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Discrepancy in percent between the suggested explicit approximation top and the recurrence formula 2 bottom in comparison to the approximation of the writers for J1. Discontinues lines indicates that the curve is limited to the range of the axis.
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Cited By (since 1996): 1, Export Date: 21 November 2012, Source: Scopus
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Citations
... Based on the regression analysis, Abad and García (2006) found an analytical expression to estimate the integral J 1 , which is well approximated by a sixth-order regression equation. The formulation for J 1 that is of practical use is shown in the following: ...
... All the coefficients are relevant to the parameter δ b as presented in Table 1. Take δ b to be 0.05 based on the existing studies for predicting sediment entrainment or near-bed sediment concentrations (Abad and García 2006). Furthermore, García and Parker (1991) provided a detailed comparison of eight relations to the near-bed concentration c b (or entrainment rate at equilibrium condition) against a standard set of experimental data. ...
... As such, P 23 represents the percentage of the transitions 2 → 3 in all the state transitions (2 → 1 and 2 → 3). Provided that there are N 2 particles moving in the bed-load layer (state 2) and N 2j ðj ¼ 1; 2; 3Þ is the number of bed-load particles that will be in state j at the next moment, P 23 can be expressed as follows: Note: Data from Abad and García (2006). The row in bold: Used in this study. ...
A three-state continuous-time Markov chain is proposed to model the movement of sediment particles across three different states, i.e.,bed material, bed load, and suspended load layer. The proposed model incorporates an exchange process between the bed load and the suspended load layer, in addition to the interface between the bed-load layer and the bed material, as normally considered in most of the existing sediment transport studies. In this study the mathematical treatment of the continuous-time Markov chain is clarified to stress the difference in definitions of the continuous-time and discrete-time Markov chains. With the employment of the continuous-time Markov model, the bed-load transport capacity in the long run and the time-varying transport rates can be derived. On the other hand, the three-state model can assist in distinguishing whether the flow is subject to significant suspended load or not. Furthermore, the distribution of particles in each of the three layers can be quantified. The proposed model is validated against natural river data. The comparison has shown a reasonably good agreement and thus the validity of the proposed model is confirmed. (C) 2013 American Society of Civil Engineers.
Microplastics (MPs) pose significant risks to marine ecosystems and human health, necessitating accurate predictions of their distributions in aquatic environments for effective risk mitigation. However, understanding MP transport dynamics is challenging because of the inadequate representation of MP characteristics such as size, shape, and density in numerical models. Further, the accuracy of the MP vertical profiles in existing models has not been thoroughly validated. Thus, we developed an MP transport model within the Finite Volume Community Ocean Model framework (FVCOM-MP) by integrating MP characteristics. We validated FVCOM-MP against experimental and analytical data, focusing on various MP transport modes and transitions. FVCOM-MP successfully replicates MP profiles in different transport modes, including the bedload, surface load, suspended load, and mixed load modes. Additionally, we introduce phase diagrams for classifying MP transport modes based on particle characteristics, enhancing our understanding of MP dynamics in aquatic systems. The transport modes for a number of real-world MP particles, including fishing line, plastic bag/bottle fragments, synthetic fibers, tire wear particles, polyvinyl chloride and expanded polystyrene pellets, were analyzed with these phase diagrams.
Future sediment dynamics may be affected by changing climates or hydrological regimes because of the close link between hydrology and sediment erosion, deposition, and transport. Previously, investigations of these potential changes have been constrained by a combination of limited observational data, hydrological drivers, and appropriate mechanistic models. Additionally, there is often ambiguity regarding how to disentangle the impacts of climate and hydrology from direct human factors such as reservoirs and land‐use change which often exert more control over sediment dynamics. In this study, we utilize a recently‐developed, large‐scale, distributed, mechanistic sediment transport model to project future sediment erosion, deposition, and transportation within the Fraser River Basin (FRB) in British Columbia, Canada—a basin with historical water flux and sediment load observations and limited anthropogenic influences upstream of its delta. The sediment model is driven by synthetic land‐surface hydrology derived from SRES scenarios A1B, A2, and B1 which were provided by the Pacific Climate Impacts Consortium. Resulting simulations of water flux and sediment load from 1965‐1994 are first validated against observational data then compared to future projections. Future projections show an overall increase in annual hillslope erosion and in‐channel transportation, a shift towards earlier spring peak erosion and transportation, and longer persistence of the sediment signal through the year. These shifts in timing and annual yield may have deleterious effects on spawning sockeye salmon and are insufficient to counteract future coastal retreat caused by sea‐level rise.
Modeling sediment transport through large basins presents a challenging problem. The relation between water flux and sediment load is complex, and substantial erosion and transport can occur over small spatial and temporal scales. Analysis of large-scale basins often relies on lumped empirical models that do not consider spatial or subannual variability. In this study, we adapt a small-scale, mechanistic, distributed suspended sediment transport model for application to large basins. The model is integrated into the Terrestrial Hydrology Model with Biochemistry to make use of the Terrestrial Hydrology Model with Biochemistry's dynamic water routing. The coupled model is applied to the 230,000-km² Fraser River Basin in British Columbia, Canada, using climatic and hydrological inputs provided by a historical run of the Variable Infiltration Capacity model. Hourly simulations are aggregated into monthly and long-term averages which are compared against observations. Simulated long-term lake sedimentation values are within an order of magnitude of observations, and monthly load simulations have an average R² of 0.70 across the five study stations with available data. Model results indicate that sediment loads from tributaries do not heavily influence dynamics along the main stem and suggest the importance of network connectivity. Sensitivity analysis indicates that models may benefit from characterizing bed load irrespective of its contribution to total sediment load. Historical simulations over the 1965–2004 period reveal important changes in sediment dynamics that could not be captured with a lumped model, including a decrease in basin sediment load interannual variability driven by changes in runoff and load variability within a key subbasin.
Sediment yield (SY) plays an important role in the global carbon cycle for carrying particulate carbon into rivers and oceans, but it is rarely represented in Earth System Models (ESMs). Existing SY models have mostly been tested over a few small catchments in specific regions or in large river basins globally. By comparing the performance of eight well-known SY models in 454 small catchments with various land covers and uses across the United States, Canada, Puerto Rico, U.S. Virgin Islands and Guam, we identified the simple Morgan model for its better performance in representing the spatial variability of continental scale SY at spatial scales relevant to ESMs (several to hundreds of km 2) than other models because of a more realistic representation of runoff-driven erosion and sediment transport capacity in the context of current data availability. The results also indicated that runoff-driven erosion should be formulated using a power function of runoff, shear stress or stream power to better represent the total effect of concentrated flow if gully erosion and channel erosion are not explicitly modeled. We also demonstrated that the Morgan model can be further improved by removing snowmelt-driven runoff in modeling runoff-driven erosion and to a minor degree by integrating a landslide model. The improved Morgan model explains 57% of the spatial variability of the measured SY. The new model also demonstrated the capability to simulate SY in cross-validation catchments at fine temporal scales, which is important for coupling sediment yield with other biogeochemistry processes in ESMs.
Einstein’s integrals constitute one of the salient developments in theoretical sediment mechanics. An analysis of the accuracy and computational efficiency of proposed methods for the calculation of the Einstein’s integrals is presented. First, the accuracy of those techniques is determined using comparisons against highly accurate numerical results. For an infinite series solution, a study of accuracy versus number of terms in the partial sum is performed. Then, the central processing unit (CPU) times of the procedures are determined and compared over a full set of Rouse numbers and relative bedload-layer thicknesses. Finally, parallel versions of the methods are presented, and their parallel efficiency is assessed. Based on the criteria of accuracy, CPU time, and parallelization efficiency, it is concluded that the method by Guo and Julien, with modifications by Srivastava, is overall more efficient for implementation in sediment-transport codes.
By the use of the binomial expansion theorem, the series expansion relations in terms of the complete gamma function are obtained for Einstein integrals arising in the hydraulic and modern sediment transport mechanics. The approach presented for Einstein integrals is accurate enough over the whole range of parameters. The computational time for calculation of the series with respect to the literature is fast. Furthermore, the comparison of the method with numerical calculations demonstrates the applicability and accuracy of the method.
A modeling framework that combines both two-dimensional (2D) and one-dimensional (1D) numerical models for the evaluation of organic-matter transport across the bed-water interface is presented. Emphasis is placed on capturing oxygen demand in the water column associated with the resuspension of organic sediments from the bottom. The proposed numerical approach solves the hydrodynamics coupled with sediment transport and water quality dynamics and represents a substantial improvement to the state of the art of water quality modeling methodologies available in the literature. A biochemical oxygen demand (BOD)-dissolved oxygen (DO) water quality module is incorporated into the 2D depth-averaged numerical model STREMR-HySedWq. The model is applied to the South Fork of the South Branch of the Chicago River, known as Bubbly Creek, with the goal of modeling combined sewer overflow (CSO) events and their impact on DO levels in the short-term (hours or days). Given the intermittent nature of this kind of events, STREMR-HySedWq was used for modeling the overflow phase, while the period following a given CSO event, when water is essentially quiescent in the creek, was modeled with a simpler 1D, area-averaged, dispersion-reaction BOD-DO model. The proposed conceptual and numerical approach is capable of capturing the key processes, thus providing both useful preliminary results as well as important guidance to assess potential water quality improvement and sediment management solutions in Bubbly Creek, Illinois.
Export Date: 2 April 2013, Source: Scopus, Art. No.: F00A04, doi: 10.1029/2012JF002400, Language of Original Document: English, Correspondence Address: Patil, S.; National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, Corvallis, OR 97333, United States; email: sopan.patil@gmail.com, References: Abad, J.D., Garcia, M.H., Discussion of efficient algorithm for computing Einstein integrals by Junke Guo and Pierre Y. Julien (2006) Journal of Hydraulic Engineering, 132 (3), pp. 332-334. , DOI 10.1061/(ASCE)0733-9429(2006)132:3(332);
