A goal interval programming model for resource allocation in a marine environmental protection program

A multidimensional “goal programming” model is developed to aid resource allocation decisions in the U. S. Coast Guard's Marine Environmental Protection (MEP) program. It is then extended to a model of “goal interval programming” (GIP ) type where exact values for the indicated goals, as in ordinary goal programming, are replaced by ranges. Deviations outside these ranges are also accommodated by piecewise linear functions with slopes that vary with distance from the goal intervals. Uses and generalizations are discussed in the context of applications to allocating manhours and planning the activities of the Coast Guard's MEP program.     

A chance-constrained goal programming model to evaluate response resources for marine pollution disasters

This paper develops a model to aid Coast Guard managers in formulating appropriate policies with respect to planning for various types of equipment required to contain major pollution incidents. The model is elaborated in terms of three primary stages of response: offloading, containment, and removal. The zero order rule of chance constrained programming is used to obtain a deterministic equivalent of the original chance constrained model. This is then replaced by a goal programming formulation to allow for plans that come “as close as possible” to desired quality and risk levels for each pertinent region and type of incident. Numerical examples illustrate potential uses of the model with special emphasis on its value for budgetary (equipment) planning by central management that extends to evaluation of risk and performance quality levels, as well as the usual dual evaluator approaches for evaluating initially prescribed levels for equipment and their efficiency coefficients.     

基于净初级生产力的能源足迹模型及其与传统模型的比较分析

将净初级生产力和土地利用变化2个新指标纳入传统能源足迹模型,构建了基于净初级生产力的能源足迹模型。应用传统模型和改进后的模型分别计算了1999—2008年的吉林省能源足迹,并对2组结果进行了比较分析。研究结果表明：10年间,采用传统模型计算的吉林省人均能源足迹由0.7908hm2增至1.6770hm2,采用净初级生产力模型计算的人均能源足迹由0.2490hm2增至0.5237hm2。2种模型的计算结果在整体变化趋势和构成顺序上较为一致,但在历年变化速率和具体构成份额上存在一定差别。净初级生产力模型扩展了传统模型的研究范围,并在碳吸收参数选取等方面进行了较大改进,所得结果反映了区域综合碳吸收能力下的能源消费生态环境影响,更符合区域自然和社会实际状况,一定程度上是对传统模型的完善。     

水信息学及其在水环境中的应用研究综述

水信息学是一门新兴的学科,是在水范围内运用知识的新途径、元知识.它着重运用计算机技术、通信网络技术、3S技术、可视化技术等一系列高新技术,并结合传统水科学和工程学的方法,研究与水环境相关数据的收集、存储、处理、模拟、预测和结果显示等问题.文章首先探讨了几种不同的水环境概念及水环境研究模型,阐述了近年生态水力学模型的制约因素.生态水力学模型建市在时空一致性和质量能量守恒等假设上,而水生态系统的高度复杂性、非线性和时空特异性制约模型的发展.从"知识发现"和"知识管理"两个视角出发,重点阐述数学模型、数据挖掘、数据同化、数据驱动、地理信息系统、决策支持系统、商业软件等水信息学方法在水环境研究中的应用.目前水信息学还处于起步阶段,各方法交叉结合的研究还比较少,在今后的研究中有待加强,包括基于数据的各方法手段的结合、基于数据和基于过程的两者结合、水环境的知识发现和知识管理的结合等.     

A model of Cellular Automata for the spatial and temporal analysis of Citrus Sudden Death with the fuzzy parameter

Citrus Sudden Death (CSD) is a disease that has affected sweet orange trees grafted on Rangpur lime in the south of Minas Gerais state and in the north of São Paulo state (Brazil). This is a worrying characteristic because the Rangpur lime responds to 85% of the Brazilian citrus rootstocks. This disease is believed to be caused by a virus transmitted by aphids (vector) of the citrus. In this work, we have adopted the Cellular Automata model (CA) to study the temporal evolution of the disease. We take into account the effect of the wind in the space covered by the aphid. To establish the relationship between the space covered by the aphid and the intensity of the wind, we have adopted the rule-based fuzzy system. Simulations were performed and compared to real data. Through the use of the mean absolute error (MAE) method, it was possible to verify a 70% of similarity between our model of data and the real one.     

