Search results for: snow cover persistence period

Authors: Yinsheng Zhang

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Changes in the extent and amount of snow cover in Eurasia are of great interest because of their vital impacts on the global climate system and regional water resource management. This study investigated the spatial and temporal variability of the snow cover extent (SCE) and snow water equivalent (SWE) of continental Eurasia using the Northern Hemisphere Equal-Area Scalable Earth Grid (EASE-Grid) Weekly SCE data for 1972–2006 and the Global Monthly EASE-Grid SWE data for 1979–2004. The results indicated that, in general, the spatial extent of snow cover significantly decreased during spring and summer, but varied little during autumn and winter over Eurasia in the study period. The date at which snow cover began to disappear in spring has significantly advanced, whereas the timing of snow cover onset in autumn did not vary significantly during 1972–2006. The snow cover persistence period declined significantly in the western Tibetan Plateau as well as the partial area of Central Asia and northwestern Russia but varied little in other parts of Eurasia. ‘Snow-free breaks’ (SFBs) with intermittent snow cover in the cold season were mainly observed in the Tibetan Plateau and Central Asia, causing a low sensitivity of snow cover persistence period to the timings of snow cover onset and disappearance over the areas with shallow snow. The averaged SFBs were 1–14 weeks in the Tibetan Plateau during 1972–2006 and the maximum intermittence could reach 25 weeks in some extreme years. At a seasonal scale, the SWE usually peaked in February or March but fell gradually since April across Eurasia. Both annual mean and annual maximum SWE decreased significantly during 1979–2004 in most parts of Eurasia except for eastern Siberia as well as northwestern and northeastern China.

Keywords: Eurasia, snow cover extent, snow cover persistence period, snow-free breaks, onset and disappearance timings, snow water equivalent

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Authors: Muhammad Tayyab Afzal, Muhammad Arslan, Mirza Muhammad Waqar

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Snow constitutes an important component of the cryosphere, characterized by high temporal and spatial variability. Because of the contribution of snow melt to water availability, snow is an important focus for research on climate change and adaptation. MODIS satellite data have been used to identify spatial-temporal trends in snow cover in the upper Indus basin. For this research MODIS satellite 8 day composite data of medium resolution (250m) have been analysed from 2001-2005.Pixel based supervised classification have been performed and extent of snow have been calculated of all the images. Results show large variation in snow cover between years while an increasing trend from west to east is observed. Temperature data for the Upper Indus Basin (UIB) have been analysed for seasonal and annual trends over the period 2001-2005 and calibrated with the results acquired by the research. From the analysis it is concluded that there are indications that regional warming is one of the factor that is affecting the hydrology of the upper Indus basin due to accelerated glacial melting during the simulation period, stream flow in the upper Indus basin can be predicted with a high degree of accuracy. This conclusion is also supported by the research of ICIMOD in which there is an observation that the average annual precipitation over a five year period is less than the observed stream flow and supported by positive temperature trends in all seasons.

Keywords: indus basin, MODIS, remote sensing, snow cover

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Authors: Rajashree Bothale, Venkateswara Rao

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Indian Himalayas also known as third pole with 0.9 Million SQ km area, contain the largest reserve of ice and snow outside poles and affect global climate and water availability in the perennial rivers. The variations in the extent of snow are indicative of climate change. The snow melt is sensitive to climate change (warming) and also an influencing factor to the climate change. A study of the spatio-temporal dynamics of snow cover and melt/freeze conditions is carried out using space based observations in visible and microwave bands. An analysis period of 2003 to 2015 is selected to identify and map the changes and trend in snow cover using Indian Remote Sensing (IRS) Advanced Wide Field Sensor (AWiFS) and Moderate Resolution Imaging Spectroradiometer(MODIS) data. For mapping of wet snow, microwave data is used, which is sensitive to the presence of liquid water in the snow. The present study uses Ku-band scatterometer data from QuikSCAT and Oceansat satellites. The enhanced resolution images at 2.25 km from the 13.6GHz sensor are used to analyze the backscatter response to dry and wet snow for the period of 2000-2013 using threshold method. The study area is divided into three major river basins namely Brahmaputra, Ganges and Indus which also represent the diversification in Himalayas as the Eastern Himalayas, Central Himalayas and Western Himalayas. Topographic variations across different zones show that a majority of the study area lies in 4000–5500 m elevation range and the maximum percent of high elevated areas (>5500 m) lies in Western Himalayas. The effect of climate change could be seen in the extent of snow cover and also on the melt/freeze status in different parts of Himalayas. Melt onset day increases from east (March11+11) to west (May12+15) with large variation in number of melt days. Western Himalayas has shorter melt duration (120+15) in comparison to Eastern Himalayas (150+16) providing lesser time for melt. Eastern Himalaya glaciers are prone for enhanced melt due to large melt duration. The extent of snow cover coupled with the status of melt/freeze indicating solar radiation can be used as precursor for monsoon prediction.

