High Flow Characteristics Research Articles

Superhydrophobic Co-MOF-based sponge for efficient oil-water separation utilizing photothermal effect

Effectively addressing crude oil spills remains a global challenge due to its high viscosity and limited flow characteristics. In this study, we successfully prepared a modified sponge (PCP@MS) by embedding the photothermal material of Co-HHTP and coating the melamine sponge (MS) with low-surface-energy polydimethylsiloxane (PDMS). The PCP@MS exhibited outstanding hydrophobicity with WCA of 160.2° and high oil absorption capacity of 59–107 g/g. The PCP@MS showed high separation efficiency of 99.2% for various oil-water mixtures, along with notable self-cleaning properties and mechanical stability. The internal micro-nano hierarchical structure on the sponge surface significantly enhanced light absorption, synergizing with the photo-thermal conversion properties of Co-HHTP, enabled PCP@MS to achieve a surface temperature of 109.2 °C under 1.0 solar light within 300 s. With the aid of solar radiation, PCP@MS is able to heat up quickly and successfully lowering the viscosity of the surrounding crude oil, resulting in an oil recovery rate of 8.76 g/min. Density functional theory (DFT) calculation results revealed that Co-HHTP featured a zero-gap band structure, rendering advantageous electronic properties for full-wavelength light absorption. This in situ solar-heated absorbent design is poised to advance the practical application of viscous oil spill cleanup and recovery.

Investigation of turbulence models for aerodynamic analysis of a high-pressure-ratio centrifugal compressor

The aerodynamic design and optimization of modern centrifugal compressors are inseparable from computational fluid dynamics (CFD) tools. In a design environment, CFD simulations are expected to predict compressor performance characteristics with reasonable accuracy. Turbulence models and model simplification can play a significant role in the discrepancy between analysis and reality. To investigate the influence of turbulence models on aerodynamic analysis results of centrifugal compressors, the National Aeronautics and Space Administration's high efficiency centrifugal compressor stage is selected as the test vehicle. Six eddy-viscosity models, namely, Spalart–Allmaras (SA), standard k–epsilon (k−ε), renormalization group k–epsilon (RNG k−ε), Wilcox k–omega (k−ω), shear stress transport (SST), and SST-reattachment modification (SST-RM) are considered. In all numerical analyses, measured surface roughness is included with the aim of improving numerical solution accuracy. Although some discrepancies exist, the compressor performance characteristics predicted by the k−ω model are in satisfactory agreement with the test data over the whole speedline. The k−ε model overpredicts the isentropic efficiency than the other models, while the SST-RM model underestimates the total pressure ratio in the near-stall region. The RNG k−ε model matches high flow characteristics but overestimates the choked mass flow rate. The SST model obtains a similar operating range with the test data but underestimates the compressor's isentropic efficiency and total pressure ratio, while the SA model totally overestimates the compressor characteristics due to the wall function. Furthermore, variations caused by turbulence models are discussed together with the flow field analysis. Finally, to verify the impact of the impeller backplate bleed cavity, an additional simulation is conducted that specifically accounts for this feature.

Identifying bridges prone to instream wood accumulation: insights from bridges across the UK

Accumulation of instream large wood (i.e., fallen trees, trunks, branches, and roots) at bridges during floods may exacerbate flooding, scour and cause structural failure. Yet, explaining and predicting the likelihood of a bridge trapping wood remains challenging. Quantitative data regarding wood accumulation at bridges are scarce, and most equations proposed to estimate the accumulation probability were derived from laboratory experiments, and include variables such as flow velocity, Froude number, and approaching wood volume or size which are difficult to obtain. Other evaluations based on technical reports and information regarding wood removal have been proposed but are mostly qualitative. Until now, a data-driven approach combining multiple quantitative accessible variables at the river reach and catchment scales remains lacking. As a result, the controlling parameters explaining whether a bridge is prone to trap wood are still unclear. This work aims to fill this gap by analysing a database of 49 bridges across the United Kingdom (UK) classified as prone and not prone to wood accumulation. The database contained information regarding the geometry of the bridge (i.e., number of piers and pier shape) and we added parameters describing the upstream river channel morphology, the riparian landcover, and high-flow characteristics. We applied multivariate statistics and a machine learning approach to identify the variables that explained and predicted the predisposition of bridges to wood accumulation. Results showed that the number of bridge piers, the unit stream power, the pier shape, and the riparian forested area explained 87% of the total variability for the training dataset (0.87 training accuracy), and the selected model had a testing accuracy of 0.60 (60%). Although limited by the sample size, this study sheds light on the identification of bridges prone to wood accumulation and can inform bridge design and management to mitigate wood-related hazards.

