Reservoir Level Research Articles

Assessment of Groundwater Response Scenarios for Surrounding Areas After Filling the Proposed Badush Dam Reservoir, Northern Iraq

In the current study, the depth of groundwater was detected in (39) wells in the banks surrounding Tigris River between Mosul and Badush dams, and then the maps of depth and level of groundwater were drawn. To predict the response of groundwater behavior in the banks of Badush reservoir in the strips adjacent to the river when starting the filling process, the lines of selected water levels in Badush dam were plotted on the map of groundwater equipotential lines to detect the areas confined between the water level in the reservoir and the same level for groundwater. It is assumed that these areas are affected by the bank storage; therefore, they are prone to leakage or geotechnical problems within the zone of engineering facilities foundations including Badush Dam itself, the regulatory dam and infrastructure projects. In the pre-storage stage, it is noted that the area of influence of the bank storage is very limited and does not exceed 2 km2 on each side of the river in the area very close to the dam. When the water level raises more at the beginning of the storage, the area of influence of the bank storage will extend towards the upstream close to the river meandering. The effect on the eastern bank (left) will be wider compared to the situation in the western bank (right) where the effect is limited. The eastern side is characterized by having a higher population density and more urban establishments; therefore, the foundations of these establishments will be more affected. The area affected by the bank storage continues to widen towards upstream with the increase in the level of the dam reservoir until the effect reaches the maximum limit and approaches the shoulders of the regulatory dam, when the water levels in Badush reservoir are more than 245 m above sea level (a. s. l.). The variation in the groundwater extension effect with the continuous or gradual filling of reservoir requires monitoring and caution during filling, for fear of affecting the geotechnical properties of the soil and rocks within the foundations zone, and thus affecting the stability of the two dams.

Using Remote Sensing to Study Impact El Niño Southern Oscillation on Reservoir Level at Murum and Bakun Dam Hydropower, Sarawak

In the years 2015 and 2016 has happened El Niño phenomenon was one of the three worst in history that has been happened since 1908. The El Niño phenomenon is usually related to the drought in Southeast Asia, Asia Pacific, and the Caribbean. This study analyses the impact of El Niño in the year 2015/2016 on rainfall at Bakun and Murum Hydropower using the technique of remote sensing. Global Precipitation Measurement (GPM) satellite was applied to understanding, the impact of 2015/2016 El Niño on rainfall at Bakun and Murum Hydropower. The results of this study show that drought conditions are widespread have reduced the total amount of rainfall and reservoir level and led to unusually low lake levels in Bakun and Murum reservoirs. Better understand the hydrological response and the complexity of different methods. The study found the rainfall decrease 20 until 30 % from normal during neutral and reduced 25 until 30 meters above sea level the reservoir water level at Murum and Bakun dam during the El Niño 2015/2016. The impact approach can support the design of more adaptive management strategies for specific areas.

Optimizing the Flood Limit Water Level of Reservoirs in Sediment-Laden Rivers under Changing Water and Sediment Conditions: A Case Study of the Xiaolangdi Reservoir

Optimizing the flood limit water level (FLWL) of reservoirs in sediment-laden rivers under changing water and sediment conditions is an important research topic that could improve comprehensive utilization benefits. Because reservoir operation has multiple objectives in sediment-laden rivers, this study established a water–sediment mathematical model, a comprehensive benefit evaluation model, and an evaluation index system. Taking the Xiaolangdi Reservoir of the Yellow River as an example, the operation mode of the FLWL under changing water and sediment conditions was studied. Under the scenarios of incoming sediment amounts of 300–800 million tons, when using the operation mode of gradually raising the FLWL, the sediment retention period was 4–13 years longer; the lower average annual siltation of the downstream channel and minimum bank-full discharge of the downstream channel after 50 years was larger by 150–260 m3/s than the operation mode of raising the FLWL at one time. However, with enhanced benefits of sediment blocking and siltation reduction, other benefits such as water resources supply, hydropower generation, and ecological improvement are reduced. The average annual number of days that do not meet the downstream water resources supply requirements, irrigation, and ecological improvement was increased by 0.64–2.16 days, and 91–197 million kW·h reduced average annual hydropower generation. The critical amount of incoming sediment was 350 million for conversion between the two FLWL operation modes, and it will increase to 450 million tons if the incoming runoff of the Yellow River increases by 20%. After constructing the Guxian Reservoir in the middle of the Yellow River, the critical amount of incoming sediment will increase to 600 million tons. This study is of great significance for improving the utilization efficiency of water resources and promoting the socio-economic development of river basins.

