Quantifying global agricultural water appropriation with data derived from earth observations

Wu，Bingfang1,2; Tian，Fuyou1; Zhang，Miao1; Piao，Shilong3; Zeng，Hongwei1,2; Zhu，Weiwei1; Liu，Junguo4; Elnashar，Abdelrazek1,2,5; Lu，Yuming1,2

2022-07-15

10.1016/j.jclepro.2022.131891

Journal of Cleaner Production   影响因子和分区

0959-6526

1879-1786

Agricultural water appropriation has undergone rapid changes in recent decades, but estimates of global water appropriation have not been updated with the latest data and consistent methods. Documenting these changes is challenging given the heterogeneous water use landscape and the growing influence of human activities worldwide, and this complexity cannot be well addressed with the existing methodology, which is subject to large model uncertainties. Here, a spatial analysis and aggregated method was proposed to quantify and refine estimates of global agricultural water appropriation (GAWA) in terms of consumptive freshwater use, with data derived from Earth observations, independent of estimates from hydrological models. The results show the global water appropriation at the pixel scale, in agroecological zones and in the main water-consuming countries, including global maps of rainfed and irrigated cropland evapotranspiration (ET), net water consumption due to irrigation, natural ET and renewable freshwater resources (RFWR), and indicate that agriculture remains the largest user in terms of both water consumption and withdrawals worldwide, representing 87% of global water consumption, with approximately 60% of global freshwater withdrawals devoted to irrigation circa 2015. The percentage of withdrawals devoted to irrigation has decreased in recent decades when compared to the previous estimate of 70%. The results reveal the actual global crop consumptive use (8053.6 km/yr) of blue and green water and the total human water consumption (8442 km/yr), which represents the part of the water cycle affected by human intervention, mainly (95.4%) by agriculture. This study reveals that high-resolution irrigated croplands are essential for accurate estimations of water use appropriation and demonstrates that earth observation-derived data can provide a new understanding of global water use landscape. The study can support decision making in sustaining food and water security, and implementing water-adapted sustainable agricultural policies.

Agricultural water appropriation Crop water consumption High-resolution dataset Spatial analysis

SCI ; EI

英语

其他

National Key Research and Development Program of China[2016YFA0600304];National Natural Science Foundation of China[41861144019];National Natural Science Foundation of China[41991232];Chinese Academy of Sciences[QYZDY-SSW-DQC014];

Science & Technology - Other Topics ; Engineering ; Environmental Sciences & Ecology

Green & Sustainable Science & Technology ; Engineering, Environmental ; Environmental Sciences

WOS:000804679000001

ELSEVIER SCI LTD

20221912072032

Crops ; Decision making ; Irrigation ; Spatial variables measurement ; Uncertainty analysis ; Water resources ; Water supply

Water Resources:444 ; Water Supply Systems:446.1 ; Agricultural Methods:821.3 ; Agricultural Products:821.4 ; Management:912.2 ; Probability Theory:922.1 ; Mechanical Variables Measurements:943.2

2-s2.0-85129282173

Scopus

1.State Key Laboratory of Remote Sensing Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing,100101,China
2.College of Resources and Environment,University of Chinese Academy of Sciences,Beijing,100049,China
3.Sino-French Institute of Earth System Sciences,Peking University,Beijing,100871,China
4.School of Environmental Science and Engineering,South University of Science and Technology of China,Shenzhen,518055,China
5.Department of Natural Resources,Faculty of African Postgraduate Studies,Cairo University,Giza,12613,Egypt

Wu，Bingfang,Tian，Fuyou,Zhang，Miao,et al. Quantifying global agricultural water appropriation with data derived from earth observations[J]. Journal of Cleaner Production,2022,358.

Wu，Bingfang.,Tian，Fuyou.,Zhang，Miao.,Piao，Shilong.,Zeng，Hongwei.,...&Lu，Yuming.(2022).Quantifying global agricultural water appropriation with data derived from earth observations.Journal of Cleaner Production,358.

Wu，Bingfang,et al."Quantifying global agricultural water appropriation with data derived from earth observations".Journal of Cleaner Production 358(2022).