Morphological analysis of active Mount Nemrut stratovolcano, eastern Turkey: evidences and possible impact areas of future eruption

Mount Nemrut, an active stratovolcano in eastern Turkey, is a great danger for its vicinity. The volcano possesses a summit caldera which cuts the volcano into two stages, i.e. pre- and post-caldera. Wisps of smoke and hot springs are to be found within the caldera. Although the last recorded volcanic activity is known to have been in 1441, we consider here that the last eruption of Nemrut occurred more recently, probably just before 1597. The present active tectonic regime, historical eruptions, occurrence of mantle-derived magmatic gases and the fumarole and hot spring activities on the caldera floor make Nemrut Volcano a real danger for its vicinity. According to the volcanological past of Nemrut, the styles of expected eruptions are well-focused on two types: (1) occurrence of water within the caldera leads to phreatomagmatic (highly energetic) eruptions, subsequently followed by lava extrusions, and (2) effusions–extrusions (non-explosive or weakly energetic eruptions) on the flanks from fissures. To predict the impact area of future eruptions, a series of morphological analyses based on field observations, Digital Elevation Model and satellite images were realized. Twenty-two valleys (main transport pathways) were classified according to their importance, and the physical parameters related to the valleys were determined. The slope values in each point of the flanks and the Heim parameters H/L were calculated. In the light of morphological analysis the possible impact areas around the volcano and danger zones were proposed. The possible transport pathways of the products of expected volcanic events are unified in three main directions: Bitlis, Guroymak, Tatvan and Ahlat cities, the about 135 000 inhabitants of which could be threatened by future eruptions of this poorly known and unsurveyed volcano.     

Data Assimilation (4D-VAR) for Shallow-Water Flow: The Case of the Chicoutimi River

This is a web presentation of the work presented at the 10th Annual Conference of the CFD Society of Canada, “CFD 2002”, at the University of Windsor on June 9-11, 2002. This discussion paper presents the four-dimensional variational data assimilation (4D-VAR) technique as a tool to forecast floods. This discussion will be limited to hydrological forecast. We assume that the weather, here a large rainstorm, had already been forecasted by the meteorological services. In the 4D-VAR technique, we need to minimize, in the sense of Lagrange, a cost function which measures the difference between the forecast and the observations. The physical equations acts as a set of constraints. Here, the model is the shallow-water equations modified to include sediment transport. The minimum was found by using the steepest descent algorithm. This is made possible because the gradient of the cost function can be calculated analytically by using the adjoint equations of the model. To illustrate the 4D-VAR technique, the bypass of a simple theoretical dam as well as the more complex overflowing of the Chicoutimi River at the Chute-Garneau dam (during the 1996 flood) are investigated.     

Estimating River Conductance from Prior Information to Improve Surface‐Subsurface Model Calibration

Most groundwater models simulate stream‐aquifer interactions with a head‐dependent flux boundary condition based on a river conductance (CRIV). CRIV is usually calibrated with other parameters by history matching. However, the inverse problem of groundwater models is often ill‐posed and individual model parameters are likely to be poorly constrained. Ill‐posedness can be addressed by Tikhonov regularization with prior knowledge on parameter values. The difficulty with a lumped parameter like CRIV, which cannot be measured in the field, is to find suitable initial and regularization values. Several formulations have been proposed for the estimation of CRIV from physical parameters. However, these methods are either too simple to provide a reliable estimate of CRIV, or too complex to be easily implemented by groundwater modelers. This paper addresses the issue with a flexible and operational tool based on a 2D numerical model in a local vertical cross section, where the river conductance is computed from selected geometric and hydrodynamic parameters. Contrary to other approaches, the grid size of the regional model and the anisotropy of the aquifer hydraulic conductivity are also taken into account. A global sensitivity analysis indicates the strong sensitivity of CRIV to these parameters. This enhancement for the prior estimation of CRIV is a step forward for the calibration and uncertainty analysis of surface‐subsurface models. It is especially useful for modeling objectives that require CRIV to be well known such as conjunctive surface water‐groundwater use.     

