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In this paper, we developed algorithms to estimate hourly evapotranspiration (ET) during a day under clear and cloud cover conditions using data from the Chinese FengYun-2D (FY-2D) geostationary meteorological satellite over the Yellow River source area. For cloud-free conditions, the Surface Energy Balance System (SEBS) methodology and FY-2D data were used to derive the hourly ET. For cloudy cover conditions, the transmission coefficient was calculated using top of atmosphere (TOA) reflectance and the attenuation of solar radiation in the atmosphere. Heat fluxes and ET under different atmospheric and cloud cover conditions were then calculated. Compared with ground-based measurements from eddy covariance systems deployed in the Maqu Climate and Environment Comprehensive Observation Station, the average relative error was 15.20% during the experimental period. The proposed methodology can rely exclusively on remote sensing data in the absence of ancillary ground observations. Thus, the proposed method can potentially estimate the regional surface energy budget. [ABSTRACT FROM AUTHOR]

Variation of streamflow and sediment load in the Yellow River basin has received considerable attention due to its drastic reduction during the past several decades. This paper presents a detailed investigation on the changes of streamflow and sediment load from 1952 to 2011 using monthly observations at four gauging stations along the Yellow River. The results show significant decreasing trends for both streamflow and sediment load at all four gauging stations over the past 60 years. The wavelet transform demonstrated discontinuous periodicities from 1969 to 1973 and after 1986 due to the construction of large reservoirs and implementation of numerous soil and water conservations practices. The sediment rating curves with the power-law function was applied to investigate the relationship between discharge and sediment load. The results indicate distinct variations of the relationship between streamflow and sediment and implied significant hydro-morphological changes within different periods. The reducing sediment supply from the source region and the increased erosive power of the river are detected at Lanzhou station, while the decrease of the transport capacity at Toudaoguai is caused by severe siltation. Significant changes in the relationship between streamflow and sediment load are found at Huayuankou and Gaocun stations, which are largely induced by evident sediment income and trapping effects of large reservoirs. It is estimated that numerous reservoirs have strongly altered the regime and magnitude of streamflow and trapped large amount of sediment, leading to severe siltation and evident reduction of their total volumes. A decrease in precipitation, incoming water from the upper reaches, soil and water conservation measures as well as water consumption contribute most to the significant reduction of streamflow. The decrease of sediment load mainly resulted from various soil and water conservation measures and trapping in reservoirs from 1986 to 2011. [ABSTRACT FROM AUTHOR]

Abstract: Addressing the transmission and storage problems of aurora images that Arctic Yellow River Station of China faces, the present paper proposes a two-stage lossless compression algorithm based on weighted motion compensation and context-based modeling. As no specialized compression algorithms for aurora images are available, proposing a new algorithm that offers a satisfactory lossless compression performance for aurora images is necessary. The proposed algorithm utilizes the weighted motion compensation to obtain the motion vector based on the unusual movement characteristics of aurora images. Subsequently, the context-based model is combined with the motion vector. Experimental results indicated that the proposed algorithm outperformed the state-of-the-art lossless compression methods. [Copyright &y& Elsevier]