利用可见光/近红外反射光谱估算土壤总氮含量的实验研究

利用土壤的室内反射率光谱，探讨土壤氮元素的高光谱机理。利用土壤光谱各吸收带的特征参数与总氮含量进行逐步回归运算，确定与氮元素关系比较密切的几个吸收带。计算出这几个特征吸收带内土壤反射率的变化形式：一阶导数(FDR)、倒数(1/R)、倒数之对数(log(1/R))、波段深度(Depth)，并与总氮含量进行逐步回归分析，得到比较理想的结果：建模样本的Ra^2(修正的判定系数)分别为0．789、0．753、0．736、0．699，验证样本的Ra^2分别为0．759、0．468、0．794、0．725。可见土壤的反射率光谱与氮元素含量之间存在比较明显的相关性，可见光／近红外反射光谱具有快速估算土壤中氮元素含量的潜力。     

空间分析与自然地理综合研究

通过对空间分析技术和自然地理综合研究发展历程与趋势的分析，得出两个结论：1)现代地理学的快速发展越来越离不开空间分析的支撑，即空间分析技术在地理学中的应用空间愈来愈广，在自然地理综合研究中尤为如此，其主要原因就是空间分析在综合研究中的优势愈来愈明显；2)空间分析技术随其理论与实践的迅速发展及逐步拓展，愈来愈成为自然地理学发展的巨大推动力，也越来越离不开自然地理综合研究这个促使其发展壮大的空间和能发挥其主导作用的领域。空间分析技术和自然地理综合研究的结合已经成为现代自然地理学以及地球空间信息学研究的主要发展趋势之一。     

1952~2003年我国区域经济发展不均衡的 长期变化态势

文中分别利用Gini、GE等指数，以实际人均国内生产总值(GDP)为指标，详细考查了从1952~2003年，我国省市区间经济发展不均衡的变化态势及其在东部-内陆、南方-北方、高城镇化-低城镇化地区等方向上的变化。人均实际GDP的Gini、GE等指数显示，从1952~2003年，我国省级区域经济发展不均衡的总体态势是以较缓慢的速度逐步增加。具体的变化是，随着时间的推移区域经济不均衡呈周期性地上升、下降运动。就我国省市区经济发展不均衡在空间上的变化而言，一是在沿海-内陆和高城镇化-低城镇化方向上，分别在1990s中期和1980s中期以前，我国省市区经济不均衡主要表现为区域内部不均衡，但区域之间不均衡则不断增加，并逐步成为省市区经济不均衡主要部分；一是，在北方-南方方向上，我国省市区经济不均衡则是一直表现为区域内部不均衡，区域之间不均衡对省市区经济不均衡的贡献一直显得微不足道。     

Statistical identification of orographic effects in the regional analysis of extreme rainfall

Regional models of extreme rainfall must address the spatial variability induced by orographic obstacles. However, the proper detection of orographic effects often depends on the availability of a well‐designed rain gauge network. The aim of this study is to investigate a new method for identifying and characterizing the effects of orography on the spatial structure of extreme rainfall at the regional scale, including where rainfall data are lacking or fail to describe rainfall features thoroughly. We analyse the annual maxima of daily rainfall data in the Campania region, an orographically complex region in Southern Italy, and introduce a statistical procedure to identify spatial outliers in a low order statistic (namely the mean). The locations of these outliers are then compared with a pattern of orographic objects that has been a priori identified through the application of an automatic geomorphological procedure. The results show a direct and clear link between a particular set of orographic objects and a local increase in the spatial variability of extreme rainfall. This analysis allowed us to objectively identify areas where orography produces enhanced variability in extreme rainfall. It has direct implications for rain gauge network design criteria and has led to promising developments in the regional analysis of extreme rainfall. Copyright © 2015 John Wiley & Sons, Ltd.     

