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

Abstract

ABSTRACTWater 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 1.45 g C kg−1 H2O, followed by the temperate meadow steppe and the typical steppe. The desert steppe had the lowest WUE with 0.53 g 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 (R2) 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 0.37 g 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, GPPMOD performed better than GPPBESS 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.