کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6536966 | 158309 | 2016 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Parameterizing ecosystem light use efficiency and water use efficiency to estimate maize gross primary production and evapotranspiration using MODIS EVI
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
علم هواشناسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Quantifying global carbon and water balances requires accurate estimation of gross primary production (GPP) and evapotranspiration (ET), respectively, across space and time. Models that are based on the theory of light use efficiency (LUE) and water use efficiency (WUE) have emerged as efficient methods for predicting GPP and ET, respectively. Currently, LUE and WUE estimates are obtained from biome-specific look-up tables and coarse resolution remote sensing data with large uncertainties. The major objective of this study was to parameterize eddy covariance tower-based ecosystem LUE (ELUEEC), defined as the ratio of tower-based GPP (GPPEC) to photosynthetically active radiation (PAR), and ecosystem WUE (EWUEEC), defined as the ratio of GPPEC to tower-based ET (ETEC), using the Moderate Resolution Imaging Spectroradiometer (MODIS)-derived enhanced vegetation index (EVI) for predicting maize (Zea mays L.) GPP and ET, respectively. Three adjacent AmeriFlux maize sites with different rotations (continuous maize vs. annual rotation of maize and soybean, Glycine max L.) and water management practices (rainfed vs. irrigated) located near Mead, NE, USA were selected. The EVI tracked the seasonal variations of ELUEEC (R2 = 0.83) and EWUEEC (R2 = 0.74) across sites, indicating that EVI can be explicitly used as a measure of ELUEEC and EWUEEC. The predicted GPP (GPPELUE) using the parameterized ELUE model correlated well with GPPEC (slope = 1.0, R2 = 0.83, and RMSE = 2.85 g C mâ2 dâ1) and was significantly improved when compared to widely used models that estimate GPP by integrating EVI and climate variables (Greenness and Radiation, Temperature and Greenness, and Vegetation Index) and the standard MOD17 GPP product. Similarly, the predicted ET (ETEWUE) using the parameterized EWUE correlated well with ETEC (slope = 1.02, R2 = 0.62, and RMSE = 0.83 mm ETâ1) and was significantly improved when compared to the standard MOD16 ET product. Preliminary data demonstrate that ELUE and EWUE can be parameterized using EVI, offering new methods for predicting GPP and ET.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Agricultural and Forest Meteorology - Volume 222, 28 May 2016, Pages 87-97
Journal: Agricultural and Forest Meteorology - Volume 222, 28 May 2016, Pages 87-97
نویسندگان
Pradeep Wagle, Prasanna H. Gowda, Xiangming Xiao, Anup KC,