Quantifying patterns of streamflow peaks over the southeastern United States using a long‐term retrospective data set

AbstractUtilizing simulated daily flow values for 61 948 stream nodes from the National Water Model (NWM) v.2.1 retrospective data set, which covers the period 1979–2020, streamflow peaks (SFP) were determined using an objective threshold method based on the Fisher‐Jenks breakpoint algorithm. This approach provides estimates of low probability, high in‐channel water level conditions. Strong spatial relations in temporal streamflow peak distribution were observed, with four main spatial clusters covering: (1) the central parts of Mississippi to South Carolina; (2) the south and north parts of Mississippi to South Carolina; (3) Florida, the Gulf Coast, and parts of North Carolina and Virginia; and (4) the Atlantic Coast and parts of the Gulf Coast. The first area is characterized by high multiannual SFP occurrence with long total durations, high contribution to total discharge, and occurrence throughout the year with peaks in February and March. Increasing annual peak trends are present locally. The second area is characterized by similar parameters with increased flash flooding potential. In the third area, lower occurrence and share in total discharge are observed, with two peaks of occurrence in the September–October and March periods. In the fourth region, the lowest occurrences and shortest durations are present, along with strong seasonality manifested in September–October occurrences that constitute over 80% of all SFP volumes. Decreasing trends in maximal monthly flows for the June–October period are also observed here. The results provide valuable regionalized information about historical high flow characteristics across the southeast United States, which can be used as a basis for improved long‐term flood prediction based on seasonality models and constitute a baseline for defining regional changes in high flow frequency and distribution.

A Signal Optimization Model of Adjacent Closely Spaced Intersections Which Optimizes Pedestrian Crossing

Adjacent closely spaced intersections with characteristics of short link distance and high pedestrian flow are primarily located in high-density urban areas. To address the problems of queue overflow, poor traffic operation, and high pedestrian travel delays, a pedestrian-motor vehicle signal optimization method for adjacent closely spaced intersections was proposed in this paper. First, the traffic flow entering the closely spaced intersections is divided into nonarterial and arterial flow categories to establish a delay model of pedestrian crossing. Then, a pedestrian crossing delay model based on pedestrian demand is constructed according to pedestrian crossing time and a space diagram. An optimization model for pedestrians and vehicles at adjacent closely spaced intersections is established, and an artificial intelligence algorithm is used to optimize this model. Finally, a selected case intersection is optimized. The results show that compared with a traditional single optimization method, vehicle delay decreased about 4%, 13.8%, 17.1%, and 25.9% and total pedestrian delay decreased by 3%, 15%, 25%, and 31%, respectively, for the four proposed scenarios.

Tailoring Light-Weight Aggregates for Concrete 3D Printing Applications

Concrete 3D printing is a sustainable solution for manufacturing efficient designs and creating less waste, and selecting the optimal materials to use can amplify the advantages of this technology. In this study, we explore printing lightweight concrete by replacing normal weight aggregate with lightweight aggregates such as cenospheres, perlite, and foam beads. We adopt a systematic approach to investigate mixtures using different formulation methods such as the specific gravity and packing factor methods to improve the printing and mechanical performances of the mixtures. The rheological results showed significant improvement in the flow characteristics of the different mixtures using both the specific gravity method and the packing factor method to formulate the mixtures. Furthermore, a statistical tool was used to achieve optimal performance of the mixtures in terms of high specific compressive strength, high flow characteristics, and good shape retention capability by maximizing the specific compressive strength ratio, slump flow, and the static yield stress, while minimizing the slump, dynamic yield stress, and plastic viscosity. With the above design objectives, the optimal percentages of the aggregate replacements (cenosphere, perlite, and EPS foam beads) were 42%, 68%, and 44%, respectively. Finally, the optimized results also showed that the mixture with cenosphere aggregate replacement had the highest specific strength.

