Earlier Snowmelt Research Articles

Hydrological process controls on streamflow variability in a glacierized headwater basin

AbstractMountain glacierized headwaters are currently witnessing a transient shift in their hydrological and glaciological systems in response to rapid climate change. To characterize these changes, a robust understanding of the hydrological processes operating in the basin and their interactions is needed. Such an investigation was undertaken in the Peyto Glacier Research Basin, Canadian Rockies over 32 years (1988–2020). A distributed, physically based, uncalibrated glacier hydrology model was developed using the modular, object‐oriented Cold Region Hydrological Modelling Platform to simulate both on and off‐glacier high mountain processes and streamflow generation. The hydrological processes that generate streamflow from this alpine basin are characterized by substantial inter‐annual variability over the 32 years. Snowmelt runoff always provided the largest fraction of annual streamflow (44% to 89%), with smaller fractional contributions occurring in higher streamflow years. Ice melt runoff provided 10% to 45% of annual streamflow volume, with higher fractions associated with higher flow years. Both rainfall and firn melt runoff contributed less than 13% of annual streamflow. Years with high streamflow were on average 1.43°C warmer than low streamflow years, and higher streamflow years had lower seasonal snow accumulation, earlier snowmelt and higher summer rainfall than years with lower streamflow. Greater ice exposure in warmer, low snowfall (high rainfall) years led to greater streamflow generation. The understanding gained here provides insight into how future climate and increased meteorological variability may impact glacier meltwater contributions to streamflow and downstream water availability as alpine glaciers continue to retreat.

High nest failure but better nestling quality for early breeders in an alpine population of Northern Wheatear (Oenanthe oenanthe)

Climate change is leading to the advancement of spring conditions, resulting in an earlier snowmelt and green‐up, with highest rates of change in highly seasonal environments, including alpine habitats. Migratory birds breeding at high elevations need to time their arrival and lay dates accurately with this advancement, but also with the annually variable spring conditions at their breeding sites, to maximize nest survival probabilities and reproductive output. Nest survival probability and mean nestling mass were analysed in relation to lay date and habitat conditions in an alpine population of the migratory Northern Wheatear Oenanthe oenanthe collected over six consecutive breeding seasons in the Western Italian Alps. This open grassland species showed the lowest nest survival probability in years with an early onset of spring conditions. Within‐season, nest survival was highest when breeding late, at lower elevations, and when grass cover and grass height were higher. Both across‐ and within‐season, severe weather conditions may indirectly lead to higher early season nest failure rates by increasing predation risk. By contrast, mean nestling mass, and thus the quality of the fledglings, was lower when breeding late. This might be driven by a mismatch with the peak in food abundance. Breeding early is thus generally advantageous in terms of chick quality in our high‐elevation population, but reproductive success is limited by the risk of nest failure that is higher in early springs and early in the season. This trade‐off between breeding early and late may thus allow Northern Wheatears to maximize fitness under highly variable spring conditions. However, climate change may cause disruption to this trade‐off, and shifts in phenology could become a threat for migratory alpine birds that might not be able to keep track of advancing spring conditions.

