Hydrodynamic Model Simulations Research Articles

Assessment of Mangrove Cover Change Based on Combining Remote Sensing Technique and Hydrodynamic Model Simulation

Mangrove ecosystems along Vietnam's coastline face significant degradation due to human activities, despite their crucial role in coastal protection against natural hazards. This study aims to assess the spatial and temporal changes in mangrove coverage along Vietnam's southern coast by integrating remote sensing techniques with hydrodynamic model simulations. The research methodology combines the Collect Earth tool analysis of Spot-4 and Planet satellite imagery (2000-2020) with Mike 21-HD two-dimensional (2D) hydrodynamic modeling to evaluate mangrove coverage changes by simulating shoreline erosion. Results analysis reveals that a significant increase of 109.83 ha in mangrove area within Vinh Chau Town of Soc Trang Province during the period 2010-2020, predominantly in the eastern region. Hydrodynamic simulations demonstrate that the coastal zone is primarily influenced by the interaction of nearshore currents, East Sea tides, and seasonal monsoon wave patterns. The model results effectively capture the complex interactions between these hydrodynamic factors and mangrove distribution. These findings not only validate the effectiveness of combining remote sensing and hydrodynamic modeling for mangrove assessment but also provide crucial insights for sustainable coastal ecosystem management. The study's integrated approach offers a robust framework for monitoring mangrove dynamics and developing evidence-based conservation strategies, highlighting the importance of maintaining these vital ecosystems for coastal protection.

A hybrid statistical–dynamical framework for compound coastal flooding analysis

Abstract Compound coastal flooding due to astronomic, atmospheric, oceanographic, and hydrologic forcings poses severe threats to coastal communities. While physics-driven approaches are able to dynamically simulate temporally and spatially varying compound flooding generated by multiple partially correlated drivers, computational burdens limit their capability to explore the full range of conditions that contribute to compound coastal hazards. Data-driven statistical approaches address some of these computational challenges, however they are also unable to explore all possible forcing combinations due to short observational records, and projections are typically limited to a few locations. This study proposes a hybrid statistical-dynamical framework for compound coastal flooding analysis that integrates a stochastic generator of compound flooding drivers, a hydrodynamic model, and a machine learning-based surrogate model. The framework is demonstrated in San Francisco (SF) Bay over the past 500 years with high accuracy and computational efficiency. The stochastic generator of compound flooding drivers is developed by coupling a sea surface temperature (SST) reconstruction model with a climate emulator, weather generator, and hydrologic model. Using reconstructed SSTs as input, the generator of compound flooding drivers is employed to simulate time series of the forcing factors contributing to compound flooding in SF Bay. A process-based hydrodynamic model is built to predict total water levels (TWLs) varying in time and space throughout SF Bay based on the stochastically generated drivers. A machine learning-based surrogate model is then developed from a relatively small library of hydrodynamic model simulations to efficiently predict water levels (WLs) for compound flooding analysis under the full range of stochastic drivers. This study contributes a hybrid statistical-dynamical framework to better understand the spatial distribution and temporal evolution of compound coastal flooding, along with the relative contributions of the forcing drivers in complex nearshore, estuarine, and river environments for centennial timescales under past, present, and future climates.

A novel relaxed modified pipe hydrodynamic model for mixed flow simulation

In this study, we propose a novel modified pipe hydrodynamic model with a partial relaxation approach and develop a corresponding numerical algorithm within the framework of the finite volume method for its computation to enable robust, accurate, and comprehensive pipe modeling. The proposed numerical model provides some key improvements compared to existing numerical schemes for simulating mixed pipe flows: (1) it is capable of preserving both moving- and stationary-water steady states, and (2) it effectively reduces post-bore oscillations while maintaining second-order accuracy in the non-pressurized regime for unsteady pipe flows. Such improvements have been verified against theoretical and experimental data through tests involving both smooth and sharp-gradient steady and unsteady flows across various regimes in straight and locally bent circular pipes, which are fundamental elements of stormwater drainage, sewage networks, and industrial process pipelines. The proposed pipe flow model can be further improved regarding post-pore stability by utilizing specific post-bore oscillation suppression techniques, and it can be integrated into a practical hydraulic modeling tool for pipeline networks in future work.

