Establishing backcountry use quotas: An example from Mineral King,California

Increasing levels of visitor use and consequent resource damage have necessitated that backcountry use restrictions be established in the Mineral King area of Sequoia National Park, California. In this paper we review the steps taken in developing a trailhead quota system. The availability of acceptable campsites, based on a detailed inventory of site distribution and impact, was used to quantitatively derive use capacities for each camp area. Wilderness permit data on visitor dispersal patterns from the major trailheads, including length of stay at each camp area, were then used to translate the area capacities into daily trailhead quotas that would assure that these capacities were not surpassed. The general approach is applicable to any backcountry area, although large complex areas may require the use of available computer simulation models.     

MODELING HYDROLOGIC TIME SERIES FROM THE ARCTIC1

The general intervention model is applied to hydrologic and meteorologjc time series from the Canadian Arctic. The authors show how the model is able to account for environmental interventions, missing observations in the data, changes in data collection procedures, the effects of external inputs, as well as seasonality and autocorrelation. Methods for identifying transfer functions by making use of a physical understanding of the processes involved are demonstrated and sample applications of the general intervention model to Arctic data are shown.     

AN APPROACH TO MARGINAL ECONOMIC ANALYSIS OF HYDROMETRIC DATA COLLECTION1

ABSTRACT: A procedure for computing the benefit/cost ratio of a hydrometric network is outlined. It consists of two steps: firstly, establishing a relationship between hydrometric station density and error in hydrologic parameters and, secondly, relating hydrologic eror to changes in project cost. The procedure was applied to both the whole Canadian hydrometric network and the provincial networks.     

Smart city data architecture for energy prosumption in municipalities: concepts,requirements, and future directions

ABSTRACT

Big data is gaining visibility and importance, and its use is attaining higher levels of influence within municipalities. Due to this proliferation smart cities are posed to deploy architectures toward managing energy for Electric Vehicles (EV) and orchestrate the production, consumption, and distributing of energy from renewable sources such as solar, wind etc. in communities also known as prosumption. In smart city domain, Enterprise Architecture (EA) can be employed to facilitate alignment between municipality goals and the direction of the city in relation to Information Technology (IT) that supports stakeholders within the city. Hence, the alignment between IT and goals of the city is a critical process to support the continued growth and improvement of city services and energy sustainability. However, despite several research effort focused on data architecture in smart city, there have been few studies aimed at exploring how EA can be applied in smart cities to support residential buildings and EV for energy prosumption in municipalities. Therefore, this study conducts an extensive review and develops an architecture that can be employed in smart city domain based on big data management for energy prosumption in residential buildings and EV. Furthermore, secondary data was employed to present a case study to show the applications of the developed architecture in promoting energy prosumption. Findings suggest that the architecture provides interoperable open real-time, online, and historical data in facilitating energy prosumption. Respectively, this study offers exchange of data for sharing energy resources and provides insights to improve energy prosumption services.     

大数据条件下环境规制的变革——环境信息规制功能的视角

环境规制往往面临规制失灵的困境，而信息不对称是规制失灵的重要原因。环境信息是一种重要的环境规制工具，可以改变环境规制能力不足与规制意愿不足的问题。在大数据条件下，环境信息可以降低政府环境规制成本，实现环境规制的互动。随着技术的发展，环境大数据对环境规制会发挥更加积极的作用，并促进环境规制向精准规制、反身性规制、整体性规制的方向发展，有效地提高环境规制的绩效。     