Numerical Simulation and Sensitivity Analysis of Sediment Issues in Pumped Storage Power Stations: Sediment Conveyance of Turbine and Sedimentation of Reservoirs

In this paper, a 1D process-based numerical model is established to study the sediment concentration via the turbine (TSC) and sedimentation of the lower reservoir and the upper reservoir of a certain pumped storage power station (PSPS), which is intended to be built on a sandy river. In addition, the sensitivity of TSC to some factors, such as suspended sediment gradation, the water level of the lower reservoir, and the coefficients of the sediment-carrying capacity formula, are analyzed in this paper. It is revealed that (1) the TSC will decrease by 30.8~34.5% when the incoming sediments of particle sizes less than 0.002 mm (which accounts for 3.95% of the totality) are replaced with incoming sediments of particle sizes between 0.002 mm and 0.004 mm. At the same time, the sedimentation thickness of the upper reservoir will decrease by 20.9%, and the siltation rate of the lower reservoir will increase by 2.4%. (2) The TSC will decrease by 12.6~13.1% as the water level of the lower reservoir rises by 17.55 m. This represents an increase of 8.4% in the average water depth and 26.4% in the storage capacity of the lower reservoir. At the same time, the sedimentation thickness of the upper reservoir will decrease by 32.2%, and the siltation rate of the lower reservoir will increase by 2.5%. (3) The TSC will decrease by 1.2~1.4% as the index of the sediment-carrying capacity formula m changes from 1.12 to 0.666, and the coefficient of the sediment-carrying capacity formula K changes from 0.2 to 0.6. At the same time, the sedimentation thickness of the upper reservoir will decrease by 7.2%, and the siltation rate of the lower reservoir will increase by 1.7%. Through the research on the sensitivity of the TSC, the direction and amplitude of the TSC changes with the boundary conditions are found, which provides a basis for the scheme comparison of specific projects and further supplements the prediction method system of the TSC. Meanwhile, the results remind researchers to pay more attention to the determination of boundary conditions and also provide the basis for the error analysis of the TSC. In summary, the results have certain guiding significance for the related research, and the sensitivity analysis results of the case could provide a reference for other specific projects.

Magmatic volatile content and the overpressure ‘sweet spot’: Implications for volcanic eruption triggering and style

Volatile exsolution is widely considered to be capable of generating magmatic overpressure and triggering volcanic eruptions. Despite its role as an eruption trigger, exsolution-driven overpressurisation is relatively poorly understood. Part of the problem is that thermodynamic models do not consider how the behaviour of small quantities of magma scales up to reservoir level – where variations in temperature and crystallinity become important. In contrast, many thermomechanical models focus only on magma injection, and do not consider how overpressure evolves spatially or temporally, when related to crystallisation and volatile exsolution. Here, we use Rhyolite-MELTS to track exsolution-driven overpressure during cooling for a variety of natural compositions, storage pressures, initial volatile contents and magmatic XH2O (molar H2O/ (CO2 + H2O)). We then couple these outputs to a thermal model to determine the timescales and spatial extent of overpressurisation with varying volatile content.We find that the highest overpressures occur in magmas which are initially at their H2O solubility limit, with the addition or removal of H2O resulting in a decrease in peak overpressure. We also find that maximum overpressure decreases with the addition of CO2 (decreasing XH2O) at typical magma storage pressures of 100–230 MPa. The higher overpressures generated at the volatile ‘sweet spot’ have a greater potential to trigger eruptions – or to favour their initiation by making the system more susceptible to other triggers, such as magma injection. The reduction in overpressure with increasing or decreasing initial H2O suggests that triggering by volatile exsolution is less likely for these magmas. Peak overpressure at the volatile sweet spot also coincides with an increased incidence of explosive eruptions at water contents ∼4–5.5 wt%. This suggests that higher magmatic overpressures may produce more explosive eruptions, by driving faster initial ascent rates and decreasing outgassing efficiency in the conduit. Our thermal modelling demonstrates that, for small magmatic systems, exsolution-driven overpressurisation can operate on timescales which are much shorter than the crustal relaxation timescale. In these cases, overpressure cannot be dissipated by a visco-elastic crustal response, and therefore has the potential to trigger a volcanic eruption.

Groundwater Flow Model along a Vertical Profile of the Sardas Landfill in Sabiñánigo, Huesca, Spain

Lindane (a harmful contaminant) was produced in Sabiñánigo (Huesca, Spain) and deposited at the Sardas landfill. This site contains a large mass of pollutants, which have an extremely large contamination potential of the Ebre River. The site has undergone numerous human interventions that have modified the natural conditions. The site exhibits complex hydrogeological patterns and has been monitored systematically for a long period of time, and a large amount of geological, hydrological, and hydrogeological data are available. Here, a 2D finite element groundwater flow model along a vertical profile heading east–west along the thalweg of the former gully is presented. The main goal is modelling groundwater flow through the landfill, the Gállego River alluvial aquifer, and its interactions with the Sabiñánigo reservoir. The numerical model confirms the prevailing conceptual hydrogeological model of the site. The main results include: (1) Groundwater flows into the landfill mainly along perimeter ditches, which do not properly drain the surface and subsurface runoff (13.84 m3/d) and from the underlying marly rock (8.84 m3/d); (2) The total landfill leachate outflow towards the alluvial floodplain underneath the front slurry wall through a shallow marl layer is equal to 17 m3/d; (3) The oscillations of the Sabiñánigo reservoir water level produce a tidal effect that results in periodic changes of the hydraulic gradient between the alluvial gravels and the reservoir; (4) Groundwater flows generally from the alluvial aquifer towards the reservoir in an average E–W direction with an average Darcy velocity equal to 5 cm/d. The flow direction, however, changes to W–E when the reservoir level rises suddenly and; (5) The hydrodynamic parameters of the alluvial silts and reservoir silting sediments are crucial in determining the influence radius of the inversion of groundwater flow direction when the reservoir level rises suddenly. Model results enhance the confidence of the conceptual model, provide the basis for detailed specific models of the landfill and the alluvial aquifer, and highlight the importance of considering the tidal effect of the reservoir level oscillations. They also provide valuable information for managing the landfill and its impact on the surrounding groundwater system.

Optimization of Reservoir Level Scheduling Based on InSAR-LSTM Deformation Prediction Model for Rockfill Dams

The Xiaolangdi reservoir has a storage capacity of more than 10 billion cubic meters, and the dam has significant seasonal deformation. Predicting the deformation of the dam during different periods is important for the safe operation of the dam. In this study, a long short-term memory (LSTM) model based on interferometric synthetic aperture radar (InSAR) deformation data is introduced to predict dam deformation. First, a time series deformation model of the Xiaolangdi Dam for 2017–2023 was established using Sentinel-1A data with small baseline subset InSAR (SBAS-InSAR), and a cumulative deformation accuracy of 95% was compared with the on-site measurement data at the typical point P. The correlation between reservoir level and dam deformation was found to be 0.81. Then, a model of reservoir level and dam deformation predicted by neural LSTM was established. The overall deformation error of the dam was predicted to be within 10 percent. Finally, we used the optimized reservoir level to simulate the deformation at the measured point P of the dam, which was reduced by about 36% compared to the real deformation. The results showed that the combination of InSAR and LSTM could predict dam failure and prevent potential failure risks by adjusting the reservoir levels.

