bluuebunny/crossref_metadata_2025 huggingface dataset:
Transboundary transport of central Asian dust to the Pamirs: measurements and modeling
Authors: Dong Qingqing , Huang Zhongwei , Zhou Tian , Wang Yufei , Wang Tianhe , Bi Jianrong , Liu Qiantao , Li Zhengpeng , Li Wuren , Shi Jinsen , Li Ze , Liu Wentao , Niu Zuorong , Song Xiaodong
Published: March 2024

Tajikistan is located in an arid and semi-arid region, with a dry climate and sparse precipitation and the sandstorms frequently occur in summer. The Shaartuz lidar site (68.0°E, 36.9°N, 274 masl) is located in a basin in southern Tajikistan. It is observed that the dust storms occur in this area are usually lifted to a height of 5-6 km above the ground, which is equivalent to the height of the Pamirs covered with ice and snow. With the effects of complex terrain, there is a possibility of the dust being transported to the Pamirs under the mid-latitude westerly belt. In this work, the two lidar systems located in Shaartuz and Taxian (75.2°E, 37.8°N, 3087 masl) which is in the southeast of the Pamirs are utilized to study the dust event in summer. The significant variations of dust optical properties and vertical distribution can be captured by the two lidar system during June 11th to 15th, 2023. The backward trajectory model and satellite observation are used to verify the transport path of the dust event. WRF-Chem also successfully simulated the transport process of the dust event, and analyzed the spatiotemporal evolution characteristics and the dust effects. These results will help us explore the characteristics of central Asian dust transboundary transport toward Pamirs and its regional climate effects.
Future projection of  extreme climate events using various general circulation model scenarios over the Mahi River Basin, India
Authors: Maurya Swati , Srivastava Prashant K , Suman Swati , Pandey Varsha
Published: March 2024

The authors have analyzed twentieth-century precipitation extreme events from the climatic models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) generated by NASA (NEX-GDDP). This study is focused on the long west flowing perennial Mahi River Basin (MRB) has great ecologically and economically significance basin of India. A precipitation extreme is quantified using the Expert Team on Climate Change Detection and Indices (ETCCDI) index. The most suitable Global Climate Models (GCMs), INMCM-4, MRI-CGCM3 and ensemble mean (Root Mean Square-0.075 mm/day, Correlation Coefficient-0.9, Standard Deviations-0.75mm/day) were applied for base period (1981-2010) and near future projection (2011-2040). The precipitation extreme events in term of Consecutive Dry Days (CDD), Annual maximum 1-day precipitation amount in day (RX1) and Annual maximum 5-day precipitation amount in days (RX5), Simple Daily Intensity Index (SDII) as well as maximum annual number of Consecutive Wet Days (CWD) are overestimated whereas, 10 Rainy days with heavy precipitation in days (R10) and 20 Rainy days with very heavy precipitation in days (R20) are overestimated in future (2011-2040) with respect to (1981-2010). The spatial extent of precipitation extreme indicated that, CDD values are increases in N-W region of Rajasthan and Gujarat while CWD, increases in Madhya-Pradesh. Consequently, SDII decreases in all region. Further, the RX1, RX5 along with R10 and R20 day precipitation decreases all region of MRB. Thus, overall finding indicated the CDD decrease with increases CWD may be good for agriculture and local society also. In addition, SDII decreases same manner in all the region indicated precipitation intensity decreases, which affect the hydrological cycle. Similarly, RX1 and RX5 represented that low precipitation, indicates that the sufficient amount of water is needed to manage the irrigation scheduling for increment of crop productivity. The changes in R10 and R20 day precipitation have affect the geographic condition. Thus, the scope of developing the extreme climate indices would be beneficial for farmers who are the main stakeholders in agriculture as well as it will help in water resource developer and disaster preparedness.
Urbanization and climate change impacts on future heavy summer rainfall in Milan, Italy
Authors: Koukoula Marika , Torelló-Sentelles Herminia , Peleg Nadav
Published: March 2024

Over the past fifty years, urbanization has undergone a swift surge, with over 50% of the global population now residing in cities. A further rise in urban population in the forthcoming decades is expected based on future projections. This surge in urbanization, along with associated alterations in land use/land cover, has the potential to modify the temporal and spatial characteristics of precipitation. Additionally, the anticipated escalation in global warming is likely to amplify both the magnitude and frequency of short-duration (convective) heavy rainfall. These two factors separately have the potential to lead to an increased risk of urban flooding. Consequently, it is imperative to comprehend how urbanization and climate change together may impact short-duration heavy rainfall events - a crucial aspect for effective flood risk assessments and planning sustainable urban drainage systems. To this end, we explore the influence of climate change and urbanization on the spatiotemporal properties of rainfall. Our investigation involves the simulation of current and future scenarios of urban development and warming over Milan, utilizing the convection-permitting Weather Research and Forecasting (WRF) physically-based atmospheric model. The findings of this study underscore that future urbanization will influence the distribution of rainfall in terms of both time and space. Furthermore, the combined effects of urbanization and climate change can significantly reshape the structure of short-duration heavy precipitation events.
Detecting Groundwater Flow Induced by Underground Research Laboratory Excavation through Active-DTS Measurements
Authors: Dong Yanhui , Wang Liheng , Fu Yunmei
Published: March 2024