Discrete element method modeling of inherently anisotropic rocks under uniaxial compression loading

A new numerical approach is proposed in this study to model the mechanical behaviors of inherently anisotropic rocks in which the rock matrix is represented as bonded particle model, and the intrinsic anisotropy is imposed by replacing any parallel bonds dipping within a certain angle range with smooth‐joint contacts. A series of numerical models with β = 0°, 15°, 30°, 45°, 60°, 75°, and 90° are constructed and tested (β is defined as the angle between the normal of weak layers and the maximum principal stress direction). The effect of smooth‐joint parameters on the uniaxial compression strength and Young's modulus is investigated systematically. The simulation results reveal that the normal strength of smooth‐joint mainly affects the behaviors at high anisotropy angles (β > 45°), while the shear strength plays an important role at medium anisotropy angles (30°–75°). The normal stiffness controls the mechanical behaviors at low anisotropy angles. The angle range of parallel bonds being replaced plays an important role on defining the degree of anisotropy. Step‐by‐step procedures for the calibration of micro parameters are recommended. The numerical model is calibrated to reproduce the behaviors of different anisotropic rocks. Detailed analyses are conducted to investigate the brittle failure process by looking at stress‐strain behaviors, increment of micro cracks, initiation and propagation of fractures. Most of these responses agree well with previous experimental findings and can provide new insights into the micro mechanisms related to the anisotropic deformation and failure behaviors. The numerical approach is then applied to simulate the stress‐induced borehole breakouts in anisotropic rock formations at reduced scale. The effect of rock anisotropy and stress anisotropy can be captured. Copyright © 2015 John Wiley & Sons, Ltd.     

The use of the exponent K(q) function to delimit homogeneous regions in regional frequency analysis of extreme annual daily rainfall

The regional frequency analysis of extreme annual rainfall data is a useful methodology in hydrology to obtain certain quantile values when no long data series are available. The most crucial step in the analysis is the grouping of sites into homogeneous regions. This work presents a new grouping criterion based on some multifractal properties of rainfall data. For this purpose, a regional frequency analysis of extreme annual rainfall data from the Maule Region (Chile) has been performed. Daily rainfall data series of 53 available stations have been studied, and their empirical moments scaling exponent functions K(q) have been obtained. Two characteristics parameters of the K(q) functions (γ_max and K(0)) have been used to group the stations into three homogeneous regions. Only five sites have not been possible to include into any homogenous regions, being the local frequency analysis of extreme daily rainfall the most appropriate method to be used at these locations. Copyright © 2014 John Wiley & Sons, Ltd.     

Validating the ability of the discontinuous deformation analysis method to model normal P‐wave propagation across rock fractures

The effects of fractures on wave propagation problems are increasingly abstracting the attention of scholars and engineers in rock engineering field. This study aims to fully validate the ability of discontinuous deformation analysis (DDA) to model normal P‐wave propagation across rock fractures. The effects of a single fracture and multiple parallel fractures are all tested. The results indicate that DDA can accurately reflect the fracture effects, including the fractures stiffness, the fracture spacing and the fracture number, and the effects of incident wave frequency on one‐dimensional P‐wave propagation problems. Thus, DDA is able to deal well with normal incident P‐wave propagation problems. Copyright © 2017 John Wiley & Sons, Ltd.     

Characterizing rainfall–groundwater dynamics in a hard‐rock aquifer system using time series,geographic information system and geostatistical modelling

