The TKE dissipation rate in the northern South China Sea

The microstructure measurements taken during the summer seasons of 2009 and 2010 in the northern South China Sea (between 18°N and 22.5°N, and from the Luzon Strait to the eastern shelf of China) were used to estimate the averaged dissipation rate in the upper pycnocline 〈ε _p〉 of the deep basin and on the shelf. Linear correlation between 〈ε _p〉 and the estimates of available potential energy of internal waves, which was found for this data set, indicates an impact of energetic internal waves on spatial structure and temporal variability of 〈ε _p〉. On the shelf stations, the bottom boundary layer depth-integrated dissipation $ {\widehat{\varepsilon}}_{\mathrm{BBL}} $ reaches 17–19 mW/m², dominating the dissipation in the water column below the surface layer. In the pycnocline, the integrated dissipation $ {\widehat{\varepsilon}}_{\mathrm{p}} $ was mostly ～10–30 % of $ {\widehat{\varepsilon}}_{\mathrm{BBL}} $ . A weak dependence of bin-averaged dissipation $ \overline{\varepsilon} $ on the Richardson number was noted, according to $ \overline{\varepsilon}={\varepsilon}_0+\frac{\varepsilon_{\mathrm{m}}}{{\left(1+ Ri/R{i}_{\mathrm{cr}}\right)}^{1/2}} $ , where ε ₀ + ε _m is the background value of $ \overline{\varepsilon} $ for weak stratification and Ri _cr?=?0.25, pointing to the combined effects of shear instability of small-scale motions and the influence of larger-scale low frequency internal waves. The latter broadly agrees with the MacKinnon–Gregg scaling for internal-wave-induced turbulence dissipation.     

Correlation of Geoelectric Data with Aquifer Parameters to Delineate the Groundwater Potential of Hard rock Terrain in Central Uganda

Knowledge of aquifer parameters is essential for management of groundwater resources. Conventionally, these parameters are estimated through pumping tests carried out on water wells. This paper presents a study that was conducted in three villages (Tumba, Kabazi, and Ndaiga) of Nakasongola District, central Uganda to investigate the hydrogeological characteristics of the basement aquifers. Our objective was to correlate surface resistivity data with aquifer properties in order to reveal the groundwater potential in the district. Existing electrical resistivity and borehole data from 20 villages in Nakasongola District were used to correlate the aquifer apparent resistivity (ρ _e) with its hydraulic conductivity (K _e), and aquifer transverse resistance (TR) with its transmissivity (T _e). K _e was found to be related to ρ _e by; $ {\text{Log }}(K_{\text{e}} ) = - 0.002\rho_{\text{e}} + 2.692 $ . Similarly, TR was found to be related to T by; $ {\text{TR}} = - 0.07T_{\text{e}} + 2260 $ . Using these expressions, aquifer parameters (T _c and K _c) were extrapolated from measurements obtained from surface resistivity surveys. Our results show very low resistivities for the presumed water-bearing aquifer zones, possibly because of deteriorating quality of the groundwater and their packing and grain size. Drilling at the preferred VES spots was conducted before the pumping tests to reveal the aquifer characteristics. Aquifer parameters (T _o and K _o) as obtained from pumping tests gave values (29,424.7 m²/day, 374.3 m/day), (9,801.1 m²/day, 437.0 m/day), (31,852.4 m²/day, 392.9 m/day). The estimated aquifer parameter (T _c and K _c) when extrapolated from surface geoelectrical data gave (7,142.9 m²/day, 381.9 m/day), (28,200.0 m²/day, 463.4 m/day), (19,428.6 m²/day, 459.2 m/day) for Tumba, Kabazi, and Ndaiga villages, respectively. Interestingly, the similarity between the K _c and K _o pairs was not significantly different. We observed no significant relationships between the T _c and T _o pairs_. The root mean square errors were estimated to be 18,159 m²/day and 41.4 m/day.     