Last two millennia of streamflow variability in the headwater catchment of the Yellow River basin reconstructed from tree rings

The headwater catchment of the Yellow River Basin (HCYRB) controls 35% of the streamflow of the Yellow River (YR) which faces increasing water shortages. To better understand streamflow variability in the region we require a better understanding of high and low flow characteristics. This study presents a new annual (Nov-Oct) streamflow reconstruction at the Tangnaihai station in the HCYRB for the last two millennia (159–2016 C.E.) using 12 tree-ring chronologies. The nested principal component regression model combined with the stepwise best subset selection method was proposed to improve the temporal length and model skill of reconstruction. The stepwise best subset selection method was presented to select the best principal components subset, instead of a confidence test, based on k-fold cross-validation error and Akaike’s information criteria (AIC). The model assessment results verify that the proposed model exhibits strong reconstruction skills. Besides, the magnitude and duration of both high and low flow periods were analyzed. The results show that (1) the significant high-flow periods are the early 3rd century, circa 300 C.E., early 13th century, 16th century and circa 1900 C.E., while the low-flow periods are the late 5th century and late 15th century; (2) the durations and magnitudes of low-flow periods are longer and larger than high-flow periods and the severities of high-flow periods are greater than low-flow periods. The reconstruction also suggests that a warm climate is more likely accompanied by a high-flow period and low-flow periods are more likely to occur in cold periods associated with the Asian Summer Monsoon and solar activity.

Expression Characteristics of microRNA in Pig Umbilical Venous Blood and Umbilical Arterial Blood.

Simple SummaryUmbilical cord blood is an important biological resource for research on fetal development and treatment of related diseases. To further explore the biological functions of umbilical cord blood, we sequenced the small RNAs in porcine umbilical venous blood and umbilical arterial blood and analyzed them through two differential expression analysis methods. Through comparative analysis, it is found that highly expressed miRNAs in umbilical venous blood and umbilical artery blood perform similar functions, but there may be differences in immunity and angiogenesis. Because miRNAs are highly conserved and have the ability to transmit across species, they have great potential in the treatment of human-related diseases. Further analysis shows that cord venous blood miRNA may be helpful in the treatment of muscle-related diseases, while cord arterial blood miRNA may be beneficial in the treatment of liver- and brain-related diseases. This research helps to analyze the biological functions of cord blood miRNA and provides a reference for the development and application of porcine cord blood miRNA-related products. At the same time, it provides new insights for the further development of value-added products in the animal husbandry industry and the treatment of human diseases.As the medium of material exchange between mother and fetus, umbilical cord blood is closely connected with fetal development. microRNA (miRNA) has a wide range of biological functions and has high flow characteristics. Small RNA sequencing of pig umbilical venous blood (UVB) and umbilical arterial blood (UAB) revealed that a total of 302 miRNAs were identified, and 106 and 22 miRNAs were specifically expressed in the UVB and UAB, respectively. Using the two methods of differential expression multiple and differential expression percentage, it is found that only 35% of the highly expressed miRNAs in the UVB by the two analysis modes overlap, but 56.25% of the enriched signal pathways are the same. Only 20% of the highly expressed miRNAs in the UAB overlap, but 62.07% of the signal pathways are the same. Further analysis revealed that miR-423 can be used as a characteristic miRNA of UVB and has the potential to treat muscle-related diseases. miR-122-5p can be used as a characteristic miRNA of UAB and may help to improve liver- and brain-related diseases. In summary, these results enrich understanding of miRNA in mother–fetal communication and provide a reference for the development and application of porcine cord blood products.

