scholarly journals Space and time differentiation of snow cover in the Kasmala river basin, Altai krai

2019 ◽  
Vol 46 (4) ◽  
pp. 359-369
Author(s):  
D. V. Chernykh ◽  
D. V. Zolotov ◽  
D. K. Pershin ◽  
R. Yu. Biryukov
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Snow Accumulation ◽  
Forest Steppe ◽  
Factors Affecting ◽  
Space And Time ◽  
Different Types ◽  
Main Factors

Results of the 2011–2014 snow-course survey in the Kasmaly River basin, which is typical of the southern forest-steppe in Altai Territory, Russia, were analyzed. The interannual differential snow cover, major properties, and main factors affecting the amount of snow accumulation within different types of geological systems in the basin were examined.

scholarly journals Modeling Snow Depth and Snow Water Equivalent Distribution and Variation Characteristics in the Irtysh River Basin, China

2021 ◽  
Vol 11 (18) ◽  
pp. 8365
Author(s):  
Liming Gao ◽  
Lele Zhang ◽  
Yongping Shen ◽  
Yaonan Zhang ◽  
Minghao Ai ◽  
...  
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Snow Depth ◽  
Snow Water Equivalent ◽  
Snow Accumulation ◽  
Implicit Scheme ◽  
Snow Water ◽  
Irtysh River ◽  
Simulation Results ◽  
The Irtysh River

Accurate simulation of snow cover process is of great significance to the study of climate change and the water cycle. In our study, the China Meteorological Forcing Dataset (CMFD) and ERA-Interim were used as driving data to simulate the dynamic changes in snow depth and snow water equivalent (SWE) in the Irtysh River Basin from 2000 to 2018 using the Noah-MP land surface model, and the simulation results were compared with the gridded dataset of snow depth at Chinese meteorological stations (GDSD), the long-term series of daily snow depth dataset in China (LSD), and China’s daily snow depth and snow water equivalent products (CSS). Before the simulation, we compared the combinations of four parameterizations schemes of Noah-MP model at the Kuwei site. The results show that the rainfall and snowfall (SNF) scheme mainly affects the snow accumulation process, while the surface layer drag coefficient (SFC), snow/soil temperature time (STC), and snow surface albedo (ALB) schemes mainly affect the melting process. The effect of STC on the simulation results was much higher than the other three schemes; when STC uses a fully implicit scheme, the error of simulated snow depth and snow water equivalent is much greater than that of a semi-implicit scheme. At the basin scale, the accuracy of snow depth modeled by using CMFD and ERA-Interim is higher than LSD and CSS snow depth based on microwave remote sensing. In years with high snow cover, LSD and CSS snow depth data are seriously underestimated. According to the results of model simulation, it is concluded that the snow depth and snow water equivalent in the north of the basin are higher than those in the south. The average snow depth, snow water equivalent, snow days, and the start time of snow accumulation (STSA) in the basin did not change significantly during the study period, but the end time of snow melting was significantly advanced.

Impact factor analysis of aquatic species diversity in the Huai River Basin, China

2019 ◽  
Vol 19 (7) ◽  
pp. 2061-2071
Author(s):  
Hao Chen ◽  
Qi-ting Zuo ◽  
Yong-yong Zhang
Keyword(s):  
Species Diversity ◽  
River Basin ◽  
Environmental Indicators ◽  
Analysis Method ◽  
Factors Affecting ◽  
Physicochemical Variables ◽  
Huai River Basin ◽  
Huai River ◽  
Main Factors ◽  
The Huai River Basin

Abstract Water pollution has been a significant issue in the Huai River Basin (HRB) of China since the late 1970s. From December 2012, five experiments were carried out along the main streams of the HRB. The monitoring indices contained physicochemical variables, habitat environmental indicators and the community structure of phytoplankton, zooplankton and zoobenthos. The correlations between species diversity and physicochemical variables were analyzed using cluster analysis, correlation analysis method and redundancy analysis method. Results indicated that the species diversities of the Shaying River's upstream and Huai River's mainstream were better than the Shaying River's midstream and downstream. All the sections were divided into five clusters, and different clusters were affected by different physicochemical factors. Dissolved oxygen (DO), habitat quality index (HQI) and chemical oxygen demand (CODCr) were the main factors affecting the species diversity of the Shaying River's upstream; total phosphorus (TP), total nitrogen (TN), ammonia nitrogen (NH4-N), CODCr and permanganate index (CODMn) had a great influence on the Shaying River's midstream and downstream; DO, water temperature (WT), HQI and CODCr were the main factors affecting the Huai River's mainstream. These results provide valuable information for policy decision makers and stakeholders on water quality assessment, water ecosystem restoration, and sustainable watershed management in the HRB.

