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Proceedings Paper

Exploring the relationship between irrigation water requirements and potential yield in the Huang-Huai-Hai plain
Author(s): Huaxiu Tang; Jinyan Zhan; Xiangzheng Deng
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Paper Abstract

By using the GIS technologies, we interpolate the site-based meteorological data into climatic surface data, which are the main input parameters for the CropWat model, used to estimate the reference evapotranspiration (ET0). And then by combining the ET0 with the information on share of cultivated land decoded from the Landsat TM/ETM digital imagines covering the entire case study area, the Huang-Huai-Hai plain, we estimate the amount of irrigation water requirements (IWRs) in the years of 1991 and 2000. We then introduce the potential yield (PY) of cultivated land estimated from the Estimation Model for the Agricultural Productivity Potential (EMAPP) to explore the relationship between the IWRs and the PY . By conducting GIS-based spatial overlay analyses, we explore the positive correlation relationship between the IWRs and the PY of cultivated land. Finally, we conclude that the IWRs is now a constrain factor on the PY of cultivated land in the Huang-Huai-Hai plain in those areas with the irrigation water constrains. The result has offered a scientific basis for the decision makings in the exploitation and utilization of resources and energy as well as the land use planning, protection of the potential yields and the managements of irrigation water at the regional level.

Paper Details

Date Published: 14 November 2007
PDF: 7 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67903I (14 November 2007); doi: 10.1117/12.751656
Show Author Affiliations
Huaxiu Tang, Nanjing Univ. (China)
Jinyan Zhan, Beijing Normal Univ. (China)
Xiangzheng Deng, Institute of Geographical Sciences and Natural Resources Research (China)
Ctr. for Chinese Agricultural Policy (China)

Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications
Yongji Wang; Jun Li; Bangjun Lei; Chao Wang; Liang-Pei Zhang; Jing-Yu Yang, Editor(s)

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