A data‐based mechanistic modelling (DBM) approach to understanding dynamic sediment transmission through Wyresdale Park Reservoir,Lancashire, UK

This paper outlines the application of a new data‐based mechanistic (DBM) modelling methodology to the characterization of the sediment transmission dynamics in a small upland reservoir, Wyresdale Park, Lancashire. The DBM modelling strategy exploits advanced statistical procedures to infer the dynamic model structure and its associated parameters directly from the instrumented data, producing a parametrically efficient, continuous time, transfer function model which relates suspended sediment load at the reservoir inflow to the outflow at the event scale. The associated differential equation model parameters have physical attributes which can be interpreted in terms of sediment transmission processes and associated reservoir trap efficiency. Sedigraph analysis suggests that wind‐induced resuspension episodically supplies an additional load to the reservoir outlet. The stochastic nature of the DBM model makes it ideal for evaluating the effects of uncertainty through Monte Carlo simulations (MCS) for discharge and sediment transmission. Copyright © 2000 John Wiley & Sons, Ltd.     

Storm rainfall conditions for floods and debris flows from recently burned areas in southwestern Colorado and southern California

Debris flows generated during rain storms on recently burned areas have destroyed lives and property throughout the Western U.S. Field evidence indicate that unlike landslide-triggered debris flows, these events have no identifiable initiation source and can occur with little or no antecedent moisture. Using rain gage and response data from five fires in Colorado and southern California, we document the rainfall conditions that have triggered post-fire debris flows and develop empirical rainfall intensity–duration thresholds for the occurrence of debris flows and floods following wildfires in these settings. This information can provide guidance for warning systems and planning for emergency response in similar settings.Debris flows were produced from 25 recently burned basins in Colorado in response to 13 short-duration, high-intensity convective storms. Debris flows were triggered after as little as six to 10 min of storm rainfall. About 80% of the storms that generated debris flows lasted less than 3 h, with most of the rain falling in less than 1 h. The storms triggering debris flows ranged in average intensity between 1.0 and 32.0 mm/h, and had recurrence intervals of two years or less. Threshold rainfall conditions for floods and debris flows sufficiently large to pose threats to life and property from recently burned areas in south-central, and southwestern, Colorado are defined by: I = 6.5D^− 0.7 and I = 9.5D^− 0.7, respectively, where I = rainfall intensity (in mm/h) and D = duration (in hours).Debris flows were generated from 68 recently burned areas in southern California in response to long-duration frontal storms. The flows occurred after as little as two hours, and up to 16 h, of low-intensity (2–10 mm/h) rainfall. The storms lasted between 5.5 and 33 h, with average intensities between 1.3 and 20.4 mm/h, and had recurrence intervals of two years or less. Threshold rainfall conditions for life- and property-threatening floods and debris flows during the first winter season following fires in Ventura County, and in the San Bernardino, San Gabriel and San Jacinto Mountains of southern California are defined by I = 12.5D^−0.4, and I = 7.2D^−0.4, respectively. A threshold defined for flood and debris-flow conditions following a year of vegetative recovery and sediment removal for the San Bernardino, San Gabriel and San Jacinto Mountains of I = 14.0D^−0.5 is approximately 25 mm/h higher than that developed for the first year following fires.The thresholds defined here are significantly lower than most identified for unburned settings, perhaps because of the difference between extremely rapid, runoff-dominated processes acting in burned areas and longer-term, infiltration-dominated processes on unburned hillslopes.     

2006年6月10日浙江飑线FY-2C卫星云图特征

利用国际卫星云气候计划（International Satellite Cloud Climate Program,简称ISCCP）提供的1998—2007年共10 a的深对流路径跟踪资料,统计分析了影响江淮地区对流系统（Convection system,简称CS）的时空分布及其参数特征。结果表明：影响江淮地区的CS主要集中在春夏两季,大多生成于江淮本地及我国中西部地区,呈现以江淮地区为中心的带状分布特征,越靠近江淮区域CS分布越为密集。依据源地不同,将影响江淮地区的CS分为5类,受气候条件与地形地貌的共同作用,各源地CS参数特征差异显著,总体来说CS的水平尺度越大,其生命史、对流云团(Convective clusters,简称CC)数目及水平云温度梯度也越大。其中江淮中心区域（MID）区域CS水平尺度、生命史和CC数目的平均值均为最小;东南（SE）区域CS生命周期以中长周期为主,水平尺度、最大对流比和云温度梯度的平均值最大。梅雨期内江淮地区对流活动频繁,CS的水平尺度大、生命史长、CC数目多。