The characteristics of groundwater flow within fractured rock formations and the distribution of their hydraulic conductivity form the foundational basis for subsurface engineering endeavors, including the disposal of high-level radioactive waste. Traditional methodologies for measuring groundwater flux are constrained due to their inability to gather distributed data. The novel approach, employing active distributed temperature sensing (A-DTS), presents a promising methodology for flux mapping. This study conducted flow rate tests using A-DTS within boreholes located at an Underground Research Laboratory for the Geological Disposal of High level waste in China. Utilizing the flow rate data, this investigation delineates the impact of ramp and shaft excavations on groundwater dynamics. Furthermore, the integration of flow rate data with hydraulic head measurements is essential for characterizing the flow regime and delineating the permeability structure within the granite fractures.
Development of analytical method to measure halogenated volatile organic compounds in the Amazon rainforest
Authors: Hartmann Christoph , Byron Joseph , Pugliese Giovanni , Lelieveld Jos , Williams Jonathan
Published: March 2024

Halogenated volatile organic compounds (XVOCs) are volatile hydrocarbons that have at least one halogen atom. These substances are of global importance because their relatively long atmospheric lifetimes enable transport of halogen atoms to the stratosphere leading to stratospheric ozone depletion. Since the regulation of anthropogenic XVOC emissions through the Montreal Protocol and subsequent amendments, the importance of naturally formed XVOCs has been increasing. Chloromethane (CH3Cl), for example, represents the largest natural source of chlorine in the stratosphere, currently contributing to approximately 16% of stratospheric ozone depletion, with plants suggested to be its major source. Other XVOCs like Chloroform (CHCl3) can influence atmospheric chemistry more on a local scale due to their shorter atmospheric lifetimes.In this work, we present the implementation of an instrumentational setup for long-term in-situ XVOC monitoring at the Amazon Tall Tower Observatory (ATTO) site. The 325 m tall tower, located in the pristine Amazon rainforest (circa 150 km NE of Manaus, Brazil), enables measurements of natural XVOC emissions almost free of anthropogenic influence due to its remote location.The analytical setup consists of the tower inlet system and a Multi-Capillary Column Trapping System (MCCTS) coupled to GC-MS. Here we show several days of preliminary data for methyl chloride, isoprene and several CFC species as a proof of concept. Furthermore, we examine the applicability of simultaneous CFC measurements as a “natural internal standard” for the correction of systematic errors like MS sensitivity changes.The presented analytical method is able to provide data in form of atmospheric mixing ratios of the desired XVOC compounds at four different heights (ground level, 80 m, 150 m and 320 m) with a time resolution of approximately two hours per height. It has the potential to open up new opportunities to better quantify the XVOC net production and consumption of the Amazon Basin ecosystem and to understand the underlying processes, especially with respect to future ecosystem transformations due to climate and land use changes.
Orbit Determination of Near-Earth Asteroids and Impact Efficiency Assessment of Asteroid 2015XF2
Authors: Song Yezhi
Published: March 2024

In defense against the threat of asteroid impacts, countries worldwide are vigorously engaged in asteroid monitoring and warning efforts. This report briefly introduces the use of short arc observations based on astronomical optical measurements for the initial orbit determination of newly discovered asteroid targets. It also explores the analysis of precise orbit data for near-Earth asteroids through joint optical measurements from both space-based and ground-based platforms. The study investigates the orbit determination capabilities of different space-based platforms for various types of near-Earth asteroid orbits.Additionally, the report discusses the dynamical behavior of periodic orbits in the restricted three-body problem and the corresponding search strategies. To meet the requirements of subsequent related missions, an analysis of the impact efficiency assessment for asteroid 2015XF261 is conducted. The simulation of the asteroid impact process is carried out, and the precision of orbit determination before and after the asteroid impact is analyzed through ground-based optical and Doppler measurements.
Parameter estimation of the geomagnetic activity model by non-linear least squares
Authors: Ćorković Martina , Verbanac Giuliana , Bandić Mario
Published: March 2024

