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Shaoxing, China

Lou W.,Xinchang Weather Bureau | Lou W.,CMA Technologies, Inc. | Wu L.,Zhejiang Provincial Climate Center | Chen H.,Zhejiang Provincial Meteorological Observatory | And 2 more authors.
Natural Hazards | Year: 2012

This study adopts a loss assessment and indemnity approach for rice crops at risk of flooding in Yuhang County, Zhejiang Province. Employing a hydrological model for simulating floods and a reduction model for predicting rice yield, the relationship between the rate of reduction in the rice yield and precipitation is discussed. We argue that the yield reduction rate can be assessed according to the amount of precipitation and designed a weather-based indemnity index for agricultural insurance purposes in Zhejiang Province. With geographic information system technology, the yield reduction rate and weather-based indemnity index were refined and found to effectively reduce the shortcomings of traditional agricultural insurance, i. e., moral hazard, large error in assessing disaster loss and high basis risk. The validity of the method was verified by the amount of rice lost due to No. 16 typhoon Krosa in 2007, and the results show that the proposed method can well simulate the reduction rate of rice yield according to precipitation data. © 2011 Springer Science+Business Media B.V. Source


Lou W.,Xinchang Weather Bureau | Chen H.,Zhejiang Weather Station | Shen X.,ShaoXing Weather Bureau | Sun K.,Xinchang Weather Bureau | Deng S.,Xinchang Weather Bureau
Natural Hazards | Year: 2012

Tropical cyclones represent major natural disasters in low- and mid-latitude coastal areas. Effective assessment of tropical cyclone disasters provides a scientific reference for the formulation of tropical cyclone prevention and disaster-relief measures. Tropical cyclone disasters in Zhejiang Province are mainly studied based on GIS technology, by considering disaster-causing factors, disaster-affected bodies, the disaster-formative environment, and spatial distribution of disaster prevention and relief capacity. In light of an uncertain nonlinear relationship between assessment factors and disaster factors, we used support vector machines to establish a fine, quantitative assessment model. This model evaluates the following disaster indices: Disaster-affected population, direct economic loss, affected crop area, and number of damaged houses resulting from a tropical cyclone disaster in Zhejiang, with the county as basic assessment unit. Assessment of tropical cyclone No. 0908 shows that the developed assessment model is able to accurately evaluate the geographical distribution of losses caused by a tropical cyclone. © 2012 Springer Science+Business Media B.V. Source


Lou W.,Xinchang Weather Bureau | Ji Z.,ShaoXing Weather Bureau | Sun K.,Xinchang Weather Bureau | Zhou J.,Taizhou Weather Bureau
Precision Agriculture | Year: 2013

This study aims to develop a method to evaluate economic loss resulting from damage of spring frost to tea plantations, with the help of remote sensing and geographic information system (GIS) technology. The study site was the Yuezhou Longjing tea producing area in the Shaoxing region of China and evaluated the economic loss resulting from damage to Wuniuzao, Longjing-43 and Jiukeng tea plantations caused by frost on 10 March 2010. Based on a linear equation for representing the variations of each tea tree species with geographical factors, their beginning date of tea plucking (BDTP) were calculated at each grid points with a GIS database. Minimum temperatures were retrieved with four split-window algorithms and satellite remote sensing data was acquired at 06:29 and 12:57 on 10 March 2010. A variational correction method was performed with data from automatic weather stations. Mean absolute error between the retrieved minimum temperatures and actual minimum temperatures of only 0.3 °C was obtained. The BDTP for each species, based on minimum temperature values, and the frost index for each grid point were referenced to assess economic loss resulting from damage to Wuniuzao, Longjing-43, and Jiukeng tea plantations caused by frost. The economic loss estimated in our study was close to the actual value. © 2013 Springer Science+Business Media New York. Source

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