基于GIS的区域农业气候资源要素分布模拟

针对当前一定区域范围内气象站点非常有限,而区域内农业生产却在一定程度上依赖农业气候条件这一特点,文章将地理信息系统（GIS）技术与农业气候资源要素推算数学模式相结合,以获取区域主要农业气候资源要素的精确定量值,并用图形等多种方式来表达最终成果。以重庆区域为例,具体模拟了其区域范围内主要农业气候资源要素的空间分布。     

基于GIS技术的重庆市危险废物管理信息系统研究

重庆市每年都会产生大量的危险废物，直接威胁到了重庆市的水环境及生态环境，因此，有效的管理重庆市的危险废物是处理和处置的重要保证。主要介绍了基于CIS危险废物管理信息系统的设计，将危险废物、计算机技术和GIS技术相结合，为危险废物的管理提供快捷、方便、科学的管理和决策支持。该系统包括六个子系统，分别是数据输入、数据查询、数据库管理和维护、模型库、决策支持、系统管理。该系统具有界面友好、操作方便、实用等特点，将在重庆市危险废物管理方面起到重要作用。     

基于GIS的哈密地区旅游资源分析与评价

按国家标准(GB/T18972—2003)对哈密地区旅游资源进行普查,并结合前人所获得的资料,在地理信息系统(GIS)的支持下,从资源的丰度、品质、空间结构和空间分布等方面评价了哈密地区旅游资源,总结出哈密地区旅游资源具有类型较丰富、分布不均衡、资源品质一般、特品级旅游资源缺乏;人文旅游资源在数量上占有绝对优势且特色明显,但自然旅游资源仍有较大开发潜力等主要特征。该分析与评价结果可为该地区决策的制定提供战略参考。     

基于Web GIS的四川省自然保护区信息管理系统

本文简要介绍了四川省自然保护区信息管理系统的设计思路、框架结构及运行界面。以ArcGIS Server为开发平台,使用SQL Server管理属性数据,采用四川省1∶25万基础地理数据,设计并开发四川省自然保护区信息管理系统,在地图服务的基础上,实现对四川省自然保护区的浏览、查询,为自然保护区的管理提供一个科学、准确的决策支持。     

基于GIS技术的高速铁路线网规划适应性研究

高速铁路线网是网规策划中十分重要的内容之一,合理的线网规划能够有效防止规划以及建设目的的盲目性。本文结合GIS技术,对社会经济发展水平以及高速铁路线网规模之间的耦合关系进行分析,结合多方面因素组建高速铁路线网规模预算模型。在上述分析的基础上,分别从目标规划需求以及高速铁路线网结构性能两方面对网规划适应性进行研究。实验选取某地区高速铁路线网作为研究对象,验证了所提方法的有效性。     

基于GIS技术的生态环境脆弱性模糊综合评价

研究过程中摒弃了以往生态环境脆弱性分析中常有的以乡、镇为研究单元的传统模式,改用栅格单元为基本研究单元,切实反映了区域自然环境特征的非均衡性和连续性,使研究结果打破行政区界限从而具有＂空间性＂;并基于栅格单元首次提出了将＂地理信息系统技术＂和＂AHP-模糊综合评价模型＂互相融合的生态环境脆弱性研究的＂分解-合成＂新方法,使得原本数据信息有限的模糊矩阵扩展成包含大量网格信息的巨型空间矩阵,较好的解决了图层属性单一化与模糊隶属最大原则之间的矛盾。文章从＂模糊隶属度＂层面进行生态环境脆弱性综合分析评价。     

基于GIS的城市土地利用与交通网络一体化模型

在蓬勃发展的城市化进程中,一方面,城市交通需求迅速增长,交通运输供给能力不足成为制约区域经济快速发展的瓶颈;另一方面,在城市化进程中突出的景观标志--土地利用的变化包含着城市极其丰富的信息量,城市交通网络设计必然要求将城市土地利用与交通网络设计整合考虑.概述了土地利用与交通网络设计的关系,构建了一个基于GIS的城市土地利用与交通网络设计一体化模型 (LTGIS) ,同时对模型中的系统设计进行了论述,表明城市土地利用与交通网络设计是密切相关的.基于GIS的城市土地利用与交通网络设计一体化模型(LTGIS)的提出具有理论与实践的双重意义.     

