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Tongren Xu, Shaomin Liu, Shunlin Liang, and Jun Qin

Abstract

Four data assimilation scheme combinations derived from two strategies and two optimization algorithms [the ensemble Kalman filter (EnKF) and the shuffled complex evolution method developed at The University of Arizona (SCE-UA)] are developed based on the Common Land Model (CLM) to improve predictions of water and heat fluxes. The first strategy is constructed through adjusting the soil temperature, while the second strategy adjusts the soil moisture. Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) products are compared with ground-measured surface temperature, and assimilated into the CLM. The relationship equation between the MODIS LST products and CLM surface temperature is taken as the observation operator and the root-mean-square error (RMSE) is applied as the observation error. The assimilation results are validated by measurements from six observation sites located in Germany, the United States, and China. Results indicate that the developed data assimilation schemes can improve estimates of water and heat fluxes. Overall, strategy 2 is superior to strategy 1 when using the same optimization algorithm. The EnKF algorithm performs slightly better than the SCE-UA algorithm when using the same strategy. Strategy 2 combined with the EnKF algorithm performs best for water and heat fluxes, and the reductions in the RMSE are found to be 24.0 and 15.2 W m−2 for sensible and latent heat fluxes, respectively. The joint assimilation of the MODIS LST and soil moisture observations can produce better results for strategy 2 with the SCE-UA. Since preprocessing model parameters are used in this study, the uncertainties in the model parameters may have resulted in suboptimal assimilation results. Therefore, model calibrations should be conducted in the future.

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Ziwei Xu, Yanfei Ma, Shaomin Liu, Wenjiao Shi, and Jiemin Wang

Abstract

A unique and intensive flux observation matrix was established during May to September of 2012 in an oasis–desert area located in the middle reaches of the Heihe River basin, China. The flux observation matrix included 22 eddy covariance systems belonging to the first thematic experiment of the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project. The energy balance closure ratio (EBR) was assessed and possible mechanisms were investigated using remote sensing data. The results showed that 1) the EBR was in the range of 0.78–1.04 at all sites with an average EBR of 0.92, and 2) the calculated daily EBR exhibited better performance than the 30-min averages. 3) The heat storage cannot be ignored during the crop growing season. An improvement of approximately 6% in the total closure was found after considering the heat storage terms (canopy and photosynthesis storage) in the energy budget at the maize surface, and the canopy and photosynthesis showed approximately equal contributions of 3% for each storage term. The results also showed that 4) the land heterogeneous surface had a significant effect on the EBR. The EBR decreased with land surface heterogeneity increasing (taking the standard deviation of the surface temperature in the eddy covariance system source area as an index). The EBR also decreased when irrigation occurred and increased after irrigation was completed. The advection or secondary circulation broke the closed system of the energy balance given the phenomenon of EBR increasing when the advection or secondary circulation occurred.

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Tongren Xu, Sayed M. Bateni, Steven A. Margulis, Lisheng Song, Shaomin Liu, and Ziwei Xu

Abstract

The primary objective of this study is to assess the accuracy of the two-source variational data assimilation (TVDA) system for partitioning evapotranspiration (ET) into soil evaporation (ETS) and canopy transpiration (ETC). Its secondary aim is to compare performance of the TVDA system with the commonly used two-source surface energy balance (TSEB) method. A combination of eddy-covariance-based ET observations and stable-isotope-based measurements of the ratio of evaporation and transpiration to total evapotranspiration (ETS/ET and ETC/ET) over an irrigated cropland site (the so-called Daman site) in the middle reach of the Heihe River basin (northwestern China) was used to investigate these objectives. The results indicate that the TVDA method predicts ETS and ETC more accurately than TSEB. Root-mean-square errors (RMSEs) of midday (1300–1500 LT) averaged soil and canopy latent heat flux (LES and LEC) estimates from TVDA are 23.1 and 133.0 W m−2, respectively. Corresponding RMSE values from TSEB are 41.9 and 156.0 W m−2. Compared to TSEB, the TVDA method takes advantage of all of the information in land surface temperature observations in the estimation period by leveraging a dynamic model (the heat diffusion equation) and thus can generate more accurate LES and LEC estimates.

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Kun Yang, Toshio Koike, Hirohiko Ishikawa, Joon Kim, Xin Li, Huizhi Liu, Shaomin Liu, Yaoming Ma, and Jieming Wang

Abstract

Parameterization of turbulent flux from bare-soil and undercanopy surfaces is imperative for modeling land–atmosphere interactions in arid and semiarid regions, where flux from the ground is dominant or comparable to canopy-sourced flux. This paper presents the major characteristics of turbulent flux transfers over seven bare-soil surfaces. These sites are located in arid, semiarid, and semihumid regions in Asia and represent a variety of conditions for aerodynamic roughness length (z 0 m; from <1 to 10 mm) and sensible heat flux (from −50 to 400 W m−2). For each site, parameter kB −1 [=ln(z 0 m/z 0 h), where z 0 h is the thermal roughness length] exhibits clear diurnal variations with higher values during the day and lower values at night. Mean values of z 0 h for the individual sites do not change significantly with z 0 m, resulting in kB −1 increasing with z 0 m, and thus the momentum transfer coefficient increases faster than the heat transfer coefficient with z 0 m. The term kB −1 often becomes negative at night for relatively smooth surfaces (z 0 m ∼ 1 mm), indicating that the widely accepted excess resistance for heat transfer can be negative, which cannot be explained by current theories for aerodynamically rough surfaces. Last, several kB −1 schemes are evaluated using the same datasets. The results indicate that a scheme that can reproduce the diurnal variation of kB −1 generally performs better than schemes that cannot.

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Xin Li, Guodong Cheng, Shaomin Liu, Qing Xiao, Mingguo Ma, Rui Jin, Tao Che, Qinhuo Liu, Weizhen Wang, Yuan Qi, Jianguang Wen, Hongyi Li, Gaofeng Zhu, Jianwen Guo, Youhua Ran, Shuoguo Wang, Zhongli Zhu, Jian Zhou, Xiaoli Hu, and Ziwei Xu

A major research plan entitled “Integrated research on the ecohydrological process of the Heihe River Basin” was launched by the National Natural Science Foundation of China in 2010. One of the key aims of this research plan is to establish a research platform that integrates observation, data management, and model simulation to foster twenty-first-century watershed science in China. Based on the diverse needs of interdisciplinary studies within this research plan, a program called the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) was implemented. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system, and to enhance the applicability of remote sensing in integrated ecohydrological studies and water resource management at the basin scale. This paper introduces the background, scientific objectives, and experimental design of HiWATER. The instrumental setting and airborne mission plans are also outlined. The highlights are the use of a flux observing matrix and an eco-hydrological wireless sensor network to capture multiscale heterogeneities and to address complex problems, such as heterogeneity, scaling, uncertainty, and closing water cycle at the watershed scale. HiWATER was formally initialized in May 2012 and will last four years until 2015. Data will be made available to the scientific community via the Environmental and Ecological Science Data Center for West China. International scientists are welcome to participate in the field campaign and use the data in their analyses.

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