Simulated Snowmelt Research Articles

Elevation-dependent effects of snowfall and snow cover changes on runoff variations at the source regions of the Yellow River basin

ABSTRACT Accurate simulation of the snowmelt runoff process is of great significance in understanding the evolution of water resources in high-altitude cold regions and achieving efficient utilization of water resources. This study focuses on the source regions of the Yellow River basin (SYRB) and aims to improve the snow identification and snowmelt simulation methods in the WEP-L hydrological model. The results show a significant decrease in the snowfall ratio from 2002 to 2018. The fraction of snow cover decreased at lower altitudes but increased at higher altitudes, displaying an exponential relationship with negative accumulated temperature. Snowmelt was found to be negatively correlated with snowfall and snow cover, with a stronger negative correlation at higher altitudes. The decrease in the snowfall ratio intensified with increasing elevation, while snow cover increased with elevation. However, the overall trend of snowmelt runoff was not significant. These findings highlight the dynamic relationship between snowfall, snow cover, and temperature in the SYRB. By incorporating the established response function, the accuracy of snow identification and snowmelt simulation in the WEP-L model has been enhanced. This study contributes to a better understanding of water resource evolution and the efficient utilization of water resources in high-altitude cold regions.

Release of phosphorus and metal(loid)s from manured soils to floodwater during a laboratory simulation of snowmelt flooding.

Phosphorus (P) and metal accumulation in manured agricultural soils and subsequent losses to waterways have been extensively studied; however, the magnitudes and the factors governing their losses during spring snowmelt flooding are less known. We examined the P and metal release from long-term manured soil to floodwater under simulated snowmelt flooding with recent manure additions. Intact soil columns collected from field plots located in Randolph, Southern Manitoba, 2 weeks after liquid swine manure treatments (surface-applied, injected, or control with no recent manure addition) were flooded and incubated for 8 weeks at 4± 1°C to simulate snowmelt conditions. Floodwater (syringe filtered through 0.45µm) and soil porewater (extracted using Rhizon-Mom samplers) samples were periodically extracted and analyzed for dissolved reactive phosphorus (DRP), pH, zinc (Zn), manganese (Mn), iron (Fe), magnesium (Mg), calcium (Ca), and arsenic (As). Mean floodwater DRP concentrations (mg L-1) for manure injected (2.0±0.26), surface-applied (2.6±0.26), and control (2.2±0.26) treatments did not differ significantly. Despite manure application, DRP loss to floodwater did not significantly increase compared to the control, possibly due to the elevated residual soil P at this site from the long-term manure use. At the end of simulated flooding, the DRP concentrations increased by 1.5-fold and 5-fold in porewater and floodwater, respectively. Metal(loid) concentrations were not affected by manure treatments in general, except for Zn and Mg on certain days. Unlike DRP, where porewater and floodwater concentrations increased with time, metalloid concentration in porewater and floodwater did not show consistent trends with flooding time.

Extension of a Monolayer Energy-Budget Degree-Day Model to a Multilayer One

This paper presents the extension of the monolayer snow model of a semi-distributed hydrological model (HYDROTEL) to a multilayer model that considers snow to be a combination of ice and air, while accounting for freezing rain. For two stations in Yukon and one station in northern Quebec, Canada, the multilayer model achieves high performances during calibration periods yet similar to the those of the monolayer model, with KGEs of up to 0.9. However, it increases the KGE values by up to 0.2 during the validation periods. The multilayer model provides more accurate estimations of maximum SWE and total spring snowmelt dates. This is due to its increased sensitivity to thermal atmospheric conditions. Although the multilayer model improves the estimation of snow heights overall, it exhibits excessive snow densities during spring snowmelt. Future research should aim to refine the representation of snow densities to enhance the accuracy of the multilayer model. Nevertheless, this model has the potential to improve the simulation of spring snowmelt, addressing a common limitation of the monolayer model.