基于GIS技术的安徽省城市旅游空间关联分析

运用空间相互作用理论中的威尔逊模型,结合GIS中网络分析技术和空间自相关分析对安徽省17个城市的旅游空间关联进行分析。结果发现,安徽省的全局旅游关联显著性水平不高,全省旅游空间关联度很低;而局部旅游空间关联在黄山和池州形成热点区,在皖北和皖中的巢湖、滁州形成冷点区,其他城市的旅游空间关联呈现明显的差异性。计算结果表明,对旅游空间关联影响最大的指标是城市旅游供给量,因此增强城市的旅游供给水平对增强旅游吸引力具有决定性的意义。     

基于多源数据AnnAGNPS西枝江流域的污染模拟研究

以西枝江流域为研究对象,结合GIS技术,建立了AnnAGNPS模型数据库,对流域内非点源污染主要影响因素的特征以及非点源污染的时空分布特征进行了分析。结果表明：流域内降雨侵蚀力、径流深、土壤侵蚀和沉积负荷的年际问变化很大,降雨侵蚀力月问分布极不均匀,季节变化十分明显,后三者的变化趋势都与平均降水量表现出较好的对应关系,但是又并不完全一致;流域内的径流深空间分布极不均匀,而土壤侵蚀、沉积负荷空间变化相对不是十分明显,三者都有沿河道向两边逐渐递减的趋势,在人口密集地区及河塘密集地区,径流相对其他区域比较大。本文为西枝江流域的非点源污染模拟研究提供了基础数据平台,也为该模型在整个东江流域的合理应用奠定了科学基础。     

GIS与大气污染扩散模型的整合研究

大气扩散模型与GIS整合是当前的重要发展趋势。文章分析了该技术存在的主要问题和可行的解决路线,并指出了其主要发展方向。主张采用GIS二次开发工具和大气污染模型进行整合。详细介绍了开发“硫化氢应急专家系统”的工作中,解决二者整合所取得的研究进展和成果。将GIS、大气模型与应急救援工作三者有机的整合,实现了GIS数据和应急数据的紧密结合及对硫化氢扩散的预测。     

VALIDATION OF AGNPS FOR SMALL WATERSHEDS USING AN INTEGRATED AGNPS/GIS SYSTEM1

ABSTRACT: The AGNPS (AGricultural NonPoint Source) model was evaluated for predicting runoff and sediment delivery from small watersheds of mild topography. Fifty sediment yield events were monitored from two watersheds and five nested subwater-sheds in East Central Illinois throughout the growing season of four years. Half of these events were used to calibrate parameters in the AGNPS model. Average calibrated parameters were used as input for the remaining events to obtain runoff and sediment yield data. These data were used to evaluate the suitability of the AGNPS model for predicting runoff and sediment yield from small, mild-sloped watersheds. An integrated AGNPS/GIS system was used to efficiently create the large number of data input changes necessary to this study. This system is one where the AGNPS model was integrated with the GRASS (Geographic Resources Analysis Support System) GIS (Geographical Information System) to develop a decision support tool to assist with management of runoff and erosion from agricultural watersheds. The integrated system assists with the development of input GIS layers to AGNPS, running the model, and interpretation of the results.     

Optimal Reorganization of NASA Earth Science Data for Enhanced Accessibility and Usability for the Hydrology Community

A long‐standing “Digital Divide” in data representation exists between the preferred way of data access by the hydrology community and the common way of data archival by earth science data centers. Typically, in hydrology, earth surface features are expressed as discrete spatial objects (e.g., watersheds), and time‐varying data are contained in associated time series. Data in earth science archives, although stored as discrete values (of satellite swath pixels or geographical grids), represent continuous spatial fields, one file per time step. This Divide has been an obstacle, specifically, between the Consortium of Universities for the Advancement of Hydrologic Science, Inc. and NASA earth science data systems. In essence, the way data are archived is conceptually orthogonal to the desired method of access. Our recent work has shown an optimal method of bridging the Divide, by enabling operational access to long‐time series (e.g., 36 years of hourly data) of selected NASA datasets. These time series, which we have termed “data rods,” are pre‐generated or generated on‐the‐fly. This optimal solution was arrived at after extensive investigations of various approaches, including one based on “data curtains.” The on‐the‐fly generation of data rods uses “data cubes,” NASA Giovanni, and parallel processing. The optimal reorganization of NASA earth science data has significantly enhanced the access to and use of the data for the hydrology user community.     

