水化前兆观测的探讨和反思

从水文地球化学的角度说明利用水化组分预报地震是可行的 ,并以历次地震的震例说明水化组分具有映震能力 ,进而对映震组分的不灵敏原因作了探讨。并就今后如何利用水化观测手段进行地震预报的分析研究提出几点建议。     

国外厌氧颗粒污泥培养研究简介

本文荟萃了荷兰、美国、德国、法国许多学者对厌氧颗粒污泥培养的研究，强调了颗粒化的机理仍是一个较为复杂而尚存在许多未知数的领域，并介绍了颗粒污泥的贮存。     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Response of Organic and Inorganic Carbon and Nitrogen to Long-Term Grazing of the Shortgrass Steppe

We investigated the influence of long-term (56 years) grazing on organic and inorganic carbon (C) and nitrogen (N) contents of the plant–soil system (to 90 cm depth) in shortgrass steppe of northeastern Colorado. Grazing treatments included continuous season-long (May–October) grazing by yearling heifers at heavy (60–75% utilization) and light (20–35% utilization) stocking rates, and nongrazed exclosures. The heavy stocking rate resulted in a plant community that was dominated (75% of biomass production) by the C₄ grass blue grama (Bouteloua gracilis), whereas excluding livestock grazing increased the production of C₃ grasses and prickly pear cactus (Opuntia polycantha). Soil organic C (SOC) and organic N were not significantly different between the light grazing and nongrazed treatments, whereas the heavy grazing treatment was 7.5 Mg ha^–1 higher in SOC than the nongrazed treatment. Lower ratios of net mineralized N to total organic N in both grazed compared to nongrazed treatments suggest that long-term grazing decreased the readily mineralizable fraction of soil organic matter. Heavy grazing affected soil inorganic C (SIC) more than the SOC. The heavy grazing treatment was 23.8 Mg ha^–1 higher in total soil C (0–90 cm) than the nongrazed treatment, with 68% (16.3 Mg ha^–1) attributable to higher SIC, and 32% (7.5 Mg ha^–1) to higher SOC. These results emphasize the importance in semiarid and arid ecosystems of including inorganic C in assessments of the mass and distribution of plant–soil C and in evaluations of the impacts of grazing management on C sequestration.     

Information Management System for Site Remediation Efforts

/ Environmental regulatory agencies are responsible for protecting human health and the environment in their constituencies. Their responsibilities include the identification, evaluation, and cleanup of contaminated sites. Leaking underground storage tanks (USTs) constitute a major source of subsurface and groundwater contamination. A significant portion of a regulatory body's efforts may be directed toward the management of UST-contaminated sites. In order to manage remedial sites effectively, vast quantities of information must be maintained, including analytical dataon chemical contaminants, remedial design features, and performance details. Currently, most regulatory agencies maintain such information manually. This makes it difficult to manage the data effectively. Some agencies have introduced automated record-keeping systems. However, the ad hoc approach in these endeavors makes it difficult to efficiently analyze, disseminate, and utilize the data. This paper identifies the information requirements for UST-contaminated site management at the Waste Cleanup Section of the Department of Environmental Resources Management in Dade County, Florida. It presents a viable design for an information management system to meet these requirements. The proposed solution is based on a back-end relational database management system with relevant tools for sophisticated data analysis and data mining. The database is designed with all tables in the third normal form to ensure data integrity, flexible access, and efficient query processing. In addition to all standard reports required by the agency, the system provides answers to ad hoc queries that are typically difficult to answer under the existing system. The database also serves as a repository of information for a decision support system to aid engineering design and risk analysis. The system may be integrated with a geographic information system for effective presentation and dissemination of spatial data.     

