Forest operations,tree species composition and decline in rainfall explain runoff changes in the Nacimiento experimental catchments,south central Chile

Few long-term studies have explored how intensively managed short rotation forest plantations interact with climate variability. We examine how prolonged severe drought and forest operations affect runoff in 11 experimental catchments on private corporate forest land near Nacimiento in south central Chile over the period 2008–2019. The catchments (7.7–414 ha) contain forest plantations of exotic fast-growing species (Pinus radiata, Eucalyptus spp.) at various stages of growth in a Mediterranean climate (mean long-term annual rainfall = 1381 mm). Since 2010, a drought, unprecedented in recent history, has reduced rainfall at Nacimiento by 20%, relative to the long-term mean. Pre-drought runoff ratios were <0.2 under 8-year-old Eucalyptus; >0.4 under 21-year-old Radiata pine and >0.8 where herbicide treatments had controlled vegetation for 2 years in 38% of the catchment area. Early in the study period, clearcutting of Radiata pine (85%–95% of catchment area) increased streamflow by 150 mm as compared with the year before harvest, while clearcutting and partial cuts of Eucalyptus did not increase streamflow. During 2008–2019, the combination of emerging drought and forestry treatments (replanting with Eucalyptus after clearcutting of Radiata pine and Eucalyptus) reduced streamflow by 400–500 mm, and regeneration of previously herbicide-treated vegetation combined with growth of Eucalyptus plantations reduced streamflow by 1125 mm (87% of mean annual precipitation 2010–2019). These results from one of the most comprehensive forest catchment studies in the world on private industrial forest land indicate that multiple decades of forest management have reduced deep soil moisture reservoirs. This effect has been exacerbated by drought and conversion from Radiata pine to Eucalyptus, apparently largely eliminating subsurface supply to streamflow. The findings reveal tradeoffs between wood production and water supply, provide lessons for adapting forest management to the projected future drier climate in Chile, and underscore the need for continued experimental work in managed forest plantations.     

Water quality data for Fall Creek,New York,USA: 1972–1995

The 33 086 ha mixed land use Fall Creek watershed in upstate New York is part of the Great Lakes drainage system. Results from more than 3500 water samples are available in a data set that compiles flow data and measurements of various water quality analytes collected between 1972 and 1995 in all seasons and under all flow regimes in Fall Creek and its tributaries. Data is freely accessible at https://ecommons.cornell.edu/handle/1813/8148 and includes measurements of suspended solids, pH, alkalinity, calcium, magnesium, potassium, sodium, chloride, nitrate nitrogen (NO3-N), sulphate sulphur (SO4-S), phosphorus (P) fractions molybdate reactive P (MRP) and total dissolved P (TDP), percent P in sediment, and ammonium nitrogen (NH4-N). Methods, sub-watershed areas, and coordinates for sampling sites are also included. The work represented in this data set has made important scientific contributions to understanding of hydrological and biogeochemical processes that influence loading in mixed use watersheds and that have an impact on algal productivity in receiving water bodies. In addition, the work has been foundational for important regulatory and management decisions in the region.     

An evaluation of Guided Regularized Random Forest for classification and regression tasks in remote sensing

New Earth observation missions and technologies are delivering large amounts of data. Processing this data requires developing and evaluating novel dimensionality reduction approaches to identify the most informative features for classification and regression tasks. Here we present an exhaustive evaluation of Guided Regularized Random Forest (GRRF), a feature selection method based on Random Forest. GRRF does not require fixing a priori the number of features to be selected or setting a threshold of the feature importance. Moreover, the use of regularization ensures that features selected by GRRF are non-redundant and representative. Our experiments based on various kinds of remote sensing images, show that GRRF selected features provides similar results to those obtained when using all the available features. However, the comparison between GRRF and standard random forest features shows substantial differences: in classification, the mean overall accuracy increases by almost 6% and, in regression, the decrease in RMSE almost reaches 2%. These results demonstrate the potential of GRRF for remote sensing image classification and regression. Especially in the context of increasingly large geodatabases that challenge the application of traditional methods.     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

基于噪声谱比法的内蒙古西部地区台站场地响应研究

利用内蒙古西部12个台站的地脉动噪声数据，采用噪声谱比法研究台站的场地响应情况。分析表明，台站场地响应按曲线形态可分为3类，且可能受地形地貌、局部构造和台基状况等条件影响。对比分析噪声谱比法与Moya方法的场地响应结果发现，场地响应曲线形态基本一致，只有极少数台站存在明显差异。结果表明，内蒙古西部区域大部分台站的台基状况总体较好，场地响应曲线较为平坦，无明显频率放大点。     

自然和自然贡献情景模型研究综述

本文回顾了自然和自然贡献情景模型发展的背景、历史和内容,概括总结了自然和自然贡献情景模型的发展进程以及联合国生物多样性与生态系统服务政府间科学—政策平台(IPBES)情景模型的概念框架,讨论了自然和自然贡献情景模型存在的问题和发展方向。为了在全球层面解决现有综合集成模型存在的问题,根据地球表层建模基本定理和生态环境曲面建模基本定理,提出了具有中国原创特点的自然与自然贡献情景模型概念框架。     

Overview of In - Situ Biodegradation and Enhancement

Microbial degradation technologies have been developed to restore ground water quality in aquifers polluted by organic contaminants effectively in recent years. However, in course of the degradation, the formation of biofilms in ground water remediation technology can be detrimental to the effectiveness of a ground water remediation project. Several alternatives are available to a remedial design engineer, such as Permeable Reactive Barriers (PRBs) and in -situ bioremediation, Hydrogen Releasing Compounds (HRCs) barrier, Oxygen Releasing Compounds (ORCs) barrier etc. which are efficient and cost- effective technologies. Excessive biomass formation renders a barrier ineffective in degrading the contaminants, Efforts are made to develop kinetics models which accurately determine bio - fouling and bio - filn formation and to control excessive biomass formation.     

Pulsar magnetic field for an infinitely conductive accretion disk

The magnetic-field distribution outside a flat, infinitely conductive unbounded disk in the field of a point magnetic dipole is determined. A relationship is established between the problem of magnetic-field determination and the problem of the flow of an ideal incompressible fluid around an infinitely thin disk.