Keywords: Indian Himalaya, Scatterometer, Snow Melt/Freeze, AWiFS, Cryosphere

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Authors: M. Irannezhad, E. H. N. Gashti, S. Mohammadighavam, M. Zarrini, B. Kløve

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Climate warming would increase rainfall by shifting precipitation falling form from snow to rain, and would accelerate snow cover disappearing by increasing snowpack. Using temperature and precipitation data in the temperature-index snowmelt model, we evaluated variability of snowfall and continuous snow cover duration(CSCD) during 1944-2010 over Pelso, central Finland. MannKendall non-parametric test determined that annual precipitation increased by 2.69 (mm/year, p<0.05) during the study period, but no clear trend in annual temperature. Both annual rainfall and snowfall increased by 1.67 and 0.78 (mm/year, p<0.05), respectively. CSCD was generally about 205 days from 14 October to 6 May. No clear trend was found in CSCD over Pelso. Spearman’s rank correlation showed most significant relationships of annual snowfall with the East Atlantic (EA) pattern, and CSCD with the East Atlantic/West Russia (EA/WR) pattern. Increased precipitation with no warming temperature caused the rainfall and snowfall to increase, while no effects on CSCD.

Keywords: variations, snowfall, snow cover duration, temperature-index snowmelt model, teleconnection patterns

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Authors: Aleh Meshyk, Anastasiya Vouchak

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On the average snow covers Belarus for 75 days in the south-west and 125 days in the north-east. During the cold season snowpack often destroys due to thaws, especially at the beginning and end of winter. Over 50% of thawing days have a positive mean daily temperature, which results in complete snow melting. For instance, in December 10% of thaws occur at 4 С mean daily temperature. Stable snowpack lying for over a month forms in the north-east in the first decade of December but in the south-west in the third decade of December. The cover disappears in March: in the north-east in the last decade but in the south-west in the first decade. This research takes into account that precipitation falling during a cold season could be not only liquid and solid but also a mixed type (about 10-15 % a year). Another important feature of snow cover is its density. In Belarus, the density of freshly fallen snow ranges from 0.08-0.12 g/cm³ in the north-east to 0.12-0.17 g/cm³ in the south-west. Over time, snow settles under its weight and after melting and refreezing. Averaged annual density of snow at the end of January is 0.23-0.28 g/сm³, in February – 0.25-0.30 g/сm³, in March – 0.29-0.36 g/сm³. Sometimes it can be over 0.50 g/сm³ if the snow melts too fast. The density of melting snow saturated with water can reach 0.80 g/сm³. Average maximum of snow depth is 15-33 cm: minimum is in Brest, maximum is in Lyntupy. Maximum registered snow depth ranges within 40-72 cm. The water content in snowpack, as well as its depth and density, reaches its maximum in the second half of February – beginning of March. Spatial distribution of the amount of liquid in snow corresponds to the trend described above, i.e. it increases in the direction from south-west to north-east and on the highlands. Average annual value of maximum water content in snow ranges from 35 mm in the south-west to 80-100 mm in the north-east. The water content in snow is over 80 mm on the central Belarusian highland. In certain years it exceeds 2-3 times the average annual values. Moderate water content in snow (80-95 mm) is characteristic of western highlands. Maximum water content in snow varies over the country from 107 mm (Brest) to 207 mm (Novogrudok). Maximum water content in snow varies significantly in time (in years), which is confirmed by high variation coefficient (Cv). Maximums (0.62-0.69) are in the south and south-west of Belarus. Minimums (0.42-0.46) are in central and north-eastern Belarus where snow cover is more stable. Since 1987 most gauge stations in Belarus have observed a trend to a decrease in water content in snow. It is confirmed by the research. The biggest snow cover forms on the highlands in central and north-eastern Belarus. Novogrudok, Minsk, Volkovysk, and Sventayny highlands are a natural orographic barrier which prevents snow-bringing air masses from penetrating inside the country. The research is based on data from gauge stations in Belarus registered from 1944 to 2014.

Keywords: density, depth, snow, water content in snow

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Authors: Temenuzhka Spasova, Nadya Yanakieva

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Snow modulates the hydrological cycle and influences the functioning of ecosystems and is a significant resource for many populations whose water is harvested from cold regions. Snow observations are important for validating climate models. The accumulation and rapid melt of snow are two of the most dynamical seasonal environmental changes on the Earth’s surface. The actuality of this research is related to the modern tendencies of the remote sensing application in the solution of problems of different nature in the ecological monitoring of the environment. The subject of the study is the dynamic during the different seasons on Livingstone Island, South Shetland Islands in Antarctica and on Svalbard in Arctic. The objects were analyzed and mapped according to the Еuropean Space Agency data (ESA), acquired by sensors Sentinel-1 SAR (Synthetic Aperture Radar), Sentinel 2 MSI and GIS. Results have been obtained for changes in snow coverage during the summer-winter transition and its dynamics in the two hemispheres. The data used is of high time-spatial resolution, which is an advantage when looking at the snow cover. The MSI images are with different spatial resolution at the Earth surface range. The changes of the environmental objects are shown with the SAR images and different processing approaches. The results clearly show that snow and snow melting can be best registered by using SAR data via hh- horizontal polarization. The effect of the researcher on aerospace data and technology enables us to obtain different digital models, structuring and analyzing results excluding the subjective factor. Because of the large extent of terrestrial snow coverage and the difficulties in obtaining ground measurements over cold regions, remote sensing and GIS represent an important tool for studying snow areas and properties from regional to global scales.

