Share Email Print

Proceedings Paper

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands
Author(s): Weimin Ju; Ping Gao; Jun Wang; Xianfeng Li; Shu Chen
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

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.

Paper Details

Date Published: 3 November 2008
PDF: 8 pages
Proc. SPIE 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments, 714517 (3 November 2008); doi: 10.1117/12.813021
Show Author Affiliations
Weimin Ju, Nanjing Univ. (China)
Ping Gao, Meteorological Observatory of Jiangsu Province (China)
Jun Wang, Nanjing Univ. (China)
Xianfeng Li, Nanjing Univ. (China)
Shu Chen, Nanjing Univ. (China)

Published in SPIE Proceedings Vol. 7145:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Yong Lao, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?