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Making sense of cosmic-ray soil moisture measurements and eddy covariance data with regard to crop water use and field water balance

Wang, Enli, Smith, Chris J., Macdonald, Ben C.T., Hunt, James R., Xing, Hongtao, Denmead, O.T., Zeglin, Steve, Zhao, Zhigan, Isaac, Peter
Agricultural water management 2018 v.204 pp. 271-280
arid zones, barley, biogeochemical cycles, carbon, dry environmental conditions, eddy covariance, environmental performance, evapotranspiration, grain crops, greenhouse gas emissions, leaching, models, neutrons, rain, soil ecology, soil water, soil water balance, water uptake, wheat
Changes in soil moisture influence the water availability to crop plants and soil ecological processes like carbon and nutrient cycling, impacting on crop productivity and environmental performance (greenhouse gas emissions, leaching) of agricultural systems. While traditional soil moisture measurements are done using point-based methods, the recent development of the cosmic-ray soil moisture neutron sensor (CRNS) offers the opportunity to measure soil water at the field scale. However, due to its shallow (<300 mm) and variable measurement depth, the relevance of the measurements to crop water use has been questioned. In this paper, we combine point-based soil moisture measurements (soil cores, TDR), areal-based soil moisture and evapotranspiration measurements (CRNS, eddy covariance), and soil-plant systems modelling together to investigate the consistency in measured soil moisture and crop water use with these different methods We also quantify how relevant the CRNS soil moisture measurements are in understanding the water use of cereal crops (wheat and barley). Our results show that crop water uptake from CRNS layers accounted for 50–90% of the total water uptake in dry environments (location, year) with annual rainfall <300 mm, but only 30–50% of the total crop water uptake in wetter environments (locations, years). This demonstrates a higher relevance of CRNS measurements in semi-arid and arid regions where water is a limiting factor for crop growth and other ecological processes. The high temporal resolution of soil moisture data from CRNS can be assimilated with eddy covariance measurements and point measurements in field to better calibrate soil-plant models and to more accurately simulate field water balance.