Earlier spring snowmelt drives arrowleaf balsamroot phenology in montane meadows

AbstractClimate change is shifting phenology globally, altering when and how species respond to environmental cues such as temperature and the timing of snowmelt. These shifts may result in phenological mismatches among interacting species, creating cascading effects on community and ecosystem dynamics. Using passive warming structures and snow removal, we examined how experimentally increased temperatures, earlier spring snowmelt, and the poorly understood interaction between warming and earlier spring snowmelt affected flower onset, flowering duration, and maximum floral display of the spring‐flowering montane species, arrowleaf balsamroot (Balsamorhiza sagittata), over a 7‐year period. Additionally, potential cumulative effects of treatments were evaluated over the study duration. The combination of heating with snow removal led to earlier flower onset, extended flowering duration, and increased maximum floral display. While there was year‐to‐year variation in floral phenology, the effect of heating with snow removal on earlier onset and maximum floral display strengthened over time. This suggests that short‐term studies likely underestimate the potential for climate change to influence phenological plant traits. Overall, this research indicates that B. sagittata's flowering onset responded more strongly to snow removal than to heating, but the combination of heating with snow removal allowed plants to bloom earlier, longer, and more profusely, providing more pollinator resources in spring. If warming and early snowmelt cause similar responses in other plant species, these patterns could mitigate phenological mismatches with pollinators by providing a wider window of time for interaction and resiliency in the face of change. This example demonstrates that a detailed understanding of how spring‐flowering plants respond to specific aspects of predicted climatic scenarios will improve our understanding of the effects of climate change on native plant–pollinator interactions in montane ecosystems. Studies like this help elucidate the long‐term physiological effects of climate‐induced stressors on plant phenology in long‐lived forbs.

Spring snow cover duration and tundra greenness in the Lena Delta, Siberia: two decades of MODIS satellite time series (2001–2021)

The Lena Delta in Siberia is the largest delta in the Arctic and as a snow-dominated ecosystem particularly vulnerable to climate change. Using the two decades of MODerate resolution Imaging Spectroradiometer satellite acquisitions, this study investigates interannual and spatial variability of snow-cover duration and summer vegetation vitality in the Lena Delta. We approximated snow by the application of the normalized difference snow index and vegetation greenness by the normalized difference vegetation index (NDVI). We consolidated the analyses by integrating reanalysis products on air temperature from 2001 to 2021, and air temperature, ground temperature, and the date of snow-melt from time-lapse camera (TLC) observations from the Samoylov observatory located in the central delta. We extracted spring snow-cover duration determined by a latitudinal gradient. The ‘regular year’ snow-melt is transgressing from mid-May to late May within a time window of 10 days across the delta. We calculated yearly deviations per grid cell for two defined regions, one for the delta, and one focusing on the central delta. We identified an ensemble of early snow-melt years from 2012 to 2014, with snow-melt already starting in early May, and two late snow-melt years in 2004 and 2017, with snow-melt starting in June. In the times of TLC recording, the years of early and late snow-melt were confirmed. In the three summers after early snow-melt, summer vegetation greenness showed neither positive nor negative deviations. Whereas, vegetation greenness was reduced in 2004 after late snow-melt together with the lowest June monthly air temperature of the time series record. Since 2005, vegetation greenness is rising, with maxima in 2018 and 2021. The NDVI rise since 2018 is preceded by up to 4 °C warmer than average June air temperature. The ongoing operation of satellite missions allows to monitor a wide range of land surface properties and processes that will provide urgently needed data in times when logistical challenges lead to data gaps in land-based observations in the rapidly changing Arctic.

Pervasive alterations to snow-dominated ecosystem functions under climate change

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.

Early snowmelt by an extreme warming event affects understory more than overstory trees in Japanese temperate forests

AbstractThe occurrence of extreme warm events and early snowmelt is predicted to increase in high‐latitude ecosystems, even during periods of time when there is no coincident reduction in total precipitation. However, because extreme events like these occur unpredictably, little is known about how advancing snowmelt by a single extreme warm event, without a reduction in precipitation amount, influences overstory trees and understory vegetation simultaneously in an ecosystem. We conducted a warming experiment (four 20 × 20 m plots) in temperate forests of Japan to determine the effects of earlier snowmelt on both understory dwarf bamboo plants and overstory birch trees. Our experimental treatment advanced snowmelt by about 10 days and increased soil temperatures that were associated with increased rates of soil nitrogen (N) mineralization and nitrification. Furthermore, these changes led to lower C:N ratios of leaves together with the greater growth of understory bamboo vegetation, with no changes in leaf C:N or growth rates of overstory birch trees. Together, our results demonstrate that advancing snowmelt by an extreme warm event in temperate forests is likely to affect N cycling and will benefit understory vegetation without a commensurate change in overstory vegetation, likely due to the increase in available soil N. These results also demonstrate that with the projected increase in the frequency of extreme warm events and advanced snowmelt, understory vegetation is likely to benefit more than overstory trees in Japanese temperate forests with heavy snow.