Research on turbulence model parameters for the prediction of waterjet propulsion pump hydrodynamic performance

Abstract The hydrodynamic performance of waterjet propulsion pumps has an important impact on improving the speed of waterjet propulsion ships. High-precision prediction of the hydrodynamic performance of water-jet propulsion pumps based on CFD is of great significance to improving the pump design quality. Based on the Reynolds-averaged Naiver-Stokes equation, this paper conducts a grid-independence verification on a water jet propulsion pump based on hydrodynamic test data, uses the Latin hypercube sampling method to generate SST k-ω turbulence model parameter space calculation samples, performs steady-state calculation on all samples, analyzes the sensitivity of changes in the parameters of the turbulence model to the prediction of the external characteristics of the waterjet propulsion pump, and finally obtains the influence of changes in the parameters of the turbulence model on the prediction of the external characteristics of the pump. Among them, the sensitivities of the three parameters β *, β1 and a1 are higher. The results show that the prediction accuracy of the external characteristics of the water jet propulsion pump can be effectively improved by correcting these three highly sensitive parameters, and the correction values of the three key parameters are obtained. The prediction error of the external characteristics of the water jet propulsion pump is reduced from 4.3% to less than 2.1%. A feedforward neural network is used to establish a mapping model between the three turbulence model parameters and the head coefficient and power coefficient of the waterjet propulsion pump in order to achieve rapid prediction. The genetic algorithm is applied to optimize the weights, thresholds and other coefficients in the neural network, thereby improving the prediction accuracy. Based on the optimized neural network, the genetic algorithm is used to optimize the three turbulence model parameters, and the optimized coefficients are obtained. The optimized turbulence model parameters are put into the hydrodynamic model for RANS simulation to verify the degree of optimization of the model coefficients by the genetic algorithm.

Interacting Influences of Diurnal Tides, Winds, and River Discharge on a Large Coastal Plume

AbstractThe dispersal of large river plumes in the coastal ocean depends on multiple factors, and in some cases, can be categorized into distinct dynamical regimes: a tidally dominated near‐field, a rotational mid‐field, and a coastal current far‐field. In this study, observations and modeling are used to evaluate the factors controlling the variability in the buoyant plume from Mobile Bay. Rather than distinct dynamical regimes, the Mobile Bay plume depends on forcings that act at overlapping temporal and spatial scales: diurnal tides, river discharge events, and winds. Satellite synthetic aperture radar images along with shipboard in‐situ sampling and marine radar are used to observe plume fronts in spring 2021. Hydrodynamic model simulations are compared with observations and used to characterize a large coastal plume at consistent tidal phase across a range of forcing conditions. The along‐shore position of the plume depends primarily on advection by wind‐driven surface currents. The cross‐shore extent and plume area depend primarily on the tidal amplitude and river discharge, and secondarily on northerly (seaward) winds. Along‐shore winds influence the buoyancy anomaly by altering salinity in the estuary and offshore. Upwelling winds increase the buoyancy anomaly and advect previous plumes away from the mouth. Downwelling winds reduce the buoyancy anomaly by trapping previous plumes near the coast and directing freshwater discharge toward a secondary outlet. Thus, the combined, overlapping influences of the tide, wind, and discharge dominate the variability in freshwater delivery to the shelf at time scales of days and distances of tens of km.

A direct two-way coupling of the hydrologic and 1D-2D hydrodynamic models for watershed flood simulation

