Nonstationary frequency analysis and uncertainty quantification for extreme low lake levels in a large river-lake-catchment system.

Extreme hydrological events have become increasingly frequent on a global scale. The middle Yangtze River also faces a substantial challenge in dealing with extreme flooding and drought. However, the long-term characteristics of the extreme hydrological regime have not yet been adequately recognized. Moreover, there is uncertainty in the extreme value estimation, and this uncertainty needs to be distinguished and quantified. In this study, we investigated the nonstationary frequency characteristics of extreme low lake levels (ELLLs), taking the Poyang Lake as an example. Daily lake levels from 1960 to 2022 were utilized to estimate the return level using the generalized Pareto distribution (GPD). The uncertainty from three sources, i.e., the parameter estimator, threshold selection, and covariate, was quantified via variance decomposition. The results indicate that (1) the parameter estimator is the predominant source of uncertainty, with a contribution rate of approximately 87 %. The total uncertainty of the covariate, threshold, and interaction term is only 13 %. (2) Two indexes, namely the annual minimum water level (WLmin) and the days with peak over the 90 % threshold per year (DPOT90), decreased (0.01-0.03 m/year) and increased (0.17-1.39 days/year), respectively, indicating a progressively severe drought trend for Poyang Lake. (3) The return level with return period of 5 to 100 years significantly decreased after the early 21st century. A large spatial heterogeneity was identified for the variation in the return level, and the change rate of the return level with a 100-year return period ranged from 5 % to 40 % for the whole lake. (4) The ELLLs had a stronger correlation with the catchment discharge than with the Yangtze River discharge and the large-scale atmospheric circulation indices. This study provides a methodology with reduced uncertainty for nonstationary frequency analysis (NFA) of ELLLs exemplified in large river-lake systems.

Multiple latent variables but functionally dependent output mappings underlying the recognition of own- and other-race faces for Chinese individuals: Evidence from state-trace analysis.

To explore the number of latent variables underlying recognition of own- and other-race faces for Chinese observers, we conducted a study-recognition task where orientation, stimuli type, and duration were manipulated in the study phase and applied state trace analysis as a statistic method. Results showed that each state trace plot on each pair of stimuli types matched a single monotonic curve when stimuli type was set to state factor, but separate curves between face and non-face showed up when the state factor was orientation. The results implied that at least two latent variables affected recognition performance in the inversion paradigm. Besides, the unidimensional structure between own- and other-race faces regardless of the state factor suggested that Chinese participants used the same recognition mechanism for unfamiliar own- and other-race faces in the inversion paradigm.

[Zonation on non-point source pollution risk in the lower reaches of Zijiang River based on the "source-sink" theory]. / 基于"源-汇"理论的资江下游地区非点源污染风险区划.

Non-point source pollution risk assessment and zonation research are of great significance for the eco-environmental protection and optimization of land use structure. We identified the "source" and "sink" landscape using the "source-sink" landscape pattern theory based on the two phases of land use data in the lower reaches of Zijiang River in 2010 and 2018. We comprehensively considered the non-point source pollution occurrence and migration factors, and used location-weighted landscape contrast index (LCI) and non-point source pollution load index (NPPRI) to analyze non-point source pollution risk spatio-temporal characteristics in the study area. Zonation on non-point source pollution in the lower reaches of Zijiang River was studied by identifying the key factors of non-point source pollution risk. The results showed that the overall risk of non-point source pollution was relatively low. The sub-basin with "sink" landscape was the main type, accounting for 61.2%. Non-point source pollution risk was low in the southwest and was high along the banks of Zhixi River, Taohua River and main stream of Zijiang River, as well as plain in the northeast of the lower Zijiang River. The risk of non-point source pollution from 2010 to 2018 showed an increasing trend. The changes in landscape pattern, especially the expansion of rural settlement, arable land and the shrinkage of forest land had positive and negative responses to the risk of non-point source pollution, respectively. LCI, slope, and distance were the key factors affecting the change of the risk index of non-point source pollution. The lower reaches of the Zijiang River could be divided into four control regions: pollution treatment area near river, low slope pollution control area, ecological restoration-risk prevention and control area, and ecological priority protection area.