Projected Effects of Temperature and Precipitation Variability Change on Streamflow Patterns Using a Functional Flows Approach

AbstractStreamflow patterns are shifting with climate change, and these shifts pose increasing risk to freshwater ecosystems. These emerging changes must be linked with ecological functions of river systems to understand how climate change may affect freshwater biota. In this study we used a functional flows approach to analyze the ecological effects of changing streamflow patterns in snowmelt‐dominated watersheds of the Sierra Nevada mountains of California. Our climate change modeling method combined ensemble Global Climate Models (GCMs) and decision scaling methods to incorporate the effects of GCM‐projected changes in precipitation variability on streamflow patterns. Of climate parameters explored, air temperature causes the most change in functional flows, although precipitation variability compounds changes driven by air temperature. The greatest changes in ecologically‐relevant streamflow patterns manifest as longer and drier dry season conditions, earlier snowmelt recession, and higher‐magnitude peak flows. Although the directions of changes in functional flow metrics are largely consistent across models and watersheds, the magnitude of change depends strongly on human emissions levels. The analytical approach used in this study can serve as a model for integrating multiple approaches in hydroclimatic assessment of ecological change, and the results can help prioritize specific aspects of the flow regime for restoration efforts.

Climate Change Shrinks and Fragments Salmon Habitats in a Snow-Dependent Region.

Climate change threatens biodiversity through global alteration of habitats, but efficient conservation responses are often hindered by imprecise downscaling of impacts. Besides thermal effects, warming also drives important ancillary environmental changes, such as when river hydrology evolves in response to climate forcing. Earlier snowmelt runoff and summer flow declines are broadly manifested in snow-dependent regions and relevant to socioeconomically important cold-water fishes. Here, we mechanistically quantify how climate-induced summer flow declines during historical and future periods cause complex local changes in Chinook salmon (Oncorhynchus tshawytscha) habitats for juveniles and spawning adults. Changes consisted of large reductions in useable habitat area and connectivity between the main channel and adjacent off-channel habitats. These reductions decrease the capacity of freshwater habitats to support historical salmon abundances and could pose risks to population persistence in some areas.

Numerical analysis of midwinter infiltration along the soil-rock interface: A pathway for enhanced bedrock recharge

Shallow bedrock aquifers are prevalent across the Northern Hemisphere and can be the primary source of freshwater for many communities. Cryospheric impacts from climate warming are particularly concerning for bedrock aquifers where recharge is dominated by winter precipitation. For the management and protection of fractured rock groundwater supplies, the processes influencing infiltration and recharge under warmer winter conditions require a greater understanding. As such, a numerical investigation was undertaken with the objective of testing a conceptual model of midwinter infiltration and recharge near a granitic Canadian Shield bedrock outcrop using data collected over an unseasonably warm and rainy winter in eastern Ontario, Canada. Additional objectives were to determine if infiltration and recharge would be limited through frozen soils without an outcrop and to explore the hydrologic implications of an additional midwinter snowmelt event. Results supported the concept that outcrops provide preferential infiltration along the soil-rock interface at outcrop margins, which enables localized bedrock recharge under frozen conditions. To simulate soil moisture content near the outcrop, bedrock runoff was needed as additional lateral input in the lower soil profile (75 cm). The amount of runoff required as input was controlled by the hydraulic conductivity of the soil-rock interface. In the absence of an outcrop, limited midwinter infiltration occurs due to reduced permeabilities of frozen soils from repeated early winter rainfall and snowmelt events. Additional midwinter melt events can likely increase bedrock recharge, but the associated decline in snow depth deepens soil frost which delays further infiltration and increases surface runoff. Simulations suggest winter is becoming a more active time for bedrock recharge where outcrops are present, but wetter conditions have implications for frozen soil permeability. Findings extend to similar seasonally frozen bedrock environments which are relied on as a source of freshwater and are rapidly changing under a warming climate.

High Daily and Year-Round Variability in Denitrification and Nitrogen Fixation in a Northern Temperate River

Rates of nitrogen (N) cycling processes like denitrification and dinitrogen (N2) fixation, which together are the primary contributors to N2 flux rates from surface waters, may change at different time scales from seasons to weeks to days. Yet, we know little about the magnitude, mechanisms or drivers of these temporal changes, especially at shorter daily and weekly timescales. Quantifying variation in rates and drivers across temporal scales is essential to understand how nutrient cycling processes operate in aquatic ecosystems and predict how they may respond to shifting seasonal dynamics caused by global change (i.e., earlier snowmelt and extreme weather events). This study quantified denitrification and N2 fixation rates seasonally and daily in a northern temperate river, and explored how environmental conditions such as discharge, light, and N and phosphorus (P) concentrations were related to that variation at different time scales. We measured denitrification and N2 fixation rates on biweekly and daily intervals at a single 20-m long sampling reach in the Pilgrim River in Michigan's Upper Peninsula from May 2017 through May 2019. We found high rates of daily change (difference in rate from one day to the next) for both processes in all seasons (maximum daily change 5,690 μg N/m2/h for denitrification and 38 μg N/m2/h for N2 fixation). No detectable differences in rates among seasons were detected using Multiple Response Permutation Procedure (MRPP). Day-to-day variation did not change before and after elevated discharge events, including a 1,000-year flood that occurred in June 2018. Partial least squares (PLS) regression identified total dissolved N, dissolved organic N, and ammonium as important predictors of denitrification and N2 fixation, but explained only 15–28% of the variation in all measured rates. The unexpectedly high daily variation and lack of seasonal difference in rates found in this study demonstrate the need to use caution when studying these processes and/or extrapolating rates across time scales, as discrete and infrequent measurements may be misleading.

Snow Albedo Feedbacks Enhance Snow Impurity‐Induced Radiative Forcing in the Sierra Nevada

This study employs a fully coupled meteorology‐chemistry‐snow model to investigate the impacts of light‐absorbing particles (LAPs) on snow darkening in the Sierra Nevada. After comprehensive evaluation with spatially and temporally complete satellite retrievals, the model shows that LAPs in snow reduce snow albedo by 0.013 (0–0.045) in the Sierra Nevada during the ablation season (April‐July), producing a midday mean radiative forcing of 4.5 W m−2 which increases to 15–22 W m−2 in July. LAPs in snow accelerate snow aging processes and reduce snow cover fraction, which doubles the albedo change and radiative forcing caused by LAPs. The impurity‐induced snow darkening effects decrease snow water equivalent and snow depth by 20 and 70 mm in June in the Sierra Nevada bighorn sheep habitat. The earlier snowmelt reduces root‐zone soil water content by 20%, deteriorating the forage productivity and playing a negative role in the survival of bighorn sheep.

Nitrogen migration paths and source areas at different snowmelt periods in a seasonal freezing agricultural watershed

Study regionHeidingzi, a typical seasonal freezing agricultural watershed in northeastern China. Study focusThis study’s objectives were to: (1) confirm whether nitrogen source areas and migration paths have changed with the melting of snow and frozen soil; (2) find an effective way to recognize the change points and separate nitrogen export processes to different periods during snowmelt; and (3) identify the source areas, migration paths, and critical influencing factors of ammonium nitrogen (NH4+-N) and nitrate nitrogen (NO3−-N) in river water during these snowmelt periods. New hydrological insights for the regionThe nitrogen export process during snowmelt can be divided into two stages according to the relationship between δ18O and nitrogen concentration. Nitrogen concentration had a linear relationship with δ18O during early snowmelt periods, while they varied within a small range during the late stages. Paddy field area proportion (PFP), Rural area proportion (RAP), Average Slope (AS), Slope area proportion < 2° (SAP < 2°), and SAP (6–15°) greatly affected water discharge, nitrogen concentration, and yield. Lower slope areas along the river expended water and nitrogen via soil saturation and depression detention. The NH4+-N and NO3−-N in these areas were flushed into rivers by water from steeper areas (slope > 6°). Abundant nitrogen reserves near the river compensated for the negative impact of water shortage on nitrogen yield during early snowmelt periods. Water and nitrogen in rural areas came mainly from snow-scattered areas during early snowmelt periods, and from frozen domestic sewage or refrozen snowmelt in drainage ditches during late snowmelt periods.