A direct two-way coupling of hydrologic and 1D-2D hydrodynamic models (DCM2D) for watershed flood simulation was proposed. This coupling included three models (i.e., fully distributed hydrologic, 1D hydrodynamic, and 2D hydrodynamic models) and three coupling strategies: the bidirectionally coupled hydrologic-2D hydrodynamic module, two-way coupled hydrologic-1D hydrodynamic module (HH1D), and two-way coupled 1D-2D hydrodynamic module (HH2D). The refined river links (RLs) were used to couple the hydrologic and 1D hydrodynamic models, and the exchange discharge between these models was determined using either the weir flow equations or hydrologic model, depending on the flow transitions. Four cases were used to evaluate the proposed DCM2D. The results indicated that the discharge obtained from the proposed HH1D exhibited a high level of consistency with analytical solutions, with NSE of 0.986. This finding supported the validity of the proposed coupling schemes for hydrologic and 1D hydrodynamic models, particularly in scenarios where there were no distinct flow transitions. The DCM2D accurately represented the physical flood process by allowing rainfall runoff discharge into both 2D low-lying inundation regions and 1D rivers. This contrasted with the indirect coupling models (ICM2D), which required runoff to enter the 1D rivers before flowing into the 2D inundation regions. It exhibited reasonable flow directions and achieved satisfactory simulation accuracy, with higher NSE compared to the ICM2D. The proposed DCM2D model can effectively adapt to the real-life flood evolution process and offer practical and reliable solutions for simulating floods in watersheds.

Multi-objective optimisation framework for Blue-Green Infrastructure placement using detailed flood model

Designing city-scale Blue-Green Infrastructure (BGI) for flood risk management requires detailed and robust methods. This is due to the complex interaction of flow pathways and the need to assess cost-benefit trade-offs for various BGI options. This study aims to find a cost-effective BGI placement scheme by developing an improved approach called the Cost OptimisatioN Framework for Implementing blue-Green infrastructURE (CONFIGURE). The optimisation framework integrates a detailed hydrodynamic flood simulation model with a multi-objective optimisation algorithm (Non-dominated Sorting Genetic Algorithm II). The use of a high-resolution flood simulation model ensures the explicit representation of BGI and other land use features to simulate flow pathways and surface flood risk accurately, while the optimisation algorithm guarantees achieving the best cost-benefit trade-offs for given BGI options. The current study uses the advanced CityCAT hydrodynamic flood model to evaluate the efficiency of the optimisation framework and the impact of location and size of permeable interventions on the optimisation process and subsequent cost-benefit trade-offs. This is achieved by dividing permeable surface areas into intervention zones of varying size and quantity. Furthermore, rainstorm events with 100-year and 30-year return periods are analysed to identify any common optimal solutions for different rainfall intensities. Depending on the number of intervention locations, the automated framework reliably achieves optimal BGI implementation solutions in a fraction of the time required to find the best solutions by trialling all possible options. Designing and optimising interventions with smaller sizes but many permeable zones save a good fraction of investment. However, such a design scheme requires more computational time to find optimal options. Furthermore, the optimal spatial configuration of BGI varies with different rainstorm severities, suggesting a need for careful selection of the rainstorm return period. Based on the results, CONFIGURE shows promise in devising sustainable urban flood risk management designs.

Development of a multi-objective reservoir operation model for water quality-quantity management

This study aims to develop a multi-objective quantitative-qualitative reservoir operation model (MOQQROM) by a simulation-optimization approach. However, the main challenge of these models is their computational complexity. The simulation-optimization method used in this study consists of CE-QUAL-W2 as a hydrodynamic and water quality simulation model and a multi-objective firefly algorithm-k nearest neighbor (MOFA-KNN) as an optimization algorithm which is an efficient algorithm to overcome the computational burden in simulation-optimization approaches by decreasing simulation model calls. MOFA-KNN was expanded for this study, and its performance was evaluated in the MOQQROM. Three objectives were considered in this study, including (1) the sum of the squared mass of total dissolved solids (TDS), (2) the sum of the squared temperature difference between reservoir inflow and outflow as water quality objectives, and (3) the vulnerability index as a water quantity objective. Aidoghmoush reservoir was employed as a case study, and the model was investigated under three scenarios, including the normal, wet, and dry years. Results showed the expanded MOFA-KNN reduced the number of original simulation model calls compared to the total number of simulations in MOQQROM by more than 99%, indicating its efficacy in significantly reducing execution time. The three most desired operating policies for meeting each objective were selected for investigation. Results showed that the operation policy with the best value for the second objective could be chosen as a compromise policy to balance the two conflicting goals of improving quality and supplying the demand in normal and wet scenarios. In terms of contamination mass, this policy was, on average, 16% worse than the first policy and 40% better than the third policy in the normal scenario. In the wet scenario, it was, on average, 55% worse than the first policy and 16% better than the third policy. The outflow temperature of this policy was, on average, only 8.35% different from the inflow temperature in the normal scenario and 0.93% different in the wet scenario. The performance of the developed model is satisfactory.