Geomagnetic disturbances during coronal mass ejections (CMEs), which are powerful plasma ejections from Sun’s corona, pose significant challenges for space weather forecasting. In this study, we propose an improvement to the O’Brien-McPherron model [1] for forecasting the storm-time disturbance index Dst, a key parameter reflecting geomagnetic storm intensity during CMEs, in terms of solar wind parameters. By optimizing the parameters of the O’Brien-McPherron model with respect to the sunspot number, we enhanced the model’s performance for both very low and high solar activity.We have analysed 48 CME-induced geomagnetic storms from 1996 to 2020 and grouped them in four different solar activity levels based on the mean number of sunspots during each storm. We derived the new optimal values for three model parameters for each activity level by employing a non-linear least squares approach, specifically utilizing the Levenberg-Marquardt algorithm.By taking into account the number of sunspots during a geomagnetic storm, we successfully mitigated the model’s tendency to consistently overestimate the intensity of very weak geomagnetic storms in the very low solar activity level. While the average difference between the forecasted maximum storm intensity and the observed intensity for the regular O’Brien-McPherron model is 17 nT, the optimized model demonstrates a notably reduced difference of 2 nT. Simultaneously, we expanded the model’s applicability to include hazardous superstorms (Dst < -150 nT) occurring during high solar activity, effectively preventing the substantial underestimation of their intensity. The O’Brien-McPherron model is not suited for superstorms and exhibits deviations of about 100 nT in forecasting their maximum intensity, whereas the optimized model underestimates it on average by only 25 nT.Geomagnetic superstorms can induce very strong electrical currents in power grids, navigation and communication systems and satellites. Underestimating their impact can lead to insufficient shielding and permanent damage of these systems. Enhancing our ability to forecast these events with greater precision, as demonstrated by the improved performance of the optimized model, is crucial in minimizing disruptions and safeguarding infrastructure and technology.[1] O'Brien, T. P., and R. L. McPherron (2000), An empirical phase space analysis of ring current dynamics: Solar wind control of injection and decay, J. Geophys. Res., 105(A4), 7707–7719, doi:10.1029/1998JA000437.
Injection Rate effects on failure of a saturated gouge-filled fault failure: Dilation vs. Diffusion
Authors: Sarma Pritom , Aharonov Einat , Toussaint Renaud , Parez Stanislav
Published: March 2024

Understanding the underlying mechanisms controlling earthquake triggering by fluids has become increasingly important in recent decades, driven largely by observations that link subsurface fluid injections to subsequent nearby earthquakes. It is clear that understanding and predicting fluid-induced triggering is required in many energy-related activities (e.g. geothermal energy, CO2 injection), as well as for naturally triggered events. One of the main open questions is the effect of fluid-injection rate. Usually the ‘effective stress law’ is invoked to predict the failure of fluid-saturated granular or porous media. This law assumes that in fluid-pressurized faults the instantaneous value of pore pressure controls fault strength and failure. But recent laboratory results (Passelègue et. al., 2018) suggest that the level of pressure by itself cannot describe the full mechanics. These experiments show that the rate of fluid injection is also important: slower injections lead to failure at lower pressures than fast injection rates.  We shall present results from a coupled hydromechanical-discrete element model that simulates the response of a pre-stressed, fully saturated fault, filled with a granular fault gouge, subject to fluid injection at different rates. Our simulation results find similar rate-dependence as seen in the laboratory experiment, i.e. that slow injection causes failure at lower fluid pressure than faster injection. Several mechanisms can be theorized to explain these observations, and we explore the two main end-member cases, dilation-driven and diffusion-driven rate-dependence, by comparing theoretical predictions for the poro-elastic response of the layer vs. pore-pressure diffusion. Our theoretical analysis provides upper and lower bounds to the numerically observed  rate dependence, suggesting the reason why the effective stress law is an insufficient approximation for failure of material exposed to pore fluid injection, when the pore-pressure injection rate is varied.
An integrated multilevel and geostatistical approach to study the impact of environmental factors on biodiversity at different spatial and temporal scales
Authors: Maggio Sabrina , De Iaco Sandra
Published: March 2024

Nowadays, biodiversity loss and climate variability are among the most pressing threats to human societies and ecosystems. Consequently, it becomes of fundamental importance to identify methodological approaches which can jointly analyse the dynamics of biodiversity in connection with climate variations. In this context, a combination of multilevel and geostatistical models is proposed to determine the influence of environmental factors on biodiversity occurring in a spatio-temporal domain. In particular, the present study is carried out in four interlinked phases, focusing on: a) the computation of the biodiversity multilevel indicator, which considers both the diversity of species and landscape features of the area being investigated, b) the spatio-temporal analysis of potential environmental factors (such as air pollutants and meteorological variables) which could alter the biodiversity, c) the selection of the triggering and driving determinants which can affect the biodiversity, through a dedicated multilevel analysis, d) the construction of probability maps which allow to identify low or high biodiversity areas within the domain under study, by non-parametric geostatistical techniques. The empirical findings reveal a statistically significant relationship between the reduction of biodiversity and the increasing air pollutantsconcentrations. These results can be extremely useful to devise strategies that aim to safeguard both the environment and the public health according to the Sustainable Development Goals reported in the 2030 Agenda of the United Nations.
Vegetation Dynamics Regulate Baseflow Seasonal Characteristics in the Chaohe Watershed of Northern China
Authors: Cao Wenxu , Li Qinghe , Xu Hang , Zhang Zhiqiang
Published: March 2024

