Snowmelt Research Articles

High altitude horse use and early horse transport in eastern Eurasia: New evidence from melting ice

While few places on earth have been as deeply impacted by the human-horse relationship as the steppes of Mongolia and eastern Eurasia, gaps in the archaeological record have made it strikingly difficult to trace when and how the first domestic horses were integrated into ancient societies in this key region of the world. Recently, organic materials preserved in melting mountain ice have emerged as a key source of archaeological insight into the region’s deep past. Newly-identified artefacts recovered from melting snow and ice in the Altai Mountain range of western Mongolia (including metal artefacts, skeletal remains, and hoof fragments) provide archaeological evidence for the use of horses at high altitudes from the Bronze Age through the 20th century. Direct radiocarbon dating and genomic sequencing demonstrate the presence of Przewalski’s horse in the region during the early second millennium BCE, suggesting that this taxon may have once foraged at high altitudes frequented by human hunters. Importantly, directly-dated remains of horse hoof trimmings provide some of the oldest direct evidence of horse transport in the Eastern Steppe as early as the 14th century BCE, and suggest a role for high-mountain hunting in the innovation of reliable mounted riding.

The dual role of meltwater in buffering river runoff in the Yarlung Zangbo Basin, Tibetan Plateau

Study regionThe Yarlung Zangbo Basin (YZB) on the Tibetan Plateau, the world's highest river basin, features a significant cryosphere with glaciers and seasonal snow cover crucial to its hydrology. The study focuses on the region between the Nuxia and Dexing river gauging stations, where glaciers cover 15.4 % of the area. Study focusThe research quantifies the contributions of snow melt (SM) runoff, glacier melt (GM) runoff, rainfall runoff, and baseflow to the total runoff in the YZB. The Spatial Processes in Hydrology (SPHY) model, enhanced with a cryosphere module, was utilized, calibrated with runoff data from the Nuxia station and evapotranspiration data from 2003 to 2014. New hydrological insightsThe study found rainfall runoff to be the primary contributor to annual runoff (66.3 %), followed by snow melt runoff (19.7 %), glacier melt runoff (6.2 %), and baseflow (7.8 %). Snow melt runoff is dominant in early spring, while baseflow prevails in winter. Glacier melt runoff contributes directly to river flow (90.1 %) and replenishes groundwater (9.9 %), which then drains as baseflow. In glacier-rich areas, percolated glacier meltwater significantly recharges groundwater, underscoring its vital role in sustaining river flow in the YZB. This research enhances the understanding of hydrological processes in large alpine river basins and highlights the crucial role of glacier and snow melt in maintaining the Tibetan Plateau's water resources.

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, developed for hectometer scale applications. HICAR can run more than 500x faster than conventional atmospheric models, while containing many of the same physics parameterizations. Station measurements of air temperature, wind speed, and radiation, in combination with data from a scanning Doppler wind LiDAR, are compared to 50 m resolution HICAR output during late spring. We examine the model’s performance over bare ground and melting snow. The model shows a smaller root mean squared error in 2 m air temperature than the driving model, and approximates the 3D flow features present around ridges and along slopes. Timing and magnitude of changes in shortwave and longwave radiation also show agreement with measurements. Nocturnal cooling during clear nights is overestimated at the snow covered site. Additionally, the thermal wind parameterization employed by the model typically produces excessively strong surface winds, driven in part by this excessive nocturnal cooling over snow. These findings highlight the utility of HICAR as a tool for dynamically downscaling forcing datasets, and expose the need for improvements to the snow model used in HICAR.