低周荷载下型钢混凝土柱抗剪性能智能分析

为了研究型钢混凝土短柱的抗震性能，通过21根SRC柱在低周反复荷载作用下的剪切黏结破坏试验结果，在利用灰色关联理论进行模型输入变量选择的基础上，建立了其基于改进神经网络模型的受剪承载力分析模型，进而研究了混凝土抗压强度、腹板宽度、轴压比及箍筋间距等因素对SRC柱抗剪能力的影响规律，并对SRC柱的受剪承载力进行了预测。结果表明，所提方法能够反映受剪承载力与影响因素间的非线性变化规律，可供SRC柱在低周往复荷载作用下的受剪承载力分析参考。     

CO2 storage capacity estimation: Methodology and gaps

Implementation of CO₂ capture and geological storage (CCGS) technology at the scale needed to achieve a significant and meaningful reduction in CO₂ emissions requires knowledge of the available CO₂ storage capacity. CO₂ storage capacity assessments may be conducted at various scales—in decreasing order of size and increasing order of resolution: country, basin, regional, local and site-specific. Estimation of the CO₂ storage capacity in depleted oil and gas reservoirs is straightforward and is based on recoverable reserves, reservoir properties and in situ CO₂ characteristics. In the case of CO₂-EOR, the CO₂ storage capacity can be roughly evaluated on the basis of worldwide field experience or more accurately through numerical simulations. Determination of the theoretical CO₂ storage capacity in coal beds is based on coal thickness and CO₂ adsorption isotherms, and recovery and completion factors. Evaluation of the CO₂ storage capacity in deep saline aquifers is very complex because four trapping mechanisms that act at different rates are involved and, at times, all mechanisms may be operating simultaneously. The level of detail and resolution required in the data make reliable and accurate estimation of CO₂ storage capacity in deep saline aquifers practical only at the local and site-specific scales. This paper follows a previous one on issues and development of standards for CO₂ storage capacity estimation, and provides a clear set of definitions and methodologies for the assessment of CO₂ storage capacity in geological media. Notwithstanding the defined methodologies suggested for estimating CO₂ storage capacity, major challenges lie ahead because of lack of data, particularly for coal beds and deep saline aquifers, lack of knowledge about the coefficients that reduce storage capacity from theoretical to effective and to practical, and lack of knowledge about the interplay between various trapping mechanisms at work in deep saline aquifers.     

WATER BUDGET COMPUTATION FOR A SHALLOW LAKE-LAKE OKEECHOBEE,FLORIDA1

ABSTRACT: The water budget computation in shallow lakes is complicated because marsh vegetation can transpire large quantities of lake water. Thus, a model including the marsh zone evapotranspiration (WET) was developed to compute the water budget for Lake Okeechobee. Three periods of testing (1969–74), planning (1963–74), and recorded period (1952–77) were used to compare the differences of the sum of storage deviation between the WET and conventional methods (WOET). Results of the WOET method showed that the sum of stage deviations were 87.42 cm (2.868 ft.), 231.80 cm (7.605 ft.), and 284.50 cm (9.333 ft.) in the testing, planning, and recorded periods, respectively. These stage deviations are equivalent in the same order to 29, 76, and 93 percent of the lake volume. In general, the WET method not only was applicable to compute the water budget for the lake but also reduced the sum of storage deviation by about 42, 31, and 49 percent, respectively, in those three periods. The storage deviation in WET method was reduced on an average to about 2 percent each year in all three periods, and the deviations were scattered more randomly than in WOET.     

COMPARISON OF TWO AUTOREGRESSIVE MODELS FOR MONTHLY STREAM FLOW GENERATION1

ABSTRACT: Two autoregressive models for monthly stream flow generation are compared based on the reproduction of the historical record in terms of several important statistics such as the mean, standard deviation, skewness coefficient, correlation coefficient, and the reservoir storage components. In the comparison, both theoretical considerations and practical applications are employed to evaluate the performance of each model.     

MICRO-RELIEF SURFACE DEPRESSION STORAGE: ANALYSIS OF MODELS TO DESCRIBE THE DEPTH-STORAGE FUNCTION1

ABSTRACT: Micro-relief surface depression storage is one of the components of the rainfall-runoff process. The quantification of surface depression storage values and a depth-storage model to describe the storage was the subject of this study. Point measurement data were collected on 258 surfaces of 5 soils and three artificial surfaces. Five methods of computing storage, 15 depth-storage models, two depth increments, and six grid spacings were investigated. The 1-inch grid computational method, 0.1-inch depth increment, and 1-inch grid spacings were recommended. The surface depression storage function is best described by the model S = aD^b, which relates surface depression storage as a function of depth with two equation parameters. Equations for describing the surface depression storage model parameters have been developed.