Annual Snowmelt Research Articles

Susceptibility assessment of glacier-related debris flow on the southeastern Tibetan Plateau using different hybrid machine learning models

The southeastern Tibetan Plateau (SETP) is a construction area of several key infrastructure projects in China, such as the Sichuan-Tibet Railway and hydropower developments, which has historically faced the threat of glacier-related debris flows. However, a robust assessment of such debris flow susceptibility is a challenge due to the complex and variable climate, terrain and glacial environment. In this study, we used the hybrid models that combine statistical techniques (certainty factors, CF) with machine learning methods (logistic regression, LR; random forest, RF; extreme gradient boosting, XGBoost) to more accurately identify debris flow susceptible (DFS) areas. Topography, geology, and hydrological factors including glaciers and snow cover were used in these models to assess the DFS. Results show that 21 % to 42 % of the study area is very high susceptible to debris flows, particularly from Ranwu to Bomi and around Namcha Barwa. The hybrid models effectively enhance the accuracy of the DFS assessments. The CF-RF model showed the greatest improvement, with an 8.4 % increase in accuracy compared to the single model, the DFS spatial distribution of which aligns closely with field survey results. The glacial area ratio and annual snowmelt positively impact DFS accuracy, ranking 2nd and 9th in the factor importance, respectively. The results of this research could provide valuable assistance and guidance in mitigating glacier-related debris flow hazards.

Predictive Analytics of Air Temperature in Alaskan Permafrost Terrain Leveraging Two-Level Signal Decomposition and Deep Learning

Local weather forecasts in the Arctic outside of settlements are challenging due to the dearth of ground-level observation stations and high computational costs. During winter, these forecasts are critical to help prepare for potentially hazardous weather conditions, while in spring, these forecasts may be used to determine flood risk during annual snow melt. To this end, a hybrid VMD-WT-InceptionTime model is proposed for multi-horizon multivariate forecasting of remote-region temperatures in Alaska over short-term horizons (the next seven days). First, the Spearman correlation coefficient is employed to analyze the relationship between each input variable and the forecast target temperature. The most output-correlated input sequences are decomposed using variational mode decomposition (VMD) and, ultimately, wavelet transform (WT) to extract time-frequency patterns intrinsic in the raw inputs. The resulting sequences are fed into a deep InceptionTime model for short-term forecasting. This hybrid technique has been developed and evaluated using 35+ years of data from three locations in Alaska. Different experiments and performance benchmarks are conducted using deep learning models (e.g., Time Series Transformers, LSTM, MiniRocket), and statistical and conventional machine learning baselines (e.g., GBDT, SVR, ARIMA). All forecasting performances are assessed using four metrics: the root mean squared error, the mean absolute percentage error, the coefficient of determination, and the mean directional accuracy. Superior forecasting performance is achieved consistently using the proposed hybrid technique.

ОСОБЕННОСТИ ДОЛГОВРЕМЕННЫХ ФАЗ ПОВЫШЕННОЙ И ПОНИЖЕННОЙ ВОДНОСТИ ДОНА И ЛЕНЫ В XIX-XXI ВЕКАХ

The results of studying long-term (lasting 10-15 years or more) phases of decreased and increased conditionally natural annual and seasonal runoff of the Don River near the village of Razdorskaya and the Lena River near the village of Kyusyur are considered. The retrieval of long-term water flow time series (excluding the changes that are caused by anthropogenic impacts from the observed water flow) is based on the transformation of the annual hydrograph of average daily water flow using the Kalinin-Milyukov method. The long-term phases of annual and seasonal runoff have been identified on the basis of cumulative deviation curves and criteria for statistical homogeneity of time series by their averages. For the entire period of observations on the Don (1891-2019) and the Lena (1936-2019), two cardinally different types of long-term dynamics for contrasting phases of annual and seasonal runoff that are characteristic of these rivers and common in most of Russia have been revealed. On the Lena, the phases of decreased and increased values of annual and seasonal runoff have changed quasisynchronously, whereas on the Don, the phases of annual runoff and snow melt flood runoff on the one hand and summer-autumn and winter runoff on the other hand have changed asynchronously. The main characteristics of the contrast phases have been determined.