Generation and distribution of overpressure in ultra-deep carbonate reservoirs controlled by intra-cratonic strike-slip faults: The Ordovician of Shuntuoguole area in the Tarim Basin

The strike-slip fault-controlled ultra-deep fractured-vuggy carbonate reservoir is an increasingly important exploration target. However, the high heterogeneity of fault-controlled reservoirs and the ineffective methods available for pressure prediction make it difficult to assess the risk of potential overpressure in ultra-deep carbonate reservoirs. Abnormal overpressure is common in the ultra-deep strike-slip fault-controlled carbonate reservoirs in the Shunbei Oilfield of the Tarim Basin. According to measured pressures, petroleum accumulation history, and fault framework, this study investigates the generation mechanisms of overpressure in fault-controlled carbonates and reconstructs the pressure evolution of reservoirs. Finally, the effect of strike-slip faults on current overpressure distribution is discussed. Measured pore pressure data from 90 wells showed that all reservoirs present in the major fault zones are normally pressured, and the reservoirs present far away from the major faults commonly develop overpressures. The distribution patterns of overpressure in the Middle-Lower Ordovician reservoirs coincide with areas with fault reactivation during the Himalayan Period. The results of the comprehensive analysis of petroleum accumulation history, fault activity, and well production suggested that dry gas generation is a primary cause of overpressure in the Middle-Lower Ordovician reservoirs. The relatively low temperature in the reservoir, in addition to the highly compartmentalized nature of overpressure, indicated that these overpressured gas migrate vertically into the Ordovician formation from deep strata along strike-slip faults. The pressure evolution restored by basin modelling and fluid inclusion showed that distinct differences in overpressure magnitude in the different reservoirs were formed at the stage of gas charging but not at the early stages of oil accumulation. The difference in physical properties of the two types of fault-controlled reservoirs resulted in different pressure distributions and oil-bearing levels in the ultra-deep carbonate reservoirs at present. The strike-slip fault zones are the primary pathways by which overpressured fluids migrate from the deeper Cambrian formation into the Ordovician reservoirs and act as barriers to separate the pressure systems in the ultra-deep carbonate reservoirs. These findings are expected to help mitigate the drilling risks with overpressure in deep strike-slip fault-controlled carbonate reservoirs.

Smart Home Remote Control System Prototype Using Internet of Things (IoT) Based ESP8266 Microcontroller

Technology is developing very rapidly in the current era, there will be several impacts that will result from the development of technology. Electronic equipment control can be done remotely in real time using the IoT system. The problem faced is the concern when leaving home. Because when leaving the house, homeowners sometimes often forget about electronic devices whether they are turned off or still on. IoT can be utilized at home as a smart home system by connecting an electronic device to an android application. This IoT-based smart home system uses an ESP8266 microcontroller which is used to connect between hardware and software that is controlled through the Blynk application. Blynk application is used as an interface that functions to provide input and produce output. This system consists of four sensors, namely the MQ2 sensor to detect gas leaks in the kitchen, the DHT11 sensor to determine the level of humidity and temperature in the bedroom, the PIR sensor to detect human movement at the front entrance, the ULTRASONIC sensor as a detector of the water level in the water reservoir and using three relays as a connector for lights and other electronic components. And using the Blynk application as a control system on the ESP8266 microcontroller.

