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In general, there are no long-term meteorological or hydrological data available for karst river basins. The lack of rainfall data is a great challenge that hinders the development of hydrological models. Quantitative precipitation estimates (QPEs) based on weather satellites offer a potential method by which rainfall data in karst areas could be obtained. Furthermore, coupling QPEs with a distributed hydrological model has the potential to improve the precision of flood predictions in large karst watersheds. Estimating precipitation from remotely sensed information using an artificial neural network-cloud classification system (PERSIANN-CCS) is a type of QPE technology based on satellites that has achieved broad research results worldwide. However, only a few studies on PERSIANN-CCS QPEs have occurred in large karst basins, and the accuracy is generally poor in terms of practical applications. This paper studied the feasibility of coupling a fully physically based distributed hydrological model, i.e., the Liuxihe model, with PERSIANN-CCS QPEs for predicting floods in a large river basin, i.e., the Liujiang karst river basin, which has a watershed area of 58 270 km-2, in southern China. The model structure and function require further refinement to suit the karst basins. For instance, the sub-basins in this paper are divided into many karst hydrology response units (KHRUs) to ensure that the model structure is adequately refined for karst areas. In addition, the convergence of the underground runoff calculation method within the original Liuxihe model is changed to suit the karst water-bearing media, and the Muskingum routing method is used in the model to calculate the underground runoff in this study. Additionally, the epikarst zone, as a distinctive structure of the KHRU, is carefully considered in the model. The result of the QPEs shows that compared with the observed precipitation measured by a rain gauge, the distribution of precipitation predicted by the PERSIANN-CCS QPEs was very similar. However, the quantity of precipitation predicted by the PERSIANN-CCS QPEs was smaller. A post-processing method is proposed to revise the products of the PERSIANN-CCS QPEs. The karst flood simulation results show that coupling the post-processed PERSIANN-CCS QPEs with the Liuxihe model has a better performance relative to the result based on the initial PERSIANN-CCS QPEs. Moreover, the performance of the coupled model largely improves with parameter re-optimization via the post-processed PERSIANN-CCS QPEs. The average values of the six evaluation indices change as follows: the Nash-Sutcliffe coefficient increases by 14 %, the correlation coefficient increases by 15 %, the process relative error decreases by 8 %, the peak flow relative error decreases by 18 %, the water balance coefficient increases by 8 %, and the peak flow time error displays a 5 h decrease. Among these parameters, the peak flow relative error shows the greatest improvement; thus, these parameters are of page1506 the greatest concern for flood prediction. The rational flood simulation results from the coupled model provide a great practical application prospect for flood prediction in large karst river basins.

The freshwater discharge from melting ice sheets in the deglaciation or glaciation is prone to anomalies in ocean-atmosphere transport between different latitudes, which can lead to a series of abrupt millennial-scale climate events, either obvious or not, such as the Younger Dryas (YD) events and YD-like events. Marine Isotope Stage 11c (MIS 11c) serves as one of the best references for the current Holocene, and the studies of possible YD-like events and their triggering mechanisms during Holocene are conducive to the understanding of the occurrence pattern of extreme climate events. In this paper, the results of the study on the J33 δ18O sequence records of stalagmites in Jinfo Cave, Chongqing, are shown: (1) Stalagmites in the Asian monsoon climate zone reveal a millennial-scale weak monsoon event that occurred around 410 ka BP prior to the Glacial Maximum of MIS 11 interglacial period. (2) Both the 410 ka weak monsoon event and the YD event occurred during the gradual strengthening of the monsoon and ascending branch of summer insolation in the Northern Hemisphere prior to the Glacial Maximum of interglacial period. This was also a time when Atlantic Meridional Overturning Circulation (AMOC) disturbance occurred. The duration, internal structure, and pattern of the events were similar, with differences in the change magnitude and ice volume conditions. (3) The weak monsoon event that occurred in 410 ka BP was primarily influenced by the combined effects of insolation and AMOC. This event was characterized by a sustained warming process that accelerated the melting of the Greenland ice sheet, leading to the destabilization of this ice sheet. The continuous flowing of freshwater into the North Atlantic resulted in a short-lived AMOC oscillation. The weakening of the AMOC resulted in a cold anomaly over the North Atlantic. As a result of atmospheric telecorrelation, the weaker AMOC led to a weaker Asian Summer Monsoon (ASM). [ABSTRACT FROM AUTHOR]

There is limited knowledge about microbial communities and their ecological functions in karst caves with high CO2 concentrations. Here, we studied the microbial community compositions and functions in Shuiming Cave ("SMC", CO2 concentration 3 303 ppm) and Xueyu Cave ("XYC", CO2 concentration 8 753 ppm) using Illumina MiSeq high-throughput sequencing in combination with BIOLOG test. The results showed that Proteobacteria, Actinobacteria and Bacteroidetes were dominant phyla in these two caves, and Thaumarchaeota was the most abundant in the rock wall samples of SMC. The microbial diversity in the water samples decreased with increasing HCO3− concentration, and it was higher in XYC than that in SMC. The microbial community structures in the sediment and rock wall samples were quite different between the two caves. High concentrations of CO2 can reduce the microbial diversity on the rock walls in karst caves, probably through changing microbial preference for different types of carbon sources and decreasing the microbial utilization rate of carbon sources. These results expanded our understanding of microbial community and its response to environments in karst caves with high CO2. [ABSTRACT FROM AUTHOR]