Streamflow Hydrology Estimate Using Machine Learning (SHEM)

Continuity and accuracy of near real‐time streamflow gauge (streamgage) data are critical for flood forecasting, assessing imminent risk, and implementing flood mitigation activities. Without these data, decision makers and first responders are limited in their ability to effectively allocate resources, implement evacuations to save lives, and reduce property losses. The Streamflow Hydrology Estimate using Machine Learning (SHEM) is a new predictive model for providing accurate and timely proxy streamflow data for inoperative streamgages. SHEM relies on machine learning (“training”) to process and interpret large volumes (“big data”) of historic complex hydrologic information. Continually updated with real‐time streamflow data, the model constructs a virtual dataset index of correlations and groups (clusters) of relationship correlations between selected streamgages in a watershed and under differing flow conditions. Using these datasets, SHEM interpolates estimated discharge and time data for any indexed streamgage that stops transmitting data. These estimates are continuously tested, scored, and revised using multiple regression analysis processes and methodologies. The SHEM model was tested in Idaho and Washington in four diverse watersheds, and the model's estimates were then compared to the actual recorded data for the same time period. Results from all watersheds revealed a high correlation, validating both the degree of accuracy and reliability of the model.     

Incorporating Variable Source Area Hydrology into a Spatially Distributed Direct Runoff Model1

Buchanan, Brian, Zachary M. Easton, Rebecca Schneider, and M. Todd Walter, 2011. Incorporating Variable Source Area Hydrology Into a Spatially Distributed Direct Runoff Model. Journal of the American Water Resources Association (JAWRA) 48(1): 43‐60. DOI: 10.1111/j.1752‐1688.2011.00594.x Abstract: Few hydrologic models simulate both variable source area (VSA) hydrology, and runoff‐routing at high enough spatial resolutions to capture fine‐scale hydrologic pathways connecting VSA to the stream network. This paper describes a geographic information system‐based operational model that simulates the spatio‐temporal dynamics of VSA runoff generation and distributed runoff‐routing, including through complex artificial drainage networks. The model combines the Natural Resource Conservation Service’s Curve Number (CN) equation for estimating storm runoff with the topographic index concept for predicting the locations of VSA and a runoff‐routing algorithm into a new spatially distributed direct hydrograph (SDDH) model (SDDH‐VSA). Using a small agricultural watershed in central New York, SDDH‐VSA results were compared to those from a SDDH model using the traditional land use assumptions for the CN (SDDH‐CN). The SDDH‐VSA model generally agreed better with observed discharge than the SDDH‐CN model (average, Nash‐Sutcliffe efficiency of 0.69 vs. 0.58, respectively) and resulted in more realistic spatial patterns of runoff‐generating areas. The SDDH approach did not correctly capture the timing of runoff from small storms in dry periods. Despite this type of limitation, SDDH‐VSA extends the applicability of the SDDH technique to VSA conditions, providing a basis for new tools to help identify critical management areas and assess water quality risks due to landscape alterations.     

Modeling Hydrology in a Small Rocky Mountain Watershed Serving Large Urban Populations1

Abstract: This article describes the development of a calibrated hydrologic model for the Blue River watershed (867 km²) in Summit County, Colorado. This watershed provides drinking water to over a third of Colorado’s population. However, more research on model calibration and development for small mountain watersheds is needed. This work required integration of subsurface and surface hydrology using GIS data, and included aspects unique to mountain watersheds such as snow hydrology, high ground‐water gradients, and large differences in climate between the headwaters and outlet. Given the importance of this particular watershed as a major urban drinking‐water source, the rapid development occurring in small mountain watersheds, and the importance of Rocky Mountain water in the arid and semiarid West, it is useful to describe calibrated watershed modeling efforts in this watershed. The model used was Soil and Water Assessment Tool (SWAT). An accurate model of the hydrologic cycle required incorporation of mountain hydrology‐specific processes. Snowmelt and snow formation parameters, as well as several ground‐water parameters, were the most important calibration factors. Comparison of simulated and observed streamflow hydrographs at two U.S. Geological Survey gaging stations resulted in good fits to average monthly values (0.71 Nash‐Sutcliffe coefficient). With this capability, future assessments of point‐source and nonpoint‐source pollutant transport are possible.     

