喀斯特旅游地的旅游形象定位策划——以四川兴文县为例

旅游地形象的策划是当今旅游发展中倍受瞩目的课题之一。文章分析了喀斯特旅游地形象定位策划的重要性，对喀斯特旅游地形象定位策划进行了一种模式探讨——旅游形象定位模式。从喀斯特旅游地的地方文脉、旅游形象调查、竞争性三个因子分析入手，探讨了喀斯特旅游地形象定位的方法，并以四川省兴文县为例，进行了喀斯特旅游地旅游形象定位策划的实例分析。     

区域环评中产业定位调整建议的探讨

本文以山东省两个经济开发区区域环评为例，分析了各开发区在资源和环境方面的优劣势条件，论证了各开发区规划产业定位的合理性，探讨了开发区产业定位合理性评价的指标体系、调整原则、思路、方法，提出了各开发区产业定位的调整建议，并论证了调整后产业定位的合理性，促进了开发区的可持续发展。     

GPS卫星定位技术在河道整治与环境保护方面的应用

结合GPS卫星定位技术在河道整治与环境保护的应用实例,简要介绍了卫星定位技术的工作原理、基准站设置与应用效果。     

基于邻近线路行波监测的故障定位方法研究

以输电线路分布式监测技术为基础，将双端行波定位的应用范围从本线路延申至同电压等级的相邻线路，以拓展双端定位的途径。首先，分析了行波信号在相邻及同塔多回线路之间串入式传播的衰变规律，提出以串入式行波信号进行双端定位的方法，指明了其应用条件；其次，在某地区电网选取典型输电线路进行实例验证，分析比对了串入式行波双端定位的误差。结果表明，在串入途径选取合适时，串入式行波的定位方法仍具有较高的定位精度。     

秦皇岛城市旅游CTIS形象设计研究

在日趋激烈的国际城市旅游竞争中,若想取得一席之地,旅游城市需要构建系统的城市形象识别系统,即CTIS。城市CTIS系统需要在明确的市场定位基础上,通过构建旅游城市核心理念识别系统、行为识别系统及视觉识别系统实现。在对秦皇岛旅游市场进行STP(市场细分—目标市场选择—市场定位)分析的基础上,提出秦皇岛建设"健康之都"的城市定位,并且构建了相关城市CTIS系统内容。     

SWOT分析在区域性旅游业发展战略定位中的应用——以崇州市旅游业“十一五”战略策划为例

SWOT分析是企业管理理论中的一种技术分析手段,企业在选择经营或发展战略时常常以其结果作为决策的依据或重要参考.在旅游业蓬勃发展、旅游开发此起彼伏、方兴未艾的今天,区域性旅游业发展中的战略定位显得尤为重要.以崇州市旅游业"十一五"战略策划为例,简述了这种方法在区域性旅游业发展战略定位中的具体应用,供相关部门在制定旅游业发展战略定位时参考.     

贵州省旅游资源特性及其开发

揭示了贵州旅游资源的独特个性,深入探讨了贵州旅游业的形象定位--奇异秀美的喀斯特王国、神秘独特的地域文化旅游区,对贵州客源市场进行了细分和定位,并强调贵州近期应主抓普通兴趣旅游,但也要特别重视和扶持发展极有潜力的特殊兴趣旅游,最后提出了搞好贵州旅游开发营销的4点措施.     

冲压模具定位销的断裂失效分析

冲压模具定位销的材料为0Cr17Ni4Cu4Nb沉淀硬化马氏体不锈钢,在使用过程中,发生定位销断裂失效,导致模具损伤。通过化学成分、洛氏硬度、SEM-EDS分析、金相分析、拉伸测试、夏比冲击等试验,对其进行失效分析,结果显示:定位销显微组织中存在的铁素体条带组织以及螺纹孔处存在的腐蚀坑和应力腐蚀开裂是导致定位销断裂的主要原因。     

转型期地方环保职能初探

本文以经济转型期为大背景,通过对目前地方环保职能现状的分析．揭示地方环保职能重新定位紧迫性．重点围绕地方环保职能定位需要落实的“环保统一管理职能”和”全覆盖环保管理职能”两个主要内容,进行探索,以寻找一条适应转型期新时代环保部门机构职能定位及其转变的新思路。     

绿色农业产业化的政策性金融支持研究

绿色农业产业化的政策性金融支持是一种特殊的金融活动和金融形式。本文阐述了绿色农业产业化.政策性金融支持的内涵、融资渠道、职能定位和运营定位,认为完善绿色农业产业化的政策性金融支持应从商业性金融支持、合作性支持、民间性金融支持和政策性支持四个方面寻求对策思路。     

