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.     

DEM格网尺度对AnnAGNPS预测山地小流域径流和物质输出的影响

为了解流域地形空间参数和其它参数的精度对农业非点源污染模型AnnAGNPS预测准确性的影响,利用三峡库区黑河小流域观测资料校准了AnnAGNPS模型,分析了1.5-12.5m格网尺度DEM对地形参数和模型负载输出的影响.结果表明,1.5～12.5m格网尺度DEM对流域径流量、洪峰流量、总N输出影响不显著,但对泥沙、总P、有机碳输出影响显著.三峡库区类似小流域宜采用5m格网尺度DEM,AnnAGNPS模型较不适合于尺度较小、坡度较大的小流域泥沙负载预测.     

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.     

工业噪声对脑认知影响的功率谱估计分析

为明确工业噪声对大脑认知的负面影响,采集火电厂球磨机的工业噪声,征集10名在校大学生在90 dB(A)的稳态工业噪声状态下及安静状态下的32导联脑电图(EEC).采用傅里叶变换方法进行频域分析,提取δ频段、θ频段、α1频段、α2频段和β频段功率谱,并进行统计分析.结果 表明:噪声环境与静音环境相比较,被试在δ频段、θ频...     

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.     

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.     

Spatial Variability of Soil Organic Carbon in Relation to Environmental Factors of a Typical Small Watershed in the Black Soil Region, Northeast China

A total of 292 soil samples were taken from surface soil (0–20 cm) of a typical small watershed–Tongshuang in the black soil region of Heilongjiang province, northeast China in June 2005 for examining the concentration of soil organic carbon (SOC). Spatial variability of SOC in relation to topography and land use was evaluated using classical statistics, geostatistics and geographic information system (GIS) analyses. The objective of this study was to provide a scientific basis for land management targeting at improving soil quality in this region. Classical statistical analysis results indicated that the variability of SOC was moderate (C _V = 0.30). Slope position and land use types were discriminating factors for its spatial variability. Geostatistics analyses showed that SOC had a strong spatial autocorrelation, which was mainly induced by structural factors. Mean concentration of SOC in surface soil was 2.27% in this watershed, which was a very low level in the northern black soil region of northeast China. In this small watershed, present soil and water conservation measures played an important role in controlling soil loss. But SOC's restoration was unsatisfactory. Nearly three-quarters of the area had worrisome productivity. How to improve SOC concentration targeting at soil fertility is a pressing need in the future.     

RUNOFF MODELING OF A MOUNTAINOUS CATCHMENT USING TOPMODEL: A CASE STUDY1

ABSTRACT: The rainfall‐runoff response of the Tygarts Creek Catchment in eastern Kentucky is studied using TOPMODEL, a hydrologic model that simulates runoff at the catchment outlet based on the concepts of saturation excess overland flow and subsurface flow. Unlike the traditional application of this model to continuous rainfall‐runoff data, the use of TOPMOEL in single event runoff modeling, specifically floods, is explored here. TOPMODEL utilizes a topographic index as an indicator of the likely spatial distribution of rainfall excess generation in the catchment. The topographic index values within the catchment are determined using the digital terrain analysis procedures in conjunction with digital elevation model (DEM) data. Select parameters in TOPMODEL are calibrated using an iterative procedure to obtain the best‐fit runoff hydrograph. The calibrated parameters are the surface transmissivity, T_O, the transmissivity decay parameter, m, and the initial moisture deficit in the root zone, S_r0. These parameters are calibrated using three storm events and verified using three additional storm events. Overall, the calibration results obtained in this study are in general agreement with the results documented from previous studies using TOPMODEL. However, the parameter values did not perform well during the verification phase of this study.