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Potential of the remotely-derived products in monitoring ecosystem water use efficiency across grasslands in Northern China

机译:遥感产品在监测中国北方草原生态系统用水效率方面的潜力

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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.
机译:用水效率(WUE)已被视为描述碳与水循环之间相互关系的关键参数。鉴于地球土地表面上的草地比例很大,对草地生态系统WUE的时空动态进行定量评估至关重要。通过对中国北方七个草原站点的连续涡动协方差(EC)进行测量,本研究考察了四个典型草地生态系统中沿水可利用量梯度的一次总产值(GPP),蒸散量(ET)和WUE的季节和年际变化。 WUE最高发生在高寒草甸生态系统,水含量为1.45g C kg(-1)H2O,其次是温带草甸草原和典型草原。沙漠草原的WUE最低,为0.53g C kg(-1)H2O。此外,中分辨率成像光谱仪(MODIS)和呼吸地球系统模拟器(BESS)GPP和ET产品的远程推导WUE估计值用于表征这些草原生态系统中基于塔的WUE的可变性。通常,与WUEMOD的变异性相比,WUEBESS在大多数草原站点的WUEEC具有更一致的季节性轨迹。 WUEBESS的WUEBESS的Pearson相关系数(R-2)值最高(约0.83),最低均方根误差(RMSE)在0.21至0.37g C kg( -1)H2O。然而,WUEBESS和WUEMOD的性能在植被生产力较低的沙漠草原地区都缺乏技巧。这些偏远地区的WUE产品,尤其是WUEMOD,往往高估了这些草原类型的年平均WUEEC,除了表现良好的高山草甸地区以外。还研究了基于MODIS和BESS的产品在捕获草地WUE的季节动态方面存在偏差的根本原因。通常,在8天的时间内,GPP(MOD)的性能优于GPP(BESS),而在不同的草地生态系统中,ETBESS的精度比ETMOD的精度更高。我们的分析可能有助于改进基于遥感的GPP和ET产品,以准确监测大面积草地的生态系统WUE模式。

著录项

  • 来源
    《International journal of remote sensing》 |2019年第16期|6203-6223|共21页
  • 作者单位

    Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China|Southwest Univ, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Sch Geog Sci, Chongqing, Peoples R China;

    Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China|Southwest Univ, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Sch Geog Sci, Chongqing, Peoples R China;

    Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China|Southwest Univ, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Sch Geog Sci, Chongqing, Peoples R China;

    Univ Illinois, Dept Nat Resources & Environm Sci, Urbana, IL USA;

    Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China|Southwest Univ, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Sch Geog Sci, Chongqing, Peoples R China;

    Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China|Southwest Univ, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Sch Geog Sci, Chongqing, Peoples R China;

    Southwest Univ, Sch Geog Sci, Minist Nat Resources, Res Base Karst Ecoenvironm Nanchuan Chongqing, Chongqing 400715, Peoples R China|Southwest Univ, Chongqing Engn Res Ctr Remote Sensing Big Data Ap, Sch Geog Sci, Chongqing, Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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