Numerical model of convection in sills

The numerical model of convection in magma sills is developed. The model is based on a full system of equations of fluid dynamics and includes heat transfer, buoyancy effects and diffusion of some minor component (marker). Solidification is treated as a phase transition. The results indicate that there are some qualitative differences between very thin sills with Rayleigh number Ra = 10⁵ and thin sills with Ra = 10⁶. For a basaltic magma the first case corresponds to the thickness of the sills of approximately 30 cm and the second case corresponds to the thickness of 60 cm. In the first case mixing is inefficient and conduction is the dominant form of heat transfer. In the second case mixing is efficient and convection is the dominant form of heat transfer. Some of the results can be scaled for the more viscous magmas in thicker sills.     

Deep Mechanical Background for the Cenozoic Volcanism in the Tibetan Plateau

INTRODUCTION Volcanoesaremostlyobservedinoceanicridges,hotspotsandcontinentalriftzones(Hongetal.,2003),andarerarelyobservedincontinentalinteri ors.However,sincethevolcanoeswithintheconti nentinteriorscannotbeattributedtotheplate/block marginprocess,theydr…     

A new bounding surface model for thermal cyclic behaviour

To accurately predict soil volume changes under thermal cycles is of great importance for analysing the performance of many earth structures such as the energy pile and energy storage system. Most of the existing thermo‐mechanical models focus on soil behaviour under monotonic thermal loading only, and they are not able to capture soil volume changes under thermal cycles. In this study, a constitutive model is proposed to simulate volume changes of saturated soil subjected to cyclic heating and cooling. Two surfaces are defined and used: a bounding surface and a memory surface. The bounding surface and memory surface are mainly controlled by the preconsolidation pressure (a function of plastic volumetric strain) and the maximum stress experienced by the soil, respectively. Under thermal cycles, the distance of the two surfaces and plastic modulus increase with an accumulation of plastic strain. By adopting the double surface concept, a new elastoplastic model is derived from an existing single bounding surface thermo‐mechanical model. Comparisons between model predictions and experimental results reveal that the proposed model is able to capture soil volume changes under thermal cycles well. The plastic strain accumulates under thermal cycles, but at a decreasing rate, until stabilization. Copyright © 2017 John Wiley & Sons, Ltd.     

The June 2013 Alberta catastrophic flooding event – part 2: fine‐scale precipitation and associated features

Data obtained from a variety of sources including the Canadian Lightning Detection Network, weather radars, weather stations and operational numerical weather model analyses were used to address the evolution of precipitation during the June 2013 southern Alberta flood. The event was linked to a mid‐level closed low pressure system to the west of the region and a surface low pressure region initially to its south. This configuration brought warm, moist unstable air into the region that led to dramatic, organized convection with an abundance of lightning and some hail. Such conditions occurred in the southern parts of the region whereas the northern parts were devoid of lightning. Initially, precipitation rates were high (extreme 15‐min rainfall rates up to 102 mm h^?1 were measured) but decreased to lower values as the precipitation shifted to long‐lived stratiform conditions. Both the convective and stratiform precipitation components were affected by the topography. Similar flooding events, such as June 2002, have occurred over this region although the 2002 event was colder and precipitation was not associated with substantial convection over southwest Alberta. Copyright © 2016 Her Majesty the Queen in Right of Canada. Hydrological Processes. © John Wiley & Sons, Ltd.     

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.     

Quantitative estimation of submarine groundwater discharge using airborne thermal infrared data acquired at two different tidal heights

Submarine groundwater discharge (SGD) plays an important role in coastal biogeochemical processes and hydrological cycles, particularly off volcanic islands in oligotrophic oceans. However, the spatial and temporal variations of SGD are still poorly understood owing to difficulty in taking rapid SGD measurements over a large scale. In this study, we used four airborne thermal infrared surveys (twice each during high and low tides) to quantify the spatiotemporal variations of SGD over the entire coast of Jeju Island, Korea. On the basis of an analytical model, we found a linear positive correlation between the thermal anomaly and squares of the groundwater discharge velocity and a negative exponential correlation between the anomaly and water depth (including tide height and bathymetry). We then derived a new equation for quantitatively estimating the SGD flow rates from thermal anomalies acquired at two different tide heights. The proposed method was validated with the measured SGD flow rates using a current meter at Gongcheonpo Beach. We believe that the method can be effectively applied for rapid estimation of SGD over coastal areas, where fresh groundwater discharge is significant, using airborne thermal infrared surveys.