Study On The Early Warning Technique For Wind And Sown Disaster Of Greenhouse

Facility agriculture is the important direction of modern agriculture in our country, the development of agricultural facility has its vital significance to ensure the effective supply of agricultural products, promote agricultural development and farmers’income, enhance agricultural comprehensive production capacity. Solar greenhouse and plastic greenhouse are main types of agricultural facilities in China, in2012the area in whole country reached to37million mu. Wind and snow are the main meteorological disasters for facility agriculture, facility agriculture meteorology disaster prevention and service is in its initial stage at present in our country, the determination of wind and snow disaster indexes of facilities agriculture are only based on the statistical results, which is limited in the application of meteorological service.The study is based on the observed meteorological data, combined with wind tunnel test and computational fluid dynamics (CFD) system, the wind pressure distribution of solar greenhouse and plastic greenhouse has been studied, the snow model based on energy balance has been built, the facility agriculture wind and snow disaster indexes has been confirmed. At the same time, we developed the early warning system of snow thickness of facility surface with the use of. NET development platform. The main conclusions of the research were as follows:(1) We adopted the wind tunnel to measure and analysis wind pressure coefficient and distribution law of facility canopy surface under wind direction angle, and deduced the critical wind speed of facility canopy in all regions when wind disaster occurred. Results showed that windward side of facility greenhouse was wind pressure based with intensive isograms and big wind gradient, while wind changed gently of leeside because of wind suction. Under different wind angles, there was positive pressure and negative pressure transition of wind pressure coefficients of facility greenhouse in all windward areas, zero pressure area appeared during the process, while wind pressure coefficients of windward area were always negative. Under the45°direction Angle, negative pressure in top highest point of greenhouse windward edge reached the maximum. The critical wind speed of each area was deduced by formula, both sides at the top of the facility greenhouse was affected by wind suction mostly. The wind pressure coefficients of all area on top of solar greenhouse varied a lot with the changing wind angle, while the largest suction occurred in VII zone at direction angle135°, at which the wind pressure coefficient was close to1.41, the wind suction suffered reached the maximum value. The research suggested that the minimum critical wind speed for facility plastic greenhouse was14.5m/s, while for solar greenhouse the critical wind speed was18.86m/s.(2) The research studied the disaster-causing critical time under different snowfall levels (light snow, moderate snow, snow, and blizzard) to be used as the meteorological index of disaster according to meteorological industry snowfall standard. We calculated the snow accumulation rate according to the energy balance of greenhouse surface and CFD simulated results. We calculated the time from snow started to snow accumulation started by using energy balance model. And the according to the load of solar greenhouse and plastic greenhouse, within the critical number of days required to reach the critical snow accumulation thickness of solar greenhouse and plastic greenhouse under different wind speed, snowfall and wind direction which we calculated, that the critical number of days the snow disaster occurred were got. Results showed that under the constant wind speed, critical number of days decreased with the snowfall increased, the minimum critical number of days was1.7days when heavy snow occurred(snowfall was5-9mm within24h), upper region was vulnerable to be affected when the wind speed was at Om/s. The law of snow disaster critical number of days of plastic greenhouse was in good agreement with the solar greenhouse; the critical number of days was1.2days.(3) We set up a snow accumulation prediction model by using meteorological data in two snow processes in Nanjing, December25,2012and December29,2012respectively. And then we used the snow thickness observed in CMA comprehensive observation training practice base (Nanjing) meteorological observation station. There was certain error between stimulated snow thickness and measured values. The thickness error of facility surface without snow accumulation was the largest, while error of facility surface with snow accumulation was smaller relatively, the simulated and measured vales in the two process of the snow the coefficient R2based on the1:1line are0.9522,07425. We could predict snow thickness of facility surface with the model basically, which provided the scientific basis for facility agriculture meteorological service.(4) The study based on VS2010.NET and SQL database platform, building snow disaster early warning and decision support service system for facility greenhouse, realizing early warning of the critical wind speed and largest snow thickness of facility surface by using C#programming language, to achieve to provide support for facility greenhouse wind and snow disaster meteorological service.