Regional Water Balance Based on Remotely Sensed Evapotranspiration and Irrigation: An Assessment of the Haihe Plain, China

Remote Sensing

Yanmin Yang³  Yonghui Yang³  De Li Liu¹  Tom Nordblom¹  Bingfang Wu² 

[1] EH Graham Centre for Agricultural Innovation, Wagga Wagga, New South Wales 2650, Australia; E-Mails:;Key Lab. Of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth Chinese Academy of Science, P.O. Box 9718, No. 20, Datun Road, Olympic Science Park, Beijing 100101, China; E-Mails:;Key Laboratory of Agricultural Water Resources, Center for Agricultural Resources Research, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, 286 Huaizhong Road, Shijiazhuang 050020, China; E-Mail:

关键词: ETWatch;    remote sensing technique;    ET;    irrigation requirement;   

DOI  :  10.3390/rs6032514

来源: mdpi

【 摘 要 】

Optimal planning and management of the limited water resources for maximum productivity in agriculture requires quantifying the irrigation applied at a regional scale. However, most efforts involving remote sensing applications in assessing large-scale irrigation applied (IA) have focused on supplying spatial variables for crop models or studying evapotranspiration (ET) inversions, rather than directly building a remote sensing data-based model to estimate IA. In this study, based on remote sensing data, an IA estimation model together with an ET calculation model (ETWatch) is set up to simulate the spatial distribution of IA in the Haihe Plain of northern China. We have verified this as an effective approach for the simulation of regional IA, being more reflective of regional characteristics and of higher resolution compared to single site-specific results. The results show that annual ET varies from 527 mm to 679 mm and IA varies from 166 mm to 289 mm, with average values of 602 mm and 225 mm, respectively, from 2002 to 2007. We confirm that the region along the Taihang Mountain in Hebei Plain has serious water resource sustainability problems, even while receiving water from the South-North Water Transfer (SNWT) project. This is due to the region’s intensive agricultural production and declining groundwater tables. Water-saving technologies, including more timely and accurate geo-specific IA assessments, may help reduce this threat.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland