Stream Flow Research Articles

Abrupt Late Holocene Closure of San Elijo Lagoon, Northern San Diego County, California

The San Elijo Lagoon experienced a sudden shift in sedimentation type around 1000 AD, as evidenced by the 14C dating. This shift is marked by a sharp boundary between a lower layer of medium to fine sand and an upper layer of dark, silty clay that reflects the lagoon closure. The dated sediments also reveal a history of marine conditions in the lagoon basin since about 7400 ± 140 years before the present (ybp), when the sea level was −12.2 meters (m), and the shoreline was 400 m away from the current location. The sea level rose at a rate of 2.84 m per 1000 years until about 4170 ± 100 ybp. After that, the rising sea level slowed and reached the present level about 3100 years ago. However, the lagoon remained closed after about 730 to 1180 ybp, with only fine organic sediment accumulating in the basin, which coincides with a severe drought in the southwest around 1150 AD. A higher sedimentation rate is interpreted from bluff erosion as seen after 520 ± 40 ybp but without enough stream flow to force the reopening of the lagoon.

Application of empirical mode decomposition, particle swarm optimization, and support vector machine methods to predict stream flows.

Modeling stream flows is vital for water resource planning and flood and drought management. In this study, the performance of hybrid models constructed by combining least square support vector machines (LSSVM), empirical model decomposition (EMD), and particle swarm optimization (PSO) methods in modeling monthly streamflow was evaluated. For establishing the models, 42years of monthly average streamflow data was used in two hydrometer stations located in the Konya Closed Basin, covering 1964 to 2005. Lagged streamflow values ​​were selected as inputs according to partial autocorrelation values ​​in establishing the models. The dataset was divided into 70% training and 30% testing. Model performances were evaluated according to mean square error, root mean square error, correlation coefficients, scatter plot, and Taylor and Violin diagrams. As a result of the analysis, it was determined that the PSO-LSSVM and EMD-LSSVM models were slightly more successful than the single LSSVM model, and the best model was obtained with the EMD-PSO-LSSVM. In addition, in estimating monthly stream flows, 1-, 9-, 10-, 11-, and 12-month lagged streamflow values were the input combination that gave the best results in semi-arid climatic regions. This result demonstrated that EMD improved the performance of both LSSVM and PSO-LSSVM models by 1% to 5% based on correlation coefficient (R) values.

Continuous Electrolysis of Carbon Dioxide for the Production of Formate with High Efficiency

Carbon dioxide capture, storage, and utilization is nowadays considered one of the most interesting approaches to reduce emissions to the atmosphere and, therefore, to mitigate climate change. In this sense, the electrochemical reduction of carbon dioxide to value-added products is gaining attention, since it permits storing excess of energy from renewable and intermittent sources (e.g. solar or wind), in the form of chemicals [1]. Among the reaction products, both formic acid and formate are products of great interest that could be obtained by this process, due to its use as raw materials in several industries and its promising use as a reactant in low-temperature fuel cells and as a renewable hydrogen carrier molecule. Although there is a large number of studies published in literature focusing on the electrocatalytic reduction of carbon dioxide to formic acid and formate[2], few of them achieve relevant trade-offs among the figures of merit typically used to analyze the performance of the process, like (i) the concentration of formate, (ii) the Faradaic Efficiency towards the reaction products, (iii) the energy consumption per kmol of formate and (iv) the current density supplied to the electrochemical reactor.In this context, this communication aims at studying the continuous electrolysis of carbon dioxide, operating with a single pass of the reactants through the electrochemical reactor and using Bi-carbon supported electrocatalysts, to obtain formate with high energy efficiency. In this sense, the electrocatalysts are deposited by air-brushing techniques in the form of a membrane electrode assembly in the cathodic compartment of the electrochemical reactor. This configuration permits direct contact between the Gas Diffusion Electrode and the Nafion cationic exchange membrane which acts as a separator between both compartments of the electrochemical filter press reactor [3].The influence of some key variables is rigorously studied, such as (i) the amount of water in the carbon dioxide input stream, (ii) the current density and (iii) the Bi catalyst loading deposited over the cathode. Firstly, the performance of the electrocatalytic reduction of carbon dioxide to formate employing a Bi catalyst loading of 0.75 mg·cm-2 in terms of i) formate concentration, ii) Faradaic Efficiency towards formate and iii) energy consumption per kmol of formate are assessed as a function of the current density and the water flow in the carbon dioxide input stream. In this point, it is important to remark that, working with an industrially-relevant current density of 200 mA·cm-2 and with a water flow of 0.5 g·h-1, high formateconcentrations of up to 312 g·L-1 were obtained with Faradaic Efficiency towards formateof 25 %, respectively. Consequently, additional tests are performed with a Bi loading in the cathode of the electrochemical filter press of 1.5 mg·cm-2. Combinations of relevant values of concentrations, Faradaic Efficiency for formate and energy consumption of 337 g·L-1, 89 %, and 180 kWh·kmol-1, respectively, are achieved with a current density of 45 mA·cm-2 and with a water flow of 2 g·h-1. These results are one of the best trade-offs reported in the field of carbon dioxide electroreduction to formic acid or formate among these figures of merit, thus achieving a significant advance in this field. However, there are many challenges to be addressed for the implementation of the process at an industrial scale, and therefore, more research focused on the advanced electrocatalytic materials, innovative electrode configuration, and improved electrochemical reactors are still required.

