Diffraction of multidirectional random waves by multiple rectangular submarine pits

A numerical model is presented to predict the interaction of multidirectional random surface waves with one or more rectangular submarine pits. The water depth is assumed uniform and the method involves the superposition of diffraction solutions based on linearized shallow water wave theory obtained by a two-dimensional boundary integral approach. The incident wave conditions are specified using a discrete form of the Mitsuyasu directional spectrum. The present numerical model has been validated through comparisons with previous theoretical results for regular waves. Good agreement was obtained in all cases. Based on these comparisons it is concluded that the present numerical model is an accurate and efficient tool to predict the wave field around multiple submarine pits and navigation channels in many practical situations.     

非线性随机海浪模型的一种新形式

以反映随机海浪非线性的波面高度分布高阶矩为参量，提出一种新形式的非线性随机海浪模型，在三阶近似下具体导出其波面高度的表达工和推导出二阶谱。本文模式为Ｌｏｎｇｕｅｔ－Ｈｇｇｉｎｓ模式的另一种新的数学表示。     

A note on wave energy dissipation over steep beaches

This paper revisits the derivation of the parametric surf zone model proposed by Baldock et al. [Baldock, T. E., Holmes, P., Bunker, S. & Van Weert, P. 1998 Cross-shore hydrodynamics within an unsaturated surf zone. Coast. Eng. 34, 173–196.]. We show that a consistent use of the proposed Rayleigh distribution for surf zone wave heights results in modification of the expressions for the bulk dissipation rate and enhanced dissipation levels on steep beaches and over-saturated surf zone conditions. As a consequence, the modification proposed herein renders the model robust even on steep beaches where it could otherwise develop a shoreline singularity.     

Boundary element modeling of multidirectional random waves in a harbor with partially reflecting boundaries

A numerical model is presented for the prediction of the wave field due to the diffraction of directional random waves in a harbor of arbitrary shape with partially reflecting boundaries. The water depth is assumed uniform and the method is based upon the superposition of diffraction solutions for monochromatic waves obtained by a two-dimensional boundary integral equation approach. The incident wave conditions are specified using a discrete form of the Mitsuyasu directional spectrum. The present numerical model has been validated through comparisons with previous experimental data and theoretical results for both regular and random wave diffraction by offshore breakwaters and in harbors. Good agreement was obtained in all cases. Based on these comparisons it is concluded that the present numerical model is an accurate and efficient tool to predict the wave field inside a harbor or around a breakwater in many practical applications.     

Potential influence of climate change on ecosystems within the Boreal Plains of Alberta

Ecosystems within the subhumid Boreal Plains of Northern Alberta host ecologically and commercially significant habitat and natural resources. However, these ecosystems exist under a delicate hydrologic balance that may be upset as the climate warms by 2 to 5 °C over the next century. In this study, numerical simulations were used to predict climate change impacts at a catchment composed of a mosaic of Boreal Plains ecosystems including a small pond, peatlands with sparse black spruce, and hillslopes with predominantly aspen forests. Simulations were conducted with a fully integrated groundwater–surface water code using a 2‐D model previously calibrated to a decade of hydrologic data that included a range in climatic conditions. Projections from 13 climate change scenarios were simulated from 2011 to 2090 and compared to a base case scenario that assumed no climate change. Results indicate peatland water levels may decline by up to 1 m; however, sensitivity simulations indicate that the decline in water levels may be moderated by several feedback mechanisms that restrict evaporative losses and moderate water level changes. In contrast, higher evapotranspiration losses from the aspen hillslopes are predicted to result in near‐surface soils becoming increasingly drier. Thus, the aspen may frequently be water stressed and increasingly susceptible to secondary maladies such as pests and disease. Reduced pond water levels are also predicted with the development of frequent ephemeral conditions in warmer and drier scenarios. Concurrent decreases in stream flow may further impact downstream ecosystems. Further research into the regional health and sustainability of Boreal Plains ecosystems is warranted and could benefit from the development of improved numerical tools capable of extending the processes considered.     