Comparative impacts of long‐term trends in snowmelt and species interactions on plant population dynamics

Abstract Climate change can impact plant fitness and population persistence directly through changing abiotic conditions and indirectly through its effects on species interactions. Pollination and seed predation are important biotic interactions that can impact plant fitness, but their impact on population growth rates relative to the role of direct climatic effects is unknown. We combined 13 years of experiments on pollen limitation of seed set and pre‐dispersal seed predation in Ipomopsis aggregata, a subalpine wildflower, with a long‐term demographic study that has documented declining population growth with earlier spring snowmelt date. We determined how pollen limitation and seed predation changed with snowmelt date over 21 years and incorporated those effects into an integral projection model to assess relative impacts of biotic factors on population growth. Both pollen limitation and the difference in stigma pollen load between pollen‐supplemented and control plants declined over years. Neither pollen limitation nor seed predation changed detectably with snowmelt date, suggesting an absence of indirect effects of that specific abiotic factor on these indices of biotic interactions. The projected biotic impacts of pollen limitation and seed predation on population growth rate were small compared to factors associated with snowmelt date. Providing full pollination would delay the projected date when earlier snowmelt will cause populations to fall below replacement by only 14 years. Synthesis. Full pollination and elimination of seed predation would not compensate for the strong detrimental effects of early snowmelt on population growth rate, which in I. aggregata appears driven largely by abiotic environmental factors. The reduction over two decades in pollen limitation also suggests that natural selection on floral traits may weaken with continued climate change. These results highlight the value of studying both abiotic factors and biotic interactions to understand how climate change will influence plant populations.

Phenotypic plasticity and selection on leaf traits in response to snowmelt timing and summer precipitation

Vegetative traits of plants can respond directly to changes in the environment, such as those occurring under climate change. That phenotypic plasticity could be adaptive, maladaptive, or neutral. We manipulated the timing of spring snowmelt and amount of summer precipitation in factorial combination and examined responses of specific leaf area (SLA), trichome density, leaf water content (LWC), photosynthetic rate, stomatal conductance and intrinsic water-use efficiency (iWUE) in the subalpine herb Ipomopsis aggregata. The experiment was repeated in three years differing in natural timing of snowmelt. To examine natural selection, we used survival, relative growth rate, and flowering as fitness indices. A 50% reduction in summer precipitation reduced stomatal conductance and increased iWUE, and doubled precipitation increased LWC. Combining natural and experimental variation, earlier snowmelt reduced soil moisture, photosynthetic rate and stomatal conductance, and increased trichome density and iWUE. Precipitation reduction reversed the mortality selection favoring high stomatal conductance under normal and doubled precipitation, and higher LWC improved growth. Earlier snowmelt is a strong signal of climate change and can change expression of leaf morphology and gas exchange traits, just as reduced precipitation can. Stomatal conductance and SLA showed adaptive plasticity under some conditions.

Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.