The implementation of ecological restoration programs (ERP) and the acceleration of climate change (CC) in recent decades have led to severe water shortages and threatened water security and ecosystem function in Northern China. Baseflow is essential for sustaining river flows, yet its seasonal responses to CC and ERP remain not fully understood, which limits the understanding of available water resource variation and the mechanisms behind them. In this study, we quantified and attributed the variation in baseflow across dry and wet seasons in the main source of Beijing's potable water – the Chaohe watershed of Northern China from 1961 to 2016 by thoroughly assessing nine different approaches for separating baseflow. We found that the two-parameter Eckhardt digital filter method could better characterize baseflow variation. Hereinto, the wet-season dominated baseflow (seasonality ratio was 2.12 ± 1.28 on average) accounted for 64.21% ± 13.04% about the entire year in the watershed. Both dry and wet seasons' baseflow exhibited a significant reduction, with changes of 32.61% and 68.21%, therefore posing more serious threats to the sustainability of water resources, especially under the prevailing global warming. For the baseflow variation, we further found the significantly declined sub-surface runoff (with a rate of 1.91 mm per decade) played a critical role in the decrease in dry-season baseflow. Meanwhile, vegetation regulated the seasonal distribution of water resources and maintained dry-season streamflow. It is vital to improve water resource management by vegetation measures, especially in water-limited regions. However, as a supplementary water source, the decrease in wet-season baseflow was the result of offering more water supply to meet the evapotranspiration demand. Overall, our findings offer novel insight into understanding the influence of vegetation dynamics on water resources and highlight the essential role of vegetation in regulating baseflow to maintain water balance and water resources' seasonal distribution.
Model diagnostic analysis in a cold basin influenced by frozen soils with the aid of stable isotope
Authors: Nan Yi , Tian Fuqiang
Published: March 2024

Understanding the hydrological processes on the Tibetan Plateau (TP) is an important scientific question under climate change. The frequent multiphase transfer exacerbates the complexity of hydrological processes on the TP, which brings equifinality problem to hydrological models and causes large uncertainties in quantifying the contributions of runoff components. Tracer-aided hydrological models are helpful for improving model performances and have been adopted in cryospheric regions, but the influence of frozen soil has yet to be considered. This study adopted the tracer-aided hydrological model THREW-T (Tsinghua Representative Elementary Watershed, Tracer-aided version) in a typical cold basin with widespread frozen soil on the TP. The model structure was diagnosed with isotope by identifying the influences of frozen soil. A simplified catchment-scale frozen soil module was incorporated into the model. Results showed that: (1) The THREW-T model cannot simultaneously simulate baseflow and stream water isotope well. The imbalance of simulations on two objectives could be attributed to the influence of frozen soil, resulting in seasonal variation of soil-related parameters, which was not considered in the model. (2) Incorporating the frozen soil module significantly improved the balance of baseflow and isotope simulation, simultaneously producing low baseflow and high contribution of subsurface runoff during wet seasons. (3) The frozen soil had little influence on the annual streamflow, but changed the runoff seasonality by reducing baseflow during dry seasons and increasing subsurface runoff during wet seasons. The frozen soil module was still simplified, and further work is needed to improve the physical representation of soil freeze-thaw process. This study highlights the value of tracer-aided hydrological modeling method on diagnosing model structure by identifying the influence of specific processes such as frozen soil.
Assessment of Land Subsidence Hazards in the Choshui Delta Under Climate Change Scenarios Using Artificial Intelligence
Authors: Liu Chih-Yu , Ku Cheng-Yu
Published: March 2024

In recent years, global climate change has significantly impacted fluctuations in groundwater levels, with Taiwan experiencing a severe water shortage crisis during the 2021 century drought. The intensive depletion of groundwater from aquifer systems has led to a significant increase in land subsidence in the Choshui delta of central Taiwan. In this study, we propose the assessment of land subsidence hazards in the Choshui delta under climate change scenarios using artificial intelligence. This study first compiles basic data such as groundwater levels, pumping, precipitation, drilling data, land-use patterns, and other historical monitoring data from the past 20 years. The geographic information systems are then utilized to establish spatial layers of geographical information factors. Subsequently, principal component analysis is employed to reduce the dimensionality of the above factors, analyzing the coupled relationships and correlations between land subsidence and relevant factors. This process aims to identify factors highly correlated with land subsidence, serving as input data for the proposed neural network model. The proposed model is then used to predict land subsidence and validated against historical land subsidence events. This facilitates the subsequent development of a neural network-based analysis model for land subsidence hazards. Results indicate a high correlation between groundwater levels and extraction quantities with the impact on land subsidence. Furthermore, the neural network model developed in this study demonstrates high precision during both training and prediction stages, with root mean square error values of 10-3 and 10-1, respectively. The future application of the developed neural network model enables continuous prediction of land subsidence hazard potential under various climate change scenarios in the Choshui delta.
Analysis and Policy Response to Mitigate Methane Emissions from Rice Farming for an Environmental- Sustainability
Authors: Ibeh Dr Gabriel Friday , Ibeh Dr Lawrence M , Ojeh Dr Vincent N , Okoh Dr Daniel
Published: March 2024

