<p><strong>Abstract:</strong>In order to grasp the temporal and spatial variation of runoff and sediment transport and the relationship between runoff and sediment in the Yellow River, the Mann-Kendall test was used to analyze the trend of runoff and sediment load based on the data of runoff and sediment load from 1950 to 2020 at Tongguan station. This paper adopted a method based on moving correlation coefficient to diagnose the variation of watershed runoff and sediment, which was verified with cumulative curve method and regression analysis method. The Pearson III distribution was selected to fit the runoff and sediment distribution before and after the variation, and the combined runoff and sediment distribution was established based on Copula function. The variation characteristics of runoff and sediment at Tongguan station were compared and analyzed to study the wetness-dryness encountering of runoff and sediment at different times. Results show that: (1) The annual runoff at Tongguan station underwent a stepwise decrease until about 1990, and the amount of sediment load continued to decrease after 1983. (2) Taking 1985 as the segmentation point, the mean value of runoff and sediment decreased from 1986 to 2020 compared with that from 1956 to 1985. When the design frequency P&#8804;90%, the runoff and sediment load decreased, while when P>90%, the runoff decreased and sediment load increased. (3) In both time periods, the synchronous frequency of runoff and sediment load wetness-dryness was greater than the asynchronous frequency of wetness-dryness, and the probability of wetness-dryness combination was the smallest, and the frequency of each combination was more uniform after the variation period. The implementation of soil and water conservation measures and the control of water and sediment by large-scale water conservancy projects were the main reasons that led to the change of the wetness-dryness of water and sediment. This work was supported by the National Key Research and Development Program [grant number 2016YFC0500802].</p><p><strong>Keywords</strong>: runoff; sediment load; Copula function; the Yellow River Basin</p>
Translation-based knowledge graph embedding has been one of the most important branches for knowledge representation learning since TransE came out. Although many translation-based approaches have achieved some progress in recent years, the performance was still unsatisfactory. This paper proposes a novel knowledge graph embedding method named TripleRE with two versions. The first version of TripleRE creatively divide the relationship vector into three parts. The second version takes advantage of the concept of residual and achieves better performance. In addition, attempts on using NodePiece to encode entities achieved promising results in reducing the parametric size, and solved the problems of scalability. Experiments show that our approach achieved state-of-the-art performance on the large-scale knowledge graph dataset ogbl-wikikg2, and competitive performance on other datasets.
Abstract. For the rapid development of economy, China has seen more than 200 million kW capacity of hydropower plant installed and more than 55 billion m3 reservoir storage formed since 1950s. As a result, over 25 million resettlers have been wholly or partially affected. To displace and settle so many people is by no means a simple task. However, China has made great progress based on researches, studies, experiences and lessons drawn from the past over 60 years. To provide an overview of water resources and hydropower induced resettlement in China, this paper firstly introduces hydropower-induced resettlement briefly, and then examines the development of policies, laws and regulations. Afterwards, hydropower projects in Sichuan are taken as examples to show how inundation loses of hydropower projects develops. Moreover, some problems are posed and relevant suggestions are proposed in order to relocate those people more comfortably.
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