Climate Variation Influences Flowering Time Overlap in a Pair of Hybridizing Montane Plants

Flowering time is sensitive to climatic conditions and has been a frequent focus of climate change research, yet the implications of phenological shifts for hybridization within plant communities have seldom been explored. Reproductive overlap between interfertile species is a key requirement for the production of hybrid (inter-species) offspring, and climate change may influence the opportunities for hybrid production through changes to species' flowering time, duration, and overlap with other species. To test how climate variation influences flowering overlap between hybridizing species, we analyzed 45 years of flowering phenology data on 2 common plants in the Rocky Mountains of Colorado that are known to produce hybrids (Potentilla pulcherrima and Potentilla hippiana, family Rosaceae). We estimated flowering overlap from flowering distributions in 2 ways that focus on how similar species are in terms of flowering time (“symmetric overlap”) or relative floral abundance across the season (“relative overlap”). We found that the 2 species had similar phenological responses to most climate variables. Both flowered earlier in years with warm, dry growing seasons preceded by earlier snowmelt and winters with less snow, and later in cool, wet growing seasons with later snowmelt after winters with heavy snowfall. Precipitation was the best predictor of flowering time overlap. In wetter years, both species flowered later and longer, and reached peak flowering date at a more similar time in the growing season. While our results suggest that precipitation patterns influence the extent of flowering overlap between these 2 species in any given growing season, precipitation has not consistently increased or decreased in this region over the past 45 years, and therefore we do not see a consistent signature of global climate change on flowering overlap. Finally, we found that even though temperature was an important predictor of flowering phenology within each species, it was not a major driver of overlap between species, emphasizing that data on individual species responses cannot necessarily predict how climate change will affect species interactions.

Effects of Aerosol–Induced Snow Albedo Feedback on the Seasonal Snowmelt Over the Himalayan Region

AbstractAerosol‐induced snow darkening and its feedback on seasonal snow cover, snowmelt, and runoff were investigated using the Regional Climate Model (RegCM4.6) coupled with SNow, Ice, and Aerosol Radiation (SNICAR) and aerosol modules over the Himalayas during the melting season (March‐September). The snow albedo reduction due to the deposition of absorbing aerosols increases the 2 m air temperature (1.47°C) and thus decreases the snow cover (10.6%) over the Himalayas during spring. This aerosol‐induced excess warming accelerates the seasonal snowmelt (1.2 mm day−1), which reduces the number of snow‐covered periods by more than 20 days throughout the Himalayas. The accumulated total snowmelt also increased by 41.3% over the Himalayas during the melting season. The early snowmelt and increase in runoff due to aerosol forcing have significant implications on rivers originating from the western Himalayas (Indus Basin). The change in snowmelt distribution and doubling of snowmelt extremes due to aerosol‐induced snow darkening could also translate to an increase in flood risks across the Himalayan river basins. Therefore, the present study highlights the importance of aerosol‐induced snow albedo forcing and its feedback on snowmelt and runoff over the Himalayan region, which has further implications on water availability over the South Asian region.

Earlier snowmelt predominates advanced spring vegetation greenup in Alaska

Snow is considered a vital component in the northern climate system, however, our understanding of the impacts of snowmelt on spring phenological shifts is still limited for high-latitude ecosystems. In this study, we analyzed the start of growing season (SOS) and its response to the process of snowmelt over 2000–2019 using multiple ground observations, satellite data products, and climate datasets in Alaska and part of Canada Yukon among five ecoregions. We found that the earlier snowmelt resulting from warming spring dominates the advanced spring vegetation phenology in the region. Spring vegetation greenup follows the start of snowmelt (SOM). During 2000–2019, the SOM and SOS advanced in a similar spatial pattern across the ecoregions, and SOS experienced further advancement than SOM. On average, SOS advanced about 0.49 days per day of SOM advancement. The impacts of snowmelt on vegetation phenology are largely driven by the snowmelt-induced synergistic changes in soil temperature and soil water content. As snowmelt starts, the infiltration of snowmelt water and insulation of the remaining snow cover stimulate the vegetation activities below the snow. The responses of SOS to the snowmelt phenology varied among the different ecoregions are associated with the varied climate backgrounds and vegetation types. Greater SOS and SOM advancements were found in the taiga-tundra ecotone, while lower changes were detected over the tundra. This study suggests that the snow cover and snowmelt phenology should be considered to better understand the vegetation seasonality under climate change in the high latitudes.

