Drought assessment in a south Mediterranean transboundary catchment

ABSTRACT

Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability.     

Strong ground motion record selection for the reliable prediction of the mean seismic collapse capacity of a structure group

How to select a limited number of strong ground motion records (SGMRs) is an important challenge for the seismic collapse capacity assessment of structures. The collapse capacity is considered as the ground motion intensity measure corresponding to the drift‐related dynamic instability in the structural system. The goal of this paper is to select, from a general set of SGMRs, a small number of subsets such that each can be used for the reliable prediction of the mean collapse capacity of a particular group of structures, i.e. of single degree‐of‐freedom systems with a typical behaviour range. In order to achieve this goal, multivariate statistical analysis is first applied, to determine what degree of similarity exists between each selected small subset and the general set of SGMRs. Principal Component analysis is applied to identify the best way to group structures, resulting in a minimum number of SGMRs in a proposed subset. The structures were classified into six groups, and for each group a subset of eight SGMRs has been proposed. The methodology has been validated by analysing a first‐mode‐dominated three‐storey‐reinforced concrete structure by means of the proposed subsets, as well as the general set of SGMRs. The results of this analysis show that the mean seismic collapse capacity can be predicted by the proposed subsets with less dispersion than by the recently developed improved approach, which is based on scaling the response spectra of the records to match the conditional mean spectrum. Copyright © 2010 John Wiley & Sons, Ltd.     

MULTIVARIATE GEOMORPHIC ANALYSIS OF FOREST STREAMS: IMPLICATIONS FOR ASSESSMENT OF LAND USE IMPACTS ON CHANNEL CONDITION

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10 disturbed from 13 undisturbed reaches with 90 per cent and 92 per cent correct classification respectively. These variables are the total number of pools per reach, the ratio of mean residual pool depth to mean bankfull depth, and the ratio of critical shear stress of the median surface grain size to bankfull shear stress. The last variable can be dropped without a decrease in rate of correct classification; however, the resulting two-variable model may be less robust. Analysis of the distribution of channel units, including pool types, can also be used to discriminate disturbed from undisturbed reaches and is particularly useful for assessment of aquatic habitat condition. However, channel unit classification and inventory can be subject to considerable error and observer bias. Abundance of pool-related large woody debris is highly correlated with pool frequency and is an important factor determining channel morphology. Results of this study yield a much needed, objective, geomorphic discrimination of pristine and disturbed channel conditions, providing a reference standard for channel assessment and restoration efforts.     

通过对调查数据的趋势和多变量分析确定宏观场

通过多变(相关分析)和趋势分析等统计方法对宏观调查数据进行了解释.这种方法使我们通过评定不同宏观效应叠加的程度、估计调查数据的不确定性更客观地评定烈度.通过滤波确定烈度场的区域分量,使我们消除观测中的局部变化.给出了选取适当滤波参数的准则.本文应用这一方法对发生在意大利的一次地震的调查数据进行了处理.     

上海市商务办公楼租金差异及其影响因素

上海房地产市场在国家房产新政下出现了较大的转折,商务办公楼市场升温。本文从总体上分析了上海部分区域商务办公楼的平均租金差异,并选择商务办公楼比较集中的南京路、延安路和淮海路三条线路作为典型调查区段,共采集24个样本区域、66幢甲级商务办公楼、492个具体样本资料,运用多元线性回归分析方法,揭示了上海市商务办公楼租金差异与地理区位、服务设施、交通条件、平均层数、平均停车位及绿化景观6个影响因子的相互作用关系。回归分析结果表明:服务设施和停车位是影响上海市商务办公楼租金差异的主要因子;其次为绿化景观、地理区位和交通条件;而平均层数的影响甚微。最后针对上海商务办公楼多中心化趋势,就有关问题进行了分析和讨论。     

A classification of drainage and macropore flow in an agricultural catchment

This paper uses a variety of multivariate statistical techniques in order to improve current understanding of the antecedent and rainfall controls on drainage characteristics for an agricultural underdrained clay site. Using the dataset obtained from a two‐year hillslope study at Wytham (Oxfordshire, UK) a number of patterns in the nature and style of drainage events were explored. First, using principal components analysis, a distinction was drawn between drainflow controlled by antecedent conditions and drainflow controlled by rainfall characteristics. Dimensional analysis then distinguished between two further types of drainflow event: antecedent limited events (ALE) and non‐antecedent limited events (NALE). These were drainflow events requiring a minimum antecedent hydraulic head to occur (ALE) and events that occurred in response to rainfall irrespective of the antecedent conditions, because the rainfall was either of high enough intensity or duration to prompt a response in drainflow (NALE). 2. The dataset also made possible a preliminary investigation into the controls on and types of macropore flow at the site. Principal components analysis identified that rainfall characteristics were more important than antecedent conditions in generating high proportions of macropore flow in drainflow. Of the rainfall characteristics studied, rainfall amount and intensity were the dominant controls on the amount of macropore flow, with duration as a secondary control. Two styles of macropore flow were identified: intensity‐driven and duration‐driven. Intensity‐driven events are characterized by rainfall of high intensity and short duration. During such events the amount of macropore flow is proportional to the rainfall intensity and the interaction between macropore and matrix flow is kinetically limited. The second style of macropore flow is characterized by long‐duration events. For these events the amount of macropore flow approaches a maximum value whatever the rainfall duration. This suggests that these events are characterized by an equilibrium interaction between macropores and matrix flow. Copyright © 2002 John Wiley & Sons, Ltd.     

Calibration of diatoms along a nutrient gradient in Florida Everglades Water Conservation Area-2A, USA

The relationship between diatom taxa preserved in surface soils and environmental variables at 31 sites in Water Conservation Area 2A (WCA-2A) of the Florida Everglades was explored using multivariate analyses. Surface soils were collected along a phosphorus (P) gradient and analyzed for diatoms, total P, % nitrogen (N), %carbon (C), calcium (Ca), and biogenic silica (BSi). Phosphorus varied from 315-1781 g g^-1, and was not found to be correlated with the other geochemical variables. Canonical correspondence analysis (CCA) was used to examine which environmental variables correlated most closely with the distributions in diatom taxa. Canonical correspondence analysis with forward selection, constrained and partial CCA, and Monte Carlo permutation tests of significance show the most significant changes in diatom assemblages along the P gradient (p < 0.01), with additional species differences correlated with soil C, N, Ca, and BSi.Weighted-averaging (WA) regression and calibration models of diatom assemblages to P and BSi were developed. The diatom-based inference model for soil [P] had a high apparent r² (0.86) with RMSE_boot = 218 g g^-1. Indicator diatom species identified by assessing species WA optima and WA tolerance to [P], such as Nitzschia amphibia and N. palea for high [P] (~1300-1400 g^-1) and Achnanthes minutissima var. scotica and Mastogloia smithii for low [P] (~400-600 g g^-1), may be useful as monitoring tools for eutrophication in WCA-2A as well as other areas of the Everglades. Diatom assemblages analyzed by cluster analysis were related to location within WCA-2A, and dominant taxa within clusters are discussed in relation to the geochemical variables measured as well as hydrology and pH. Diversity of diatom assemblages and a Disturbance Index based on diatom data are discussed in relation to the historically P-limited Everglades ecosystem. Diatom assemblages should be very useful for reconstructions of [P] through time in the Florida Everglades, provided diatoms are well preserved in soil cores.     

Detecting subtle hydrochemical anomalies with multivariate statistics: an example from ‘homogeneous’ groundwaters in the Great Artesian Basin,Australia

The major ion composition of Great Artesian Basin groundwater in the lower Namoi River valley is relatively homogeneous in chemical composition. Traditional graphical techniques have been combined with multivariate statistical methods to determine whether subtle differences in the chemical composition of these waters can be delineated. Hierarchical cluster analysis and principal components analysis were successful in delineating minor variations within the groundwaters of the study area that were not visually identified in the graphical techniques applied. Hydrochemical interpretation allowed geochemical processes to be identified in each statistically defined water type and illustrated how these groundwaters differ from one another. Three main geochemical processes were identified in the groundwaters: ion exchange, precipitation, and mixing between waters from different sources. Both statistical methods delineated an anomalous sample suspected of being influenced by magmatic CO₂ input. The use of statistical methods to complement traditional graphical techniques for waters appearing homogeneous is emphasized for all investigations of this type. Copyright © 2006 John Wiley & Sons, Ltd.     

Mixture models and atypical values

The resolution of a mixture of two or more populations into its component distributions may be markedly influenced by one or a few atypical values. The maximum likelihood solution effectively assigns (part of) each observation to one or another of the components via the posterior probabilities, even though the observation may be widely discrepant from all components. This paper presents a modification of the mixture problem, in which the typicality of each observation is considered, as well as the posterior probabilities, with the contribution of atypical observations being downweighted. The extension to the multivariate case is discussed.