An application of Markov Decision Programming to ecologico-cybernetics—A decision method applied to the antifrost of winter wheat

Modern ecologico-cybernetic principle is of importance to decreasing damages in relation to agricultural productions. As an illustration of this, the authors studied some of the questions about the optimal policy of choosing actions for the antifrost measures of winter wheat by means of the finite-stage model of Markov Decision Programming (MDP). The related data came from the investigation results of the investigated region in the northeastern part of Henan, China. First, the authors give the states, ecologico-cybernetic action measures, transition probabilities and reward values in relation to these antifrost action measures of winter wheat crop. Second, the authors describe the principles and computational procedures of the ecologico-cybernetic decision-makings based on the finite-stage model of MDP. Third, a simple table applicable to the decision-making practice is given. Finally, we evaluate the results of this study, point out their shortcomings and suggest that this method is applicable to the other fields in relation to decreasing damage ecologico-cybernetics.     

A hierarchical Bayesian non-linear spatio-temporal model for the spread of invasive species with application to the Eurasian Collared-Dove

The spread of invasive species is a long studied subject that garners much interest in the ecological research community. Historically the phenomenon has been approached using a purely deterministic mathematical framework (usually involving differential equations of some form). These methods, while scientifically meaningful, are generally highly simplified and fail to account for uncertainty in the data and process, of which our knowledge could not possibly exist without error. We propose a hierarchical Bayesian model for population spread that accommodates data sources with errors, dependence structures between population dynamics parameters, and takes into account prior scientific understanding via non-linear relationships between model parameters and space-time response variables. We model the process (i.e., the bird population in this case) as a Poisson response with spatially varying diffusion coefficients as well as a logistic population growth term using a common reaction-diffusion equation that realistically mimics the ecological process. We focus the application on the ongoing invasion of the Eurasian Collared-Dove.     

A process-based population dynamics model to explore target and non-target impacts of a biological control agent

The risks and benefits associated with efforts to control invasive alien species using classical biological control are being subjected to increasing scrutiny. A process-based population dynamics model was developed to explore the interactions between a folivorous biological control agent, Cleopus japonicus, and its plant host Buddleja davidii. The model revealed that climate could have a significant impact upon the interactions between B. davidii and C. japonicus. At the coolest sites, the impact of C. japonicus on B. davidii was slowed, but it was still eventually capable of controlling populations of B. davidii. At the warmer sites where both B. davidii and C. japonicus grew faster, B. davidii succumbed rapidly to weevil damage. We hypothesise that barring an encounter with a natural enemy, C. japonicus will eventually be able to provide sustained control B. davidii throughout the North Island of New Zealand. The model scenarios illustrate the potential for the C. japonicus population to attain high densities rapidly, and to defoliate patches of B. davidii, creating the potential for spill-over feeding on non-target plants. The potential magnitude of this threat will depend partly on the climate suitability for C. japonicus, the pattern by which it migrates in response to a reduction in the available leaf resource, and the suitability of non-target plants as hosts. In all migration scenarios considered, the pattern of population growth and resource consumption by C. japonicus was exponential, with a strong tendency toward complete utilisation of resource patches more quickly at the warmer compared to colder sites. In addition to providing some useful hypotheses about the effects of climate on the biological control system, and the non-target risks, it also provides some insight into the mechanisms by which climate affects the system.     

A linear programming model of residuals management for integrated iron and steel production

This paper briefly describes a linear programming model designed to allow the exploration of questions surrounding the management of the environmental impacts of integrated iron and steel facilities. In particular, the model can show how plant discharges will change in the absence of specific legal restrictions or effluent charges, with such variables as product mix, steel-furnace type, casting technology, and the scrap-ore price ratio. In addition, the costs implied by placing restrictions on discharges of specific residuals (e.g., BOD, oil, suspended solids, particulates) may be estimated, or response to proposed effluent charges may be predicted.     