Spatial distribution and controls of snowmelt runoff in a sublimation-dominated environment in the semiarid Andes of Chile

Abstract. Sublimation is the main ablation component of snow in the upper areas of the semiarid Andes (∼ 26 to ∼ 32∘ S and ∼ 69 to ∼ 71∘ W). This region has elevations up to 6000 m, is characterized by scarce precipitation, high solar radiation receipt, and low air humidity, and has been affected by a severe drought since 2010. In this study, we suggest that most of the snowmelt runoff originates from specific areas with topographic and meteorological features that allow large snow accumulation and limited mass removal. To test this hypothesis, we quantify the spatial distribution of snowmelt runoff and sublimation in a catchment of the semiarid Andes using a process-based snow model that is forced with field data. Model simulations over a 2-year period reproduce point-scale records of snow depth (SD) and snow water equivalent (SWE) and are also in good agreement with an independent SWE reconstruction product as well as satellite snow cover area and indices of winter snow absence and summer snow persistence. We estimate that 50 % of snowmelt runoff is produced by 21 %–29 % of the catchment area, which we define as “snowmelt hotspots”. Snowmelt hotspots are located at mid-to-lower elevations of the catchment on wind-sheltered, low-angle slopes. Our findings show that sublimation is not only the main ablation component: it also plays an important role shaping the spatial variability in total annual snowmelt. Snowmelt hotspots might be connected with other hydrological features of arid and semiarid mountain regions, such as areas of groundwater recharge, rock glaciers, and mountain peatlands. We recommend more detailed snow and hydrological monitoring of these sites, especially in the current and projected scenarios of scarce precipitation.

Estimating surface water availability in high mountain rock slopes using a numerical energy balance model

Abstract. Water takes part in most physical processes that shape mountainous periglacial landscapes and initiation of mass-wasting processes. An observed increase in rockfall activity in high mountain regions was previously linked to permafrost degradation, and water that infiltrates into rock fractures is one of the likely drivers of processes related to thawing and destabilization. However, there is very little knowledge of the quantity and timing of water availability for infiltration into steep rock slopes. This knowledge gap originates from the complex meteorological, hydrological, and thermal processes that control snowmelt, as well as challenging access and data acquisition in extreme alpine environments. Here we use field measurements and numerical modeling to simulate the energy balance and hydrological fluxes on a steep high-elevation permafrost-affected rock slope at Aiguille du Midi (3842 m a.s.l, France), in the Mont Blanc massif. Our results provide new information about water balance at the surface of steep rock slopes. Model results suggest that only ∼ 25 % of the snowfall accumulates in our study site; the remaining ∼ 75 % is likely transported downslope by wind and gravity. The snowpack thickness was found to decrease with surface slopes between 40 and 70∘. We found that among all water fluxes, sublimation is the main process of snowpack mass loss at our study site. Snowmelt occurs between spring and late summer, but most of it may not reach the rock surface due to refreezing and the formation of an impermeable ice layer at the base of the snowpack, which was observed at the field site. The annual snowmelt that is available for infiltration (i.e., effective snowmelt) is highly variable in the simulated years 1959–2021, and its onset occurs mostly between May and August and ends before October. By applying the model to a range of altitudes, we show that effective snowmelt is the main source of water for infiltration above 3600 m a.s.l.; below, direct rainfall on the snow-free surface is the dominant source. This change from snowmelt- to rainfall-dominated water input leads to an abrupt, nonlinear increase in water availability at altitudes below 3600 m a.s.l and may point to higher sensitivity of permafrost-affected rock slopes to climate change at these altitudes.