Turbulent heat fluxes by profile and inertial dissipation methods: analysis of the atmospheric surface layer from shipboard measurements during the SOFIA/ASTEX and SEMAPHORE experiments

Heat flux estimates obtained using the inertial dissipation method, and the profile method applied to radiosonde soundings, are assessed with emphasis on the parameterization of the roughness lengths for temperature and specific humidity. Results from the inertial dissipation method show a decrease of the temperature and humidity roughness lengths for increasing neutral wind speed, in agreement with previous studies. The sensible heat flux estimates were obtained using the temperature estimated from the speed of sound determined by a sonic anemometer. This method seems very attractive for estimating heat fluxes over the ocean. However allowance must be made in the inertial dissipation method for non-neutral stratification. The SOFIA/ASTEX and SEMAPHORE results show that, in unstable stratification, a term due to the transport terms in the turbulent kinetic energy budget, has to be included in order to determine the friction velocity with better accuracy. Using the profile method with radiosonde data, the roughness length values showed large scatter. A reliable estimate of the temperature roughness length could not be obtained. The humidity roughness length values were compatible with those found using the inertial dissipation method.     

Formation of Zn–Ca phyllomanganate nanoparticles in grass roots

It is now well established that a number of terrestrial and aquatic microorganisms have the capacity to oxidize and precipitate Mn as phyllomanganate. However, this biomineralization has never been shown to occur in plant tissues, nor has the structure of a natural Mn(IV) biooxide been characterized in detail. We show that the graminaceous plant Festuca rubra (red fescue) produces a Zn-rich phyllomanganate with constant Zn:Mn and Ca:Mn atomic ratios (0.46 and 0.38, respectively) when grown on a contaminated sediment. This new phase is so far the Zn-richest manganate known to form in nature (chalcophanite has a Zn:Mn ratio of 0.33) and has no synthetic equivalent. Visual examination of root fragments under a microscope shows black precipitates about ten to several tens of microns in size, and their imaging with backscattered and secondary electrons demonstrates that they are located in the root epidermis. In situ measurements by Mn and Zn K-edge extended X-ray absorption fine structure (EXAFS) spectroscopy and X-ray diffraction (XRD) with a micro-focused beam can be quantitatively described by a single-phase model consisting of Mn(IV) octahedral layers with 22% vacant sites capped with tetrahedral and octahedral Zn in proportions of 3:1. The layer charge deficit is also partly balanced by interlayer Mn and Ca. Diffracting crystallites have a domain radius of 33 Å in the ab plane and contain only 1.2 layers (8.6 Å) on average. Since this biogenic Mn oxide consists mostly of isolated layers, basal 00l reflections are essentially absent despite its lamellar structure. Individual Mn layers are probably held together in the Mn–Zn precipitates by stabilizing organic molecules. Zinc biomineralization by plants likely is a defense mechanism against toxicity induced by excess concentrations of this metal in the rhizosphere.     

