PROBLEMS IN WEIGHTING OF HYETOGRAPHS1

ABSTRACT: It was found that the conventional weighting factor application to hyetograph ordinates results in artificially attenuated storm patterns. A modified weighting procedure is suggested which allows adjustments in the storm timing, peak intensity, and volume but conserves the storm pattern observed at the raingage nearest to the watershed point of interest. The systematic underestimation of peak flood flows, which result from conventional hyetograph weighting, can be avoided by conserving the hyetograph shape from the raingage nearest to any subarea of a modeled watershed and merely applying weighting factors to the rainfall volumes and temporal center of gravity of several hyetographs.     

Land Management in the American Southwest: A State-and-Transition Approach to Ecosystem Complexity

State-and-transition models are increasingly being used to guide rangeland management. These models provide a relatively simple, management-oriented way to classify land condition (state) and to describe the factors that might cause a shift to another state (a transition). There are many formulations of state-and-transition models in the literature. The version we endorse does not adhere to any particular generalities about ecosystem dynamics, but it includes consideration of several kinds of dynamics and management response to them. In contrast to previous uses of state-and-transition models, we propose that models can, at present, be most effectively used to specify and qualitatively compare the relative benefits and potential risks of different management actions (e.g., fire and grazing) and other factors (e.g., invasive species and climate change) on specified areas of land. High spatial and temporal variability and complex interactions preclude the meaningful use of general quantitative models. Forecasts can be made on a case-by-case basis by interpreting qualitative and quantitative indicators, historical data, and spatially structured monitoring data based on conceptual models. We illustrate how science- based conceptual models are created using several rangeland examples that vary in complexity. In doing so, we illustrate the implications of designating plant communities and states in models, accounting for varying scales of pattern in vegetation and soils, interpreting the presence of plant communities on different soils and dealing with our uncertainty about how those communities were assembled and how they will change in the future. We conclude with observations about how models have helped to improve management decision-making.     

USING GEOLOGY TO IMPROVE FLOOD HAZARD MANAGEMENT ON ALLUVIAL FANS ‐ AN EXAMPLE FROM LAUGHLIN,NEVADA1

A study of the piedmont of the Newberry Mountains near Laughlin, Nevada, demonstrates that geologic information can improve the scientific basis of flood‐hazard management on alluvial fans in desert areas. Comparison of geologic information against flood insurance rate maps (FIRMs) reveals flaws in conventional methods for flood hazard delineation in this setting. Geologic evidence indicates that large parts of the Newberry piedmont have been isolated from significant flooding for at least the past 10,000 years. This contrasts with existing FIRMs that include large tracts of nonflood prone land in the 100‐year and 500‐year flood hazard zones and exclude areas of indisputably flood prone land from the regulatory flood plain. From the basis of the geology, flood hazards on at least one‐third of the piedmont are mischaracterized on the regulatory maps. The formal incorporation of geologic data into flood hazard studies on desert piedmonts could significantly reduce this type of discrepancy and substantially reduce the scope, hence cost, of more elaborate engineering studies and hazard mitigation strategies. The results of this study affirm the value of new Federal Emergency Management Agency (FEMA) recommendations for characterizing alluvial fan flood hazards and support an argument for mandating geological studies in the regulatory process.     

Spatiotemporal dynamics of spring and stream water chemistry in a high-mountain area

The present study deals with the application of the self-organizing map (SOM) technique in the exploration of spatiotemporal dynamics of spring and stream water samples collected in the Chocho?owski Stream Basin located in the Tatra Mountains (Poland). The SOM-based classification helped to uncover relationships between physical and chemical parameters of water samples and factors determining the quality of water in the studied high-mountain area. In the upper part of the Chocho?owski Stream Basin, located on the top of the crystalline core of the Tatras, concentrations of the majority of ionic substances were the lowest due to limited leaching. Significantly higher concentration of ionic substances was detected in spring and stream samples draining sedimentary rocks. The influence of karst-type springs on the quality of stream water was also demonstrated.     

Nitrogen concentrations in mosses indicate the spatial distribution of atmospheric nitrogen deposition in Europe

In 2005/6, nearly 3000 moss samples from (semi-)natural location across 16 European countries were collected for nitrogen analysis. The lowest total nitrogen concentrations in mosses (<0.8%) were observed in northern Finland and northern UK. The highest concentrations (≥1.6%) were found in parts of Belgium, France, Germany, Slovakia, Slovenia and Bulgaria. The asymptotic relationship between the nitrogen concentrations in mosses and EMEP modelled nitrogen deposition (averaged per 50 km × 50 km grid) across Europe showed less scatter when there were at least five moss sampling sites per grid. Factors potentially contributing to the scatter are discussed. In Switzerland, a strong (r² = 0.91) linear relationship was found between the total nitrogen concentration in mosses and measured site-specific bulk nitrogen deposition rates. The total nitrogen concentrations in mosses complement deposition measurements, helping to identify areas in Europe at risk from high nitrogen deposition at a high spatial resolution.     