Modeling compound hydrologic disturbances in the Rio Grande Headwaters

AbstractIn recent decades, the western United States (U.S.) has experienced increasing magnitudes and frequencies of natural land cover disturbances that impact water budget partitioning. Post‐disturbance hydrologic response is often variable at the stream outlet and is difficult to detect and quantify with traditional before–after control–impact studies. This study uses a modified version of the U.S. Geological Survey's Monthly Water Balance Model (MWBM) to simulate and separate the hydrologic response to several forest disturbances, including (1) wildfire, (2) forest conversion (subalpine to mid‐elevation forest) and (3) a climate that is hotter and drier than present in the Rio Grande Headwaters (RGH) in Colorado, U.S. (this climate scenario was derived from an ensemble of climate scenarios from the Coupled Model Intercomparison Project phases 3 and 5, which were selected based on water stress potential in the state of Colorado). We leverage historic post‐disturbance vegetation data in the RGH to add quantitative vegetation representation to the MWBM, then modeled synthetic future (2021–2050) streamflow scenarios as both single and compound disturbances. Relative to a baseline scenario, modeled scenarios predict several changes to average annual water trends over the final simulation decade (2041–2050); (1) decreases in average annual water yield under a hot and dry climate (−14%), except during the rising limb of annual snowmelt; (2) increases in average annual water yield (+32%) and peak runoff under a fire simulation; and (3) increases in average annual water yield (+24%) along with earlier and higher peak runoff under compound (fire + hot/dry) conditions. These findings show the strengths of hydrologic models in separating compound disturbance signals at the stream outlet and a need for quantitative vegetation representation within models to adequately represent dynamic disturbance conditions.

Pacific Barrow’s Goldeneye refine migratory phenology in response to overwintering temperatures and annual snowmelt

Abstract Timing of seasonal bird migrations is broadly determined by internal biological clocks, which are synchronized by photoperiod, but individuals often refine their migratory timing decisions in response to external factors. Using 11 years of satellite telemetry data, we show that Pacific Barrow’s Goldeneye (Bucephala islandica) at higher latitudes initiated spring and molt migrations later and fall migration earlier than individuals at lower latitudes. We further show that individuals refined migratory timing in response to interannual variation in environmental conditions. Individual Barrow’s Goldeneye initiated spring migration earlier in years with warmer springs at their overwintering locations and concluded spring migration earlier in years with earlier annual snowmelt on their breeding grounds. Because individuals respond to conditions both where they initiate and where they conclude spring migration, our results suggest that Barrow’s Goldeneye update their migratory decisions en route. For all 3 migrations in their annual cycle, birds delayed initiating migration if they had been captured and tagged prior to that migration. Birds that initiated migration late for their latitude were less likely to include a stopover and completed that migration faster, partially compensating for delayed departures. Our results are consistent with the hypothesis that Barrow’s Goldeneye uses a combination of endogenous cues and environmental cues in migratory decision making. Sensitivity to environmental cues suggests that Barrow’s Goldeneye may have behavioral plasticity that is adaptive when faced with ongoing climate change.

Simulation of the impact of future changes in climate on the hydrology of Bow River headwater basins in the Canadian Rockies

This study diagnoses the impact of projected changes in climate and glacier cover on the hydrology of several natural flowing Bow River headwater basins in the Canadian Rockies: the Bow River at Lake Louise (∼420.7 km2), the Pipestone River near Lake Louise (∼304.2 km2), the Bow River at Banff (∼2192.2 km2) all of which drain the high elevation, snowy, partially glaciated Central Range, and the Elbow River at Calgary (∼1191.9 km2), which drains the drier Front Ranges and foothills, using models created using the modular, flexible, physically based Cold Regions Hydrological Modelling platform (CRHM). Hydrological models were constructed and parameterised in CRHM from local research results to include relevant streamflow generation processes for Canadian Rockies headwater basins, such as blowing snow, avalanching, snow interception and sublimation, energy budget snow and glacier melt, infiltration to frozen and unfrozen soils, hillslope sub-surface water redistribution, wetlands, lakes, evapotranspiration, groundwater flow, surface runoff and open channel flow. Surface layer outputs from Weather Research and Forecasting (WRF) model simulations for the current climate and for the late 21st century climate under a “business-as-usual” scenario, Representative Concentration Pathway 8.5 (RCP8.5) at 4-km resolution, were used to force model simulations to examine the climate change impact. A projected glacier cover under a “business-as-usual” scenario (RCP8.5) was incorporated to assess the impact of concomitant glacier cover decline. Uncalibrated model simulations for the current climate and glacier coverage showed useful predictions of snow accumulation, snowmelt, and streamflow when compared to surface observations from 2000 to 2015. Under the RCP8.5 climate change scenario, the basins of the Bow River at Banff and Elbow River at Calgary will warm up by 4.7 and 4.5 °C respectively and receive 12% to 15% more precipitation annually, with both basins experiencing a greater proportion of precipitation as rainfall. Peak snow accumulation in Bow River Basin will slightly rise by 3 mm, whilst it will drop by 20 mm in Elbow River Basin, and annual snowmelt volume will increase by 43 mm in Bow River Basin but decrease by 55 mm in Elbow River Basin. Snowcovered periods will decline by 37 and 46 days in Bow and Elbow river basins respectively due to suppressed snow redistribution by wind and gravity and earlier melt. The shorter snowcovered period and warmer, wetter climate will increase evapotranspiration and glacier melt, if the glaciers were held constant, and decrease sublimation, lake levels, soil moisture and groundwater levels. The hydrological responses of the basins will differ despite similar climate changes because of differing biophysical characteristics, climates and hydrological processes generating runoff. Climate change with concomitant glacier decline is predicted to increase the peak discharge and mean annual water yield by 12.23 m3 s−1 (+11%) and 11% in the higher elevation basins of the Bow River but will decrease the mean annual peak discharge by 3.58 m3 s−1 (-9%) and increase the mean annual water yield by 18% in the lower elevation basin of the Elbow River. This shows complex and compensatory hydrological process responses to climate change with the reduced glacier contribution reducing the impact of higher precipitation in high elevation headwaters and drier soil conditions and lower spring snowpacks reducing peak discharges despite increased precipitation during spring runoff in the Front Range and foothills headwaters under a warmer climate.