Quantifying Volumetric Scattering Bias in ICESat‐2 and Operation IceBridge Altimetry Over Greenland Firn and Aged Snow

AbstractThe Ice, Cloud, and Land Elevation Satellite‐2 (ICESat‐2) mission has collected surface elevation measurements for over 5 years. ICESat‐2 carries an instrument that emits laser light at 532 nm, and ice and snow absorb weakly at this wavelength. Previous modeling studies found that melting snow could induce significant bias to altimetry signals, but there is no formal assessment on ICESat‐2 acquisitions during the melting season. We performed two case studies over the Greenland Ice Sheet to quantify bias in ICESat‐2 signals over snow: one to validate Airborne Topographic Mapper (ATM) data against Next Generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS‐NG) grain sizes, and a second to estimate ICESat‐2 bias relative to ATM. We used snow optical grain sizes derived from ATM and AVIRIS‐NG to attribute altimetry bias to snowpack properties. For the first case study, the mean and standard deviation of optical grain sizes were 340 ± 65 µm (AVIRIS‐NG) and 670 ± 420 µm (ATM). A mean altimetry bias of 4.81 ± 1.76 cm was found for ATM, with larger biases linked to increases in grain size. In the second case study, we found a mean grain size of 910 ± 381 µm and biases of 6.42 ± 1.77 cm (ICESat‐2) and 9.82 ± 0.97 cm (ATM). The grain sizes and densities needed to recreate biases with a model are uncommon in nature, so we propose that additional surface attributes must be considered to characterize ICESat‐2 bias over snow. The altimetry biases are within the accuracy requirements of the ICESat‐2 mission, but we cannot rule out more significant errors over coarse‐grained snow.

Response of runoff and its components to climate change and its future trend in the source region of the Yangtze River

AbstractUnder global climate changes, the temperature and precipitation on the Tibetan Plateau changed significantly, causing accelerated melting of glaciers and snow and changes in runoff. The response of runoff and its components to climate change is important for water resource management and ecology conservation in the region. Therefore, the Spatial Processes in Hydrology model, a distributed cold‐zone hydrological model that contains a glacial ablation module, was used to simulate runoff in the Yangtze River source located in the middle of the Tibetan Plateau during 2000–2050, and the Nash‐Sutcliffe efficiency coefficient, relative error and coefficient of determination (R2) for the calibration period and validation period revealed that the model performed well in most years. The results showed that rainfall runoff contributed the most to the total runoff (61%), followed by baseflow (23%), snowmelt runoff (12%) and glacier runoff (4%) in the Yangtze River source during 2000–2020. The runoff amounts of the three source rivers, Dangqu River, Tuotuo River and Chumar River, accounted for approximately 53% of the total runoff in the Yangtze River source basin, with rainfall runoff (52%) contributing the most and glacier runoff (6%) contributing the least. Compared to the contributions of glacial runoff in the Dangqu River (9%) and Tuotuo River (7%), the proportion of glacial runoff in the Chumar River is small (1%). Under the CMIP6 climate model, the mean runoff depth is predicted to increase by approximately 13.5 mm from 2020 to 2050 compared with that from 2000 to 2020.

Gully regulates snowmelt runoff, sediment and nutrient loss processes in Mollisols region of Northeast China

Gully is a prominent indicator of land degradation in agroecosystems, functioning as a crucial pathway connecting upslopes to downstream channels. However, little is known about how gully regulates runoff, sediment, and nutrient loss processes in the catchment during snowmelt. In this study, we monitored these processes in situ at both the gully head (the upslope accumulated catchment of the gully head, CGH) and outlet of two representative and typical gully-dominated catchments (F1 and F2) during snowmelt in Mollisols region of Northeast China. Our results showed that runoff discharge of CGH and outlet exhibited a multi-peak trend during snowmelt, driven by the transition from snow melting to soil thawing. This transition resulted in distinct runoff patterns in both CGH and outlet, with significant differences in their response to air temperature. The total runoff yield of CGH accounted for 57.8 % in F1 and 40.6 % in F2 of the total runoff yield of the outlet. Notably, the peak sediment concentration displayed a marked lag compared to the peak runoff discharge, primarily dominated by the increased sensitivity of gully erosion after the thawing of gully slopes. Gully erosion was the main source of sediment yield in the catchment, contributing 98.2 % in F1 and 96.6 % in F2. Furthermore, nutrient concentrations exhibited a decreasing trend during snowmelt. The comparison of high nutrient concentrations in CGH and relatively low nutrient concentrations in outlet highlighted the gully's role in intercepting and diluting runoff nutrients. Hysteresis analysis confirmed the differential contribution of CGH and gully to nutrient sources. CGH accounting for 50.9 % and 93.3 % of runoff TN and runoff TP loss, while contributing only 8.3 % and 5.8 % to sediment TN and sediment TP loss, respectively. These findings offer valuable insights for effective erosion control and nonpoint source pollution management in gully-dominated agroecosystems during snowmelt.

