MODIFIED SMEMAX TRANSFORMATION FOR FREQUENCY ANALYSIS1

ABSTRACT: SMEMAX is a transformation technique suggested by Bethalmy to transform random hydrological series to a near normal series. This paper puts forward an alternative simpler form of the SMEMAX transformation. The modified SMEMAX transformation avoids use of trigonometric functions and the transformed variables range from 0 to 100.     

GENERALIZED SKEW COEFFICIENTS OF ANNUAL FLOODS FOR LOUISIANA STREAMS1

ABSTRACT: A generalized skew map for Louisiana streams was developed using data from Louisiana, Mississippi, Arkansas, and Texas with 20 or more years of annual flood records. A comparison between the newly developed Louisiana Generalized Skew Map (LGSM) and the generalized skew map recommended by the U.S. Water Resources Council (WRCGSM) was performed. The mean square error for the LGSM was 16 percent less than that of WRCGSM in direct application of the two maps. Performance of the new map was compared with the WRCGSM and with a regional analysis procedure through its application to the Log Pearson Type 3 (LP3) distribution. Two-thirds of the stations tested had lower standardized root mean square deviations (SRMSD) by a narrow margin using the skew coefficients obtained from LGSM instead of WRCGSM. The regional analysis also performed as well as the LGSM in terms of SRMSD. Thus, it was concluded that both LGSM and the regional analysis provide a more reliable tool for flood frequency analysis for Louisiana streams with short annual flood records.     

Application of Index Procedures to Flood Frequency Analysis in Turkey1

Abstract: This study investigates the regional analysis of annual maximum flood series of 48 stream gauging stations in the basins of the West Mediterranean Region in Turkey. The region is divided into three homogeneous subregions according to both Student‐t test and Dalrymple homogeneity test. The regional relationships of mean annual flood per unit area‐drainage area and coefficient of skew‐coefficient of variation are obtained. Two statistically meaningful relationships of the mean flood per unit area‐drainage area and a unique relationship between skewness and variation coefficients exist. Results show that the index‐flood method may be applicable to each homogenous subregion to estimate flood quantiles in the study area.     

PREDICTION OF PEAK FLOWS ON SMALL WATERSHEDS IN OREGON FOR USE IN CULVERT DESIGN1

ABSTRACT: Using data from 80 Oregon watersheds that ranged in size from 0.54 km² to 27.45 km², equations were developed to predict peak flows for use in culvert design on forest roads. Oregon was divided into six physiographic regions based on previous studies of flood frequency. In each region, data on annual peak flow from gaging stations with more than 20 years of record were analyzed using four flood frequency distributions: type 1 extremal, two parameter-log normal, three parameter-log normal, and log-Pearson type III. The log-Pearson type III distribution was found to be suitable for use in all regions of the State, based on the chi-square goodness-of-fit-test. Flood magnitudes having recurrence intervals of 10, 25, 50, and 100 years were related to physical and climatic characteristics of drainage basins by multiple regression. Drainage basin size was the most important variable in explaining the variation of flood peaks in all regions. Mean basin elevation and mean annual precipitation were also significantly related to flood peaks in two regions of western Oregon. The standard error of the estimate for the regression relationships ranged from 26 to 84 percent.     

基于信息量的ALI影像最佳波段选择及融合研究

分析了EO-1 ALI多光谱遥感影像各个波段的信息特征,根据信息量大小和波段间的相关性,联合偏度—峰度指数JSKF,提出针对ALI图像新的最佳波段组合方法。在最佳波段组合下对ALI多光谱数据与全色数据分别进行IHS、HPF、PCA和Wavelet变换融合,从信息量角度出发,按照定量指标对融合前后的遥感影像进行评价,并对融合前后影像进行分类应用。     

Using rank-order geostatistics for spatial interpolation of highly skewed data in a heavy-metal contaminated site

