Regional evapotranspiration (ET) can be enhanced by human activities such as irrigation or reservoir impoundment. Here the potential of using Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage data in water budget calculations to detect human‐induced ET change is investigated over the Haihe River basin of China. Comparison between GRACE‐based monthly ET estimate (2005–2012) and Global Land Data Assimilation System (GLDAS)‐modeled ET indicates that human‐induced ET due to intensive groundwater irrigation from March to May can only be detected by GRACE. GRACE‐based ET (521.7 ± 21.1 mm/yr), considerably higher than GLDAS ET (461.7 ± 29.8 mm/yr), agrees well with existing estimates found in the literature and indicates that human activities contribute to a 12% increase in ET. The double‐peak seasonal pattern of ET (in May and August) as reported in published studies is well reproduced by GRACE‐based ET estimate. This study highlights the unique capability of GRACE in detecting anthropogenic signals over regions with large groundwater consumption.

Abstract:We describe the design, implementation and performance of a novel airborne system, which integrates commercial waveform LiDAR, CCD (Charge-Coupled Device) camera and hyperspectral sensors into a common platform system. CAF's (The Chinese Academy of Forestry) LiCHy (LiDAR, CCD and Hyperspectral) Airborne Observation System is a unique system that permits simultaneous measurements of vegetation vertical structure, horizontal pattern, and foliar spectra from different view angles at very high spatial resolution (~1 m) on a wide range of airborne platforms. The horizontal geo-location accuracy of LiDAR and CCD is about 0.5 m, with LiDAR vertical resolution and accuracy 0.15 m and 0.3 m, respectively. The geo-location accuracy of hyperspectral image is within 2 pixels for nadir view observations and 5-7 pixels for large off-nadir observations of 55˝with multi-angle modular when comparing to LiDAR product. The complementary nature of LiCHy's sensors makes it an effective and comprehensive system for forest inventory, change detection, biodiversity monitoring, carbon accounting and ecosystem service evaluation. The LiCHy system has acquired more than 8000 km 2 of data over typical forests across China. These data are being used to investigate potential LiDAR and optical remote sensing applications in forest management, forest carbon accounting, biodiversity evaluation, and to aid in the development of similar satellite configurations. This paper describes the integration of the LiCHy system, the instrument performance and data processing workflow. We also demonstrate LiCHy's data characteristics, current coverage, and potential vegetation applications.

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