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901.
Measuring and analyzing internal dam temperature may provide insight into evaluating the integrity of earthen dams. Temperature in a dam, with the advent of modern distributed temperature sensing (DTS) technique, is conveniently measured. The analysis of the temperature is conducted based on a hydro-thermal coupled analysis technique. In this study, DTS-based temperature data and VS2DHI (a finite difference code for analyzing two-dimensional heat transport in porous media) were used to analyze the hydro-thermal coupled behavior in a dam. The results of this analysis show that the temperature variation in an earthen dam is closely related to seepage conditions. Additionally, a localized high-temperature (26 °C) zone found in the measured data of the dam, which raised concern to engineers on site, is explained through either hot water infiltration into the foundation layer or lower permeability of the foundation layer than the magnitude that appeared in the design document. These findings demonstrate that hydro-thermal coupled analysis has the potential for evaluating the integrity of earthen dams. 相似文献
902.
This paper presents a new method that integrates gradient and residual values for rank ordering of stations in a monitoring network (GaRiRO). The innovation is derived from the fact that the parameter (dependent variable) gauged through the monitoring network is modelled using independent variables that influence its measured quantity. And the dependent variable exhibit non-stationary spatial gradient with respect to the independent variables, particularly in complex terrain. GaRiRO technique was developed to prioritize the rain gauge stations for optimizing the existing network and selection of the best locations for relocation or installation of gauges. Although initially aimed to assist hydrologists with a ranking scheme for rain gauge stations, it can be applied to any environmental, meteorological or hydro-meteorological monitoring network. The new procedure is based on deriving gradient and residual value at each station by modeling the spatial relationship of dependent-independent variable using geographically weighted regression (GWR) technique. For the prospective stations with no record, the gradient value is estimated using GWR model and the residual value is derived from the residual map generated by applying kriging technique on the residual derived at all gauged locations. The method combines the decision factor with analytical strength of GIS for prioritizing the stations which results in limited number of trials for installation or relocation of gauges to yield optimized network configuration. 相似文献
903.
Mohammad Saleh Vahdatpour Hedieh Sajedi Farzad Ramezani 《Earth Science Informatics》2018,11(3):413-422
Air pollution is one of the most important problems in the new era. Detecting the level of air pollution from an image taken by a camera can be informative for the people who are not aware of exact air pollution level be declared daily by some organizations like municipalities. In this paper, we propose a method to predict the level of the air pollution of a location by taking an image by a camera of a smart phone then processing it. We collected an image dataset from city of Tehran. Afterward, we proposed two methods for estimation of level of air pollution. In the first method, the images are preprocessed and then Gabor transform is used to extract features from the images. At the end, two shallow classification methods are employed to model and predict the level of air pollution. In the second proposed method, a Convolutional Neural Network(CNN) is designed to receive a sky image as an input and result a level of air pollution. Some experiments have been done to evaluate the proposed method. The results show that the proposed 9 method has an acceptable accuracy in detection of the air pollution level. Our deep classifier achieved accuracy about 59.38% which is 10 about 6% higher than traditional combination of feature extraction and classification methods. 相似文献
904.
Earth System Science (ESS) observational data are often inadequately semantically enriched by geo-observational information systems to capture the true meaning of the associated data sets. Data models underpinning these information systems are often too rigid in their data representation to allow for the ever-changing and evolving nature of ESS domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in a computable way. Object oriented techniques that are typically employed to model data in a complex domain (with evolving domain concepts) can unnecessarily exclude domain specialists from the design process, invariably leading to a mismatch between the needs of the domain specialists, and how the concepts are modelled. In many cases, an over simplification of the domain concept is captured by the computer scientist. This paper proposes that two-level modelling methodologies developed by health informaticians to tackle problems of domain specific use-case knowledge modelling can be re-used within ESS informatics. A translational approach to enable a two-level modelling process within geo-observational sensor systems design is described. We show how the Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard can act as a pragmatic solution for a stable reference-model (necessary for two-level modelling), and upon which more volatile domain specific concepts can be defined and managed using archetypes. A rudimentary use-case is presented, followed by a worked example showing the implementation methodology and considerations leading to an O&M based, two-level modelling design approach, to realise semantically rich and interoperable Earth System Science based geo-observational sensor systems. 相似文献
905.
Qiuping Huang Jiejun Huang Yunjun Zhan Wei Cui Yanbin Yuan 《Earth Science Informatics》2018,11(4):567-578
Quantifying land use patterns and functions is critical for modeling urban ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Methods of determining the optimum scale of land use patterns are commonly considered using landscape metrics. Landscape metrics are quantitative indicators for analyzing landscape heterogeneity at the landscape level. In this study, due to their widespread use in urban landscape analyses and well-documented effectiveness in quantifying landscape patterns, landscape metrics that represent dominance, shape, fragmentation and connectivity were selected. Five metrics include Patch Density, Contagion, Landscape Shape Index, Aggregation Index and Connectivity. Despite a wide application of landscape metrics for land use studies, the majority mainly focuses on the qualitative analysis of the characteristics of landscape metrics. The previous models are limited in exploring the optimum scale of land use patterns for their lack of quantitation. Therefore, taking the City of Wuhan as an example, the land use unit was treated as a patch, and the landscape pattern metrics at different spatial scales were calculated and compared so as to find the optimum one. Furthermore, a mathematical model of landscape metrics was proposed to quantify the scale effect of urban land use patterns, generating a complementary tool to select the optimum scale. In addition, Analytic Hierarchy Process (AHP) was introduced to determine the respective weights of the chosen landscape metrics in this model. Fractal dimension was ultimately applied to verify the chosen optimum scale of our study region. The results indicated that 60 m is confirmed to be the optimum scale for capturing the spatial variability of land use patterns in this study area. 相似文献
906.
