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

Abstract

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.

The uncertainty analysis of the MODIS GPP product in global maize croplands

“…Asian site of CN_DM is located in typical irrigated farmland in Daman village, Gansu Province, Northwest China, with a primary crop of maize (Tang et al, 2017). The precipitation in this site is about 100-250 mm every year with continental arid climate: dry and hot in summer and cold in winter.…”

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.…”

On the use of alternative water use efficiency parameters in dryland ecosystems: a review

“…Although data quality and processing present issues with EC flux data, this method has been widely applied to estimate footprint-scale WUE for various plant function types (PFTs). Model and satellite remote sensing have also been applied to estimate ecosystem WUE using various process-based models (Huang et al 2015;Sun et al 2015;Chen et al 2017) and satellite-based biophysical parameters, such as MODIS GPP and ET products (Tang et al 2017). Sometimes, satellite-derived parameters are integrated into models to enhance accuracy (Liu et al 2015).…”

“…Water use efficiency (WUE) is a measure of the trade-off between carbon gain and water loss in plants or terrestrial ecosystems (Liu et al 2015), both of which are related to photosynthesis and evapotranspiration processes, respectively. Hence, as an integrative measure of carbon and water processes, WUE has been a focus of dryland studies at various spatial scales from site to regional or continental (Emmerich 2007;Niu et al 2011;Tang et al 2017).…”