Calibration Catchment Selection for Flood Regionalization Modeling1

Wan Jaafar, Wan Zurina, and Dawei Han, 2012. Calibration Catchment Selection for Flood Regionalization Modeling. Journal of the American Water Resources Association (JAWRA) 48(4): 698‐706. DOI: 10.1111/j.1752‐1688.2012.00648.x Abstract: There are two unsolved problems in flood regionalization model development related to the quantity and quality of calibration catchments: (1) how many calibration catchments should be used? and (2) how to select the calibration catchments? This study explores these two questions through a case study on the median annual maximum flood (QMED) model in the United Kingdom. It has been found that the chance of developing a good QMED model decreases significantly when the number of calibration catchments drops below a critical number (e.g., 60 in the case study). However, no significant improvement is achieved if the number of calibration catchments is above it. This number could be used as a benchmark for choosing randomly selected calibration catchments. Across a broad range of calibration catchment numbers, there are good and poor calibrated models regardless of calibration catchment numbers. High quality models could be developed from a small number of calibration catchments and also poor models from a large number of calibration catchments. This indicates that the number of calibration catchments may not be the dominating factor for developing a high quality regionalization model. Instead, the information content could be more important. The study has demonstrated that the standard deviation values between the best and poorest groups are distinctive and could be used in choosing appropriate calibration catchments.     

单推三校正系数在光离子化检测器应用中的测量研究

在利用光离子化检测器监测单推三推进剂贮存环境时,必须首先要知道单推三相对于光离子化检测器校准气体的校正系数。通过简要介绍了校正系数的测量计算原理,并进行实验测量计算,求得单推三的校正系数。     

Importance of Crop Yield in Calibrating Watershed Water Quality Simulation Tools1

Surendran Nair, Sujithkumar, Kevin W. King, Jonathan D. Witter, Brent L. Sohngen, and Norman R. Fausey, 2011. Importance of Crop Yield in Calibrating Watershed Water Quality Simulation Tools. Journal of the American Water Resources Association (JAWRA) 47(6):1285–1297. DOI: 10.1111/j.1752‐1688.2011.00570.x Abstract: Watershed‐scale water‐quality simulation tools provide a convenient and economical means to evaluate the environmental impacts of conservation practices. However, confidence in the simulation tool’s ability to accurately represent and capture the inherent variability of a watershed is dependent upon high quality input data and subsequent calibration. A four‐stage iterative and rigorous calibration procedure is outlined and demonstrated for Soil Water Analysis Tool (SWAT) using data from Upper Big Walnut Creek (UBWC) watershed in central Ohio, USA. The four stages and the sequence of their application were: (1) parameter selection, (2) hydrology calibration, (3) crop yield calibration, and (4) nutrient loading calibration. Following the calibration, validation was completed on a 10 year period. Nash‐Sutcliffe efficiencies for streamflow over the validation period were 0.5 for daily, 0.86 for monthly, and 0.87 for annual. Prediction efficiencies for crop yields during the validation period were 0.69 for corn, 0.54 for soybeans, and 0.61 for wheat. Nitrogen loading prediction efficiency was 0.66. Compared to traditional calibration approaches (no crop yield calibration), the four‐stage approach (with crop yield calibration) produced improved prediction efficiencies, especially for nutrient balances.     

Applications of Explicitly Incorporated/Post‐Processing Measurement Uncertainty in Watershed Modeling

In the field of watershed modeling, the impact of measurement uncertainty (MU) on calibration results indicates the potential issue of inaccurate model predictions. It is important to note that MU refers to the uncertainty in measured data such as flow and nutrient values that are used to evaluate model outputs. The calculation of error statistics assuming measured data are deterministic may not be appropriate as has been frequently stated in literature. Although MU can affect model calibration results, it is rarely incorporated in modeling practice. MU can be incorporated in two schemes: explicitly incorporated (MU‐EI) during model calibration and post‐processed (MU‐PP) after calibration is completed. In this study, both schemes are implemented in a case study of the Arroyo Colorado Watershed, Texas. Unexpectedly, no substantial differences were observed between each scheme for flow predictions. Although MU did not cause dramatic differences in most sediment and NH₄‐N predictions, error statistics were affected in cases with MU greater than 50%, especially for sediment and NH₄‐N. Therefore, it is concluded that MU may not exert a significant impact on model predictions until certain threshold is reached. This study demonstrates that high levels of uncertainty in measured calibration/validation data significantly affect parameter estimation, especially in the auto‐calibration process.     

THE EFFECT OF DATA INDEPENDENCE IN MODEL CALIBRATION AND MODEL TESTING1

ABSTRACT: With the increased use of models in hydrologic design, there is an immediate need for a comprehensive comparison of hydrologic models, especially those intended for use at ungaged locations (i.e., where measured data are either not available or inadequate for model calibration). But some past comparisons of hydrologic models have used the same data base for both calibration and testing of the different models or implied that the results of model calibration are indicative of the accuracy at ungaged locations. This practice was examined using both the regression equation approach to peak discharge estimation and a unit hydrograph model that was intended for use in urban areas. The results suggested that the lack of data independence in the calibration and testing of regression equations may lead to both biased results and misleading statements about prediction accuracy. Additionally, although split-sample testing is recognized as desirable, the split-samples should be selected using a systematic-random sampling scheme, rather than random sampling, because random sampling with small samples may lead to a testing sample that is not representative of the population. A systematic-random sampling technique should lead to more valid conclusions about model reliability. For models like a unit hydrograph model, which are more complex and for which calibration is a more involved process, data independence is not as critical because the data fitting error variation is not as dominant as the error variation due to the calibration process and the inability of the model structure to conform with data variability.     

