Spatial Modeling of Nitrogen Leaching

2002 ◽  
pp. 33-53
Author(s):  
P. Cepuder ◽  
V. aus der Schmitten
Keyword(s):  
Spatial Modeling ◽  
Nitrogen Leaching

Using Spatial Modeling to Improve Wetland Inventories in Great Smoky Mountains National Park

2019 ◽  
Vol 39 (4) ◽  
pp. 482
Author(s):  
Alix A. Pfennigwerth ◽  
Joshua Albritton ◽  
Troy Evans
Keyword(s):  
Spatial Modeling ◽  
National Park ◽  
Great Smoky Mountains ◽  
Smoky Mountains

Using HFire for spatial modeling of fire in shrublands

2009 ◽  
Author(s):  
Seth H. Peterson ◽  
Marco E. Morais ◽  
Jean M. Carlson ◽  
Philip E. Dennison ◽  
Dar A. Roberts ◽  
...  
Keyword(s):  
Spatial Modeling

Spatial modeling of air pollution based on data streams from geosensor networks

2018 ◽  
Vol 930 (12) ◽  
pp. 39-43 ◽  
Author(s):  
V.P. Savinikh ◽  
A.A. Maiorov ◽  
A.V. Materuhin
Keyword(s):  
Air Pollution ◽  
Data Streams ◽  
Spatial Modeling ◽  
Spatial Model ◽  
Large City ◽  
Field Tests ◽  
Processing Unit ◽  
Geosensor Network ◽  
Spatio Temporal ◽  
Different Sources

The article is a brief summary of current research results of the authors in the field of spatial modeling of air pollution based on spatio-temporal data streams from geosensor networks. The urban environment is characterized by the presence of a large number of different sources of emissions and rapidly proceeding processes of contamination spread. So for the development of an adequate spatial model is required to make measurements with a large spatial and temporal resolution. It is shown that geosensor network provide researchers with the opportunity to obtain data with the necessary spatio-temporal detail. The article describes a prototype of a geosensor network to build a detailed spatial model of air pollution in a large city. To create a geosensor in the prototype of the system, calibrated gas sensors for a nitrogen dioxide and carbon monoxide concentrations measurement were interfaced to the module, which consist of processing unit and communication unit. At present, the authors of the article conduct field tests of the prototype developed.

scholarly journals Erratum: Dieu, T.B. et al. A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides. Remote Sens. 2018, 10, 1538

2018 ◽  
Vol 11 (1) ◽  
pp. 57 ◽  
Author(s):  
Dieu Tien Bui ◽  
Himan Shahabi ◽  
Ataollah Shirzadi ◽  
Kamran Kamran Chapi ◽  
Nhat-Duc Hoang ◽  
...  
Keyword(s):  
Spatial Modeling ◽  
Imperialist Competitive Algorithm ◽  
Integrated Approach ◽  
Relevance Vector Machine ◽  
Shallow Landslides ◽  
Competitive Algorithm

The authors wish to make the following corrections to this paper [...]

scholarly journals Response of Vertical Migration and Leaching of Nitrogen in Percolation Water of Paddy Fields under Water-Saving Irrigation and Straw Return Conditions

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 868 ◽  
Author(s):  
Chengxin Zheng ◽  
Zhanyu Zhang ◽  
Yunyu Wu ◽  
Richwell Mwiya
Keyword(s):  
Vertical Migration ◽  
Growth Stage ◽  
Nitrogen Leaching ◽  
Water Saving ◽  
Paddy Fields ◽  
N Leaching ◽  
Leaching Losses ◽  
Leaching Loss ◽  
Straw Return ◽  
Percolation Water

The use of water-saving irrigation techniques has been encouraged in rice fields in response to irrigation water scarcity. Straw return is an important means of straw reuse. However, the environmental impact of this technology, e.g., nitrogen leaching loss, must be further explored. A two-year (2017–2018) experiment was conducted to investigate the vertical migration and leaching of nitrogen in paddy fields under water-saving and straw return conditions. Treatments included traditional flood irrigation (FI) and two water-saving irrigation regimes: rain-catching and controlled irrigation (RC-CI) and drought planting with straw mulching (DP-SM). RC-CI and DP-SM both significantly decreased the irrigation input compared with FI. RC-CI increased the rice yield by 8.23%~12.26%, while DP-SM decreased it by 8.98%~15.24% compared with FI. NH4+-N was the main form of the nitrogen leaching loss in percolation water, occupying 49.06%~50.97% of TN leaching losses. The NH4+-N and TN concentration showed a decreasing trend from top to bottom in soil water of 0~54 cm depth, while the concentration of NO3−-N presented the opposite behavior. The TN and NH4+-N concentrations in percolation water of RC-CI during most of the rice growth stage were the highest among treatments in both years, and DP-SM showed a trend of decreasing TN and NH4+-N concentrations. The NO3−-N concentrations in percolation water showed a regular pattern of DP-SM > RC-CI > FI during most of the rice growth stage. RC-CI and DP-SM remarkably reduced the amount of N leaching losses compared to FI as a result of the significant decrease of percolation water volumes. The tillering and jointing-booting stages were the two critical periods of N leaching (accounted for 74.85%~86.26% of N leaching losses). Great promotion potential of RC-CI and DP-SM exists in the lower reaches of the Yangtze River, China, and DP-SM needs to be further optimized.

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