Variation of Seismic Coda Wave Attenuation in the Garhwal Region, Northwestern Himalaya

Seismic coda wave attenuation ( $ Q_{\text{c}}^{ - 1} $ ) characteristics in the Garhwal region, northwestern Himalaya is studied using 113 short-period, vertical component seismic observations from local events with hypocentral distance less than 250?km and magnitude range between 1.0 to 4.0. They are located mainly in the vicinity of the Main Boundary Thrust (MBT) and the Main Central Thrust (MCT), which are well-defined tectonic discontinuities in the Himalayas. Coda wave attenuation ( $ Q_{\text{c}}^{ - 1} $ ) is estimated using the single isotropic scattering method at central frequencies 1.5, 3, 5, 7, 9, 12, 16, 20, 24 and 28?Hz using several starting lapse times and coda window lengths for the analysis. Results show that the ( $ Q_{\text{c}}^{ - 1} $ ) values are frequency dependent in the considered frequency range, and they fit the frequency power law ( $ Q_{\text{c}}^{ - 1} \left( f \right) = Q_{0}^{ - 1} f^{ - n} $ ). The Q ₀ (Q _c at 1?Hz) estimates vary from about 50 for a 10?s lapse time and 10?s window length, to about 350 for a 60?s lapse time and 60?s window length combination. The exponent of the frequency dependence law, n ranges from 1.2 to 0.7; however, it is greater than 0.8, in general, which correlates well with the values obtained in other seismically and tectonically active and highly heterogeneous regions. The attenuation in the Garhwal region is found to be lower than the Q _c ^?1 values obtained for other seismically active regions of the world; however, it is comparable to other regions of India. The spatial variation of coda attenuation indicates that the level of heterogeneity decreases with increasing depth. The variation of coda attenuation has been estimated for different lapse time and window length combinations to observe the effect with depth and it indicates that the upper lithosphere is more active seismically as compared to the lower lithosphere and the heterogeneity decreases with increasing depth.     

Developing a novel methodology for ecological risk assessment of thiosalts

A new methodology is developed to estimate an aquatic community toxicity threshold concentration based on the limited toxicity data that are available for thiosalts. To analyze the indirect effect of thiosalts on decreasing pH, an exposure model is developed that estimates the residual concentration of thiosalts and pH in the water body. The results from this model are incorporated in thiosalts risk assessment and a case study is used to illustrate the applicability of the proposed model. In this study, the exposure model predicts that, trithionate and tetrathionate degraded to $ {{\text{SO}}_{4}}^{2 - } $ ions, $ {{\text{HSO}}_{3}}^{ - } $ ions, $ {{\text{SO}}_{3}}^{2 - } $ ions and elemental sulfur. The concentration of thiosulfate, trithionate and tetrathionate, initially at 25, 40 and 6 mg/L, respectively are expected to decrease. Over the duration of 77 h, thiosulfate degrades completely, while the estimated residual trithionate and tetrathionate concentrations are 13 and 5.77 mg/L, respectively. pH of the undiluted effluent is estimated to decrease from 9.2 to 5.6 within an hour of the effluent discharge and decreases further to 4 over a period of next 3 days. A framework and methodology developed in this paper can be utilized to estimate the potential direct and indirect risk of thiosalts exposure to ecological entities.     

Comparisons of Snowfall Measurements in Complex Terrain Made During the 2010 Winter Olympics in Vancouver

Solid precipitation (SP) intensity ( $ R_{\text{s}} $ ) using four automatic gauges, Pluvio, PARSIVEL (PArticle, SIze and VELocity), FD12P and POSS, and radar reflectivity factor ( $ Z $ ) using the POSS and PARSIVEL were measured at a naturally sheltered station (VOA) located at high level (1,640 m) on the Whistler Mountain in British Colombia, Canada. The R _s and other standard meteorological parameters were collected from March 2009, and from November 2009, to February 2010. The wind speed (ws) measured during this period ranged from 0 to 4.5 ms^?1, with a mean value of 0.5 ms^?1. The temperature varied from 4 to ?17 °C. The SP amount reported by the PARSIVEL was higher than that reported by the Pluvio by more than a factor of 2, while the FD12P and POSS measured relatively smaller amounts, but much closer to that reported by the Pluvio and manual measurements. The dependence of R _s from the PARSIVEL on wind speed was examined, but no significant dependence was found. The PARSIVEL’s precipitation retrieval algorithm was modified and tested using three different snow density size relationships (ρ _s–D) reported in literature. It was found that after modification of the algorithm, the derived R _s amounts using the raw data agreed reasonably well with the Pluvio. Statistical analysis shows that more than 95 % of $ Z_{{h_{\text{poss}} }} $ data measured by POSS appears to correlates well with the reflectivity factors determined using the three ρ _s–D relationships. The automated Pluvio accumulation and manually determined daily SP amount (SPm) measured during five winter months were compared. The mean ratio (MR) and the mean difference (MD), and the correlation coefficient (r) calculated using the data collected using the two methods, were found to be 0.96, 0.4 and 0.6 respectively, indicating respectable agreement between these two methods, with only the Pluvio underestimating the amount by about 4 %.     