The spatial distribution of a pollutant in contaminated soils is usually highly skewed. As a result, the sample variogram often differs considerably from its regional counterpart and the geostatistical interpolation is hindered. In this study, rank-order geostatistics with standardized rank transformation was used for the spatial interpolation of pollutants with a highly skewed distribution in contaminated soils when commonly used nonlinear methods, such as logarithmic and normal-scored transformations, are not suitable. A real data set of soil Cd concentrations with great variation and high skewness in a contaminated site of Taiwan was used for illustration. The spatial dependence of ranks transformed from Cd concentrations was identified and kriging estimation was readily performed in the standardized-rank space. The estimated standardized rank was back-transformed into the concentration space using the middle point model within a standardized-rank interval of the empirical distribution function (EDF). The spatial distribution of Cd concentrations was then obtained. The probability of Cd concentration being higher than a given cutoff value also can be estimated by using the estimated distribution of standardized ranks. The contour maps of Cd concentrations and the probabilities of Cd concentrations being higher than the cutoff value can be simultaneously used for delineation of hazardous areas of contaminated soils.     

CONFIDENCE INTERVALS FOR FLOOD EVENTS UNDER A PEARSON 3 OR LOG PEARSON 3 DISTRIBUTION1

ABSTRACT: The Pearson type 3 (P3) and log Pearson type 3 (LP3) distributions are very frequently used in flood frequency analysis. Existing methods for constructing confidence intervals for quantiles (X_p) of these two distributions are very crude. Most of these methods are based on the idea of adjusting confidence intervals for quantiles Y_p of the normal distribution to obtain approximate confidence inervals for quantiles X_p of the P3/LP3 distribution. Since there is no theoretical reason why this “base” distribution, Y, should be taken to be normal, we search in the present study for the best possible base distribution for producing confidence intervals for P3/LP3 quantiles. We consider a group of base distributions such as the normal, log normal, Weibull, Gumbel, and exponential. We first assume that the skew coefficient, γ of X, to be known, and develop a method for adjusting confidence intervals for Y_p to produce approximate confidence intervals for X_p. We then compare this method (Method A) with another method (Method B) introduced by Stedinger. Simulation shows that the performance of each of these two methods depends on the base distribution Y that is being used, but as a whole, the normal distribution appears to be the best-fit distribution for producing confidence intervals for P3/LP3 quantiles when γ is assumed to be known. We then extend our method (Method A) to the more important case of unknown coefficient of skewness. It is shown that by taking Y to be Weibull, fairly accurate confidence intervals for P3/LP3 quantiles can be obtained for quite a wide range of sample sizes and coefficients of skewness commonly found in hydrology. The case of the P3 distribution with negative skewness needs further research.     

Comparison of Stormwater Lag Times for Low Impact and Traditional Residential Development1

Abstract: This study compared lag time characteristics of low impact residential development with traditional residential development. Also compared were runoff volume, peak discharge, hydrograph kurtosis, runoff coefficient, and runoff threshold. Low impact development (LID) had a significantly greater centroid lag‐to‐peak, centroid lag, lag‐to‐peak, and peak lag‐to‐peak times than traditional development. Traditional development had a significantly greater depth of discharge and runoff coefficient than LID. The peak discharge in runoff from the traditional development was 1,100% greater than from the LID. The runoff threshold of the LID (6.0 mm) was 100% greater than the traditional development (3.0 mm). The hydrograph shape for the LID watershed had a negative value of kurtosis indicating a leptokurtic distribution, while traditional development had a positive value of kurtosis indicating a platykurtic distribution. The lag times of the LID were significantly greater than the traditional watershed for small (<25.4 mm) but not large (≥25.4 mm) storms; short duration (<4 h) but not long duration (≥4 h) storms; and low antecedent moisture condition (AMC; <25.4 mm) storms but not high AMC (≥25.4 mm) storms. This study indicates that LID resulted in lowered peak discharge depth, runoff coefficient, and discharge volume and increased lag times and runoff threshold compared with traditional residential development.     

