Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Development of a Methodology for Selecting Criteria and Indicators of Sustainable Forest Management: A Case Study on Participatory Assessment

This paper describes an application of multiple criteria analysis (MCA) in assessing criteria and indicators adapted for a particular forest management unit. The methods include: ranking, rating, and pairwise comparisons. These methods were used in a participatory decision-making environment where a team representing various stakeholders and professionals used their expert opinions and judgements in assessing different criteria and indicators (C&I) on the one hand, and how suitable and applicable they are to a forest management unit on the other. A forest concession located in Kalimantan, Indonesia, was used as the site for the case study. Results from the study show that the multicriteria methods are effective tools that can be used as structured decision aids to evaluate, prioritize, and select sets of C&I for a particular forest management unit. Ranking and rating approaches can be used as a screening tool to develop an initial list of C&I. Pairwise comparison, on the other hand, can be used as a finer filter to further reduce the list. In addition to using these three MCA methods, the study also examines two commonly used group decision-making techniques, the Delphi method and the nominal group technique. Feedback received from the participants indicates that the methods are transparent, easy to implement, and provide a convenient environment for participatory decision-making.     

Using Decision Analysis to Choose Phosphorus Targets for Lake Erie

Lake Erie water quality has improved dramatically since the degraded conditions of the 1960s. Additional gains could be made, but at the expense of further investment and reductions in fishery productivity. In facing such cross-jurisdictional issues, natural resource managers in Canada and the United States must grapple with conflicting objectives and important uncertainties, while considering the priorities of the public that live in the basin. The techniques and tools of decision analysis have been used successfully to deal with such decision problems in a range of environmental settings, but infrequently in the Great Lakes. The objective of this paper is to illustrate how such techniques might be brought to bear on an important, real decision currently facing Lake Erie resource managers and stakeholders: the choice of new phosphorus loading targets for the lake. The heart of our approach is a systematic elicitation of stakeholder preferences and an investigation of the degree to which different phosphorus-loading policies might satisfy ecosystem objectives. Results show that there are potential benefits to changing the historical policy of reducing phosphorus loads in Lake Erie.     

Methodological Development of an Index of Coastal Water Quality: Application in a Tourist Area

With the aim of obtaining an index of coastal water quality, a methodological procedure based on numerical classification and discriminant analysis is presented. The procedure was applied to nutrient data (ammonia, nitrite, nitrate, and phosphate) analyzed along the coastal waters of a Spanish tourist area. Using numerical classification, three levels of nutrient loading were revealed, characterizing oligotrophic, mesotrophic, and potentially eutrophic waters. Discriminant analysis was shown to be an effective methodological tool in the discrimination between trophic groups. For every group, the discriminant procedure generated the centroids. The centroids representing oligotrophic and potentially eutrophic conditions were used to establish the two extremes of the continuum of mesotrophic conditions in these coastal waters: Standardizing values from -1 to 1, the centroids for oligotrophic and potentially eutrophic waters yielded an interval that defined the range of mesotrophic conditions. This interval is proposed as a water quality index. The ability of the coastal water quality index to successfully predict mesotrophic conditions was proved with random samples.     

多元回归分析法在突发性事故污染预测中的应用

运用多元回归性，通过预测模型的选择、基础数据系列化、回归模型的建立和回归效果的检验，建立了化学污染危害面积、纵深与诸条件的关系，达到了快速估算的目的，是突出性化学环境污染危害预测的一种方法。     

REVIEW ON GLOBAL NATURAL DISASTERS IN 2000

20 0 0ｗａｓａｒｅｌａｔｉｖｅｌｙｎｏｒｍａｌｙｅａｒｉｎｔｅｒｍｓｏｆｇｌｏｂａｌｄｉｓａｓｔｅｒｅｖｅｎｔｓ.Ｔｈｅｇｌｏｂａｌｌｏｓｓｆｒｏｍｎａｔｕｒａｌｄｉｓａｓｔｅｒｓｗａｓａｐｐｒｏｘｉｍａｔｅｌｙ 30ｂｉｌｌｉｏｎＵＳＤ ,ｗｈｅｒｅａｓｔｈａｔｉｎａｎｙｏｆｔｈｅｐｒｅｖｉｏｕｓｙｅａｒｓｈａｄｅｘｃｅｅｄｅｄ 1 0 0ｂｉｌｌｉｏｎＵＳＤ .Ｔｈｅｉｎｓｕｒａｎｃｅｌｏｓｓｉｎ 2 0 0 0ｗａｓｏｎｌｙ 8.3ｂｉｌｌｉｏｎＵＳＤ ,ｗｉｔｈ 92 0 0 ｐｅｒｓｏｎｓｋｉｌｌｅｄ .Ｔｈｅｒｅｗａｓｎ…     

丝栗栲种群生命过程及谱分析

以种群生命表及生存分析理论为基础，编制丝栗栲种群静态生命表，绘制存活曲线，死亡率曲线，亏损度曲线，死亡密度函数曲线。积累死亡函数曲线和危险率函数曲线，分析种群生命过程。结果表明，丝栗栲有2个死亡高峰，存活曲线趋于Deevey-Ⅱ型。并应用谱分析方法研究丝栗栲种群动态，结果表明，在丝栗栲种群自然更新过程中存在着明显的周期性。     

引黄水库沉沙条渠沉积物的组成及理化特征

研究了济南市引黄供水鹊山水库沉沙条渠6个地理位置泥沙沉积物的组成及理化特征,并分析了沉积物的组成及理化特征参数间的相关性.结果表明,沉沙条渠内的泥沙沉积物在组成成分上与黄河沉积物基本相同,但含量及理化性质上有一定的差异.泥沙沉积物颗粒主要以粘粒、粉砂和细砂粒为主,颗粒粒度分布在0.3—125μm之间;沉积物的矿物主要由...     

Multiple-pattern parameter identification and uncertainty analysis approach for water quality modeling

This paper presents a multiple-pattern parameter identification and uncertainty analysis approach for robust water quality modeling using a neural network (NN) embedded genetic algorithm (GA). The modeling approach uses an adaptive NN–GA framework to inversely solve the governing equations in a water quality model for multiple parameter patterns, along with an alternating fitness method to maintain solution diversity. The procedure was demonstrated through a coupled 2D hydrodynamic and eutrophication model for Loch Raven Reservoir in Maryland. The inverse problem was formulated as a nonlinear optimization problem minimizing the degree of misfit (DOM) between model results and observed data. A set of NN models was developed to approximate the input-output response relationship of the Loch Raven Reservoir model and was incorporated into a GA framework in an adaptive fashion to search for near-optimal solutions minimizing the DOM. The numerical example showed that the adaptive NN–GA approach is capable of identifying multiple parameter patterns that reproduce the observed data equally well. The resulting parameter patterns were incorporated into the numerical model, and a multiple-pattern robust water quality modeling analysis, along with a compound margin of safety (CMOS) method, was proposed and applied to analyze the parameter pattern uncertainty.     

Understanding the Lessons and Limitations of Conservation and Development

Abstract: The lack of concrete instances in which conservation and development have been successfully merged has strengthened arguments for strict exclusionist conservation policies. Research has focused more on social cooperation and conflict of different management regimes and less on how these factors actually affect the natural environments they seek to conserve. Consequently, it is still unknown which strategies yield better conservation outcomes? We conducted a meta‐analysis of 116 published case studies on common resource management regimes from Africa, south and central America, and southern and Southeast Asia. Using ranked sociodemographic, political, and ecological data, we analyzed the effect of land tenure, population size, social heterogeneity, as well as internally devised resource‐management rules and regulations (institutions) on conservation outcome. Although land tenure, population size, and social heterogeneity did not significantly affect conservation outcome, institutions were positively associated with better conservation outcomes. There was also a significant interaction effect between population size and institutions, which implies complex relationships between population size and conservation outcome. Our results suggest that communities managing a common resource can play a significant role in conservation and that institutions lead to management regimes with lower environmental impacts.