Simulating the Hydrological Processes under Multiple Land Use/Land Cover and Climate Change Scenarios in the Mahanadi Reservoir Complex, Chhattisgarh, India

Land use/land cover (LULC) and climate are two crucial environmental factors that impact watershed hydrology worldwide. The current study seeks to comprehend how the evolving climate and LULC patterns are impacting the hydrology of the Mahanadi Reservoir catchment. A semi-distributed Soil and Water Assessment Tool (SWAT) model was utilized to simulate various water balance elements. Twelve distinct scenarios were developed by combining three different climatic data periods (1985–1996, 1997–2008, and 2009–2020) with four sets of land use maps (1985, 1995, 2005, and 2014). The SWAT model demonstrated strong performance in simulating monthly stream flows throughout the calibration and validation phases. The study reveals that changes in LULC have a distinct effect on the environment. Specifically, the changes in LULC lead to heightened streamflow and reduced evapotranspiration (ET). These changes are mainly attributed to amplified urbanization and the diminished presence of water bodies, forest cover, and barren land within the Mahanadi Reservoir catchment. The combined impact of climate change and LULC shifts reveals complex interactions. Therefore, the present study offers an understanding of how changes in climate and land use over the past few decades have influenced the hydrological behavior of the Mahanadi Reservoir catchment in Chhattisgarh. The findings of this study have the potential to offer advantages to governmental bodies, policymakers, water resource engineers, and planners seeking effective strategies for water resource management. These strategies would be particularly relevant in the context of climate change and land use/land cover changes in ecological regions similar to those of the Mahanadi Reservoir catchment. In addition, a rational regulatory framework for land use patterns is essential for assisting stakeholders in managing water resources and appropriately developing the entire catchment.

Modeling the sediment transport capacity of rill flow using a soil-rock mixture on steep slopes

Study regionYangkeng watershed (E118°03 ', N24°57 '), one of the typical representative areas where Benggang occurs in southern China. Study focusSediment transport capacity (Tc) plays a key role in the construction of models of soil process-based erosion, and is closely related to sediment particle properties. However, few studies have been conducted on Tc using soilrock mixtures along steep slopes. This study investigated the impacts of gravel content and gravel composition on Tc using soilrock colluvial deposits in a steep flume. New hydrological insights for the regionTc increases with the increase of gravel content and proportion of large gravel (5–10 mm), and can be simulated by slope steepness, unit flow discharge, gravel mass content and gravel composition (R2 =0.904; NSE=0.911). The mean weight diameter (MWD) can be used as a sediment characteristic parameter to simulate Tc, and the flow velocity, Reynolds number and stream power are suitable hydrodynamic parameters for predicting Tc. The new equation obtained by dimensionless analysis includes flow properties (unit flow discharge, stream power and Reynolds number) and sediment characteristics (MWD) has a good prediction effect on Tc (R2 =0.991, NSE=0.990), and the simulation accuracy is greater than that of other Tc equations deduced in this study. These results promote understanding of the relationship between Tc and sediment characteristics and contribute to further elucidating the erosion process of soilrock mixtures.

