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1.
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   
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The aim of this study is to develop a two-dimensional hydrodynamic tidal model for the Persian Gulf (PG2017) using 2D-MIKE21 software. The advantages of present study is accounting for the spatial variation of bed friction coefficient besides a precise bathymetry together with a 23-year of combined records of satellite altimetry data. We found that the bed friction coefficient has a significant effect on sea level changes in the region under our modeling consideration. Since the tidal behavior in the northern part of the Qeshm Island is significantly different from the other parts of the Persian Gulf, to present a more accurate hydrodynamic tidal model, the Gulf is divided into two regions where the bed friction coefficient is modeled separately for each region. The root mean square value of the differences between the amplitude of dominant constituents; M2, S2, K1, and O1 derived from the PG2017 model and that of 98 altimetry and coastal tide gauge stations are respectively equal to 1.6, 1.9, 2.8, and 1.3?cm. Moreover, comparing the PG2017 model efficiency with the FES2014, OSU12, EOT11a, DTU10, and Admiralty models shows that the PG2017 model has an improvement of 22.1%, 47.2%, 43.2%, 44.2%, and 57.6% in terms of relative error, respectively.  相似文献   
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Most stochastic weather generators have their focus on precipitation because it is the most important variable affecting environmental processes. One of the methods to reproduce the precipitation occurrence time series is to use a Markov process. But, in addition to the simulation of short-term autocorrelations in one station, it is sometimes important to preserve the spatial linear correlations (SLC) between neighboring stations as well. In this research, an extension of one-site Markov models was proposed to preserve the SLC between neighboring stations. Qazvin station was utilized as the reference station and Takestan (TK), Magsal, Nirougah, and Taleghan stations were used as the target stations. The performances of different models were assessed in relation to the simulation of dry and wet spells and short-term dependencies in precipitation time series. The results revealed that in TK station, a Markov model with a first-order spatial model could be selected as the best model, while in the other stations, a model with the order of two or three could be selected. The selected (i.e., best) models were assessed in relation to preserving the SLC between neighboring stations. The results depicted that these models were very capable in preserving the SLC between the reference station and any of the target stations. But, their performances were weaker when the SLC between the other stations were compared. In order to resolve this issue, spatially correlated random numbers were utilized instead of independent random numbers while generating synthetic time series using the Markov models. Although this method slightly reduced the model performances in relation to dry and wet spells and short-term dependencies, the improvements related to the simulation of the SLC between the other stations were substantial.  相似文献   
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Human health is strongly influenced by water quality which is threatened by the poor quality of polluted groundwater. In this study, the groundwater quality and its suitability for drinking have been studied in Lenjanat plain aquifer, Iran. Fifty-nine groundwater samples from study area were evaluated based on WHO and Iranian standards for drinking water. Groundwater samples from selected monitoring sources were sampled seasonally during 2009–2010. Physical and chemical parameters of groundwater such as electrical conductivity, pH, total dissolved solids, Ca2+, Na+, K+, Mg2+, HCO3 ?, SO4 2?, Cl?, F? and NO3 ? were determined. During the water quality index calculating process, the weight of each parameter is usually given by experts according to their practical experience, which is subjective, so much useful and valuable information about the water quality gets lost. In order to avoid personal judgments about the weight of parameters, an information entropy method was used to assign weight to each parameter. Calculation of entropy weighted water quality index (EWQI) for groundwater samples showed that in the wet season, over 57 and 74 % of samples were in the range of “excellent” to “medium” quality based on WHO and Iranian standards, respectively. Due to groundwater quality reduction during dry season, 42 and 62 % of samples were in the range of “excellent” to “medium” quality based on WHO and Iranian standards, respectively. The results indicate that application of the EWQI is very useful to help the public and decision-makers will be able to identify and to evaluate groundwater quality in Lenjanat, Iran.  相似文献   
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Climate extreme and its linkage to regional drought over Idaho, USA   总被引:2,自引:0,他引:2  
To investigate consequences of climate extreme and variability on agriculture and regional water resource, twenty-seven climatic indices of temperature and precipitation over Idaho, USA, were computed. Precipitation, mean temperature and maximum temperature, self-calibrated Palmer Drought Index and Standardized Precipitation Index for 1-, 3-, 6- and 12-month time scales were used to identify spatial and temporal distribution of climatic extreme and variability as well as drought frequency and magnitude. Seven oceanic indices were also used to detect teleconnections between climatic indices and regional droughts. The analyses were conducted for 56 meteorological stations, during 1962?C2008, characterized by a long-term and high-quality data set. The result indicates that decreasing trends and increasing trends are identified for precipitation and temperature, respectively. Consequently, it appears that frost and ice days dwindle as growing season (May?CAugust) length, tropical nights and summer days increase. Given current climate conditions, the results also imply that these trends will continue in the future possibly driven by uncertain climate variability. We anticipate that these indices explained by teleconnections will improve drought-forecasting capability in this region.  相似文献   
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This paper is devoted to investigate the effects of near‐fault ground motions on the seismic responses of nonlinear MDOF structures considering soil‐structure interaction (SSI). Attempts are made to take into account the effects of different frequency‐content components of near‐fault records including pulse‐type (PT) and high‐frequency (HF) components via adopting an ensemble of 54 near‐fault ground motions. A deep sensitivity analysis is implemented based on the main parameters of the soil‐structure system. The soil is simulated based on the Cone model concept, and the superstructure is idealized as a nonlinear shear building. The results elucidate that SSI has approximately increasing and mitigating effects on structural responses to the PT and HF components, respectively. Also, a threshold period exists above which the HF component governs the structural responses. As the fundamental period of the structure becomes shorter and structural target ductility reduces, the contribution of the HF component to the structural responses increases, elaborately. Soil flexibility makes the threshold period increase, and the effect of the PT component becomes more significant than the HF one. In the case of soil‐structure system, slenderizing the structure also increases this threshold period and causes the PT component to be dominant. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   
9.
Long-period pulses in near-field earthquakes lead to large displacements in the base of isolated structures.To dissipate energy in isolated structures using semi-active control,piezoelectric friction dampers(PFD) can be employed.The performance of a PFD is highly dependent on the strategy applied to adjust its contact force.In this paper,the seismic control of a benchmark isolated building equipped with PFD using PD/PID controllers is developed.Using genetic algorithms,these controllers are optimized to create a balance between the performance and robustness of the closed-loop structural system.One advantage of this technique is that the controller forces can easily be estimated.In addition,the structure is equipped with only a single sensor at the base floor to measure the base displacement.Considering seven pairs of earthquakes and nine performance indices,the performance of the closed-loop system is evaluated.Then,the results are compared with those given by two well-known methods:the maximum possive operation of piezoelectric friction dampers and LQG controllers.The simulation results show that the proposed controllers perform better than the others in terms of simultaneous reduction of floor acceleration and maximum displacement of the isolator.Moreover,they are able to reduce the displacement of the isolator systems for different earthquakes without losing the advantages of isolation.  相似文献   
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Providing safety in roads for the purpose of protecting human assets and preventing social and economic losses resulted from road accidents is a significant issue. Identifying the traffic hot spots of the roads provides the possibility of promoting the road safety which is also related to investigate frequency and intensity of occurred accidents. Accidents are multidimensional and complicated events. Identifying the accident factors is based on applying a comprehensive and integrated system for making decisions. Therefore, applying common mathematical and statistical methods in this field can be resulted in some problems. Hence, the new research methods with abilities to infer meaning from complicated and ambiguous data seem useful. Therefore, along with identifying the traffic hot spots, adaptive Neuro-Fuzzy inference system is used to predict traffic hot spots on rural roads. In this process, a fuzzy inference system from Sugeno type is trained applying hybrid optimization routine (back propagation algorithm in combination with a least square type of method) and accident data of Karaj-Chalus road in Tehran Province. Then the system was tested by a complete set of data. Finally, the stated system could predict 96.85 % of accident frequencies in the studied blocks. Furthermore, the amount of effective false negative in all cases included only 0.82 % of predictions, which indicated a good approximation of predictions and model credibility.  相似文献   
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