ALBERT

Description: The Huxingshan tungsten deposit (~0.21 Mt at 0.3 wt% WO3) is located in the Jiangnan Massif tungsten ore belt, South China. Here, the W mineralization is restricted to quartz and muscovite-quartz veins intruding variable country rocks of the Lower Cambrian strata. Rb-Sr isochron ages derived from fluid inclusions trapped in muscovite-quartz veins (ca. 134 ± 2 Ma) agree with the zircon U–Pb crystallization age of the associated Huxingshan granite (137.8 ± 0.5 Ma) and may thus suggest a close petrogenetic relationship between both rock types. Zircon εHf (t) values of the Huxingshan granite (−16.2 to +6.6) overlap with those of the specially related metasedimentary Banxi and Lengjiaxi Groups, consistent with melting of Neoproterozoic Yangtze lower crustal materials with mantle melts input to the source. We suggest that the highly differentiated signatures of tungsten and beryllium granite might be inherited from the origin chemistry of source rocks and further modified by highly fractional crystallization rather than by fluid-rock interaction processes. During this process, tungsten and beryllium was enriched in the residual melts/fluids, which finally separated from the solidifying melt body and were introduced into the county rock to precipitate scheelite and beryl along skarn and greisen horizons by large-scale fluid movements. The outlined processes are likely to be coupled to large-scale melting of continental crust and associated granitic magmatism under a regime of subduction of the paleo-Pacific Plate beneath South China and subsequent tearing of the slab. The newly discovered Huxingshan deposit underlines the huge prospecting potential for the northwestern Jiangnan Massif.

Description: Ionosphere delay is a key factor in the single-frequency Precise Point Positioning (SFPPP). In tradition, two SFPPP models are applied, i.e., ionosphere-corrected (IC) and ionosphere-free-half (IFH) models. The ionospheric delays are directly corrected in IC model with external ionospheric products, while they are eliminated by forming the ionosphere-free combination with code and phase in IFH model. However, almost all studies focus on the numerical performance of these two models and lack the comprehensive study on the estimability and solvability of SFPPP model with either code division multiple access (CDMA) or frequency division multiple access (FDMA) system, respectively. In this paper, we dedicate to the analytical study on SFPPP models for both CDMA and FDMA systems. To assimilate the impact of ionospheric delays on positioning, a general SFPPP model, i.e., ionosphere-weighted (IW) model, is first formulated to identify the varying situations with the different uncertainties of ionospheric constraints. Then, we mathematically show how the IC, IFH and ionosphere-float (IF) models are reduced from IW model. The numerical comparison with GPS and GLONASS data with geodetic and cost-effective receivers effectively confirms our theoretical inference on the relationship of IC, IF and IW models and indicates the best results of IW model for all situations.

Description: In precise point positioning (PPP) applications, uncalibrated phase delays (UPD) are applied to retrieve the ambiguity integers for achieving precise solutions over a short period. Also, the atmospheric corrections obtained from a dense reference network are applied to accomplish this task of shorter convergence time or even instantaneous ambiguity resolution. The combined BeiDou Navigation Satellite System (BDS) and Global Positioning System (GPS) PPP with regional network augmentation is presented with threefold contributions. First, in order to overcome the UPD-inherent unmodeled errors in undifferenced ambiguity resolution at reference stations, it is proposed to fix the single-differenced ambiguities and use them as a constraint to fix the undifferenced ambiguities. Second, the performance of combined GPS+BDS PPP are fully evaluated with various indicators specified by single and combined satellite systems and several ratio test thresholds for ambiguity resolution. The BDS observations can provide the user with a significant improvement on the position solutions. The fix rate and correct fix rate are found to be increased by more than 7% and 11%, respectively. Third, the GPS+BDS regional augmented PPP is assessed in a highly occluded urban canyon. The experiments show the unfix rates of the combined system are decreased by more than 40%, and the correct fix rates can be improved by up to 55% compared with a GPS-only scenario.

Description: Knowledge about the trace element distribution in sulfides is the key for understanding the trace metal inventory of ancient volcanic massive sulfide during the formation of these deposits on the seafloor. The distribution of trace metals in sulfides reflects changes in the physicochemical conditions and precipitation processes during precipitation. Hydrothermal black smoker samples or this study originate from the southern Mid-Atlantic (TVG02, TVG06) and can be classified into two types: (1) (Fe-Zn) sulfides consisting predominantly of pyrite and sphalerite, with minor chalcopyrite, isocubanite, and galena and (2) (Fe-Cu) sulfides, which contain mainly pyrite and chalcopyrite, with rare isocubanite and sphalerite. The sulfide samples were analyzed by electron microprobe for major elements, and by laser ablation inductively coupled plasma mass spectrometry and focused ion beam technique and transmission electron microscopy for in situ trace elements. The data reveal complex hydrothermal processes in high- and low- temperature fluids. Colloform and dendritic pyrite from (Fe-Zn) sulfides are enriched in Mn, Tl, As, V, Pb, and Zn and indicate precipitation from low temperature fluids (250-100°C) reflecting a rapid mixture of hydrothermal fluids with seawater. A continuous enrichment of incompatible elements at the interface of growing pyrite with fluid finally leads to the nucleation and precipitation of sphalerite and galena, and results in the enrichment of As, Hg, Pb, Au, Ag, and Cd in sphalerite micro-inclusions which are hosted in colloform pyrite at low temperature. Galena inclusions occur in the pores and the interstices of sphalerite grains and formed by the enrichment of Pb in the hydrothermal fluid at low-temperature (〈250°C). High Cu, As, Ag, Au, and Sb concentrations in colloform sphalerite indicate a medium to low formation temperature (350-200°C). Copper, Sb, Se, and Sn enrichments in coarse-grained sphalerite indicate medium temperature hydrothermal fluids. Idiomorphic pyrite and chalcopyrite have high Se and Co contents and indicate high-temperature (〉300°C) fluids.

Description: Long short-term memory (LSTM) networks have been proved to work favorably in precipitation-runoff modeling due to their outstanding performance in processing long-length temporal dynamics. However, the other hydrological processes and the spatial information are rarely incorporated in current LSTM hydrological models, which hinders the models from making full use of hydrological data. This study proposes a spatiotemporal deep-learning (DL)-based hydrological model, by coupling the 2-Dimension convolutional neural network (CNN) and LSTM and introducing actual evaporation (E) as an additional training target. We use three large mountainous basins on the Tibetan Plateau to test the proposed CNN-LSTM model and compare the results to the LSTM-only model. Further analyses are conducted to explore meteorological and hydrological information hidden in the CNN and LSTM based on the linear regression model. Results indicate that both LSTM and CNN-LSTM hydrological models perform well on runoff (Q) and E simulation, with Nash-Sutcliffe efficiency coefficients (NSE) higher than 0.82 and 0.95, respectively. Involving CNN in the LSTM-only Q model to capture spatial information enhances the overall and peak Q modeling performance. Multi-task simulation with LSTM-only models show better accuracy in the estimation of Q volume and performance. On the other hand, we conclude that CNN models can capture the basin spatially-averaged values from 2-D spatial meteorological data. The internal cells of LSTM models for Q (E) contain the E (Q) process. This study provides an essential tool for accurate flood forecasting and management in large mountainous basins.

Description: A set of Global Navigation Satellite Systems (GNSS) satellite orbit and clock offset are an essential prerequisite for precise application. However, abrupt changes in accuracy at the boundaries are prevalent in products provided by international GNSS services, resulting in decreased orbit interpolation precision near the daily boundary. In addition, the effect of this phenomenon is reflected in the deterioration of accuracy and the fluctuations in subsequent applications. In this study, time-weighted and equal-weighted calibrated methods were utilized for adjacent Global Positioning System (GPS) satellite orbits and the orbit variations were then corrected for the clock offset to ensure their consistency. The calibration method is evaluated based on the accuracy and smoothness of post-processing kinematic precise point positioning (PPP) and low earth orbit (LEO) precise orbit determination (POD) near the day boundary. In a variety of scientific applications, the results indicate that the proposed calibration method can effectively reduce the excessive differences near the day boundary between adjacent days. Near the boundary, maximum improvements for post-processing kinematic PPP, dynamic LEO precision orbit, kinematic LEO precision orbit are 41.5%, 9.4%, and 20.5%, respectively.