Impact of land surface model schemes in snow-dominated arid and semiarid watersheds using the WRF-hydro modeling systems

<abstract> <p>In the past century, water demand increased extensively due to the rapid growth of the human population. Ground observations can reveal hydrological dynamics but are expensive in the long term. Alternatively, hydrological models could be utilized for assessing streamflow with historical observations as the control point. Despite the advancements in hydrological modeling systems, watershed modeling over mountainous regions with complex terrain remains challenging. This study utilized the multi-physical Weather Research and Forecasting Hydrological enhancement model (WRF-Hydro), fully distributed over the Amu River Basin (ARB) in Afghanistan. The calibration process focused on land surface model (LSM) physics options and hydrological parameters within the model. The findings emphasize the importance of LSM for accurate simulation of snowmelt–runoff processes over mountainous regions. Correlation coefficient (R), coefficient of determination (R<sup>2</sup>), Nash-Sutcliff efficiency (NSE), and Kling-Gupta efficiency (KGE) were adopted for accuracy assessment over five discharge observation stations at a daily time scale; overall performance results were as follows: R was 0.85–0.42, R<sup>2</sup> was 0.73–0.17, NSE was 0.52 to −8.64, and KGE was 0.74 to −0.56. The findings of the current study can support snowmelt process simulation within the WRF-Hydro model.</p> </abstract>

Impacts of Temperature Data Sets on Macroscale Snowmelt Simulations in the Missouri River Basin

Impacts of Temperature Data Sets on Macroscale Snowmelt Simulations in the Missouri River Basin

Drought Timing Modulates Soil Moisture Thresholds for CO2 Fluxes and Vegetation Responses in an Experimental Alpine Grassland

Drought timing determines the degree to which dry events impact ecosystems, with the ability of key processes to withstand change differing between drought periods. Findings indicate that drought timing effects vary across ecosystems, with few studies focusing on alpine grasslands. We conducted a mesocosm experiment using small grassland monoliths collected in September from the high Alps and left to overwinter at 0 °C until the experiment began in lowland Italy under late-winter outdoor conditions. Together with watered controls, we imposed three different drought treatments (zero precipitation): (1) one-month early-drought immediately after simulated snowmelt; (2) one-month mid-drought a month after melt-out; and (3) continuous two-month drought across the entire experimental period. Ecosystem responses were assessed by measuring CO2 fluxes, while vegetation responses were investigated by measuring aboveground net primary production (ANPP) of graminoids and forbs and post-harvest resprouting after one-month rehydration. We found that ecosystem respiration and gross ecosystem production (GEP) during the day were more negatively affected by mid-season drought compared to drought starting early in the season. By the end of treatments, GEP reduction under mid-season drought was similar to that of a continuous two-month drought. ANPP reduction was similar in early- and mid-drought treatments, showing a greater decrease under an enforced two-month period without precipitation. Plant resprouting, however, was only reduced in full- and mid-season drought pots, with forbs more negatively affected than graminoids. Seasonal soil moisture variation can account for these patterns: remaining winter moisture allowed almost full canopy development during the first month of the season, despite precipitation being withheld, while soil moisture depletion in the second month, resulting from higher temperatures and greater biomass, caused a collapse of gas exchange and diminished plant resprouting. Our data illustrates the importance of the timing of zero-precipitation periods for both plant and ecosystem responses in alpine grasslands.

Response of Soil Erosion to Climate and Subsequent Vegetation Changes in a High-Mountain Basin