This research present methane distributions and mitigation innovative strategies for environmental sustainability. Satellite methane data from 2015 to 2022 at three locations across Nigeria will be used in this study. Artificial neural network application will be adopted for data modelling and analysis. Methane is a significant greenhouse gas (GHG) and its atmospheric concentration has virtually increased globally due to its anthropogenic sources such as rice farming. Rice farming is one of the engines of economic growth and economy development in Nigeria, at the same time responsible for significant portion of global methane emission which poses risk as a health burden to the environment. The study will investigate the distributions of methane emission within the locations and years of study. Reduction in rice farming will reduce methane and will have negative impact in economy development.  But, if managed properly for environmental sustainability through relevant innovations and technologies, productive rice will be achieved. To mitigate these emissions, there are several policy responses and innovations that can be implemented. The innovative strategies such as microbial process, Happy Seeder Machine approach, changing of rice production practices, integrated agronomic management strategies and other policy approaches can  mitigate and regulate methane emissions from rice farming at the same time have a proper produce. Details application on how these innovative strategies will be used to mitigate and regulate methane emmissins for environmental sustainability will be discussed in this study.
Complexity-based approach for the Predictability of High-Impact Weather and Climate Events
Authors: Fan Jinfang
Published: March 2024

This study embarks on an exploration of high-impact weather and climate events from the perspective of complex systems dynamics. By situating these events within the framework of subsystem interactions, the research aims to apply sophisticated techniques inherent in complex network methodologies. We intend to utilize an array of technical approaches, including climate network analysis, multilayer networks, and percolation phase transition theories. The primary objective is to unravel the underlying connections between these high-impact weather events and to enhance the predictability of such occurrences. Through this approach, we aspire to gain a deeper understanding of the dynamic interplay and potential correlations among these significant meteorological and climatological phenomena, thereby contributing to more accurate forecasting models and a comprehensive grasp of weather and climate systems.
Machine Learning-Based Identification of Fault Structures in Seismic Refraction and Resistivity Tomography
Authors: Doyoro Yonatan Garkebo , Lin Chih-Ping , Gelena Samuel Kebede , Pan Ernian
Published: March 2024

This study identifies subsurface geological structures by integrating geophysical tomography and machine learning techniques. Borehole drilling methods for subsurface detection are both costly and spatially limited. Geophysical imaging methods, including seismic refraction tomography (SRT) and electrical resistivity tomography (ERT), are typically employed to address these challenges. In this study, geophysical imaging was utilized, and their inversion results were processed with the k-means clustering machine learning approach to address geological challenges along the proposed Porsgrunn Highway in Norway. A total of 39 SRT and 5 ERT profiles were conducted and comprehensively evaluated using advanced post-inversion processing with the k-means clustering algorithm from the scikit-learn open-source resource in Python. The study findings show six exemplary SRT and four ERT profiles. We employed both the Elbow and Silhouette evaluation methods to ascertain the optimal cluster numbers for unsupervised k-means clustering. These methods consistently identified the optimum cluster number, with only a few exceptions. The use of both methods of evaluation is beneficial since they can complement each other and improve cluster validation. The results show that the clustered models adequately correspond to distinct lithologic units, effectively revealing fault zones and bedrock depths. Our findings suggest that combining geophysical imaging with machine learning provides valuable insights for improving subsurface geological interpretations, allowing for informed decisions in geological hazard assessment and engineering construction site selection.
Tidal force increasing the upwelling intensity off the northeastern coast of Taiwan
Authors: Ho Chia-Ying , Lee Hung-Jen
Published: March 2024

Most historical research and observations have revealed the presence of a cold dome associated with a cyclonic eddy off the northeastern coast of Taiwan. The phenomenon could be derived from the interaction between the Kuroshio and the complex terrain of the local continental slopes. Also, the monthly average SST (sea surface temperature) of satellite image data indicates the prominent features of this cold water mass in the region during the summer. In spite of experiencing long-term investigations, some specific factors contributing to the formation of this cold eddy still need to be clarified. Consequently, a three-dimensional general circulation model (MITgcm) was employed to explore the underlying physical mechanisms of the cold dome formation. In considering some particular factors, the model results at a depth of 50 m reveal that as the Kuroshio passes over the North Mian-Hwa Canyon, it generates a cold water mass with temperatures approximately 4-5 oC lower than that of the Kuroshio water. However, the temperature decrease in the model's surface layer deviates from observational data, such as satellite image information, showing a modest decrease of around 1 oC. The subsequent inclusion of wind effects imposed on the model indicates that the summer monsoon enhances the strength of the cold water mass. However, the impact on surface temperature drop is insignificant, decreasing by only 0.2 oC compared with the no-wind model case. Finally, the tidal force imposition in the model leads to a substantial temperature reduction, dropping from 1 oC (without tides ) to 5-6 oC (with tides), more closely aligning with field observations and satellite mages. Additionally, temperature time-series analysis reveals the periodic oscillations, including daily and longer 15-day tidal cycles.Key words: Cold dome; Kuroshio; MITgcm; Tide
Organic Matter Enrichment of Black Shale under Tectonic Transformation of the Wulalike Formation in the western margin of Ordos Basin, China
Authors: Li Fengjiao , Zhang Dongdong
Published: March 2024