Shipborne observations of black carbon aerosols in the western Arctic Ocean during summer and autumn 2016–2020: impact of boreal fires

Abstract. Black carbon (BC) aerosol is considered one of the most important contributors to rapid climate warming as well as snow and sea ice melting in the Arctic, yet the observations of BC aerosols in the Arctic Ocean have been limited due to infrastructural and logistical difficulties. We observed BC mass concentrations (mBC) using light absorption methods on board the icebreaker R/V Araon in the Arctic Ocean (< 80° N and 166° E to 156° W) as well as the North Pacific Ocean in summer and early autumn of 2016–2020. The levels, interannual variations, and pollution episodes of mBC in the Arctic were examined, and the emission sources responsible for the high-BC episodes were analyzed with global chemistry-transport-model simulations. The average mBC in the surface air over the Arctic Ocean (72–80° N) observed by the 2019 cruise exceeded 70 ng m−3, which was substantially higher than that observed by cruises in other years (approximately 10 ng m−3). The much higher mBC observed in 2019 was perhaps due to more frequent wildfires occurring in the Arctic region than in other years. The model suggested that biomass burning contributed most to the observed BC by mass in the western Arctic Ocean and the marginal seas. For these 5 years, we identified 10 high-BC episodes north of 65° N, including one in 2018 that was associated with co-enhancements of CO and CH4 but not CO2 and O3. The model analysis indicated that certain episodes were attributed to BC-containing air masses transported from boreal fire regions to the Arctic Ocean, with some transport occurring near the surface and others in the mid-troposphere. This study provides crucial datasets on BC mass concentrations and the mixing ratios of O3, CH4, CO, and CO2 in the western Arctic Ocean regions, and it highlights the significant impact of boreal fires on the observed Arctic BC during the summer and early autumn months.

Analysis of temperature stress and critical heating temperature for hydronic airport pavement

The hydronic heated pavement system has been widely used for snow and ice removal in airports and other transportation infrastructure facilities because of its good snow melting efficiency and environment friendliness. However, the study of the temperature stress distribution in hydronic pavement and the corresponding critical operation method shows many insufficiencies, which allows security problems during system operation. This paper investigated the temperature stress of the hydronic pavement near the pipes with a 3D finite element model. This model was validated by the measured temperature stress in a full-scale hydronic snow melting experiment system. The locations of the maximum compressive and the time-varying tensile stress in the hydronic pavement were reported. The maximum temperature stresses of the hydronic pavement with various design and operation parameters were compared, and the sensitive parameters were proposed. In particular, the critical fluid temperature with various design and weather parameters was presented by comparing the maximum temperature stress in the pavement with the failure strength of concrete material. The findings show the maximum compressive stress appears near the hydronic pipe, and the maximum tensile stress appears at the midpoint between two adjacent pipes after heating for 2 h. Maximum tensile stress increases with pipe embedded depth, pipe diameter, fluid temperature, and pavement capacity, but decreases with air temperature and pipe spacing. To ensure the safety of hydronic pavement, the critical fluid temperature under different conditions is controlled within the range from 38 °C to 77 °C.