Enabling a process-oriented hydro-biogeochemical model to simulate soil erosion and nutrient losses

Abstract. Water-induced erosion and associated particulate carbon (PC), particulate nitrogen (PN) and particulate phosphorus (PP) nutrient losses are vital parts of biogeochemical cycling. Identifying their intensity and distribution characteristics is of great significance for the control of soil and water loss and nitrogen/phosphorus nonpoint source pollution. This study incorporated modules of physical soil erosion and associated PC, PN and PP losses into a process-oriented hydro-biogeochemical model (Catchment Nutrients Management Model coupled with DeNitrification–DeComposition, CNMM-DNDC) to enable it to predict soil and water loss. The results indicated that the upgraded CNMM-DNDC (i) performed well in simulating the observed temporal dynamics and magnitudes of surface runoff, sediment and PN/PP yields in the lysimetric plot of the Jieliu catchment in Sichuan Province and (ii) successfully predicted the observed monthly dynamics and magnitudes of stream flow, sediment yield and PN yields at the catchment outlet, with significant univariate linear regressions and acceptable Nash–Sutcliffe indices higher than 0.74. The upgraded CNMM-DNDC demonstrated that a greater proportion of PN to total nitrogen (TN) during the period with large precipitation events and amounts than that during the drought period (16.2 %–26.6 % versus 2.3 %–12.4 %). The intensities of soil erosion and particulate nutrient yields in the Jieliu catchment were closely related to land use type in the following order: sloping cultivated upland (SU) > residential areas (RA) > forest land (FL). The scenario analysis demonstrated that high greenhouse gas (GHG) emissions scenarios provided a greater risk of soil erosion than did low GHG emissions scenarios and that land use change (i.e., from SU to FL) could help to mitigate soil and water loss accelerated by climate change in the future. The upgraded model was demonstrated to have the ability of predicting ecosystem productivity, hydrologic nitrogen loads, emissions of GHGs and pollutant gases, soil erosion and particulate nutrient yields, which renders it a potential decision support tool for soil erosion and nonpoint source pollution control coordinated with increasing production and reducing GHG and pollutant gases emissions in a catchment.

Numerical simulation of transpiration cooling for a high-speed boundary layer undergoing transition to turbulence

Cooling the surface of high-speed vehicles by injection of coolant into the flow stream aims to reduce the overall weight and cost of thermal protection systems. Here, the transpiration-based cooling method is studied for a Mach number M∞=5 with coolant injected through a porous layer composed of a staggered arrangement of spheres. Disturbances are introduced into the boundary layer upstream of the porous layer to study in detail the flow regime in which the boundary layer is transitional, including cases where transition is triggered either downstream or directly over the sample. The present work evaluates the effects of transition location, Reynolds number at injection location, and blowing ratio on the cooling performance downstream of the porous sample with heat fluxes that are comparable in magnitude to those seen in laboratory experiments. Flow within the porous layer is found to be unsteady, with a non-negligible streamwise pressure gradient introduced by shock and expansion waves at the leading and trailing edge of the porous sample. For cases where transition occurs just downstream of the sample, the lowest pressure/blowing ratio case results in more cooling immediately after the porous layer, but cooling performance worsens farther downstream. Higher blowing ratio cases show higher effectiveness for a longer distance downstream, despite the transition location moving upstream. For cases where transition occurs over the porous sample, the cooling effect is more consistent, with the heat flux decreasing monotonically with increasing pressure/blowing ratio. The results not only show a strong dependence on transition location, but also that opposite trends in cooling performance are possible when transition occurs just downstream of the injection.