Study of the air-sea interactions at the mesoscale: the SEMAPHORE experiment

The SEMAPHORE (Structure des Echanges Mer-Atmosphère, Propriétés des Hétérogénéités Océaniques: Recherche Expérimentale) experiment has been conducted from June to November 1993 in the Northeast Atlantic between the Azores and Madeira. It was centered on the study of the mesoscale ocean circulation and air-sea interactions. The experimental investigation was achieved at the mesoscale using moorings, floats, and ship hydrological survey, and at a smaller scale by one dedicated ship, two instrumented aircraft, and surface drifting buoys, for one and a half month in October-November (IOP: intense observing period). Observations from meteorological operational satellites as well as spaceborne microwave sensors were used in complement. The main studies undertaken concern the mesoscale ocean, the upper ocean, the atmospheric boundary layer, and the sea surface, and first results are presented for the various topics. From data analysis and model simulations, the main characteristics of the ocean circulation were deduced, showing the close relationship between the Azores front meander and the occurrence of Mediterranean water lenses (meddies), and the shift between the Azores current frontal signature at the surface and within the thermocline. Using drifting buoys and ship data in the upper ocean, the gap between the scales of the atmospheric forcing and the oceanic variability was made evident. A 2 °C decrease and a 40-m deepening of the mixed layer were measured within the IOP, associated with a heating loss of about 100 W m⁻². This evolution was shown to be strongly connected to the occurrence of storms at the beginning and the end of October. Above the surface, turbulent measurements from ship and aircraft were analyzed across the surface thermal front, showing a 30% difference in heat fluxes between both sides during a 4-day period, and the respective contributions of the wind and the surface temperature were evaluated. The classical momentum flux bulk parameterization was found to fail in low wind and unstable conditions. Finally, the sea surface was investigated using airborne and satellite radars and wave buoys. A wave model, operationally used, was found to get better results compared with radar and wave-buoy measurements, when initialized using an improved wind field, obtained by assimilating satellite and buoy wind data in a meteorological model. A detailed analysis of a 2-day period showed that the swell component, propagating from a far source area, is underestimated in the wave model. A data base has been created, containing all experimental measurements. It will allow us to pursue the interpretation of observations and to test model simulations in the ocean, at the surface and in the atmospheric boundary layer, and to investigate the ocean-atmosphere coupling at the local and mesoscales.     

Development of a rain‐on‐snow detection algorithm using passive microwave radiometry

Currently observed climate warming in the Arctic has numerous consequences. Of particular relevance, the precipitation regime is modified where mixed and liquid precipitation can occur during the winter season leading to rain‐on‐snow (ROS) events. This phenomenon is responsible for ice crust formation, which has a significant impact on ecosystems (such as biological, hydrological, ecological and physical processes). The spatially and temporally sporadic nature of ROS events makes the phenomenon difficult to monitor using meteorological observations. This paper focuses on the detection of ROS events using passive microwave (PMW) data from a modified brightness temperature (T_B) gradient approach at 19 and 37 GHz. The approach presented here was developed empirically for observed ROS events with coincident ground‐based PMW measurements in Sherbrooke, Quebec, Canada. It was then tested in Nunavik, Quebec, with the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR‐E). We obtained a detection accuracy of 57, 71 and 89% for ROS detection for three AMSR‐E grid cells with a maximum error of 7% when considering all omissions and commissions with regard to the total number of AMSR‐E passes throughout the winter period. Copyright © 2016 John Wiley & Sons, Ltd.     

Testing bedload transport equations with consideration of time scales

Bedload transport is known to be a highly fluctuating temporal phenomenon, even under constant (mean) flow conditions, as a consequence of stochasticity, bedform migration, grain sorting, hysteresis, or sediment supply limitation. Because bedload transport formulas usually refer to a single mean transport value for a given flow condition, one can expect that prediction accuracy (when compared to measurements) will depend on the amplitude and duration of fluctuations, which in turn depend on the time scale used for observations. This paper aims to identify how the time scale considered can affect bedload prediction. This was done by testing 16 common bedload transport formulas with four data sets corresponding to different measurement period durations: (i) highly fluctuating (quasi‐)instantaneous field measurements; (ii) volumes accumulated at the event scale on two small alpine gravel‐bed rivers, potentially affected by seasonal fluctuations; (iii) volumes accumulated at the interannual scale in a meandering gravel bed river, thought to be weakly subject to fluctuations; (iv) time‐integrated flume measurements with nearly uniform sediments. The tests confirmed that the longer the measurement period, the better the precision of the formula's prediction interval. They also demonstrate several consequential limitations. Most threshold formulas are no longer valid when the flow condition is below two times the threshold condition for the largest elements' motion on the bed surface (considering D₈₄). In such conditions, equations either predict zero transport, or largely overestimate the real transport, especially when D₈₄ is high. There is a need for new sediment data collected with highly reliable techniques such as recording slot bedload samplers to further investigate this topic. Copyright © 2012 John Wiley & Sons, Ltd.