Geospatial analysis of specific degradation in South Korea

2019 Summer.Includes bibliographical references.South Korea experienced many local and concentrated sediment problems such as landslides, upland erosion, rills and valleys, aggradation/degradation, and flood plain sediment deposition. These problems vary in space and time, therefore a reliable and consistent approach to model sediment processes is desirable. In contrast to sediment yield at the basin scale, Specific Degradation (SD) is defined as the ratio of the sediment yield divided by the watershed area. Field measurements of discharge and sediment concentration are analyzed at 70 stations in South Korea. Half of the sampled river basins (35 stations) represent streams in mountain regions and the other half represent rivers. The Modified Einstein Procedure (MEP) was used to determine the total sediment load at all stations. The Flow Duration – Sediment Rating Curve (FD-SRC) method was used to determine the sediment yield and specific degradation for all gauging stations. The annual sediment yield of 70 rivers and streams in South Korea ranged from 10 to 1,000 tons/km2▪yr. The application of three existing models from the literature showed Root Mean Square Errors (RMSE) in excess of 1,400 tons/km2▪yr and gave negative values of the Nash-Sutcliffe Efficiency coefficient (NSE) for existing models, which indicates that the observed mean is a better predictor than the model. The main characteristics of each watershed were analyzed using GIS tools such as ArcGIS version 10.3.1. The data used for the analysis included: (1) daily precipitation data at 60 stations from the Korea Meteorological Administration (KMA); (2) a detailed soil map from the National Institute of Agriculture Sciences; (3) a 5m by 5m resolution Digital Elevation Model (DEM); and (4) land cover raster data at a 10 m resolution from the Ministry of Environment (ME). Seven regression models based on these watershed characteristics are proposed to estimate the mean annual sediment yield and specific degradation. In decreasing order of importance, the meaningful parameters are: (1) drainage area; (2) mean annual precipitation; (3) percentage of urbanized area; (4) percentage of sand of the surface soil (upper 50cm); (5) percentage of wetland and water; and (6) morphometric parameters such as watershed average slope and two parameters of the hypsometric curve. The RMSE for the newly developed models decreased to 90 tons/km2▪yr and the NSE increased from -50 to 0.5, which shows good agreement between the model and the measured sediment yield on these watersheds. The calculated specific degradation and mean annual soil loss of mountain streams were larger than alluvial rivers. Erosion loss mapping at 5m, 30m and 90m was also developed from the Revised Universal Soil Loss Equation (RUSLE). Satellite images and aerial photos were used to better represent geospatial features affecting erosion and sedimentation. Long-term reservoir sedimentation measurements were available to determine the Sediment Delivery Ratio (SDR). An important finding from this analysis is that the percentage of the area covered with wetland and water is well-correlated with the estimated sediment delivery ratios. It suggests that the transfer of sediment to the rivers is affected by wetlands located near alluvial rivers. The erosion maps at 5m resolution could clearly show unique erosion features (i.e. hill slopes, croplands, and construction sites) and locate areas for sediment deposition (i.e. wetlands and agricultural reservoirs). In comparison, the gross erosion rates at 90 m resolution were highly distorted and could not delineate the areas with high upland erosion rates. Sustainable sediment management with these methodologies could be helpful to solve various erosion and sedimentation problems