Process-Based Modeling of the High Flow of a Semi-Mountain River under Current and Future Climatic Conditions: A Case Study of the Iya River (Eastern Siberia)

The purpose of the study was to analyze the formation conditions of catastrophic floods in the Iya River basin over the observation period, as well as a long-term forecast of the impacts of future climate change on the characteristics of the high flow in the 21st century. The semi-distributed process-based Ecological Model for Applied Geophysics (ECOMAG) was applied to the Iya River basin. Successful model testing results were obtained for daily discharge, annual peak discharge, and discharges exceeding the critical water level threshold over the multiyear period of 1970–2019. Modeling of the high flow of the Iya River was carried out according to a Kling–Gupta efficiency (KGE) of 0.91, a percent bias (PBIAS) of −1%, and a ratio of the root mean square error to the standard deviation of measured data (RSR) of 0.41. The preflood coefficient of water-saturated soil and the runoff coefficient of flood-forming precipitation in the Iya River basin were calculated in 1980, 1984, 2006, and 2019. Possible changes in the characteristics of high flow over summers in the 21st century were calculated using the atmosphere–ocean general circulation model (AOGCM) and the Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES) as the boundary conditions in the runoff generation model. Anomalies in values were estimated for the middle and end of the current century relative to the observed runoff over the period 1990–2019. According to various Representative Concentration Pathways (RCP-scenarios) of the future climate in the Iya River basin, there will be less change in the annual peak discharge or precipitation and more change in the hazardous flow and its duration, exceeding the critical water level threshold, at which residential buildings are flooded.

Modelling the impacts of future coal mining and coal seam gas extraction on river flows: A methodological framework

This manuscript outlines a methodological framework for modelling the hydrological impacts of future coal mining and coal seam gas extraction. Such impacts potentially include changes to both high flow and low flow characteristics such as total volume, high flow rate and frequency, low flow rate and frequency, and cease to flow frequency. In particular, the manuscript proposes a methodology that is suitable for the prediction of cumulative impacts from multiple coal resource developments and for making such predictions at multiple locations in the landscape. The proposed methodology is framed in terms of a structured uncertainty analysis to provide information on the likelihood and potential ranges of various impacts. The approach can be applied under a wide range of data availability, even when there is little to no observed data, whilst additional data can easily be incorporated to better constrain the results. The assessments thus derived can provide regulators with crucial objective information on the potential social, economic, environmental and ecological risks of future developments. Whilst discussed here in terms of coal resource development, this methodology has the potential to be readily adapted and applied to a range of extractive industries, including but not limited to minerals and other sources of unconventional gas. As it stands, the methodology does not explicitly consider impacts on water quality, but could be extended to include this if required.

Changes in the wintertime hydroclimatic regime in St. John River, Maine, USA

Abstract Changes in the flow regime in snowmelt- and ice-dominated rivers have important implications for navigation, flood hazard, recreation, and ecosystems. We investigated recent changes in the high flows of the St. John River basin in Maine, USA, with a view to quantify changes in high-flow characteristics, as well as extreme event estimates. The results analyzed herein demonstrate shifts in springtime streamflow as well as in emergent wintertime (January–February) streamflow over the past four decades. A Poisson-based regression approach was applied to develop a model for the diagnosis of weather–climate linkage. The sensitivity of episodic warm weather events to the negative phase of the Tropical–Northern Hemisphere (TNH) atmospheric teleconnection pattern is evident. Although a modest sample size of historical data on the weather–climate linkage imposes a limit in terms of reliability, the approach presented herein shows a modest role of the TNH pattern, in response to the warm phase of El Niño/Southern Oscillation, as one of the factors that contribute to hydroclimate variability in the St. John River basin. This diagnostic study sought to investigate the changes in the wintertime streamflow regime and the relative linkages with short-term concurrent weather events, as well as large-scale climatic linkages. This improved an understanding of hydrological extremes within a climatological context and offers new knowledge to inform water resources planning and decision-making.

Study on Direct Writing of Gallium Metal for the Flexible Sensor

There is an urgent need for a simple and effective method to manufacture flexible sensors composed of liquid metal. Gallium (Ga) metal has become an ideal flexible conductive material due to its high conductivity, low melting point, and high flow characteristics. In this paper, liquid Ga metal is directly written on the polyvinyl alcohol (PVA) film through the driving mode of piston extrusion; then, the Ga metal wire is transferred and sealed with silica gel. The advantages of piston mode are studied, and the direct writing parameters of the liquid Ga metal, including extrusion speed, nozzle height, printing speed, and nozzle inner diameter, are systematically optimized. The flexible sensor based on the sealed liquid Ga metal has good resilience under the external load. This work provides a specific reference for direct writing of liquid Ga metal and its sealing technology for the flexible sensor.

Accumulation contribution differences between lacustrine organic-rich shales and mudstones and their significance in shale oil evaluation

Abstract The differences in organic matter abundance and rock composition between shale and mudstone determine the discrepancy of their contributions to the formation of conventional and shale oil/gas reservoirs. The evaluation criteria of source rocks are different in the future exploration in self-sourced petroleum systems. Shales are deposited in deep/semi-deep lacustrine, with low sedimentation rate and chemical depositions of various degrees, while mudstones are mostly formed in shallow lacustrine/lakeside, with high deposition rate and density flow characteristics. Three factors contribute to the enrichment of organic matter in shales, including the “fertility effect” caused by volcanic ash deposition and hydrothermal injection, excessive and over-speed growth of organisms promoted by radioactive materials, and deep-water anaerobic environment and low sedimentation rate to protect the accumulation of organic matter from dilution. Lamellations in shales are easy to be stripped into storage space, and acid water produced during hydrocarbon generation can dissolve some particles to generate new pores. The massive mudstones with high clay content are of poor matrix porosity. Shales with high total organic carbon, developed laminations, relatively good reservoir property, and high brittle mineral content, are the most favorable lithofacies for shale oil exploration and development. It is necessary to conduct investigation on the differences between shale and mudstone reservoirs, to identify resources distribution in shale and mudstone formations, determine the type and standard of “sweet-spot” evaluation parameters, optimize “sweet-spot areas/ sections”, and adopt effective development technologies, which is of great significance to objectively evaluate the total amount and economy of shale oil resources, as well as the scale of effective exploitation.

Velocity and density contrasts across the Moho interface of Guangdong province in south China constrained by receiver functions*

The P receiver function includes P-to-SV converted phases and multiple reverberations of the discontinuities in the crust and mantle. The time of these phases is related to the crustal thickness and vP/vS ratio, and the amplitude of these phases is mainly controlled by the velocity and density contrast of interfaces. By using H-κ stacking method, this work estimated the crustal thickness and vP/vS ratio beneath the stations in the Guangdong province of South China. The velocity and density contrast (δβ-δρ) scanning stacking algorithm of the receiver function is applied to constrain the velocity and density contrast of the Moho in Guangdong province. This work analyzed the results of the crustal thickness, vP/vS ratio, and the velocity and density contrasts of Moho. The results indicate that the velocity contrast is higher beneath Yangjiang area in western Guangdong province and Nanao area in eastern Guangdong, which has a strong correlation with the distribution of geothermal springs in local areas and the characteristics of high heat flow. The velocity contrast of Moho has also a good correlation with the vP/vS ratio and the crustal thickness, which indicates that there is a strong material composition contrasts of the Moho in the study area. Velocity and density contrasts of Moho in some local area (such as western Guangdong) are somewhat consistent with the seismic activities.

Turbulence characteristics of high Reynolds number flow inside a three-dimensional cubic lid-driven cavity

Large eddy simulation (LES) with dynamic Smagorinsky model (DSM) has been implemented to elicit the turbulence characteristic of the flow inside a cubic lid-driven cavity at Reynolds number of 10000. The coherent organized structures tear, pair and disintegrate leading to the evolution of turbulence. They are reflected in the RMS (root mean square) plots of the turbulent fluctuations in different planes. The flow has a near zero helicity value; unlike the other two velocity component, the probability density function of span wise velocity component shows the flow symmetry on the both side of the mid plane in span wise direction; kurtosis being largely leptokurtic except near wall locations indicates their peakedness. The quadrant analysis shows presence of more coherent structures near the down stream wall and the joint probability distribution function shows that turbulence is anisotropic. Power spectra is observed to follow the −5∕3 law. Both Taylor microscale λ and Kolmogorov length scale η show greater near-wall dissipation