Different tectonic settings affect organic matter enrichment by influencing sedimentary environments. The formation, preservation, and enrichment patterns of organic matter in the Wulalike Formation are still unclear. The influence of the ancient tectonic pattern and sedimentary environment of the Wulalike Formation are summarized to provide insights into the organic matter enrichment through analysis methods such as tectonics, petrology, mineralogy, and geochemistry. The abundance of organic matter is low and heterogeneous vertically in the bulk of the Wulalike Formation. The Wulalike Formation was formed during a tectonic transformation, during which it transitioned from an active continental margin to a passive continental margin. It was at high sedimentation rates that the organic matter content was diluted by the input of clastic sediments. The terrestrial inputs increased through time. The preservation conditions of organic matter were disrupted by the increasing oxygen content with the increase of terrestrial inputs. The level of ancient productivity is gradually decreasing, and the hydrocarbon-generating organisms are a combination of floating algae and benthic algae. The enrichment pattern of organic matter in the Wulalike Formation is controlled by regional structures, dominated by sedimentation rate, terrestrial input, and preservation conditions, supplemented by primary productivity levels. The organic matter accumulation model proposed in this study will provide theoretical support for the exploration of shale gas in northern China.
Coupled Impacts of Ventilation of the North Pacific Intermediate Water and Biological Productivity on Late Quaternary sedimentary oxygenation in the Subtropical North Pacific
Authors: Dou Yanguang
Published: March 2024

    The North Pacific Ocean has been identified as an important region for studying the atmospheric carbon cycle on glacial-interglacial timescales. However, due to the lack of long-term records, the coupling relationship between ventilation of the North Pacific Intermediate Water, biological productivity and late Quaternary sedimentary oxygenation in the subtropical North Pacific, as well as their roles in regulating atmospheric CO2 are still unclear. In this study, we reconstructed the redox records in the subtropical North Pacific since Marine Isotope Stage (MIS) 6 based on geochemical parameters and productivity proxies in sediment from the Okinawa Trough. Sedimentary δ98/95Mo and other redox proxies show suboxic conditons during MIS5 and late MIS3. These suboxic environments were mainly driven by the increased productivity associated with the Kuroshio Current and East Asian Summer Monsoon (EASM). During interglacial periods, the enhanced induced upwelling carried nutrients and CO2 from the bottom water to the sea surface. We suggest that some CO2 outgassing from the subtropical Northwest Pacific helped to maintain high atmospheric CO2 concentrations during the interglacial period and contributed to the deglacial CO2 rise. The Okinawa Trough experienced a peak in anoxic or even sulfate reducing conditions during MIS4 and early MIS3. When enhanced deep water ventilation offset the impact of primary productivity in the Okinawa Trough during interglacial periods MIS1 and MIS5, the sedimentary environment was in a weakly oxic state. In contrast, NPIW produced strong downstream effects in the subtropical North Pacific during glacial periods (MIS6, MIS4 and MIS2), leading to suboxic and oxic conditions in the deep water Okinawa Trough. At those times, strengthened intermediate and deep-water stratification prevented the upwelling of deep-sea nutrients and CO2 transport to the surface. Overall, the sedimentary redox variation in the Okinawa Trough is tightly coupled with NPIW, upwelling, and biological productivity during glacial-interglacial cycles, indicating the important role that the subtropical North Pacific plays in regulating the atmospheric CO2 budget of the ocean.
On the possibility of the 2022-like spatio-temporally compounding event across the Yangtze River Valley
Authors: Liao Zhen , An Ning , Chen* Yang , Zhai Panmao
Published: March 2024

    During July-September 2022, heatwaves, droughts, forest fires and floods hit the Yangtze River Valley (YRV) successively, constituting a spatio-temporally compounding event. Starting in mid-July, one of the most severe, sustained and extensive hot-drought took place over much of the YRV, leading to power outages and harvest failures in the electricity- and water-rich region. The hot-dry weather dried out forests, and sparked numerous wildfires. The hazard chain extended as some of the burned areas received heavy precipitation, where the flood and debris flow risks stayed high in the following months. The rapid sequencing of multiple extremes shortens relief windows, enhances exposure/vulnerability of natural and human systems to the next hazard(s), and therefore overwhelms their ability to respond. Understanding its risks matters to disaster preparedness.
      The single-model initial-condition large ensembles (SMILEs) offer a broad range of physically plausible climates that better serve for exploring the possibility of extremes at a given warming level. To this end, we address the event possibility issue in the SMILEs framework. Through searching for event analogues in SMILEs, we report that the 2022 unprecedentedly widespread and intense hot drought might have occurred as early as in the 1970s, and would become increasingly possible and spatially extensive with warming. This tendency is also supported by the conventional multi-model (CMIP6) projection, especially evident in larger ensembles. Lower reaches of the valley and parts of Southwest China have greater chances of repeated exposure to the 2022-like heat—drought—fire—flood quadruple compound events. In the context of favorable internal variability in line with future warming, it is plausible to see more than half of the valley at simultaneous risk of similar quadruple compound events. Our possibility projections highlight the urgency of accelerating the existing univariate extremes—oriented adaptation measures to address emerging threats from unfamiliar compound hazards.
Groundwater level prediction using hybrid ML: Bridging the gap between nature-based solutions and nature-inspired algorithms
Authors: Singh Abhilash , Bhadani Vipul , Kumar Vaibhav , Gaurav Kumar
Published: March 2024

