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Spatial Variability

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Gautam Bhattacharya - One of the best experts on this subject based on the ideXlab platform.

  • Reliability Analysis of Earth Slopes Considering Spatial Variability
    Geotechnical and Geological Engineering, 2015
    Co-Authors: Subhadeep Metya, Gautam Bhattacharya
    Abstract:

    The paper presents a computational procedure for reliability analysis of earth slopes considering Spatial Variability of soils under the framework of the Limit Equilibrium Method. In the reliability analysis of earth slopes, the effect of Spatial Variability of soil properties is generally included indirectly by assuming that the probabilistic critical slip surface is the same as that determined without considering Spatial Variability. In contrast to this indirect approach, in the direct approach, the effect of Spatial Variability is included in the process of determination of the probabilistic critical surface itself. While the indirect approach requires much less computational effort, the direct approach is definitely more rigorous. In this context this paper attempts to investigate, with the help of numerical examples, how far away are the results obtained from the indirect approach from that obtained from the direct approach. In both the approaches, it is required to use a model of discretization of random fields into finite random variables. A few such models are available in the literature for one-dimensional (1D) as well as two-dimensional (2D) Spatial Variability. The developed computational scheme is based on the First Order Reliability Method (FORM) coupled with the Spencer Method of Slices valid for limit equilibrium analysis of general slip surfaces. The study includes bringing out the computational advantages and disadvantages of the three commonly used discretization models. The sensitivity of the reliability index to the magnitudes of the scales of fluctuation has also been studied.

Qiu Yang - One of the best experts on this subject based on the ideXlab platform.

  • Review on Spatial Variability and Scale Effects of Land Quality
    Progress in geography, 2005
    Co-Authors: Qiu Yang
    Abstract:

    Land quality indicating the effects of natural factors and human activities on land resource plays an important role in environment improvement and sustainable land use. Population increasing and economic development have brought greater pressures on land resource since 1980's, which resulted in different land degradation. More and more governments, international organizations and scientists have paid attention to the improvement and management of land quality, and it is important to deeply understand the Spatial Variability of land quality in different scales. In this paper, the concept and characteristics of land quality and scale, methdology of Spatial Variability are first intruduced, then Spatial Variability and scale effects of land quality is streesed. At the same time, the development trends of land quality Spatial Variability and its relative researches are discussed, aiming to provide insights into further study of land quality and sustainable land use in China. Future study concerned includes: close relationship between land quality indexes and practical applications; more research on related mechanism and effects; and more focus on land use patterns and ecological processes.

Subhadeep Metya - One of the best experts on this subject based on the ideXlab platform.

  • Reliability Analysis of Earth Slopes Considering Spatial Variability
    Geotechnical and Geological Engineering, 2015
    Co-Authors: Subhadeep Metya, Gautam Bhattacharya
    Abstract:

    The paper presents a computational procedure for reliability analysis of earth slopes considering Spatial Variability of soils under the framework of the Limit Equilibrium Method. In the reliability analysis of earth slopes, the effect of Spatial Variability of soil properties is generally included indirectly by assuming that the probabilistic critical slip surface is the same as that determined without considering Spatial Variability. In contrast to this indirect approach, in the direct approach, the effect of Spatial Variability is included in the process of determination of the probabilistic critical surface itself. While the indirect approach requires much less computational effort, the direct approach is definitely more rigorous. In this context this paper attempts to investigate, with the help of numerical examples, how far away are the results obtained from the indirect approach from that obtained from the direct approach. In both the approaches, it is required to use a model of discretization of random fields into finite random variables. A few such models are available in the literature for one-dimensional (1D) as well as two-dimensional (2D) Spatial Variability. The developed computational scheme is based on the First Order Reliability Method (FORM) coupled with the Spencer Method of Slices valid for limit equilibrium analysis of general slip surfaces. The study includes bringing out the computational advantages and disadvantages of the three commonly used discretization models. The sensitivity of the reliability index to the magnitudes of the scales of fluctuation has also been studied.

Martin De Luis - One of the best experts on this subject based on the ideXlab platform.

  • Spatial Variability of precipitation in Spain
    Regional Environmental Change, 2013
    Co-Authors: Nicola Cortesi, José Carlos González-hidalgo, Michele Brunetti, Martin De Luis
    Abstract:

    The Spatial Variability of annual and seasonal precipitation in the conterminous land of Spain has been evaluated by using correlation decay distance analysis (CDD). The CDD analysis essentially explores how the correlation between neighbouring stations varies according to distance. We analysed CDD independently for the decades 1956–1965, 1966–1975, 1976–1985, 1986–1995, and 1996–2005 using only those stations with no missing values for each decade. To this end, 972, 1,174, 1,242, 773 and 695 complete series were used for each decade, respectively. In particular, for each station and decade, we calculated the threshold distance at which the common variance between target (i) and neighbour series is higher than 50 % (r 2  = 0.5) to evaluate whether current density of the climate data set captures the Spatial Variability of precipitation within the study area. Results indicate that, at an annual scale, neighbouring stations with 50 % of common variance are restricted on average to about 105 km, but this distance can vary from 28 to 251 km within the study area. The lowest Variability is located to the SW and in winter, while the higher Spatial Variability is found to the north, in the Cantabrian area, and to the east, in the Mediterranean and Pyrenees, during summer. Our results suggest that current density of climate stations (those operating in 2005) is good enough to study precipitation Variability at an annual scale for winter, spring and autumn, but not enough for summer.

Liu Changming - One of the best experts on this subject based on the ideXlab platform.

  • Model Output Uncertainty Due to Spatial Variability of Rainfall
    Progress in geography, 2003
    Co-Authors: Liu Changming
    Abstract:

    Traditionally in the application of hydrologic/water quality (H/WQ) models, rainfall is assumed to be Spatially homogeneous and is considered not to contribute to output uncertainty. The objective of this study was to assess the uncertainty induced by model outputs-runoff and sediment yield- solely due to rainfall Spatial Variability. The study was conducted using the SWAT model and the rainfall captured by a network of 24 rain gauges in Lushi Basin. For each rainfall event, the model was run using the rainfall captured by each rain gauge, one at a time, under the assumption of rainfall Spatial homogeneity in the study area, A large uncertainty in the modeled outputs was resulted from the rainfall Spatial Variability. The uncertainty in the modeled outputs exceeded the input rainfall uncertainty. The uncertainty of simulated sediment yield outranges that of the runoff. The uncertainty of the simulated runoff increases with the Spatial Variability of rainfall. The more homogeneous of the rainfall, the more certainty of the modeled runoff. The uncertainty of the modeled sediment yield increased with the increase of Spatial Variability of rainfall, and the uncertainty of the modeled sediment yield is inversely related with the simulated sediment yield. Results of this study indicate that Spatial Variability of rainfall should be captured and used in H/WQ models in order to accurately assess the model outputs.In the application of H/WQ models, the assumption of the Spatial homogeneity of the rainfall may not be valid. Spatial Variability of rainfall introduces uncertainty into model outputs when uniformity of rainfall is assumed. Spatial Variability of rainfall should be captured and used in H/WQ models in order to accurately assess the release and transport of pollutants. Since rainfall is a driving force behind many kinds of pollutant release and subsequent transport mechanisms, ignoring this property of rainfall in the application of H/WQ models will put a limit on the accuracy of the model results.