Description: The Middle-Lower Yangtze River Valley Belt (MLYRB) in South China contains many stratabound Fe-Cu-Pb-Zn deposits hosted in Middle-Upper Carboniferous carbonates. The origin and nature of the ore fluids are poorly constrained (syngenetic vs. epigenetic). Trace elements and sulfur isotope compositions of sphalerite and galena from the Qixiashan carbonate-hosted Pb-Zn deposit (Eastern of MLYRB) help to clarify the ore-fluid source and metallogenic processes. Three types of sphalerites have been distinguished (black sphalerite a, zoned sphalerite b and light color sphalerite c). High Fe and Mn contents of the early black sphalerite (Sp-a) were possibly derived from preceding Fe-Mn-rich sulfide layer or sediments from ore-bearing strata via replacement at 274–315 °C. The zoned sphalerite (Sp-b) has a dark Fe-Cu-rich core (321–348 °C) overgrown by a light Fe-Cu-poor rim (285–314 °C). The Sp-b rims are compositionally similar to Sp-a, Therefore, zoned Sp-b possibly represents the transition stage from poor copper (Sp-a) to rich copper (Sp-c) fluids. The light-color late sphalerite (Sp-c) is characterized by Fe-Mn depletion, as well as Ga, Cu, Cd and Sn enrichments. The Ga-rich Sp-c was possibly precipitated by the mixing of Ga-bearing sulfate and metalliferous fluid at 146–255 °C. We considered the Qixiashan Pb-Zn deposit to be of epigenetic origin that has undergone multistage ore-forming processes, in which the ore sulfur (δ34S: –3.7‰ to +7.8‰) was sourced from seawater sulfate (+22‰) via thermochemical sulfate reduction (TSR).

Description: Uncertainties are inevitable when using hydrological models for runoff forecasting. The Xinanjiang model considering snowmelt and the recession curve method were established respectively for the runoff forecast in the flood season (including the snowmelt season) and in the dry season. The error autoregressive correction model was integrated to improve the real-time forecast accuracy. A probabilistic forecast model of daily runoff was established by combining the deterministic forecast results and the hydrological uncertainty processor, and the probabilistic forecast accuracy was assessed by two types of indicators: precision evaluation and reliability evaluation. In order to verify the validity of the probabilistic forecasting framework, we carried out a case study with the watershed above the Houziyan Reservoir of the Dadu River as the study area. The multi-year average Nash-Sutcliffe efficiency coefficient of the Xinanjiang model was 0.85 in both calibration and validation periods, and the overall accuracy was high. With the error correction, the forecast accuracy was improved, and the forecast accuracy could be guaranteed on the basis of extending the forecast period. The forecast accuracy of the median of the probability distribution function was better than the original deterministic forecast to a certain extent. The coverage rate and dispersion degree of the 90% confidence interval were about 90% and below 0.40, respectively, indicating that it can cover most of the measured discharge values in a relatively narrow interval and has high reliability. The findings can provide technical support for flood control power generation scheduling and risk management in the study area.

Description: The incorporation of multi-frequency signals into global navigation satellite systems (GNSS) has presented new possibilities for precise positioning and rapid ambiguity resolution. Inter-frequency clock bias (IFCB) pertains to the time-varying biases among distinct frequencies within carrier phase observations in GNSS signals. The appropriate handling of IFCB is critical in enhancing the accuracy and convergence time of precise point positioning (PPP) solutions. The focus of this study is on the proper modeling of phase IFCB in multi-GNSS multi-frequency PPP. In this paper, the optimal IFCB power spectral density value of 0.6 m/sqrt(s) is first determined. To obtain the optimal stochastic model for IFCB, a thorough comparison and analysis of the product correction and parameter estimation methods is conducted. Additionally, experiments are conducted on the effect of IFCB modeling on the performance of undifferenced and uncombined PPP using data from 130 multi-GNSS experiment stations across the globe over a period of one week in January 2022. The study reveals that the optimal power spectral density for IFCB is within [60, 0.006] m/sqrt(s), modeling IFCB as a random walk is feasible, and the PPP is comparable for the three IFCB processing schemes of product correction, random walk, and white noise. Meanwhile, it is not reasonable to treat IFCB as a random constant or neglect it in the multi-GNSS multi-frequency PPP. In the absence of product correction or for users who require immediate and continuous positioning solutions, modeling IFCBs as random walks can lead to more reliable positioning results and improved convergence performance.

Description: GPS Block IIR-M and Block IIF satellites have the ability to redistribute transmit power between different signal components. This is known as “flex power” capability and used for anti-jamming by increasing the signal power. Flex power has been enabled since January 2017 and shown different modes in bands, signal components, coverage and power enhancement. Though flex power improves the signal immunity, the power enhancement causes imbalance of signal power at receivers, which would lead to multiple assess interference effects and impacts on observation. Thus, the detection of flex power is of great importance for the users. A noval detection model based on the distribution of carrier-to-noise density ratio (C/N0) in GPS satellites’ azimuth and elevation is proposed and can be adopted for any receiver in real time. The detection results are compared with published flex power activation period in order to verify the performance of detection model. The results show that the successful detection rate is about 99.8%, which proves the feasibility of the detection model for GPS flex power.