Diverging Trends in Rain‐On‐Snow Over High Mountain Asia

AbstractRain‐on‐snow (ROS) over snow‐dominated regions such as High Mountain Asia (HMA) modulates snowmelt and runoff and is key contributor in influencing water availability and hazards (e.g., floods and landslides). We studied the trends in ROS in HMA over the past two decades from 2001 to 2018 using the land surface model Noah‐MP driven by an ensemble precipitation data set. Our results show that changes in precipitation phase and rainfall are altering ROS. Because of the strong physical heterogeneity and atmospheric dynamics of HMA, ROS characteristics and trends are region‐dependent and ROS occurs predominantly over the Indus, Ganges‐Brahmaputra, and northwestern basins. In the Indus, ROS representing ∼5% of the annual precipitation and ∼20% of the annual snowmelt, has an increasing trend. This is contrary to the Ganges‐Brahmaputra characterized by decreasing ROS trends, where it represents ∼11% of the annual precipitation and ∼60% of the annual snowmelt. In the northwestern basins, ROS has bidirectional trends due to elevation patterns and trends in rainfall, and it constitutes ∼5 to ∼10% of the annual precipitation. Increasing trends in ROS over Indus contribute to reducing the snowpack in late summer, with concerns of reduced water availability and increased groundwater exploitation. Similarly, because of its high amount and contribution to snowmelt, the decreasing ROS trends in the Ganges‐Brahmaputra will have consequences of decreased recharge from the headwaters and exacerbated use of groundwater unless increasing trends in rainfall compensate for the decreasing snowmelt. These results provide new insights on ROS‐driven changes in the hydrological cycle over HMA.

PCB containment using geosynthetics in Canada's Arctic

Two funnel-and-gate permeable reactive barriers (PRBs) with settling ponds comprised of a composite liner (geomembrane and geosynthetic clay liners (GCL)) were installed at Resolution Island (BAF-5), Nunavut to contain residual polychlorinated biphenyls (PCBs) moving with the sediment and annual snowmelt. The long-term performance of the geosynthetics used in the PRB funnels is studied for physical integrity and diffusive barrier properties after nine years of operation. Exhumed geomembrane specimens are compared with virgin material by index testing: diffusive resistance to benzene, toluene, ethylbenzene, and xylenes (BTEX) compounds, as well as puncture, burst, and tensile strength. Exhumed GCLs are evaluated concerning hydraulic conductivity, the mass of bentonite per unit area, and swell index. The migration of PCBs through the composite liner system by diffusion is modelled and the diffusive and sorptive properties of the geomembrane (Dg = 1.7 × 10−14 m2/s, Sgf = 160,000) and GCL (De = 3.1 × 10−10 m2/s, bentonite plus fibers layer Kd = 15 mL/g, cover geotextile Kd = 12,000 mL/g, and carrier geotextile Kd = 16,000 mL/g) were calculated. Modelling results estimate that the composite liner was successfully containing PCBs. This was confirmed by downgradient monitoring. The challenges of the location and terrain, PRB design, construction, and maintenance are discussed along with recommendations for designing PRBs in other remote and cold region environments.