Assessing Collaborative Governance Outcomes and Indicators across Spatial and Temporal Scales: Stewardship Contract Implementation by the United States Forest Service

Abstract

Scholarship on collaboration in natural resource management is restricted by a lack of large-N assessments and mixed methods approach to examine relationships between collaborative structures and processes, and management actions and outcomes. This paper examines the relationship between perceived levels of collaboration, collaborative process indicators, and benefits of USDA Forest Service stewardship contracts at a broad spatial and temporal scale using mixed methodology. This study found higher levels of collaboration were strongly associated with jointly initiated processes that included a breadth of interests and utilized a broad range of outreach mechanisms and opportunities for engagement. Highly collaborative processes were closely linked with attaining project objectives and social and economic benefits. Findings contribute to defining collaboration by uncovering the relationship between perceived levels of collaboration, the role of process characteristics, and perceived benefits of collaborative stewardship contracting processes through a large-N dataset (n?=?1,064) and case study (n?=?61) findings.     

Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data

Land use and climate change could have huge impacts on food security and the health of various ecosystems. Leaf nitrogen (N) and above-ground biomass are some of the key factors limiting agricultural production and ecosystem functioning. Leaf N and biomass can be used as indicators of rangeland quality and quantity. Conventional methods for assessing these vegetation parameters at landscape scale level are time consuming and tedious. Remote sensing provides a bird-eye view of the landscape, which creates an opportunity to assess these vegetation parameters over wider rangeland areas. Estimation of leaf N has been successful during peak productivity or high biomass and limited studies estimated leaf N in dry season. The estimation of above-ground biomass has been hindered by the signal saturation problems using conventional vegetation indices. The objective of this study is to monitor leaf N and above-ground biomass as an indicator of rangeland quality and quantity using WorldView-2 satellite images and random forest technique in the north-eastern part of South Africa. Series of field work to collect samples for leaf N and biomass were undertaken in March 2013, April or May 2012 (end of wet season) and July 2012 (dry season). Several conventional and red edge based vegetation indices were computed. Overall results indicate that random forest and vegetation indices explained over 89% of leaf N concentrations for grass and trees, and less than 89% for all the years of assessment. The red edge based vegetation indices were among the important variables for predicting leaf N. For the biomass, random forest model explained over 84% of biomass variation in all years, and visible bands including red edge based vegetation indices were found to be important. The study demonstrated that leaf N could be monitored using high spatial resolution with the red edge band capability, and is important for rangeland assessment and monitoring.     

基于随机抽样一致性算法的稳健点云平面拟合方法

针对点云数据平面拟合过程中存在粗差及异常值等问题,文章提出一种基于随机抽样一致性算法(RANSAC)的稳健平面拟合方法。该方法以RANSAC算法为基础并结合特征值法,通过设置一定的准则,剔除点云数据中存在的粗差及异常值,达到获得理想平面拟合参数的目的。运用此算法对仿真数据及实测数据进行平面拟合,并与传统算法进行比较,结果表明该方法可以很好地适应于点云数据中存在粗差及异常值的情况,获得较好的平面参数估计值,是一种稳健的平面拟合算法。     

基于随机森林的国产小卫星遥感影像分类研究

近年来随着小卫星数量与传感器类型的快速增加,急需研究和发展快速可靠的小卫星遥感影像分类方法。针对分类方法各具局限性、具体应用中最优分类器选取困难等问题,本文基于多分类器集成学习的思路,引入随机森林(Random Forests)方法用于小卫星遥感影像分类。采用灾害监测预报小卫星(HJ-1)、北京1号小卫星(BJ-1)两种国产小卫星多光谱遥感影像进行试验,并与传统分类方法进行比较,结果表明,随机森林比最大似然分类器(MLC)、支持向量机分类器(SVM)等具有更好的稳定性、更高的分类精度和更快的运算速度,具有很好的适用性。     

人促天然更新米槠次生林与杉木人工林乔木层碳贮量分配特征比较

以杉木人工林为对照,分析三明陈大人工促进天然更新形成的米槠次生林乔木层碳贮量及其随树种、径阶、高阶的分配特点．结果表明：米槠次生林乔木层物种丰富度高于杉木林,人促天然更新有利于保持乔木层的树种多样性．米槠次生林乔木层碳贮量为178．67t·hm^-2,高于杉木人工林（111．24t·hm^-2）．米槠次生林和杉木人工林均以单优树种碳贮量占绝对优势,但米槠次生林中大个体林木（大径阶、大高阶）的碳贮量远大于杉木人工林．与杉木人工林相比,米槠次生林呈现出异龄的林分结构,这可能是其能够保持高碳吸存和高树种丰富度的重要原因．