Multi-component reactive transport modeling of natural attenuation of an acid groundwater plume at a uranium mill tailings site

Natural attenuation of an acidic plume in the aquifer underneath a uranium mill tailings pond in Wyoming, USA was simulated using the multi-component reactive transport code PHREEQC. A one-dimensional model was constructed for the site and the model included advective-dispersive transport, aqueous speciation of 11 components, and precipitation-dissolution of six minerals. Transport simulation was performed for a reclamation scenario in which the source of acidic seepage will be terminated after 5 years and the plume will then be flushed by uncontaminated upgradient groundwater. Simulations show that successive pH buffer reactions with calcite, Al(OH)3(a), and Fe(OH)3(a) create distinct geochemical zones and most reactions occur at the boundaries of geochemical zones. The complex interplay of physical transport processes and chemical reactions produce multiple concentration waves. For SO4(2-) transport, the concentration waves are related to advection-dispersion, and gypsum precipitation and dissolution. Wave speeds from numerical simulations compare well to an analytical solution for wave propagation.     

不同楼梯布局条件下行人疏散效果仿真研究

为研究不同楼梯类型的行人疏散效果，改进传统社会力模型，模拟4种常见梯形中行人的疏散过程，并通过总疏散时间和平均疏散速度指标以及微观速度密度分布图分析其疏散效果中存在的内在物理机制。研究表明:从安全和高效疏散角度上看，在限定空间中，单跑无平台梯形布局有利于低密度人群下人员的快速疏散；在中、高密度人群中，双分梯形的分流特点更有利于人员安全、快速疏散。从微观密度、速度分布图可看到这4种梯形在人员疏散过程中均易造成人员聚集拥堵，但发生事故风险的位置不同。单跑有、无平台梯形在楼梯上端和下端均易发生拥堵，且此时速度值大，发生事故的风险高；双分与双跑梯形在楼梯与平台的转角处易发生拥堵。     

城市化与环境污染：中国省际面板数据的实证研究

对环境库兹涅茨曲线（EKC）假说进行了扩展，选取1998～2005年中国30个省（市、自治区）的面板数据，构建了6类环境污染指标同城市化水平及控制变量间的计量模型，并运用Eviews软件进行了实证检验。研究结果表明：4类污染物同城市化水平之间存在倒U形曲线关系，另外2类污染物同城市化水平之间存在正U形曲线关系，目前中国大体上已经进入U形曲线的右半段，但由于地区发展差距的存在，各地进入曲线右半段的时间不同；控制变量的加入不仅改变了转折点出现的时间，而且改变了某些污染指标同城市化水平之间的U形曲线关系；贸易开放并不一定造成环境的恶化，“污染天堂”假说在中国不成立；产业结构变动是造成环境污染的重要因素；技术进步引致的单位GDP能耗下降能减轻环境污染压力；快速的经济增长将导致更加严重的环境污染。     

Modeling of the Mendoza river watershed as a tool to study climate change impacts on water availability

Unmitigated anthropogenic climate change is set to exacerbate current stresses on water resources management and creates the need to develop strategies to face climate change impacts on water resources, especially in the long term. Insufficient information on possible impacts on water availability limits the organization and promotion of efforts to adapt and improve the resilience and efficiency of water systems. To document the potential impacts of climate change in the region of Mendoza, Argentina, we perform a hydrological modeling of the Mendoza River watershed using a SWAT model and project climate change scenarios to observe hydrological changes. The results show the impact of higher temperature on glaciers as river flow increases due to glacier melting; at the same time, runoff decreases as precipitation is reduced. Furthermore, the runoff timing is shifted and an earlier melting becomes more important in more pronounced climate change scenarios. Scenarios show a reduction in water availability that ranges between 1 and 10%. An additional scenario under stronger climate change conditions without glaciers data shows a reduction of the river flow by up to 11.8%. This scenario would correspond to a future situation in which glaciers have completely melted. These situations would imply a reduction in the water availability and the possibility of future unsatisfied water uses, in particular for irrigation, which received most of the available water in Mendoza, on which agricultural activities and regional economy depends.     

WATERSHED SCALE MODELING OF CRITICAL SOURCE AREAS OF RUNOFF GENERATION AND PHOSPHORUS TRANSPORT1

ABSTRACT: A curve number based model, Soil and Water Assessment Tool (SWAT), and a physically based model, Soil Moisture Distribution and Routing (SMDR), were applied in a headwater watershed in Pennsylvania to identify runoff generation areas, as runoff areas have been shown to be critical for phosphorus management. SWAT performed better than SMDR in simulating daily streamflows over the four‐year simulation period (Nash‐Sutcliffe coefficient: SWAT, 0.62; SMDR, 0.33). Both models varied streamflow simulations seasonally as precipitation and watershed conditions varied. However, levels of agreement between simulated and observed flows were not consistent over seasons. SMDR, a variable source area based model, needs further improvement in model formulations to simulate large peak flows as observed. SWAT simulations matched the majority of observed peak flow events. SMDR overpredicted annual flow volumes, while SWAT underpredicted the same. Neither model routes runoff over the landscape to water bodies, which is critical to surface transport of phosphorus. SMDR representation of the watershed as grids may allow targeted management of phosphorus sources. SWAT representation of fields as hydrologic response units (HRUs) does not allow such targeted management.     

Foliar washoff of pesticides (FWOP) model: Development and evaluation

Abstract

The Foliar Washoff of Pesticides (FWOP) Model was developed to provide an empirical simulation of pesticide washoff from plant leaf surfaces as influenced by rainfall amount. To evaluate the technique, simulations by the FWOP Model were compared to those by the foliar washoff algorithm of the Chemical, Runoff and Erosion from Agricultural Management Systems (CREAMS) Model. The two algorithms were linked individually to the Pesticide Runoff Simulator (PRS) for the comparison. Five years of test data from a Mississippi watershed were used to evaluate six insecticides (carbaryl, profenofos, methyl parathion, permethrin, phorate, and toxaphene).

Initially, the FWOP model was used to evaluate the relative impact of chemical distribution (foliage versus soil) on the subsequent foliar washoff and soil surface contributions to runoff losses. Results indicated that runoff losses were low If all of the insecticide was applied to the foliage whereas high losses occurred if applied only to the soil. When an assumed application was distributed between the plant and soil (i.e., 90% to foliage and 10% to soil), predicted runoff losses compared well with observed field data (<3% of the application rate).

Except for toxaphene, the FWOP model generally predicted less washoff and subsequent runoff losses than the CREAMS approach. Simulated toxaphene washoff losses were in good agreement with observed field data. Statistical comparisons of the two modeling approaches using the Kolmogorov‐Smirnov test showed differences in the two cumulative frequency distributions for washoff but smaller differences for runoff. Average 5‐year runoff losses, however, were greater using the CREAMS approach—by factors of 2, 3, and 3 for profenofos, methyl parathion and phorate, respectively.

Results from this study will be useful for upgrading current exposure assessment models to more accurately address foliar washoff losses of pesticides as well as for assessing the impact of foliar‐applied chemicals on environmental quality.     

Representing general theoretical concepts in structural equation models: the role of composite variables

Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically-based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling heterogeneous concepts of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially-reduced-form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influence of suites of variables are often of interest.     

The Sensitivity of Population Viability Analysis to Uncertainty about Habitat Requirements: Implications for the Management of the Endangered Southern Brown Bandicoot

Abstract:  Whenever population viability analysis (PVA) models are built to help guide decisions about the management of rare and threatened species, an important component of model building is the specification of a habitat model describing how a species is related to landscape or bioclimatic variables. Model-selection uncertainty may arise because there is often a great deal of ambiguity about which habitat model structure best approximates the true underlying biological processes. The standard approach to incorporate habitat models into PVA is to assume the best habitat model is correct, ignoring habitat-model uncertainty and alternative model structures that may lead to quantitatively different conclusions and management recommendations. Here we provide the first detailed examination of the influence of habitat-model uncertainty on the ranking of management scenarios from a PVA model. We evaluated and ranked 6 management scenarios for the endangered southern brown bandicoot ( Isoodon obesulus ) with PVA models, each derived from plausible competing habitat models developed with logistic regression. The ranking of management scenarios was sensitive to the choice of the habitat model used in PVA predictions. Our results demonstrate the need to incorporate methods into PVA that better account for model uncertainty and highlight the sensitivity of PVA to decisions made during model building. We recommend that researchers search for and consider a range of habitat models when undertaking model-based decision making and suggest that routine sensitivity analyses should be expanded to include an analysis of the impact of habitat-model uncertainty and assumptions.     

National short-term dietary exposure assessment of a selected group of pesticides in Argentina

ABSTRACT

An evaluation of acute dietary exposure to pesticide residues, applying deterministic and stochastic methods, was performed for a selected group of pesticides in two representative age groups from Argentina. Thus, 28 active ingredients (a.i.) and 75 food items were evaluated for the group of 2–5-year-old children, while 9 a.i. and 59 food items were considered for the 10–49-year-old women group. A deterministic assessment was conducting following the Food and Agriculture Organization (FAO) and World Health Organization (WHO) procedure but using the national maximum residue limits (MRLs) as pesticide residue concentration data, while in the stochastic approach, a theoretical distribution modeled with the available information was used. Food consumption data were obtained from the 2004–2005 comprehensive national nutrition and health survey. The risk was estimated by comparing the short-term dietary exposure with the acute reference dose (ARfD) values for each pesticide-food combination evaluated. In the deterministic assessment, 173 (39.1%) and 40 (31.3%) combinations exceeded the ARfD thresholds for the 2–5-year-old children and 10–49-year-old women groups, respectively. This conservative study generated relevant information as a first stage of acute dietary risk assessment in Argentina.     

Disciplined Planning,Structured Participation,and Collaborative Modeling — Applying Shared Vision Planning to Water Resources

Participatory planning applied to water resources has sparked significant interest and debate during the last decade. Recognition that models play a significant role in the formulation and implementation of design and management strategies has encouraged the profession to consider how such models can be best implemented. Shared Vision Planning (SVP) is a disciplined planning approach that combines traditional water resources planning methodologies with innovations such as structured public participation and the use of collaborative modeling, resulting in a more complete understanding and an integrative decision support tool. This study reviews these three basic components of SVP and explains how they are incorporated into a unified planning approach. The successful application of SVP is explored in three studies involving planning challenges: the National Drought Study, the Lake Ontario‐St. Lawrence River Study, and the Apalachicola‐Chattahoochee‐Flint/Alabama‐Coosa‐Tallapoosa River Basin Study. The article concludes by summarizing the advantages and limitations of this planning approach.