Reactive transport modeling of nutrients in arctic tundra streams

2014 Fall.Includes bibliographical references.The one dimensional solute transport inflow and storage (OTIS) model is used to simulate the transport of non-conservative and conservative solutes in arctic tundra streams. Field research was conducted in I8 Inlet and Outlet streams, (in northen Alaska) which are located upstream and downstream of 18 Lake between June and September 2010 and 2011 (thaw season) and these two streams are classified as alluvial, low gradient, headwater tundra streams. Repeat solute injections were conducted on both streams. Two sets of solute injections were made, Injection A is sodium chloride (NaCl) and phosphate (PO4) and Injection B is sodium chloride (NaCl) and ammonium (NH4). The sodium chloride is conservative and other two solutes are non-conservative solutes. With the observed concentration data, OTIS-P was used to estimate the model parameters values related to transport (dispersion and advection), transient storage and nutrient uptake mechanisms, by nonlinear least squares fit. The dispersion coefficient and main channel cross-sectional area parameters represented transport, storage zone cross-sectional area and exchange coefficient parameters represent transient storage, and 1st order decay coefficient in main channel and storage zone represent nutrient uptake. Additionally, transport and uptake metrics were calculated with estimated parameters. We assumed discharge, stream water temperature, and date (as a surrogate for thaw depth beneath the stream) were potential control variables on transport, transient storage, and nutrient uptake processes. Linear regression was conducted to identify potential relationships between these estimated parameters and metrics and control variables. Hydraulic controls are positively correlated with transport and transient storage mechanisms and stream temperature has positive relationships with nutrient uptake of non-conservative solutes (NH4 and PO4). Although, this study did not found direct influence of date (indicate of thaw depth) as a control, active layer condition is an important factor in solute transport dynamics in arctic region. Moreover, additional controls should be considered to explain solute transport dynamics more exactly. Beyond the scope of this study, for example, stream ecosystem status or activity may more directly explain NH4 and PO4 uptake variability

Effective Scheduling of Grid Resources Using Failure Prediction

In large-scale grid environments, accurate failure prediction is critical to achieve effective resource allocation while assuring specified QoS levels, such as reliability. Traditional methods, such as statistical estimation techniques, can be considered to predict the reliability of resources. However, naive statistical methods often ignore critical characteristic behavior of the resources. In particular, periodic behaviors of grid resources are not captured well by statistical methods. In this paper, we present an alternative mechanism for failure prediction. In our approach, the periodic pattern of resource failures are determined and actively exploited for resource allocation with better QoS guarantees. The proposed scheme is evaluated under a realistic simulation environment of computational grids. The availability of computing resources are simulated according to real trace that was collected from our large-scale monitoring experiment on campus computers. Our evaluation results show that the proposed approach enables significantly higher resource scheduling effectiveness under a variety of workloads compared to baseline approaches

A Derivative-Free Mesh Optimization Algorithm for Mesh Quality Improvement and Untangling

We propose a derivative-free mesh optimization algorithm, which focuses on improving the worst element quality on the mesh. The mesh optimization problem is formulated as a min-max problem and solved by using a downhill simplex (amoeba) method, which computes only a function value without needing a derivative of Hessian of the objective function. Numerical results show that the proposed mesh optimization algorithm outperforms the existing mesh optimization algorithm in terms of improving the worst element quality and eliminating inverted elements on the mesh

Effect of grain boundaries on ion migration in stabilized δ-Bi2O3 thin- film electrolyte

Solid electrolytes with high oxygen-ion conductivity are of significant interest for many applications. Over the past several decades, numerous studies have been conducted on the effect of grain boundaries on the process of increasing the ionic conductivity of solid electrolytes. Given that nanocrystalline thin- or thick-films have been investigated in relation to lowering the operating temperature of solid electrolytes to less than 650 °C, more rigorous and quantitative assessments are necessary to determine how the ion transport characteristics are affected by the numerous interfaces formed in nano-grains devices. Please click Additional Files below to see the full abstract

Right sizes of nano- and microstructures for high-performance and rigid bulk thermoelectrics

In this paper, we systematically investigate three different routes of synthesizing 2% Na-doped PbTe after melting the elements: (i) quenching followed by hot-pressing (QH), (ii) annealing followed by hot-pressing, and (iii) quenching and annealing followed by hot-pressing. We found that the thermoelectric figure of merit, zT, strongly depends on the synthesis condition and that its value can be enhanced to similar to 2.0 at 773 K by optimizing the size distribution of the nanostructures in the material. Based on our theoretical analysis on both electron and thermal transport, this zT enhancement is attributed to the reduction of both the lattice and electronic thermal conductivities; the smallest sizes (2 similar to 6 nm) of nanostructures in the QH sample are responsible for effectively scattering the wide range of phonon wavelengths to minimize the lattice thermal conductivity to similar to 0.5 W/m K. The reduced electronic thermal conductivity associated with the suppressed electrical conductivity by nanostructures also helped reduce the total thermal conductivity. In addition to the high zT of the QH sample, the mechanical hardness is higher than the other samples by a factor of around 2 due to the smaller grain sizes. Overall, this paper suggests a guideline on how to achieve high zT and mechanical strength of a thermoelectric material by controlling nano-and microstructures of the material

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong