Modeling Streams and Hydrogeomorphic Attributes in Oregon From Digital and Field Data1

Abstract: Managers, regulators, and researchers of aquatic ecosystems are increasingly pressed to consider large areas. However, accurate stream maps with geo‐referenced attributes are uncommon over relevant spatial extents. Field inventories provide high‐quality data, particularly for habitat characteristics at fine spatial resolutions (e.g., large wood), but are costly and so cover relatively small areas. Recent availability of regional digital data and Geographic Information Systems software has advanced capabilities to delineate stream networks and estimate coarse‐resolution hydrogeomorphic attributes (e.g., gradient). A spatially comprehensive coverage results, but types of modeled outputs may be limited and their accuracy is typically unknown. Capitalizing on strengths in both field and regional digital data, we modeled a synthetic stream network and a variety of hydrogeomorphic attributes for the Oregon Coastal Province. The synthetic network, encompassing 96,000 km of stream, was derived from digital elevation data. We used high‐resolution but spatially restricted data from field inventories and streamflow gauges to evaluate, calibrate, and interpret hydrogeomorphic attributes modeled from digital elevation and precipitation data. The attributes we chose to model (drainage area, mean annual precipitation, mean annual flow, probability of perennial flow, channel gradient, active‐channel width and depth, valley‐floor width, valley‐width index, and valley constraint) have demonstrated value for stream research and management. For most of these attributes, field‐measured, and modeled values were highly correlated, yielding confidence in the modeled outputs. The modeled stream network and attributes have been used for a variety of purposes, including mapping riparian areas, identifying headwater streams likely to transport debris flows, and characterizing the potential of streams to provide high‐quality habitat for salmonids. Our framework and models can be adapted and applied to areas where the necessary field and digital data exist or can be obtained.     

Stream Temperature Relationships to Forest Harvest in Western Washington1

Abstract: We compared summer stream temperature patterns in 40 small forested watersheds in the Hoh and Clearwater basins in the western Olympic Peninsula, Washington, to examine correlations between previous riparian and basin‐wide timber harvest activity and stream temperatures. Seven watersheds were unharvested, while the remaining 33 had between 25% and 100% of the total basin harvested, mostly within the last 40 years. Mean daily maximum temperatures were significantly different between the harvested and unharvested basins, averaging 14.5°C and 12.1°C, respectively. Diurnal fluctuations between harvested and unharvested basins were also significantly different, averaging 1.7°C and 0.9°C, respectively. Total basin harvest was correlated with average daily maximum temperature (r² = 0.39), as was total riparian harvest (r² = 0.32). The amount of recently clear‐cut riparian forest (<20 year) within 600 m upstream of our monitoring sites ranged from 0% to 100% and was not correlated to increased stream temperatures. We used Akaike’s Information Criteria (AIC) analysis to assess whether other physical variables could explain some of the observed variation in stream temperature. We found that variables related to elevation, slope, aspect, and geology explain between 5% and 14% more of the variability relative to the variability explained by percent of basin harvested (BasHarv), and that the BasHarv was consistently a better predictor than the amount of riparian forest harvested. While the BasHarv is in all of the models that perform well, the AIC analysis shows that there are many models with two variables that perform about the same and therefore it would be difficult to choose one as the best model. We conclude that adding additional variables to the model does not change the basic findings that there is a relatively strong relationship between maximum daily stream temperatures and the total amount of harvest in a basin, and strong, but slightly weaker relationship between maximum daily stream temperatures and the total riparian harvest in a basin. Seventeen of the 40 streams exceeded the Washington State Department of Ecology’s (DOE) temperature criterion for waters defined as “core salmon and trout habitat” (class AA waters). The DOE temperature criterion for class AA waters is any seven‐day average of daily maximum temperatures in excess of 16°C. The probability of a stream exceeding the water quality standard increased with timber harvest activity. All unharvested sites and five of six sites that had 25‐50% harvest met DOEs water quality standard. In contrast, only nine of eighteen sites with 50‐75% harvest and two of nine sites with >75% harvest met DOEs water quality standard. Many streams with extensive canopy closure, as estimated by the age of riparian trees, still had higher temperatures and greater diurnal fluctuations than the unharvested basins. This suggests that the impact of past forest harvest activities on stream temperatures cannot be entirely mitigated through the reestablishment of riparian buffers.     

