Size-Dependent Selective Leaf Damage by Insects and Some Methodological Implications of This Phenomenon

The area of leaves on birch (Betula pubescens ssp. tortuosa) auxiblasts and brachyblasts and the degree of their damage by the complex of leaf-gnawing and leaf-mining insects were studied in a light birch forest. The results showed that phyllophagous insects, primarily snout beetles, prefer young leaves on the apexes of auxiblasts. Thus, selective damage is inflicted on smaller leaves, both on the auxiblasts and in the entire sample. This phenomenon is widespread and may manifest itself in different ways, depending on the pattern of leaf area distribution along the extended shoot and the feeding preferences of the insects. Thus, it is necessary to reconsider research methods and approaches based on the assumption that insects damage leaves nonselectively, irrespective of their size.     

湖北省区域可持续发展能力综合评价

从区域可持续发展的观点出发，根据湖北省具体区域特征，通过构建湖北省区域可持续发展指标体系和评估方法，得出湖北省12个地市人口、资源、环境、经济和社会5个系统的可持续发展指数以及区域综合可持续发展指数。从总体上看，湖北省区域可持续发展水平处于偏低水平，其中武汉市是唯一具有强可持续发展能力的城市，但优势地位不明显；其它城市可持续发展5个系统均存在发展不平衡状况，且城市特色不突出。     

Suburbanization and drought: A mixed methods vulnerability assessment in rainy Massachusetts

This paper presents evidence that water restrictions in suburbanizing eastern Massachusetts towns are becoming more common, controlling for climate. We then assess the relationship between these suburban droughts and residential development. Focusing on the suburbs of Boston, seven towns independent of the Boston water supply system were selected to represent differing levels of sprawl-style growth. Water restrictions are becoming more frequent in all of the towns studied, and models demonstrate that restrictions are increasing in duration, independent of climate. Interviews suggest that residential development is playing a central role in this increasing sensitivity to suburban drought, though other factors are also important. Long-term planning and integration of land-use planning and water management emerged as two key paths for attenuating the impacts of development.     

模糊聚类法在大气环境质量评价中的应用

通过对2004年甘肃省5个有代表性城市的大气质量监测数据进行分析,较为详细地介绍了将模糊聚类法应用于大气环境质量综合评价的过程,从而展示了模糊聚类在环境评价和管理中的积极作用和重要意义.     

HSE管理体系的基层安全教育培训探讨

安全教育培训是石油行业一项非常重要的安全基础性工作,扎实开展基层员工安全培训,提高安全综合素质,增强事故防范能力,防止发生不安全行为,才能真正达到预防事故的目的。本文从七个方面介绍基层安全教育培训的一些方法与实践,针对性强、实用性好,并已在基层单位取得了较好的效果。     

小城镇基准地价更新方法研究

基准地价评估及更新是目前土地管理的一项重要和经常性的工作。针对小城镇的土地利用特点，对小城镇土地定级估价更新中的地价样本祷点、土地级别调整、基准地价更新评估等方面进行了研究，选择级别界线修订法更新小城镇土地级别，并在此基础上探索出适合小城镇特点的基准地价更新方法。     

Development and Operational Testing of a Super‐Ensemble Artificial Intelligence Flood‐Forecast Model for a Pacific Northwest River

Coastal catchments in British Columbia, Canada, experience a complex mixture of rainfall‐ and snowmelt‐driven contributions to flood events. Few operational flood‐forecast models are available in the region. Here, we integrated a number of proven technologies in a novel way to produce a super‐ensemble forecast system for the Englishman River, a flood‐prone stream on Vancouver Island. This three‐day‐ahead modeling system utilizes up to 42 numerical weather prediction model outputs from the North American Ensemble Forecast System, combined with six artificial neural network‐based streamflow models representing various slightly different system conceptualizations, all of which were trained exclusively on historical high‐flow data. As such, the system combines relatively low model development times and costs with the generation of fully probabilistic forecasts reflecting uncertainty in the simulation of both atmospheric and terrestrial hydrologic dynamics. Results from operational testing by British Columbia's flood forecasting agency during the 2013‐2014 storm season suggest that the prediction system is operationally useful and robust.     

Calibration and Verification of SWMM for Low Impact Development

The Storm Water Management Model was used to simulate runoff and nutrient export from a low impact development (LID) watershed and a watershed using traditional runoff controls. Predictions were compared to observed values. Uncalibrated simulations underpredicted weekly runoff volume and average peak flow rates from the multiple subcatchment LID watershed by over 80%; the single subcatchment traditional watershed had better predictions. Saturated hydraulic conductivity, Manning's n for swales, and initial soil moisture deficit were sensitive parameters. After calibration, prediction of total weekly runoff volume for the LID and traditional watersheds improved to within 12 and 5% of observed values, respectively. For the validation period, predicted total weekly runoff volumes for the LID and traditional watersheds were within 6 and 2% of observed values, respectively. Water quality simulation was less successful, Nash–Sutcliffe coefficients >0.5 for both calibration and validation periods were only achieved for prediction of total nitrogen export from the LID watershed. Simulation of a 100‐year, 24‐h storm resulted in a runoff coefficient of 0.46 for the LID watershed and 0.59 for the traditional watershed. Results suggest either calibration is needed to improve predictions for LID watersheds or expanded look‐up tables for Green–Ampt infiltration parameter values that account for compaction of urban soil and antecedent conditions are needed.     

Calibrating a Basin‐Scale Groundwater Model to Remotely Sensed Estimates of Groundwater Evapotranspiration

Remotely sensed vegetation indices correspond to canopy vigor and cover and have been successfully used to estimate groundwater evapotranspiration (ET_g) over large spatial and temporal scales. However, these data do not provide information on depth to groundwater (dtgw) necessary for groundwater models (GWM) to calculate ET_g. An iterative approach is provided that calibrates GWM to ET_g derived from Landsat estimates of the Enhanced Vegetation Index (EVI). The approach is applied to different vegetation groups in Mason Valley, Nevada over an 11‐year time span. An uncertainty analysis is done to estimate the resulting mean and 90% confidence intervals in ET_g to dtgw relationships to quantify errors associated with plant physiologic complexity, species variability, and parameter smoothing to the 100 m GWM‐grid, temporal variability in soil moisture and nonuniqueness in the solution. Additionally, a first‐order second moment analysis shows ET_g to dtgw relationships are almost exclusively sensitive to estimated land surface, or maximum, ET_g despite relatively large uncertainty in extinction depths and hydraulic conductivity. The EVI method of estimating ET_g appears to bias ET_g during years with exceptionally wet spring/summer conditions. Excluding these years improves model performance significantly but highlights the need to develop a methodology that accounts not only on quantity but timing of annual precipitation on phreatophyte greenness.