Analyzing the encounter frequency of high–low runoff and sediment yield is important for the appropriate dispatching of runoff–sediment resources, as well as river regulation. However, there have been no reports on the utilization of the pair-copula function in analyzing the runoff–sediment characteristics from a probabilistic perspective and conducting probability control on the runoff–sediment yields of different hydrologic stations. This paper builds marginal distribution functions on the basis of kernel distribution theory. In addition, this paper builds the joint distribution functions through pair-copula functions in order to analyze the encounter probability and the compensation characteristics of high–low runoff and sediment at different stations on the Weihe River in China, as well as the origins of runoff–sediment, to conduct probability control of river runoff–sediment resource allocation. The results show that, in different periods, the synchronous probability of high–low runoff of the Weihe River’s Xianyang and Huaxian Stations, and the Jinghe River’s Zhangjiashan Station differ, while that of high–low sediment at the three stations changes little—remaining at around 54%. Therefore, the sediment and runoff of the Weihe River apparently have different origins. In years of high and low runoff, if the runoffs of the Xianyang and Zhangjiashan Stations can be kept within a certain range, then the runoff of the Huaxian Station will be in a particular range, at a certain probability. Sediment at the Huaxian Station can be controlled, in a similar way. These results are of great significance for the water and sediment management department of the Weihe river, in order to reasonably allocate water and sediment resources.
There is a close relationship between land use/cover change and regional development in new urban areas. In this paper, based on the land-use data before (2010, 2013) and after (2015, 2018) the establishment of Xixian New Area and the economic development data of the corresponding period, with the help of indexes such as the land use transfer matrix, relative change rate/net change rate and the composite index of land use degree, the temporal and spatial differences of land-use change and land use degree in the ten years before and after the establishment of Xixian New Area were analyzed, and the driving factors of land-use change and their relationship with the level of social and economic development were discussed. The results indicate that cultivated land and construction land are the main land-use types in Xixian New Area in the whole studying period. From 2010 to 2018, the area of cultivated land and forest land in the region decreased over time, but the construction land area continuously increased dramatically (increased by 36.5% from 2010 to 2018) and the land-use change corresponds basically to the construction and development process of the New Area. In the spatial transfer of land use, the transformation of cultivated land to construction land was the most evident, and the urbanization construction in the New Area occupied the most cultivated land. The composite index of land use degree in the New Area was generally high and increased with time. Geographical location and policy guidance are the main reasons for the spatial difference of land use degree. The land use benefits in the New Area increased significantly, and the land use degree was positively correlated with the level of regional, social and economic development. The main driving factor of land-use change was human activities guided by policy.
Rapid identification of inrush water sources is vital for the safe operation of a coal mine. Hydrogeochemical (fuzzy comprehensive evaluation method and cluster analysis method) and isotope analyses are applied to identify the inrush water sources of the Mindong No. 1 mine, which is located in northeast Inner Mongolia, China. The clustering analysis and isotope analysis results show that the inrush water sources are from aquifer 1 (A1), aquifer 2 (A2) and Yimin river. However, fuzzy comprehensive evaluation shows that the inrush water sources are from A2, aquifer 3 (A3) and Yimin river. Considering the hydrogeological conditions of the study area, it is concluded that the inrush water sources are A1, A2 and Yimin river, with mixing ratios of 30.8%, 60.6% and 8.6%, respectively. The application of multiple methods makes the conclusion more reliable. Additionally, this study improves the speed and effectiveness of the identification of inrush water sources in coal mines and provides a practical reference for research related to mine water inrush to ensure the safe operation of coal mines.
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