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Arild Holt-Jensen 《GeoJournal》2000,51(4):281-291
Changes in the urban social geography; the development of urban neighbourhoods of multiple deprivation, in which different processes of social exclusion reinforce one another, is a grave challenge to the European society. Housing initiatives and local neighbourhood practices seem to be key factors in finding solutions in combating social exclusion and improving the quality of life in deprived urban neighbourhoods. The OECD-report `Integrating distressed urban areas' (Paris, 1998) states that a combination of policies focusing on specific urban areas and more general socio-economic measures are necessary to integrate such areas into the fabric of the cities. This evaluation of bottom-up neighbourhood solutions, within their national contexts, is the central focus of a European research project (NEHOM) involving housing researchers and providers in 8 European countries. Pilot case studies have been undertaken in United Kingdom, Norway and Hungary to test a common case study methodology. Using a range of indicators of improvements in the quality of life in case study areas, the research will seek to identify innovative housing initiatives and neighbourhood practices, as well as a toolkit for neighbourhood assessment and improvement. A special challenge for the research project is to assess and identify opportunities for and barriers to transferability of best practices and housing policies between European countries. 相似文献
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ABSTRACTThere is an implicit assumption in most work that the parameters calibrated based on observations remain valid for future climatic conditions. However, this might not be true due to parameter instability. This paper investigates the uncertainty and transferability of parameters in a hydrological model under climate change. Parameter transferability is investigated with three parameter sets identified for different climatic conditions, which are: wet, intermediate and dry. A parameter set based on the baseline period (1961–1990) is also investigated for comparison. For uncertainty analysis, a k-simulation set approach is proposed instead of employing the traditional optimization method which uses a single best-fit parameter set. The results show that the parameter set from the wet sub-period performs the best when transferred into wet climate condition, while the parameter set from the baseline period is the most appropriate when transferred into dry climate condition. The largest uncertainty of simulated daily high flows for 2011–2040 is from the parameter set trained in the dry sub-period, while that of simulated daily medium and low flows lies in the parameter set from the intermediate calibration sub-period. For annual changes in the future period, the uncertainty with the parameter set from the intermediate sub-period is the largest, followed by the wet sub-period and dry sub-period. Compared with high and medium flows/runoffs, the uncertainty of low flows/runoffs is much smaller for both simulated daily flows and annual runoffs. For seasonal runoffs, the largest uncertainty is from the intermediate sub-period, while the smallest is from the dry sub-period. Apart from that, the largest uncertainty can be observed for spring runoffs and the lowest one for autumn runoffs. Compared with the traditional optimization method, the k-simulation set approach shows many more advantages, particularly being able to provide uncertainty information to decision support for watershed management under climate change.
EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR not assigned 相似文献
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Synthetic Aperture Radar (SAR) texture has been demonstrated to have the potential to improve forest biomass estimation using backscatter. However, forests are 3D objects with a vertical structure. The strong penetration of SAR signals means that each pixel contains the contributions of all the scatterers inside the forest canopy, especially for the P-band. Consequently, the traditional texture derived from SAR images is affected by forest vertical heterogeneity, although the influence on texture-based biomass estimation has not yet been explicitly explored. To separate and explore the influence of forest vertical heterogeneity, we introduced the SAR tomography technique into the traditional texture analysis, aiming to explore whether TomoSAR could improve the performance of texture-based aboveground biomass (AGB) estimation and whether texture plus tomographic backscatter could further improve the TomoSAR-based AGB estimation. Based on the P-band TomoSAR dataset from TropiSAR 2009 at two different sites, the results show that ground backscatter variance dominated the texture features of the original SAR image and reduced the biomass estimation accuracy. The texture from upper vegetation layers presented a stronger correlation with forest biomass. Texture successfully improved tomographic backscatter-based biomass estimation, and the texture from upper vegetation layers made AGB models much more transferable between different sites. In addition, the correlation between texture indices varied greatly among different tomographic heights. The texture from the 10 to 30 m layers was able to provide more independent information than the other layers and the original images, which helped to improve the backscatter-based AGB estimation. 相似文献