scholarly journals Fuzzy AHP Integrated with GIS Analyses for Drought Risk Assessment: A Case Study from Upper Phetchaburi River Basin, Thailand

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 939 ◽  
Author(s):  
Saowanee Wijitkosum ◽  
Thavivongse Sriburi
Keyword(s):  
River Basin ◽  
Fuzzy Ahp ◽  
Physical Factors ◽  
Drought Risk ◽  
Land Utilization ◽  
Factors Affecting ◽  
Risk Levels ◽  
Main Factors ◽  
Agricultural Areas ◽  
Hierarchy Process

This study aimed to analyse and assess desertification risks in the Upper Phetchaburi River Basin. Upstream areas are especially crucial for aquatic ecosystems since the mid- and downstream areas are continuously being utilized for agricultural and community purposes. Many parts of the basin have been at moderate risk of drought. The fuzzy analytical hierarchy process (FAHP) is an effective and widely accepted model used to identify complicated environmental problems and disasters and prioritize factors in environmental studies. This study emphasized on four main factors influencing drought: Climate, physical factors, soil and land utilization factors. Each factor contains ten sub-criteria to identify severity levels and specific issues. The major areas of the basin were facing different risk levels: moderate (21%), high (5.79%) and severe (0.07%). Precipitation and slope gradient were the main factors affecting drought risks. The problematic areas were agricultural areas located in midstream and downstream areas. Therefore, spatial mitigations and possible ways forward should focus on increasing moisture contents—to reduce soil erosion and enhance soil fertility—and create restrictions to ensure appropriate land use. The mitigations must take into account spatially critical factors and must also include an integrated plan for the entire basin area.

Space and Time Differentiation of Snow Cover in the Kasmala River Basin, Altai Krai

2019 ◽  
Vol 46 (4) ◽  
pp. 504-514
Author(s):  
D. V. Chernykh ◽  
D. V. Zolotov ◽  
D. K. Pershin ◽  
R. Yu. Biryukov
Keyword(s):  
Snow Cover ◽  
River Basin ◽  
Space And Time

scholarly journals THE MAIN FACTORS INFLUENCING EFFICIENCY OF SPRING COMMON WHEAT AGROCENOSIS

2019 ◽  
Vol 48 (6) ◽  
pp. 21-29
Author(s):  
A. L. Pakul ◽  
N. A. Lapshinov ◽  
G. V. Bozhanova ◽  
V. N. Pakul
Keyword(s):  
Common Wheat ◽  
Bipolaris Sorokiniana ◽  
Soil Tillage ◽  
Forest Steppe ◽  
Tillage Systems ◽  
Northern Forest ◽  
Factors Affecting ◽  
Main Factors ◽  
Bare Fallow ◽  
Spring Common Wheat

The paper presents the results of research (2015– 2018) into the main factors affecting efficiency of agrocenosis of spring common wheat, cultivar Siberian Alliance, with various systems of soil tillage and renewable bio-resources in a grain-fallow rotation. The research was conducted in the northern forest-steppe of Kuznetsk Depression in a threecourse grain-fallow crop rotation (fallow-wheatpeas-barley, barley intercropped with melilot) in a long-term stationary experiment. Various soil tillage systems were applied (deep moldboard, deep combined, minimum combined, minimum moldboard) preceded by bare fallow and green-manured fallow with rape and melilot. The soil of the experimental plot was leached chernozem. Crops of spring common wheat were sown with all types of soil tillage systems by the tillage and sowing machine Tom’5.1. It was revealed that the main factor influencing the yield of spring common wheat is water availability in the planting periods – full tillering, (r = 0.9579), beginning of earring – yellow ripeness, (r = 0.9611; R = 0.9500). A positive effect on wheat productivity was made by cellulosolytic activity and soil structure. The direct correlation between these factors and the crop yield was established, r = 0.6366 – 0.7298 and r = 0.6343 – 0.7103 respectively. A negative effect on the yield of wheat was made by the development of root decay (Bipolaris sorokiniana (Sacc.) Shoem), (r = – 0.4808). It was established that alongside the above-mentioned fac tors, the significant effect on productivity of spring common wheat was made by the systems of soil tillage (72.4%,) and the predecessor (22.0 %). The optimum conditions in agrocenosis of spring common wheat for formation of its yield during the years of research proved to be created by green-manured fallow (with rape) with minimum moldboard and deep moldboard soil tillage (2.72 and 2.78 t/ha respectively), which is 0.55 and 0.51 t/ha higher compared to analogous soil tillage systems preceded by bare fallow – control. Minimum moldboard soil tillage has an economic advantage over others with profitability of 193.6% and production cost at 5,000 rubles per 1 ton of grain.