水安全智能识别模型的建立及应用

通过人口迁移算法优化投影寻踪模型,提出了一种新的水安全智能识别模型。与遗传算法优化的投影模型相对比,人口迁移算法的自身优势有效地避免了网络早熟现象及寻找全局最优解的困扰。从水安全的评价结果来看,用人口迁移算法优化投影寻踪是可行的,并显示出优越性。人口迁移算法为求解投影寻踪模型的非线性约束提供了新的优化方法,并为水安全评价工作提供了新的智能识别模型。     

Development and test of a crop growth model for application within a Global Change decision support system

When examining potential impacts of Global Change on water resources on the regional scale, spatial and temporal changes in crop water and nitrogen demand are of fundamental significance. State-of-the-art crop growth models are powerful tools to assess the response of crops to altered environmental conditions and cultivation practices. In this paper, the process-based, object-oriented and generic DANUBIA crop growth model is presented. To evaluate the performance of the model, a validation analysis is carried out by comparing modelled data with various field measurements of sugar beet, spring barley, maize, winter wheat and potato crops. Model performance statistics show that crop growth is efficiently simulated. The closest agreement between measured and modelled biomass and leaf area index is achieved for sugar beet and winter wheat. Additionally, the response of the model to changed nitrogen availability caused by cultivation practices is analysed and reveals good results. The results suggest that the model is a suitable tool for numerically assessing the consequences of Global Change on biomass production, water and nitrogen demand, taking into account the complex interplay of water, carbon and nitrogen fluxes in agro-ecosystems.     

环境保护优化经济增长的贡献度模型及实证分析

在界定环境保护投入产出核算的概念基础上,根据环保投资与治理费用作用于经济的原理,借鉴环境经济投入产出基本思想,构建了环境保护优化经济增长的贡献度模型,主要包括污染治理投资对经济的影响模型和污染治理运行费用对经济的影响模型,并对该模型进行了实证模拟分析,得出了相关结论与政策建议.     

A holistic approach to the development of sustainable agriculture: application of the ecosystem health model

Serious resource depletion has made sustainable agriculture an important and pressing issue for scientists, policy makers, and stakeholders worldwide, particularly in developing countries. Researchers have focused on methods to assess agriculture correctly, and to introduce sound solutions for sustainability, but have reached no agreement. In this paper, we introduce the theoretical framework of the agro-ecosystem health model, a new holistic approach, and apply it at a regional scale using four aspects (4S): sound structure, stable function, safe service, and sustainable development. We examine how 12 indicators of an agro-ecosystem health assessment (AHA) were selected using three dimensions based on this theoretical framework. In an AHA, we used an amoeba approach to examine a high-yield agro-ecosystem in Huantai County, Shandong Province, China. The results indicate that this model of ecosystem health can reflect the complex ecological, economic, and human conditions of an agro-ecosystem and evaluate these conditions using perspectives pertinent to system structure, function, and responses (services).     

A closure approach with multi-scale mixing length,and its application to wind and shear stress profiles within the atmospheric boundary layer

A method to determine flow specific first-order closure for the turbulent flux of momentum in the atmospheric boundary layer (ABL) is presented. This is based on the premise that eddy viscosity is a flow rather than a fluid property, and the physically more realistic assumption that the transfer of momentum and other scalar quantities in a turbulent flow takes place by a large, but finite number of length scales, than the often used single length scale, the ‘mixing length’. The resulting eddy viscosity is flow specific and when applied to the study of the ABL, yields the vertical profiles of shear stress and mean wind velocity in good agreement with observations. The method may be extended to other types of turbulent flows, however it should be recognized that each type of flow may yield a different eddy viscosity profile. Using the derived eddy viscosity the paper presents simple analytical solutions of the ABL equations to determine observationally consistent wind speed and shear stress profiles in the ABL for a variety of practical applications including air pollution modelling.     

Manifestation of an advanced fuzzy logic model coupled with Geo-information techniques to landslide susceptibility mapping and their comparison with logistic regression modelling