四川简阳东溪镇土壤环境六种元素含量评价

本文用随机布点法，采集了简阳东溪镇土壤样品29个，分析了土壤中Cd、Zn、Ni、Cu、Mn、Pb六种元素含量，用Shapiro-Wilk法和偏态系数检验了土壤中的元素含量分布类型，结果六种元素含量均为正态分布。根据元素含量类型分布，统计简阳东溪镇土壤中六种元素平均含量为：Cd0．295ppm、Zn62．5ppm、Ni27．49ppm、Cu23．25ppm、bin157．25ppm、Pb17．47ppm。     

基于Voronoi图的居民点空间分布特征研究——以甘肃省为例

采用GIS查询统计与Voronoi图CV值相结合的分析方法,通过计算点状目标的Voronoi多边形面积的变异系数(CV值)方法来分析点状目标的空间分布特征。分析结果表明,甘肃省有9个市、县为随机分布,其余市、县为集群分布,但总体上为集群分布。最近邻指数和CV值通过级差变换后,发现其存在相关性,相关系数为负值,表明两者之间存在负相关关系。     

GENERATED MONTHLY STREAMFLOWS FOR THE MIDWESTERN AND SOUTHWESTERN UNITED STATES1

ABSTRACT A critical examination of single gage site, monthly streamflow statistical characteristics for two southern Illinois rivers, an Oklahoma river and a Texas river was made using a digital computer at Northwestern University. High flow variability for the rivers was evident in that, for the rivers tested, 8 to 11 months had coefficients of variation in excess of unity. The gamma distribution was not as efficient as the normal distribution for fitting power or logarithmic transforms of the historical monthly flow data (i.e., F^1-0, F^0-5, F^0-25, Fa¹²⁵, F^0.085, and log F). No single transform to a normal distribution was adequate for all twelve monthly flows, since definite seasonal grouping patterns were found for the four rivers examined. The highly variable flow in the low-flow season(s) indicated much more skewness than was typical of the remainder of the year. For the low-flow seasons, the higher-root (smaller exponent) transforms were particularly useful. Flows were generated from a linear regression model of lag one utilizing two or more transforms for the twelve periods. The definite seasonal patterns found historically were reproduced quite well in the generated streamflows. The effect of a change in data transform from one season to the next was insignificant after one month. Thus the use of different transforms within the year did not bias the results from the linear regression model appreciably, but did help in reproducing the seasonal distribution pattern. The technique seems especially well suited for rivers with highly variable flows.     

NON-ZERO LOWER LIMIT IN LOW FLOW FREQUENCY ANALYSIS?1

ABSTRACT: The implications of fitting distributions with non-zero lower limits to low flow data are examined. The 3-parameter Weibull distribution is fitted to annual minimum flow series from 60 long term stations in Canada. The relations between the estimated lower limit and three sampling variables (skewness, smallest, and largest observations) were investigated. The lower limit strongly depends on the sample skewness; it varies directly with the sample skewness, which in turn is highly influenced by the largest observation. For a given skewness, the value of the estimated lower limit is determined by the value of the smallest observation. Therefore, the lower limit cannot be accurately determined, and the resulting low flow estimates will be either too small or too high.     

A NEW LOOK AT FLOOD RISK DETERMINATION1

ABSTRACT: The probability distributions of annual peak flows used in flood risk analysis quantify the risk that a design flood will be exceeded. But the parameters of these distributions are themselves to a degree uncertain and this uncertainty increases the risk that the flood protection provided will in fact prove to be inadequate. The increase in flood risk due to parameter uncertainty is small when a fairly long record of data is available and the annual flood peaks are serially independent, which is the standard assumption in flood frequency analysis. But standard tests for serial independence are insensitive to the type of grouping of high and low values in a time series, which is measured by the Hurst coefficient. This grouping increases the parameter uncertainty considerably. A study of 49 annual peak flow series for Canadian rivers shows that many have a high Hurst coefficient. The corresponding increase in flood risk due to parameter uncertainty is shown to be substantial even for rivers with a long record, and therefore should not be neglected. The paper presents a method of rationally combining parameter uncertainty due to serial correlation, and the stochastic variability of peak flows in a single risk assessment. In addition, a relatively simple time series model that is capable of reproducing the observed serial correlation of flood peaks is presented.     

