Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

Weimin Ju; Ping Gao; Jun Wang; Xianfeng Li; Shu Chen

doi:10.1117/12.813021

3 November 2008 Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

Weimin Ju, Ping Gao, Jun Wang, Xianfeng Li, Shu Chen

Author Affiliations +

Proceedings Volume 7145, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Monitoring and Assessment of Natural Resources and Environments; 714517 (2008) https://doi.org/10.1117/12.813021
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

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.

Citation Download Citation

Weimin Ju, Ping Gao, Jun Wang, Xianfeng Li, and Shu Chen "Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands", 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); https://doi.org/10.1117/12.813021

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KEYWORDS

Data modeling

Solar radiation models

Remote sensing

Atmospheric modeling

Meteorology

Vegetation

Ecosystems

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