Study on high temperature mechanical behavior and microstructure evolution of Ni3Al-based superalloy JG4246A

Ni3Al-based polycrystalline intermetallic compound is a kind of engineering superalloy, which have been used in the adjustment flaps of aeroengine tail nozzle. In order to explore its mechanical properties and microstructure evolution in service, the high temperature flow characteristics and microstructural changes of alloys were investigated by uniaxial isothermal compression tests on Gleeble-1500. The true stress-true strain curves were obtained and the microstructures were analyzed by OM, SEM, and EBSD. Based on the experimental data, three different constitutive models, belonging to phenomenological model, physical-based model, and radial basis function (RBF) neural network model, separately, were established to predict the deformation stress. The results show that the true stress is very sensitive to temperature and stain rate. Flow instability occurred during the deformation process, which caused some decline in the stress. Microstructure evolution under different deformation conditions indicated that the γ' to γn' phase transformation was also related to the degree of deformation and the four stage evolutionary process was identified. The SEM and EBSD results showed that the DRX appeared at the later stage of the deformation. The prediction capabilities of the three models were assessed by correlation coefficient (R), the absolute value of relative error (ARE), and the absolute average error (AARE). The result demonstrated that the RBF neural network had the best ability to predict the flow stress and the coefficient.

Can complementary preferential flow and non-preferential flow domains contribute to soil water supply for rubber plantation?

Preferential flow has always been hotspot of research regarding soil water flow, biological activity, and carbon and nitrogen dynamics. However, the mechanism of water flow exchange between two adjacent zones (with and without root system) and the pattern of soil water supply for rubber are still unclear. In the present study, we considered two plots experiencing similar farming history: in the first plot we measured soil physical properties and soil volumetric water content (VWC) during rainfall, and the second plot was used to visualise water flow path and to measure root biomass. Besides, a model was developed on preferential flow domain (PFD, matching the root zone) and on non-preferential flow domain (NPFD, matching the remote root zone) to compute differences in soil properties between the PFD and NPFD. The results revealed that the dominant flow type in the PFD was preferential flow and the one in the NPFD was capillary flow. Dye stained area and wetting front rate negatively correlated with bulk density, while they positively correlated to non-capillary porosity and root biomass. Accordingly, PFD showed a quick response to rainfall. Indeed, during the rain, a lateral flow (driven by water gravity and pressure head gradient) predominantly carried water (0.95, 0.27, and 0.44 cm3 cm−3 for various rainfall events 1, 2, and 3, respectively) from PFD to NPFD. During the soil drainage stage, the lateral flow direction changed, and water (about 0.63, 0.30, and 0.39 cm3 cm−3 for rainfall events 1, 2, and 3, respectively) flowed from NPFD to PFD. As a result, PFD presented low storage and high flow characteristics compared with NPFD, suggesting this complementary relationship for water interaction between the two domains could be beneficial for rubber plants growth and development.

Prediction of high temperature deformation characteristics of an Fe-based shape memory alloy using constitutive and artificial neural network modelling

The high temperature deformation characteristics of an Fe-28Ni-17Co-11.5Al-2.5Ta-0.05B (at.%) shape memory alloy (SMA) were studied by high temperature compression testing under large temperature (1323–1473 K) and strain rate (0.01–10 s−1) ranges. These were predicted by applying the Arrhenius-type and strain-compensated Arrhenius-type constitutive models, and the artificial neural network (ANN) model to the results obtained from the experiments. The capability of the models for prediction was assessed as a function of the correlation coefficient (R) and the relative percentage error. The results reveal that the true stress prediction by the strain-compensated Arrhenius-type constitutive model is more precise at a lower strain rate (0.01 s−1) than at a higher strain rate (10 s−1). Moreover, it yields better results in comparison with those obtained from Arrhenius-type model. They further reveal ANN model shows higher efficiency and preciseness in forecasting the high temperature flow characteristics of the SMA as compared to the strain-compensated Arrhenius-type and Arrhenius-type models.

