关于岩石圈有效弹性厚度的地质理解

简要回顾了岩石圈均衡理论的发展及岩石圈区域均衡和挠曲理论在岩石圈动力学研究中起的作用,阐述岩石圈有效弹性厚度(Te)的概念和特征。强调Te的研究是地质学和地球物理学的紧密结合,即通过岩石圈挠曲理论和区域均衡原理,对地形和重力资料进行谱分析计算,来获取岩石圈的物理性质信息。计算的Te(和相应的挠曲刚度)是岩石圈等效的强度,与爆破地震、地震层析成像和大地电磁测深等方法观测到的岩石圈和地壳厚度不同,它们之间只有通过岩石圈的屈服刚度包络面(YSE)才能比较。大洋和大陆岩石圈YSE的理论计算,表明Te值显著小于地震学的地壳和岩石圈厚度。尤其对于大陆岩石圈,地壳厚度、热年龄和应变率均可显著影响岩石圈的强度。本文还以滇西为实例介绍了对相干值曲线计算的新认识和当前岩石圈Te研究的最新趋势。     

WATER QUALITY STUDIES IN MALAYSIAN DISUSED MAN MADE LAKFS FOR SUITABILITY OF AN AQUACULTURE PROJECT

A study has been conducted on the status of water quality in two disused man made lakes, which have potential for cage aquaculture project. This study highlights the quality of water analyzed with reference to various physical - chemical parameters in two selected lakes and their suitability for fish farming. A number of parameters were measured including the amount of NH3 - N, NO3 - N, NO2 - N and total phosphorus while in - situ measurement including DO, pH, temperature, conductivity, TDS and Secchi disk visibility. Beside the physical -chemical of water, the location, morphometry and climate conditions were also investigated. The chemical data analyzed for six months indicated that Lake A and Lake B are characterized by relatively high DO, slightly neutral pH and low TSS. The concentration of NH3 -N and NO2 -N was very low （0. 058 mg/L and 0. 04 mg/L, respectively） and total phosphorus was usually in low concentration and sometimes would seem negligible. Besides, NO3 - N occurred in slightly higher concentration （1.75 mg/L）. Results obtained indicated that the study site has high potentiality for development of inland fisheries practices.     

元江-红河跨境水质环境问题和保护研究

在红河干流不同污染流域,设立5个环境监测断面,同时选定人烟稀少、无工业、自然条件良好的李仙江加禾断面为对照。利用1999～2002年对水质影响大的DO、COD、BOD5、NH 3-N、NO3-N、NO 2-N、Cu、Pb、Cd、T-P、石油类及SS 12项污染物,均在枯、丰、平3个不同水期采样监测,将监测结果做数理统计分析,研究污染物的迁移、转化规律,并得出:出境断面NH 3-N平均含量高达0.18～0.86m gL/,T-P高达0.045～0.315m g/L,SS高达69～3412m gL/,从而提出小流域治理、退耕还林、城市水网改造及控制含磷洗涤剂使用的建议。     

Characterizing and classifying urban watersheds with compositional and structural attributes

Current land-use classifications used to assess urbanization effects on stream water quality date back to the 1980s when limited information was available to characterize watershed attributes that mediate non-point source pollution. With high resolution remote sensing and widely used GIS tools, there has been a vast increase in the availability and precision of geospatial data of built environments. In this study, we leverage geospatial data to expand the characterization of developed landscapes and create a typology that allows us to better understand the impact of complex developed landscapes across the rural to urban gradient. We assess the ability of the developed landscape typology to reveal patterns in stream water chemistry previously undetected by traditional land-cover based classification. We examine the distribution of land-cover, infrastructure, topography and geology across 3876 National Hydrography Dataset Plus catchments in the Piedmont region of North Carolina, USA. From this dataset, we generate metrics to evaluate the abundance, density and position of landscape features relative to streams, catchment outlets and topographic wetness metrics. While impervious surfaces are a key distinguishing feature of the urban landscape, sanitary infrastructure, population density and geology are better predictors of baseflow stream water chemistry. Unsupervised clustering was used to generate a distinct developed landscape typology based on the expanded, high-resolution landscape feature information. Using stream chemistry data from 37 developed headwater catchments, we compared the baseflow water chemistry grouped by traditional land-cover based classes of urbanization (rural, low, medium and high density) to our composition and structure-based classification (a nine-class typology). The typology based on 22 metrics of developed landscape composition and structure explained over 50% of the variation in NO₃⁻-N, TDN, DOC, Cl⁻, and Br⁻ concentration, while the ISC-based classification only significantly explained 23% of the variation in TDN. These results demonstrate the importance of infrastructure, population and geology in defining developed landscapes and improving discrete classes for water management.     