Effective groundwater management requires accurate prediction of GroundWater Level (GWL) fluctuations. This study proposes six novel regression algorithms by integrating a Fuzzy Inference System (FIS) with six Nature-inspired Algorithms (NiA) to enhance GWL prediction accuracy. The proposed algorithms contribute to several Nature-based Solutions (NbS) goals, including improving water security by ensuring that groundwater resources are used sustainably and helping to ensure that people have access to clean and safe water. In this study, we coupled FIS with Invasive Weed Optimization (IWO), Ant Colony Optimization (ACO), Teaching-Learning-Based Optimization (TLBO), Differential Evolution (DE), Harmony Search (HS), and Weevil Damage Optimization Algorithm (WDOA). We used precipitation, relative humidity, and groundwater level lag as potential input features to predict the groundwater level. We found that the Fuzzy-IWO-GWL model accurately predicts GWL fluctuations, achieving a high correlation coefficient (R = 0.89), low normalized root mean square error (nRMSE = 0.18), and minimal bias (bias = 0.08). A comparative analysis involving eleven benchmark algorithms (consisting of standalone and deep learning algorithms) reveals the superior performance of the proposed algorithm. This study highlights the potential of Nature-Based Solutions and nature-inspired algorithms in groundwater management applications, providing valuable insights for policymakers and stakeholders involved in ensuring groundwater sustainability.
Characterization of wormhole dissolution in different fractal dimensionless fractures
Authors: Zhang Yutian , Xie Jinfeng , Wang Fengqiao , Gao Yilei , Ling Bowen , Wang Xiaoguang
Published: March 2024

Wormhole dissolution is a key phenomenon in various underground geo-engineering applications, such as carbon dioxide sequestration, contaminant migration in groundwater and petroleum reservoirs stimulation. It can create conductive channels for fluid flow and significantly enhance the permeability of fractured reservoirs. Fractal dimension is an important parameter to characterize the fracture surface topography. We employ a Fourier-transformation based approach to generate different fractal dimension fracture surfaces, and two mated surfaces with a specified aperture can form artificial fractured 3D rocks. We use the lattice Boltzmann method to simulate the wormhole dissolutions in 3D fractured rocks by varying Péclet and Damköhler numbers. We analyze the permeability evolutions and aperture spatial distributions under different Pe and Da conditions. Our simulations indicate that the fractal dimension has a non-linear effect on permeability change. It implies that, for a given fractured rock, the permeability evolution rate increases as both Pe and Da numbers increase; for the same Pe and Da conditions, when Pe and Da are both small, the permeability evolution rate decreases as the fractal dimension increases; however, when Pe and Da are both large, the permeability evolution rate increases as the fractal dimension increases. Based on the aperture spatial distribution analysis, we find that when the ratio of Da to Pe is large, the inlet regions are almost completely dissolved, which would slow down the rate of permeability increase.
Implementation and application of ABAQUS-PFC3D coupling program framework based on CFD-DEM fluid-solid coupling model: indoor test scale and engineering scale
Authors: Xie Qiang , Cao Zhilin , Sun Weichen , Song Zhanping , Fu Xiang , Ban Yuxin
Published: March 2024

In this study, an ABAQUS-PFC3D coupling program framework based on the Computational Fluid Dynamics (CFD)-Discrete Element Method (DEM) coupled fluid-solid analysis method is constructed, which can be run in Windows computer system and Python language environment, and takes into account the high efficiency, simplicity, and computational stability of the bi-directional interaction of fluid-solid field information. The coupled program framework is validated using a classical particle-fluid coupling model case to assess its stability and accuracy. Further, the ABAQUS-PFC3D coupling program is used to study the evolution characteristics of internal erosion of gap-graded soil-rock mixtures of different fines contents (indoor test scale) and reproduce the whole process of water and mud-surge disaster in the Yonglian water-rich fault tunnel in Jiangxi, China, including the disaster-causing stages of palm collapse, accumulation of broken rock inside the tunnel, collapse within the fault, and surface collapse (engineering scale). The results show the stability of the coupling program framework, which improves a good reference for the popularization and application of the CFD-DEM fluid-solid coupling model.
Rapid nitrate formation during a dust-to-haze episode in a semi-arid city near the dust source regions
Authors: jiayun Li
Published: March 2024