基于三维灰色关联度方法的大型煤炭企业转型能力评价研究

在中国转变经济发展方式的背景下,结合大型煤炭企业的转型任务与目标,对其转型能力结构进行分析,构建了主客观指标相结合的转型能力评价指标体系.采用三维灰色关联度方法,基于21家上市煤炭企业面板数据进行评价,发现大型煤炭企业转型能力不断提高,但整体水平欠佳,尤其是转型战略规划能力亟需提高,因此必须加强高管团队建设与学习,根据转型战略积极进行包括人才资源在内的资源储备,大力进行技术创新与管理创新.     

REGIONAL FLOOD EQUATIONS FOR THE PROVINCES OF ONTARIO AND QUEBEC1

ABSTRACT: When nonparametric frequency analysis was performed on 183 stations from Ontario and Quebec, unimodal and multimodal maximum annual flood density functions were discovered. In order to determine generating mechanisms, a monthly partitioning of the annual maximum floods was undertaken. The timing of the floods revealed that the unimodal distributions reflected a single flood generating mechanism while the multi-modal densities reflected two or more mechanisms. Based on the division of the flood series by mechanisms, nine homogeneous regions were delineated. L-moment distributional homogeneity tests along with smaller standard errors for the regional equations supported the delineation.     

ESTIMATING PARAMETERS OF EV1 DISTRIBUTION FOR FLOOD FREQUENCY ANALYSIS1

ABSTRACT: The parameters of the extreme value type 1 distribution were estimated for 55 annual flood data sets by seven methods. These are the methods of (1) moments, (2) probability weighted moments, (3) mixed moments, (4) maximum likelihood estimation, (5) incomplete means, (6) principle of maximum entropy, and (7) least squares. The method of maximum likelihood estimation was found to be the best and the method of incomplete means the worst. The differences between the methods of principle of maximum entropy, probability weighted moments, moments, and least squares were only minor. The difference between these methods and the method of maximum likelihood was not pronounced.     

GENERATION OF DAILY PRECIPITATION OVER AN AREA1

ABSTRACT: A model was developed of the periodic-stochastic structure of daily precipitation over an area. The model is based ona multivariate normal distribution. The square roots of daily precipitation at a point were found to approximate a sample from a univariate normal distribution that had been truncated at zero. The zero daily precipitation amounts were considered negative amounts of unknown quantity. The multivariate normal distribution was used to describe the variation of daily precipitation over an area. The periodic fluctuations of the model parameters were described with Fourier series. The model was tested using data from two areas of different precipitation characteristics. Data generated with the model contained many of the statistical characteristics observed in the historical data.     

Flooding in Texas: Examination of Temporal Changes and Impacts of Tropical Cyclones

Annual maximum peak discharge measurements from 62 stations with a record of at least 70 years are used to assess extreme flooding in Texas at the regional scale. This work focuses on examination of the validity of the stationarity assumption and on the impact of tropical cyclones (TCs) on the upper tail of the flood peak distribution. We assess the validity of the stationarity assumption by testing the records for abrupt and gradual changes. The presence of abrupt changes in the first two moments of the flood peak distribution is assessed using the Lombard test. We use the Mann‐Kendall test to examine the presence of monotonic trends. Results indicate that violations of the stationarity assumption are most commonly caused by abrupt changes, which are often associated with river regulation. We fit the time series of stationary flood records with the generalized extreme value distribution to investigate whether TCs control the upper tail of the flood peak distribution. Our results indicate that TCs play a diminished role in shaping the upper tail of the flood peak distribution compared with areas of the eastern United States subject to frequent TCs.