Advancing energy solutions: Carbon-based cementitious composites in energy storage and harvesting

The rapid progress of smart and sustainable cities has led to an increased demand for construction materials that possess functional capabilities in energy storage and harvesting. In light of this, a comprehensive literature review is conducted in this study to investigate the multifunctional properties exhibited by carbon-based cementitious materials. Specifically, the piezoelectric, thermoelectric, tensile, compressive, and flexural behaviors of carbon fiber (CF), graphene, graphite powder (GP), and carbon nanotubes (CNTs) are thoroughly examined through multi-scale research approaches. The electrical conductivity and mechanical properties of these carbon-based additives are analyzed in relation to their molecular structures. Evaluation results reveal that CNTs-based cementitious composites demonstrate 160 %–269 % superior multifunctional performance compared to their CF-based counterparts. Furthermore, the feasibility of potential applications of carbon-based cementitious composites in concrete construction is extensively discussed, encompassing diverse areas such as thermoelectric energy harvesting, intelligent structural adjustment, cathodic protection systems, snow and ice melting, electromagnetic shielding, and structural health monitoring. The research outcomes presented in this study offer a systematic evaluation of a wide range of carbon-based cementitious materials, providing valuable guidelines and recommendations for engineers.

Discrete element analysis of heat transfer characteristics of concrete pavement under electrical heating for snow melting and deicing

The carbon fiber electrothermal method is an efficient approach for snow melting and deicing of pavements in the cold winter. The heat transfer mechanism needs to be explored for the carbon fiber electrothermal system design, especially how the microstructure affects the thermal behavior of pavement. To do so, a discrete element method (DEM) based heat transfer model considering the pavement microstructure has been established in the current study. The shape and content of coarse-grained aggregates have been represented by using the irregular polygonal aggregate method. The accuracy and feasibility of the proposed model were verified by comparing the numerical results with the measured data. On this basis, the heat transfer characteristics of pavements during snow melting and deicing using the carbon fiber electrothermal method have been investigated. The results show that the ambient temperature and the carbon fiber heating wire (CFHW) temperature are the two primary factors affecting the heating efficiency and the maximum temperature on the pavement surface. The spacing and buried depth of the CFHW also play a crucial role in determining the temperature rise rate and the uniformity of temperature distribution of the road surface layer. Furthermore, the effect of the aggregate content on the overall heating rate is not as significant as that of the specific heat capacity ratio of the aggregate to the mortar, suggesting modifying the thermal conductivity of aggregates to enhance deicing efficiency rather than changing the aggregate contents. The effects of the CFHW design parameters on the temperature distribution of the pavement surface are also investigated. The maximum and minimum temperatures of the pavement layer decrease gradually with the increase of the laying spacing and burial depth of the CFHW, but the temperature difference increases with the increase of the laying spacing of the CFHW and decreases with the increase of the burial depth. The research results can provide a reference for the optimization design of snow melting and deicing of pavements by the CFHW heating method.

Northern Pacific sea-level pressure controls rain-on-snow in North America

Rain-on-snow (ROS) events, a phenomenon of liquid rainfall falling over accumulated snowpack, cause quick melting of snow, often leading to rapid and catastrophic flooding. Here we explore the causal drivers of ROS events across North America. A ROS identification method is proposed, which builds on the existing methods but adds more realism in terms of rain and snow conditions for ROS occurrence. We consider a wide range of observed hydrometeorological variables along with climatic oscillations over the period of 1951 to 2022. Causal linkages between the potential drivers and ROS frequency are explored by implementing Convergent Cross Mapping (CCM). Results suggest a strong causal link between the North-Pacific (NP) Index, a measure of sea-level pressure in the Northern Pacific Ocean, and ROS frequencies in North America, specifically in the eastern and western parts. We show the association of the NP index with the hydroclimatic variables and explain how this association might have contributed to this causal link. Thus, our findings provide valuable insights into the potential mechanisms of ROS events in different regions in North America.

Long range transport of South and East Asian anthropogenic aerosols counteracting Arctic warming

The large-scale convection during the Asian summer monsoon plays an important role in the rapid transport of boundary layer aerosols into the Asian summer monsoon anticyclone. Here, using the state-of-the-art ECHAM6–HAMMOZ aerosol-chemistry-climate model, we show that these aerosols are further transported to the Arctic along isentropic surfaces by the Brewer-Dobson-Circulation (BDC) during the monsoon season. Our model simulations show that East and South Asian anthropogenic emissions contribute significantly to the aerosol transported to the Arctic, which causes a higher negative net aerosol radiative forcing at the surface (dimming) of −0.09 ± 0.02 Wm−2 and −0.07 ± 0.02 Wm−2, respectively. Over the Arctic, the East Asian anthropogenic aerosols that include large amounts of sulfate cause a seasonal mean net radiative forcing at the top of the atmosphere (TOA) of −0.003 ± 0.001Wm−2 and a surface cooling of −0.56 K while the black carbon dominated aerosol from South Asia shows a positive TOA forcing of +0.004 ± 0.001Wm−2 with an only minor surface cooling of −0.043 K. Overall, the long-range transport of South Asian aerosols results in a notably warming throughout the atmospheric column but minimal temperature response at the Arctic surface. Conversely, East Asian aerosols cool the troposphere and heat the lower stratosphere in the Arctic. The Asian aerosol thus plays an ambivalent role, with the East Asian sources in particular having the potential to counteract the rapid rise in Arctic temperatures and the associated melting of snow and ice.

Let It Snow: Designing Snowfall Experience in VR

We present Snow, a cross-modal interface that integrates cold and tactile stimuli in mid-air to create snowflakes and raindrops for VR experiences. Snow uses six Peltier packs and an ultrasound haptic display to create unique cold-tactile sensations for users to experience catching snowflakes and getting rained on their bare hands. Our approach considers humans' ability to identify tactile and cold stimuli without masking each other when projected onto the same location on their skin, making illusions of snowflakes and raindrops. We design both visual and haptic renderings to be tightly coupled to present snow melting and rain droplets for realistic visuo-tactile experiences. For multiple snowflakes and raindrops rendering, we propose an aggregated haptic scheme to simulate heavy snowfall and rainfall environments with many visual particles. The results show that the aggregated haptic rendering scheme demonstrates a more realistic experience than other schemes. We also confirm that our approach of providing cold-tactile cues enhances the user experiences in both conditions compared to other modality conditions.

Arctic Sea Ice Albedo Estimation from Fengyun-3C/Visible and Infra-Red Radiometer

The sea ice albedo can amplify global climate change and affect the surface energy in the Arctic. In this paper, the data from Visible and Infra-Red Radiometer (VIRR) onboard Fengyun-3C satellite are applied to derive the Arctic sea ice albedo. Two radiative transfer models, namely, 6S and FluxNet, are used to simulate the reflectance and albedo in the shortwave band. Clear sky sea ice albedo in the Arctic region (60°~90°N) from 2016 to 2019 is derived through the physical process, including data preprocessing, narrowband to broadband conversion, anisotropy correction, and atmospheric correction. The results are compared with aircraft measurements and AVHRR Polar Pathfinder-Extended (APP-x) albedo product and OLCI MPF product. The bias and standard deviation of the difference between VIRR albedo and aircraft measurements are −0.040 and 0.071, respectively. Compared with APP-x product and OLCI MPF product, a good consistency of albedo is shown. And analyzed together with melt pond fraction, an obvious negative relationship can be seen. After processing the 4-year data, an obvious annual trend can be observed. Due to the influence of snow on the ice surface, the average surface albedo of the Arctic in March and April can reach more than 0.8. Starting in May, with the ice and snow melting and melt ponds forming, the albedo drops rapidly to 0.5–0.6. Into August, the melt ponds begin to freeze and the surface albedo increases.