A Subseasonal Regime Approach for Assessing Intra-annual Variability of Evapotranspiration and Application to the Upper Colorado River Basin

Evapotranspiration (ET) is strongly influenced by gradual climate change and fluctuations in meteorological conditions, such as earlier snowmelt and occurrence of droughts. While numerous studies have investigated how climate change influences the inter-annual variability of ET, very few studies focused on quantifying how subseasonal events control the intra-variability of ET. In this study, we developed the concept of subseasonal regimes, whose timing and duration are determined statistically using Hidden Markov Models (HMM) based on meteorological conditions. We tested the value of subseasonal regimes for quantitatively characterizing the variability of seasonal and subseasonal events, including the onset of snow accumulation, snowmelt, growing season, monsoon, and defoliation. We examined how ET varied as a function of the timing of these events within a year and across six watersheds in the region. Variability of annual ET across these six sites is much less significant than the variability in hydroclimate attributes at the sites. Subseasonal ET, defined as the total ET during a given subseasonal regime, provides a measure of intra-annual variability of ET. Our study suggests that snowmelt and monsoon timing influence regime transitions and duration, such as earlier snowmelt can increase springtime ET rapidly but can trigger long-lasting fore-summer drought conditions that lead to decrease subseasonal ET. Overall, our approach provides an enhanced statistically based framework for quantifying how the timing of subseasonal-event transitions influence ET variability. The improved understanding of subseasonal ET variability is important for predicting the future impact of climate change on water resources from the Upper Colorado River Basin regions.

Assessment of snowmelt and groundwater-surface water dynamics in mountains, foothills, and plains regions in northern latitudes

Snowmelt and groundwater-surface water (GW-SW) dynamics are the most dominant controllers of hydrological processes and water availability in northern latitudes, particularly in warm seasons. The dynamics and changes of snowmelt and GW-SW interactions and their interrelationship at the regional scale are poorly understood in regional analyses. To fill this gap, this study implements a process-based hydrological model, using a coupled Soil and Water Assessment Tool (SWAT) and MODFLOW model, to map snowmelt and GW-SW dynamics at regional scales. The primary research questions are “how are GW-SW interactions altered by snowmelt dynamics?” and “what is the effect of climate change on snowmelt and GW-SW dynamics?” We simulated snowmelt and groundwater dynamics across a large watershed encompassing different ecohydrological regions, including mountains, foothills, and plains, analyzing the spatio-temporal relationships between GW-SW interactions and snowmelts in historical (1983–2007) and future (2040–2064) periods. We used an ensemble of five global climate models (GCMs) for future projections based on two emission scenarios (i.e., RCP2.6 and RCP8.5). We also used the Least Absolute Shrinkage and Selection Operator (LASSO) method to examine the effects of snowmelt, evapotranspiration (ET), and rainfall on GW-SW interactions. These analyses are implemented in mountains, foothills, and plains regions in a large snow-dominated watershed in western Canada. Results show that earlier snowmelt is predicted in mountains and foothills regions under climate change scenarios, while less snow accumulation and melt is anticipated in plains region. Future projections of GW-SW interactions show an increase in groundwater discharge to streams in the winter and spring seasons, mainly due to earlier snowmelt in winter and spring in mountains and foothills regions. On the other hand, more surface water loss to groundwater in summer and fall is predicted, which can be caused by the low level of groundwater under future conditions in foothills regions. Correlation analysis between regional snowmelt and GW-SW interactions for historical simulations show a higher correlation (R2= 0.494) in mountains region, compared to very low correlations (R2<0.01) in foothills and plains regions. LASSO results showed that ET was the main control of dynamics of GW-SW interactions in all regions of the study. Snowmelt was the next most important predictor of GW-SW dynamics in the mountains region, while rainfall was more important in the foothills region. Nevertheless, none of the three predictors strongly influenced GW-SW dynamics in the plains region, mainly due to low groundwater levels and a lack of connectivity with the surface water. Overall, it is shown that the eco-hydrogeological and climatic variability of different regions plays an important part in governing GW-SW dynamics.