The aim of this study was to investigate rainfall–groundwater dynamics over space and annual time scales in a hard‐rock aquifer system of India by employing time series, geographic information system and geostatistical modelling techniques. Trends in 43‐year (1965–2007) annual rainfall time series of ten rainfall stations and 16‐year (1991–2006) pre‐monsoon and post‐monsoon groundwater levels of 140 sites were identified by using Mann–Kendall, Spearman rank order correlation and Kendall rank correlation tests. Trends were quantified by Kendall slope method. Furthermore, the study involves novelty of examining homogeneity of pre‐monsoon and post‐monsoon groundwater levels, for the first time, by applying seven tests. Regression analysis between rainfall and post‐monsoon groundwater levels was performed. The pre‐monsoon and post‐monsoon groundwater levels for four periods – 1991–1994, 1995–1998, 1999–2002 and 2003–2006 – were subjected to geographic information system‐based geostatistical modelling. The rainfall showed considerable spatiotemporal variations, with a declining trend at the Mavli rainfall station (p‐value < 0.05). The Levene's tests revealed spatial homogeneity of rainfall at α = 0.05. Regression analyses indicated significant relationships (r² > 0.5) between groundwater level and rainfall for eight rainfall stations. Non‐homogeneity and declining trends in the groundwater level, attributed to anthropogenic and hydrologic factors, were found at 5–61 more sites in pre‐monsoon compared with post‐monsoon season. The groundwater declining rates in phyllite–schist, gneiss, schist and granite formations were found to be 0.18, 0.26, 0.21 and 0.14 m year^?1 and 0.13, 0.19, 0.16 and 0.02 m year^?1 during the pre‐monsoon and post‐monsoon seasons, respectively. The geostatistical analyses for four time periods revealed linkages between the rainfall and groundwater levels. Copyright © 2013 John Wiley & Sons, Ltd.     

Characterizing and classifying urban watersheds with compositional and structural attributes

Current land-use classifications used to assess urbanization effects on stream water quality date back to the 1980s when limited information was available to characterize watershed attributes that mediate non-point source pollution. With high resolution remote sensing and widely used GIS tools, there has been a vast increase in the availability and precision of geospatial data of built environments. In this study, we leverage geospatial data to expand the characterization of developed landscapes and create a typology that allows us to better understand the impact of complex developed landscapes across the rural to urban gradient. We assess the ability of the developed landscape typology to reveal patterns in stream water chemistry previously undetected by traditional land-cover based classification. We examine the distribution of land-cover, infrastructure, topography and geology across 3876 National Hydrography Dataset Plus catchments in the Piedmont region of North Carolina, USA. From this dataset, we generate metrics to evaluate the abundance, density and position of landscape features relative to streams, catchment outlets and topographic wetness metrics. While impervious surfaces are a key distinguishing feature of the urban landscape, sanitary infrastructure, population density and geology are better predictors of baseflow stream water chemistry. Unsupervised clustering was used to generate a distinct developed landscape typology based on the expanded, high-resolution landscape feature information. Using stream chemistry data from 37 developed headwater catchments, we compared the baseflow water chemistry grouped by traditional land-cover based classes of urbanization (rural, low, medium and high density) to our composition and structure-based classification (a nine-class typology). The typology based on 22 metrics of developed landscape composition and structure explained over 50% of the variation in NO₃⁻-N, TDN, DOC, Cl⁻, and Br⁻ concentration, while the ISC-based classification only significantly explained 23% of the variation in TDN. These results demonstrate the importance of infrastructure, population and geology in defining developed landscapes and improving discrete classes for water management.     

Spatiotemporal estimation of snow depth using point data from snow stakes,digital terrain models,and satellite data

Snow availability in Alpine catchments plays an important role in water resources management. In this paper, we propose a method for an optimal estimation of snow depth (areal extension and thickness) in Alpine systems from point data and satellite observations by using significant explanatory variables deduced from a digital terrain model. It is intended to be a parsimonious approach that may complement physical‐based methodologies. Different techniques (multiple regression, multicriteria analysis, and kriging) are integrated to address the following issues: We identify the explanatory variables that could be helpful on the basis of a critical review of the scientific literature. We study the relationship between ground observations and explanatory variables using a systematic procedure for a complete multiple regression analysis. Multiple regression models are calibrated combining all suggested model structures and explanatory variables. We also propose an evaluation of the models (using indices to analyze the goodness of fit) and select the best approaches (models and variables) on the basis of multicriteria analysis. Estimation of the snow depth is performed with the selected regression models. The residual estimation is improved by applying kriging in cases with spatial correlation. The final estimate is obtained by combining regression and kriging results, and constraining the snow domain in accordance with satellite data. The method is illustrated using the case study of the Sierra Nevada mountain range (Southern Spain). A cross‐validation experiment has confirmed the efficiency of the proposed procedure. Finally, although it is not the scope of this work, the snow depth is used to asses a first estimation of snow water equivalent resources.