Scaling Transition in Earthquake Sources: A Possible Link Between Seismic and Laboratory Measurements

We estimate the corner frequencies of 20 crustal seismic events from mainshock–aftershock sequences in different tectonic environments (mainshocks 5.7 < M _W < 7.6) using the well-established seismic coda ratio technique (Mayeda et al. in Geophys Res Lett 34:L11303, 2007; Mayeda and Malagnini in Geophys Res Lett, 2010), which provides optimal stability and does not require path or site corrections. For each sequence, we assumed the Brune source model and estimated all the events’ corner frequencies and associated apparent stresses following the MDAC spectral formulation of Walter and Taylor (A revised magnitude and distance amplitude correction (MDAC2) procedure for regional seismic discriminants, 2001), which allows for the possibility of non-self-similar source scaling. Within each sequence, we observe a systematic deviation from the self-similar \( M_{0} \propto \mathop f\nolimits_{\text{c}}^{ - 3} \) line, all data being rather compatible with \( M_{0} \propto \mathop f\nolimits_{\text{c}}^{ - (3 + \varepsilon )} \) , where ε > 0 (Kanamori and Rivera in Bull Seismol Soc Am 94:314–319, 2004). The deviation from a strict self-similar behavior within each earthquake sequence of our collection is indicated by a systematic increase in the estimated average static stress drop and apparent stress with increasing seismic moment (moment magnitude). Our favored physical interpretation for the increased apparent stress with earthquake size is a progressive frictional weakening for increasing seismic slip, in agreement with recent results obtained in laboratory experiments performed on state-of-the-art apparatuses at slip rates of the order of 1 m/s or larger. At smaller magnitudes (M _W < 5.5), the overall data set is characterized by a variability in apparent stress of almost three orders of magnitude, mostly from the scatter observed in strike-slip sequences. Larger events (M _W > 5.5) show much less variability: about one order of magnitude. It appears that the apparent stress (and static stress drop) does not grow indefinitely at larger magnitudes: for example, in the case of the Chi–Chi sequence (the best sampled sequence between M _W 5 and 6.5), some roughly constant stress parameters characterize earthquakes larger than M _W ~ 5.5. A representative fault slip for M _W 5.5 is a few tens of centimeters (e.g., Ide and Takeo in J Geophys Res 102:27379–27391, 1997), which corresponds to the slip amount at which effective lubrication is observed, according to recent laboratory friction experiments performed at seismic slip velocities (V ~ 1 m/s) and normal stresses representative of crustal depths (Di Toro et al. in Nature in press, 2011, and references therein). If the observed deviation from self-similar scaling is explained in terms of an asymptotic increase in apparent stress (Malagnini et al. in Pure Appl Geophys, 2014, this volume), which is directly related to dynamic stress drop on the fault, one interpretation is that for a seismic slip of a few tens of centimeters (M _W ~ 5.5) or larger, a fully lubricated frictional state may be asymptotically approached.     

Calibration of an M L scale for South Africa using tectonic earthquake data recorded by the South African National Seismograph Network: 2006 to 2009

A relation to determine local magnitude (M _L) based on the original Richter definition is empirically derived from synthetic Wood–Anderson seismograms recorded by the South African National Seismograph Network. In total, 263 earthquakes in the distance range 10 to 1,000 km, representing 1,681 trace amplitudes measured in nanometers from synthesized Wood–Anderson records on the vertical channel were considered to derive an attenuation relation appropriate for South Africa through multiple regression analysis. Additionally, station corrections were determined for 26 stations during the regression analysis resulting in values ranging between ?0.31 and 0.50. The most appropriate M _L scale for South Africa from this study satisfies the equation: $$ {M_{{{\bf L}}}} = {\text{lo}}{{\text{g}}_{{10}}}(A) + 1.149\;{\text{lo}}{{\text{g}}_{{10}}}(R) + 0.00063R + 2.04 - S $$ The anelastic attenuation term derived from this study indicates that ground motion attenuation is significantly different from Southern California but comparable with stable continental regions.     