Undervalued dry riverbeds: A key factor in equating intermittent river CO2 emissions to perennial rivers

Intermittent rivers in semiarid and arid regions, constituting over half of the world's rivers, alternate the carbon cycle interactions among the biosphere, hydrosphere, and atmosphere. Inadequate quantification of flow duration and river water surface area, along with overlooked CO2 emissions from dry riverbeds, result in notable inaccuracies in global carbon cycle assessments. High-resolution remote sensing images combined with intensive field measurements and hydrological modelling were used to estimate and extract the flow duration, river water surface area and dry riverbed area of Huangfuchuan, an intermittent river watershed that acts as a major tributary of the Yellow River in semiarid Northwest China. CO2 emission rates and partial pressures in water and air across the watershed were in-situ measured. In 2018, the flow duration of Huangfuchuan increased from less than 5 days in the first-order tributary to 150 days in the sixth-order mainstream. River water surface area estimated by remote sensing extraction plus the hydrodynamic model simulation varied from 3.9 to 88.6 km2 under 5 %–95 % discharge frequencies. CO2 emissions from the water-air interface and dry riverbed in 2018 were estimated at 582.3 × 103 and 355.2 × 103 ton, respectively. The estimated total annual emission (937.5 × 103 ton) aligns closely with the range of emissions (67.3 × 103–1377.2 × 103 ton) calculated for the water-air interface alone, derived using DEM river length and hydraulic geometry method. This similarity can be attributed to the overestimation of flow duration and flow velocity, as well as the over- or under-estimation of river water surface area and slope. The new method proposed in this study has large potential to be applied in estimating CO2 emissions from data-scarce intermittent rivers located in mountainous regions and provides a standardized solution in the estimation of CO2 emission. Results of this research reveal the spatiotemporal distribution of CO2 emissions along an intermittent river system and highlight the substantial role of dry riverbed in carbon cycle.

Assessing Tidal Models in the Ryukyu Islands Region Using the ENOPF Method

Abstract Satellite remote sensing can monitor sea level changes at temporal and spatial scales, plays an important role in the study of tides, and is widely used in numerical tidal models. However, these tidal models are usually computationally expensive. The equidistant nodes orthogonal polynomial fitting (ENOPF) method may overcome that drawback. This study evaluates the accuracy of the ENOPF method in fitting the major tidal constituents in the region near the Ryukyu Islands, where the water depth on either side of the islands varies significantly. The results show that the ENOPF method can accurately fit the major tidal constituents in the presence of complex topography. Furthermore, this approach can also be used to generate reasonable cotidal charts and provide valuable tidal information for hydrodynamic model simulations in the East China Sea. For the high-resolution hydrodynamic model of the East China Sea in particular, reasonable open boundary conditions can be provided by the ENOPF method.

SWE Modelling of Debris-flow body-sedimentation and Tail-flow Remobilization in a Check-dam Controlled Gully (Unzen Volcano, Japan) using UAV LiDAR, SfM-MVS

On 13th August 2021 at Unzen Volcano (Japan), an 81 mm.hr-1 peak-rainfall (1486 mm in 2 weeks) triggered series of erosion and deposition features in the Tansandani and the Gokurakudani gullies, all adding up to 57,800 m3 of erosion and 39,600 m3 of deposition. Upstream of the Sabo dam located at the exit of the Tansandani Gully, a large deposit has been visually identified as a potential debris-flow front candidate. However, the absence of direct observation leaves some uncertainty on the process that deposited the material and the magnitude of the flow. In the present contribution, the authors are investigating (1) the role of the debris-flow body in constructing the deposit and (2) the role of the tail of the debris-flow in eroding the fresh deposit. To reach this objective, the authors have combined a field investigation with direct observation, UAV (Unmanned Aerial Vehicle) LiDAR (Light Detection And Ranging) and Photogrammetry, and GIS (Geographic Information System) analysis of the field data. From this data, a 2D hydrodynamic simulation and sediment transport models were applied. The results show that the debris-flow ran beyond the first Sabo dam, with part of the material trapped on both sides of the gully. Afterwards, a central channel connected to sub-channels conveyed the diluted flow, most probably < 25 cm with maximum velocities between 4 to 5 m.s-1 at peak flow. Only the debris-flow phase went over the internal shoulders of the Sabo dam. A lobe occupies the top half of the study area and its deposition has been discussed to be related to the sudden widening of the gully, while the lower half is connected to the base-level created by the check dam.

A direct insertion technique to assimilate sea surface height into a storm surge model

Natural hazards like hurricanes, cyclones, and typhoons frequently cause major economic and livelihood loss in coastal areas around the world. However, accurately predicting sea surface height and flood inundation extent at the operational level remains a challenge. This work tests the hypothesis that assimilating satellite-like sea surface observations within a storm surge model can improve the estimation of storm surge dynamics for operational forecasting. A synthetic experiment is proposed based on Hurricane Irene, which moved along the United States East Coast in 2011. With a focus on the Chesapeake Bay area, a framework is developed to simulate coastal sea surface height using a storm surge model and merging synthetic satellite observations. To represent the “truth” of the system, a hindcast simulation was run for the Hurricane Irene event. Different satellite revisit times are considered to assess the improvement over the numerical model open-loop (i.e., no data assimilation) simulation. Results indicate that the assimilation of synthetic sea surface height observations has the potential to reduce errors and improve the accuracy in the hydrodynamic model simulations by up to 25% (in terms of correlation coefficient), especially when the satellite has short revisit times (i.e., daily, half-daily and flood tides). Such improvements are consistent regardless of the bias sign in the satellite observations and the location, which is fundamental in an operational setting where errors in satellite observations are often unknown.

Investigation of historical severe storms and storm tides in the German Bight with century reanalysis data

Abstract. Century reanalysis models offer a possibility to investigate extreme events and gain further insights into their impact through numerical experiments. This paper is a comprehensive summary of historical hazardous storm tides in the German Bight (southern North Sea) with the aim of comparing and evaluating the potential of different century reanalysis data to be used for the reconstruction of extreme water levels. The composite analysis of historical water level extremes, underlying atmospheric situations and their uncertainties may further support decision-making on coastal protection and risk assessment. The analysis is done based on the results of the regional hydrodynamic model simulations forced by atmospheric century reanalysis data, e.g. 20th Century Reanalysis Project (20CR) ensembles, ERA5 and UERRA–HARMONIE. The eight selected historical storms lead either to the highest storm tide extremes for at least one of three locations around the German Bight or to extreme storm surge events during low tide. In general, extreme storm tides could be reproduced, and some individual ensemble members are suitable for the reconstruction of respective storm tides. However, the highest observed water level in the German Bight could not be simulated with any considered forcing. The particular weather situations with corresponding storm tracks are analysed to better understand their different impact on the peak storm tides, their variability and their predictability. Storms with more northerly tracks generally show less variability in wind speed and a better agreement with the observed extreme water levels for the German Bight. The impact of two severe historical storms that peaked at low tide is investigated with shifted tides. For Husum in the eastern German Bight this results in a substantial increase in the peak water levels reaching a historical maximum.

Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers

During extreme floods caused by climate change, reliable flow discharge data are essential for successful reservoir operation to mitigate downstream flood damage. Generally, the flow discharge is computed using the rating curve (RC) established from the relationship between the flow rate and water stage level. Determining the parameters of rating curves is subject to uncertainties related to the difficulties and limitations of flow monitoring in covering a wide range of flow variations. Especially at river confluences, the uncertainties are pronounced when floods occur owing to several factors such as roughness change, backwaters, and levee overflow. The Seomjin River Basin in Korea suffered from flood inundation that occurred at the tributary confluence during an extreme flood in 2020. To identify a reliable flow rate of the main stream and tributary, this study proposes an indirect flow assessment scheme using a 1D hydrodynamic simulation model to find the best simulated water level in an iterative manner based on Monte Carlo (MC) simulations. With a large amount of discharge data generated from random-number combinations, it is possible to obtain the best results automatically by specifying the reliability limitation considering the uncertainty of the predetermined RC parameters associated with the roughness coefficient. Nash Sutcliffe Efficiency (NSE) was incorporated to evaluate the reproduced water level to meet the threshold specified for NSE ≥ 0.75. The simulated flowrates computed from the revised RC and roughness coefficients revealed an error range of 8%–36.6% compared with the design flood. The approach proposed in this study is applicable for determining the valid parameters necessary to create a revised RC at an existing water level gauge station, where the uncertainties of the RC are pronounced, particularly in the vicinity of the channel confluence.

Fast-Processing DEM-Based Urban and Rural Inundation Scenarios from Point-Source Flood Volumes

Flooding has always been a huge threat to human society. Global climate change coupled with unsustainable regional planning and urban development may cause more frequent inundations and, consequently, higher societal and economic losses. In order to characterize floods and reduce flood risk, flood simulation tools have been developed and widely applied. Hydrodynamic models for inundation simulation are generally sophisticated, yet they normally require massive setup and computational costs. In contrast, simplified conceptual models may be more easily applied and efficient. Based on the Hierarchical Filling-and-Spilling or Puddle-to-Puddle Dynamic Filling-and-Spilling Algorithms (i.e., HFSAs), Safer_RAIN has been developed as a fast-processing DEM-based model for modelling pluvial flooding over large areas. This study assesses Safer_RAIN applicability outside the context for which it was originally developed by looking at two different inundation problems with point-source flooding volumes: (1) rural inundation modelling associated with levee breaching/overtopping; (2) urban flooding caused by drainage systems outflow volumes.

A simulation model for oil production by intermittent gas lift technology

The operating principle of the oil production by intermittent gas lift (IGL) technology and the mechanical processes occurring in it are complex with many different stages and many flows interacting with each other in each stage. This leads to many difficulties in calculating and optimizing oil well production system with IGL technology. This study develops a hydrodynamic simulation model of the flows occurring during oil production by IGL. By improving until now published hydrodynamic simulations the model in this work is developed based on changes/adjustments to be applicable for specific field conditions. Simulation of the IGL process is performed based on numerical solutions of the systems of conservation equations of mass and momentum and closure equations for each system component and each stage of the IGL process. The ordinary differential equations in the model are solved by the implicit Euler method. The simulation program has been developed and used in selecting a reasonable design of IGL technology for an oil well previously produced by the continuous gas lift (CGL). After the IGL system was installed and put into operation, the daily liquid production rate of the well increased by 91% and the measured data showed good agreement with the simulated results. The application result has initially demonstrated the applicability of the proposed model and the developed simulation program. Keywords: well; intermittent gas lift; simulation model; oil production.

Modeling Extreme Water Levels in the Salish Sea: The Importance of Including Remote Sea Level Anomalies for Application in Hydrodynamic Simulations

Extreme water-level recurrence estimates for a complex estuary using a high-resolution 2D model and a new method for estimating remotely generated sea level anomalies (SLAs) at the model boundary have been developed. The hydrodynamic model accurately resolves the dominant physical processes contributing to extreme water levels across the Washington State waters of the Salish Sea, including the relative contribution of remote SLA and other non-tidal residual processes that drive extreme water levels above the predicted tide. The model’s predictions have errors of less than 15 cm (&lt;5% of 3–4 m tidal range) at eight tide gauge locations across the model domain. The influence of remote SLAs at the seaward boundary of the model was implemented using a multivariate regression of readily available and locally relevant wind, sea surface temperature, and pressure anomaly data, combined with El Niño Index data (R2 = 0.76). The hydrodynamic model simulations using the remote SLA predictor compared well with simulations using the widely used data-assimilative global ocean model HYCOM SLA data (root mean square difference of 5.5 cm). Extreme water-level recurrence estimates with and without remote SLA show that remote forcing accounts for 50–60% of the total water level anomaly observed along Salish Sea shorelines. The resulting model simulations across decadal timescales provide estimates of extreme water level recurrence across the Salish Sea, capturing climate variability important to long-term coastal hazard planning. This approach has widespread applications for other complex estuarine systems.

