Share Email Print
cover

Journal of Applied Remote Sensing

Spatially explicit estimation of soil-water resources by coupling of an eco-hydrological model with remote sensing data in the Weihe River Basin of China
Author(s): Shudong Wang; Yujuan Wang; Shengtian Yang; Mingcheng Wang; Lifu Zhang; Jia Liu
Format Member Price Non-Member Price
PDF $20.00 $25.00

Paper Abstract

Soil-water resources are key components for agriculture and have great potential. Strategic and significant efforts are, therefore, required to make full use of soil-water resources, especially in dry or semidry areas. We coupled a soil-water model with remotely sensed data and associated techniques to analyze the spatial-temporal dynamics of soil-water resources in the Weihe River Basin in China. The moderate-resolution imaging spectroradiometer (MODIS), Chinese meteorological satellite precipitation estimation data (FY-2), and global land data assimilation system (GLDAS) products were used for spatial land surface characteristics interpretation and model parameters derivation. The modeling results were compared and validated using data from a nearby observation site. The average soil-water resources of the Weihe River Basin vary between 40 and 100 mm during the simulation period from January to December, with a maximum of 99 mm appearing in August and a minimum of 38 mm in December. Forest land was characterized by large soil-water resources, with an average annual rate of 1094.7 mm. Farmland and grassland exhibited low values, with average annual rates of 986.7 and 893.5 mm, respectively. The results could be taken into consideration for soil-water resources management.

Paper Details

Date Published: 2 April 2014
PDF: 18 pages
J. Appl. Remote Sens. 8(1) 083653 doi: 10.1117/1.JRS.8.083653
Published in: Journal of Applied Remote Sensing Volume 8, Issue 1
Show Author Affiliations
Shudong Wang, Institute of Remote Sensing and Digital Earth (China)
Yujuan Wang, Institute of Remote Sensing and Digital Earth (China)
Shengtian Yang, Beijing Normal Univ. (China)
Mingcheng Wang, Beijing Normal Univ. (China)
Lifu Zhang, Institute of Remote Sensing and Digital Earth (China)
Jia Liu, Institute of Remote Sensing and Digital Earth (China)


© SPIE. Terms of Use
Back to Top