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101.
Habitat fragmentation in channel networks and riverine ecosystems is increasing globally due to the construction of barriers and river regulation. The resulting divergence from the natural state poses a threat to ecosystem integrity. Consequently, a trade‐off is required between the conservation of biodiversity in channel networks and socio‐economic factors including power generation, potable water supplies, fisheries, and tourism. Many of Scotland's rivers are regulated for hydropower generation but also support populations of Atlantic salmon (Salmo salar L.) that have high economic and conservation value. This paper investigates the use of connectivity metrics and weightings to assess the impact of river barriers (impoundments) associated with hydropower regulation on natural longitudinal channel connectivity for Atlantic salmon. We applied 2 different weighting approaches in the connectivity models that accounted for spatial variability in habitat quality for spawning and fry production and contrasted these models with a more traditional approach using wetted area. Assessments of habitat loss using the habitat quality weighted models contrasted with those using the less biologically relevant wetted area. This highlights the importance of including relevant ecological and hydrogeomorphic information in assessing regulation impacts on natural channel connectivity. Specifically, we highlight scenarios where losing a smaller area of productive habitat can have a larger impact on Atlantic salmon than losing a greater area of less suitable habitat. It is recommended that future channel connectivity assessments should attempt to include biologically relevant weightings, rather than relying on simpler metrics like wetted area which can produce misleading assessments of barrier impacts.  相似文献   
102.
Shrink–swell soils can cause distresses in buildings, and every year, the economic loss associated with this problem is huge. This paper presents a comprehensive system for simulating the soil–foundation–building system and its response to daily weather conditions. Weather data include rainfall, solar radiation, air temperature, relative humidity, and wind speed, all of which are readily available from a local weather station or the Internet. These data are used to determine simulation flux boundary conditions. Different methods are proposed to simulate different boundary conditions: bare soil, trees, and vegetation. A coupled hydro‐mechanical stress analysis is used to simulate the volume change of shrink–swell soils due to both mechanical stress and water content variations. Coupled hydro‐mechanical stress‐jointed elements are used to simulate the interaction between the soil and the slab, and general shell elements are used to simulate structural behavior. All the models are combined into one finite element program to predict the entire system's behavior. This paper first described the theory for the simulations. A site in Arlington, Texas, is then selected to demonstrate the application of the proposed system. Simulation results are shown, and a comparison between measured and predicted movements for four footings in Arlington, Texas, over a 2‐year period is presented. Finally, a three‐dimensional simulation is made for a virtual residential building on shrink–swell soils to identify the influence of various factors. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   
103.
Stream water temperature plays a significant role in aquatic ecosystems where it controls many important biological and physical processes. Reliable estimates of water temperature at the daily time step are critical in managing water resources. We developed a parsimonious piecewise Bayesian model for estimating daily stream water temperatures that account for temporal autocorrelation and both linear and nonlinear relationships with air temperature and discharge. The model was tested at 8 climatically different basins of the USA and at 34 sites within the mountainous Boise River Basin (Idaho, USA). The results show that the proposed model is robust with an average root mean square error of 1.25 °C and Nash–Sutcliffe coefficient of 0.92 over a 2‐year period. Our approach can be used to predict historic daily stream water temperatures in any location using observed daily stream temperature and regional air temperature data.  相似文献   
104.
Developing an appropriate data collection scheme to infer stream–subsurface interactions is not trivial due to the spatial and temporal variability of exchange flowpaths. Within the context of a case study, this paper presents the results from a number of common data collection techniques ranging from point to reach scales used in combination to better understand the spatial complexity of subsurface exchanges, infer the hydrologic conditions where individual influences of hyporheic and groundwater exchange components on stream water can be characterized, and determine where gaps in information arise. We start with a tracer‐based, longitudinal channel water balance to quantify hydrologic gains and losses at a sub‐reach scale nested within two consecutive reaches. Next, we look at groundwater and stream water surface levels, shallow streambed vertical head gradients, streambed and aquifer hydraulic conductivities, water chemistry, and vertical flux rates estimated from streambed temperatures to provide more spatially explicit information. As a result, a clearer spatial understanding of gains and losses was provided, but some limitations in interpreting results were identified even when combining information collected over various scales. Due to spatial variability of exchanges and areas of mixing, each technique frequently captured a combination of groundwater and hyporheic exchange components. Ultimately, this study provides information regarding technique selection, emphasizes that care must be taken when interpreting results, and identifies the need to apply or develop more advanced methods for understanding subsurface exchanges. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
105.
