湖北郧西县庹家湾剖面粒度组成特征及其环境意义

对湖北省郧西县庹家湾(TJW)剖面的地层序列、年代、磁化率及粒度组成进行研究。结果表明:TJW剖面具有表土(MS)→全新世黄土(L0)→古土壤(S0)→过渡层(Lt)→马兰黄土(L1)→黄土与砂互层(T1-al2)→砾石层(T1-al1)的地层序列;在马兰黄土层上部的黏粒含量、黏粒/粉砂值以及磁化率值明显高于典型马兰黄土,而接近古土壤(S0),其成壤作用明显,属于较典型的弱古土壤层(L1-S1和L1-S2),其年龄在27.3~21.6 ka B.P.之间。此现象反映了在汉江上游地区,晚更新世时期的冰期气候并不是持续稳定的,在27.3~21.6 ka B.P.期间存在相对短暂的温暖湿润阶段,这次气候事件可与黄土高原地区进行良好对比。     

基于面板数据的土地投入对经济增长的影响-以浙江省为例

采用生产函数与面板数据回归模型相结合的研究手段,以地处经济发达地区的浙江省为实证研究区域对土地要素投入对经济增长的影响进行了定量的研究。研究结果表明：(1)就规模效应而言,浙江省的经济增长处于规模报酬不变的发展阶段;(2)浙江省经济增长对劳动力要素的投入最为敏感,其中土地要素、劳动力要素和资本要素增加1个单位的投入量对经济增长的推动为 0.247 3、0.538 5 和 0.321 6;（3）固定资产投入在研究期间是浙江省经济增长的主要推动力,其贡献率达到6823%,而劳动力要素与土地要素则分别为2346%和625%;(4)浙江省土地利用不够集约,在研究期间土地要素对经济增长的影响能被资本要素与劳动力要素有效替代,而劳动力要素则难以被资本投入与土地投入有效替代,劳动集约型产业应该成为浙江省未来发展方向之一。     

Analysis of long-term changes in the dates of seasonal phenomena in plants and insects of the Il’men Reserve as related to climatic factors

The results of monitoring the dates of the onset of flowering and leaf budding in eight herbaceous and woody plant species and the first appearance of three insect species in the Il’men Reserve (1972–2005) were processed by means of regression and correlation analyses. No significant changes in test parameters were revealed in the majority of these species. Only two early spring plants, coltsfoot (Tussilago farfara L.) and goat willow (Salix caprea L.), showed a weak tendency toward earlier flowering in the 1980s and 1990s. This is explained primarily by the absence of any significant trends in spring and summer air temperatures in the study region over the observation period. On the other hand, interannual fluctuations in the dates of plant flowering and insect appearance were well manifested not only in early spring but also in late-spring species. These fluctuations proved to depend largely on spring temperatures: in years with early and warm springs, flowering and leaf budding in plants and the appearance of first individuals in insects were recorded on significantly earlier dates.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.     

Field Evaluation of DRAINMOD 5.1 Under a Cold Climate: Simulation of Daily Midspan Water Table Depths and Drain Outflows1

Abstract: The hydrologic performance of DRAINMOD 5.1 was assessed for the southern Quebec region considering freezing/thawing conditions. A tile drained agricultural field in the Pike River watershed was instrumented to measure tile drainage volumes. The model was calibrated using water table depth and subsurface flow data over a two‐year period, while another two‐year dataset served to validate the model. DRAINMOD 5.1 accurately simulated the timing and magnitude of subsurface drainage events. The model also simulated the pattern of water table fluctuations with a good degree of accuracy. The R² between the observed and simulated daily WTD for calibration was >0.78, and that for validation was 0.93. The corresponding coefficients of efficiency (E) were >0.74 and 0.31. The R² and E values for calibration/validation of subsurface flow were 0.73/0.48 and 0.72/0.40, respectively. DRAINMOD simulated monthly subsurface flow quite accurately (E > 0.82 and R² > 0.84). The model precisely simulated daily/monthly drain flow over the entire year, including the winter months. Thus DRAINMOD 5.1 performed well in simulating the hydrology of a cold region.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

What is most important for safety climate: The company belonging or the local working environment? – A study from the Norwegian offshore industry

Obtaining knowledge about factors affecting health, safety and environment (HSE) is of major interest to the petroleum industry, but there is currently a severe shortage of relevant studies. The aim of this study was to examine the relative influence of offshore installation (local working environment) and company belonging on employees’ opinions concerning occupational health and safety. We analyzed data from a safety climate survey answered by 4479 Norwegian offshore petroleum employees in 2005 on the dimensions “Safety prioritisation”, “Safety management and involvement”, “Safety versus production”, “Individual motivation”, “System comprehension” and “Competence” using one way analysis of variance (ANOVA), effect size and mixed model. The companies differed significantly for “Safety prioritisation”, “Safety versus production”, “Individual motivation”, “System comprehension” and “Competence”. The local offshore installation explained more of the safety climate than the company they were employed in or worked for did.     

复杂社会技术系统安全事故的成因结构敏感性及预防对策研究

简要回顾现有复杂社会技术系统安全事故的成因理论存在的局限性,根据大量统计资料和经验总结构建事故成因理论的缺陷。该研究试图从分析和推理入手,根据复杂社会技术系统运行机制及事故成因结构敏感性特征,探索由于新技术快速普及应用而不断涌现的复杂社会技术系统的失效机制及事故的成因理论;解释复杂社会技术系统安全事故的严重程度差异性、时间方向性及情境依赖性;为任何因新技术普及应用而产生的人造系统的安全分析及事故预防提供理论和方法支撑。     

Adaptation Scenarios of Agriculture in Poland to Future Climate Changes

This paper demonstrates the ability of Polish agriculture to adapt to predicted climate change according to GISS and GFDL scenarios. Both climate-change scenarios will significantly affect farming conditions in Poland through water deficit, shifts in planting and harvesting seasons, changes in crop yields and crop structure. Neither scenario seems to endanger the self-sufficiency of Poland as long as preventative measures are taken. Moreover, the realization of GISS creates the possibility of a surplus in production. It must be emphasized that regardless of the scenario, the adaptation of agriculture to an expected climate change cannot be handled by the farming community itself.     

Montane Meadows as Indicators of Environmental Change

We used a time series of satellite multispectral imagery for mapping and monitoring six classes of montane meadows arrayed along a moisture gradient (from hydric to mesic to xeric). We hypothesized that mesic meadows would support the highest species diversity of plants, birds, and butterflies because they are more moderate environments. We also hypothesized that mesic meadows would exhibit the greatest seasonal and interannual variability in spectral response across years. Field sampling in each of the meadow types was conducted for plants, birds, and butterflies in 1997 and 1998. Mesic meadows supported the highest plant species diversity, but there was no significant difference in bird or butterfly species diversity among meadow types. These data show that it may be easier to detect significant differences in more species rich taxa (e.g., plants) than taxa that are represented by fewer species (e.g., butterflies and birds). Mesic meadows also showed the greatest seasonal and interannual variability in spectral response. Given the rich biodiversity of mesic montane meadows and their sensitivity to variations in temperature and moisture, they may be important to monitor in the context of environmental change