A comparative assessment of open flame flares and enclosed ground flares for cleaner and safer hydrocarbon production in Mexico

Hydrocarbon industry flaring practices emit large amounts of unburned hydrocarbons and climate forcers, creating environmental and social impacts. The objective of this study is to thoroughly compare different flaring technologies in situations where the industry is unable to avoid flaring. An integrated methodology for assessing two flare technologies in terms of Health-Environment-Safety (HES) impacts, economic performance, and safety benefits is proposed. The methodology includes stoichiometric calculations of combustion reactions, pollutants emission estimation, flare dimensioning for an equivalent inflow stream to be flared, and economic scenarios for assessing Enclosed Ground Flares (EGFs) versus Open Flame Flares (OFFs). The methodology was applied to a Mexican hydrocarbon installation that currently operates OFFs with a historical record of low combustion efficiency. If an EGF were to replace the existing OFF, there would be a significant emissions abatement that depends on their realistic operating efficiencies. Furthermore, the EGF has the potential to utilize 1.55thermal GW for energy applications, which is currently being wasted as the OFF releases it into the environment by flaring 3.75 Mm3/d. The safety radius required for the OFF is 9.3 times that required for the EGF of equivalent capacity. Over a 30-year period for the case study, the cumulative investment and O&M costs for EGF are about 23% less than for OFF. The consequence analysis with the PHAST software found that various failure conditions can be contained within the EGF combustion chamber without causing significant damage to the facility. However, the impacts of disturbances in the OFF such as gas clouds, flash fires, and explosions are around the torch. All these findings indicate that replacing OFF with EGF would be a safer and more economical solution in the future, as it also helps reduce pollutant emissions.

Adaptive real-time reconfiguration gate scheduling scheme using time perceptive stream

An adaptive real-time gate scheduling scheme for time perceptive stream or packet flow is proposed to improve the standards of Ultra Low Latency during data transmission. For highly dynamic network conditions, the conventional configuration scheme is not suitable and therefore an adaptive real-time gate scheduling method is proposed for time perceptive streams. This dynamicity reconfiguration is difficult and the scheduling problem is formulated using Field Programmable Gate Array – Boolean Satisfiability Problem (FPGA-BSP) solver. This proposed scheme highly helps in network dynamicity conditions with good bandwidth utilization and high flexibility. End-to-end latency is required to be on sub-milliseconds order deal with the applications such as Industrial Internet of Things, 5G and 6G mobile, tactile internet and so on. Simulation analysis is carried out to prove the efficiency of the proposed model.

Role of Biosynthesized Silver Nanoparticles with Trigonella foenum-graecum Seeds in Wastewater Treatment

As the human population continues to escalate, its requirement for clean water is also increasing. This has resulted in an increased dependency on wastewater effluent to maintain the base flow of urban streams, especially in water-stressed regions. The present study reports the synthesis of AgNPs with green credentials using an aqueous extract of Trigonella foenum-graecum seeds. The observance of surface plasmon resonance (SPR) with UV–Vis spectrophotometry confirmed the presence of spherical/oblong particles with a mean diameter of 43.8 nm and low polydispersity index (PDI) of 0.391 measured by transmission electron microscopy (TEM) and DLS (dynamic light scattering) technique, respectively. The elemental map of AgNPs was demonstrated with energy-dispersive spectroscopy (EDS) and the constituent functional groups were identified by the FTIR spectra, which were similar to the bulk seed extract with a slight shift in the pattern. The emission spectrum of nanoparticles was recorded for the excitation wavelength of 349 using fluorescence microscopy and the crystalline structure was assessed using X-ray diffraction. The potential wastewater remedial efficacy of the synthesized AgNPs was evaluated based on the water quality parameters (pH, EC, BOD, COD) of the sewage effluent collected from a local Sewage Treatment Plant (STP). Furthermore, the photo degradative efficacy was investigated using the degradation percentage of Crystal Violet (CV) dye, which was recorded as 94.5% after 20 min. In addition, the antimicrobial activity of the NPs versus bulk seed extract was assessed against two bacterial strains, Escheria coli and Staphylococcus aureus, using the disc diffusion method. The AgNPs showed a profound modulatory effect on the water quality parameters, coupled with marked antimicrobial and photodegradative activity. Thus, the biogenically synthesized AgNPs offer a prospective potential for use in wastewater remediation strategies.

