by the RCP scenario impact halfway through the experiment. The management actions are the most dominant uncertainty factors for Hyytiälä and as important as RCP scenarios at the end of the simulations, but they contribute only half as much for Sodankylä. The parameter uncertainty is the least influential of the examined uncertainty sources, but it is also the most elusive to estimate due to non-linear and adverse effects on the simulated ecosystem indicators. Our analysis underlines the importance of carefully considering the implementation of forest use when simulating future ecosystem conditions, as human impact is evident and even increasing in boreal forested regions.

The Snowmelt Niche Differentiates Three Microbial Life Strategies That Influence Soil Nitrogen Availability During and After Winter.

Soil microbial biomass can reach its annual maximum pool size beneath the winter snowpack and is known to decline abruptly following snowmelt in seasonally snow-covered ecosystems. Observed differences in winter versus summer microbial taxonomic composition also suggests that phylogenetically conserved traits may permit winter- versus summer-adapted microorganisms to occupy distinct niches. In this study, we sought to identify archaea, bacteria, and fungi that are associated with the soil microbial bloom overwinter and the subsequent biomass collapse following snowmelt at a high-altitude watershed in central Colorado, United States. Archaea, bacteria, and fungi were categorized into three life strategies (Winter-Adapted, Snowmelt-Specialist, Spring-Adapted) based upon changes in abundance during winter, the snowmelt period, and after snowmelt in spring. We calculated indices of phylogenetic relatedness (archaea and bacteria) or assigned functional attributes (fungi) to organisms within life strategies to infer whether phylogenetically conserved traits differentiate Winter-Adapted, Snowmelt-Specialist, and Spring-Adapted groups. We observed that the soil microbial bloom was correlated in time with a pulse of snowmelt infiltration, which commenced 65 days prior to soils becoming snow-free. A pulse of nitrogen (N, as nitrate) occurred after snowmelt, along with a collapse in the microbial biomass pool size, and an increased abundance of nitrifying archaea and bacteria (e.g., Thaumarchaeota, Nitrospirae). Winter- and Spring-Adapted archaea and bacteria were phylogenetically clustered, suggesting that phylogenetically conserved traits allow Winter- and Spring-Adapted archaea and bacteria to occupy distinct niches. In contrast, Snowmelt-Specialist archaea and bacteria were phylogenetically overdispersed, suggesting that the key mechanism(s) of the microbial biomass crash are likely to be density-dependent (e.g., trophic interactions, competitive exclusion) and affect organisms across a broad phylogenetic spectrum. Saprotrophic fungi were the dominant functional group across fungal life strategies, however, ectomycorrhizal fungi experienced a large increase in abundance in spring. If well-coupled plant-mycorrhizal phenology currently buffers ecosystem N losses in spring, then changes in snowmelt timing may alter ecosystem N retention potential. Overall, we observed that snowmelt separates three distinct soil niches that are occupied by ecologically distinct groups of microorganisms. This ecological differentiation is of biogeochemical importance, particularly with respect to the mobilization of nitrogen during winter, before and after snowmelt.

Regulation of Cu and Zn migration in soil by biochar during snowmelt

To study the migration characteristics of the heavy metals Cu and Zn carried by snowmelt water infiltrating soil during snowmelt periods and the regulation of this process by biochar, field experiments were carried out in which the variation in the Cu and Zn contents in soils on bare land (S1) and in soils with biochar coverage (S2) were analysed before snowfall and during snowmelt periods, and the degree of Cu and Zn pollution was determined on the basis of the enrichment factor (EF) and index of geoaccumulation (Igeo). The migration characteristics of Cu and Zn in soil were studied by combining the migration coefficient and leaching ratio. During the snowmelt period, the use of biochar reduced the migration coefficients of Cu and Zn carried by snowmelt water in shallow soil. The transport coefficients (Tj) of Cu and Zn in shallow soil (0–30 cm) in the S2 treatment were 0.89 and 0.81, respectively, lower than those in the S1 treatment. In addition, during the snowmelt period, the leaching ratios (Cij) of Cu and Zn in the 0–10 cm soil layer of the S2 treatment were 0.22 and 0.24 less than those of the S1 treatment, the index of geoaccumulation (Igeo) was 0.52 and 0.23 less, and the enrichment factor (EF) was 1.20 and 0.09 less, respectively. This study provides practical and theoretical guidance for future research on soil heavy metal pollution mitigation.

Snow and glacier melt runoff simulation under variable altitudes and climate scenarios in Gilgit River Basin, Karakoram region

The snow and glacial resource of the Himalayan region are a major source of fresh water for Indus basin irrigation system on which sustenance of millions of people depends. In the context of recent growth in global warming, it has become inevitable to estimate snow and glacier melt to manage future water resource in this region. In the present study, snow and glacier melt runoff was estimated from various altitudinal ranges and under variable climate scenarios in Gilgit River Basin of Pakistan using an integrated modeling approach. The findings of the study revealed > 80% runoff contribution from 4000 to 5000 m elevation range in the Gilgit Basin. The scenario of temperature increase by 1 °C indicated 9% and 13% rise in annual and summer flows, while 3 °C rise in temperature exhibited an increase of 75% and 95% in annual and summer flows of the Gilgit River. As a result of 10% rise in precipitation, the Gilgit River indicated an increase of 48% in annual and 57% in summer flows. A shift in snow melting period was predicted from April to March due to rising warm temperature. Major contribution in the runoff was estimated from snowmelt followed by glacier melt and rainfall. Overall rising trend in snow cover area was observed in the basin, which support the fact of mass gaining behavior of the Karakoram glaciers. The increased summer flows expected under future climate change in this basin should be managed to fulfill the growing water demands of numerous communities living in the downstream in the future.

Recent Trends in Freshwater Influx to the Arctic Ocean from Four Major Arctic-Draining Rivers

Runoff from Arctic rivers constitutes a major freshwater influx to the Arctic Ocean. In these nival-dominated river systems, the majority of annual discharge is released during the spring snowmelt period. The circulation regime of the salinity-stratified Arctic Ocean is connected to global earth–ocean dynamics through thermohaline circulation; hence, variability in freshwater input from the Arctic flowing rivers has important implications for the global climate system. Daily discharge data from each of the four largest Arctic-draining river watersheds (Mackenzie, Ob, Lena and Yenisei; herein referred to as MOLY) are analyzed to identify historic changes in the magnitude and timing of freshwater input to the Arctic Ocean with emphasis on the spring freshet. Results show that the total freshwater influx to the Arctic Ocean increased by 89 km3/decade, amounting to a 14% increase during the 30-year period from 1980 to 2009. A distinct shift towards earlier melt timing is also indicated by proportional increases in fall, winter and spring discharges (by 2.5%, 1.3% and 2.5% respectively) followed by a decrease (by 5.8%) in summer discharge as a percentage of the mean annual flow. This seasonal increase in discharge and earlier pulse onset dates indicates a general shift towards a flatter, broad-based hydrograph with earlier peak discharges. The study also reveals that the increasing trend in freshwater discharge to the Arctic Ocean is not solely due to increased spring freshet discharge, but is a combination of increases in all seasons except that of the summer.