scholarly journals Spatio-temporal Web Performance Prediction: Turning Bands Method and Sequential Gaussian Simulation

2016 ◽  
Vol 96 ◽  
pp. 568-576
Author(s):  
Leszek Borzemski ◽  
Michał Danielak ◽  
Anna Kamińska-Chuchmała
Keyword(s):  
Performance Prediction ◽  
Sequential Gaussian Simulation ◽  
Web Performance ◽  
Turning Bands ◽  
Spatio Temporal ◽  
Gaussian Simulation

scholarly journals Spatio-Temporal Change and Pollution Risk of Agricultural Soil Cadmium in a Rapidly Industrializing Area in the Yangtze Delta Region of China

2018 ◽  
Vol 15 (12) ◽  
pp. 2743 ◽  
Author(s):  
Xianghua Xu ◽  
Jiaying Qian ◽  
Enze Xie ◽  
Xuezheng Shi ◽  
Yongcun Zhao
Keyword(s):  
Potential Risk ◽  
Agricultural Soil ◽  
Sequential Gaussian Simulation ◽  
Rapid Urbanization ◽  
Pollution Risk ◽  
Soil Cadmium ◽  
Rapid Industrialization ◽  
Spatio Temporal ◽  
Major Attention ◽  
Gaussian Simulation

The impacts of rapid industrialization on agricultural soil cadmium (Cd) accumulation and their potential risks have drawn major attention from the scientific community and decision-makers, due to the high toxicity of Cd to animals and humans. A total of 812 topsoil samples (0–20 cm) was collected from the southern parts of Jiangsu Province, China, in 2000 and 2015, respectively. Geostatistical ordinary kriging and conditional sequential Gaussian simulation were used to quantify the changes in spatial distributions and the potential risk of Cd pollution between the two sampling dates. Results showed that across the study area, the mean Cd concentrations increased from 0.110 mg/kg in 2000 to 0.196 mg/kg in 2015, representing an annual average increase of 5.73 μg/kg. Given a confidence level of 95%, areas with significantly-increased Cd covered approximately 12% of the study area. Areas with a potential risk of Cd pollution in 2000 only covered 0.009% of the study area, while this figure increased to 0.75% in 2015. In addition, the locally concentrating trend of soil Cd pollution risk was evident after 15 years. Although multiple factors contributed to this elevated Cd pollution risk, the primary reason can be attributed to the enhanced atmospheric deposition and industrial waste discharge resulting from rapid industrialization, and the quick increase of traffic and transportation associated with rapid urbanization.

scholarly journals Optimal Irrigation Mode and Spatio-Temporal Variability Characteristics of Soil Moisture Content in Different Growth Stages of Winter Wheat

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1180 ◽  
Author(s):  
Yujian Yang ◽  
Yanbo Huang ◽  
Yong Zhang ◽  
Xueqin Tong
Keyword(s):  
Moisture Content ◽  
Winter Wheat ◽  
Time Domain Reflectometry ◽  
Sequential Gaussian Simulation ◽  
Growth Stages ◽  
Evolution Characteristics ◽  
Spatio Temporal ◽  
Jointing Stage ◽  
Gaussian Simulation ◽  
Different Growth Stages

To advance site-specific management of soil volumetric moisture content (VMC), this study analyzed the spatio-temporal evolution characteristics of soil VMC using the method of sequential Gaussian simulation (SGS) during the different growth stages of winter wheat. This was compared with data measured by time domain reflectometry (TDR) which is a well-established electromagnetic technique to measure soil VMC. The spatial autocorrelation coefficient of VMC indicated the strongest clustering of VMC in the tillering stage, and the least clustering of VMC in the harvest stage. A threshold of VMC in topsoil in the jointing stage of winter wheat was put forward. This threshold is 26, signifying that at a lower value, irrigation should be performed and irrigation efficiencies can be improved. Stable and sub-stable areas in the spatial variability maps of VMC were identified in the winter wheat jointing stage. Furthermore, the optimal irrigation stage was the early jointing stage, and irrigation was performed once as a guide. A loose-couple spatial model was constructed using the VMC in topsoil and the volume of water for irrigation. The VMC in the jointing stage of winter wheat was linked with efficient and water-saving irrigation.

Which Path to Choose in Sequential Gaussian Simulation

2017 ◽  
Vol 50 (1) ◽  
pp. 97-120 ◽  
Author(s):  
Raphaël Nussbaumer ◽  
Grégoire Mariethoz ◽  
Erwan Gloaguen ◽  
Klaus Holliger
Keyword(s):  
Sequential Gaussian Simulation ◽  
Gaussian Simulation
Sign in / Sign up

Export Citation Format

Share Document