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

SHAFTS (v2022.3): a deep-learning-based Python package for simultaneous extraction of building height and footprint from sentinel imagery

Abstract. Building height and footprint are two fundamental urban morphological features required by urban climate modelling. Although some statistical methods have been proposed to estimate average building height and footprint from publicly available satellite imagery, they often involve tedious feature engineering which makes it hard to achieve efficient knowledge discovery in a changing urban environment with ever-increasing earth observations. In this work, we develop a deep-learning-based (DL) Python package – SHAFTS (Simultaneous building Height And FootprinT extraction from Sentinel imagery) to extract such information. Multi-task deep-learning (MTDL) models are proposed to automatically learn feature representation shared by building height and footprint prediction. Besides, we integrate digital elevation model (DEM) information into developed models to inform models of terrain-induced effects on the backscattering displayed by Sentinel-1 imagery. We set conventional machine-learning-based (ML) models and single-task deep-learning (STDL) models as benchmarks and select 46 cities worldwide to evaluate developed models’ patch-level prediction skills and city-level spatial transferability at four resolutions (100, 250, 500 and 1000 m). Patch-level results of 43 cities show that DL models successfully produce discriminative feature representation and improve the coefficient of determination (R2) of building height and footprint prediction more than ML models by 0.27–0.63 and 0.11–0.49, respectively. Moreover, stratified error assessment reveals that DL models effectively mitigate the severe systematic underestimation of ML models in the high-value domain: for the 100 m case, DL models reduce the root mean square error (RMSE) of building height higher than 40 m and building footprint larger than 0.25 by 31 m and 0.1, respectively, which demonstrates the superiority of DL models on refined 3D building information extraction in highly urbanized areas. For the evaluation of spatial transferability, when compared with an existing state-of-the-art product, DL models can achieve similar improvement on the overall performance and high-value prediction. Furthermore, within the DL family, comparison in building height prediction between STDL and MTDL models reveals that MTDL models achieve higher accuracy in all cases and smaller bias uncertainty for the prediction in the high-value domain at the refined scale, which proves the effectiveness of multi-task learning (MTL) on building height estimation

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

Spatial scale effect of surface routing and its parameter upscaling for urban flood simulation using a grid‐based model

Urban catchments are characterized by a wide variety of complex juxtapositions and surface compositions that are linked to multiple overland flow paths. Their extremely high spatial heterogeneity leads to great sensitivity of hydrologic simulation to the scale variation of calculation units. Although extensive efforts have been made for investigating the scale effects and indicate its significance, less is understood of how routing features vary with spatial scales and further how the variation of routing features influences the hydrological response. In this paper, a grid-based distributed urban hydrological model is applied to study spatial scale effects ranging from 10 to 250 m. Two parameters are proposed to quantitatively depict the routing features of overland flow specified for impervious and pervious areas. The results show that routing features are quite sensitive to spatial resolution. Large differences among simulations exist in the infiltration amounts attributed to the combined effects of the two routing parameters, which leads to opposite effects for both total flow volume and peak flow for various rainfall events. The relationship of the key model parameters at different spatial resolutions can be explicitly expressed by corresponding routing features. With this relationship, parameters transfer among different spatial scales can be realized to obtain consistent simulation results. This study further revealed the quantitative relationship between spatial scales, routing features and the hydrologic processes, and enabled accurate and efficient simulations required by real time flooding forecasting and land-atmosphere coupling, while fully taking the advantages of detailed surface information. Plain Language Summary Given the inherent complex underlying surface compositions and overland flow paths in urban areas, underlying high spatial resolution surface data eventually become necessary. Unfortunately, high resolution modelling in urban catchment is still challenging in terms of computational restricts, proper setting up of parameters etc., due to the high spatial heterogeneity. Practical simulation requirements often limit the use of high resolution models, as in the case of real time prediction of urban flooding, the coupling of land-atmosphere processes. Therefore, it is necessary to investigate the scale effects and its mechanism, and then to explore an accommodation approach to enable precise flooding prediction with a coarse model. For grid-based and distributed hydrologic models, the mosaic method can basically eliminate the scale effects on the runoff generation process. However, the scale effects on overland flow routing remain insufficiently understood, and to help understand the scale effects, simulations were performed under five different resolutions, ranging from 10 m to 250 m, for various rainfall events. Two physical parameters are introduced to quantify the scale effects on routing features. Three variables are concurrently calculated to assess the effects on modeling outputs. The results indicate that routing features are sensitive to changes in spatial resolution, which results in opposite effects on simulation results under different rainfall conditions. In conclusion, an accommodation approach is proposed based on the affecting mechanism

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

Investigation of robust visual reaction and functional connectivity in the rat brain induced by rocuronium bromide with functional MRI

