Influence Of Spatial Variability Research Articles

The relative contribution of environmental and spatial factors on the composition of assemblages of Chironomidae (Insecta, Diptera) in Atlantic Forest springs

ABSTRACT Environmental and spatial factors can affect the distribution of aquatic insect metacommunities. In tropical springs, few studies have been conducted on the subject, especially regarding the influence of spatial variables. Our main objective was to assess the influence of environmental and spatial factors on the composition of Chironomidae assemblages in 48 pristine springs in different watersheds in Minas Gerais state, Brazil. This is the first study of the composition of Chironomids assemblages in springs in the Neotropical region. A single time in the dry season, three samples of the substrate at each spring were collected with a hand net. To assess the importance of environmental and/or spatial predictors of the composition of the Chironomidae metacommunities Partial redundancy analysis was performed. The results show that environmental variables explained little of the composition of Chironomids assemblages in Atlantic Forest springs. The local environmental factors selected by the model were dissolved oxygen, conductivity and plant cover, and the spatial factors selected were PCNM 1 and PCNM 6. Most of the variation in the Chironomidae assemblage remained unexplained by the partial redundancy models. Our results suggest the influence of temporal and spatial variables on the structure of metacommunities of Chironomidae in tropical springs.

An Integrated Spatial Autoregressive Model for Analyzing and Simulating Urban Spatial Growth in a Garden City, China.

In the past, the research on models related to urban land-use change and prediction was greatly complicated by the high precision of models. When planning some garden cities, we should explore a more applicable, specific, and effective macro approach than the community-level one. In this study, a model consisting of spatial autoregressive (SAR), cellular automata (CA), and Markov chains is constructed. One It can well-consider the spatial autocorrelation and integrate the advantages of CA into a geographical simulation to find the driving forces behind the expansion of a garden city. This framework has been applied to the urban planning and development of Chengdu, China. The research results show that the application of the SAR model shows the development trend in the southeast region and the needs to optimize the central region and protect the western region as an ecological reserve. The descriptive statistics and the spatial autocorrelation of the residuals are reliable. The influence of spatial variables from strong to weak is distance to water, slope, population density, GDP, distance to main roads, distance to railways, and distance to the center of the county (district). Taking 2005 as the initial year, the land-use situation in 2015 was simulated and compared with the actual land-use situation. It seems that the Kappa coefficient of the construction-land simulation is 0.7634, with high accuracy. Therefore, the land use in 2025 and 2035 is further simulated, which provides a reference for garden cities to formulate a reasonable urban space development strategy.

Hydrochemistry characteristics of groundwater with the influence of spatial variability and water flow in Hetao Irrigation District, China.

Groundwater is an important resource of water in arid and semi-arid agricultural regions. Thus, identification of hydrogeochemical characters and the influence of geospatial variability and flow pooling are of significance on groundwater resources management and making irrigation decisions in salinized areas. The study specifically focused on the Hetao Irrigation District located in the semi-arid region of northern China. A total of 85 groundwater samples (42 from the upstream Shenwu Irrigation Area (SWIA), 43 from the downstream Wulate Irrigation Area (WLTIA)) were collected, and 15 water quality indexes were analyzed. Methods including mathematical statistics, Piper diagram, Gibbs model, forward succession model, and ionic rations were used to analyze the hydrochemical characteristics and evolution mechanisms, RSBC, PS, SAR, WQI were selected to evaluate water quality and irrigation suitability from the perspective of salt and alkali damage. Results showed that the groundwater of the study area is weakly alkaline, SWIA is mainly fresh water (47.62%), WLTIA is mainly brackish water (65.12%), and the hydrochemistry of the groundwater consists of Cl-Na type and Cl·SO-Ca·Mg. The solute content of downstream (WLTIA) is higher than that of upstream (SWIA), Na+ and Cl- have obvious advantages in WLTIA, and they are the main contribution indicators of groundwater TDS in the study area. The groundwater is subjected to the ongoing influence of rock weathering, ions exchange, and evaporate crystallization Na+ mainly originates from the dissolution of evaporate salt rock and silicate rock, and Ca2+ from the dissolution of gypsum and carbonate. The order of contribution of different rocks is evaporation rock > silicate rock > carbonate rock. Based on the classifications of sodium absorption ratio (SAR), residual sodium bicarbonate (RSBC), and potential salinity (PS), most of the groundwater samples are unsuitable for irrigating, and the groundwater quality of the SWIA is better than that of the WLTIA.