River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction is a main issue in many environmental applications, which however is hampered by data scarcity, when using data‐demanding deterministic models, and modelling limitations, when using simpler statistical models. In this work we test a suite of models belonging to air2stream family, which are characterized by a hybrid formulation that combines a physical derivation of the key equation with a stochastic calibration of parameters. The air2stream models rely solely on air temperature and streamflow, and are of similar complexity as standard statistical models. The performances of the different versions of air2stream in predicting river water temperature are compared with those of the most common statistical models typically used in the literature. To this aim, a dataset of 38 Swiss rivers is used, which includes rivers classified into four different categories according to their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed rivers and regulated rivers. The results of the analysis provide practical indications regarding the type of model that is most suitable to simulate river water temperature across different time scales (from daily to seasonal) and for different hydrological regimes. A model intercomparison exercise suggests that the family of air2stream hybrid models generally outperforms statistical models, while cross‐validation conducted over a 30‐year period indicates that they can be suitably adopted for long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
106.
To investigate the sources of particulate organic matter (POM) and the impact of Three Gorges Dam (TGD), two large lakes and erosion processes on determining the composition and flux of POM in low water discharge periods along the middle and lower Changjiang, suspended particulate samples were collected along the middle and lower reaches of the Changjiang (Yangtze River) in January 2008. Organic geochemistry of bulk sediment (particulate organic carbon, organic carbon to nitrogen molar ratio (C/N), stable carbon isotope (δ13C) and grain size) and biomarker of bulk sediment (lignin phenols) were measured to trace the sources of POM. The range of C/N ratios (6.4–8.9), δ13C (?24.3‰ – ?26.2‰) and lignin phenols concentration Λ8 (0.45 mg/100 mg OC‐2.00 mg/100 mg OC) of POM suggested that POM originated from the mixture of soil, plant tissue and autochthonous organic matter (OM) during the dry season. POM from lakes contained a higher portion of terrestrial OM than the mainstream, which was related to sand mining and hydropower erosion processes. A three end‐member model based on δ13C and Λ8 was performed. The results indicated that soil contributed approximately 50% of OM to the POM, which is the dominant OM source in most stations. POM composition was affected by total suspended matter (TSM) and grain size composition, and the direct OM input from two lakes and channel erosion induced OM. The lower TSM concentration in January 2008 was mainly caused by seasonal variations; the impact from the TGD in the dry season was relatively small. A box model indicated that more than 90% of the terrestrial OM transported by the Changjiang in January 2008 was from the middle and lower drainage basins. Channel erosion induced OM, and contributions from Poyang Lake were the major terrestrial OM sources in the dry season. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
107.
The relationship between air (Ta) and water temperature (Tw) is very important because it shows how the temperature of a water body might respond to future changes in surface Ta. Mean monthly Tw records of three gauging stations (Bezdan, Bogojevo i Veliko Gradi?te) were analysed alongside mean monthly discharge (Q) for the same stations. Additionally, Ta series from two meteorological stations (Sombor and Veliko Gradi?te) were correlated with Tw variations over the period 1950–2012. Locally weighted scatter point smoothing (LOWESS) was used to investigate long‐term trends in the raw data, alongside the Mann–Kendall (MK) trend test. Trend significance was established using Yue–Pilon's pre‐whitening approaches to determine trends in climate data. Also, the rescaled adjusted partial sums (RAPS) method was used to detect dates of possible changes in the time series. Statistically significant warming trends were observed for annual and seasonal minimum and maximum Tw at all investigated sites. The strongest warming was observed at Bogojevo gauging station for seasonal maximum Tw, with +0.05 °C per year on average. RAPS established that the trend began in the 1980s. This behaviour is linked to climate patterns in the North and East Atlantic which determine the amount of heat advected onto mainland Europe. Statistically significant correlations were found for all Tw on an annual basis. Overall, the strongest correlations (p < 0.01) between Tw residuals and the North Atlantic Oscillation (NAO) were recorded for the winter period. These findings suggest possible predictability of Tw over seasonal time‐scales. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   
108.