iTree‐Hydro: Snow Hydrology Update For The Urban Forest Hydrology Model1

Yang, Yang, Theodore A. Endreny, and David J. Nowak, 2011. iTree‐Hydro: Snow Hydrology Update for the Urban Forest Hydrology Model. Journal of the American Water Resources Association (JAWRA) 47(6):1211–1218. DOI: 10.1111/j.1752‐1688.2011.00564.x Abstract: This article presents snow hydrology updates made to iTree‐Hydro, previously called the Urban Forest Effects—Hydrology model. iTree‐Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process‐based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate hydrology routines presented in this update to iTree‐Hydro include: (1) snow interception to simulate the capture of snow by the vegetation canopy, (2) snow unloading to simulate the release of snow triggered by wind, (3) snowmelt to simulate the solid to liquid phase change using a heat budget, and (4) snow sublimation to simulate the solid to gas phase via evaporation. Cold climate hydrology routines were tested with research‐grade snow accumulation and weather data for the winter of 1996‐1997 at Umpqua National Forest, Oregon. The Nash‐Sutcliffe efficiency for open area snow accumulation was 0.77 and the Nash‐Sutcliffe efficiency for under canopy was 0.91. The USDA Forest Service offers iTree‐Hydro for urban forest hydrology simulation through http://www.iTreetools.org .     

数字旅游初探

数字旅游是一个基于网络环境的旅游信息服务体系,是经济、旅游与信息科学技术的结合,是一门综合性的科学技术.数字旅游一般由关键技术、数字化信息和服务对象等部分组成,主要包括旅游管理信息化、旅游产品信息化、旅游营销信息化、旅游服务信息化、旅游灾难处理和恢复信息化、旅游教育信息化等方面的内容.文章从政策法规等方面探讨了数字旅游的保障体系.     

Runoff Simulation of the Headwaters of the Yellow River Using The SWAT Model With Three Snowmelt Algorithms1

Abstract: The Soil and Water Assessment Tool (SWAT) model combined with different snowmelt algorithms was evaluated for runoff simulation of an 114,345 km² mountainous river basin (the headwaters of the Yellow River), where snowmelt is a significant process. The three snowmelt algorithms incorporated into SWAT were as follows: (1) the temperature‐index, (2) the temperature‐index plus elevation band, and (3) the energy budget based SNOW17. The SNOW17 is more complex than the temperature‐based snowmelt algorithms, and requires more detailed meteorological and topographical inputs. In order to apply the SNOW17 in the SWAT framework, SWAT was modified to operate at the pixel scale rather than the normal Hydrologic Response Unit scale. The three snowmelt algorithms were evaluated under two parameter scenarios, the default and the calibrated parameters scenarios. Under the default parameters scenario, the parameter values were determined based on a review of the current literature. The purpose of this type of evaluation was to assess the applicability of SWAT in ungauged basins, where there is little observed data available for calibration. Under the calibrated parameters scenario, the parameters were calibrated using an automatic calibration program, the Shuffled Complex Evolution (SCE‐UA). The purpose of this type of evaluation was to assess the applicability of SWAT in gauged basins. Two time periods (1975‐1985 and 1986‐1990) of monthly runoff data were used in this study to evaluate the performance of SWAT with different snowmelt algorithms. Under the default parameters scenario, the SWAT model with complex energy budget based SNOW17 performed the best for both time periods. Under the calibrated parameters scenario, the parameters were calibrated using monthly runoff from 1975‐1985 and validated using monthly runoff from 1986‐1990. After parameter calibration, the performance of SWAT with the three snowmelt algorithms was improved from the default parameters scenario. Further, the SWAT model with temperature‐index plus elevation band performed as well as the SWAT model with SNOW17. The SWAT model with temperature‐index algorithm performed the poorest for both time periods under both scenarios. Therefore, it is suggested that the SNOW17 model be used for modeling ungauged basins; however, for gauged basins, the SNOW17 and simple temperature‐index plus elevation band models could provide almost equally good runoff simulation results.     

氧化镁湿法烟气脱硫废水处理技术探讨

介绍了镁法脱硫技术的发展,以及镁法脱硫废水处理系统的特点和处理工艺。