中国城镇居民食物消费碳排放的时空演变特征分析

本文运用碳折算系数法和投入产出模型测算了1990—2018年中国30个省(区、市)城镇居民食物消费的人均直接碳排放、人均家庭间接碳排放和人均产业间接碳排放,并运用探索性空间数据分析(ESDA)对总碳排放的空间特征进行分析。研究表明:1990—2018年中国30个省(区、市)人均间接碳排放在研究期内呈增长趋势,人均产业碳排放增长幅度最大且始终处于主导地位,大部分地区的人均直接碳排放增长较为缓慢;人均碳排放和总碳排放都呈显著增长趋势,人均碳排放的增长幅度宁夏>新疆>上海>浙江>青海>北京,甘肃最小,总碳排放增长幅度广东>浙江>山东>江苏>河北>上海,吉林最低;总碳排放在大部分年份呈正的空间相关性,整体上呈"M"形波动;局部空间自相关分析结果表明,食物消费总碳排放存在高高型和低高型两种,且2000年及以后高高型稳定在上海、江苏、浙江地区。最后,本文依据实证结果对如何降低城镇居民食物消费碳排放提出了相应的政策建议。     

A PROCEDURE FOR ASSESSING WATER RESOURCES FOR URBAN PLANNING1

A matrix has been developed to guide the assessment of urban water resources. The matrix provides a means for determining the relative importance of water-related problems, and for identifying the data needed to evaluate these problems for the purpose of urban planning. The matrix columns list nine categories of potential water-related urban problems. The rows list 51 categories of data inputs which may be needed to evaluate the potential problems. The inputs include standard types of basic hydrologic data, information based on analysis and interpretation of these data, and information on the interfacing factors of climate, land, and culture. A system is described for ranking the relative importance of the problem categories and data inputs on a numerical scale of 0 to 3. From this, an index is derived that evaluates the relative importance of each input item to an overall program for water resource assessment. From the completed matrix the hydrologist can determine the availability of data to meet the identified requirements. Judgement can then be made as to priorities on work elements to provide the planner with maximum information in minimum time. The matrix also provides a basis for the development of programs and their funding in order to overcome critical data deficiencies.     

ON THE MISMATCH BETWEEN DATA AND MODELS OF HYDROLOGIC AND WATER RESOURCE SYSTEMS1

ABSTRACT: Many difficulties exist in the matching of models with data. This paper identifies elements of this problem and discusses considerations involved in model evaluation. The well known multivariate linear regression model is used to illustrate the distinctions between accuracy and precision and between estimation and prediction (because the model is commonly misused.) No amount of additional data will improve the accuracy of a poor model. A high R², while indicative of a good matching between the observed data and model estimates, is a poor criterion for judging adequacy of the model to make good predictions of future events. Model evaluation also includes the problem of introducing secondary data and proxy variables into a model. Secondary data frequently enter, for example, the mass, energy and water budget equations because of difficulties in measuring the primary variables. Proxy variables arise because of a desire to collapse a vector of incomparable values, say, of water quality into a single number. Review of the above issues indicates that model evaluation is a multi-criterion problem, often imbedded in a larger framework where models are intended to meet multiple objectives. The mismatch of models and data has increasing legal and social consequences.     

DATA REQUIREMENTS OF A WATER QUALITY MANAGEMENT PROGRAM1

ABSTRACT: Routine data collection currently consumes a large amount of the total resources devoted to water quality management. All too often data collection becomes an end in itself, with little thought given to the purpose of the data collection. The problem generally stems from a lack of proper routine surveillance system design and a failure on the part of the designers to initially identify the data needs of the management program. This study attempts, in a general way, to delineate the data needs of a water quality management program. This first required an identification of the activities involved in water quality management. The activities were then discussed in terms of the types of information needed to successfully complete their assigned tasks. Several detailed examples are given. The results of the discussion are summarized and several strategies are proposed to relate the results to surveillance system design.     

卫星云图资料同化中的质量控制及其在暴雨预报中的应用

以1996年7月3—4日发生在江淮流域的暴雨过程为例，依据统计特征分别以常规分析场、正涡度高值区、高低空急流为标准，设计了三套方案对卫星反演湿度场进行质量控制。利用中尺度MM5模式进行的数值试验表明：经质量控制后预报场得到较大改善；质量控制方案的优劣对预报效果有直接影响，选择合理的控制标准是重要的。