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。

     

Understanding interlinkages between long-term trajectory of exposure and vulnerability,path dependency and cascading impacts of disasters in Saint-Martin (Caribbean)

This empirical and interdisciplinary study investigates the contribution of deeply enrooted social-political factors to the accumulation of exposure and vulnerability and amplification of cascading impacts of disasters, with implications on the creation and reinforcement of path dependency maintaining social-ecological systems on a maladaptive trajectory. Applying the Trajectory of Exposure and Vulnerability approach to Saint-Martin (Caribbean), we more specifically highlight how the causal chain linking historical geopolitical and political-institutional drivers to legal, economic, demographic, sociocultural, planning-related and environmental drivers, created the accumulation of exposure and vulnerability over time and contributed to the propagation and amplification of the impacts of tropical cyclones Irma and José in 2017. We find that historical social-political dynamics involving unsustainable development and settlement patterns, the weakness of local institutions, population mistrust in public authorities, high social inequalities and environmental degradation maintained Saint-Martin on a maladaptive trajectory through powerful reinforcing mechanisms operating both between and during cyclonic events. This study demonstrates that long-term interdisciplinary approaches are required for a better understanding of path dependency and the identification of levers to break it in risk-prone contexts. In Saint-Martin, breaking path dependency requires the alignment of local institutional capacities with national risk reduction policies, the promotion of social justice and involvement of local communities in decision making. This study therefore confirms the relevance of backward-looking approaches to support forward-looking climate adaptation.     

Reliability of X-band Dual-polarization Phased Array Radars Through Comparison with an S-band Dual-polarization Doppler Radar

Based on the observations of a squall line on 11 May 2020 and stratiform precipitation on 6 June 2020 from two X-band dual-polarization phased array weather radars(DP-PAWRs) and an S-band dual-polarization Doppler weather radar(CINRAD/SA-D), the data reliability of DP-PAWR and its ability to detect the fine structures of mesoscale weather systems were assessed. After location matching, the observations of DP-PAWR and CINRAD/SA-D were compared in terms of reflectivity(ZH), radial velocity(V), dif...     

一类广义Hamilton系统的辛格式

通过引人泊松括号，分析了无限维Hamilton的性质，并将其推广到广义Hamilton系统，且从理论和实用角度讨论了这类广义Hamilton系统的辛格式构造问题，从而为辛几何算法在一般的时间发展方程的数值求解提供新的具体途径。     

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.     

Connecting Local to Global: Geographic Information Systems and Ecological Footprints as Tools for Sustainability

Tools that support public engagement with sustainability are essential for local sustainability planning. This research investigates the ability of two geographic information system (GIS)-based tools to promote discussion of sustainability in a suburban context. A local ecological footprint tool and a community environmental atlas (an environmentally themed online mapping system) were created for seven suburban boroughs of Montreal. Variations of both tools have been used to support sustainability efforts, but their use has not been widely evaluated. Working from a public participation GIS (PPGIS) framework that recognizes the powerful influence of data representation, this research uses focus groups to evaluate how well these tools address three criteria that have emerged from the literature on public engagement in sustainability: interdependency across systems, reflexivity about personal and social decision making, and interactions across spatial scales. Whereas the atlas remains advantageous for discussing local spatial specifics, it was found that the ecological footprint helped people see the interconnections among systems, integrate local and global aspects of sustainability, and reflect on the values and assumptions underlying current social and economic structures.     

Human and Environmental Factors Affect Patterns of Crop Diversity in an Ethiopian Highland Agroecosystem

The Ethiopian highlands are a center of diversity for numerous globally important crops. Heterogeneous landscapes, traditional agricultural practices, and inaccessibility have created and maintained diverse subsistence agroecosystems. We surveyed sixty-three farms in twelve communities of the Gamo highlands and found high levels of on-farm diversity of crop species and varieties. The extent and nature of this diversity are related to both ecological factors, namely elevation, and anthropogenic factors such as land-use history, accessibility to markets and extension, and strength and scale of farmer exchange networks. These human landscape features have the potential to both enhance and mediate effects of elevation and other environmental factors on crop diversity. The interaction of environmental and anthropogenic forces on the diversity of crops grown by farmers affects the strategies farmers employ to adapt their farming to changing conditions.     

Rapid generation of Digital Elevation Models from topographic maps

Abstract

In this article we demonstrate that substantial gains in time can be made when using point sampling rather than contour line digitising for generation of Digital Elevation Models (DEMs). A simple sampling scheme, based on regularly distributed points, was used supplemented with points near break-lines in the terrain. An evaluation of surfaces created with three different interpolation methods at three different resolutions shows that the statistical distribution was better when using points as opposed to contours, and that the accuracy was comparable despite the much smaller amount of input data.