Construction and Verification of Two-dimensional Surface Hydraulic Calculation Model

Accurate calculation and prediction of the surface water flow process in the substation and surrounding area is of great significance for on-site flood control and disaster reduction of the substation. Aiming at the dynamic process of surface water flow, this paper simulated the spatial and temporal distribution characteristics of surface water flow by establishing a two-dimensional hydrodynamic calculation model. Based on the N-S equation, a finite volume integral method is used to discrete the governing equations. On this basis, a hydrodynamic model for two-dimensional numerical simulation of surface water flow is constructed, and the basic governing equations for two-dimensional surface shallow water movement are derived. Based on the Toce River physical model and water flow control experiment, the corresponding conceptual model is established. On this basis, the measured data are used to verify the constructed two-dimensional surface hydrodynamic calculation model. The results show that the model can better simulate the process of surface water flow and describe its temporal and spatial distribution characteristics. The research results will provide effective technical support for substation site flood warning and prevention.

Comprehensive characterization of Marine Heatwaves in a coastal Northern Humboldt Current System regional model over recent decades

In this study, a high-resolution hydrodynamic model simulation was used to analyze the three-dimensional characteristics of marine heatwaves (MHWs) in the coastal region of the Northern Humboldt Current System (NHCS) over the period 2000–2019. Three distinct vertical layers were identified. The near-surface layer, extending down to 75 m depth, is identified as the region where both the maximum MHW intensity and cumulative intensity are found, predominantly concentrated along the thermocline depth. The intermediate layer, spanning from 75 to 125 m depth, exhibited the longest MHW durations and the lowest MHW frequencies. MHWs in this layer tend to be of moderate intensity and are often associated with ENSO variability. In contrast, the deep layer, from 125 to 250 m depth, was characterized by short-lived MHWs of low intensity. These MHWs exert a lesser thermal impact on the region. To understand the drivers of MHWs, a composite analysis was performed. The results highlighted the significant role exerted by wind-driven anomalies in the life cycle of MHWs. It was found that the combined effect of a sluggish coastal upwelling circulation and suppressed oceanic heat loss, as a result of weakened winds, preceded the MHW formation. Conversely, the strengthening of winds, which enhanced net heat loss, primarily driven by latent heat flux anomalies, and an enhancement of the cooling effect due to the recovery of the coastal upwelling circulation, are key processes in ending a typical MHW event in the coastal region. These findings expand our understanding of the MHWs and their associated potential drivers and help to reveal which regions are most susceptible to extreme climate events in one of the most productive marine ecosystems worldwide.

A Comparison of Hydrogen and Gasoline Piston Ring Simulations

This paper presents a transient mixed-lubrication hydrodynamic and gas flow simulation model for a piston ring pack for a four-stroke internal combustion engine. The analyses carried out compare two fuel types, hydrogen and gasoline, at a 2000 rpm low engine load (20%), as well as 3000 rpm low (20%) and high (100%) engine loads, to investigate the effects of the different fuels and loading conditions on the ring pack. In particular, the minimum oil film thickness at the top compression ring, the total ring friction of the ring pack, the friction power loss and the blow-by are studied. The simulation shows that, under the high load conditions at 3000 rpm, the hydrogen variant exhibits larger friction power losses, around a 200 W peak difference and larger blow-by throughout the expansion stroke of the engine cycle. A similar trend can be observed for the low loads, where larger friction power losses with peak differences of 30 W and 40 W for 2000 rpm and 3000 rpm, respectively, are observed. The blow-by results for the low load at 2000 rpm show a slight increase of approximately 22% more gas flow into the crankcase, while the 3000 rpm simulation shows a 50% increase in blow-by for the hydrogen variant at low load and a 40% increase at high load. The findings that are presented indicate that, although alternative fuel sources such as hydrogen are very attractive alternatives to fossil fuels such as gasoline, there can be unwanted side effects that could lead to the permanent damage of components through quicker wear or hydrogen embrittlement from the blow-by gas.