Entity

Time filter

Source Type


Chen Y.,Chongqing Institute of Meteorological science | You Y.,Chongqing University
Applied Mechanics and Materials | Year: 2013

In this paper, MODIS-250m vegetation index from first 10-day of March to last 10-day of November in 2010and 2011, land use data and the yield data from 9 counties such as Jiangjin, Wanzhou, Fengdu, Liangping, Qijiang, Liangping, Fuling, Yunyang, Kaixian, Wixi in Chongqing were used. Based on GIS,RS technique and NDVI analysis results, the rice planting area was extracted. Four key growth period of rice such tillering, jointing, heading and milk were selected to establish dynamic assessment model. In nine counties, the average relative error of the remaining 8 counties was between 5.36%-17.09%, and the mean was 12.31% except Qijiang that estimation results and actual yield deviation was too large. The results show that building rice yield estimation model using normalized difference vegetation index was feasible that can realize the dynamic yield estimation of rice. © (2013) Trans Tech Publications, Switzerland. Source


Wu W.,Southwest University | Fan L.,Chongqing Institute of Meteorological science | Li M.,Southwest University | Liu H.,Southwest University | Li Y.,Agricultural Commission of Wanzhou District
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering | Year: 2012

The records of daily solar radiation (Rs, MJ·m -2·d -1) are the important inputs for crop simulation models. However, for some model users, Rs at longer temporal intervals are more available than that at daily scale. The objective of this study was to analyze the sensitivity of simulated crop growth and production using CERES-Maize and GROPGRO-Soybean, two widely used crop growth models, to uncertainty in Rs at different time scales (5-day, 10-day, and monthly). Daily radiation data (1961-1990) from Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) for the state of Georgia, USA were used to create 5-day, 10-day, and monthly mean daily Rs data sets. Datasets related to daily Rs were used as background baselines. The overall performance of the models was not significantly affected by Rs under the studied time scales. Within locations, the simulated days to anthesis and grain yields from 5-day, 10-day, and monthly Rs were close to that from daily Rs for maize and soybean under rainfed and irrigated conditions, respectively. Mean values of relative mean bias error (RMBE), mean bias error (MBE) and root mean square error (RMSE) of the simulated days to anthesis were 0, 0 and 3.5 d for the two crops under the studied scenarios, respectively. The simulated yields were underestimated for maize and overestimated for soybean using 5-day, 10-day, and monthly Rs for both rainfed and irrigated conditions, respectively. Under rainfed and irrigated conditions, the average RMBE and RMSE were -0.59%, 120 kg/hm 2 and -0.52%, 129 kg/hm 2 for maize yield, and 5%, 152 kg/hm 2 and 4.7%, 165 kg/hm 2 for soybean, respectively. Short-term bias in the difference between evaluated time scales and daily scale could affect the outputs of the crop models. Under the scenarios evaluated, CGOPGRO-Soybean model showed higher sensitivity to changes in multi-temporal Rs and water regimes than CERES-Maize model. Based on the results of this study, it can be concluded that 5-day, 10-day, and monthly mean daily Rs could be used as an input for crop growth simulation models when daily Rs are not available. Source


Zuo X.,Chongqing Institute of Meteorological science
Journal of Natural Disasters | Year: 2010

Emergency rescue is a critical part of emergency management. Based on the case study of the emergency rescue during the landslide in Wulong County, Chongqing Municipality this paper analyzes the current condition of emergency rescue during natural disasters in China, indicates the main problems existing in the current rescue status, and discusses solutions to improve emergency rescue capability for natural disasters. Source


Wang J.,China Agricultural University | Wang E.,CSIRO | Yin H.,National Climate Center | Feng L.,China Agricultural University | Zhang J.,Chongqing Institute of Meteorological science
Agricultural and Forest Meteorology | Year: 2014

Quantifying the changes in crop potential yields and yield gaps is essential to determine the yield-contributing and yield-limiting factors and enhance crop productivity. Here we combine simulation modeling and long-term maize yield records (1981-2009) from 10 sites to investigate the changes in maize yield potential, actual yield and yield gaps in the past three decades in the North China Plain (NCP). The cultivar parameters in the APSIM-maize model were derived based on the recorded flowering and maturity dates at each site, and the simulation results of calibrated model was able to explain >63% of the variations in recorded maize grain yield across the 10 sites. Potential maize yield simulated under sufficient water and nitrogen supply showed a general declining trend, significantly (P<. 0.01) at half of the study sites. This was mainly caused by the declining radiation together with increasing temperature, particularly during the pre-flowering period. Continuous adoptions of new maize varieties helped to maintain the pre-flowering periods at some sites and to extend post-flowering periods at most sites. This, together with increasing planting density, led to continuous increase in maize yields. As a result, maize yield gaps continued to shrink (P< 0.05) at all the sites except for Zhengzhou, with a rate ranging from -116.8 kg/ha. a to -356.5 kg/ha a across sites. At two of the studied sites, the maize potential yield had already been achieved. While application of irrigation and nitrogen fertilizers has been managed at near optimal level already, other new technological breakthroughs will be needed for future advance of maize yield. © 2014 Elsevier B.V. Source


He Z.,Chongqing Institute of Meteorological science
2010 4th International Conference on Bioinformatics and Biomedical Engineering, iCBBE 2010 | Year: 2010

Based on the acid rain data measured at Shapingba weather station in Chongqing from 1993 to 2007 and the emission data of SO2 in Chongqing, Guizhou and Sichuan, the acid rain change trend and its relationship with SO2 emission were analyzed. The results indicated that in the past 15 years, the change trend of the pH value of the precipitation in Chongqing changed between 3.8 and 4.5. The annual variation trend was increasing. In the past 15 years, acid rain (pH<5.6) frequency in Chongqing was high and increased with fluctuate. The frequency of acid rain exceed relatively strong intensity (pH<4.5) had greatly annual change, which was mainly between 30% and 80%. There was relativity between SO2 emission and pH value in Chongqing. The pH value was influenced mainly by SO2 emission besides other factors such as meteorological condition. SO2 emission in Guizhou and Sichuan could have some influence to acid rain in Chongqing. In which Guizhou could be the main distal contamination emission source area. © 2010 IEEE. Source

Discover hidden collaborations