Recent research into flood modelling has primarily concentrated on the simulation of inundation flow without considering the influences of channel morphology. River channels are often represented by a simplified geometry that is implicitly assumed to remain unchanged during flood simulations. However, field evidence demonstrates that significant morphological changes can occur during floods to mobilize the boundary sediments. Despite this, the effect of channel morphology on model results has been largely unexplored. To address this issue, the impact of channel cross‐section geometry and channel long‐profile variability on flood dynamics is examined using an ensemble of a 1D–2D hydraulic model (LISFLOOD‐FP) of the ~1 : 2000 year recurrence interval floods in Cockermouth, UK, within an uncertainty framework. A series of simulated scenarios of channel erosional changes were constructed on the basis of a simple velocity‐based model of critical entrainment. A Monte‐Carlo simulation framework was used to quantify the effects of this channel morphology together with variations in the channel and floodplain roughness coefficients, grain size characteristics and critical shear stress on measures of flood inundation. The results showed that the bed elevation modifications generated by the simplistic equations reflected an approximation of the observed patterns of spatial erosion that enveloped observed erosion depths. The effect of uncertainty on channel long‐profile variability only affected the local flood dynamics and did not significantly affect the friction sensitivity and flood inundation mapping. The results imply that hydraulic models generally do not need to account for within event morphodynamic changes of the type and magnitude of event modelled, as these have a negligible impact that is smaller than other uncertainties, e.g. boundary conditions. Instead, morphodynamic change needs to happen over a series of events to become large enough to change the hydrodynamics of floods in supply limited gravel‐bed rivers such as the one used in this research. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
109.
A microscale air pollutant dispersion model system is developed for emergency response purposes. The model includes a diagnostic wind field model to simulate the wind field and a random-walk air pollutant dispersion model to simulate the pollutant concentration through consideration of the influence of urban buildings. Numerical experiments are designed to evaluate the model's performance, using CEDVAL(Compilation of Experimental Data for Validation of Microscale Dispersion Models) wind tunnel experiment data, including wind fields and air pollutant dispersion around a single building. The results show that the wind model can reproduce the vortexes triggered by urban buildings and the dispersion model simulates the pollutant concentration around buildings well. Typically, the simulation errors come from the determination of the key zones around a building or building cluster. This model has the potential for multiple applications; for example, the prediction of air pollutant dispersion and the evaluation of environmental impacts in emergency situations; urban planning scenarios;and the assessment of microscale air quality in urban areas.  相似文献   
110.
基于贝叶斯模型的中国未来气温变化预估及不确定性分析   总被引:3,自引:0,他引:3  
利用第5次耦合模式比较计划(CMIP5)中35个全球气候模式历史模拟与RCP4.5预估结果,通过贝叶斯模型平均(Bayesian Model Averaging,BMA)对中国气温进行多模式集合研究,给出了中国未来气温变化预估及其不确定性的时空分布。结果表明,中国21世纪冬夏将持续升温,且升温具有冬季高于夏季,北方高于南方的特点。初期(2016—2035年)北方有很大可能(80%)升温超过0.7℃,南方升温相同幅度的概率则超过50%;中期(2046—2065年)北方和南方升温超过1.5℃的概率分别为80%和50%;末期(2081—2100年),北方(南方)有80%(50%)的可能的升温超过2℃。气温预估的不确定性研究发现,无论冬夏,21世纪不同时期升温相对较弱的塔里木盆地、青藏高原南侧和中国东南地区为不确定性低值区,基本低于0.6℃,对应可信度较高,如21世纪初期信噪比超过4;而不确定性的高值区则主要分布在新疆北部、东北平原北部和青藏高原东南侧等升温相对较大的地区,普遍高于1℃,对应可信度较低,如初期信噪比低于2.5。此外,基于信噪比对比发现除青藏高原东部外,其他区域夏季预估的可信度均高于冬季,21世纪末期高于初期,且空间分布特征一致。  相似文献   
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