Permeability Tests and Numerical Simulation of Argillaceous Dolomite in the Jurong Pumped-Storage Power Station, China

Due to its poor hydro-physical properties and other characteristics, argillaceous dolomite is susceptible to seepage failure under high water pressure, affecting the seepage stability of a rock mass. To ensure the safety of the project, when the argillaceous dolomite is present, it is necessary to study the conditions pertaining to its seepage failure. Taking the argillaceous dolomite of Jurong Pumped Storage Power Station as the research object, the spatial distribution, occurrence, scale, degree of weathering, and mechanical and hydrogeological characteristics of the argillaceous dolomite were studied. Through on-site water pressure tests and laboratory variable head tests, the permeability characteristics of argillaceous dolomite were analyzed, and the hydraulic conductivity of the argillaceous dolomite in the upper reservoir and underground powerhouse areas was quantified. The argillaceous dolomite specimens were collected, and seepage failure tests were conducted to determine the critical water pressure for its seepage failure. Based on the results of the laboratory tests, a numerical model of groundwater flow was established. By changing the water level of the upper reservoir and the measures of the anti-seepage and drainage, the seepage stability of the argillaceous dolomite was discussed. The actual water pressure of argillaceous dolomite in the underground powerhouse area was identified during the operation of the Jurong pumped-storage power station. The calculations show that when fully enclosed anti-seepage and drainage measures are taken for the underground powerhouse, the maximum head of water is 98 m, which is lower than the critical water pressure of seepage failure for the argillaceous dolomite. Therefore, no seepage failure will occur. The results provide a scientific basis for the anti-seepage and drainage design of the underground powerhouse area.

Deciphering the black box of deep learning for multi-purpose dam operation modeling via explainable scenarios

Operational rules of a multi-purpose dam are hidden due to missing of the records for decision-making processes. This study aims to assess the explainability of a deep learning model for the multi-purpose dam operation of Seomjin River, Juam, and Juam Control dams in the Seomjin River basin, South Korea. In this study, the Gated Recurrent Unit (GRU) algorithm is employed to predict the hourly water level of the dam reservoirs over 2002–2021. First, the GRU models are trained and validated using the local dam input (precipitation, inflow, and outflow) and output (water level) data to examine similarity/singularity in the operational patterns of these three dams. The hyper-parameters are optimized by the Bayesian algorithm. Secondly, the sensitivity test of the trained GRU model to altered input data (−40%, −20%, +20%, and +40%) is conducted to understand how the GRU models facilitate the input data to simulate the target output data (herein, hourly water level), which is known as explainability scenarios. Results show that the trained GRU models predict the hourly water level well across the three dams (above 0.9 of the Kling-Gupta Efficiency). Results from the explainability scenarios show a linear response to the altered inflow rates, but no response to altered precipitation. Furthermore, the GRU models show a site-specific response to altered outflow rates, depending on whether the observed outflow rate-water level relationship is linear or not. This study hints how to decipher the black box of deep learning in multi-purpose dam operation modeling via explainable scenarios.

Characteristics of energy evolution and acoustic emission response of concrete under the action of acidic drying-saturation processes cycle

The continuous fluctuation in the acidic mine water level of the underground reservoir will affect the artificial dam's strength and stability. The uniaxial compression test of C25 concrete under different drying-saturation processes cycle (DSPC) numbers and pH solutions were performed. The degradation mechanism of mechanical properties of concrete under acidic DSPC was investigated; the calculation formula for the elastic strain energy at peak stress has been corrected and the energy evolution law has been obtained; besides, the evolution characteristics of acoustic emission (AE) parameters were studied using multi-fractal theory and the precursor characteristics of concrete failure were obtained. The results revealed that increasing the DSPC times or decreasing the pH caused an increase in the saturation moisture content of the concrete, the strain and elastic strain energy of the concrete at peak stress increased, a drop in the ultrasonic velocity, the uniaxial compressive strength (UCS), the elastic modulus (EM) and the overall input energy. The accumulated ringing count and accumulated energy of AE dramatically increased before the concrete was close to failure, and numerous low-frequency and high-amplitude signals started to appear. The information mentioned above might be considered a short-impending warning of concrete failure. During the plastic deformation, the large increase of the multi-fractal parameter Δα and the significant drop of Δf might be viewed as early warning for concrete failure. This research will offer some theoretical direction for artificial dam design and long-term stability monitoring in underground reservoirs.