Soil erosion is one of the global threats to the environment. Further, climate and vegetation changes have pronounced effects on soil erosion in high-mountain areas. In this study, the revised universal soil loss equation (RUSLE) was improved by developing a method for calculating snowmelt runoff erosivity based on a simulated snowmelt runoff and the observed sediment load, using which the soil erosion rate in the upper Heihe River Basin (UHRB) was calculated. The proposed approach provides an effective method for estimating the soil erosion rate and identifying the causes for its change in high-mountain areas. The normalized difference vegetation index (NDVI) was significantly and positively correlated with both precipitation and temperature in the region and exhibited a significant increasing trend. The increase in NDVI led to a decrease in the soil erosion rate (for the annual, rainfall, and snowmelt periods), although erosive rainfall and snowmelt runoff showed increasing trends, indicating the dominating impact of vegetation cover on soil erosion. The average soil erosion rate of UHRB was 806.2 t km−2 a−1 from 1982 to 2015. On average, soil erosion during rainfall and snowmelt periods contributed to 90.67% and 9.33% of annual soil erosion, respectively. However, the resultant soil erosion rate caused by 1 mm of snowmelt runoff was about 1.9 times that caused by 1 mm erosive rainfall. Soil erosion during the snowmelt period was particularly sensitive to temperature and showed consistent responses to climate and vegetation changes in UHRB and its two tributaries. An increasing NDVI promoted by climate change and anthropogenic factors played a major role in alleviating soil erosion, and the warming exerted intense impacts on soil erosion during the snowmelt period. These findings would be helpful for proposing effective measures for soil conservation in high-mountain areas under climate and vegetation changes.

Evaluating fall application of soil amendments to mitigate phosphorus losses during spring snowmelt

The potential of soil amendments in reducing phosphorus (P) loss has been reported under simulated snowmelt, but not evaluated in the field, under snowmelt conditions. We examined the effectiveness of alum (Al2(SO4)3·18H2O), gypsum (CaSO4·2H2O), and Epsom salt (MgSO4·7H2O) in reducing P loss from two flood-prone agricultural fields (non-manured field with initial soil test P concentrations, STP, of 76 mg kg−1 and manured field with initial STP of 202 mg kg−1), during snowmelt on Canadian Prairies. Amendments were applied (2.5 Mg ha−1) in 2020 fall to four replicated plots (3 m × 1 m) with pre-installed runoff boxes (1.2 m × 0.9 m). In the 2021 spring, snowmelt water in each runoff box was pumped out, volume recorded for each sampling day, and analysed for dissolved reactive P (DRP). Snowmelt DRP concentrations was greater in manured soil (0.73 ± 0.23 mg L−1) with high STP, than in non-manured soil (0.28 ± 0.10 mg L−1.) with low STP, implying a greater risk of P loss to snowmelt runoff when STP is high. Cumulative snowmelt DRP loads in non-manured soil ranged from 3.1 to 3.8 mg (equivalent to 0.03–0.04 kg ha−1) and were not significantly different among treatments. In the control treatment of the manured soil, the cumulative snowmelt DRP load from runoff boxes was 20.8 mg (equivalent to 0.19 kg ha−1), while amended treatments had 42 to 68 % lower cumulative DRP load than control, with the difference being significant only in Epsom salt treatment. Cumulative snowmelt DRP load was significantly and positively correlated to cumulative snowmelt volume (R2 = 0.84 for each soil). This study shows the potential of fall application of soil amendments, particularly Epsom salt, to reduce P loss to snowmelt from soils with high STP.

When and Where Are Multiple Snow Layers Important for Simulations of Snow Accumulation and Melt?

AbstractMany watershed‐scale and land surface models incorporate snowmelt modules with simplified representations of the snowpack with three or fewer layers. These modeling choices were traditionally made to reduce model complexity and computational demand while still being able to simulate large model domains. However, these simple snow layering schemes may not always simulate snow processes and the effects of climate change across a range of climatic and geographic conditions. Here we evaluate simple snow layering schemes (having two to five layers, commonly found in watershed‐scale and land surface models) against a synthetic benchmark with up to 100 layers at three locations with different climate conditions using the SUMMA modeling framework. We evaluate 10 different layering configurations of two to five layers with variable thicknesses and show that the effect of the layering scheme varies with site conditions. We find that the layer configuration is more important at a cold high elevation site in the Sierra Nevada, California (∼1.4°C annual average temperature), and at a warm site in the French Alps (∼6.5°C), and less important at a site in Idaho (∼5.0°C). The top layer thickness of the simpler snow layering configurations also influences the simulated snow surface and snowpack temperatures and timing of snowmelt. Our tests showed that the five‐layer model with thin layers near the surface was closest to the benchmark (median NSE = 0.99), and therefore we recommend using multiple snow layers for reliable simulations of snow accumulation and melt across a range of climates.

A dynamic snow accumulation simulation approach for forecasting snow distribution over regional‐scale terrain

AbstractEconomic losses due to snow‐related disasters in pastoral areas of China have become severe in recent decades. Terrain and wind play prominent roles in determining snow distribution patterns. As complex topography and dynamic wind conditions are strong nonlinear multivariables with many uncertain factors, it is difficult to predict elevation‐ and wind‐affected snow depth distribution. The complex characteristics of the snow accumulation process call for highly reliable comprehensive simulation for disaster management. The accuracy of these simulations mainly depends on the integration of multiple models for multi‐stage snow accumulation processes. Focusing on coupling wind‐affected snowdrift and snowmelt processes, we put forward a virtual geographical environment snow accumulation simulation approach. The approach consists of three main steps: (1) computational fluid dynamics prediction of 3D dynamic wind‐flow fields; (2) wind‐affected snowdrift simulation; and (3) snowmelt simulation based on degree‐day model. To check its reliability and efficiency, this approach has been validated by reconstructing a historical snow event at Tacheng City, Xinjiang Province, China. The results have characterized the elevation‐ and wind‐induced snowdrift patterns and their specific levels of risk under various conditions. The comprehensive simulation method described here can be applied to help the government and the public examine future events, and stimulate consideration of appropriate policies and techniques for snow risk mitigation.

Ferric chloride amendment reduces phosphorus losses from flooded soil monoliths to overlying floodwater

The accumulation of phosphorus (P) in agricultural soils and subsequent losses to waterways contribute to eutrophication in surface water bodies. In agricultural lands prone to prolonged flooding during spring snowmelt, P may be released to overlying floodwater and transported to lakes downstream. Ferric chloride (FeCl3) is a potential soil amendment to mitigate P losses, but its effectiveness for flooded soils with snowmelt is not well documented. Thirty-six intact soil monoliths taken from four agricultural fields in Manitoba's Red River Valley region were surface-amended with FeCl3 at three rates (0, 2.5, and 5 Mg ha–1) to evaluate the effectiveness of FeCl3 in minimizing P losses to porewater and floodwater. Over 8 weeks of simulated snowmelt flooding, porewater, and floodwater samples taken weekly were analyzed for concentrations of dissolved reactive P (DRP), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), and pH. Change in the redox potential was also measured weekly. With time of flooding, redox potential decreased in all soil monoliths. At early stages of flooding, the porewater pH values were significantly lower in FeCl3-amended monoliths but increased with flooding time. Porewater and floodwater DRP concentrations increased in all soils when flooded, but the magnitudes varied. Amendment of FeCl3 decreased the DRP concentrations from 17% to 97% in porewater and 26% to 99% in floodwater, with the effectiveness varying depending on the soil, FeCl3 rate, and flooding time. Amendment of FeCl3 increased porewater concentrations of Ca, Mg, Fe, and Mn. Soil amendment with FeCl3 at both rates shows promise in mitigating redox-induced P losses from flooded soils.

Alum and Gypsum Amendments Decrease Phosphorus Losses from Soil Monoliths to Overlying Floodwater under Simulated Snowmelt Flooding

Phosphorus (P) loss from soils poses a threat of eutrophication to downstream waterbodies. Alum (Al2(SO4)3·18H2O) and gypsum (CaSO4·2H2O) are effective in reducing P loss from soils; however, knowledge on their effectiveness under cold temperatures is limited. This study examined the reduction of P loss from soils with alum and gypsum amendment under simulated snowmelt flooding. Intact soil monoliths (15 cm depth) collected from eight agricultural fields in flood-prone areas of Manitoba, Canada, were surface amended with alum or gypsum, pre-incubated for 2 weeks, then flooded and incubated at 4 °C for 8 weeks. Porewater and floodwater samples collected weekly were analyzed for dissolved reactive P (DRP), dominant cations and anions. An enhanced P release with flooding time was observed in all soils whether amended or unamended; however, alum/gypsum amendment reduced DRP concentrations in porewater and floodwater in general, with alum showing a more consistent effect across soils. The reduction in floodwater DRP concentrations (maximum DRP concentration during flooding) with alum and gypsum ranged from 34–90% and 1–66%, respectively. Based on Visual MINTEQ thermodynamic model predictions, precipitation of P and formation of P-sorbing mineral species with alum and gypsum amendment reduced DRP concentrations at latter stages of flooding.

Assessment of Climate Change Impact on Snowmelt Runoff in Himalayan Region

Under different climate change scenarios, the current study was planned to simulate runoff due to snowmelt in the Lidder River catchment in the Himalayan region. A basic degree-day model, the Snowmelt-Runoff Model (SRM), was utilized to assess the hydrological consequences of change in the climate. The performance of the SRM model during calibration and validation was assessed using volume difference (Dv) and coefficient of determination (R2). The Dv was found to be 11.7, −10.1, −11.8, 1.96, and 8.6 in 2009–2014, respectively, while the respective R2 was 0.96, 0.92, 0.95, 0.90, and 0.94. The Dv and R2 values indicate that the simulated snowmelt runoff closely agrees with the observed values. The simulated findings were assessed under three different climate change scenarios: (a) an increase in precipitation by +20%, (b) a temperature rise of +2 °C, and (c) a temperature rise of +2 °C with a 20% increase in snow cover. In scenario (b), the simulated results showed that runoff increased by 53% in summer (April–September). In contrast, the projected increased discharge for scenarios (a) and (c) was 37% and 67%, respectively. The SRM efficiently forecasts future water supplies due to snowmelt runoff in high elevation, data-scarce mountain environments.

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.

Meteorological parameters and water balance components of Priyadarshini Lake at the Schirmacher Oasis, East Antarctica

The meteorological parameters and water balance components of Priyadarshini Lake at Schirmacher Oasis, East Antarctica, were studied using meteorological data procured from the India Meteorological Department (IMD) weather station, Maitri and field observations in summer seasons of 2017–2018 and 2018–2019. Meteorological data was analysed (daily temporal and diurnal variation) for 2018, and the water balance components were estimated for January–February of 2018. The present work revealed the status of meteorological parameters (air temperature, relative humidity, wind speed, and snowfall) at Schirmacher Oasis compared to long-term historical trends at the east and west regions of Antarctica. As Priyadarshini Lake is non-endorheic, it transferred freshwater to the sea at the rate of ∼335 × 103 m3/month during summer season of 2018. The water consumption by Maitri station (term W) is very minimal compared to other terms and does not play a substantial role in the lake's water balance. The limited availability of topographic and historical hydro-meteorological data limits the application of physically based hydrological models to simulate snow melt surface runoff at the inflow and assess the impact of climate change on hydrological regimes of the lake. Thus, long term monitoring of the lake with a permanent gauging network for inflows and outflow will pronounce our understanding and enable the option to assess linkage with changing climate.

