Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.     

Modeling the Effects of Potential Salinity Shifts on the Recovery of Striped Bass in the Savannah River Estuary,Georgia–South Carolina,United States

Increased salinity in spawning and nursery grounds in the Savannah River estuary was cited as the primary cause of a 97% decrease in adult striped bass (Morone saxatilis) and a concomitant 96% decrease in striped bass egg production. Restoration efforts focused on environmental remediation and stock enhancement have resulted in restored salinity patterns and increased egg and adult abundances. However, future water needs or harbor development may preclude further recovery by reducing freshwater inflow or increasing salinity intrusion. To assess the effect of potential changes in the salinity regime, we developed models relating discharge, tidal phase, and salinity to striped bass egg and early larval survival and re-cast these in a quantitative Bayesian belief network. The model indicated that a small upstream shift (≤1.67 km) in the salinity regime would have the least impact on striped bass early life history survival, whereas shifts >1.67 km would have progressively larger impacts, with a 8.33-km shift potentially reducing our estimated survival probability by >28%. Such an impact could have cumulative and long-term detrimental effects on the recovery of the Savannah River striped bass population. The available salinity data were collected during average and low flows, so our model represents some typical and some extreme conditions during a striped bass spawning season. Our model is a relatively simplistic, “first-order” attempt at evaluating potential effects of changes in the Savannah River estuarine salinity regime and points to areas of concern and potential future research.     

灾难事件后继风险决策

对小概率/高风险的灾难事件的后继风险决策进行探讨,着重在决策的认知神经经济模型框架下,讨论灾难事件后继风险决策的影响因素。灾难事件后人们的风险觉知、信念和假定、经验等认知因素以及灾后情绪因素对于决策分别有不同的影响;人们灾后决策的特点为决策更多直觉化而较少运用理性分析;灾难后继决策有随时间变化的趋势,灾难事件后人们为寻求安全感而出现"损失偏差"(loss bias),该偏差在"获得"和"损失"两种条件下的影响是不同的。灾后风险决策的内在机制或可用思维和决策的双加工系统(dual-process)模型来解释。最后展望了灾难事件后继决策进一步的研究方向。     

建筑物消防系统可靠性分析

为评估建筑物消防系统的可靠性,首先将系统分为探测报警系统和灭火系统等部分,再用事件树法分析事故发生时消防系统不同部分的反应情况.通过贝叶斯理论及历史统计数据得到系统失效率的不确定性概率分布,建立消防系统可靠性随时间变化的数学模型; 用蒙特卡罗方法模拟求得系统可靠性的时间函数并对模型的不确定性参数进行敏感性分析.该方法将统计数据与经验公式、理论方法相结合,并利用蒙特卡罗方法处理模型中的不确定性,不仅能够有效估计消防系统的可靠性,还可对其他类似系统的可靠性进行分析,并通过敏感性分析为进一步减少估计的不确定性提出合理建议.     

防洪物资储备决策方法初探

根据防洪抢险物资储备属于一种信息不全型决策问题的特点,本文提出了一种用于确定每年防灾物资准备量概率排序决策模型,并以孙不河流泥石流灾害预报火灾决策为例进行说明。     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.     

Optimal Expansion Strategy for a Sewer System under Uncertainty

Because of fast urban sprawl, land use competition, and the gap in available funds and needed funds, municipal decision makers and planners are looking for more cost-effective and sustainable ways to improve their sewer infrastructure systems. The dominant approaches have turned to planning the sanitary sewer systems within a regional context, while the decentralized and on-site/cluster wastewater systems have not overcome the application barriers. But regionalization policy confers uncertainties and risks upon cities while planning for future events. Following the philosophy of smart growth, this paper presents several optimal expansion schemes for a fast-growing city in the US/Mexico borderlands—the city of Pharr in Texas under uncertainty. The waste stream generated in Pharr is divided into three distinct sewer sheds within the city limit, including south region, central region, and north region. The options available include routing the wastewater to a neighboring municipality (i.e., McAllen) for treatment and reuse, expanding the existing wastewater treatment plant (WWTP) in the south sewer shed, and constructing a new WWTP in the north sewer shed. Traditional deterministic least-cost optimization applied in the first stage can provide a cost-effective and technology-based decision without respect to associated uncertainties system wide. As the model is primarily driven by the fees charged for wastewater transfer, sensitivity analysis was emphasized by the inclusion of varying flat-rate fees for adjustable transfer schemes before contracting process that may support the assessment of fiscal benefits to all parties involved. Yet uncertainties might arise from wastewater generation, wastewater reuse, and cost increase in constructing and operating the new wastewater treatment plant simultaneously. When dealing with multiple sources of uncertainty, the grey mixed integer programming (GIP) model, formulated in the second stage, can further allow all sources of uncertainties to propagate throughout the optimization context, simultaneously leading to determine a wealth of optimal decisions within a reasonable range. Both models ran for three 5-year periods beginning in 2005 and ending in 2020. The dynamic outputs of this analysis reflect the systematic concerns about integrative uncertainties within this decision analysis, which enable decision makers and stakeholders to make all-inclusive decisions for sanitary sewer system expansion in an economically growing region.     

A database for integrated assessment of European agricultural systems

A major bottleneck for data-based policy making is that data sources are collected, managed, and distributed by different institutions, residing in different locations, resulting in conceptual and practical problems. The use of dispersed data for agricultural systems research requires the integration of data sources, which means to ensure consistency in data interpretations, units, spatial and temporal scales, to respect legal regulations of privacy, ownership and copyright, and to enable easy dissemination of data. This paper describes the SEAMLESS integrated database on European agricultural systems. It contains data on cropping patterns, production, farm structural data, soil and climate conditions, current agricultural management and policy information. To arrive at one integrated database, a shared ontology was developed according to a collaborative process, which facilitates interdisciplinary research. The paper details this process, which can be re-used in other research projects for integrating data sources.     

Structuring Decisions for Managing Threatened and Endangered Species in a Changing Climate

The management of endangered species under climate change is a challenging and often controversial task that incorporates input from a variety of different environmental, economic, social, and political interests. Yet many listing and recovery decisions for endangered species unfold on an ad hoc basis without reference to decision‐aiding approaches that can improve the quality of management choices. Unlike many treatments of this issue, which consider endangered species management a science‐based problem, we suggest that a clear decision‐making process is equally necessary. In the face of new threats due to climate change, managers’ choices about endangered species require closely linked analyses and deliberations that identify key objectives and develop measurable attributes, generate and compare management alternatives, estimate expected consequences and key sources of uncertainty, and clarify trade‐offs across different dimensions of value. Several recent cases of endangered species conservation decisions illustrate our proposed decision‐focused approach, including Gulf of Maine Atlantic salmon (Salmo salar) recovery framework development, Cultus Lake sockeye salmon (Oncorhynchus nerka) management, and Upper Columbia River white sturgeon (Acipenser transmontanus) recovery planning. Estructuración de Decisiones para Manejar Especies Amenazadas y en Peligro en un Clima Cambiante     

DECISION-MAKING PROCESS ON THE DANUBE AND THE PLATTE1

ABSTRACT: Two case studies highlighting the institutional arrangements and decision-making processes used to attempt to allocate water on large scale river systems in two countries are presented. In both cases the implementation of river plans has been blocked by conflicts between those who wish to use water for irrigation, hydropower, or municipal purposes and those who wish to maintain instream flows for fish and wildlife. To date conflict has blocked the implementation of a large hydropower scheme on the Danube River, downstream from Vienna, Austria, and the construction of municipal and agricultural projects, as well as the relicensing of an existing hydropower facility on the Platte River in Nebraska. Analysis of the decision-making processes and institutional settings of both cases led to the identification of problem areas and development of recommendations that would support the achievement of compromise solutions for management.