Spatial and temporal variations of tap water 17O-excess in China

Compared to tap water δ2H and δ18O, tap water 17O-excess preserves additional information about source water dynamics. In this study, we provide the first report of 17O-excess variations of tap water across China (652 samples). Annual 17O-excess of tap waters at the national scale did not show obvious spatial pattern, and was almost unaffected by local environmental factors except in the Qinghai-Tibet Plateau region with a strong latitudinal trend. The mean 17O-excess values in different seasons were not significantly different. The isotopic compositions of most of the tap waters at the annual and seasonal scale were likely influenced by the equilibrium fractionation effect (δ′18O-δ′17O slope ranged from 0.5277 to 0.5301), except for the northwest region in the summer (slope = 0.5264) influenced by kinetic fractionation associated with re-evaporation effect. Based on the information of tap water source distribution, site aridity index and the known precipitation δ18O values, a subset of the tap water can be considered as precipitation proxy. Different from the obvious spatial characteristics of precipitation δ18O, precipitation 17O-excess did not show a clear spatial pattern. But it revealed much detailed precipitation formation mechanisms related to different climate regions and geographical conditions. The lower 17O-excess values of the precipitation-sourced tap waters were caused by kinetic fractionation associated with supersaturation process in snow or glacier formation and re-evaporation effect in some arid regions. The higher 17O-excess values of the precipitation-sourced tap waters in the inland were caused by continental moisture recycling, while likely caused by multiple factors in the southeast coastal region including short transport from ocean source and the humid local environment. Overall, this study provides a unique tap water 17O-excess dataset across China, and probes the precipitation formation mechanisms using tap waters

Stable Isotope Composition of River Waters across the World

Stable isotopes of O and H in water are meaningful indicators of hydrological and ecological patterns and processes. The Global Network of Isotopes in Precipitation (GNIP) and the Global Network of Isotopes in Rivers (GNIR) are the two most important global databases of isotopes in precipitation and rivers. While the data of GNIP is almost globally distributed, GNIR has an incomplete spatial coverage, which hinders the utilization of river isotopes to study global hydrological cycle. To fill this knowledge gap, this study supplements GNIR and provides a river isotope database with global-coverage by the meta-analysis method, i.e., collecting 17015 additional data points from 215 published articles. Based on the newly compiled database, we find that (1) the relationship between δ18O and δ2H in river waters exhibits an asymmetric imbricate feature, and bifurcation can be observed in Africa and North America, indicating the effect of evaporation on isotopes; (2) multiple regression analysis with geographical factors indicates that spatial patterns of river isotopes are quite different across regions; (3) multiple regression with geographical and meteorological factors can well predict the river isotopes, which provides regional regression models with r2 of 0.50 to 0.89, and the best predictors in different regions are different. This work presents a global map of river isotopes and establishes a benchmark for further research on isotopes in rivers

VAST: A Vision-Audio-Subtitle-Text Omni-Modality Foundation Model and Dataset

Vision and text have been fully explored in contemporary video-text foundational models, while other modalities such as audio and subtitles in videos have not received sufficient attention. In this paper, we resort to establish connections between multi-modality video tracks, including Vision, Audio, and Subtitle, and Text by exploring an automatically generated large-scale omni-modality video caption dataset called VAST-27M. Specifically, we first collect 27 million open-domain video clips and separately train a vision and an audio captioner to generate vision and audio captions. Then, we employ an off-the-shelf Large Language Model (LLM) to integrate the generated captions, together with subtitles and instructional prompts into omni-modality captions. Based on the proposed VAST-27M dataset, we train an omni-modality video-text foundational model named VAST, which can perceive and process vision, audio, and subtitle modalities from video, and better support various tasks including vision-text, audio-text, and multi-modal video-text tasks (retrieval, captioning and QA). Extensive experiments have been conducted to demonstrate the effectiveness of our proposed VAST-27M corpus and VAST foundation model. VAST achieves 22 new state-of-the-art results on various cross-modality benchmarks. Code, model and dataset will be released at https://github.com/TXH-mercury/VAST.Comment: 23 pages, 5 figure

Divergence of stable isotopes in tap water across China

Stable isotopes in water (e.g., δ2H and δ18O) are important indicators of hydrological and ecological patterns and processes. Tap water can reflect integrated features of regional hydrological processes and human activities. China is a large country with significant meteorological and geographical variations. This report presents the first national-scale survey of Stable Isotopes in Tap Water (SITW) across China. 780 tap water samples have been collected from 95 cities across China from December 2014 to December 2015. (1) Results yielded the Tap Water Line in China is δ2H = 7.72 δ18O + 6.57 (r2 = 0.95). (2) SITW spatial distribution presents typical "continental effect". (3) SITW seasonal variations indicate clearly regional patterns but no trends at the national level. (4) SITW can be correlated in some parts with geographic or meteorological factors. This work presents the first SITW map in China, which sets up a benchmark for further stable isotopes research across China. This is a critical step toward monitoring and investigating water resources in climate-sensitive regions, so the human-hydrological system. These findings could be used in the future to establish water management strategies at a national or regional scale

Analysis of face stability for shallow shield tunnels in sand

The stability of the tunnel face is the key problem in shield tunnel construction. This paper focuses on the face stability of a shallow tunnel in sand. Numerical simulation and theoretical analysis are combined to study the limit support pressure and failure zone. Firstly, numerical simulation is employed to study the collapse of the tunnel face, obtaining the limit support pressure and collapse zone. A new failure model suitable for shallow tunnels is constructed based on these numerical simulations. Then, an analytic solution for the limit support pressure is derived using limit analysis upper bound theory. The accuracy and applicability of this proposed model are verified by comparing it with numerical results and classical analytical models. Through this research, it is found that the proposed model provides a more accurate description of situations where soil arches cannot be formed for shallow tunnels in sand, leading to higher accuracy in calculating the limit support pressure. The influence of various factors on stability of the tunnel face is analyzed, revealing mechanisms of tunnel face collapse