Study on the influencing factors of mechanical properties of anti-icing modified asphalt mortar

Accumulated snow and ice on road surface affect traffic operation. Anti-icing asphalt pavement is widely implemented as an active snow melting technology. However, there are few studies on anti-icing modified asphalt mortar mechanical properties and the effect of mortar materials on the interaction between modified asphalt and anti-icing filler. For this reason, this study investigated the mechanical properties of asphalt including rheological, high-temperature, fatigue and low-temperature properties through frequency and temperature scan, multiple stress creep recovery, linear amplitude scan, and single edge notched beam test. Based on this, the significant factors affecting asphalt mechanical properties were identified by analysis of variance. Subsequently, the Palierne-C-G* parameter was used to quantify the interaction between modified asphalt and anti-icing filler, and the effect of asphalt chemical structure on the interaction was revealed by Fourier Transform Infrared Spectroscopy (FTIR) test. The results indicated that the anti-icing filler significantly improved the high temperature and fatigue resistance of asphalt. Compared with SBS modified asphalt mortar, the mechanical properties of composite modified asphalt mortar were superior. The most significant factor affecting the mechanical properties of SBS modified asphalt mortar was modifier dosage, while the most significant factor affecting the composite modified asphalt mortar was crushed rubber dosage. The interaction showed a decreasing trend with the increase of frequency, while it appeared to increase and then decrease with the increase of temperature. The carbonyl functional group of asphalt correlated best with the interaction between asphalt and filler.

Atmospheric black carbon observations and its valley-mountain dynamics: Eastern cordillera of the central Andes of Peru

Glacial bodies in the Peruvian Andes Mountains store and supply freshwater to hundreds of thousands of people in central Peru. Atmospheric black carbon (BC) is known to accelerate melting of snow and ice, in addition to contributing to air pollution and the health of people. Currently there is limited understanding on the sources and temporal variability of BC in valley and mountain environments in Peru. To address this problem, this study combined surface observations of BC collected during 2022–2023 with WRF model simulations and HYSPLIT trajectories to analyze the dispersion and sources of BC in valley and high elevation environments and the associated local atmospheric circulations. Results show high BC concentrations are associated with the valley-mountain wind system that occurs on both sides of the Huaytapallana mountain range. A pronounced circulation occurs on the western slopes of Huaytapallana when concentrations of BC increase during daylight hours, which transports atmospheric pollutants from cities in the Mantaro River Valley to the Huaytapallana mountain range. Low concentrations of BC are associated with circulations from the east that are channeled by the pronounced ravines of the Andes-Amazon transition. On average, during the season of highest BC concentrations (July–November), the relative contributions of fossil fuels are dominant to biomass burning at the valley observatory and are slightly lower at the Huaytapallana observatory. These results demonstrate the need to promote mitigation actions to reduce emissions of BC and air pollution associated with forest fires and local anthropogenic activity.

Elevation dependent climate assessment and its influence on snow cover variability in Hindu Kush Himalayan region using Google Earth Engine for the period of 2003–2021

The Hindu Kush Himalayan (HKH) regions are taken for this study, which is predominantly characterized by amplified climatic uncertainty and rapid snow melting. Because at the present there is a lack of studies estimating the elevation dependent and climate influenced snow cover variability in the HKH region. This present study examines elevation-dependent (2003–2021) distribution and trends in precipitation, temperature, and snow cover area (SCA) by employing numerous non-parametric statistical applications using the Google Earth Engine (GEE). The Modified Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua snow cover data is employed to estimate SCA along with the Climate Hazards Group Infrared Precipitation with Station Data version 2.0 (CHIRPS-V2.0) for precipitation and MODIS land surface temperature (LST). The study reveals statistically significant decreasing annual, seasonal, and monthly trends of SCA in most of the elevation zones typically during winter season (−0.256%/year), whereas temperature and precipitation exhibit strong spatial variability. Inclusive investigation portrays maximum mean annual and seasonal increased precipitation at the low-elevated regions, whereas seasonal disparities in temperature ostensible marginal decreased at high-elevation, albeit increased at lowland. Moreover, topographic importance on SCA distribution showcases maximum snow (43.4%) at north-facing less surface inclination with flat topography (14.6%). The comprehensive elevation wise analysis improves our understanding of the overall hydrological challenge and assist in the development of more reliable flood forecasting and water resource management.

Estimating Stage-Frequency Curves for Engineering Design in Small Ungauged Arctic Watersheds

The design of hydraulic structures in the Arctic is complicated by shallow relief, which cause unique runoff processes that promote snow-damming and refreeze of runoff. We discuss the challenges encountered in modeling snowmelt runoff into two coastal freshwater lagoons in Utqiaġvik, Alaska. Stage-frequency curves with quantified uncertainty were required to design two new discharge gates that would allow snowmelt runoff flows through a proposed coastal revetment. To estimate runoff hydrographs arriving at the lagoons, we modeled snowpack accumulation and ablation using SnowModel which in turn was used to force a physically-based hydraulic runoff model (HEC-RAS). Our results demonstrate the successful development of stage-frequency curves by incorporating a Monte Carlo simulation approach that quantifies the variability in runoff timing and volume. Our process highlights the complexities of Arctic hydrology by incorporating significant delays in runoff onset due to localized snow accumulation and melting processes. This methodology not only addresses the uncertainty in snow-damming and refreeze processes which affect the arrival time of snowmelt inflow peaks, but is also adaptable for application in other challenging environments where secondary runoff processes are predominant.

Dissolving the mystery of subsurface controls on snowmelt–discharge dynamics in karst mountain watersheds using hydrologic timeseries

AbstractStreamflow generation in mountain watersheds is strongly influenced by snow accumulation and melt as well as groundwater connectivity. In mountainous regions with limestone and dolomite geology, bedrock formations can host karst aquifers, which play a significant role in snowmelt–discharge dynamics. However, mapping complex karst features and the resulting surface‐groundwater exchanges at large scales remains infeasible. In this study, timeseries analysis of continuous discharge and specific conductance measurements were combined with gridded snowmelt predictions to characterize seasonal streamflow response and evaluate dominant watershed controls across 12 monitoring sites in a karstified 554 km2 watershed in northern Utah, USA. Immense surface water hydrologic variability across subcatchments, years and seasons was linked to geologic controls on groundwater dynamics. Unlike many mountain watersheds, the variability between subcatchments could not be well described by typical watershed properties, including elevation or surficial geology. To fill this gap, a conceptual framework was proposed to characterize subsurface controls on snowmelt–discharge dynamics in karst mountain watersheds in terms of conduit flow direction, aquifer storage capacity and connectivity. This framework requires only readily measured surface water and climatic data from nested monitoring sites and was applied to the study watershed to demonstrate its applicability for evaluating dominant controls and climate sensitivity.

Pollution Characteristics and Sources of Ambient Air Dustfall in Urban Area of Beijing

Since 2016, the Ministry of Ecology and Environment and the Beijing Municipal Government have adjusted the minimum concentration limit for ambient air dustfall several times, indicating that they attach great importance to dustfall. To grasp the pollution characteristics and sources of dustfall, in this work, the filtration method was used to determine the insoluble dustfall and water-soluble dustfall in the urban area of Beijing. From our analysis, the influence of the meteorological parameters on dustfall was found, and the chemical components of dustfall were determined. The positive matrix factorization (PMF) model was also utilized to analyze the sources of dustfall. The results indicated that the average amount of dustfall in 2021–2022 was 4.4 t·(km2·30 d)−1, and the proportion of insoluble dustfall deposition was 82.4%. Dustfall was positively correlated with the average wind speed and temperature and negatively correlated with the relative humidity and rain precipitation. The impact of the meteorological parameters on insoluble dustfall and water-soluble dustfall was the opposite. The average proportions of crustal material, ions, organic matter, element carbon, trace elements, and unknown components were 48%, 16%, 14%, 1.4%, 0.20%, and 20%, respectively. The proportions of the crustal material and ions were the highest in spring (57%) and summer (37%). The contribution rates of fugitive dust source, secondary inorganic source, mobile source, coal combustion source, snow melting agent source, and other sources were 42.4%, 19.3%, 8.3%, 3.0%, 2.7%, and 24.3%, respectively. This study supported dustfall pollution control by analysing the pollutant characteristics and sources of dustfall from the standpoint of total chemical components. In order to better control dustfall pollution, control measures and evaluation standards for fugitive dust pollution should be formulated.