Space-time modeling for the Missouri Turkey Hunting Survey

The Missouri Turkey Hunting Survey (MTHS) is a postseason mail survey conducted by the Missouri Department of Conservation. The 1996 MTHS provides information concerning the number of turkeys harvested by hunters on each day and the total number of trips made to the counties by these hunters on each day of the hunting season. The success rates are then found from this information. Small sample sizes produce large standard errors for the estimates at the county level. We use a Bayesian hierarchical generalized linear model to estimate daily hunting success rates at the county level. The model includes an autoregressive process for the days of the hunting season and spatially correlated random geographic effects. The computations are performed using Gibbs sampling and adaptive rejection sampling techniques. Results show that there are significant spatial corelations between counties and correlations between days of the hunting season. The estimates are close to the frequency estimates at the state level and much more stable at the county level.     

Modeling Prescribed Surface-Fire Regimes for Pinus strobus Conservation

Abstract:  We developed a simple model of   Pinus strobus L. stand dynamics to compare the impacts of different temporal arrangements of surface fires designed to reflect the application of fire as both an essential ecosystem process (natural fire) and as an efficient means of producing specific habitat features or other values (optimal fire). We used a stochastic simulation model of fire processes to estimate the mean fire-return interval that would maximize stand structural diversity. We investigated trade-offs between structural diversity and temporal population stability associated with changes in the fire interval and used a deterministic version of the model to explore the effects of scheduling fires at fixed intervals. In stochastic simulations, maximum structural diversity occurred at intermediate levels of disturbance (40-year mean fire interval). When fires were scheduled at fixed intervals, a longer, 100-year return interval maximized diversity. Mean fire-return interval was a mitigating factor in the diversity-stability relationship, which changed from positive to negative as the fire interval was reduced progressively from 250 to 5 years. As an alternative to scheduling fires at specified mean intervals, we developed a goal-programming model (a form of linear programming model) and used it to identify an optimal fire schedule for achieving habitat and visual-quality objectives. In comparison with the 40-year stochastic mean fire interval, which maximized structural diversity, the optimal schedule produced comparable levels of both diversity and fire frequency. Our results show how simulation and goal-programming models can be used to evaluate prescribed fire-scheduling alternatives and to explore the comparative advantages of natural and optimal fire-management approaches.     

Wind Tunnel Experiments and Numerical Simulation of Snow Drifting around an Avalanche Protecting Dam

To learn about wind flow and snow drifting around avalanche dams, experiments were done in the Jules Verne Climatic Wind Tunnel. The paper reports the results from numerical wind flow simulations that were done to support the findings from the wind tunnel. Satisfying the model similitude criteria for the wind tunnel configuration was difficult due to the inevitable small geometric scale of the model, while on the contrary the snow drifting conditions in the facilities were full scale. By comparing numerical wind flow results of full scale and model scale dams with the snow pattern observed in the wind tunnel, it was possible to conclude that albeit poor model similitude, the snowdrifts on the windward side of the wind tunnel model are likely to indicate the full scale natural situation.     

蔬菜地土壤磷提取及模拟径流中磷素潜在流失的影响

蔬菜地磷素流失是一种典型农业非点源污染类型。通过观测地表径流中溶解态反应磷(DRP)、生物可利用磷(BAP)可以监测土壤磷素流失程度。受到各种客观条件的限制,这两个指标比较难于获取,而土壤中的总磷(TP)、Olsen(OP)、Mehlich-1(M-1P)和水溶性磷(Pw)可以通过常规分析手段获取。本文选取27个典型蔬菜样地,分析测定各样地土壤中的总磷(TP)、Olsen(OP)、Mehlich-1(M-1P)和水溶性磷(Pw)四个磷提取变量,采用了经典方法计算土壤磷流失潜能指标——磷吸持饱和度(DPS)。同时采用模拟径流实验得出典型蔬菜样地地表径流样中溶解态反应磷(DRP)、生物可利用磷(BAP)。结果表明:M-1P、Pw与DPS呈极显著正相关,相关系数分别达到了0.85和0.74(p<0.01);而M-1P、Pw与DRP浓度相关系数(r2=0.843和0.786,p<0.01)大于TP、OP与DRP浓度的相关系数(r2=0.554和0.722,p<0.01)。结论认为,通过测定M-1P、Pw和计算DPS能比较准确、便捷地预测土壤径流磷素流失风险程度。     

Simulation of Ekman Boundary Layers by Large Eddy Model with Dynamic Mixed Subfilter Closure

Theoretical analysis of boundary layer turbulence has suggested a feasibility of sufficiently accurate turbulence resolving simulations at relatively coarse meshes. However, large eddy simulation (LES) codes, which employ traditional eddy-viscosity turbulence closures, fail to provide adequate turbulence statistics at coarse meshes especially within a surface layer. Manual tuning of parameters in these turbulence closures may correct low order turbulence statistics but severely harms spectra of turbulence kinetic energy (TKE). For more than decade, engineering LES codes successfully employ dynamic turbulence closures. A dynamic Smagorinsky turbulence closure (DSM) has been already tried in environmental LES. The DSM is able to provide adequate turbulence statistics at coarse meshes but it is not completely consistent with the LES equations. This paper investigates applicability of an advanced dynamic mixed turbulence closure (DMM) to simulations of Ekman boundary layers of high Reynolds number flows. The DMM differs from the DSM by explicit calculation of the Leonard term in the turbulence stress tensor. The Horizontal Array Turbulence Study (HATS) field program has revealed that the Leonard term is indeed an important component of the real turbulence stress tensor. This paper presents validation of a new LES code LESNIC. The study shows that the LES code with the DMM provides rather accurate low order turbulence statistics and the TKE spectra at very coarse meshes. These coarse LES maintain more energetic small scale fluctuations of velocity especially within the surface layer. This is critically important for success of simulations. Accurate representation of higher order turbulence statistics, however, requires essentially better LES resolution. The study also shows that LES of the Ekman boundary layer cannot be directly compared with conventionally neutral atmospheric boundary layers. The depth of the boundary layer is an important scaling parameter for turbulence statistics.     

Efficiency of composite sampling for estimating a lognormal distribution

In many environmental studies measuring the amount of a contaminant in a sampling unit is expensive. In such cases, composite sampling is often used to reduce data collection cost. However, composite sampling is known to be beneficial for estimating the mean of a population, but not necessarily for estimating the variance or other parameters. As some applications, for example, Monte Carlo risk assessment, require an estimate of the entire distribution, and as the lognormal model is commonly used in environmental risk assessment, in this paper we investigate efficiency of composite sampling for estimating a lognormal distribution. In particular, we examine the magnitude of savings in the number of measurements over simple random sampling, and the nature of its dependence on composite size and the parameters of the distribution utilizing simulation and asymptotic calculations.     

Renormalized numerical simulation of flow over planar and non-planar fractal trees

We review the fundamentals of a new numerical modeling technique called Renormalized Numerical Simulation (RNS). The goal of RNS is to model the drag force produced by high Reynolds-number turbulent flow over objects that display scale-invariant properties, objects such as tree-like fractals. The hallmark of RNS in this application is that the drag of the unresolved tree branches is modeled using drag coefficients measured from the resolved branches and unresolved branches (as modeled in previous iterations of the procedure). In the present paper, RNS is used to study the effects of branch orientation on the drag force generated by highly idealized trees in which trunk and branches have square cross-section, and the branches all lie in a plane perpendicular to the incoming flow. Then, the procedure is generalized to the more general case of non-planar branch arrangements. Results illustrate that RNS may enable numerical modeling of environmental flow processes associated with fractal geometries using affordable computational resolution.     

Bayesian areal wombling via adjacency modeling

Recently, public health professionals and other geostatistical researchers have shown increasing interest in boundary analysis, the detection or testing of zones or boundaries that reveal sharp changes in the values of spatially oriented variables. For areal data (i.e., data which consist only of sums or averages over geopolitical regions), Lu and Carlin (Geogr Anal 37: 265–285, 2005) suggested a fully model-based framework for areal wombling using Bayesian hierarchical models with posterior summaries computed using Markov chain Monte Carlo (MCMC) methods, and showed the approach to have advantages over existing non-stochastic alternatives. In this paper, we develop Bayesian areal boundary analysis methods that estimate the spatial neighborhood structure using the value of the process in each region and other variables that indicate how similar two regions are. Boundaries may then be determined by the posterior distribution of either this estimated neighborhood structure or the regional mean response differences themselves. Our methods do require several assumptions (including an appropriate prior distribution, a normal spatial random effect distribution, and a Bernoulli distribution for a set of spatial weights), but also deliver more in terms of full posterior inference for the boundary segments (e.g., direct probability statements regarding the probability that a particular border segment is part of the boundary). We illustrate three different remedies for the computing difficulties encountered in implementing our method. We use simulation to compare among existing purely algorithmic approaches, the Lu and Carlin (2005) method, and our new adjacency modeling methods. We also illustrate more practical modeling issues (e.g., covariate selection) in the context of a breast cancer late detection data set collected at the county level in the state of Minnesota.     

Comparison of Spatial Methods for the Assessment of Planktonic Patches

Planktonic patches are defined as areas where the abundance of plankters is above a threshold value τ. The estimation of patch size and shape can be approached using spatial statistical tools, using truncated random fields or indicator random fields as classifiers. In all cases there is the risk of false positive and false negative errors. In this paper we present the results of a comparative study on the performance of four commonly used methods: conditional simulation and kriging, both in the original measurement units of the data and under an indicator transform. We used a misclassification cost function to compare the four methods. Our results show that conditional simulation in the original measurement units attains the lowest misclassification cost. We also illustrate how the point at which this minimum is attained can be used to chose an optimal cut-off value for binary classification. Received: December 2003 / Revised: June 2005     

Subgrid-Scale Modeling of Reacting Scalar Fluxes in Large-Eddy Simulations of Atmospheric Boundary Layers

In large-eddy simulations of atmospheric boundary layer turbulence, the lumped coefficient in the eddy-diffusion subgrid-scale (SGS) model is known to depend on scale for the case of inert scalars. This scale dependence is predominant near the surface. In this paper, a scale-dependent dynamic SGS model for the turbulent transport of reacting scalars is implemented in large-eddy simulations of a neutral boundary layer. Since the model coefficient is computed dynamically from the dynamics of the resolved scales, the simulations are free from any parameter tuning. A set of chemical cases representative of various turbulent reacting flow regimes is examined. The reactants are involved in a first-order reaction and are injected in the atmospheric boundary layer with a constant and uniform surface flux. Emphasis is placed on studying the combined effects of resolution and chemical regime on the performance of the SGS model. Simulations with the scale-dependent dynamic model yield the expected trends of the coefficients as function of resolution, position in the flow and chemical regime, leading to resolution-independent turbulent reactant fluxes.