Climate Change Impacts on the Hydrology of the Brahmaputra River Basin

Climate change (CC) is impacting the hydrology in the basins of the Himalayan region. Thus, this could have significant implications for people who rely on basin water for their lives and livelihoods. However, there are very few studies on the Himalayan river basins. This study aims to fill this gap by presenting a water balance for the Brahmaputra River Basin using the Soil and Water Assessment Tool (SWAT). Results show that snowmelt contributed about 6% of the total annual flow of the whole Brahmaputra, 21% of the upper Brahmaputra, and 5% of the middle Brahmaputra. The basin-wide average annual water yield (AWY) is projected to increase by 8%, with the maximum percentage increase in the pre-monsoon season. The annual snowmelt is projected to decrease by 17%, with a marked decrease during the monsoon but an increase in other seasons and the greatest percentage reduction in the upper Brahmaputra (22%). The contribution of snowmelt to AWY is projected to decrease while rain runoff will increase across the entire Brahmaputra and also in the upper and middle Brahmaputra. The impact assessment suggests that the upper Brahmaputra will be most affected by CC, followed by the middle Brahmaputra. The results can be used to support future water management planning in the basin taking into account the potential impact of CC.

Variation in the hydrological cycle in the Three-River Headwaters Region based on multi-source data

The hydrological processes in the Three-River Headwaters Region (TRHR), which is located in the Qinghai-Tibetan Plateau and includes the Yangtze River Headwater Region (YARHR), the Yellow River Headwater Region (YERHR), and the Lantsang River Headwater Region (LARHR), have changed under climate warming. Based on multi-source data, the spatial and temporal changes in precipitation, evapotranspiration, soil water storage, glacier melt, snowmelt and runoff in the Three-River Headwaters Region from 1982 to 2014 were comprehensively analysed. The annual precipitation data for the Three-River Headwaters Region from ERA5-Land, the Climatic Research Unit, the China Meteorological Forcing Dataset and the Global Land Data Assimilation System (GLDAS) all showed an increasing trend; the annual evapotranspiration data from ERA5-Land, Global Land Data Assimilation System, Global Land Evaporation Amsterdam Model (GLEAM) and Terrestrial Evapotranspiration Dataset across China (TEDC) all showed an increasing trend; and the annual soil water storage data from ERA5-Land, Global Land Data Assimilation System and Global Land Evaporation Amsterdam Model all showed an increasing trend. The annual snowmelt data from ERA5-Land, Global Land Data Assimilation System and SMT-Y datasets all showed a decreasing trend. The annual glacier melt increased in the Yangtze River Headwater Region and Yellow River Headwater Region and decreased in the Lantsang River Headwater Region. The increases in precipitation, evapotranspiration, soil water content and glacial melt, and the decreases in snowfall and snowmelt indicate an accelerated hydrological cycle in the Three-River Headwaters Region over the 1982 to 2014 period. The significant increase in precipitation is the main reason for the significant increase in runoff in the Yangtze River Headwater Region. The increase in precipitation in the Yellow River Headwater Region was less than the sum of the increase in evapotranspiration and soil water storage, resulting in a decreasing trend of runoff in the Yellow River Headwater Region. The increase in precipitation in the Lantsang River Headwater Region was slightly larger than the sum of that in evapotranspiration and soil water storage, and there was an insignificant increase in the runoff in the Lantsang River Headwater Region.

Temporal changes in headwater streams macroinvertebrate assemblages during the snowmelt season in northeast china

Mid-latitude areas such as Northeast China are predicted to have warmer temperature according to IPCC sixth which may influence the duration of the snowmelt season. What remains unknown, however, is how annual snowmelt can influence the biodiversity of macroinvertebrate communities, especially in headwater streams in Northeast China. Here, we investigated the temporal changes (before, during, and after the snowmelt period) of macroinvertebrate communities and stream physicochemical characteristics in five headwater streams in Northeast China. We found that: (1) Macroinvertebrate taxa richness, density, Shannon diversity index, and functional diversity were lower in the melting period than in the other two periods, while biomass and percentage of dominant species were significantly higher in this period; (2) As to functional traits, “erosional”, “strong swimming ability”, “some attachment”, “streamlined shape” and “large size at maturity” traits of the macroinvertebrates taxa were significantly higher in the melting period than in the other two periods; and (3) Redundancy analysis (RDA) and multiple linear regression model found that temperature, turbidity, and velocity were key environmental factors affecting the functional traits of macroinvertebrates during the whole snowmelt process. This study could provide crucial data to support biodiversity conservation and ecosystem restoration of freshwater ecosystems in mid-to high-latitude and alpine areas.

Trends and variability in snowmelt in China under climate change

Abstract. Snowmelt is a major fresh water resource, and quantifying snowmelt and its variability under climate change is necessary for the planning and management of water resources. Spatiotemporal changes in snow properties in China have drawn wide attention in recent decades; however, country-wide assessments of snowmelt are lacking. Using precipitation and temperature data with a high spatial resolution (0.5′; approximately 1 km), this study calculated the monthly snowmelt in China for the 1951–2017 period, using a simple temperature index model, and the model outputs were validated using snowfall, snow depth, snow cover extent and snow water equivalent. Precipitation and temperature scenarios developed from five CMIP5 models were used to predict future snowmelt in China under three different representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5 and RCP8.5). The results show that the mean annual snowmelt in China from 1951 to 2017 is 2.41×1011 m3 yr−1. The mean annual snowmelt values in Northern Xinjiang, Northeast China and the Tibetan Plateau – China's three main stable snow cover regions – are 0.18×1011, 0.42×1011 and 1.15×1011 m3 yr−1, respectively. From 1951 to 2017, the snowmelt increased significantly in the Tibetan Plateau and decreased significantly in northern, central and southeastern China. In the whole of China, there was a decreasing trend in snowmelt, but this was not statistically significant. The mean annual snowmelt runoff ratios are generally more than 10 % in almost all third-level basins in West China, more than 5 % in third-level basins in North and Northeast China and less than 2 % in third-level basins in South China. From 1951 to 2017, the annual snowmelt runoff ratios decreased in most third-level basins in China. Under RCP2.6, RCP4.5 and RCP8.5, the projected snowmelt in China in the near future (2011–2040; mid-future –2041–2070; far future – 2071–2099) may decrease by 10.4 % (15.8 %; 13.9 %), 12.0 % (17.9 %; 21.1 %) and 11.7 % (24.8 %; 36.5 %) compared to the reference period (1981–2010), respectively. Most of the projected mean annual snowmelt runoff ratios in third-level basins in different future periods are lower than those in the reference period. Low temperature regions can tolerate more warming, and the snowmelt change in these regions is mainly influenced by precipitation; however, the snowmelt change in warm regions is more sensitive to temperature increases. The spatial variability in snowmelt changes may lead to regional differences in the impact of snowmelt on water supply.

Changes in snowmelt runoff timing in the contiguous United States

AbstractChanges in timing of snowmelt‐fed streamflow have great importance for water supply, flood management, and ecological processes, as well as being a common indicator of climate change. In this study, snowmelt runoff timing change in the contiguous United States between 1957 and 2016 was investigated by analysing data from 97 streamflow gages. The annual snowmelt runoff timing shift was identified using ‘Center Time (CT)’ and ‘Spring Pulse Onset (SPO)’ methods, jointly with the monthly fractional streamflow (MFS) analysis, conducted between January and June. Since snowmelt‐derived streamflow timing change is mainly induced by regional meteorological factors, such as air temperature and precipitation, their trends and relationship with CT were also examined. Shifts toward earlier snowmelt runoff timing were found by both methods, CT (8.3 days on average) and SPO (8.5 days on average). Although the results of the CT change are stronger than the SPO change, both outcomes are mostly correlated, particularly in the central and northwestern parts of the country. MFS trends support the outcomes of CT and SPO. In January, February, and especially March, a higher number of the stations indicated increasing trends in MFS. In April, May, and June, their number decreased and the number of gages with diminishing trends rose sharply. The timing difference is highly related to temperature change. Annual average temperature and temperature in the melting period increase considerably. The annual average temperature is significantly negatively correlated with CT in the vast majority of the regions. Although precipitation is not as effective as the temperature, its trends have impacts on snowmelt runoff timing change depending on the region and elevation. These results demonstrate the importance of the impacts of snowmelt runoff timing changes due to global warming on the regional and large‐scale hydrology in the contiguous United States.