Influence of spatial variability of soil elastic modulus on elastic settlement of rectangular footing under fuzzy uncertainty

Influence of spatial variability of soil elastic modulus on elastic settlement of rectangular footing under fuzzy uncertainty

Influence of Spatial Variability on the Uniaxial Compressive Responses of Rock Pillar Based on 3D Random Field

AbstractKnowledge of the uniaxial compressive responses of rock mass is crucial for evaluating the stability of rock pillar in underground engineering. The inherent spatial variabilities of rock ma...

Bed‐Load Transport in Vegetated Flows: Phenomena, Parametrization, and Prediction

AbstractThis study presents an experimental study on bed‐load transport in the presence of emergent vegetation, which is simulated using uniformly sized circular cylinders arranged in a homogeneous distribution. The spatial variability of bed‐load fluxes in vegetated flows is first examined. Then a model is proposed for evaluating the bed‐load transport rate based on the scour holes that form around the vegetation stems. The influences of spatial variability and intensified turbulence on sediment transport are finally considered by relating the dimensionless transport rate and flow intensity to the stem size and vegetation density. The derived formula for predicting the bed‐load transport rate in vegetated flows is applicable for weak to moderate transport conditions.

Influence of Spatial Variability of Concrete in Large Shear- Critical Structures

Influence of Spatial Variability of Concrete in Large Shear- Critical Structures

Diversity Patterns Associated with Varying Dispersal Capabilities as a Function of Spatial and Local Environmental Variables in Small Wetlands in Forested Ecosystems

The diversity of species on a landscape is a function of the relative contribution of diversity at local sites and species turnover between sites. Diversity partitioning refers to the relative contributions of alpha (local) and beta (species turnover) diversity to gamma (regional/landscape) diversity and can be influenced by the relationship between dispersal capability as well as spatial and local environmental variables. Ecological theory predicts that variation in the distribution of organisms that are strong dispersers will be less influenced by spatial properties such as topography and connectivity of a region and more associated with the local environment. In contrast, the distribution of organisms with limited dispersal capabilities is often dictated by their limited dispersal capabilities. Small and ephemeral wetlands are centers of biodiversity in forested ecosystems. We sampled 41 small and ephemeral wetlands in forested ecosystems six times over a two-year period to determine if three different taxonomic groups differ in patterns of biodiversity on the landscape and/or demonstrate contrasting relationships with local environmental and spatial variables. We focused on aquatic macroinvertebrates (aerial active dispersers consisting predominantly of the class Insecta), amphibians (terrestrial active dispersers), and zooplankton (passive dispersers). We hypothesized that increasing active dispersal capabilities would lead to decreased beta diversity and more influence of local environmental variables on community structure with less influence of spatial variables. Our results revealed that amphibians had very high beta diversity and low alpha diversity when compared to the other two groups. Additionally, aquatic macroinvertebrate community variation was best explained by local environmental variables, whereas amphibian community variation was best explained by spatial variables. Zooplankton did not display any significant relationships to the spatial or local environmental variables that we measured. Our results suggest that amphibians may be particularly vulnerable to losses of wetland habitat in forested ecosystems as they have high beta diversity. Consequently, the loss of individual small wetlands potentially results in local extirpations of amphibian species in forested ecosystems.

Probabilistic undrained bearing capacity of skirted foundations under HM combined loading in spatially variable soils

The behaviour of skirted foundations subjected to combined vertical (V), horizontal (H) and moment (M) loading is of particular interest to the geotechnical engineers. The bearing capacity of skirted foundations under combinations of VHM loading is represented by failure envelopes, which is commonly used in its stability assessment. In current studies, failure envelopes for skirted foundations were established deterministically, ignoring the spatial variability of natural soils. The paper aimed to investigate the probabilistic failure envelope of skirted foundations in the presence of soil undrained shear strength linearly increasing with depth. Random finite element method (RFEM) combining with random field theory, finite element method and Monte Carlo simulation was conducted to evaluate the uniaxial bearing capacities and define the HM failure envelopes. The influence of spatial variability on the stochastic response of bearing capacity in the HM space was discussed.

A large-deformation random finite-element study: failure mechanism and bearing capacity of spudcan in a spatially varying clayey seabed

Although the random heterogeneity of a clayey seabed has been long recognised, it is relatively recently that the influence of spatial variability on the spudcan foundation has been explicitly explored by random finite-element analyses. Owing to technical and computational challenges, these are still limited to the small-strain Lagrangian finite-element calculation with the ‘wished-in-place’ assumption, which is a departure from the reality. Attempts were successfully made in this research to combine the large-deformation finite-element calculation with random field theory in a Monte Carlo simulation framework. The continuous penetration of a spudcan in a clayey seabed was modelled through the coupled Eulerian–Lagrangian finite-element calculation with simultaneous consideration of the strain-softening effect and linearly increasing strength with depth. The results suggest that the randomness of soil strength can obviously alter the flow pattern and failure mechanism of soil, and in turn affects the bearing capacity of the spudcan. The log-normal probability distribution function was found to fit the distribution of the bearing capacity factor well. A correlation between the failure probability and the safety factor was established, from which the level of reliability corresponding to different safety factors can be clearly evaluated. Such a correlation may facilitate the further development of reliability-based design.

Influence of spatial variability on unsaturated hydraulic properties

To investigate the effect of spatial variability on hydraulic properties of unsaturated soils, a numerical model is set up which can simulate seepage process in an unsaturated heterogeneous soil. The unsaturated heterogeneous soil is composed of matrix sand embedded with a small proportion of clay for simulating the heterogeneity. Soil-water characteristic curve and unsaturated hydraulic conductivity curve of the unsaturated soil are expressed by Van Genuchten model. Hydraulic parameters of the matrix sand are considered as random fields. Different autocorrelation lengths (ACLs) of hydraulic parameter of the matrix sand and different proportions of clay are assumed to investigate the influence of spatial variability on the equivalent hydraulic properties of the heterogeneous soil. Four model sizes are used in the numerical experiments to investigate the influence of scale effects and to determine the sizes of representative volume element (RVE) in the numerical simulations. Through a number of Monte Carlo simulations of unsaturated seepage analysis, the means and the coefficients of variations (COVs) of the equivalent hydraulic parameters of the heterogeneous soil are calculated. Simulations show that the ACL and model size has little influence on the means of the equivalent hydraulic parameters, but they have a large influence on the COVs of the equivalent hydraulic parameters. The size of an RVE is mainly affected by the ACL and the proportion of heterogeneity. The influence of spatial variability on the hydraulic parameters of the heterogeneous unsaturated soil can be used as a guidance for geotechnical reliability analysis and design related to unsaturated soils.

Impact of spatial variability of geotechnical properties on uncertain settlement of frozen soil foundation around an oil pipeline

The spatial variability of geotechnical properties can lead to the uncertainty of settlement for frozen soil foundation around the oil pipeline, and it can affect the stability of permafrost foundation. In this paper, the elastic modulus, cohesion, angle of internal friction and poisson ratio are taken as four independent random fields. A stochastic analysis model for the uncertain settlement characteristic of frozen soil foundation around an oil pipeline is presented. The accuracy of the stochastic analysis model is verified by measured data. Considering the different combinations for the coefficient of variation and scale of fluctuation, the influences of spatial variability of geotechnical properties on uncertain settlement are estimated. The results show that the stochastic effects between elastic modulus, cohesion, angle of internal friction and poisson ratio are obviously different. The deformation parameters have a greater influence on stochastic settlement than the strength parameters. The overall variability of settlement reduces with the increase of horizontal scale of fluctuation and vertical scale of fluctuation. These results can improve our understanding of the influences of spatial variability of geotechnical properties on uncertain settlement and provide a theoretical basis for the reliability analysis of pipeline engineering in permafrost regions.

Seismic Amplification of Soil Ground with Spatially Varying Shear Wave Velocity Using 2D Spectral Element Method

ABSTRACT Spatial variability of soils can have a profound effect on seismic site amplification, which cannot be reasonably captured using conventional one-dimensional analyses. In this study, the shear-wave velocity of soils is modelled as a 2D spatially correlated random field. Extensive simulations are conducted to quantify the influence of spatial variability of soils on site amplification using 2D Spectral Element Method. Key influential factors include variation and spatial correlation of shear wave velocity in both horizontal and vertical directions. Numerical simulations show that site amplification at resonance frequencies is subdued, and its variation depends on these influential factors. Spatial correlations of site amplification are also investigated, showing that the correlation range of site amplification is frequency dependent. The correlation range is much longer at low frequencies than that at high frequencies. The analyses imply that length scales of both soil heterogeneity and wavelength should be considered simultaneously when quantifying the spatial variability of ground motion amplification.

Influences of spatial variability in pelagic scattering layers on sperm whales behavior

The central slope of the Gulf of Mexico (GOM) is home to over 20 species of marine mammals. Prior to the Deep Horizon Oil Spill in 2010, sperm whales were the predominately sighted large whale in the area. This study investigated the distribution and utilization of the north-central GOM by sperm whales two years after the spill by comparing sperm whale presence to micronekton distribution. Micronekton, organisms 2–20 cm, might be a key component in understanding sperm whale behavior as they are potentially an essential link in the food web between primary producers and higher trophic levels, including cephalopods—primary prey items of sperm whales. A Simrad EK60 echosounder operating at 38 kHz recorded the backscatter of micronekton throughout the northern GOM. The spatial distribution of micronekton backscatter was highly variable and may be driven by proximity to the Mississippi Delta. Sperm whales were sighted by trained visual observers and foraging was detected using a towed hydrophone array. The sperm whales were sighted most often in shallow slope waters less than 900 meters in areas with higher micronekton backscatter, suggesting that the waters above sloping bottoms with dense patches of mesopelagic micronekton support the prey of sperm whales.

Influence of spatial variability of soil friction angle on sheet pile walls’ structural behaviour

ABSTRACTThe uncertainty in terms of soil characterisation is studied to assess its effect on the structural behaviour of extended structures as sheet pile walls. A finite element model is used. This integrates a numerical model of the soil–structure interaction together with a stochastic model that allows characterising the soil variability. The model serves in propagating the variability and the system parameter uncertainties. Discussion is mainly focused on two points: (1) testing the sensitivity of the structural behaviour of a sheet pile wall to different geotechnical parameters and (2) assessing the influence of spatial variability of soil properties on the structural behaviour by identifying the most sensitive geotechnical parameter and the most significant correlation length values. The findings showed that in assessing the sheet pile wall’s structural behaviour, there are spatial variability parameters that cannot be considered negligible. In this study, soil friction angle is found to be an important parameter.

Influence of spatially random soil on lateral thrust and failure surface in earth retaining walls

ABSTRACTThe present study investigates the influence of spatial variability of soil properties on the lateral thrust and failure surface of a 6 m high frictionless rigid earth retaining wall in active condition. The drained friction angle of the soil is modelled as a log-normal anisotropic random field in two dimensions, using the Cholesky decomposition technique. The effect of horizontal and vertical scale of fluctuation is observed on the lateral thrust. The failure surface in the backfill is found to be more or less similar for different combinations of spatial variability in vertical and horizontal directions. Monte-Carlo simulation technique is used to compute the probability of failure and to obtain the worst-case spatial variability configuration.

Determining soil moisture by assimilating soil temperature measurements using the Ensemble Kalman Filter

This study investigates the potential to estimate the vertical profile of soil moisture by assimilating temperature observations at a limited number of depths into a coupled heat and moisture transport model (Hydrus-1D). The method is developed with a view to assimilating temperature data from distributed temperature sensing (DTS) to estimate soil moisture at high resolution over large areas. The correlation between temperature and soil moisture in the shallow soil (top ∼ 50 cm) ensures that soil moisture can be estimated using just soil temperature observations. Synthetic tests across a range of soil textures show that with data assimilation both modeled temperature and the moisture profile are improved considerably compared to the ensemble open loop model simulations. In addition, employing data assimilation provides a means to quantitatively account for different sources of uncertainty. This is particularly relevant in the context of DTS given the influence of spatial variability in soil texture and its impact on estimation error. The data assimilation approach could also be used to determine, the number of temperature observations required and the depths at which they should be made. Results suggest that temperature observed at two depths is typically sufficient to estimate soil moisture using this approach. The root mean square error (RMSE) in soil moisture was reduced by up to 75% in the top 20 cm. Furthermore, this approach solves many of the challenges identified in the application of an inversion approach to estimate soil moisture from DTS.

Influence of Spatial Variability of Seismic Shock on Steel Hall with Experimentally Determined Elasto-Plastic Parameters of Steel Material

In the paper the influence of spatial variability of a seismic shock on an industrial steel hall was examined. Different models of seismic excitation were introduced. Firstly, a uniform seismic excitation model was applied, assuming identical motion of all supports of the hall. Then, a non-uniform excitation model was implemented. In that model subsequent points of the ground in the direction of wave propagation repeat the same motion with a certain time delay dependent on the wave velocity. Two direction of the wave passage were assumed: longitudinal (along the longer side of the hall) and transverse (along the shorter side of the hall). To guarantee proper nonlinear elasto-plastic behavior of the structure, the material parameters of the steel were determined experimentally. The dynamic analyses revealed that the response of the hall to the seismic shock was reported beyond the elastic range. Plastic effects appeared in some zones of the primary as well as the secondary structural members of the object, regardless of the excitation model. The model of non-uniform seismic excitation with transverse wave passage turned out to have the greatest impact on the dynamic response of the hall; the plastic strains obtained for that model were much greater than those obtained for other models. The transverse non-uniform excitation generated irreversible strains almost 3 times greater than the uniform excitation. The evolution of significant plastic effects was observed mainly for non-uniform excitations in the lower parts (girts and columns) of the hall, which were strongly affected by the different motions of the ground.

Probabilistic modelling of auto-correlation characteristics of heterogeneous slopes

Spatial variability of soil materials has long been recognised as an important factor influencing the reliability of geo-structures. This study stochastically investigates the influence of spatial variability of shear strength on the stability of heterogeneous slopes, focusing on the auto-correlation function, auto-correlation distance and cross-correlation between soil parameters. The finite element method is merged with the random field theory to probabilistically evaluate factor of safety and probability of failure via Monte-Carlo simulations. The simulation procedure is explained in detail with suggestions on improving efficiency of the Monte-Carlo process. A simple procedure to create cross-correlation between random variables, which allows direct comparison of the influence of each strength variable, is discussed. The results show that the auto-correlation distance and cross-correlation can significantly influence slope stability, while the choice of auto-correlation function only has a minor effect. An equation relating the probability of failure with the auto-correlation distance is suggested in light of the analyses performed in this work and other results from the literature.

Factors affecting storm event turbidity in a New York City water supply stream

Stream turbidity levels tend to increase during high stream discharge events, and it is important to quantify the suspended sediment flux during these events that could potentially lead to water quality problems. Here, a case study for estimating suspended sediment loads (as a product of turbidity and stream discharge) in streams that are part of the New York City (NYC) water supply in the Catskill region of New York State is presented. Over the 8 year study period 80% of the suspended sediment load was transported during less than 4% of the time, indicating the importance of estimating storm event suspended sediment loads. The objective of this study was to understand the underlying factors controlling the uncertainty in the discharge vs turbidity relationship at the outlet of the watershed draining into the NYC Ashokan Reservoir. High frequency (15-min) automated monitoring of stream turbidity was combined with stream discharge measurements of a similar frequency to provide an estimate of the true suspended sediment load that could be used for model testing and verification at two time scales; daily and events. Multivariate statistical analyses indicate that average daily stream turbidity during storm events can be influenced by the spatial variability in runoff, antecedent conditions, and season. A predictive relationship of event mean stream turbidity based on stream discharge alone led to a strong predictive relationship (r 2 = 0.81), but also a 10% underestimation of the cumulative measured event mean suspended sediment load. Inclusion of information on the time between events improved the regression equation (r 2 = 0.89), and reduced the cumulative difference between estimated and measured event mean suspended sediment loads to 7% underestimation. ► High frequency (15-min) automated monitoring of stream turbidity ► Factors causing variability in discharge–turbidity relationship ► Influence of spatial variability in runoff, antecedent conditions, and season