Keywords: climate changes, GIS, remote sensing, SAR images, snow coverage

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Authors: Gulijianati Abake, Ryutaro Tateishi

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Snow is one kind of special underlying surface, has high reflectivity, low thermal conductivity, and snow broth hydrological effect. Every year, frequent snow disaster in Xinjiang causing considerable economic loss and serious damage to towns and farms, such as livestock casualties, traffic jams and other disaster, therefore monitoring SWE (snow volume) in Xinjiang has a great significance. The problems of how this disaster distributes and what disaster-forming environments are important to its occurrence are the most pressing problems in disaster risk assessment and salvage material arrangement. The present study aims 1) to monitor accurate SWE using MODIS, AMSRE, and CMC data, 2) to establish the regularity of snow disaster outbreaks and the important disaster-forming environmental factors. And a spatial autocorrelation analysis method and a canonical correlation analysis method are used to answer these two questions separately, 3) to prepare the way to salvage material arrangements for snow disasters.

Keywords: snow water equivalent (snow volume), AMSR-E, CMC snow depth, snow disaster

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Authors: Evren Ozgur, Kasim Kocak

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As a result of global warming and climate change, air temperature has increased and will continue to increase in the future. Increases in air temperatures have effects on a large number of variables in meteorology. One of the most important effects is the changes in the types of precipitation, especially in mid-latitudes. Because of increasing air temperatures, less snowfall was observed in the eastern parts of Turkey. Snowfall provides most of the water supply in spring and summer months, especially in mountainous regions of Turkey. When the temperature begins to increase in spring season, this snow starts to melt and plays an important role in agricultural purposes, drinking water supply and energy production. On the other hand, defining the snow season is very crucial especially in mountainous areas which have winter tourism opportunities. A reduction in the length of the snow season (LSS) in these regions will result in serious consequences in the long run. In the study, snow season was examined for 10 meteorological stations that are located above the altitude of 1000m. These stations have decreasing trends in the ratio of number of snowy days to total precipitation days considering earlier studies. Daily precipitation records with the observation period of 1971-2011 were used in the study. Then, the observation period was separated into 4 non-overlapping parts in order to identify decadal variations. Changes in the length of the snow season with increasing temperatures were obtained for these stations. The results of LSS were evaluated with the number of snowy days for each station. All stations have decreasing trend in number of snowy days for 1971-2011 period. In addition, seven of the results are statistically significant. Besides, decrease is observed regarding the length of snow season for studied stations. The decrease varies between 6.6 and 47.6 days according to decadal snow season averages of the stations.

Keywords: climate change, global warming, precipitation, snowfall, Turkey

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Authors: Sonu Khanal, Mandira Shrestha

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Snow and Glaciers are the largest dependable reserved sources of water for the river system originating from the Himalayas so an accurate estimate of the volume of water contained in the snowpack and the rate of release of water from snow and glaciers are, therefore, needed for efficient management of the water resources. This research assess the fusion of energy exchanges between the snowpack, air above and soil below according to mass and energy balance which makes it apposite than the models using simple temperature index for the snow and glacier melt computation. UEBGrid a Distributed energy based model is used to calculate the melt which is then routed by Geo-SFM. The model robustness is maintained by incorporating the albedo generated from the Landsat-7 ETM images on a seasonal basis for the year 2002-2003 and substrate map derived from TM. The Substrate file includes predominantly the 4 major thematic layers viz Snow, clean ice, Glaciers and Barren land. This approach makes use of CPC RFE-2 and MERRA gridded data sets as the source of precipitation and climatic variables. The subsequent model run for the year between 2002-2008 shows a total annual melt of 17.15 meter is generate from the Marshyangdi Basin of which 71% is contributed by the glaciers , 18% by the rain and rest being from the snow melt. The albedo file is decisive in governing the melt dynamics as 30% increase in the generated surface albedo results in the 10% decrease in the simulated discharge. The melt routed with the land cover and soil variables using Geo-SFM shows Nash-Sutcliffe Efficiency of 0.60 with observed discharge for the study period.

Keywords: Glacier, Glacier melt, Snowmelt, Energy balance

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Syed Hammad Ali, Rijan Bhakta Kayastha, Danial Hashmi, Richard Armstrong, Ahuti Shrestha, Iram Bano, Javed Hassan

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This paper presents the results of a semi-distributed modified positive degree-day model (MPDDM) for estimating snow and ice melt contributions to discharge from the glacierized Hunza River basin, Pakistan. The model uses daily temperature data, daily precipitation data, and positive degree day factors for snow and ice melt. The model is calibrated for the period 1995-2001 and validated for 2002-2013, and demonstrates close agreements between observed and simulated discharge with Nash–Sutcliffe Efficiencies of 0.90 and 0.88, respectively. Furthermore, the Weather Research and Forecasting model projected temperature, and precipitation data from 2016-2050 are used for representative concentration pathways RCP4.5 and RCP8.5, and bias correction was done using a statistical approach for future discharge estimation. No drastic changes in future discharge are predicted for the emissions scenarios. The aggregate snow-ice melt contribution is 39% of total discharge in the period 1993-2013. Snow-ice melt contribution ranges from 35% to 63% during the high flow period (May to October), which constitutes 89% of annual discharge; in the low flow period (November to April) it ranges from 0.02% to 17%, which constitutes 11 % of the annual discharge. The snow-ice melt contribution to total discharge will increase gradually in the future and reach up to 45% in 2041-2050. From a sensitivity analysis, it is found that the combination of a 2°C temperature rise and 20% increase in precipitation shows a 10% increase in discharge. The study allows us to evaluate the impact of climate change in such basins and is also useful for the future prediction of discharge to define hydropower potential, inform other water resource management in the area, to understand future changes in snow-ice melt contribution to discharge, and offer a possible evaluation of future water quantity and availability.

Keywords: climate variability, future discharge projection, positive degree day, regional climate model, water resource management

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Authors: Ali Akber Khan

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In the 21st century, freshwater resources, especially ice cover, would have grave significance as ice carries most of the total freshwater resources in the world. The Himalayas in Pakistan is one of the biggest sources of fresh water for Pakistan. These regions of the Himalayas and neighboring mountains include Swat, Chitral, Upper Dir, Lower Dir, Mardan, Swabi, Haripur, Abbottabad, Muzaffarabad, Neelum, and Mansehra in Pakistan. The study examines ice resources in the years 1990 to 2020 and shows a decrease in snow-shrouded regions, reducing from 72,187.54 sq. km in 1990 to 66,061.17 sq. km in 2020. This indicates a total ice cover loss of 6,126.37 sq. km area in 40 years due to environmental variabilities and climatic changes. From 2010 to 2020 loss of ice-covered area was 3479.24 sq. km. The mean maximum temperature from 2000 to 2010 in December, January and February is 7.4 °C, 4.2 °Cand 7.8 °C respectively, while from 2011 to 2022 mean maximum temperature registered in December, January and February is 6.9°C, 4.1°C and 6.6 °C respectively. Investigation of anthropogenic elements in the region shows population rise. From investigation, 22 cities and towns of the Himalayas region and neighboring mountains showed the highest rise in population, 329.46%, and a minimum rise of 14.39%, while 12 towns have risen in population by more than 100% from 1990 to 2023. This examination adds to a point-by-point comprehension of the connections among normal variables, population dynamics, snow cover variation, evidence strategies, and multipurpose measures for maintained and strong improvement in the districts.

Keywords: snow, ice, Himalayas, Pakistan, climate change, population

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Authors: Ibrahim Turfanda, Soniya Rai, Karan Vadher

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Objectives— The study aims to compare real-world adherence to and persistence with dulaglutide and liraglutide in patients with type 2 diabetes (T2D) initiating treatment in UAE. Methods— This was a retrospective, non-interventional study (observation period: 01 March 2017–31 August 2019) using the UAE Dubai e-Claims database. Included: adult patients initiating dulaglutide/liraglutide 01 September 2017–31 August 2018 (index period) with: ≥1 claim for T2D in the 6 months before index date (ID); ≥1 claim for dulaglutide/liraglutide during index period; and continuous medical enrolment for ≥6 months before and ≥12 months after ID. Key endpoints, assessed 3/6/12 months after ID: adherence to treatment (proportion of days covered [PDC; PDC ≥80% considered ‘adherent’], per-group mean±standard deviation [SD] PDC); and persistence (number of continuous therapy days from ID until discontinuation [i.e., >45 days gap] or end of observation period). Patients initiating dulaglutide/liraglutide were propensity score matched (1:1) based on baseline characteristics. Between-group comparison of adherence was analysed using the McNemar test (α=0.025). Persistence was analysed using Kaplan–Meier estimates with log-rank tests (α=0.025) for between-group comparisons. This study presents 12-month outcomes. Results— Following propensity score matching, 263 patients were included in each group. Mean±SD PDC for all patients at 12 months was significantly higher in the dulaglutide versus the liraglutide group (dulaglutide=0.48±0.30, liraglutide=0.39±0.28, p=0.0002). The proportion of adherent patients favored dulaglutide (dulaglutide=20.2%, liraglutide=12.9%, p=0.0302), as did the probability of being adherent to treatment (odds ratio [97.5% CI]: 1.70 [0.99, 2.91]; p=0.03). Proportion of persistent patients also favoured dulaglutide (dulaglutide=15.2%, liraglutide=9.1%, p=0.0528), as did the probability of discontinuing treatment 12 months after ID (p=0.027). Conclusions— Based on the UAE Dubai e-Claims database data, dulaglutide initiators exhibited significantly greater adherence in terms of mean PDC versus liraglutide initiators. The proportion of adherent patients and the probability of being adherent favored the dulaglutide group, as did treatment persistence.

Keywords: adherence, dulaglutide, effectiveness, liraglutide, persistence

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Authors: Roman Marsalek

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In this paper, snow samples containing dust particles from several sampling points around the city of Ostrava were analyzed. The pH values of sampled snow were measured and solid particles analyzed. Particle size, zeta potential and content of selected heavy metals were determined in solid particles. The pH values of most samples lay in the slightly acid region. Mean values of particle size ranged from 290.5 to 620.5 nm. Zeta potential values varied between -5 and -26.5 mV. The following heavy metal concentration ranges were found: copper 0.08-0.75 mg/g, lead 0.05-0.9 mg/g, manganese 0.45-5.9 mg/g and iron 25.7-280.46 mg/g. The highest values of copper and lead were found in the vicinity of busy crossroads, and on the contrary, the highest levels of manganese and iron were detected close to a large steelworks. The proportion between pH values, zeta potentials, particle sizes and heavy metal contents was established. Zeta potential decreased with rising pH values and, simultaneously, heavy metal content in solid particles increased. At the same time, higher metal content corresponded to lower particle size.