Seasonal and diurnal fluctuations of coarse particulate organic matter transport in a snowmelt‐dominated stream

AbstractWe measured coarse particulate organic matter (CPOM) transport along a wood‐rich, pool‐riffle mountain stream in the Southern Rockies of Colorado, USA, to examine how spatial variations in storage features and temporal variations in discharge influence the transport of CPOM. Ecologists have found that the majority of annual CPOM export occurs during periods of high discharge. More recently, geomorphologists have begun to examine the transport of CPOM as bedload. There has been, however, little direct sampling of CPOM to evaluate how shorter (diurnal) and longer (seasonal peak flow) variations in discharge affect CPOM transport, and no examination of where CPOM is transported in the water column (primarily in suspension or as bedload). We collected CPOM moving as bedload, in suspension (at 0.6 of the flow depth) and at the surface to evaluate CPOM transport processes. Samples were collected at three sites: (1) in the backwater pool upstream from a channel‐spanning logjam; (2) immediately downstream from the logjam; and (3) in a riffle about 10 bankfull‐channel‐widths downstream from any channel‐spanning logjams. During sample sets, we collected samples over 15‐min increments at approximately 4‐hr intervals over a 24‐hr period. Seven sample sets were distributed over a period of 2 months that spanned the rise, peak, and recession of the annual snowmelt flood. We found that the majority of CPOM is transported in suspension following a clockwise hysteresis loop in which CPOM peaks prior to discharge during the seasonal hydrograph.

A Modified ABCD Model with Temperature-Dependent Parameters for Cold Regions: Application to Reconstruct the Changing Runoff in the Headwater Catchment of the Golmud River, China

The runoff changes due to global warming in hydrological basins in the Qinghai–Tibetan Plateau (QTP) have received worldwide attention. The headwater catchment of the Golmud River, located in the northern QTP, is the main source of water resources for the Golmud city in an arid region but has been poorly known for the hydroclimatological behaviors. In this study, a widely-used hydrological model, the ABCD model (Thomas, H.A., Washington, DC, USA), is modified by incorporating temperature-dependent hydrological processes and groundwater evapotranspiration in cold regions with a few additional parameters. The new model is used to reconstruct the monthly runoff in the past decades for the headwater catchment of the Golmud River and performs better than other comparable models. As indicated, the annual snowmelt runoff increased with the increasing air temperature and became more concentrated in April than in May. The frozen soil degradation could increase the hydraulic conductivity of soils and lead to a rise in cold season runoff. The groundwater level in the Golmud city was positively correlated to the annual runoff in the headwater catchment of the Golmud River, indicating that an increase of the groundwater level could be triggered by the rising trend in the streamflow of the Golmud River. This study suggests a useful hydrological model for the groundwater management in the Golmud city.

Borehole monitoring of thermo-hydro-mechanical rock slope processes adjacent to an actively retreating glacier

Most natural rock slope failures result from long-term strength degradation. It is often hypothesized that glacial retreat leads to enhanced progressive damage accumulation in adjacent rock slopes, due to mechanical unloading and changes to the thermal and hydraulic boundary conditions. However, direct observations of subsurface processes in a rock slope subject to glacial retreat are rare. In this paper, we present the design, implementation, and performance of a new borehole monitoring system installed on a rock slope in fractured crystalline rock located beside the glacier tongue of the retreating Great Aletsch Glacier (Valais, Switzerland). The three vertical, 50 m deep boreholes were instrumented to continuously monitor groundwater pressure, temperature and deformation at high resolution, in order to investigate thermo-hydro-mechanical coupled slope processes that drive progressive rock mass damage. We show that the system is capable of measuring both reversible and irreversible displacements along single fractures at magnitudes ranging between 0.001 mm to >2 mm in the studied rock slope, and that it is often possible to identify drivers of these deformation signals. The transient subsurface temperature field shows clear indications of former ice occupation in form of cold temperatures preserved at depth and superimposed annual temperature cycles penetrating down to a depth of about 17 m. The variability of the pressure head in the slope is driven by annual snowmelt infiltration cycles, rainfall events, and the assumed connection to englacial water of the temperate glacier. The new and continuously growing dataset presented here will enable us to relate the changing boundary conditions caused by glacial retreat and fatigue from daily to annual thermal and hydraulic loading cycles to progressive rock mass weakening, which may ultimately result in rock slope failure.