Functional magnetic resonance imaging (fMRI) has been used extensively to understand the brain function of a wide range of neurological and psychiatric disorders. When applied to animal studies, anesthesia is always used to reduce the movement of the animal and also reduce the impacts on the results of fMRI. Several awake models have been proposed by applying physical animal movement restrictions. However, restraining devices were designed for individual subject which limits the promotion of fMRI in awake animals. Here, a clinical muscle relaxant rocuronium bromide (RB) was introduced to restrain the animal in fMRI scanning time. The fMRI reactions of the animal induced with RB and the other two commonly used anesthesia protocols were investigated. The results of the fMRI showed that there were increased functional connectivity and well-round visual responses in the RB induced state. Furthermore, significant BOLD signal changes were found in the cortex and thalamus regions when the animal revived from isoflurane, which should be essential to further understand the effects of anesthesia on the brain. Keywords: Rocuronium bromide, isoflurane, animal anesthesia, fMRI, visual stimulation, resting stat

Diagenetic–Porosity Evolution and Reservoir Evaluation in Multiprovenance Tight Sandstones: Insight from the Lower Shihezi Formation in Hangjinqi Area, Northern Ordos Basin

AbstractThe reservoir property of tight sandstones is closely related to the provenance and diagenesis, and multiprovenance system and complex diagenesis are developed in Hangjinqi area. However, the relationship between provenance, diagenesis, and physical characteristics of tight reservoirs in Hangjinqi area has not yet been reported. The Middle Permian Lower Shihezi Formation is one of the most important tight gas sandstone reservoirs in the Hangjinqi area of Ordos Basin. This research compared the diagenesis-porosity quantitative evolution mechanisms of Lower Shihezi Formation sandstones from various provenances in the Hangjinqi area using thin-section descriptions, cathodoluminescence imaging, X-ray diffraction (XRD), scanning electron microscopy (SEM), and homogenization temperature of fluid inclusions, along with general physical data and high-pressure mercury intrusion (HPMI) data. The sandstones mainly comprise quartzarenite, sublitharenite, and litharenite with low porosity and low permeability and display obvious zonation in the content of detrital components as a result of multiprovenance. Pore space of those sandstone mainly consists of primary pores, secondary pores, and microfractures, but their proportion varies in different provenances. According to HPMI, the order of the pore-throat radius from largest to smallest is central provenance, eastern provenance, and western provenance, which is consistent with the change tend of porosity (middle part>northern part>western part) in Hangjinqi region. The diagenetic evolution path of those sandstones is comparable, with compaction, cementation, dissolution, and fracture development. The central provenance has the best reservoir quality, followed by the eastern provenance and the western provenance, and this variation due to the diverse diagenesis (diagenetic stage and intensity) of different provenances. These findings reveal that the variations in detrital composition and structure caused by different provenances are the material basis of reservoir differentiation, and the main rationale for reservoir differentiation is varying degrees of diagenesis during burial process

The paleoclimatic footprint in the soil carbon stock of the Tibetan permafrost region

Data and code availability The authors declare that the majority of the data supporting the findings of this study are available through the links given in the paper. The unpublished data are available from the corresponding author upon request. The new estimate of Tibetan soil carbon stock and R code are available in a persistent repository (https://figshare.com/s/4374f28d880f366eff6d). Acknowledgements This study was supported by the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (XDA20050101), the National Natural Science Foundation of China (41871104), Key Research and Development Programs for Global Change and Adaptation (2017YFA0603604), International Partnership Program of the Chinese Academy of Sciences (131C11KYSB20160061) and the Thousand Youth Talents Plan project in China. Jinzhi Ding acknowledges the General (2017M620922) and the Special Grade (2018T110144) of the Financial Grant from the China Postdoctoral Science Foundation.Peer reviewedPublisher PD

Regional metabolic patterns of abnormal postoperative behavioral performance in aged mice assessed by 1H-NMR dynamic mapping method

Abstract Abnormal postoperative neurobehavioral performance (APNP) is a common phenomenon in the early postoperative period. The disturbed homeostatic status of metabolites in the brain after anesthesia and surgery might make a significant contribution to APNP. The dynamic changes of metabolites in different brain regions after anesthesia and surgery, as well as their potential association with APNP are still not well understood. Here, we used a battery of behavioral tests to assess the effects of laparotomy under isoflurane anesthesia in aged mice, and investigated the metabolites in 12 different sub-regions of the brain at different time points using proton nuclear magnetic resonance (1H-NMR) spectroscopy. The abnormal neurobehavioral performance occurred at 6 h and/or 9 h, and recovered at 24 h after anesthesia/surgery. Compared with the control group, the altered metabolite of the model group at 6 h was aspartate (Asp), and the difference was mainly displayed in the cortex; while significant changes at 9 h occurred predominantly in the cortex and hippocampus, and the corresponding metabolites were Asp and glutamate (Glu). All changes returned to baseline at 24 h. The altered metabolic changes could have occurred as a result of the acute APNP, and the metabolites Asp and Glu in the cortex and hippocampus could provide preliminary evidence for understanding the APNP process