scholarly journals Simulation of snow accumulation and melting in the Kama river basin using data from global prognostic models

2019 ◽  
Vol 59 (4) ◽  
pp. 494-508 ◽  
Author(s):  
S. V. Pyankov ◽  
A. N. Shikhov ◽  
P. G. Mikhaylyukova
Keyword(s):  
Snow Cover ◽  
Mean Square Error ◽  
River Basin ◽  
Snow Water Equivalent ◽  
Numerical Models ◽  
Snow Accumulation ◽  
Mean Square ◽  
Snow Storage ◽  
The Mean ◽  
Weather Stations

Currently, the improvement of numerical models of weather forecasting allows using them for hydrological problems, including calculations of snow water equivalent  (SWE) or snow storage. In this paper, we discuss the applicability of daily precipitation forecasts for three global atmospheric models: GFS (USA), GEM (Canada) and PL-AV (Russia) for calculating snow storage (SWE) in the Kama river basin for the cold season of 2017–2018. As the main components of the balance of snow storages the following parameters were taken into account: precipitation (with regard for the phase); snow melting during thaws; evaporation from the surface of the snow cover; interception of solid precipitation by forest vegetation. The calculation of snow accumulation and melting was based on empirical methods and performed with the GIS technologies. The degree-day factor was used to calculate snowmelt intensity, and snow sublimation was estimated by P.P. Kuz’min formula. The accuracy of numerical precipitation forecasts was estimated by comparing the results with the data of 101 weather stations. Materials of 40 field and 27 forest snow-measuring routes were taken into account to assess the reliability of the calculation of snow storages (SWE). During the snowmelt period, the part of the snow-covered area of the basin was also calculated using satellite images of Terra/Aqua MODIS on the basis of the NDFSI index. The most important result is that under conditions of 2017/18 the mean square error of calculating the maximum snow storage by the GFS, GEM and PL-AB models was less than 25% of its measured values. It is difficult to determine which model provides the maximum accuracy of the snow storage calculation since each one has individual limitations. According to the PL-AV model, the mean square error of snow storage calculation was minimal, but there was a significant underestimation of snow accumulation in the mountainous part of the basin. According to the GEM model, snow storages were overestimated by 10–25%. When calculating with use of the GFS model data, a lot of local maximums and minimums are detected in the field of snow storages, which are not confirmed by the data of weather stations. The main sources of uncertainty in the calculation are possible systematic errors in the numerical forecasts of precipitation, as well as the empirical coefficients used in the calculation of the intensity of snowmelt and evaporation from the snow cover surface.

The number of juvenile fish and fish productivity of water bodies of the Ob River basin (Western Siberia): review

Fisheries ◽  
2021 ◽  
Vol 2021 (5) ◽  
pp. 71-79
Author(s):  
Andrey Antonov
Keyword(s):  
River Basin ◽  
Western Siberia ◽  
Juvenile Fish ◽  
Water Bodies ◽  
Forest Steppe ◽  
Ob River ◽  
Natural Zones ◽  
Rivers And Lakes ◽  
Different Types ◽  
Fish Productivity

The article presents an overview of published materials for the period 1963-2020, containing information on the number of larvae and juveniles of fish in different types of water bodies of the Ob River basin (Western Siberia). Data on the fish productivity of rivers and lakes of the Ob basin for steppe, forest-steppe, taiga and tundra natural zones are presented. The Ob River is the main waterway of Western Siberia. The area of the Ob River basin is 2929,000 km2, the length of the river is 3680 km. The existing pronounced differences in the nature of the relief, climate, soils, waters, vegetation of the natural zones of the Ob basin determine the features of the hydrological regime and the living conditions of hydrobionts. Accordingly, the floodplain of the Ob river with its numerous backwaters, kuryami, lakes, sorami is the main places of spawning and feeding of fish. In the course of generalization of the published materials, information was obtained on the number and features of the distribution of juvenile fish in different types of water bodies (channel pits, floodplain lakes, old trees, sores) of the Ob River basin. The results of studies on determining the fish productivity of rivers and lakes of the Ob basin of steppe, forest-steppe, taiga and tundra natural zones are analyzed.

