Spatial and temporal variation of mercury load in surface water and sediments around an integrated steel plant in India

2009 ◽  
Vol 29 (4) ◽  
pp. 421-430
Author(s):  
Anubhuti Koshle ◽  
Yasmeen Pervez ◽  
Shamsh Pervez
Keyword(s):  
Surface Water ◽  
Temporal Variation ◽  
Steel Plant ◽  
Spatial And Temporal Variation ◽  
Integrated Steel Plant ◽  
Mercury Load

Spatial and temporal variation of surface water vapor over northern and southern regions of Qinling Mountains

2013 ◽  
Vol 33 (12) ◽  
pp. 3805-3815 ◽  
Author(s):  
蒋冲 JIANG Chong ◽  
王飞 WANG Fei ◽  
喻小勇 YU Xiaoyong ◽  
穆兴民 MU Xingmin ◽  
杨旺明 YANG Wangming ◽  
...  
Keyword(s):  
Water Vapor ◽  
Surface Water ◽  
Temporal Variation ◽  
Spatial And Temporal Variation ◽  
Qinling Mountains

SPATIAL AND TEMPORAL VARIATION IN GROUNDWATER GEOCHEMISTRY IN THE HIGH PLAINS AQUIFER SYSTEM, SOUTHCENTRAL KANSAS

2016 ◽  
Author(s):  
Alexandria D. Richard ◽  
◽  
Adam E. Lane ◽  
Janet M. Paper ◽  
Ben R. Haller ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Spatial And Temporal Variation ◽  
High Plains ◽  
High Plains Aquifer ◽  
Aquifer System ◽  
Groundwater Geochemistry

scholarly journals Spatial and Temporal Variation Characteristics of Snowfall in the Haihe River Basin from 1960 to 2016

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu
Keyword(s):  
Temporal Variation ◽  
River Basin ◽  
Spatial And Temporal Variation ◽  
Haihe River Basin ◽  
Temperature Threshold ◽  
Threshold Method ◽  
Exponential Equation ◽  
Haihe River ◽  
The Haihe River Basin ◽  
Different Levels

The spatio-temporal variation of precipitation under global warming had been a research hotspot. Snowfall is an important part of precipitation, and its variabilities and trends in different regions have received great attention. In this paper, the Haihe River Basin is used as a case, and we employ the K-means clustering method to divide the basin into four sub-regions. The double temperature threshold method in the form of the exponential equation is used in this study to identify precipitation phase states, based on daily temperature, snowfall, and precipitation data from 43 meteorological stations in and around the Haihe River Basin from 1960 to 1979. Then, daily snowfall data from 1960 to 2016 are established, and the spatial and temporal variation of snowfall in the Haihe River Basin are analyzed according to the snowfall levels as determined by the national meteorological department. The results evalueted in four different zones show that (1) the snowfall at each meteorological station can be effectively estimated at an annual scale through the exponential equation, for which the correlation coefficient of each division is above 0.95, and the relative error is within 5%. (2) Except for the average snowfall and light snowfall, the snowfall and snowfall days of moderate snow, heavy snow, and snowstorm in each division are in the order of Zones III > IV > I > II. (3) The snowfall and the number of snowfall days at different levels both show a decreasing trend, except for the increasing trend of snowfall in Zone I. (4) The interannual variation trend in the snowfall at the different levels are not obvious, except for Zone III, which shows a significant decreasing trend.

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