Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands
Soil water content (SWC) is an important factor affecting photosynthesis,growth,and final yields of crops.The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management.A variety of methodologies have been developed to estimate SWC at local and regional scales,including field sampling,remote sensing monitoring and model simulations.The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets,including vegetation parameters,soil and meteorological data.Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters.In this study,the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province,China.Validation shows that the BEPS model is able to capture 81％ and 83％ of across-site variations of SWC at 10 and 20 cm depths during the period from September to December,2006 when a serous autumn drought occurred.The simulated SWC responded the events of rainfall well at regional scale,demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.
ecosystem model remote sensing soil water content assimilation
Weimin Ju Ping Gao Jun Wang Xianfeng Li Shu Chen
International Institute for Earth System Science,Nanjing University,22 Hankou Road,Nanjing,China,210 Meteorological Observatory of Jiangsu Province,Nanjing,Jinagsu,China,210008
国际会议
第16届国际地理信息科学与技术大会(16th International Conference on GeoInformatics and the Joint Conference)
广州
英文
2008-06-28（万方平台首次上网日期，不代表论文的发表时间）