Remotely Monitoring Ecosystem Water Use Efficiency of Grassland and Cropland in China's Arid and Semi-Arid Regions with MODIS Data
Scarce water resources are available in the arid and semi-arid areas of Northwest China, where significant water-related challenges will be faced in the coming decades. Quantitative evaluations of the spatio-temporal dynamics in ecosystem water use efficiency (WUE), as well as the underlying environmental controls, are crucial for predicting future climate change impacts on ecosystem carbon-water interactions and agricultural production. However, these questions remain poorly understood in this
... typical region. By means of continuous eddy covariance (EC) measurements and time-series MODIS data, this study revealed the distinct seasonal cycles in gross primary productivity (GPP), evapotranspiration (ET), and WUE for both grassland and cropland ecosystems, and the dominant climate factors performed jointly by temperature and precipitation. The MODIS WUE estimates from GPP and ET products can capture the broad trend in WUE variability of grassland, but with large biases for maize cropland, which was mainly ascribed to large uncertainties resulting from both GPP and ET algorithms. Given the excellent biophysical performance of the MODIS-derived enhanced vegetation index (EVI), a new greenness model (GR) was proposed to track the eight-day changes in ecosystem WUE. Seasonal variations and the scatterplots between EC-based WUE and the estimates from time-series EVI data (WUE GR ) also certified its prediction accuracy with R 2 and RMSE of both grassland and cropland ecosystems over 0.90 and less than 0.30 g kg −1 , respectively. The application of the GR model to regional scales in the near future will provide accurate WUE information to support water resource management in dry regions around the world. Remote Sens. 2017, 9, 616 2 of 17 With the help of continuous observations of ecosystems-level carbon and water exchanges between the Earth's biosphere and the atmosphere based on the eddy covariance (EC) technique, site-level evaluation or comparisons among multiple sites has been widely used to assess the WUE variability and its relationship with weather conditions across different time and space scales [8, 9] . Previous studies have found that seasonal dynamics in WUE varied with vegetation types and climate variables, including radiation, temperature and precipitation [10, 11] . Using flux measurements from four grasslands  and temperate deciduous forests  in northern mid-and high latitudes, WUE was found to reach its peak during the summertime, whereas Reichstein et al.  revealed WUE at three Mediterranean forests with the maximum in winter and the minimum in summer, and attributed it to the effects of drought during the growth period. Similar phenomena were also exhibited in northern subtropical forests [10, 15] . Meanwhile, contrasting responses of GPP and ET to climate changes will yield significant consequences to the WUE variability under water-limited , light-limited , and thermal-limited environments [11, 18] . Nevertheless, the knowledge about seasonal cycles of WUE, as well as the potential environmental influences remains insufficient for a variety of terrestrial ecosystems because these analyses are usually rely on spatially sparse site observations. Recently, the remote sensing approaches together with process-based ecosystem models have been developed to evaluate seasonal or long-term trends of WUE through GPP and ET estimates at regional to global scales [5, 19, 20] . However, large uncertainties in both components, thereby propagating to WUE, and the inconsistency of modeled and measured WUE on short and long timescales constrained its application  . It remains a challenge to accurately monitor seasonal variations in WUE over large areas for water resource management. In the northwestern arid and semi-arid regions of China, natural grassland and irrigated agriculture are the main ecosystem types which play an important role in the regional carbon balance, hydrological patterns, and food supply [22, 23] . However, few studies addressed the interactions between carbon and water cycles in this water-limited area owing to lack of eddy covariance measurements. The overall aim of this study was (1) to examine seasonal variations in GPP, ET and ecosystem WUE, as well as the dominant environmental controls at the two grassland and cropland flux sites; (2) to evaluate the performance of MODIS WUE estimates from GPP and ET products in capturing the EC-based WUE variability and the error sources; and (3) to propose an alternative method for improving the estimation accuracy directly depending on remotely-sensed data.