A Review on Snowmelt Models: Progress and Prospect

The frequency and intensity of flood events have been increasing recently under the warming climate, with snowmelt floods being a significant part. As an effective manner of simulating snowmelt flood, snowmelt models have attracted more and more attention. Through comprehensive analysis of the literature, this paper reviewed the characteristics and current status of different types of snowmelt models, as well as the different coupling methods of models for runoff generation and confluence. We then discussed key issues in snowmelt modelling, including blowing snow model, frozen ground model, and rain-on-snow model. Finally, we give some perspectives from four aspects: data, model structure, forecast and early warning, and forecast and estimation. At present, most of the snowmelt models do not have blowing snow or frozen ground modules. Explicit consideration of blowing snow and soil freezing/thawing processes can improve the accuracy of snowmelt runoff simulations. With climate warming, rain-on-snow events have increased, but the mechanism of enhanced rain and snow mixed flooding is still unclear, particularly for the mechanism of rain-snow-ice mixed runoff generation. The observation and simulation of rain and snow processes urgently need further study. A distributed physical snowmelt model based on energy balance is an advanced tool for snowmelt simulation, but the model structure and parameter schemes still need further improvements. Moreover, the integration of satellite-based snow products, isotopes, and terrestrial water storage change, monitored by gravity satellites, can help improve the calibration and validation of snowmelt models.

Photooxidation of arsenic in pristine and mine-impacted Canadian subarctic freshwater systems

The redox transformations of arsenic (As) in lakes are thought to be mainly controlled by algal/microbial processes. We tested if photochemical oxidation could also be a significant redox process in northern freshwater systems. We exposed filtered natural water samples from four northern mine-impacted lakes (Northwest Territories, Canada) and three unimpacted ponds (Nunavik, Canada) to simulated solar radiation, and followed As(III) oxidation. During short-term incubation experiments (less than 8 h), all samples amended with As(III) displayed a rapid photooxidation (ca. 0.06-0.27 h−1) whereas no significant oxidation was observed in the dark. This photooxidation process was controlled by UV radiation, was influenced by short-lived oxidants and was partly driven by the concentrations of organic matter. Natural As complexes in unamended water samples were more rapidly photooxidized than in samples with As(III) amendments. Addition of goethite or simulation of snowmelt did not alter photooxidation rates significantly. Overall, these results imply that photooxidation of As should be considered as a potentially significant mechanism controlling inorganic As speciation in aquatic systems. This is particularly true for northern systems affected by mining activities and by changes of inputs of organic matter related to climate change.

Phosphorus mobilization in unamended and magnesium sulfate-amended soil monoliths under simulated snowmelt flooding

Enhanced release of phosphorus (P) from soils with snowmelt flooding poses a threat of eutrophication to waterbodies in cold climatic regions. Reductions in P losses with various soil amendments has been reported, however effectiveness of MgSO4 has not been studied under snowmelt flooding. This study examined (a) the P release enhancement with flooding in relation to initial soil P status and (b) the effectiveness of MgSO4 at two rates in reducing P release to floodwater under simulated snowmelt flooding. Intact soil monoliths were collected from eight agricultural fields from Southern Manitoba, Canada. Unamended and MgSO4 surface-amended monoliths (2.5 and 5.0 Mg ha−1) in triplicates were pre-incubated for 7 days, then flooded and incubated (4 °C) for 56 days. Pore water and floodwater samples collected at 7-day intervals were analyzed for dissolved reactive P (DRP), pH, Ca, Mg, Fe and Mn. Redox potential (Eh) was measured on each day of sampling. Representative soil samples collected from each field were analyzed for Olsen and Mehlich 3-P. Simulated snowmelt flooding enhanced the mobility of soil P with approximately 1.2–1.6 -fold increase in pore water DRP concentration from 0 to 21 days after flooding. Mehlich-3 P content showed a strong relationship with the pore water DRP concentrations suggesting its potential as a predictor of P loss risk during prolonged flooding. Surface application of MgSO4 reduced the P release to pore water and floodwater. The 2.5 Mg ha−1 rate was more effective than the higher rate with a 21–75% reduction in average pore water DRP, across soils. Soil monoliths amended with MgSO4 maintained a higher Eh, and had greater pore water Ca and Mg concentrations, which may have reduced redox-induced P release and favored re-precipitation of P with Ca and Mg, thus decreasing DRP concentrations in pore water and floodwater.