Evaluation of Legacy Forest Harvesting Impacts on Dominant Stream Water Sources and Implications for Water Quality Using End Member Mixing Analysis

Forests are critical water supply regions that are increasingly threatened by natural and anthropogenic disturbance. Evaluation of runoff-generating processes within harvested and undisturbed headwater catchments provides insight into disturbance impacts on water quality and drinking water treatability. In this study, an extensive hydrologic dataset collected at the experimental Turkey Lakes Watershed (TLW) located on the Canadian Shield was used to quantify sources of stormflow in legacy clear-cut (24-years post harvesting) and forested (control) headwater catchments using an end member mixing analysis (EMMA) model. Stream water, groundwater, soil water, and throughfall water quality were evaluated during spring snowmelt, stormflow, and fall wet-up. Groundwater chemistry was similar to stream water chemistry in both catchments, suggesting that groundwater is a major contributor to stream flow. The water chemistry in small wetlands within the study catchments was comparable to stream water chemistry, suggesting that wetlands are also important contributors to stream flow. Differences in wetland position between the legacy clear-cut and control catchments appeared to have a greater influence on source contributions than legacy harvesting. Results from this study provide insight into runoff-generation processes that reflect event/seasonal flow dynamics and the impacts on water quality.

Low-Flow (7-Day, 10-Year) Classical Statistical and Improved Machine Learning Estimation Methodologies

Water resource managers require accurate estimates of the 7-day, 10-year low flow (7Q10) of streams for many reasons, including protecting aquatic species, designing wastewater treatment plants, and calculating municipal water availability. StreamStats, a publicly available web application developed by the United States Geologic Survey that is commonly used by resource managers for estimating the 7Q10 in states where it is available, utilizes state-by-state, locally calibrated regression equations for estimation. This paper expands StreamStats’ methodology and improves 7Q10 estimation by developing a more regionally applicable and generalized methodology for 7Q10 estimation. In addition to classical methodologies, namely multiple linear regression (MLR) and multiple linear regression in log space (LTLR), three promising machine learning algorithms, random forest (RF) decision trees, neural networks (NN), and generalized additive models (GAM), are tested to determine if more advanced statistical methods offer improved estimation. For illustrative purposes, this methodology is applied to and verified for the full range of unimpaired, gaged basins in both the northeast and mid-Atlantic hydrologic regions of the United States (with basin sizes ranging from 2–1419 mi2) using leave-one-out cross-validation (LOOCV). Pearson’s correlation coefficient (R2), root mean square error (RMSE), Kling–Gupta Efficiency (KGE), and Nash–Sutcliffe Efficiency (NSE) are used to evaluate the performance of each method. Results suggest that each method provides varying results based on basin size, with RF displaying the smallest average RMSE (5.85) across all ranges of basin sizes.