Evaluation of SWAT Impoundment Modeling Methods in Water and Sediment Simulations

Worldwide studies show 80%–90% of all sediments eroded from watersheds is trapped within river networks such as reservoirs, ponds, and wetlands. To represent the impact of impoundments on sediment routing in watershed modeling, Soil and Water Assessment Tool (SWAT) developers recommend to model reservoirs, ponds, and wetlands using impoundment tools (ITs). This study evaluates performance of SWAT ITs in the modeling of a small, agricultural watershed dominated by lakes and wetlands. The study demonstrates how to incorporate impoundments into the SWAT model, and discusses and evaluates involved parameters. The study then recommends an appropriate calibration sequence, i.e., landscape parameters calibration, followed by pond/wetlands calibration, then channel parameter calibrations, and lastly, reservoir parameter calibration. Results of this study demonstrate not following SWAT recommendation regarding modeling water land use as an impoundment depreciates SWAT performance, and may lead to misplaced calibration efforts and model over‐calibration. Further, the chosen method to model impoundments’ outflow significantly impacts sediment loads in the watershed, while streamflow simulation is not very sensitive. This study also allowed calculation of mass accumulation rates in modeled impoundments where the annual mass accumulation rate in wetlands (2.3 T/ha/yr) was 39% higher than mass accumulation rate in reservoirs (1.4 T/ha/yr).     

用区间估计法控制环境监测质量的初探

用投放质控标准样的方法来选择若干校准曲线，对这些标准曲线的截距ａ、斜率ｂ的进行总体参数进行区间估计。在实际工作中根据估计出的置信区间便可控制和检验监测所做校准曲线的质量，从而间接推断同期环境监测的质量。     

Automated Calibration of the METRIC‐Landsat Evapotranspiration Process

A remaining challenge to applying satellite‐based energy‐balance algorithms for operational estimation of evapotranspiration (ET) is the calibration of the energy‐balance model. Customized calibration for each image date is generally required to overcome biases associated with radiometric accuracy of the image, uncertainties in aerodynamic features of the landscape, background thermal conditions, and model assumptions. The CIMEC process (calibration using inverse modeling at extreme conditions) is an endpoint calibration procedure where near extreme conditions in the image are identified where the ET can be estimated and assigned. In the Mapping EvapoTranspiration at high Resolution with Internalized Calibration (METRIC?) energy‐balance model, two endpoints represent the dry and wet ends of the ET spectrum. Generally, user‐intervention is required to select locations in the image to produce best accuracy. To bring the METRIC and similar processes into the domain of less experienced operators, a consistent, reproducible, and dependable statistics‐based procedure is introduced where relationships between vegetation amount and surface temperature are used to identify a subpopulation of locations (pixels) in an image that may best represent the calibration endpoints. This article describes the background and logic for the statistical approach, how the statistics were developed, area of interest requirements and assumptions, adjustment for dry conditions in desert climates, and implementation in a common image processing environment (ERDAS Imagine).     

Automatic Calibration of Hydrologic Models With Multi‐Objective Evolutionary Algorithm and Pareto Optimization1

Abstract: In optimization problems with at least two conflicting objectives, a set of solutions rather than a unique one exists because of the trade‐offs between these objectives. A Pareto optimal solution set is achieved when a solution cannot be improved upon without degrading at least one of its objective criteria. This study investigated the application of multi‐objective evolutionary algorithm (MOEA) and Pareto ordering optimization in the automatic calibration of the Soil and Water Assessment Tool (SWAT), a process‐based, semi‐distributed, and continuous hydrologic model. The nondominated sorting genetic algorithm II (NSGA‐II), a fast and recent MOEA, and SWAT were called in FORTRAN from a parallel genetic algorithm library (PGAPACK) to determine the Pareto optimal set. A total of 139 parameter values were simultaneously and explicitly optimized in the calibration. The calibrated SWAT model simulated well the daily streamflow of the Calapooia watershed for a 3‐year period. The daily Nash‐Sutcliffe coefficients were 0.86 at calibration and 0.81 at validation. Automatic multi‐objective calibration of a complex watershed model was successfully implemented using Pareto ordering and MOEA. Future studies include simultaneous automatic calibration of water quality and quantity parameters and the application of Pareto optimization in decision and policy‐making problems related to conflicting objectives of economics and environmental quality.     

莱特生物强化技术处理高浓度有机废水的中试

采用莱特生物强化技术(LTBR—Littoral BioReactor),对兰州石化公司化工园区高浓度有机废水进行了中试试验,进行了正常运行的常规标定、水量冲击标定、浓度冲击标定。结果表明:采用LTBR生物处理工艺,使用特效微生物和营养基质,可以在高COD、高含盐等不利条件下正常进行有机物降解,达到了必须将废水中的COD降至2000mg/L以下的试验要求,为处理高浓度有机化工废水的工程应用开辟了新思路。