Mosses as biomonitors of atmospheric heavy metal deposition: Spatial patterns and temporal trends in Europe

In recent decades, mosses have been used successfully as biomonitors of atmospheric deposition of heavy metals. Since 1990, the European moss survey has been repeated at five-yearly intervals. Although spatial patterns were metal-specific, in 2005 the lowest concentrations of metals in mosses were generally found in Scandinavia, the Baltic States and northern parts of the UK; the highest concentrations were generally found in Belgium and south-eastern Europe. The recent decline in emission and subsequent deposition of heavy metals across Europe has resulted in a decrease in the heavy metal concentration in mosses for the majority of metals. Since 1990, the concentration in mosses has declined the most for arsenic, cadmium, iron, lead and vanadium (52-72%), followed by copper, nickel and zinc (20-30%), with no significant reduction being observed for mercury (12% since 1995) and chromium (2%). However, temporal trends were country-specific with sometimes increases being found.     

NEAR REAL-TIME MAPPING OF THE 1975 MISSISSIPPI RIVER FLOOD IN LOUISIANA USING LANDSAT IMAGERY1

ABSTRACT: The project described in this report was undertaken by the Louisiana State Planning Office to establish the extent of backwater flooding in Louisiana in April 1975. Band 7 Landsat imagery, enlarged to a scale of 1:250,000 was used to visually identify flooded areas. Inundated areas were delineated on overlays keyed to 1:250,000 U.S. Geological Survey topographic quadrangles. Tabular data identifying acres flooded, according to land use type, were derived by merging the flood map overlays with computerized 1972 land use data. Approximately 1.12 million acres of the state were inundated by flood waters. The total acreage and land use types affected by flooding were determined within 72 hours from the time the flood areas were imaged. Flooded maps were prepared for 26 parishes. Field observations were made by Louisiana Cooperative Extension Service county agents in order to determine the accuracy of parish flood maps and flood acreage figures by land use type. Results indicated that this was a fast, accurate, and relatively inexpensive method of compiling flood data for disaster planning and postflood analysis.     

荧光溶解性有机质EEMs的新旧自组织映射图解析方法比较研究

目前,对地表水体荧光溶解性有机质(Fluorescent Dissolved Organic Matter,FDOM)三维激发发射矩阵(Excitation-Emission Matrices,EEMs)数据的解析仍旧存在挑战.本文结合原始EEMs和从中分离的荧光平行因子分析(Parallel Factor Analysis,PARAFAC)组分,利用自组织映射图(Self-Organizing Maps,SOM),开展了基于传统EEMs-SOM和新型PARAFAC-SOM神经网络模型的复杂荧光数据解析能力对比研究,以此探索和改进EEMs多元解析方法技术体系.模型以已发表论文原始数据为基础构建,研究对象为南太湖重要入湖河流东苕溪水系.结果显示:EEMsSOM模型需依赖常规"摘峰法"对各荧光峰做出主观判断,不能有效识别重叠荧光峰,且人为割裂多激发共发射荧光物质峰之间的联系,从而弱化分析结果的实际环境意义,但神经元的模式荧光光谱可视化效果较佳,且操作简便,耗时较少;PARAFAC-SOM模型克服了上述缺陷,可清除EEMs中的噪声或无用信息,大幅降低输入变量数(从1742个降至4个),缩减运算时间,较大地改善了输出结果的准确性,获得无损可靠且实际环境意义较强的结果,但该法的PARAFAC预处理要求较高,工作量较大;两类模型解析结论大体一致,对前期研究进行了全新的阐述和补充,且生动揭示了FDOM在多级河流水体中的空间赋存变化规律及河流的动态污染过程.综上,推荐在今后研究中综合使用两类优势互补的模型以实现对EEMs的深度解析.     

Instream and offstream environmental conditions and stream biotic integrity: Importance of scale and site similarities for learning and prediction

Two different methods to predict biotic integrity were tested and compared in the present paper. The first one tries to predict the fish indices of biotic integrity (IBI) at the state or regional scale based on the most similar observations to a specific target site of interest using the simple to implement k-nearest neighbors (or kNN) method. Two different distance functions were considered to find the k-nearest neighbors: the Euclidean and the Mahalanobis. The second method was applied on the same datasets and consisted of a step-wise multiple regression. The two modeling approaches yielded similar results but kNN proved to be more time-efficient and very fast computationally for the given dataset sizes, which allowed applying a leave-one-out cross validation.In an attempt to reveal the importance of scale in the prediction of IBI, regression models were constructed at the state (or regional) scale and at the more refined cluster of sampling sites scale. Clusters of sites were extracted using Kohonen's self-organizing maps (SOM) followed by k-means clustering of the SOM neurons. Cluster-level regression models, constructed after site patterning, performed better in IBI prediction than global regression models constructed without any previous site patterning. The importance of identifying groups of sites with similar environmental characteristics affecting the IBI was revealed. The combined use of site patterning and regression modeling for IBI prediction also helped identifying important variables acting at the local scale which remain latent at the global scale.     

下扬子区早石炭世佩尔特(Pelto)D函数图和熵图及其研究意义

以下扬子区44个代表性剖面的资料为基础,求导佩尔特提出的D函数和熵函数,编制出早石炭世各时期的沉积厚度趋势图和佩尔特岩相图,研究其沉积特征和古地理,对阐明该区地质发展史和地层控矿条件提供空间分布上的有用信息。