The TKE dissipation rate in the northern South China Sea

The microstructure measurements taken during the summer seasons of 2009 and 2010 in the northern South China Sea (between 18°N and 22.5°N, and from the Luzon Strait to the eastern shelf of China) were used to estimate the averaged dissipation rate in the upper pycnocline 〈ε _p〉 of the deep basin and on the shelf. Linear correlation between 〈ε _p〉 and the estimates of available potential energy of internal waves, which was found for this data set, indicates an impact of energetic internal waves on spatial structure and temporal variability of 〈ε _p〉. On the shelf stations, the bottom boundary layer depth-integrated dissipation \( {\widehat{\varepsilon}}_{\mathrm{BBL}} \) reaches 17–19 mW/m², dominating the dissipation in the water column below the surface layer. In the pycnocline, the integrated dissipation \( {\widehat{\varepsilon}}_{\mathrm{p}} \) was mostly ∼10–30 % of \( {\widehat{\varepsilon}}_{\mathrm{BBL}} \). A weak dependence of bin-averaged dissipation \( \overline{\varepsilon} \) on the Richardson number was noted, according to \( \overline{\varepsilon}={\varepsilon}_0+\frac{\varepsilon_{\mathrm{m}}}{{\left(1+ Ri/R{i}_{\mathrm{cr}}\right)}^{1/2}} \), where ε ₀ + ε _m is the background value of \( \overline{\varepsilon} \) for weak stratification and Ri _cr = 0.25, pointing to the combined effects of shear instability of small-scale motions and the influence of larger-scale low frequency internal waves. The latter broadly agrees with the MacKinnon–Gregg scaling for internal-wave-induced turbulence dissipation.

     

Effective Solar Indices for Ionospheric Modeling: A Review and a Proposal for a Real-Time Regional IRI

The first part of this paper reviews methods using effective solar indices to update a background ionospheric model focusing on those employing the Kriging method to perform the spatial interpolation. Then, it proposes a method to update the International Reference Ionosphere (IRI) model through the assimilation of data collected by a European ionosonde network. The method, called International Reference Ionosphere UPdate (IRI UP), that can potentially operate in real time, is mathematically described and validated for the period 9–25 March 2015 (a time window including the well-known St. Patrick storm occurred on 17 March), using IRI and IRI Real Time Assimilative Model (IRTAM) models as the reference. It relies on foF2 and M(3000)F2 ionospheric characteristics, recorded routinely by a network of 12 European ionosonde stations, which are used to calculate for each station effective values of IRI indices \(IG_{12}\) and \(R_{12}\) (identified as \(IG_{{12{\text{eff}}}}\) and \(R_{{12{\text{eff}}}}\)); then, starting from this discrete dataset of values, two-dimensional (2D) maps of \(IG_{{12{\text{eff}}}}\) and \(R_{{12{\text{eff}}}}\) are generated through the universal Kriging method. Five variogram models are proposed and tested statistically to select the best performer for each effective index. Then, computed maps of \(IG_{{12{\text{eff}}}}\) and \(R_{{12{\text{eff}}}}\) are used in the IRI model to synthesize updated values of foF2 and hmF2. To evaluate the ability of the proposed method to reproduce rapid local changes that are common under disturbed conditions, quality metrics are calculated for two test stations whose measurements were not assimilated in IRI UP, Fairford (51.7°N, 1.5°W) and San Vito (40.6°N, 17.8°E), for IRI, IRI UP, and IRTAM models. The proposed method turns out to be very effective under highly disturbed conditions, with significant improvements of the foF2 representation and noticeable improvements of the hmF2 one. Important improvements have been verified also for quiet and moderately disturbed conditions. A visual analysis of foF2 and hmF2 maps highlights the ability of the IRI UP method to catch small-scale changes occurring under disturbed conditions which are not seen by IRI.     

The surface roughness and planetary boundary layer

Applications of the entrainment process to layers at the boundary, which meet the self similarity requirements of the logarithmic profile, have been studied. By accepting that turbulence has dominating scales related in scale length to the height above the surface, a layer structure is postulated wherein exchange is rapid enough to keep the layers internally uniform. The diffusion rate is then controlled by entrainment between layers. It has been shown that theoretical relationships derived on the basis of using a single layer of this type give quantitatively correct factors relating the turbulence, wind and shear stress for very rough surface conditions. For less rough surfaces, the surface boundary layer can be divided into several layers interacting by entrainment across each interface. This analysis leads to the following quantitatively correct formula compared to published measurements. 1 $$\begin{gathered} \frac{{\sigma _w }}{{u^* }} = \left( {\frac{2}{{9Aa}}} \right)^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \left( {1 - 3^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-\nulldelimiterspace} 2}} \frac{a}{k}\frac{{d_n }}{z}\frac{{\sigma _w }}{{u^* }}\frac{z}{L}} \right)^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \hfill \\ = 1.28(1 - 0.945({{\sigma _w } \mathord{\left/ {\vphantom {{\sigma _w } {u^* }}} \right. \kern-\nulldelimiterspace} {u^* }})({z \mathord{\left/ {\vphantom {z L}} \right. \kern-\nulldelimiterspace} L})^{{1 \mathord{\left/ {\vphantom {1 4}} \right. \kern-\nulldelimiterspace} 4}} \hfill \\ \end{gathered} $$ where \(u^* = \left( {{\tau \mathord{\left/ {\vphantom {\tau \rho }} \right. \kern-0em} \rho }} \right)^{{1 \mathord{\left/ {\vphantom {1 2}} \right. \kern-0em} 2}} \) , σ _w is the standard deviation of the vertical velocity,z is the height andL is the Obukhov scale lenght. The constantsa, A, k andd _n are the entrainment constant, the turbulence decay constant, Von Karman's constant, and the layer depth derived from the theory. Of these,a andA, are universal constants and not empirically determined for the boundary layer. Thus the turbulence needed for the plume model of convection, which resides above these layers and reaches to the inversion, is determined by the shear stress and the heat flux in the surface layers. This model applies to convection in cool air over a warm sea. The whole field is now determined except for the temperature of the air relative to the water, and the wind, which need a further parameter describing sea surface roughness. As a first stop to describing a surface where roughness elements of widely varying sizes are combined this paper shows how the surface roughness parameter,z ₀, can be calculated for an ideal case of a random distribution of vertical cylinders of the same height. To treat a water surface, with various sized waves, such an approach modified to treat the surface by the superposition of various sized roughness elements, is likely to be helpful. Such a theory is particularly desirable when such a surface is changing, as the ocean does when the wind varies. The formula, 2 $$\frac{{0.118}}{{a_s C_D }}< z_0< \frac{{0.463}}{{a_s C_D (u^* )}}$$ is the result derived here. It applies to cylinders of radius,r, and number,m, per unit boundary area, wherea _s =2rm, is the area of the roughness elements, per unit area perpendicular to the wind, per unit distance downwind. The drag coefficient of the cylinders isC _D . The smaller value ofz _o is for large Reynolds numbers where the larger scale turbulence at the surface dominates, and the drag coefficient is about constant. Here the flow between the cylinders is intermittent. When the Reynolds number is small enough then the intermittent nature of the turbulence is reduced and this results in the average velocity at each level determining the drag. In this second case the larger limit forz ₀ is more appropriate.     

Aftershock Statistics of the 1999 Chi–Chi, Taiwan Earthquake and the Concept of Omori Times

In this paper we consider the statistics of the aftershock sequence of the m = 7.65 20 September 1999 Chi–Chi, Taiwan earthquake. We first consider the frequency-magnitude statistics. We find good agreement with Gutenberg–Richter scaling but find that the aftershock level is anomalously high. This level is quantified using the difference in magnitude between the main shock and the largest inferred aftershock $ {{\Updelta}}m^{ *}. $ Typically, $ {{\Updelta}}m^{ *} $ is in the range 0.8–1.5, but for the Chi–Chi earthquake the value is $ {{\Updelta}}m^{ *} $  = 0.03. We suggest that this may be due to an aseismic slow-earthquake component of rupture. We next consider the decay rate of aftershock activity following the earthquake. The rates are well approximated by the modified Omori’s law. We show that the distribution of interoccurrence times between aftershocks follow a nonhomogeneous Poisson process. We introduce the concept of Omori times to study the merging of the aftershock activity with the background seismicity. The Omori time is defined to be the mean interoccurrence time over a fixed number of aftershocks.     

Characterization of the Tail of the Distribution of Earthquake Magnitudes by Combining the GEV and GPD Descriptions of Extreme Value Theory

The present work is a continuation and improvement of the method suggested in Pisarenko et al. (Pure Appl Geophys 165:1–42, 2008) for the statistical estimation of the tail of the distribution of earthquake sizes. The chief innovation is to combine the two main limit theorems of Extreme Value Theory (EVT) that allow us to derive the distribution of T-maxima (maximum magnitude occurring in sequential time intervals of duration T) for arbitrary T. This distribution enables one to derive any desired statistical characteristic of the future T-maximum. We propose a method for the estimation of the unknown parameters involved in the two limit theorems corresponding to the Generalized Extreme Value distribution (GEV) and to the Generalized Pareto Distribution (GPD). We establish the direct relations between the parameters of these distributions, which permit to evaluate the distribution of the T-maxima for arbitrary T. The duality between the GEV and GPD provides a new way to check the consistency of the estimation of the tail characteristics of the distribution of earthquake magnitudes for earthquake occurring over an arbitrary time interval. We develop several procedures and check points to decrease the scatter of the estimates and to verify their consistency. We test our full procedure on the global Harvard catalog (1977–2006) and on the Fennoscandia catalog (1900–2005). For the global catalog, we obtain the following estimates: \( \hat{M}_{{\rm max} } \)  = 9.53 ± 0.52 and \( \hat{Q}_{10} (0.97) \)  = 9.21 ± 0.20. For Fennoscandia, we obtain \( \hat{M}_{{\rm max} } \)  = 5.76 ± 0.165 and \( \hat{Q}_{10} (0.97) \)  = 5.44 ± 0.073. The estimates of all related parameters for the GEV and GPD, including the most important form parameter, are also provided. We demonstrate again the absence of robustness of the generally accepted parameter characterizing the tail of the magnitude-frequency law, the maximum possible magnitude M _max, and study the more stable parameter Q _T (q), defined as the q-quantile of the distribution of T-maxima on a future interval of duration T.     

Long-term earthquake prediction in the Aegean area based on a time and magnitude predictable model

The Aegean and surrounding area (34°N–43°N, 18°E–30°E) is separated into 76 shallow and intermediate depth seismogenic sources. For 74 of these sources intervent times for strong mainshocks have been determined by the use of instrumental and historical data. These times have been used to determine the following empirical relations: $$\begin{gathered} \log T_t = 0.24M_{\min } + 0.25M_p - 0.36\log \dot M_0 + 7.36 \hfill \\ M_f = 1.04M_{\min } - 0.31M_p + 0.28\log \dot M_0 - 4.85 \hfill \\ \end{gathered} $$ whereT ₁ is the interevent time, measured in years,M _min the surface wave magnitude of the smallest mainshock considered,M _p the magnitude of the preceding mainshock,M _f the magnitude of the following mainshock, \(\dot M_0 \) the moment rate in each source per year. A multiple correlation coefficient equal to 0.74 and a standard deviation equal to 0.18 for the first of these relations were calculated. The corresponding quantities for the second of these relations are 0.91 and 0.22. On the basis of the first of these relations and taking into consideration the time of occurence and the magnitude of the last mainshock, the probabilities for the occurrence of mainshocks in each seismogenic source of this region during the decade 1993–2002 are determined. The second of these relations has been used to estimate the magnitude of the expected mainshock.     

The boundary value problem of Poisson’s equation with Stokes’ boundary condition

The following Poisson’s equation with the Stokes’ boundary condition is dealt with $$\left\{ \begin{gathered} \nabla ^2 T = - 4\pi Gp outside S, \hfill \\ \left. {\frac{{\partial T}}{{\partial h}} = \frac{1}{\gamma }\frac{{\partial y}}{{\partial h}}T} \right|_s = - \Delta g, \hfill \\ T = O\left( {r^{ - 3} } \right) at infinity, \hfill \\ \end{gathered} \right.$$ whereS is reference ellipsord. Under spherical approximation transformation, the ellipsoidal correction terms about the boundary condition, the equation and the density in the above BVP are respectively given. Therefore, the disturbing potentialT can he obtained if the magnitudes aboveO(ε⁴) are neglected.     