Keywords: dust, snow, zeta potential, particles size distribution, heavy metals

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Authors: Noori Shafiqullah

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Millions of people reside downstream of river basins that heavily rely on snowmelt originating from the Hindu Kush (HK) region. Snowmelt plays a critical role as a primary water source in these areas. This study aimed to evaluate snowfall and snowmelt characteristics in the HK region across altitudes ranging from 2019m to 4533m. To achieve this, the study employed a combination of remote sensing techniques and the Snow Model (SM) to analyze the spatial and temporal distribution of Snow Water Equivalent (SWE). By integrating the simulated Snow-cover Area (SCA) with data from the Moderate Resolution Imaging Spectroradiometer (MODIS), the study optimized the Precipitation Gradient (PG), snowfall assessment, and the degree-day factor (DDF) for snowmelt distribution. Ground observed data from various elevations were used to calculate a temperature lapse rate of -7.0 (°C km-1). Consequently, the DDF value was determined as 3 (mm °C-1 d-1) for altitudes below 3000m and 3 to 4 (mm °C-1 d-1) for higher altitudes above 3000m. Moreover, the distribution of precipitation varies with elevation, with the PG being 0.001 (m-1) at lower elevations below 4000m and 0 (m-1) at higher elevations above 4000m. This study successfully utilized the SM to assess SCA and SWE by incorporating the two optimized parameters. The analysis of simulated SCA and MODIS data yielded coefficient determinations of R2, resulting in values of 0.95 and 0.97 for the years 2014-2015, 2015-2016, and 2016-2017, respectively. These results demonstrate that the SM is a valuable tool for managing water resources in mountainous watersheds such as the HK, where data scarcity poses a challenge."

Keywords: improved MODIS, experiment, snow water equivalent, snowmelt

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Authors: Bishnu Prasad Devkota

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Peoples` perception is reflected in their attitudes and presumably their behavior towards wildlife conservation. The success of wildlife conservation initiatives in the mountains of Nepal is heavily dependent on local people. Therefore, Nepal has emphasized the involvement of local people in wildlife conservation, especially in the mountainous region. Local peoples` perception towards snow leopard conservation in six mountainous protected area of Nepal was carried out conducting 300 household surveys and 90 face to face key informant interviews. The average livestock holding was 27.74 animals per household with depredation rate of 10.6 % per household per annum. Livestock was the source of 32.74% of the total mean annual income of each household. In average, the economic loss per household per annum due to livestock depredation was US $ 490. There was significant difference in people´s perception towards snow leopard conservation in protected areas of mountainous region of Nepal. These differences were due to economic, educational and cultural factors. 54.4% local people showed preference for snow leopard conservation. The perception of local people toward snow leopard was significantly difference by the economic status of local people. Involvement of local people in conservation activities had positive impact towards wildlife conservation in the mountain region of Nepal. Timely introducing incentive programs can be a supportive way for sustaining the conservation of snow leopards in the Nepalese Himalayas.

Keywords: economic loss, livestock depredation, local people, perception, snow leopard

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Authors: Blessing Mavhuru, Nthaduleni Nethengwe, Hector Chikoore, Onyango Beneah Daniel Odhiambo

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The main objective of this study was to classify land use/cover and how it has changed in Nzhelele Valley Limpopo Province, South Africa. The study aimed to identify and analyse the types of land use/cover in the years 2005, 2010, and 2015 with a view to assess the impact on soil erosion over time. Using GIS, the changes within land use/cover were assessed through the classification of satellite images. The study area was classified into four major land cover/use classes, which are vegetation, gravel road, built up land and agricultural fields. Over the period 2005-2015 the resultant land use/cover demonstrated (i) a significant increase (12%) for vegetation cover, (ii) a significant decrease in agriculture (16%) land use/cover, (iii) increase in built-up land (1%), as well as (iv) an increase in gravel roads (3%). This study envisages assisting policy makers in decision making on land use management for Nzhelele Valley.

Keywords: land use, land cover, change, soil erosion

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Authors: Shael Brown, Reza Farivar

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Persistence diagrams capture valuable topological features of datasets that other methods cannot uncover. Still, their adoption in data pipelines has been limited due to the lack of publicly available tools in R (and python) for analyzing groups of them with machine learning and statistical inference. In an easy-to-use and scalable R package called TDApplied, we implement several applied analysis methods tailored to groups of persistence diagrams. The two main contributions of our package are comprehensiveness (most functions do not have implementations elsewhere) and speed (shown through benchmarking against other R packages). We demonstrate applications of the tools on simulated data to illustrate how easily practical analyses of any dataset can be enhanced with topological information.

Keywords: machine learning, persistence diagrams, R, statistical inference

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

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Authors: Lei Zhang

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The carbon cycle greatly influences global change, and the land cover changes contribute to the status and rate of the carbon budget in ecosystems. This paper proposes a land cover classification system for mapping land cover, the national ecological environment assessment, and estimating carbon storage in ecosystems. The classification system consists of basic land cover classes at levels Ⅰ and Ⅱ and auxiliary features at level III. The basic 38 classes characterizing land cover features are derived from 19 criteria referring to composition, structure, pattern, phenology, etc. The basic classes reflect the status of carbon storage in ecosystems. The auxiliary classes at level III complement the attributes of higher levels by 9 criteria. The 5 environmental criteria of temperature, moisture, landform, aspect and slope mainly reflect the potential and intensity of carbon storage in ecosystems. The disturbance of vegetation succession caused by land use type influences the vegetation carbon budget. The other 3 vegetation cover criteria, growth period, and species characteristics further refine the vegetation types. The hierarchical structure of the land cover map (the classes of levels Ⅰ and Ⅱ) is independent of the products of level III, which is helpful for land cover product management and applications. The classification system has been adopted in the Chinese national land cover database for the carbon budget in ecosystems at a 30 m scale.

Keywords: classification system, land cover, ecosystem, carbon storage, object based

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Authors: Bita Mashayekhi, Zeynab Lotfi Aghel

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The determinants of Earnings Response Coefficient (ERC), including firm size, earnings growth, and earnings persistence are studied in this research. These determinants are supposed to be moderator variables that affect ERC and Return Response Coefficient. The research sample contains 82 Iranian listed companies in Tehran Stock Exchange (TSE) from 2001 to 2012. Gathered data have been processed by EVIEWS Software. Results show a significant positive relation between firm size and ERC, and also between earnings growth and ERC; however, there is no significant relation between earnings persistence and ERC. Also, the results show that ERC will be increased by firm size and earnings growth, but there is no relation between earnings persistence and ERC.

Keywords: earnings response coefficient (ERC), return response coefficient (RRC), firm size, earnings growth, earnings persistence

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Authors: Taufik Mulyadin

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The tuition reform for public colleges that the Indonesian government initiated and has implemented since 2013 resulted in the growing number of college students from low-income families, many of whose parents did not attend college. This study sought to examine the experiences of persistence for Indonesian first-generation college students in public universities utilizing social capital as a framework. It is a qualitative study with a phenomenological approach primarily to capture the essence of how Indonesian first-generation college students interpret, process, and experience their persistence during college years. Fifteen Indonesian young college graduates were involved as well as questionnaire and interview were employed for data collection in this study. It revealed certain themes from the experiences that first-generation college students attributed to their persistence: (a) family encouragement, (b) support from friends, (c) guidance from faculty and staff, (d) fund of knowledge they bring with them, (e) financial aid availability, and (f) self-motivation. By examining first-generation college students’ voices, Indonesian public universities can better support, engage, and retain this group of students who were historically struggled to persist in college and complete their degree.

Keywords: first-generation student, Indonesian higher education, persistence, public universities

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Authors: Uroš Durlević, Ivan Novković, Nina Čegar, Stefanija Stojković

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Snow avalanches represent one of the most dangerous natural phenomena in mountain regions worldwide. Material and human casualties caused by snow avalanches can be very significant. In this study, using geographic information systems and remote sensing, the natural conditions of the Šar Mountains were analyzed for geospatial modeling of dry slab avalanches. For this purpose, the Fuzzy Analytic Hierarchy Process (FAHP) multi-criteria analysis method was used, within which fifteen environmental criteria were analyzed and evaluated. Based on the existing analyzes and results, it was determined that a significant area of the Šar Mountains is very highly susceptible to the occurrence of dry slab avalanches. The obtained data can be of significant use to local governments, emergency services, and other institutions that deal with natural disasters at the local level. To our best knowledge, this is one of the first research in the Republic of Serbia that uses the FAHP method for geospatial modeling of dry slab avalanches.

Keywords: GIS, FAHP, Šar Mountains, snow avalanches, environmental protection

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Authors: Garance Liaboeuf, Alain Le Bot, Ali Daouadji, Antoine Martinet, Mohamed Bouteldja, Nicolas Grignard, Damien Pilet

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As every French road operator, Autoroutes et Tunnel du Mont Blanc (ATMB) conducts annual inspections of its infrastructures. Significant loss of skid resistance has been observed on some sections of his network, sometimes on recent pavements. In the way of making the mechanisms and factors that can lead to this loss of grip more understandable, ATMB has launched a study aimed at identifying the causes and developing solutions to prevent this phenomenon. To quantify the deterioration of different road surfaces subjected to controlled scraping with steel blades of snow removal machines, a field campaign was conducted. These operations are carried out during the winter period according to a strict protocol. In order to correct the skid-resistance values, a control panel is set up. In this way, only the effect of the scraping is taken into account. It allows us to exclude the influence of the environment (temperature, humidity, etc.) and of the surface state on the skid resistance values measured during the different sessions. Skid measurements after eight years of scraping cycles showed a 7% to 13% decrease in microtexture and a 2% to 12% decrease in macrotexture adhesion. These reductions are attributed to the phenomenon of polishing road surfaces by using steel blades. Also, regeneration phenomena occur after a certain number of blades pass. Differences in steel scraper blade resistance appear related to the intrinsic properties of the aggregate used in the pavement formulation and its type. Finally, the results of this campaign will allow the determination of the resistance characteristics of the pavement damage by the steel blade of snow plows. An evolution law of the surface condition as a function of the scraping operations will also be developed from this study.