Data-driven modeling of municipal water system responses to hydroclimate extremes

Abstract Sustainable western US municipal water system (MWS) management depends on quantifying the impacts of supply and demand dynamics on system infrastructure reliability and vulnerability. Systems modeling can replicate the interactions but extensive parameterization, high complexity, and long development cycles present barriers to widespread adoption. To address these challenges, we develop the Machine Learning Water Systems Model (ML-WSM) – a novel application of data-driven modeling for MWS management. We apply the ML-WSM framework to the Salt Lake City, Utah water system, where we benchmark prediction performance on the seasonal response of reservoir levels, groundwater withdrawal, and imported water requests to climate anomalies at a daily resolution against an existing systems model. The ML-WSM accurately predicts the seasonal dynamics of all components; especially during supply-limiting conditions (KGE > 0.88, PBias < ±3%). Extreme wet conditions challenged model skill but the ML-WSM communicated the appropriate seasonal trends and relationships to component thresholds (e.g., reservoir dead pool). The model correctly classified nearly all instances of vulnerability (83%) and peak severity (100%), encouraging its use as a guidance tool that complements systems models for evaluating the influences of climate on MWS performance.

Deformation triggers and stability evolution of landslide from multiple observations

External causes like changes in reservoir level and intense rainfall can cause reservoir landslides. Exploring the factors that govern landslide deformation and analyzing its stability evolution is essential in mitigating the associated risks. The Sanzhouxi landslide, which has experienced ongoing movements and has been implemented a professional monitoring system, is chosen for analysis in this paper. A combination of geological survey and analysis of monitoring data is utilized to explore landslide deformation characteristics. A data mining method, grey relation analysis (GRA), is subsequently performed to determine the causes of landslide deformation. Furthermore, the stability of the Sanzhouxi landslide in response to reservoir level fluctuation and rainfall for each day over an entire year is assessed using the Morgenstern-Price (MP) approach in 2D GeoStudio software. Such a process illustrates clearly how the landslide stability alters with external triggers changing. The findings reveal that the landslide deforms variably in spatial and temporal. The reservoir level rising contributes to landslide deformation primarily, while rainfall has a secondary impact. The factor of safety (FS) of the Sanzhouxi landslide drops from 1.17 to 1.07 during high reservoir water level periods and remain the same or increase in other periods except for some transitory moments while decreasing only by about 2% under the effect of rainfall. The daily FS results validate the dominant influence of reservoir level fluctuation on the stability of the landslide. The comprehensive understanding of landslide movement based on deformation characteristics, triggering factor identification, and daily stability validation, contributes to realizing nearly real-time prediction and evaluating the risk due to slope movements in similar geological settings worldwide.

Socio-economic advancement and grid-frequency control of a wind farm-PHS-solar connected EV hybrid electrical system considering imbalance prices

The Independent System Operator (ISO) plays a key role in a competitive electrical system by controlling the market with the received bidding from the different market participants. The ISO settled the energy at the location-based marginal pricing (LBMP) where all the participants get economic benefits. In the renewable combined system, the future renewable power production data need to be submitted to the ISO at least one day before the operation. There is always a chance for not fulfilling the contracted power due to the volatile nature of the renewable which creates an imbalance price in the system. In this situation, energy storage systems can alleviate the imbalance issues by supplying additional power to the electrical grid. This study proposes a two-phase scheduling technique for the optimum operation of a wind farm (WF)–pumped hydro storage (PHS)–solar-connected electric vehicle (EV) hybrid system to obtain more economic profit and revenue with a stable grid frequency. In the first phase, the energy level of PHS upper reservoirs has been scheduled to maintain the grid frequency with the presence of a wind farm. Along with the first phase, additionally solar-connected EVs are incorporated in the second phase to maximize the system profit further to get more economic benefit. A modified IEEE 30 bus system is used to effectively assess the aforesaid approach. MiPower software has been used to conduct this work. This proposed method has been compared with the existing method and got better results in all aspects.

Gut dysbiosis associates with cytokine production capacity in viral-suppressed people living with HIV.

People living with human immunodeficiency virus (PLHIV) are exposed to chronic immune dysregulation, even when virus replication is suppressed by antiretroviral therapy (ART). Given the emerging role of the gut microbiome in immunity, we hypothesized that the gut microbiome may be related to the cytokine production capacity of PLHIV. To test this hypothesis, we collected metagenomic data from 143 ART-treated PLHIV and assessed the ex vivo production capacity of eight different cytokines [interleukin-1β (IL-1β), IL-6, IL-1Ra, IL-10, IL-17, IL-22, tumor necrosis factor, and interferon-γ] in response to different stimuli. We also characterized CD4+ T-cell counts, HIV reservoir, and other clinical parameters. Compared with 190 age- and sex-matched controls and a second independent control cohort, PLHIV showed microbial dysbiosis that was correlated with viral reservoir levels (CD4+ T-cell-associated HIV-1 DNA), cytokine production capacity, and sexual behavior. Notably, we identified two genetically different P. copri strains that were enriched in either PLHIV or healthy controls. The control-related strain showed a stronger negative association with cytokine production capacity than the PLHIV-related strain, particularly for Pam3Cys-incuded IL-6 and IL-10 production. The control-related strain is also positively associated with CD4+ T-cell level. Our findings suggest that modulating the gut microbiome may be a strategy to modulate immune response in PLHIV.

The Impact of Green Institutional Pressure from Local Governments on Corporate Innovation: An Empirical Evidence from Foreign-Invested Enterprises in China

The natural environment of the human world has been deteriorating over the past few decades, and policies to protect the environment are receiving increasing attention from governments worldwide. The question of how green institutional pressures from local governments impact corporate behaviors, especially innovation behaviors, is a critical issue. However, the link between local governments’ institutional pressures and corporate innovative behaviors remains a matter of some dispute. This paper compiles data from foreign-invested enterprises in China, using the frequency of green development terms in the Chinese local governments’ annual reports as a key variable, and discusses the influence of local governments’ green institutional pressure on corporate innovation. The conclusions of this paper demonstrate that local governments’ institutional pressure has a promoting effect on corporate innovation, while the home country’s level of green knowledge reservoir has a negative moderating effect on this influence. Moreover, this conclusion exhibits heterogeneity across corporate nature, industry attributes, location characteristics, export experience and home country type.

Quantifying thresholds for advancing impact-based drought assessment using classification and regression tree (CART) models

Drought events can significantly impact water resources, agriculture, and socioeconomic sectors. Droughts are often quantified using numerous indices, which are widely used for forecasting, risk assessments, and spatiotemporal analysis. Quantifying the appropriate linkage between drought indices and their impact on hydrological and agricultural indicators will improve hazard communication with stakeholders and further advance impact-based forecasting tools. This study aims to quantify the thresholds associated with drought indices that can capture the intricate connection between droughts and impact-specific indicators. We investigated the performance of several drought indices, such as Palmer-based (e.g., PDSI, PMDI, and PHDI) and multiscale drought indices (e.g., SPI and SPEI) with the impact-specific indicators of hydrological (e.g., streamflow and reservoir level) and agricultural (soil moisture and crop yield) indicators. The 'threshold' values associated with drought indices with impact-specific indicators are quantified using the classification and regression tree (CART) algorithm. Our results suggest that the decision tree approach is suitable for identifying critical thresholds of drought indices associated with a range of hydrological and agricultural indicators relevant to the stakeholder's application to different sectors. The drought characteristics derived from selected indices broadly vary during extreme events. The results further indicate that the threshold associated with each drought index and the impact-specific indicator varies drastically within the same climate division. We argue that quantifying the drought indices thresholds can provide valuable information for impact-based monitoring and forecasting.

Multi-level ultra-deep fault-controlled karst reservoirs characterization methods for the Shunbei field

Ultra-deep carbonate fault-controlled reservoirs are characterized by large burial depths, low dissolution degrees, strong heterogeneity, and limited effective well data. Accurate 3D characterization based on seismic data is essential for efficient development of this type of reservoir. However, traditional seismic prediction methods are insufficient to accurately characterize different reservoir levels in the exploration and development of fault-controlled ultra-deep reservoirs. We propose a set of improved multi-level characterization methods for fault-controlled reservoirs. The improved methods could recover seismic information obscured by strong reflections and reduce the uncertainty of seismic interpretation. This study combined seismic strong reflection suppression and sedimentary strata seismic reflection interference elimination, proposed improved inversion methods, and advanced attribute calculation methods to improve the identification accuracy of reservoirs. In particular, we proposed the karst cave carving method based on improved inversion method and karst cave enhancement algorithm, the dissolved pore zone identification method based on optimization energy envelope algorithm, and the fault-fracture zone characterization method based on optimized atomic decomposition texture contrast. These methods were thoroughly validated by theoretical 3D models and field data. The proposed multi-level characterization methods can effectively improve the identification accuracy of fault-controlled karst reservoirs, provide a benchmark for predicting similar strong heterogeneous carbonate reservoirs, and provide reliable support for further facies modeling.

Vegetation Representation Influences Projected Streamflow Changes in the Colorado River Basin

Abstract Vegetation parameters for the Variable Infiltration Capacity (VIC) hydrologic model were recently updated using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). Previous work showed that these MODIS-based parameters improved VIC evapotranspiration simulations when compared to eddy covariance observations. Due to the importance of evapotranspiration within the Colorado River basin, this study provided a basin-by-basin calibration of VIC soil parameters with updated MODIS-based vegetation parameters to improve streamflow simulations. Interestingly, while both configurations had similar historic streamflow performance, end-of-century hydrologic projections, driven by 29 downscaled global climate models under the RCP8.5 emissions scenario, differed between the two configurations. The calibrated MODIS-based configuration had an ensemble mean that simulated little change in end-of-century annual streamflow volume (+0.4%) at Lees Ferry, Arizona, relative to the historical period (1960–2005). In contrast, the previous VIC configuration, which is used to inform decisions about future water resources in the Colorado River basin, projected an 11.7% decrease in annual streamflow. Both VIC configurations simulated similar amounts of evapotranspiration in the historical period. However, the MODIS-based VIC configuration did not show as much of an increase in evapotranspiration by the end of the century, primarily within the upper basin’s forested areas. Differences in evapotranspiration projections were the result of the MODIS-based vegetation parameters having lower leaf area index values and less forested area compared to previous vegetation estimates used in recent Colorado River basin hydrologic projections. These results highlight the need to accurately characterize vegetation and better constrain climate sensitivities in hydrologic models. Significance Statement Understanding systemic changes in annual Colorado River basin flows is critical for managing long-term reservoir levels. Single-digit percentage decreases have the potential to degrade the regions’ water supply, hydropower generation, and environmental concerns. Hydrology projections under climate change have largely been based on simulations from the Variable Infiltration Capacity model. Updating the model’s vegetation representation based on updated satellite information highlighted the sensitivity of the hydrologic projections to the models’ vegetation representation primarily within forested areas. This updated model did not increase in evapotranspiration by the end of the century as much as previous simulations. This increased the mean and ensemble spread of the projected streamflow changes, emphasizing the need to properly characterize the hydrologic model’s vegetation parameters and better constrain model climate sensitivity.