A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer,Iran

Vulnerability maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts. The objective of this research is (1) to assess the groundwater vulnerability using DRASTIC method and (2) to improve the DRASTIC method for evaluation of groundwater contamination risk using AI methods, such as ANN, SFL, MFL, NF and SCMAI approaches. This optimization method is illustrated using a case study. For this purpose, DRASTIC model is developed using seven parameters. For validating the contamination risk assessment, a total of 243 groundwater samples were collected from different aquifer types of the study area to analyze \( {\text{NO}}_{ 3}^{ - } \) concentration. To develop AI and CMAI models, 243 data points are divided in two sets; training and validation based on cross validation approach. The calculated vulnerability indices from the DRASTIC method are corrected by the \( {\text{NO}}_{3}^{ - } \) data used in the training step. The input data of the AI models include seven parameters of DRASTIC method. However, the output is the corrected vulnerability index using \( {\text{NO}}_{3}^{ - } \) concentration data from the study area, which is called groundwater contamination risk. In other words, there is some target value (known output) which is estimated by some formula from DRASTIC vulnerability and \( {\text{NO}}_{3}^{ - } \) concentration values. After model training, the AI models are verified by the second \( {\text{NO}}_{3}^{ - } \) concentration dataset. The results revealed that NF and SFL produced acceptable performance while ANN and MFL had poor prediction. A supervised committee machine artificial intelligent (SCMAI), which combines the results of individual AI models using a supervised artificial neural network, was developed for better prediction of vulnerability. The performance of SCMAI was also compared to those of the simple averaging and weighted averaging committee machine intelligent (CMI) methods. As a result, the SCMAI model produced reliable estimates of groundwater contamination risk.     

A Crustal Model for the Eastern Alps Region and a New Moho Map in Southeastern Europe

In the last two decades, south-central Europe and the Eastern Alps have been widely explored by many seismic refraction experiments (e.g., CELEBRATION 2000, ALP 2002, SUDETES 2003). Although quite detailed images are available along linear profiles, a comprehensive, three-dimensional crustal model of the region is still missing. This limitation makes this region a weak spot in continental-wide comprehensive representations of crustal structure. To improve on this situation, we select and collect 37 published active-source seismic lines in this region. After geo-referencing each line, we sample them along vertical profiles—every 50?km or less along the line—and derive P-wave velocities in a stack of homogeneous layers (separated by discontinuities: depth of crystalline basement, top of lower crust, and Moho). We finally merge the information using geostatistical methods, and infer S-wave velocity and density using empirical scaling relations. We present here the resulting crustal model for a region encompassing the Eastern Alps, Dinarides, Pannonian basin, Western Carpathians and Bohemian Massif, covering the region within $45^{\circ}\text{--}51^{\circ}\hbox{N}$ and $11^{\circ} \text{--} 22^{\circ}\hbox{E}$ with a resolution of $0.2^{\circ} \times 0.2^{\circ}.$ We are also able to extend and update the map of Moho depth in a wider region within $35^{\circ}\text{--}51^{\circ}\hbox{N}$ and $12^{\circ}\text{--}45^{\circ}\hbox{E},$ gathering Moho values from the collected seismic lines, other published dataset and using the European plate reference EPcrust as a background. All the digitized profiles and the resulting model are available online.     

New magnitude scaling relations for earthquake early warning in the Alborz region,Iran

Rapid magnitude estimation relations for earthquake early warning systems in the Alborz region have been developed based on the initial first seconds of the P-wave arrival. For this purpose, a total of 717 accelerograms recorded by the Building and Housing Research Center in the Alborz region with the magnitude (M_w) range of 4.8–6.5 in the period between 1995 and 2013 were employed. Average ground motion period (\( \tau_{\text{c}} \)) and peak displacement (\( P_{\text{d}} \)) in different time windows from the P-wave arrival were calculated, and their relation with magnitude was examined. Four earthquakes that were excluded from the analysis process were used to validate the results, and the estimated magnitudes were found to be in good agreement with the observed ones. The results show that using the proposed relations for the Alborz region, earthquake magnitude could be estimated with acceptable accuracy even after 1 s of the P-wave arrival.     

Simulation of Strong Ground Motion During the 1950 Great Assam Earthquake

In this paper, ground motion during the Independence Day earthquake of August 15, 1950 (M_w 8.6, Ben-Menahem et al., 1974) in the northeastern part of India is estimated by seismological approaches. A hybrid simulation technique which combines the low frequency ground motion simulated from an analytical source mechanism model with the stochastically simulated high-frequency components is used for obtaining the acceleration time histories. A series of ground motion simulations are carried out to estimate the peak ground acceleration (PGA) and spectral accelerations at important cities and towns in the epicentral region. One sample PGA distribution in the epicentral region encompassing the epicenter is also obtained. It is found that PGA in the epicentral region has exceeded 1 g during this earthquake. The estimated PGA’s are validated to the extent possible using the MMI values. The simulated acceleration time histories can be used for the assessment of important engineering structures in northeastern India.