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Diagnostic calibration and cross‐catchment transferability of a simple process‐consistent hydrologic model 
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下载免费PDF全文 The transferability of hydrologic models is of ever increasing importance for making improved hydrologic predictions and testing hypothesized hydrologic drivers. Here, we present an investigation into the variability and transferability of the recently introduced catchment connectivity model (Smith et al., 2013 ). The catchment connectivity model was developed following extensive experimental observations identifying the key drivers of streamflow in the Tenderfoot Creek Experimental Forest (Jencso et al., 2009 ; Jencso et al., 2010 ), with the goal of creating a simple model consistent with internal observations of catchment hydrologic connectivity patterns. The model was applied across seven catchments located within Tenderfoot Creek Experimental Forest to investigate spatial variability and transferability of model performance and parameterization. The results demonstrated that the model resulted in historically good fits (based on previous studies at the sites) to both the hydrograph and internal water table dynamics (corroborated with experimental observations). The impact of a priori parameter limits was also examined. It was observed that enforcing field‐based limits on model parameters resulted in slight reductions to streamflow hydrograph fits, but significant improvements to model process fidelity (as hydrologic connectivity), as well as moderate improvement in the transferability of model parameterizations from one catchment to the next. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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缢蛏(Sinonovacula constricta)微卫星标记的分离及近缘物种通用性 总被引：1，自引：0，他引：1
采用磁珠富集和PCR筛选相结合的方法,得到12对缢蛏(Sinonovacula constricta)的多态性微卫星引物。每个位点的观测等位基因数为2—15个,有效等位基因数为1.0339—8.8063个;观测杂合度(Ho)为0.0333—1.0000,平均观测杂合度为0.7525;期望杂合度(He)为0.0333—0.9020,平均期望杂合度为0.6866;多态信息含量(PIC)为0.0320—0.8680。所有位点中,有8个位点属于高度多态位点(PIC0.5),SC1-5和SC4-6属于低度多态位点(PIC0.25);经Bonferroni校正后,无显著偏离哈迪-温伯格平衡的位点;连锁不平衡检验结果表明,位点间不存在连锁不平衡现象。此外,分析了这些引物在近缘种长竹蛏(Solen strictus)、大竹蛏(Solen grandis)和小刀蛏(Cultellus attenuatus)的通用性情况,结果显示:长竹蛏中,位点SC1-4、SC2-8、SC3-1、SC3-14表现出了高度多态(PIC0.5);在大竹蛏中,位点SC3-4、SC3-7、SC4-6表现出了高度多态性(PIC0.5),SC2-9为低态位点(PIC0.25);在小刀蛏中,位点SC1-7、SC2-9、SC3-4、SC3-14表现出了高度多态性(PIC0.5),SC4-6为低态位点(PIC0.25)。 相似文献
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Using high‐resolution isotope data and alternative calibration strategies for a tracer‐aided runoff model in a nested catchment 下载免费PDF全文
下载免费PDF全文 Testing hydrological models over different spatio‐temporal scales is important for both evaluating diagnostics and aiding process understanding. High‐frequency (6‐hr) stable isotope sampling of rainfall and runoff was undertaken during 3‐week periods in summer and winter within 12 months of daily sampling in a 3.2‐km2 catchment in the Scottish Highlands. This was used to calibrate and test a tracer‐aided model to assess the (a) information content of high‐resolution data, (b) effect of different calibration strategies on simulations and inferred processes, and (c) model transferability to <1‐km2 subcatchment. The 6‐hourly data were successfully incorporated without loss of model performance, improving the temporal resolution of the modelling, and making it more relevant to the time dynamics of the isotope and hydrometric response. However, this added little new information due to old‐water dominance and riparian mixing in this peatland catchment. Time variant results, from differential split sample testing, highlighted the importance of calibrating to a wide range of hydrological conditions. This also provided insights into the nonstationarity of catchment mixing processes, in relation to storage and water ages, which varied markedly depending on the calibration period. Application to the nested subcatchment produced equivalent parameterization and performance, highlighting similarity in dominant processes. The study highlighted the utility of high‐resolution data in combination with tracer‐aided models, applied at multiple spatial scales, as learning tools to enhance process understanding and evaluation of model behaviour across nonstationary conditions. This helps reveal more fully the catchment response in terms of the different mechanistic controls on both wave celerites and particle velocities. 相似文献