GIS As A Tool For Assessing The Influence Of Countryside Designations and Planning Policies On Landscape Change

The county of Bedfordshire is typical of landscape in lowland England with land cover dominant over land form and agriculture forming the major land use. Landscape change can be influenced by planning policies through their control of land use. A number of designated areas such as Areas of Great Landscape Value, Areas of Outstanding Natural Beauty and Green Belt have been defined where particular planning priorities for the conservation of the countryside apply. This paper reports work where an attempt has been made to measure the influence of these designations on landscape change using the tools of aerial photograph interpretation and Geographic Information Systems (GIS). Aerial photographs were available for the study area for 1968, 1981 and 1991. These were interpreted to a landscape classification scheme in terms of point, linear and area features such as trees, hedgerows and cultivated land, respectively. Field work was carried out to assess the accuracy of the interpretation. The resulting data were input to a GIS for each date of photography. Digital maps were created for the land cover features and tables were generated of lengths of linear features or counts of point features for each kilometre square in the study area. Spatial analysis tools provided by the GIS were used to describe the landscape character of each of the designated areas and then to measure the change that had taken place within them over the time period defined by the photography. Areas which were not designated for conservation of scenic beauty were shown to be poorer in traditional landscape features.     

A spatially explicit framework for quantifying downstream hydrologic conditions

Continued improvements in spatial datasets and hydrological modeling algorithms within Geographic Information Systems (GISs) have enhanced opportunities for watershed analysis. With more detailed hydrology layers and watershed delineation techniques, we can now better represent and model landscape to water quality relationships. Two challenges in modeling these relationships are selecting the appropriate spatial scale of watersheds for the receiving stream segment, and handling the network or pass-through issues of connected watersheds. This paper addresses these two important issues for enhancing cumulative watershed capabilities in GIS. Our modeling framework focuses on the delineation of stream-segment-level watershed boundaries for 1:24 000 scale hydrology, in combination with a topological network model. The result is a spatially explicit, vector-based, spatially cumulative watershed modeling framework for quantifying watershed conditions to aid in restoration. We demonstrate the new insights available from this modeling framework in a cumulative mining index for the management of aquatic resources in a West Virginia watershed.     

高分辨率遥感影像的土地利用分类

高分辨率遥感影像在我国土地利用动态监测中展现出良好的应用前景,但与此相关的关键技术问题亟待解决.结合Ikonos影像,分析高分辨率遥感影像的特点,并在我国土地利用现状类型划分的基础上,针对高分辨遥感影像土地利用分类这一关键技术问题,概述常规分类方法,提出一套适宜高分辨率遥感影像土地利用分类的技术路线.     

基于ArcView的人机交互式土地资源遥感解译方法

对于大型复杂的土地资源遥感判读任务,传统的人工目视解译和常规的计算机遥感图像分析处理都难以满足这一要求。人机交互式判读解译方法使人与计算机相互配合,充分发挥各自的优势,可更准确有效地对遥感图像进行解译。运用ArcView软件进行土地资源遥感图像的人机交互式解译,探讨了该方法的实现过程和主要特点。     

基于模糊聚类的生态功能区若干指标定量划分的研究

以江苏省沿东陇海线地区为研究区域,利用遥感与G IS工具,研究基于模糊聚类与若干定量指标的生态功能区划方法。该方法选取了5个指标用于区划过程,首先将研究区域分成5×5km大小的空间单元,并提取各单元属性数据生成属性矩阵,利用M atlab模糊逻辑工具箱对单元进行模糊聚类。参照聚类结果与其他资料进行了生态功能区划,并根据区划结果对各分区的产业发展与生态保护提出了建议。     

基于GIS的芜湖市城市用地扩展规律

利用芜湖市1990年、2000年两个时相的遥感影像进行城市土地利用解译,提取城市新、旧建成区区块用地,通过GIS软件提供的空间统计分析功能,对城市用地空间分布进行定量分析与描述,从而揭示城市用地及其扩展规律.研究结果表明,芜湖市用地扩展呈现明显中心圈层式蔓延和轴向集中性扩展规律的模式.作者提出了城市用地扩展中应注意解决的问题.