Three dimensional numerical simulation of residential building on shrink–swell soils in response to climatic conditions

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.     

Estimation of daily stream water temperatures with a Bayesian regression approach

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.     

The role of baseflow in dissolved solids delivery to streams in the Upper Colorado River Basin

Salinity has a major effect on water users in the Colorado River Basin, estimated to cause almost $300 million per year in economic damages. The Colorado River Basin Salinity Control Program implements and manages projects to reduce salinity loads, investing millions of dollars per year in irrigation upgrades, canal projects, and other mitigation strategies. To inform and improve mitigation efforts, there is a need to better understand sources of salinity to streams and how salinity has changed over time. This study explores salinity in the baseflow fraction of streamflow, assessing whether groundwater is a significant contributor of dissolved solids to streams in the Upper Colorado River Basin (UCRB). Chemical hydrograph separation was used to estimate baseflow discharge and baseflow dissolved solids loads at stream gages (n = 69) across the UCRB. On average, it is estimated that 89% of dissolved solids loads originate from the baseflow fraction of streamflow, indicating that subsurface transport processes play a dominant role in delivering dissolved solids to streams in the UCRB. A statistical trend analysis using weighted regressions on time, discharge, and season was used to evaluate changes in baseflow dissolved solids loads in streams (n = 27) from 1986 to 2011. Decreasing trends in baseflow dissolved solids loads were observed at 63% of streams. At the three most downstream sites, Green River at Green River, UT, Colorado River at Cisco, UT, and the San Juan River near Bluff, UT, baseflow dissolved solids loads decreased by a combined 823,000 metric tons (mT), which is approximately 69% of projected basin‐scale decreases in total dissolved solids loads as a result of salinity control efforts. Decreasing trends in baseflow dissolved solids loads suggest that salinity mitigation projects, landscape changes, and/or climate are reducing dissolved solids transported to streams through the subsurface. Notably, the pace and extent of decreases in baseflow dissolved solids loads declined during the most recent decade; average decreasing loads during the 2000s (28,200 mT) were only 54% of average decreasing loads in the 1990s (51,700 mT).     

Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

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.     

Using hydrogeochemical signatures of stream water to assess pathways for rainfall events: towards a predictive model

Thanks to its simple division into agricultural and forestry land use, the Corbeira catchment (Galicia, Spain) is used as a case study to build a predictive model using hydrogeochemical signatures. Stream data acquired under recessional flow conditions over a one year period were obtained from a sampling station near the downstream end of the catchment, and using principal component analysis, it is shown that some of the analytical parameters are covariant, and some are negatively correlated. These findings support inferences about the pathways of rainfall in the catchment. Specific signatures may be associated with the dominant hydrological source, either surface runoff or subsurface waters: additionally, the dominant land use in that part of the catchment, where the flow originated, can also be predicted. The dominant runoff shows a strong covariance between suspended solids (SS) and particulate phosphorus (PP), with a clear negative correlation with pH. Dissolved organic carbon (DOC) data are associated with this covariant set when these compounds are available in the soils in question. Dissolved phosphorus, total organic nitrogen and dissolved nitrates are also associated with the same covariant set when the runoff flows through areas of extensive agricultural use. The SS ? PP covariance is less significant at lower flows. Typical base flow regimes show a significant covariance between salinity and pH, with a marked negative correlation with SS ? PP set, confirming the dominance of subsurface waters in the baseflow, as expected. Seasonally divergent DOC ? SS behaviour proves to be a useful tracer for rainfall regimes. The DOC trend shows a sinusoidal annual variation in amplitude, determined by the rainfall regime. As a result, flow from the catchment is dominated by surface water whenever there is synchronicity between the peaks of DOC and SS. Copyright © 2013 John Wiley & Sons, Ltd.     

Trends and multi‐annual variability of water temperatures in the river Danube,Serbia

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.