Numerical analysis of pore-scale CO2-EOR at near-miscible flow condition to perceive the displacement mechanism

Gas flooding through the injection of text{CO}_{2} is generally performed to achieve optimum oil recovery from underground hydrocarbon reservoirs. However, miscible flooding, which is the most efficient way to achieve maximum oil recovery, is not suitable for all reservoirs due to challenge in maintaining pressure conditions. In this circumstances, a near-miscible process may be more practical. This study focuses on pore-scale near-miscible text{CO}_{2}–Oil displacement, using available literature criteria to determine the effective near-miscible region. For the first time, two separate numerical approaches are coupled to examine the behavior of text{CO}_{2}–oil at the lower-pressure boundary of the specified region. The first one, the Phase-field module, was implemented to trace the movement of fluids in the displacement text{CO}_{2}–Oil process by applying the Navier–Stokes equation. Next is the TDS module which incorporates the effect of text{CO}_{2} mass transfer into the oil phase by coupling classical Fick’s law to the fluids interface to track the variation of text{CO}_{2} diffusion coefficient. To better recognize the oil recovery mechanism in pore-scale, qualitative analysis indicates that interface is moved into the by-passed oil due to low interfacial tension in the near-miscible region. Moreover, behind the front ahead of the main flow stream, the text{CO}_{2} phase can significantly displace almost all the bypassed oil in normal pores and effectively decrease the large amounts in small pores. The results show that by incorporating mass transfer and capillary cross-flow mechanisms in the simulations, the displacement of by-passed oil in pores can be significantly improved, leading to an increase in oil recovery from 92 to over 98%, which is comparable to the result of miscible gas injection. The outcome of this research emphasizes the significance of applying the text{CO}_{2}-EOR process under near-miscible operating conditions.

Climate change impacts on groundwater discharge-dependent streamflow in an alpine headwater catchment

Climate change will have—and, in much of the world, is already having—a pronounced impact on alpine water resources. A deeper understanding of the future role of groundwater in alpine catchments, including quantification of climate change impacts on groundwater discharge, is vital for understanding the future of alpine water resources as a whole. Here, we develop and couple a geophysics-informed groundwater model with a net recharge model to investigate the impacts of climate change on a nival-regime alpine headwater catchment with significant unconfined Quaternary aquifer coverage. Flow in the groundwater-fed stream at the catchment outlet is analysed to determine changes in its annual dynamics. Comparing the periods 2020–2040 and 2080–2100 under ten RCP-8.5 climate models, we find a 35 % decrease in mean groundwater discharge and an increase in no-flow periods from ~0 % to 4.3 %. We also observe significant changes to the timing of monthly mean discharge maxima and minima, which shift ~1 month and ~5 months earlier, respectively. While groundwater has the potential to dampen the impacts of snow cover loss, currently perennial nival-regime alpine streams could be at risk of becoming intermittent by the end of the century. Our study underscores the increasingly critical role that groundwater will play in alpine catchments and emphasizes the need for quantitative understanding of the limits to its buffering capacity.

Estimating uncertainty in streamflow and solute fluxes at the Hubbard Brook Experimental Forest, New Hampshire, USA

AbstractStream fluxes are commonly reported without a complete accounting for uncertainty in the estimates, which makes it difficult to evaluate the significance of findings or to identify where to direct efforts to improve monitoring programs. At the Hubbard Brook Experimental Forest in the White Mountains of New Hampshire, USA, stream flow has been monitored continuously and solute concentrations have been sampled approximately weekly in small, gaged headwater streams since 1963, yet comprehensive uncertainty analyses have not been reported. We propagated uncertainty in the stage height–discharge relationship, watershed area, analytical chemistry, the concentration–discharge relationship used to interpolate solute concentrations, and the streamflow gap‐filling procedure to estimate uncertainty for both streamflow and solute fluxes for a recent 6‐year period (2013–2018) using a Monte Carlo approach. As a percentage of solute fluxes, uncertainty was highest for NH4+ (34%), total dissolved nitrogen (8.8%), NO3− (8.1%), and K+ (7.4%), and lowest for dissolved organic carbon (3.7%), SO42− (4.0%), and Mg2+ (4.4%). In units of flux, uncertainties were highest for solutes in highest concentration (Si, DOC, SO42−, and Na+) and lowest for those lowest in concentration (H+ and NH4+). Laboratory analysis of solute concentration was a greater source of uncertainty than streamflow for solute flux, with the exception of DOC. Our results suggest that uncertainty in solute fluxes could be reduced with more precise measurements of solute concentrations. Additionally, more discharge measurements during high flows are needed to better characterize the stage‐discharge relationship. Quantifying uncertainty in streamflow and element export is important because it allows for determination of significance of differences in fluxes, which can be used to assess watershed response to disturbance and environmental change.