Mineral dust can accelerate secondary aerosol formation under humid conditions, it is unclear whether it can promote secondary aerosol formation under dry conditions. Two-years comprehensive observations was conducted at a semi-arid site, near the dust source regions to illustrate this issue. Three types of episodes, including dust, anthropogenic-dominated and mixed episodes (mixed with dust and anthropogenic aerosols) were selected. Compared with the anthropogenic episodes under humid conditions, rapid nitrate formation was still observed in the mixed episodes under dry conditions, suggesting active metallic oxides in dust, like titanium dioxide, could promote the photochemical reactions of nitrogen dioxide (NO2). The detailed evolution processes were further illustrated by a typical dust-to-mixed episode. After the arrival of the dust, the titanium sharply increased tenfold, a rapid nitrate formation was observed, together with a fast increase in the two most important photochemical pollutants ozone and peroxyacetyl nitrate. The increased secondary organic carbons further illustrated the suspended dust particles accelerated the atmospheric oxidative capacity, therefore enhancing secondary aerosol formation and eventually leading to haze pollution. These results are different from those in humid regions and therefore expands the scientific understanding of the impacts of dust aerosols on haze pollution under dry conditions.
A Novel Method for Analyzing Dissolved Organic Matter in Soils
Authors: Gan Shuchai , Wang Faming , Wu Ying
Published: March 2024

Soils and sediments hold the most carbon in land ecosystems, primarily as mineral-bound or solid matter. Within these, dissolved organic matter (DOM) is a minor but highly active substance aiding in soil cohesion, carbon storage, and the global carbon cycle. Essential for microbial energy and plant nutrition, DOM also transports pollutants and signals environmental changes.
We developed a novel method for analyzing dissolved organic matter (DOM) in the intricate matrices of soil environments. This novel approach represents a significant advancement in the quantification and characterization of soil organic matter (SOM), establishing essential methodological foundations for delving into the carbon cycle within soils.
By incorporating Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) coupled with induction-based nano-spray Ionization, we were able to dissect the composition of DOM within interstitial waters meticulously. The level of detail achieved uncovered nearly 10,000 distinct DOM species from less than 1 µL of sample, which is only 0.01% of the sample size required by the conventional method. These insights reveal that current models may vastly underestimate the heterogeneity of DOM. Soil DOM was not dominated by lignin-like or CRAM compounds, as determined using the conventional method. The novel method revealed more peptide/carbohydrate-like compounds, highly condensed aromatics, and more than double the number of CHNO compounds. A more complete understanding of DOM will allow us to elucidate the biogeochemical processes of nutrient and DOM. The implications of this research expand our comprehension of DOM diversity and contribute a theoretical basis for subsequent exploration of carbon cycling within soil and sedimentary contexts.
Urban water challenges in Chinese cities – Sponge City program: initiatives, progress, challenges and opportunities on NBS and urban agriculture
Authors: Chan Faith Ka Shun , Zhu Yong-Guan , Li Gang , Feng Meili , Xu Mengxia , Xie Linjun , Lu Xiaohui , Zhu Zhe , Wang Jiayu , Lu Lingwen , Liu Sitong , Wang Zilin , Chen Wei-Qiang
Published: March 2024

‘Sponge City’ is the term used to describe the Chinese government’s approach to urban surface water management. The concept was conceived in 2014 in response to an increasing incidence of urban surface flooding in many Chinese cities. While ambitious and far-reaching in its aim (of reducing national flood risk, increasing water supply and improving water quality), the initiative must be implemented by individual municipal-level government entities. In this seminar, Faith will provide the latest updates on the urban flood conditions of Chinese cities. The latest response and recovery processes will be introduced such as using the case from the Ningbo and the success of improving flood resilience. Through climate, environmental and socio-economic factors such as media analytics and socio-technological approaches such as NBS and Urban Agriculture rather than only relying on conventional engineering solutions. These practices can all influence how the National guidelines are implemented (governance), and better integration and assessment are found to contribute a better urban future in China and elsewhere. 
A semi-automatic method using remote sensing for rice crop loss estimation due to flood 
Authors: Mishra Bhogendra , Poudel Shobha
Published: March 2024

 Nepal relies heavily on agricultural production for food security and economic growth, with rice being a major staple crop that accounts for more than 25% of the country's agricultural contribution. The main rice growing season (June to October) is particularly vulnerable to monsoon rainfall-induced flooding damage. Accurate and transparent methods are crucial to assess rice crop damage and support mitigation and disaster response strategies in the country. This study developed a framework for rapid pre- and post-event crop status assessment using optical and microwave remote sensing images and estimate the actual loss based on its timing and intensity. The framework combines Sentinel 2 A/B images with Sentinel 1 SAR images to map rice areas, identify areas at risk, and quantify crop loss due to flooding. The crop status at the moment of flooding is estimated through time series analysis of rice phenology. The inundation area map and its temporal dynamics were developed using Sentinel 1 SAR images during the flooding and post-transplantation months. Statistical analysis was performed on the time-series pre- and post-flooding status of the rice crop to estimate rice yield loss and, finally, automate the method used in the region for yield loss estimation due to flooding in rice-growing areas. 