Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

The High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km³/year in 1985 to 18.2 km³/year in 2015, while irrigated croplands increased from 71,928 km² in 1985 to 78,464 km² in 2015 in the entire HPA. The hydroclimatic time-series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time-series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.     

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species-action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species-action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost-effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

HUD状态下飞行员视觉注意资源分配机制研究

为了解决平视显示器（Head Up Display,HUD）飞行中的注意资源分配问题，基于飞行模拟器，设计双作业飞行任务开展相关研究。基于事件相关电位（Event Related Potential，ERP）技术，选取行为绩效和P300成分为评价指标，采用oddball模式，在双作业飞行任务条件下开展实验研究。结果表明:随主任务难度的增加，主、辅任务的作业绩效均显著下降，被试者对HUD上异常信息的正确操作率降低，且反应时间延长；随主任务难度的增加，由辅任务所诱发的P300的波幅显著降低。在实验结果的基础上，最终提出了HUD状态下飞行员视觉注意资源分配机制。     

南岳衡山风景名胜区景观资源的调查与评价

景观资源是旅游资源的重要组成因素,本文以自然综合体的南岳衡山为考察对象,对其景观资源进行较详尽的调查,并进行定性和定量的评价,为确定南岳衡山风景名胜区性质、规划提供基础资料.     

论环境、资源与循环经济

根据质量守恒定律推导出环境与资源的数学关系,从而揭示了环境污染产生的根本原因,找到了解决环境和资源问题的根本途径,为发展循环经济,实现环境与资源可持续发展提供了科学的依据。     

钢铁酸洗废液的资源化处理技术

钢铁酸洗废液中含有大量的酸和铁盐，已被各国作为危险废物进行管理，多年来，研究者已经研究出多种有效、可行的资源化处理方法和技术，从技术成熟性、工艺特性、工艺关键、过程控制、应用前景和发展方向等方面介绍了技术上比较成熟和具有良好前景的7种主要方法，以利于保护环境和酸洗废液资源化处理技术的进步。     

超高浓度萘系磺酸染料中间体废液资源化

本文介绍了胺盐萃取回收率液中萘磺酸染料中间体的方法，回收率达９５％以上，回收浓缩液工艺套用，１０ｔ／ｄ废液量的资源化年净效益达５８０万元，投资费用两个月即可全部收回，采用Ｌａｎｇｍｕｉｒ等温方程描述体系中萃取剂用量，待萃物含量和萃取率的关系，使工艺参数的确立和工程设计完全处理指导之下。     

Uncertainty, learning, and the optimal management of wildlife

Wildlife management is limited by uncontrolled and often unrecognized environmental variation, by limited capabilities to observe and control animal populations, and by a lack of understanding about the biological processes driving population dynamics. In this paper I describe a comprehensive framework for management that includes multiple models and likelihood values to account for structural uncertainty, along with stochastic factors to account for environmental variation, random sampling, and partial controllability. Adaptive optimization is developed in terms of the optimal control of incompletely understood populations, with the expected value of perfect information measuring the potential for improving control through learning. The framework for optimal adaptive control is generalized by including partial observability and non-adaptive, sample-based updating of model likelihoods. Passive adaptive management is derived as a special case of constrained adaptive optimization, representing a potentially efficient suboptimal alternative that nonetheless accounts for structural uncertainty.     

Is Current Consumption Excessive? A General Framework and Some Indications for the United States

Abstract:  Many prior studies have explored the implications of human population growth and environmentally problematic technologies for biodiversity loss and other forms of environmental degradation. Relatively few, however, have examined the impacts of the level and composition of consumption. We offer a framework that shows how the level and composition of a society's total consumption relate to the uses of various forms of capital and to the sustainability of natural resources and human well-being. We relate the framework to two main approaches—top–down macro studies and bottom–up computer models—for measuring whether overall consumption in the United States satisfies a sustainability requirement. Existing top–down studies have shortcomings that bias their results toward optimism, and current computer simulation models, although strong on revealing biophysical outcomes, are limited in their ability to evaluate impacts on human well-being. Although some ambiguities arise in determining whether overall consumption in the United States is excessive, our conclusions regarding the composition of U.S. consumption are unambiguous. Distorted consumption patterns and associated production methods lead to excessively rapid natural resource depletion; greater conservation would yield gains to current and future generations that more than compensate for the sacrifices involved. Public policies that deal with the composition problem not only would help conserve natural resources and improve current welfare but also would reduce the costs of meeting the goal of sustainability.