NOAA16卫星积雪识别和参数提取

通过对积雪、地物和云进行光谱分析,指出传统的NOAA-AVHRR可见光和近红外波段进行云雪识别存在困难,而雪在红外波段的低反射性特点是区分云雪的一个可行途径.利用NOAA16气象卫星新增的1.6μm红外波段,对中国北方冬季的卫星积雪图象进行识别,结果显示,云雪可以准确区分.同时,提出了利用AVHRR资料估算积雪面积、积雪深度和积雪时间的方法,并对积雪深度进行了精度检验.     

积雪融雪过程中水、热、溶质耦合运移规律的研究进展

大气污染的加剧,形成大量的酸性雨,在冬季则以酸性雪的形式出现.酸性雪对土壤环境、水环境及生态环境的影响已经引起世界性的关注,而对于积雪、融雪过程中水、热、溶质耦合运移规律的研究是评价和预测这些影响的理论基础.在查阅大量中外相关文献的基础上,对该领域的研究历史、发展现状和尚待解决的问题进行了综述.     

Watershed‐scale controls on snow accumulation in a small montane watershed,southwestern Alberta,Canada

Snow accumulation in mountain headwater basins is a major water source, particularly in semi‐arid environments such as southern Alberta where water resources are stressed and snowmelt supplies more than 80% of downstream runoff. Relationships between landscape predictor variables and snow water equivalent (SWE) were quantified by combining field and LiDar measurements with classification and regression tree analysis over two winter seasons (2010 and 2011) in a small, montane watershed. 2010 was a below average snow accumulation year, while 2011 was well above normal. In both the field and regression tree data, elevation was the dominant control on snow distribution in both years, although snow distribution was driven by melt processes in 2010 and accumulation processes in 2011. The importance of solar radiation and wind exposure was represented in the regression trees in both years. The regression trees also noted the lower importance of canopy closure, slope, and aspect, which was not observed in the field data. This technique could provide an additional method of forecasting annual water supply from melting snow. However, further research is required to address the lack of data collected above treeline, to provide a full‐basin estimate of SWE. Copyright © 2012 John Wiley & Sons, Ltd.     

Prediction of temperature variation within a snowpack in open areas and under different canopy covers

Snow temperature is a major component of many physical processes in a snowpack. The temperature and the change in temperature across a layer have a dominant effect on physical properties of snow grains as well as its hardness, strength, and failure resistance. In this study, temperature and snow cover thickness were measured during the snow season of 2007–2008 in 11 elevation classes and in three different sampling locations, one in an open area and two under different forest canopy covers for each class along Kartalkaya road, Bolu. Each sampling site was visited 44 times to collect data including snow depth, snow surface temperature, ground temperature, and temperature within snowpack at 20‐cm intervals. Seven different models are developed to determine snowpack temperature variations under forest canopy covers and in an open area with different leaf area index values. All models were performed using a multilayer perceptron (MP) method for the Bolu–Kartalkaya area, Turkey. MP approach constitutes a standard form of neural network modeling and can modify two‐layer linear perceptron methods using three and more layers. The ability of MP is to handle complex nonlinear interactions, which ease the natural process of modeling. This method can overcome complex computations using neuron networks, and they can easily nonlinearly link input and output variables. The predictive errors are determined on the basis of mean absolute error and mean square error criteria. The Nash–Sutcliffe sufficiency score showing compliance between observed and predicted values is also calculated. According to the mean absolute error, the mean square error, and the Nash–Sutcliffe sufficiency score criteria, the predictive errors are within reasonable error intervals, justifying the use of the developed MP models for engineering applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Sublimation over seasonal snowpack at the southeastern edge of a desert in central Eurasia

The Gurbantonggut Desert, China, is an ideal site for study of sublimation from the snowpack because there are sparse vegetation and simple topography, and the wind speed is not large enough to blow snow into the atmosphere from the snowpack. Daily sublimation was measured by manual snow lysimeters at 8:00, and an automatic weather station was deployed at the top of a stout longitudinal dune chain at the southeastern edge of the desert. It is shown that on a daily scale, there was an extremely significant no‐intercept linear relationship between the measured sublimation and that calculated by the bulk aerodynamic method, although the former was only 83.8% of the latter. It is also demonstrated that ?10°C and 2 m/s were the thresholds where the sublimation varied with the air temperature and the wind speed. When these two thresholds were exceeded, the sublimation accelerated. However, the air temperature and the wind speed at 2 m above the ground averaged ?17.2°C and 1.3 m/s, respectively, and the percentages of the time when the air temperature was below ?10 °C and the wind speed was below 2 m/s were 76.9% and 85.1%, respectively. As a result, the rate of sublimation was quite low most of the time, and the thin snowpack remained in a quasi‐static state until the melt stage started. Copyright © 2011 John Wiley & Sons, Ltd.     

Towards improved snow water equivalent retrieval algorithms for satellite passive microwave data over the mountainous basins of western USA

Space‐borne passive microwave snow water equivalent (SWE) retrieval algorithms are attractive for continuous SWE monitoring over large mountainous areas. The performance of three SWE retrieval algorithms, which were considered relevant for operational purposes, was examined for each month over the Colorado River Basin. In addition, statistical post‐processing was tested as a means of improving the SWE estimates from each algorithm. The evaluation started with the so‐called Chang equation, which was a pioneer algorithm and is still used in practice. Successive attempts were then made to improve the algorithm's performance through the calibration of the equation's coefficient and through the inclusion of brightness temperature data from various frequency channels. The Chang equation consistently underestimated SWE with average bias between 30 mm in November and more than 300 mm in April and root mean square error (RMSE) exceeding 500 mm at many locations in April. The statistical post‐processing effectively removed the bias and reduced the RMSE by half for all the months. When the Chang equation's coefficients were calibrated at each site, biases were reduced by approximately 85%, and RMSE was reduced by 40%–50%. Finally, the multiple channel equations produced unbiased SWE estimates with RMSEs 50%–60% of those from the Chang equation. However, the statistical post‐processing did not reduce RMSE for both calibrated algorithms. The last algorithm produced the most reliable estimates for at‐site analysis, but its skill deteriorated when analyses were performed over larger areal extents; therefore, it is only recommended for SWE monitoring over smaller areas. For larger areas, the calibrated Chang equation is desirable because it only requires interpolations of a calibrated coefficient, which was spatially coherent. Copyright © 2011 John Wiley & Sons, Ltd.     

Modelling of a snowpack in interaction with a flexible structure using a coupled Lagrangian‐discrete approach

The search to improve protective techniques against natural phenomena such as snow avalanches continues to use classic methods to calculate flexible structures. This paper deals with a new method for designing avalanche protection nets; this method is based on a coupled analysis of both the net structure and the snow mantel using a coupled Lagrangian‐discrete approach. This has led to the development of computational software so that avalanche nets can be easily designed. This tool provides for the evolving forces acting on several parts of the net as a function of the snow situation. Copyright © 2003 John Wiley & Sons, Ltd.     

Snow and stream-water chemistry of the Ganga headwater basin,Garhwal Himalaya,India

Abstract

Studies of the chemical composition of snowpack and stream water were carried out in a catchment having an area of 53km² (31°03′-30°55′N and 78°40′-78°51′E) in the Garhwal Himalaya, India. The dominant ions in the snowpack and stream water were Ca²⁺, Na⁺, NO^? ₃, SO^2- ₄ and HCO^? ₃. Solute patterns in the snowpack show preferential elution. Investigation of the chemical composition of stream water shows that meltwater changes its composition substantially as it passes through soil pathways to the stream. The groundwater flushing perhaps controls the chemical composition of meltwater in the early spring. However, in the period from July to September, the stream water carries the chemical signature of monsoonal precipitation.     

Variable effects of forest canopies on snow processes in a valley of the central Spanish Pyrenees

Snowpacks and forests have complex interactions throughout the large range of altitudes where they co-occur. However, there are no reliable data on the spatial and temporal interactions of forests with snowpacks, such as those that occur in nearby areas that have different environmental conditions and those that occur during different snow seasons. This study monitored the interactions of forests with snowpacks in four forest stands in a single valley of the central Spanish Pyrenees during three consecutive snow seasons (2015/2016, 2016/2017 and 2017/2018). Daily snow depth data from time-lapse cameras were compared with snow data from field surveys that were performed every 10–15 days. These data thus provided information on the spatial and temporal changes of snow–water equivalent (SWE). The results indicated that forest had the same general effects on snowpack in each forest stand and during each snow season. On average, forest cover reduced the duration of snowpack by 17 days, reduced the cumulative SWE of the snowpack by about 60% and increased the spatial heterogeneity of snowpack by 190%. Overall, forest cover reduced SWE total accumulation by 40% and the rate of SWE accumulation by 25%. The forest-mediated reduction of the accumulation rate, in combination with the occasional forest-mediated enhancement of melting rate, explained the reduced duration of snowpacks beneath forest canopies. However, the magnitude and timing of certain forest effects on snowpack had significant spatial and temporal variations. This variability must be considered when selecting the location of an experimental site in a mountainous area, because the study site should be representative of surrounding areas. The same considerations apply when selecting a time period for study.     

On the hydrological difference between catchments above and below the intermittent-persistent snow transition

Because of the importance of snow for river discharge in mountain regions, hydrological research often focuses on seasonally snow-covered zones. However, in many basins the majority of the land surface area is intermittently snow-covered. Discharge monitoring in these areas is less common, so their contributions to downstream rivers remain largely unknown. We evaluated hydrological differences between three intermittently snow-covered (mean annual Jan 1–Jul 3 snow persistence <60%) and two seasonally snow-covered headwater catchments in the Colorado Front Range. We compared water balance variables to evaluate how and why discharge differs between the snow zones and estimated the relative contributions from each snow zone to regional river discharge. We focused on water years 2016–2019 and used a combination of in situ sensors and regional climate datasets. Annual discharge from the intermittent snow zone was low for all three catchments (10–77 mm), despite covering a wide range in annual snow persistence (25%–64%), whereas annual discharge from the seasonal snow zone was up to 73 times higher. Soil moisture in the seasonal snow zone was above field capacity for longer periods of time than in the intermittent snow zone, and the intermittent snow zone was uniquely subject to soil freezing (up to 102 days per year). For most of the year, potential evapotranspiration exceeded rainfall and snowmelt inputs in the intermittent snow zone, but was lower than rainfall and snowmelt inputs in the seasonal snow zone. This is likely a primary driver of the differences in soil moisture and discharge for catchments with a seasonal versus intermittent snow cover. Despite the large difference in discharge between these two snow zones, the intermittent snow zone contributed about a quarter of the discharge in the regional river, highlighting the importance of studying discharge generation across all elevations.