Arid
DOI10.1080/01431161.2019.1587208
Potential of the remotely-derived products in monitoring ecosystem water use efficiency across grasslands in Northern China
Wei, Jin1,2; Chen, Yanan1,2; Gu, Qing1,2; Jiang, Chongya3; Ma, Mingguo1,2; Song, Lisheng1,2; Tang, Xuguang1,2
通讯作者Tang, Xuguang
来源期刊INTERNATIONAL JOURNAL OF REMOTE SENSING
ISSN0143-1161
EISSN1366-5901
出版年2019
卷号40期号:16页码:6203-6223
英文摘要Water use efficiency (WUE) has been recognized as a crucial parameter to describe the interrelationship between carbon and water cycling. Quantitative assessment to spatiotemporal dynamics of ecosystem WUE in grasslands is of vital importance, given the large proportion of grasslands on the Earth's land surface. Through continuous eddy covariance (EC) measurements at seven grassland sites in Northern China, this study examined the seasonal and interannual variations of gross primary production (GPP), evapotranspiration (ET) and WUE across four typical grassland ecosystems along a water availability gradient. The highest WUE occurred at the alpine meadow ecosystem with 1.45g C kg(-1) H2O, followed by the temperate meadow steppe and the typical steppe. The desert steppe had the lowest WUE with 0.53g C kg(-1) H2O. In addition, the remotely-derived WUE estimates from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Breathing Earth System Simulator (BESS) GPP and ET products, were used to characterize the variability in tower-based WUE over these grassland ecosystems. Generally, WUEBESS had more consistent seasonal trajectories with WUEEC at most grassland sites compared to the variability of WUEMOD. The highest square of Pearson correlation coefficient (R-2) values of WUEBESS were achieved in the alpine meadow sites (approximately 0.83), as well as the lowest root mean square error (RMSE), which ranged from 0.21 to 0.37g C kg(-1) H2O. However, the performances of both WUEBESS and WUEMOD lacked skills at the desert steppe sites which had low vegetation productivity. These remotely-derived WUE products, particularly the WUEMOD, tended to overestimate the annual mean WUEEC across these grassland types, with exception of the alpine meadow sites, where exhibited good performance. The underlying reasons for the biases of the MODIS- and BESS-based products in capturing the seasonal dynamics of grassland WUE were also examined. In general, GPP(MOD) performed better than GPP(BESS) over an 8-day period, whereas ETBESS had a higher accuracy compared to ETMOD across the different grassland ecosystems. Our analyses may be useful for improving the remote sensing-based GPP and ET products to accurately monitor the ecosystem WUE patterns of grasslands over large areas.
类型Article
语种英语
国家Peoples R China ; USA
收录类别SCI-E
WOS记录号WOS:000467883200006
WOS关键词CARBON-DIOXIDE ; INNER-MONGOLIA ; EDDY COVARIANCE ; EVAPOTRANSPIRATION ; EXCHANGE ; PRECIPITATION ; FLUXES ; IMPROVEMENTS ; RESTORATION ; STEPPE
WOS类目Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向Remote Sensing ; Imaging Science & Photographic Technology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/216504
作者单位1.Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China;
2.Southwest Univ, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Sch Geog Sci, Chongqing, Peoples R China;
3.Univ Illinois, Dept Nat Resources & Environm Sci, Urbana, IL USA
推荐引用方式
GB/T 7714
Wei, Jin,Chen, Yanan,Gu, Qing,et al. Potential of the remotely-derived products in monitoring ecosystem water use efficiency across grasslands in Northern China[J],2019,40(16):6203-6223.
APA Wei, Jin.,Chen, Yanan.,Gu, Qing.,Jiang, Chongya.,Ma, Mingguo.,...&Tang, Xuguang.(2019).Potential of the remotely-derived products in monitoring ecosystem water use efficiency across grasslands in Northern China.INTERNATIONAL JOURNAL OF REMOTE SENSING,40(16),6203-6223.
MLA Wei, Jin,et al."Potential of the remotely-derived products in monitoring ecosystem water use efficiency across grasslands in Northern China".INTERNATIONAL JOURNAL OF REMOTE SENSING 40.16(2019):6203-6223.
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