     

Dynamics of mule deer forage in the Sonoran Desert

Forage availability for mule deer (Odocoileus hemionus) in the Sonoran Desert depends on plant biomass, which is influenced by rainfall. We determined how rainfall, temperature and plant characteristics affected biomass of deer forage. We measured forage biomass, rainfall and temperature every 3 months from April 2000 to December 2002. Quarterly rainfall ranged from <1 to 57 mm, and forage biomass in desert washes fluctuated between 6 and 34 g m⁻². There was a positive relationship between forage biomass and rainfall the previous six months (p<0.001), and a negative relationship between biomass and average temperature the previous 3 months (p<0.001). Quarterly forage growth was positively influenced by rainfall (p<0.001) and negatively influenced by forage biomass (p<0.001). The relationships between deer forage and environmental factors established here will be useful in understanding population ecology of mule deer as part of an interactive model of plant–herbivore dynamics in arid environments.     

开封市的城市生态位变化分析

城市生态位作为生态学重要理论之一,用于分析城市生态不同功能模块间竞争、演化等现象。通过以开封市不同功能模块为研究对象,在各模块污染指数和适宜度指数的基础上,运用生态位理论和方法,探讨改革开放以来,特别是近十年来开封市不同功能模块生态位格局变化规律,并对变化的原因进行了分析。研究结果表明：(1) 1994~2003年开封市自然生态环境系统各模块生态位呈上升趋势的有大气环境模块、城市绿化模块,而呈下降趋势的有水环境模块、声环境模块。(2) 1994~2003年开封市经济系统各模块生态位呈上升趋势的是第三产业模块,呈下降趋势的是第二产业模块,而变化不大的是第一产业模块。(3) 1994~2003年开封市社会系统各模块适宜度生态位呈上升趋势的有社会基础设施模块、社会资源配置模块、社会生产与保障模块,而呈下降趋势的只有人口模块。(4) 国家政策体制的改革是改革开放以来特别是近十年来开封市各功能模块生态位发生变化的最直接和最根本的原因。该研究不但对城市不同功能模块的宏观规划、经济发展和环境保护有具体的指导意义,而且对拓展城市生态学理论、研究复合生态系统的内在作用机制也同样具有重大的理论和现实意义。     

金华市水资源承载力分析

从生态学角度出发,提出水资源承载力是在社会发展的某一阶段和生态系统良性循环的条件下,水资源对人类活动的最大支撑能力。指出目前金华市的水荒不是水源型缺水,而是水质型缺水和工程型缺水。根据20多年的历史数据和2020年全面建设小康社会的标准,利用系统动力学(SD)模型,仿真研究了金华市未来政策实施后水资源承载力的动态变化过程。同时指出,对于金华市来说,单方面追求经济的快速发展、以牺牲环境作为代价的高方案和把环境保护作为首要目标、经济慢速发展的低方案都是不可取的,只有经济发展和环境保护同时兼顾的中方案才是首选方案。     

我国高寒草甸植被生产力及其影响因子

生物量是重要的植物群落数量特征，直接反映生态系统生产者的物质生产量，是生态系统生产力的重要体现。高寒草甸广泛分布于青藏高原，是高寒生态系统的主要植被类型。回顾了高寒草甸生物量的研究成果。高寒草甸生物量呈典型的金字塔式垂直分布格局，地上生物量主要集中于0—10cm的冠层，地下生物量也集中分布于0—10cm的土层内。增温和多雨会降低生物量，叶面积和物种丰富度与地上生物量成正相关关系，氮素的增加有助于植被生物量的增长，而放牧率与生物量成显著负相关。     

APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES TO REMOTE SENSING*

Remote sensing is a geographic analysis tool capable of producing large quantities of data in the spectral, temporal and spatial domains. Techniques for automating the image analysis process would be advanced by the inclusion of artificial intelligence techniques in the design of image processing systems. The remote sensing application which show promise for successful implementation of artificial intelligence techniques are intelligent onboard processing, advanced database interrogation, and the automated analysis of multispectral imagery.     

Use of Fuzzy Membership Input Layers to Combine Subjective Geological Knowledge and Empirical Data in a Neural Network Method for Mineral-Potential Mapping

Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach.