Evaluation of Water Use Efficiency Derived from MODIS Products against Eddy Variance Measurements in China

Abstract

Water use efficiency (WUE) is a useful indicator to illustrate the interaction of carbon and water cycles in terrestrial ecosystems. MODIS gross primary production (GPP) and evapotranspiration (ET) products have been used to analyze the spatial and temporal patterns of WUE and their relationships with environmental factors at regional and global scales. Although MODIS GPP and ET products have been evaluated using eddy covariance flux measurements, the accuracy of WUE estimated from MODIS products has not been well quantified. In this paper, we evaluated WUE estimated from MODIS GPP and ET products against eddy covariance measurements of GPP and ET during 2003-2008 at eight sites of the Chinese flux observation and research network (ChinaFLUX) and conducted sensitivity analysis to investigate the possible key contributors to the bias of MODIS products. Results show that MODIS products underestimate eight-day water use efficiency in four forest ecosystems and one cropland ecosystem with the bias from −0.36-−2.28 g·C·kg H2O.Mean annual WUE was underestimated by 14%-54% at four forest sites, 45% at one OPEN ACCESSRemote Sens. 2015, 7 11184 cropland site and 7% at an alpine grassland site, but overestimated by 66% and 9% at a temperate grassland site and an alpine meadow site, respectively. The underestimation of WUE by MODIS data results from underestimated GPP and overestimated ET at four forest sites, while MODIS WUE values are significantly overvalued mainly due to underestimated ET in the three grassland ecosystems. The maximum light use efficiency and fraction of photosynthetically-active radiation (FPAR) were the two most sensitive factors to the estimation of WUE derived from the MODIS GPP and ET algorithms. The error in meteorological data partly caused the overestimation of ET and accordingly underestimation in WUE in subtropical and tropical forests. The bias of MODIS-produced WUE was also derived from the uncertainties in eddy flux data due to gap-filling processes and unbalanced surface energy issue. Their contributions to the uncertainty in estimated WUE at both eight-day and annual scales still need to be further quantified.

Response of Ecosystem Water Use Efficiency to Drought over China during 1982–2015: Spatiotemporal Variability and Resilience

“…Water use efficiency (WUE) is a widely accepted parameter in describing carbon-water flux coupling between terrestrial ecosystems and the atmosphere and linking biological (e.g., vegetation transpiration and photosynthesis) and physical (e.g., soil evaporation) processes [12,13]. It reflects how much water is consumed by an ecosystem while it obtains carbon unit, which can be quantified as the ratio of carbon uptake (measured by GPP-gross primary productivity, NPP-net primary productivity or NEP-net ecosystem productivity) and water consumption (measured by ET-evapotranspiration or precipitation) [14][15][16]. Many previous studies have investigated the spatiotemporal changes of WUE.…”

Remotely Monitoring Ecosystem Water Use Efficiency of Grassland and Cropland in China’s Arid and Semi-Arid Regions with MODIS Data

“…Meanwhile, owing to a lack of effective distinction of C 3 and C 4 species, the MODIS GPP product contained large uncertainties in C 4 crops, such as maize, thereby propagating to WUE estimation. Zhang et al [59] indicated that the bias of MODIS-based WUE was partly derived from the uncertainties in eddy flux data because of gap-filling processes and an unbalanced surface energy issue. Jiang and Ryu [60] The mismatch between the actual flux tower footprint with a 1 km 2 approximation used in the comparisons to MODIS GPP and ET products is also an issue.…”

“…Additionally, remote sensing data and flux data have different observation frequencies, so there are unavoidable errors in estimating daily/eight-day GPP and ET from both transient remote sensing data and half-hourly eddy flux data [64]. Zhang et al [59] revealed that true ET values were usually underestimated by the eddy covariance measurements to a certain degree. Essentially, the GPP values were partitioned from EC-based NEE data relying on empirical models, which also included plenty of uncertainties [31,65].…”

Effects of Climate Factors and Human Activities on the Ecosystem Water Use Efficiency throughout Northern China

“…To verify the effectiveness of the WUE estimated in the TNR from the GLASS products, the WUE calculated by the GLASS GPP and ET was compared with the WUE calculated by the MODIS GPP and ET, which are widely used remote sensing products [10,11,52]. The annual GPP (MOD17A3) and ET (MOD16A3) data with a 1 km resolution from 2000 to 2014 were produced by the Numerical Terra Dynamic Simulation Group (http://www.ntsg.umt.edu) and are freely available.…”