Leveraging Groundwater Dynamics to Improve Predictions of Summer Low‐Flow Discharges

AbstractSummer streamflow predictions are critical for managing water resources; however, warming‐induced shifts from snow to rain regimes impact low‐flow predictive models. Additionally, reductions in snowpack drive earlier peak flows and lower summer flows across the western United States increasing reliance on groundwater for maintaining summer streamflow. However, it remains poorly understood how groundwater contributions vary interannually. We quantify recession limb groundwater (RLGW), defined as the proportional groundwater contribution to the stream during the period between peak stream flow and low flow, to predict summer low flows across three diverse western US watersheds. We ask (a) how do snow and rain dynamics influence interannual variations of RLGW contributions and summer low flows?; (b) which watershed attributes impact the effectiveness of RLGW as a predictor of summer low flows? Linear models reveal that RLGW is a strong predictor of low flows across all sites and drastically improves low‐flow prediction compared to snow metrics at a rain‐dominated site. Results suggest that strength of RLGW control on summer low flows may be mediated by subsurface storage. Subsurface storage can be divided into dynamic (i.e., variability saturated) and deep (i.e., permanently saturated) components, and we hypothesize that interannual variability in dynamic storage contribution to streamflow drives RLGW variability. In systems with a higher proportion of dynamic storage, RLGW is a better predictor of summer low flow because the stream is more responsive to dynamic storage contributions compared to deep‐storage‐dominated systems. Overall, including RLGW improved low‐flow prediction across diverse watersheds.

Monthly Streamflow Prediction Using ANN, KNN and ANFIS models: Example of Gediz River Basin

Stream flow forecasting is very important in many aspects such as water supply, irrigation, building water infrastructures, and taking precautions against floods. The ability to forecast future streamflow helps us anticipate and plan for upcoming flooding, decreasing property destruction, preventing deaths and managing water in the best way possible. Different hydrological models have been developed for predicting streamflow and they have different characteristics, driven by the research area and available data. İn this study, three types of Artificial Intelligence models; K-Nearest Neighbor (KNN), Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) have been used to study the Gediz River Basin which is located in the Aegean region of western Turkey. The results varied due to the complication of the data and different parts of the study area as well as the structure of the models, over all, looking at Regression coefficient (R2), Root Mean Square Error (RMSE) and Wilcoxon (WT) values, ANFIS is more accurate compared to ANN and KNN models. Conversely, according to Taylor diagram, KNN is more accurate compared to ANN and ANFIS.

Study of micro-scale flow characteristics under surface acoustic waves

As an effective tool for contactless manipulation of submicrometer scale objects, the controllability of acoustic streaming velocity and flow field morphology determines the accuracy of object migration and the completeness of three dimensional (3D) imaging. This paper proposes an equivalent acoustic streaming driving force model that is applicable to both two dimensional (2D) and 3D calculations and constructs a numerical method for submicrometer microsphere migration and rotation velocity in acoustic streaming. The results show that the relationship between the peripheral vortex size Lp/wc and the relative acoustic streaming velocity vas/vf satisfies Lp/wc = 0.125vas/vf0.36 under certain geometrical conditions. Reducing the spatial confinement and increasing the inter-vortex distance will increase the energy release efficiency, reduce the pressure gradient distribution and convective dissipation rates, increase the vortex intensity and radiation range, and consequently, increase the vortex characteristic size. In complex 3D vortex flow fields, suspended objects are affected by velocity distributions and exhibit motions such as cross-flow lines and rotation. For larger vortex structure sizes, full 3D imaging is more favorable due to the increased rotation speed and period of motion along the orbit of the submicrometer microspheres. This study helps us to reveal the modulation mechanism of acoustic streaming field flow characteristics, enrich the basic theory of alternating orbital motion and forces on objects in vortex structures, and provide guidance for acoustic flow-based contactless object manipulation.

