Cloud Simulation Platform for Water Environment Assessment

Ge, Xiao Fan; Hou, Di Bo; Zhang, Guang Xin; Huang, Ping

doi:10.4028/www.scientific.net/amm.316-317.670

Cited by 3 publications

(1 citation statement)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the MATLAB and C language development environment, a system interface was designed that integrated the input data, the early warning and forecasting model, output data, and the result expression to an organic whole. It had a friendly interface, convenient operation, and comprehensive function [28,29]. Thirdly, a two-dimensional water area was generalized and a spatial grid was discretized by MATLAB.…”

Section: Early Warning and Forecasting Systemmentioning

confidence: 99%

Early Warning and Forecasting System of Water Quality Safety for Drinking Water Source Areas in Three Gorges Reservoir Area, China

Ding

Zhang

Jiang

et al. 2017

Water

View full text Add to dashboard Cite

Nowadays, the effects of water pollution accidents on water quality safety and regional residents' living have attracted worldwide attention. Therefore, the objective of this research is to propose an early warning and forecasting model and develop a visual system of water quality safety for drinking water source areas in the Three Gorges Reservoir Area under accident conditions. Based on an Instantaneous Point Source Two-dimensional Water Quality Model and the security requirements of water quality, an early warning and forecasting model was presented, and then the system was advanced by a MATLAB platform. In addition, a hypothetical case was also carried out for the Fenghuangshan drinking water source area. Within 0.040 h to 0.096 h after the accident, the water quality could meet the standard, and the warning level was primary and intermediate, sequentially. From 0.096 h to 11.960 h after the accident, the pollutant concentration exceeded the standard, under which conditions advanced warning started. Then the intermediate and primary warnings restarted in sequence until the pollutant concentration decreased to the background value. Therefore, the proposed model could accurately predict the spatial-temporal change trend of pollutant concentration, and the developed system could efficiently realize early warnings and the forecasting of water quality safety.

show abstract

Section: Early Warning and Forecasting Systemmentioning

confidence: 99%