Measurement of Volatile Compounds for Real-Time Analysis of Soil Microbial Metabolic Response to Simulated Snowmelt.

Snowmelt dynamics are a significant determinant of microbial metabolism in soil and regulate global biogeochemical cycles of carbon and nutrients by creating seasonal variations in soil redox and nutrient pools. With an increasing concern that climate change accelerates both snowmelt timing and rate, obtaining an accurate characterization of microbial response to snowmelt is important for understanding biogeochemical cycles intertwined with soil. However, observing microbial metabolism and its dynamics non-destructively remains a major challenge for systems such as soil. Microbial volatile compounds (mVCs) emitted from soil represent information-dense signatures and when assayed non-destructively using state-of-the-art instrumentation such as Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-TOF-MS) provide time resolved insights into the metabolism of active microbiomes. In this study, we used PTR-TOF-MS to investigate the metabolic trajectory of microbiomes from a subalpine forest soil, and their response to a simulated wet-up event akin to snowmelt. Using an information theory approach based on the partitioning of mutual information, we identified mVC metabolite pairs with robust interactions, including those that were non-linear and with time lags. The biological context for these mVC interactions was evaluated by projecting the connections onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) network of known metabolic pathways. Simulated snowmelt resulted in a rapid increase in the production of trimethylamine (TMA) suggesting that anaerobic degradation of quaternary amine osmo/cryoprotectants, such as glycine betaine, may be important contributors to this resource pulse. Unique and synergistic connections between intermediates of methylotrophic pathways such as dimethylamine, formaldehyde and methanol were observed upon wet-up and indicate that the initial pulse of TMA was likely transformed into these intermediates by methylotrophs. Increases in ammonia oxidation signatures (transformation of hydroxylamine to nitrite) were observed in parallel, and while the relative role of nitrifiers or methylotrophs cannot be confirmed, the inferred connection to TMA oxidation suggests either a direct or indirect coupling between these processes. Overall, it appears that such mVC time-series from PTR-TOF-MS combined with causal inference represents an attractive approach to non-destructively observe soil microbial metabolism and its response to environmental perturbation.

Sensitivity of snowmelt runoff modelling to the level of cloud coverage for snow cover extent from daily MODIS product collection 6

Study regionThe Balkhab River Basin in northern Afghanistan Study FocusSnowmelt is a primary water resource in mountainous regions of the world. Remotely sensed snow cover products are useful for obtaining spatial snow information but have unsolved cloud cover issues. Thus, this study demonstrates (1) a spatiotemporal combination approach for reducing cloud cover and improving the accuracy in snow cover extent (SCE) estimation from 2010 to 2018 using the MODIS daily snow cover product version 6 and (2) the sensitivity of snowmelt runoff modelling to SCE inputs with different levels of cloud cover from 2012 to 2014 using a snowmelt runoff model (SRM). New Hydrological Insights for the RegionThe average cloud coverages of the original MODIS Aqua and Terra daily products for the study region and period were reduced from 37.66 % and 31.88 % to 25.9 % after the spatial combination and to 14.28 % and 8.94 %, respectively, after the temporal combination. The temporal combination with previous and following days yielded a substantial improvement in cloud removal. The sensitivity of the SRM results to the different levels of clouds clearly depicts the gradual improvement in the simulated snowmelt runoffs with a cloud cover reduction in the SCE input. Interestingly, the SRM performances with the direct SCE input from Aqua or Terra products are degraded in some cases compared to those without SCE input in the SRM. Thus, careful attention is needed when directly applying remotely sensed snow cover products as input variables in snow hydrological modelling. The simulated snowmelt runoffs are improved substantially in the melting season in March-May. The snowmelt runoff peaks in May are due to the temperature increase and are mainly responsible for extreme floods in the arid study region. This study contributes further to agricultural water resource management for crop cultivation during the dry season from June to September and to flood protection during the snowmelt runoff peaks in May with a potential hydraulic engineering solution.