Future Climate Change Impacts on Snow and Water Resources of the Fraser River Basin, British Columbia

2017 ◽  
Vol 18 (2) ◽  
pp. 473-496 ◽  
Author(s):  
Siraj ul Islam ◽  
Stephen J. Déry ◽  
Arelia T. Werner
Keyword(s):  
Climate Change ◽  
British Columbia ◽  
Snow Cover ◽  
River Basin ◽  
Snow Water Equivalent ◽  
Climate Change Impacts ◽  
Snow Accumulation ◽  
Low Flow ◽  
Future Climate Change ◽  
Fraser River

Abstract Changes in air temperature and precipitation can modify snowmelt-driven runoff in snowmelt-dominated regimes. This study focuses on climate change impacts on the snow hydrology of the Fraser River basin (FRB) of British Columbia (BC), Canada, using the Variable Infiltration Capacity model (VIC). Statistically downscaled forcing datasets based on 12 models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are used to drive VIC for two 30-yr time periods, a historical baseline (1980–2009) and future projections (2040–69: 2050s), under representative concentration pathways (RCPs) 4.5 and 8.5. The ensemble-based VIC simulations reveal widespread and regionally coherent spatial changes in snowfall, snow water equivalent (SWE), and snow cover over the FRB by the 2050s. While the mean precipitation is projected to increase slightly, the fraction of precipitation falling as snow is projected to decrease by nearly 50% in the 2050s compared to the baseline. Snow accumulation and snow-covered area are projected to decline substantially across the FRB, particularly in the Rocky Mountains. Onset of springtime snowmelt in the 2050s is projected to be nearly 25 days earlier than historically, yielding more runoff in the winter and spring for the Fraser River at Hope, BC, and earlier recession to low-flow volumes in summer. The ratio of snowmelt contribution to runoff decreases by nearly 20% in the Stuart and Nautley subbasins of the FRB in the 2050s. The decrease in SWE and loss of snow cover is greater from low to midelevations than in high elevations, where temperatures remain sufficiently cold for precipitation to fall as snow.

Factors affecting farmers' networking decisions

2011 ◽  
Vol 11 (1) ◽  
pp. 7-17 ◽  
Author(s):  
Stefano Pascucci
Keyword(s):  
Economic Sociology ◽  
Institutional Economics ◽  
New Institutional Economics ◽  
Driving Factors ◽  
Multivariate Probit ◽  
Factors Affecting ◽  
Different Types ◽  
Main Factors ◽  
Marketing Cooperatives

This paper analyses farmers' decisions to carry out transactions by using three different types of networks: input supply cooperatives, processing and/or marketing cooperatives, and producers associations. We use arguments from economic sociology and new institutional economics to define the main factors affecting farmers' networking decisions, namely relational, asset and location specificity. We applied a multivariate probit (MVP) model to a sample of 15,368 Italian farmers recorded in the 2006 FADN database in order to analyse the simultaneousness of networking decisions and the main driving factors involved. Our results show that farmers are more likely to join different network types simultaneously.

Recent Rapid Climate Changes in Antarctic and their Influence on Low Diversity Ecosystems

2010 ◽  
Vol 17 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Katarzyna J. Chwedorzewska
Keyword(s):  
Environmental Variables ◽  
Climate Changes ◽  
Biological Significance ◽  
Global Changes ◽  
Factors Affecting ◽  
Low Diversity ◽  
Main Factors ◽  
The Antarctic ◽  
High Diversity ◽  
Temperature Water

ABSTRACTThe geographic position, astronomic factors (e.g. the Earth’s maximum distance from the Sun during winter), ice cover and altitude are the main factors affecting the climate of the Antarctic, which is the coldest place on Earth. Parts of Antarctica are facing the most rapid rates of anthropogenic climate change currently seen on the planet. Climate changes are occurring throughout Antarctica, affecting three major groups of environmental variables of considerable biological significance: temperature, water, UV-B radiation.Low diversity ecosystems are expected to be more vulnerable to global changes than high diversity ecosystems

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