Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States1

Moore, Richard B., Craig M. Johnston, Richard A. Smith, and Bryan Milstead, 2011. Source and Delivery of Nutrients to Receiving Waters in the Northeastern and Mid‐Atlantic Regions of the United States. Journal of the American Water Resources Association (JAWRA) 47(5):965‐990. DOI: 10.1111/j.1752‐1688.2011.00582.x Abstract: This study investigates nutrient sources and transport to receiving waters, in order to provide spatially detailed information to aid water‐resources managers concerned with eutrophication and nutrient management strategies. SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid‐Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries. Point sources account for 28% while atmospheric deposition accounts for 20%. A second SPARROW model was used to examine the sources and delivery of phosphorus to lakes and reservoirs throughout the NE US. The greatest attenuation of phosphorus occurred in lakes that were large relative to the size of their watershed. Model results show that, within the NE US, aquatic decay of nutrients is quite limited on an annual basis and that we especially cannot rely on natural attenuation to remove nutrients within the larger rivers nor within lakes with large watersheds relative to the size of the lake.     

Estimating influence of stocking regimes on livestock grazing distributions

Livestock often concentrate grazing in particular regions of landscapes while partly or wholly avoiding other regions. Dispersing livestock from the heavily grazed regions is a central challenge in grazing land management. Position data gathered from GPS-collared livestock hold potential for increasing knowledge of factors driving livestock aggregation patterns, but advances in gathering the data have outpaced advancements in analyzing and learning from it. We fit a hierarchical seemingly unrelated regression (SUR) model to explore how season of stocking and the location where cattle entered a pasture influenced grazing distributions. Stocking alternated between summer on one side of the pasture one year and fall on another side of the pasture the next year for 18 years. Waypoints were recorded on cattle for 50 d each year. We focused our analysis on the pasture's 10 most heavily grazed 4-ha units, because these units were the most prone to negative grazing impacts. Though grazing of the study units was always disproportionately heavy, it was much heavier with the summer than fall stocking regime: Bayesian confidence intervals indicate summer grazing of study units was approximately double the average fall grazing value. This is our core result, and it illustrates the strong effect stocking season or date or both can have on grazing distributions. We fit three additional models to explore the relative importance of stocking season versus location. According to this analysis, stocking season played a role, but stocking location was the main driver. Ostensibly minor factors (e.g. stocking location) can greatly influence livestock distributions.     

Predicting modes of spatial change from state-and-transition models

State-and-transition models (STMs) can represent many different types of landscape change, from simple gradient-driven transitions to complex, (pseudo-) random patterns. While previous applications of STMs have focused on individual states and transitions, this study addresses broader-scale modes of spatial change based on the entire network of states and transitions. STMs are treated as mathematical graphs, and several metrics from algebraic graph theory are applied—spectral radius, algebraic connectivity, and the S-metric. These indicate, respectively, the amplification of environmental change by state transitions, the relative rate of propagation of state changes through the landscape, and the degree of system structural constraints on the spatial propagation of state transitions. The analysis is illustrated by application to the Gualalupe/San Antonio River delta, Texas, with soil types as representations of system states. Concepts of change in deltaic environments are typically based on successional patterns in response to forcings such as sea level change or river inflows. However, results indicate more complex modes of change associated with amplification of changes in system states, relatively rapid spatial propagation of state transitions, and some structural constraints within the system. The implications are that complex, spatially variable state transitions are likely, constrained by local (within-delta) environmental gradients and initial conditions. As in most applications, the STM used in this study is a representation of observed state transitions. While the usual predictive application of STMs is identification of local state changes associated with, e.g., management strategies, the methods presented here show how STMs can be used at a broader scale to identify landscape scale modes of spatial change.     

Modelling the fate of marine turtle hatchlings

The SLIM oceanographic model was used to examine the fate of hatchling flatback turtles (Natator depressus) in the first two weeks of their dispersal starting at Wild Duck Island, a major turtle-nesting site in the central Great Barrier Reef region of Australia. We ran simulations to investigate the effects of spring versus neap tides, hatchling's swimming behaviour during their first three days at sea, and the location of nesting beaches. The model predicted that up to 50% of the turtle hatchlings entering the sea from the windward, southern beach remained after 14 days in shallow, nearshore waters, irrespective of tides and swimming. These waters are turbid and may be inhospitable to hatchlings. In contrast >80% of hatchlings dispersing from the leeward, northern beach were dispersed to deeper water (10-40 m) in a quasi-stationary dispersion core centred around 10 km north of the nesting beach after 14 days and the offshore spread of the turtle plume was enhanced by the hatchling's seaward swimming during the first three days. This was due to the presence of a coastal boundary layer and a stagnation zone around the northern side of island, but not the southern side. The model confirmed that dispersal from eastern Queensland flatback turtle rookeries is restricted to the lagoons and coastal waters, and that water circulation and hatchling's swimming control dispersion. The model explains why more turtles nest on the northern than the southern side. This study highlights the usefulness of oceanographic models to increase knowledge about a cryptic life stage of marine turtles.     

What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods

Species distribution model is the term most frequently used in ecological modelling, but other authors used instead predictive habitat distribution model or species-habitat models. A consensual ecological modelling terminology that avoids misunderstandings and takes into account the ecological niche theory does not exist at present. Moreover, different studies differ in the type of niche that is represented by similar distribution models. I propose to use as standard ecological modelling terminology the terms “ecological niche”, “potential niche”, “realized niche” models (for modelling their respective niches), and “habitat suitability map” (for the output of the niche models). Therefore, the user can understand more easily that models always forecast species’ niche and relate more closely the different types of niche models.     

重点源大气砷铅污染排放模型及特征

在我国的非常规性污染物质中,大气重金属砷、铅已越来越多地被关注和重视。文章综述了国内外人为源对大气中重金属排放的贡献,结果显示中国是全球人为活动向大气排放重金属最多的国家之一,燃煤和有色金属冶炼行业在相当长的时间内都将是最主要且最为重要的人为排放源。通过系统调研燃煤及有色金属冶炼业资源及产业布局状况,构建目前我国大气重金属相关清单模型,进行了我国重点源大气砷、铅排放清单分析,结果表明：（1）2000-2008年我国燃煤大气砷、铅排放量共为93733t,年均增长率为7．93％,2004-2008年有色金属冶炼业大气砷、铅排放量共为18836t,年均增长率为15．2％;（2）2000-2008年各经济部门中电力部门燃煤大气砷、铅放量始终最高,占燃煤大气排放总量的44．6％-57．1％,且呈逐年升高的趋势;（3）2000-2008年各省区中山西、河北、河南和湖南省是大气砷、铅的排放大户。其中,燃煤大气砷、铅排放量主要集中在人口密集、工业集中、经济发展速度较快的北部和中东部省区,包括山西、山东、河北、河南和江苏五省,占全国燃煤排放总量的39．1％,有色金属冶炼大气砷、铅排放量主要集中在我国有色金属工业较为发达的河南及湖南省,占全国有色金属冶炼业排放总量的47．3％。可以看出,我国需要高度重视大气重金属砷、铅的污染防治,加强排放控制基础能力建设,加快建立适合中国的大气砷、铅污染防治技术政策体系。     

危险化学品道路运输安全管理现状及发展趋势研究

为降低危化品运输风险,从危化品运输风险评价、道路选线模型、技术应用、应急联动机制及平台建设、统一联控监管平台等方面进行研究分析。通过对微观视角与宏观视角、单一应用与综合应用的归类和对比,进行分析并指出存在的问题。分析表明,获取精确连续数据,考虑多种外在变量来完善评估模型,注重理论、技术和监管资源的综合应用,发展大区域联控平台将是今后研究的发展趋势。     

Random parameter models for accident prediction on two-lane undivided highways in India

Introduction

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation.

Method

The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models.

Results

The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations.

Conclusions

The paper is concluded with a discussion on modeling results and the limitations of the present study.     

Highlights of LNG risk technology

The authors have recently undertaken a major review of LNG consequence modeling, compiling a wide range of historical information with more recent experiments and modeling approaches in a book entitled “LNG Risk-Based Safety: Modeling and Consequence Analysis”. All the main consequence routes were reviewed – discharge, evaporation, pool and jet fire, vapor cloud explosions, rollover, and Rapid Phase Transitions (RPT’s). In the book, experimental data bases are assembled for tests on pool spread and evaporation, burn rates, dispersion, fire and radiation and effects on personnel and structures. The current paper presents selected highlights of interest: lessons learned from historical development and experience, comparison of predictions by various models, varying mechanisms for LNG spread of water, a modeling protocol to enable acceptance of newer models, and unresolved technical issues such as cascading failures, fire engulfment of a carrier, the circumstances for a possible LNG BLEVE, and accelerated evaporation by LNG penetration into water.     

粤港珠江三角洲区域空气质量联动监测系统质控技术

空气污染日益呈现的区域性特点,使得空气质量区域联动监测成为必然趋势.以粤港珠江三角洲区域空气质量监控网络的实践为例,介绍了区域联动监测系统的组成和运行机制,并着重探讨了系统质量保证/质量控制(QA/QC)以及数据管理等核心支撑技术.