Future shifts in extreme flow regimes in Alpine regions

Abstract. Extreme low and high flows can have negative economic, social, and ecological effects and are expected to become more severe in many regions due to climate change. Besides low and high flows, the whole flow regime, i.e., annual hydrograph comprised of monthly mean flows, is subject to changes. Knowledge on future changes in flow regimes is important since regimes contain information on both extremes and conditions prior to the dry and wet seasons. Changes in individual low- and high-flow characteristics as well as flow regimes under mean conditions have been thoroughly studied. In contrast, little is known about changes in extreme flow regimes. We here propose two methods for the estimation of extreme flow regimes and apply them to simulated discharge time series for future climate conditions in Switzerland. The first method relies on frequency analysis performed on annual flow duration curves. The second approach performs frequency analysis of the discharge sums of a large set of stochastically generated annual hydrographs. Both approaches were found to produce similar 100-year regime estimates when applied to a data set of 19 hydrological regions in Switzerland. Our results show that changes in both extreme low- and high-flow regimes for rainfall-dominated regions are distinct from those in melt-dominated regions. In rainfall-dominated regions, the minimum discharge of low-flow regimes decreases by up to 50 %, whilst the reduction is 25 % for high-flow regimes. In contrast, the maximum discharge of low- and high-flow regimes increases by up to 50 %. In melt-dominated regions, the changes point in the other direction than those in rainfall-dominated regions. The minimum and maximum discharges of extreme regimes increase by up to 100 % and decrease by less than 50 %, respectively. Our findings provide guidance in water resource planning and management and the extreme regime estimates are a valuable basis for climate impact studies. Highlights Estimation of 100-year low- and high-flow regimes using annual flow duration curves and stochastically simulated discharge time series Both mean and extreme regimes will change under future climate conditions. The minimum discharge of extreme regimes will decrease in rainfall-dominated regions but increase in melt-dominated regions. The maximum discharge of extreme regimes will increase and decrease in rainfall-dominated and melt-dominated regions, respectively.

Improved Estuaries Salinity Stratification at Gyeonggi Bay Using Data Assimilation with Finite Volume Coastal Ocean Model (FVCOM)

Gu, B.-H.; Woo, S.-B., and Kim, S.I., 2019. Improved estuaries salinity stratification at Gyeonggi Bay using data assimilation with Finite Volume Coastal Ocean Model (FVCOM). In: Lee, J.L.; Yoon, J.-S.; Cho, W.C.; Muin, M., and Lee, J. (eds.), The 3rd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 91, pp. 416-420. Coconut Creek (Florida), ISSN 0749-0208.Assimilating salinity data into coastal models is very important and salinity vertical change is an important component to coastal forecasting. The goal of this study is to represent the salinity stratification at Gyeonggi Bay (GGB) in South Korea and to improve the accuracy of the prediction in hydrodynamics via data assimilation. The GGB area is located in the Yellow Sea between Korea and China and is a semi-closed estuary that has a tidal range above 7 m with a tidal flat where salt water and fresh water is mixed. Salinity stratification appears at Yeomha channel in GGB because it has characteristics of high tide and strong river flow. To represent the tidal flat and creek in the GGB in this study, the unstructured grid numerical model called Finite Volume Coastal Ocean Model (FVCOM) is employed. The performance of the model results is validated against the measured tide, current, and salinity at the Yeomha channel. In order to improve the numerical results, the salinity observations from the surface and bottom Conductivity Temperature Depth (CTD) data in the Yeomha channel are assimilated into the model only for the 4-day middle period out of total simulation days of 15. The direct comparison results show the clear effect of data assimilation for salinity stratification along vertical salinity, and the improvement of salinity profile lasts for 1 day after the end of data assimilation. The salinity stratification in the coastal are also improved as the number of observations and/or data assimilation periods is increased. These results are expected to improve the coastal forecasting system over the GGB area when applied the data assimilation scheme in to the forecasting system.