Numerical investigation of non-planarity and relative motion for bionic slotted wings

Bird wings have split primary feathers that extend out from the wing surface. This structure is called the wingtip slot, which is recognized as a product of bird evolution to improve flight performance. In this paper, numerical simulations based on RANS (Reynolds-averaged Navier–Stokes) equations are conducted to examine and understand the influence of wingtip slots on six wings at Re = 100 000. The overlapping grid method, driven by an in-house UDF (User Defined Function), is used to model the motion of the bionic slotted wings. The motion law of the winglets is improved based on the law extracted from a level-flying bald eagle. Then the aerodynamic force, pressure distribution, vorticity contours, wake stream, and other flow structures of the slotted wings with different layouts were compared and analyzed. The results show a significant increase in aerodynamic force when the slotted wingtips are employed. The maximum lift-to-drag ratio is also improved in our designed wing model with a non-planar wingtip by a maximum of 34% from the base wing. Each winglet works as a single wing due to the existence of slots, with a chordwise pressure distribution similar to that of the main wing. The vortex structures of slotted wings show expressive changes in the tip vortex as compared with the base wing. Additionally, an innovative bionic slotted wing is proposed with a dynamic wingtip that forms varying gaps between winglets. Due to the collective mechanism of aerodynamic interaction among multiple winglets for the innovative wing, it acquires the optimal time-averaged force during a flapping period. As expected, the slotted wingtip reduces the main wingtip vortex intensity and creates weaker vortices. The non-planarity and relative motion of the wingtip strengthen its weakening effect on the wingtip vortex and wake.

A Case Study on GIS Based Method to Develop Geographically Distributed Synthetic Unit Hydrograph using Geo-Spatial Tools in Ungauged Sub-watershed of Ambika River Basin, Gujarat

Abstract In this work, using Snyder, SCS, and the geographically distributed approaches, synthetic unit hydrographs are developed for the recurring flood-impacted ungauged sub-watershed in the Ambika river basin of Gujarat. Due to the scarcity of observed rainfall-runoff data, enforcement of effective flood control measures have not been implemented in this area. Hence the districts in the Ambika river basin regularly experience unexpected floods during the monsoon season, resulting in loss of life and property. The unit hydrograph of a watershed is essential for developing a flood hydrograph, which is useful for flood forecasting. The majority of Indian watersheds are not gauged, and there is not enough rainfall-runoff data to develop a unit hydrograph. However, there are several approaches available that may be used to develop synthetic unit hydrographs using different regionally based empirical equations, and some of them are mentioned above. Using geospatial tools is one of the GIS-based methods for obtaining synthetic unit hydrographs that solely take into account the digital elevation model (DEM) which eliminates the use of regional empirical constants. The geographically distributed synthetic unit hydrograph (GDSUH) approach is employed here on the idea of distributed time-area unit hydrograph and spatial distribution of overland and channel flow velocity. The cumulative travel time map has been divided into isochrones to develop a time-area curve and the resulting unit hydrograph. In this technique, a pure translation flow process is assumed. This approach is most appropriate for watersheds of smaller size. Hence, in this present study, a smaller, unmeasured sub-watershed with an area of 46 km2 is chosen, and the synthetic unit hydrographs are derived using each of the three approaches. The findings from this study were analyzed to determine the most appropriate method for this region. It was observed that the GDSUH is more suitable in comparison to the other two conventional synthetic unit hydrograph approaches. In smaller and un-gauged watersheds, this method gives a conceptual model for forecasting stream flow hydrographs that will capture the geographically distributed nature of the rainfall-runoff process. Additionally, it has the advantages of being simple, quick, inexpensive, and time-saving, especially for smaller regions that lack rainfall-runoff data.