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为获得用于裙带菜种质结构和遗传多样性研究的微卫星标记,采用近缘物种转移法分析了15个海带微卫星引物在裙带菜中的应用情况。对38个裙带菜个体进行多样性分析,结果显示:标记SSR002和SSR115不能扩增裙带菜基因组,位点SSR194能扩增,但不具有多态性,其他12个标记均能扩增裙带菜DNA,且都具有检出多态性,其中9个符合哈迪-温伯格平衡。这9个海带微卫星标记检出的等位基因数为34个,从3～5个不等,平均每个位点扩增得到3.8个等位基因。观测杂合度(Ho)、期望杂合度(He)及多态性信息含量值(PIC)的范围分别为0.238～1.000、0.500～0.692、0.413～0.780,9个位点提供的多态性较高,适用于裙带菜遗传学研究。 相似文献
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High spatial resolution mapping of natural resources is much needed for monitoring and management of species, habitats and landscapes. Generally, detailed surveillance has been conducted as fieldwork, numerical analysis of satellite images or manual interpretation of aerial images, but methods of object-based image analysis (OBIA) and machine learning have recently produced promising examples of automated classifications of aerial imagery. The spatial application potential of such models is however still questionable since the transferability has rarely been evaluated.We investigated the potential of mosaic aerial orthophoto red, green and blue (RGB)/near infrared (NIR) imagery and digital elevation model (DEM) data for mapping very fine-scale vegetation structure in semi-natural terrestrial coastal areas in Denmark. The Random Forest (RF) algorithm, with a wide range of object-derived image and DEM variables, was applied for classification of vegetation structure types using two hierarchical levels of complexity. Models were constructed and validated by cross-validation using three scenarios: (1) training and validation data without spatial separation, (2) training and validation data spatially separated within sites, and (3) training and validation data spatially separated between different sites.Without spatial separation of training and validation data, high classification accuracies of coastal structures of 92.1% and 91.8% were achieved on coarse and fine thematic levels, respectively. When models were applied to spatially separated observations within sites classification accuracies dropped to 85.8% accuracy at the coarse thematic level, and 81.9% at the fine thematic level. When the models were applied to observations from other sites than those trained upon the ability to discriminate vegetation structures was low, with 69.0% and 54.2% accuracy at the coarse and fine thematic levels, respectively.Evaluating classification models with different degrees of spatial correlation between training and validation data was shown to give highly different prediction accuracies, thereby highlighting model transferability and application potential. Aerial image and DEM-based RF models had low transferability to new areas due to lack of representation of aerial image, landscape and vegetation variation in training data. They do, however, show promise at local scale for supporting conservation and management with vegetation mappings of high spatial and thematic detail based on low-cost image data. 相似文献
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Model calibration is important for streamflow simulations using distributed hydrological models, especially in highland and cold areas of northwest China with scarce data. Quantitative analysis of water balance based on the accurate simulation is also essential for reasonably planning and managing water resources in these river basins facing a severe water shortage. In this study, a comprehensive method was proposed to calibrate the Soil and Water Assessment Tool (SWAT) model in the Yingluoxia watershed, upstream area of the Heihe River basin; it was based on multi-temporal, multi-variable and multi-site integrated drainage characteristics. Meanwhile a fresh approach of the parameter transferability and model validation was used by applying the set of calibrated parameters in its tributary to other area of the watershed. The results indicated that the method was effective and feasible; the values of Nash–Sutcliffe Efficiency (NSE) and Coefficient of Determination (r2) were greater than 0.81 and as high as 0.94 and the absolute values of the Percent Bias (PBIAS) were less than 2. Based the output of model the water balance in the Yingluoxia watershed was analyzed, that the mean annual precipitation, evapotranspiration, and discharge of the watershed from 1990 to 2000 were 491.8 mm, 334 mm, and 157.8 mm, respectively. The comprehensive calibration method based on multi-temporal, multi-variable and multi-site integrated drainage characteristics can better portray the hydrological processes of watershed and improve the model simulation; and the output of the model then provide a reliable reference for assessing and managing water resource of the watershed. 相似文献