Landslides are very common natural problems in the Selangor area of Malaysia due to the improper use of landcover and tropical rainfall. There are many landslide susceptibility analyses such as statistical, bivariate and data mining approaches exist in the literature. This paper presents the use of fuzzy logic relations for landslide susceptibility mapping on part of Selangor area, Malaysia, using a Geographic Information System (GIS) and remote sensing data. At first, landslide locations were identified in the study area from the interpretation of aerial photographs and satellite images, supported by extensive field surveys. Topographic and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Thirteen landslide conditioning factors such as slope gradient, slope exposure, plan curvature, altitude, stream power index, topographic wetness index, distance from drainage, distance from road, lithology, distance from faults, soil, landcover and normalized difference vegetation index (ndvi) were extracted from the spatial database. These factors were analyzed using fuzzy logic relations to produce the landslide susceptibility maps. Using the landslide conditioning factors and the identified landslides, the fuzzy membership values were calculated. Then fuzzy algebraic operators were applied to the fuzzy membership values for landslide susceptibility mapping. Finally, the ROC curves for all landslide susceptibility models were drawn and the area under curve values were calculated. Landslide locations were used to validate results of the landslide susceptibility maps and the validation results showed 94% accuracy for the fuzzy gamma operator employing all parameters produced in the present study as the landslide conditioning factors. Results showed that, among the fuzzy relations, in the case in which the gamma operator (λ =  0.975) showed the best accuracy (94.73%) while the case in which the fuzzy algebraic Or was applied showed the worst accuracy (84.76%). The landslide susceptibility maps produced by the fuzzy gamma operators shows similar trends as those obtained by applying logistic regression procedure by the same author and indicate that fuzzy relations results perform slightly better than the earlier method. Qualitatively, the model yields reasonable results which can be used for preliminary land-use planning purposes.     

A method for building spatial model of annual weed seed dispersal from experimental data and its application to simulating Bromus sterilis population dispersal

Spatial model of annual weed seed dispersal, in this article, was theoretically derived. According to the requirements of building the spatial model, we designed and done an indoor experiment of weed seed dispersal by wind. In the experiment, the seeds of Bromus sterilis were released at 100 cm height under different wind velocity conditions. Based on the experimental data, the spatial models of seed dispersal of the weed species were built, which were divided into three types according to the coefficient β < 0, β = 0, β > 0. The results showed that dispersal of annual weed seed in any direction obeyed an approximate Gaussian distribution; under the experimental conditions, spatial distribution type of weed seed dispersal changed with variation of wind velocity. Well-known Howard et al.'s model (Howard et al., 1991) of Bromus sterilis seed dispersal is an especial example of the model built in this article. The result of model analysis indicated that the distribution type described by Howard's model was similar to that of seed dispersal of the weed species at the height of 100 cm under the condition of lower wind velocity (about 2.18 m/s). Using CA simulation analysis we found that mean control agent applying to a cell with weed should have a decrease with an increase of wind velocity to prevent weed with the initial configuration from spreading, which implicated less herbicide needs spraying in every cell with weed on average when wind velocity increases.     

城市环境熵模型的建立及其在城市化环境影响评价研究中的应用

城市化是20世纪以来的一个全球性进程,与此同时,城市化对环境的影响也日益明显,并逐渐成为社会各界关注的焦点之一。文章在简单介绍热力学原理的基础理论、城市化概念特别是城市化对环境影响的基础上,从系统的角度深入分析了城市化对环境的影响与热力学熵原理的相似性。由此提出在城市化环境影响评价研究中借鉴热力学方法,提出了城市化环境影响评价的新概念和新方法——"城市环境熵"模型。最后,以珠江三角洲经济区城市化河水质量影响评价为例,运用"城市环境熵"模型进行了具体计算,结果表明,用此模型的评价结果与用均值化综合污染指数法的评价结果基本一致,相对误差为6.67%。可以认为用城市环境熵模型法来评价城市化对城市环境的影响是可行的。     

Modification of a stream temperature model with Beer's law and application to GaoShan Creek in Taiwan

A physics-based stream temperature model [Tung, C.P., Lee, T.Y., Yang, Y.C., 2006. Modelling climate-change impacts on stream temperature of Formosan Landlocked Salmon habitat. Hydrol. Process. 20, 1629–1649] was improved by incorporating shading effects caused by both cliff terrain and riverbank dense vegetation to simulate hourly stream temperature variations in 1 day. Daily maximal stream temperature is a critical factor to the habit distribution of the Formosan Landlocked Salmon, an important and endangered species. Currently, it only can be found in ChiChiaWan Creek and GaoShan Creek in Taiwan. The former stream temperature model only considers the shading effects of cliff terrain and works well for ChiChiaWan Creek, but overestimates stream temperatures of GaoShan Creek having dense riverbank vegetative covers. The model was modified with the Beer's law and a parameterization scheme to describe the diminishing of the incident solar radiation to take vegetative shading effects into account. Simulation results of GaoShan Creek show the success of this improvement. The shading effects induced by both terrain and vegetation can significantly affect stream temperature distributions. Simulation experiments were conducted to indicate shading effects are varied in different watersheds and seasons.