Channel narrowing by inset floodplain formation of the lower Green River in the Canyonlands region, Utah

AbstractThe lower Green River episodically narrowed between the mid-1930s and present day through deposition of new floodplains within a wider channel that had been established and/or maintained during the early twentieth century pluvial period. Comparison of air photos spanning a 74-yr period (1940–2014) and covering a 61 km study area shows that the channel narrowed by 12% from 138 ± 3.4 m to 122 ± 2.1 m. Stratigraphic and sedimentologic analysis and tree ring dating of a floodplain trench corroborates the air photo analysis and suggests that the initial phase of floodplain formation began by the mid-1930s, approximately the same time that the flow regime decreased in total annual and peak annual flow. Tamarisk, a nonnative shrub, began to establish in the 1930s as well. Narrowing from the 1940s to the mid-1980s was insignificant, because floodplain formation was approximately matched by bank erosion. Air photo analysis demonstrates that the most significant episode of narrowing was underway by the late 1980s, and analysis of the trench shows that floodplain formation had begun in the mid-1980s during a multi-year period of low peak annual flow. Air photo analysis shows that mean channel width decreased by ∼7% between 1993 and 2009. A new phase of narrowing may have begun in 2003, based on evidence in the trench. Comparison of field surveys made in 1998 and 2015 in an 8.5 km reach near Fort Bottom suggests that narrowing continues and demonstrates that new floodplain formation has been a very small proportion of the total annual fine sediment flux of the Green River. Vertical accretion of new floodplains near Fort Bottom averaged 2.4 m between 1998 and 2015 but only accounted for ∼1.5% of the estimated fine sediment flux during that period. Flood control by Flaming Gorge Dam after 1962 significantly influenced flow regime, reducing the magnitude of the annual snowmelt flood and increasing the magnitude of base flows. Though narrowing was initiated by changes in flow regime, native and nonnative riparian vegetation promoted floodplain formation and channel narrowing especially through establishment on channel bars and incipient floodplains during years of small annual floods.

Examining the pluvial to nival river regime spectrum using nonlinear methods: Minimum delay embedding dimension

The nonlinear dynamics of streamflow time series from 667 reference hydrometric stations in North America spanning the pluvial-nival hydrological continuum are explored using minimum embedding dimensions as determined by False Nearest Neighbor (FNN) methods. Simulations using synthetic time series demonstrate that snowmelt dominated time series have lower embedding dimensions than those that are rainfall dominated, and that mixtures of the two processes result in a nearly linear change in the embedding dimension. The majority of the reference hydrometric stations drop below a 1% threshold at a dimension less than 30, showing a high degree of natural complexity in the signals ranging from annual snowmelt to weather-driven pseudo-stochastic systems. A less restrictive threshold, 5% is suggested to be more appropriate for streamflow time series. Time series smoothing impacts the embedding dimension and over-smoothing results in incorrect reductions of embedding dimensions. The relationship of the embedding dimensions to watershed and statistical properties of streamflow record showed the lowest embedding dimensions are restricted to large drainage areas, high elevations, and large mean annual flows and variance, high autocorrelations, and large fractions of the records with only small changes in magnitude. Times series that have a large proportion of consecutive days of equal streamflow typically result in higher embedding dimensions. Mapping of the embedding dimension shows spatial patterns related to the streamflow generating processes and geographical features. The use of embedding dimension resolved different dynamics across the hydrological continuum for rainfall to snowmelt over many climate zones. Changes in the embedding dimension might indicate process changes related to climate variability and change.