Viewshed analysis is widely used in many terrain applications such as siting problem, path planning problem, and etc. But viewshed computation is very time-consuming, in particular for applications with large-scale terrain data. Parallel computing as a mainstream technique with the tremendous potential has been introduced to enhance the computation performance of viewshed analysis. This paper presents a revised parallel viewshed computation approach based on the existing serial XDraw algorithm in a distributed parallel computing environment. A layered data-dependent model for processing data dependency in the XDraw algorithm is built to explore scheduling strategy so that a fine-granularity scheduling strategy on the process-level and thread-level parallel computing model can be accepted to improve the efficiency of the viewshed computation. And a parallel computing algorithm, XDraw-L, is designed and implemented taken into account this scheduling strategy. The experimental results demonstrate a distinct improvement of computation performance of the XDraw-L algorithm in this paper compared with the coarse-partition algorithm, like XDraw-E which is presented by Song et al. (Earth Sci Inf 10(5):511–523, 2016), and XDraw-B that is the basic algorithm of serial XDraw. Our fine-granularity scheduling algorithm can greatly improve the scheduling performance of the grid cells between the layers within a triangle region. 相似文献
907.
Due to the complex natural geological conditions, many slope-related geological hazards occur in the Three Gorges Reservoir area in China. This study focuses on the characteristics of landslide development and their underlying mechanisms in this area. A statistical analysis is conducted to determine the characteristics of landslide development in the Wushan area, including the landslide distribution as a function of the elevation, slope, landslide material composition, scale, lithology, boundary conditions, instability mechanism, stratigraphic age, attitude, and sliding direction. The mechanisms of slope instability and the effect on the occurrence of landslides are analyzed. This study provides important reference material for landslide research in the Three Gorges Reservoir area and similar stratigraphic areas. 相似文献
908.
909.
Coastal aquifers are usually exposed to saltwater intrusion. Therefore, groundwater extracted from these aquifers should be regulated considering their dimensions and effective parameters. In this paper, optimum discharge from a large number of exploitation wells is evaluated according to variations of width, length, and anisotropy coefficient in the Qom aquifer near the salt lake in central Iran. First, the wells are divided into clusters to decrease the number of decision variables. Then, the location and discharge from each cluster is obtained using SEAWAT and charged system search (CSS) simulation–optimization model with the assumption of three-dimensional variable density flow. The maximum discharge considering various anisotropy rates is computed based on different values of lengths and widths of the aquifer. Finally, an M5-tree model is trained using the obtained samples to derive a linear relationship between input and output data. Based on the results, for various ranges of width and length of an aquifer with impermeable boundaries, different linear equations for optimum discharge are obtained. Also, it was found that for an aquifer with a small width, the critical discharge is a function of the length while the effect of the boundaries is negligible. Sensitivity analysis of the anisotropy coefficient reveals that with increasing the anisotropy rate, thickness and slope of the transition zone decrease and as the maximum discharge increases consequently. However, the sensitivity of the discharge to anisotropy rate is not remarkable. A comparison between the results of this study with those of the analytical method based on sharp interface assumption is carried out. For the critical condition, the best agreement between analytical equation (\(\overline {L} =0.87\overline {W} +0.62\)) and proposed method (\(\overline {L} =0.83\overline {W} - 1.41\)) is achieved for the anisotropic aquifer when the 50% isochlor is assumed as the measure of salt water intrusion. 相似文献
910.
M. Rocío Fernández San Juan Carolina B. Albornoz Karen Larsen Roberto Najle 《Environmental Earth Sciences》2018,77(11):404
Contamination with heavy metals in surface and groundwater is a threat to human health and ecosystems. Due to this, the need arises to remediate water polluted through ecological and profitable technologies, such as phytoremediation. The objective of the work was to evaluate the concentration of lead (Pb) and zinc (Zn) in the floating macrophytes Limnobium laevigatum and Ludwigia peploides, after being exposed to contaminated water experimentally. In this way to be able to determine if these plants have mechanisms that allow them to accumulate the metals in the roots and to perform the translocation of these to different vegetative organs, L. laevigatum and L. peploides were placed in solutions contaminated with Pb ([Pb]?=?5 mg/l) and Zn ([Zn]?=?20 mg/l). The concentrations of metals in water, root and leaf samples were evaluated as a function of time (0, 1, 2 and 4 days). The determination of the metals was performed by the atomic absorption spectrophotometry technique. After 4 days of exposure to Pb and Zn, the plants showed high metal removal efficiencies of water, more to 70% in all cases. Pb was accumulated fundamentally by roots, while Zn was accumulated more in the leaves. In addition, the bioconcentration and translocation factors for each metal were calculated. 相似文献