Keywords: pavement, skid, surface, snow plow

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Authors: Corinna Zeli, Silvia Calati, Marco Simeoni, Chiara Comastri

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Developmental stuttering affects about 10% of preschool children; although the high percentage of natural recovery, a quarter of them will become an adult who stutters. An effective early intervention should help those children with high persistence risk for the future. The Psicodizione method for early stuttering is an Italian behavior indirect treatment for preschool children who stutter in which method parents act as good guides for communication, modeling their own fluency. In this study, we give a preliminary measure to evaluate the long-term effectiveness of Psicodizione method on stuttering preschool children with a high persistence risk. Among all Italian children treated with the Psicodizione method between 2018 and 2019, we selected 8 kids with at least 3 high risk persistence factors from the Illinois Prediction Criteria proposed by Yairi and Seery. The factors chosen for the selection were: one parent who stutters (1pt mother; 1.5pt father), male gender, ≥ 4 years old at onset; ≥ 12 months from onset of symptoms before treatment. For this study, the families were contacted after an average period of time of 14,7 months (range 3 - 26 months). Parental reports were gathered with a standard online questionnaire in order to obtain data reflecting fluency from a wide range of the children’s life situations. The minimum worthwhile outcome was set at "mild evidence" in a 5 point Likert scale (1 mild evidence- 5 high severity evidence). A second group of 6 children, among those treated with the Piscodizione method, was selected as high potential for spontaneous remission (low persistence risk). The children in this group had to fulfill all the following criteria: female gender, symptoms for less than 12 months (before treatment), age of onset <4 years old, none of the parents with persistent stuttering. At the time of this follow-up, the children were aged 6–9 years, with a mean of 15 months post-treatment. Among the children in the high persistence risk group, 2 (25%) hadn’t had stutter anymore, and 3 (37,5%) had mild stutter based on parental reports. In the low persistency risk group, the children were aged 4–6 years, with a mean of 14 months post-treatment, and 5 (84%) hadn’t had stutter anymore (for the past 16 months on average).62,5% of children at high risk of persistence after Psicodizione treatment showed mild evidence of stutter at most. 75% of parents confirmed a better fluency than before the treatment. The low persistence risk group seemed to be representative of spontaneous recovery. This study’s design could help to better evaluate the success of the proposed interventions for stuttering preschool children and provides a preliminary measure of the effectiveness of the Psicodizione method on high persistence risk children.

Keywords: early treatment, fluency, preschool children, stuttering

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Authors: Parvin Berenjkar, Qiuyan Yuan, Richard Sparling, Stan Lozecznik

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Landfills highly contribute to anthropological global warming through CH₄ emissions. Landfills are usually capped by a conventional soil cover to control the migration of gases. Methane is consumed by CH₄-oxidizing microorganisms known as methanotrophs that naturally exist in the landfill soil cover. The growth of methanotrophs can be optimized in a bio-cover that typically consists of a gas distribution layer (GDL) to homogenize landfill gas fluxes and an overlying oxidation layer composed of suitable materials that support methanotrophic populations. Materials such as mature yard waste composts can provide an inexpensive and favourable porous support for the growth and activity of methanotrophs. In areas with seasonal cold climates, it is valuable to know if methanotrophs in a bio-cover can survive in winter until the next spring, and how deep they are active in the bio-cover to mitigate CH₄. In this study, a pilot bio-cover was constructed in a closed landfill cell in Winnipeg that has a very cold climate in Canada. The bio-cover has a surface area of 2.5 m x 3.5 m and 1.5 m of depth, filled with 50 cm of gravel as a GDL and 70 cm of biosolids compost amended with yard and leaf waste compost. The observed in situ potential of methanotrophs for CH₄ oxidation was investigated at a specific period of time from December 2016 to April 2017 as well as November 2017 to April 2018, when the transition to surface frost and thawing happens in the bio-cover. Compost samples taken from different depths of the bio-cover were incubated in the laboratory under standardized conditions; an optimal air: methane atmosphere, at 22ºC, but at in situ moisture content. Results showed that the methanotrophs were alive oxidizing methane without a lag, indicating that there was the potential for methanotrophic activity at some depths of the bio-cover.

Keywords: bio-cover, global warming, landfill, methanotrophic activity

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Authors: Parvin Ghafarian, Mohammadreza Mohammadpur Panchah, Mehri Fallahi

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Synoptic patterns from surface up to tropopause are very important for forecasting the weather and atmospheric conditions. There are many tools to prepare and analyze these maps. Reanalysis data and the outputs of numerical weather prediction models, satellite images, meteorological radar, and weather station data are used in world forecasting centers to predict the weather. The forecasting extreme precipitating on the southern coast of the Caspian Sea (CS) is the main issue due to complex topography. Also, there are different types of climate in these areas. In this research, we used two reanalysis data such as ECMWF Reanalysis 5th Generation Description (ERA5) and National Centers for Environmental Prediction /National Center for Atmospheric Research (NCEP/NCAR) for verification of the numerical model. ERA5 is the latest version of ECMWF. The temporal resolution of ERA5 is hourly, and the NCEP/NCAR is every six hours. Some atmospheric parameters such as mean sea level pressure, geopotential height, relative humidity, wind speed and direction, sea surface temperature, etc. were selected and analyzed. Some different type of precipitation (rain and snow) was selected. The results showed that the NCEP/NCAR has more ability to demonstrate the intensity of the atmospheric system. The ERA5 is suitable for extract the value of parameters for specific point. Also, ERA5 is appropriate to analyze the snowfall events over CS (snow cover and snow depth). Sea surface temperature has the main role to generate instability over CS, especially when the cold air pass from the CS. Sea surface temperature of NCEP/NCAR product has low resolution near coast. However, both data were able to detect meteorological synoptic patterns that led to heavy rainfall over CS. However, due to the time lag, they are not suitable for forecast centers. The application of these two data is for research and verification of meteorological models. Finally, ERA5 has a better resolution, respect to NCEP/NCAR reanalysis data, but NCEP/NCAR data is available from 1948 and appropriate for long term research.

Keywords: synoptic patterns, heavy precipitation, reanalysis data, snow

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Authors: Rachelle M. Johnson, Jenna E. Finch

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Motivation, persistence, and learning disability status are all associated with academic performance, but to the author's knowledge, little research has been done on how these variables interact with one another and how that interaction looks different within children with and without learning disabilities. The present study's goal was to examine the role motivation and persistence play in the academic success of children with learning disabilities and how these variables interact. Measurements were made using surveys and direct cognitive assessments on each child. Analyses were run on student's scores in motivation, persistence, and ability to learn compared to other fifth grade students. In this study, learning ability was intended as a proxy for learning disabilities (LDs). This study included a nationally representative sample of over 8,000 fifth-grade children from across the United States. Multiple interactions were found among these variables of motivation, persistence, and motivation as they relate to academic achievement. The major finding of the study was the significant role motivation played in academic achievement. This study shows the importance of measuring the within-group. One key finding was that motivation was associated with academic success and was moderated by the other variables. The interaction results were different for math and reading outcomes, suggesting that reading and math success are different and should be addressed differently. This study shows the importance of measuring the within-group differences in levels of motivation to better understand the academic success of children with and without learning disabilities. This study's findings call for further investigation into motivation and the possible need for motivational intervention for students, especially those with learning disabilities

Keywords: academic achievement, learning disabilities, motivation, persistence

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Authors: Alam Zeb, Glen W. Armstrong, Muhammad Qasim

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Loss of forest cover is one of the most important land cover changes and has been of great concern to policy makers. This study quantified forest cover changes over pre logging ban (1973-1993) and post logging ban (1993-2015) to examine the role of geophysical factors and spatial attributes of land in the two periods. We show that despite a complete ban on green felling, forest cover decreased by 28% and mostly converted to rangeland. Nevertheless, the logging ban was completely effective in controlling agriculture expansion. The binary logistic regression revealed that the south facing aspects at low elevation witnessed more deforestation in the pre-ban period compared to post-ban. Opposite to deforestation, forest degradation was more prominent on the northern aspects at higher elevation during the policy period. Agriculture expansion was widespread in the low elevation flat areas with gentle slope, while during the policy period agriculture contraction in the form of regeneration was observed on the low elevation areas of north facing slopes. All proximity variables, except distance to administrative boundary, showed a similar trend across the two periods and were important explanatory variables in understanding forest and agriculture expansion. The changes in determinants of forest and agriculture expansion and contraction over the two periods might be attributed to the influence of policy and a general decrease in resource availability.

Keywords: forest conservation , wood harvesting ban, logistic regression, deforestation, forest degradation, agriculture expansion, Chitral, Pakistan

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Authors: A. O. Abulibdeh

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The aim of this study is to investigate and compare the changes in the Land Surface Temperature (LST) as a function of urbanization, particularly land use/land cover changes, in three cities in the UAE, mainly Abu Dhabi, Dubai, and Al Ain. The scale of this assessment will be at the macro- and micro-levels. At the macro-level, a comparative assessment will take place to compare between the four cities in the UAE. At the micro-level, the study will compare between the effects of different land use/land cover on the LST. This will provide a clear and quantitative city-specific information related to the relationship between urbanization and local spatial intra-urban LST variation in three cities in the UAE. The main objectives of this study are 1) to investigate the development of LST on the macro- and micro-level between and in three cities in the UAE over two decades time period, 2) to examine the impact of different types of land use/land cover on the spatial distribution of LST. Because these three cities are facing harsh arid climate, it is hypothesized that (1) urbanization is affecting and connected to the spatial changes in LST; (2) different land use/land cover have different impact on the LST; and (3) changes in spatial configuration of land use and vegetation concentration over time would control urban microclimate on a city scale and control macroclimate on the country scale. This study will be carried out over a 20-year period (1996-2016) and throughout the whole year. The study will compare between two distinct periods with different thermal characteristics which are the cool/cold period from November to March and warm/hot period between April and October. The best practice research method for this topic is to use remote sensing data to target different aspects of natural and anthropogenic systems impacts. The project will follow classical remote sensing and mapping techniques to investigate the impact of urbanization, mainly changes in land use/land cover, on LST. The investigation in this study will be performed in two stages. Stage one remote sensing data will be used to investigate the impact of urbanization on LST on a macroclimate level where the LST and Urban Heat Island (UHI) will be compared in the three cities using data from the past two decades. Stage two will investigate the impact on microclimate scale by investigating the LST and UHI using a particular land use/land cover type. In both stages, an LST and urban land cover maps will be generated over the study area. The outcome of this study should represent an important contribution to recent urban climate studies, particularly in the UAE. Based on the aim and objectives of this study, the expected outcomes are as follow: i) to determine the increase or decrease of LST as a result of urbanization in these four cities, ii) to determine the effect of different land uses/land covers on increasing or decreasing the LST.

Keywords: land use/land cover, global warming, land surface temperature, remote sensing

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