Water productivity mapping methods using remote sensing

被引:25
作者
Biradar, Chandrashekhar M. [1 ,2 ]
Thenkabail, Prasad S. [3 ,4 ]
Platonov, Alexander [4 ]
Xiao, Xingming [1 ,2 ]
Geerken, Roland [5 ]
Noojipady, Praveen [6 ]
Turral, Hugh
Vithanage, Jagath [4 ]
机构
[1] Univ Oklahoma, Ctr Spatial Anal, Stephenson Res & Technol Ctr, Coll Atmospher & Geog Sci, Norman, OK 73019 USA
[2] Univ New Hampshire, Complex Syst Res Ctr, Inst Study Earth Oceans & Space, Durham, NH 03824 USA
[3] US Geol Survey, Flagstaff, AZ 86001 USA
[4] IWMI, Colombo, Sri Lanka
[5] Yale Univ, Dept Geol & Geophys, New Haven, CT 06520 USA
[6] Univ Maryland, Dept Geog, College Pk, MD 20742 USA
基金
美国国家航空航天局;
关键词
water productivity mapping; biophysical relationship; vegetation indices; evapotranspiration; remote sensing;
D O I
10.1117/1.3033753
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The goal of this paper was to develop methods and protocols for water productivity mapping (WPM) using remote sensing data at multiple resolutions and scales in conjunction with field-plot data. The methods and protocols involved three broad categories: (a) Crop Productivity Mapping(CPM) (kg/m2); (b) Water Use (evapotranspiration) Mapping (WUM) (m3/m2); and (c) Water Productivity Mapping (WPM) (kg/m3). First, the CPMs were determined using remote sensing by: (i) Mapping crop types; (ii) modeling crop yield; and (iii) extrapolating models to larger areas. Second, WUM were derived using the Simplified Surface Energy Balance (SSEB) model. Finally, WPMs were produced by dividing CPMs and WUMs. The paper used data from Quickbird 2.44m, Indian Remote Sensing (IRS) Resoursesat-1 23.5m, Landsat-7 30m, and Moderate Resolution Imaging Spectroradiometer (MODIS) 250m and 500m, to demonstrate the methods for mapping water productivity (WP). In terms of physical water productivity (kilogram of yield produced per unit of water delivered), wheat crop had highest water productivity of 0.60 kg/m3 (WP), followed by rice with 0.5 kg/m3, and cotton with 0.42 kg/m3. In terms of economic value (dollar per unit of water delivered), cotton ranked highest at $ 0.5/m3 followed by wheat with $ 0.33/m3 and rice at $ 0.10/m3. The study successfully delineated the areas of low and high WP. An overwhelming proportion (50+%) of the irrigated areas were under low WP for all crops with only about 10% area in high WP.
引用
收藏
页数:22
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