A semiempirical mathematical model of the secondary pollution of water bodies by soluble iron and manganese forms

A semiempirical mathematical model of iron and manganese migration from bottom sediments into the water mass of water bodies has been proposed based on some basic regularities in the geochemistry of those elements. The entry of dissolved forms of iron and manganese under aeration conditions is assumed negligible. When dissolved-oxygen concentration is <0.5 mg/L, the elements start releasing from bottom sediments, their release rate reaching its maximum under anoxic conditions. The fluxes of dissolved iron and manganese (Me) from bottom sediments into the water mass (J _Me) are governed by the gradients of their concentrations in diffusion water sublayer adjacent to sediment surface and having an average thickness of h = 0.025 cm: \({J_{Me}} = - {D_{Me}}\frac{{{C_{Me\left( {ss} \right)}} - {C_{Me\left( w \right)}}}}{h}\) (D _Me ≈ 1 × 10^–9 m²/s is molecular diffusion coefficient of component Me in solution; C _Me(ss) and C _Me(w) ≈ 0 are Me concentrations on sediment surface, i.e., on the bottom boundary of the diffusion water sublayer, and in the water mass, i.e., on the upper boundary of the diffusion water sublayer). The value of depends on water saturation with dissolved oxygen (\({\eta _{{O_2}}}\)) in accordance with the empiric relationship \({C_{Me\left( {ss} \right)}} = \frac{{C_{_{Me\left( {ss} \right)}}^{\max }}}{{1 + k{\eta _{{O_2}}}}}\) (k is a constant factor equal to 300 for iron and 100 for manganese; C _Me(ss) ^max is the maximal concentration of Me on the bottom boundary of the diffusion water sublayer with C _Fe(ss) ^max ≈ 200 μM (11 mg/L), and C _Mn(ss) ^max ≈ 100 μM (5.5 mg/L).     

Effects of temporally correlated infiltration on water flow in an unsaturated–saturated system

Effects of temporally correlated infiltration on water flow in an unsaturated–saturated system were investigated. Both white noise and exponentially correlated infiltration processes were considered. The moment equations of the pressure head (ψ) were solved numerically to obtain the variance and autocorrelation functions of ψ at 14 observation points. Monte Carlo simulations were conducted to verify the numerical results and to estimate the power spectrum of ψ (S _ψψ ). It was found that as the water flows through the system, the variance of the ψ (\( \sigma_{\psi }^{2} \)) were damped by the system: the deeper in the system, the smaller the \( \sigma_{\psi }^{2} \), and the larger the correlation timescale of the infiltration process (λ _I ), the larger the \( \sigma_{\psi }^{2} \). The unsaturated–saturated system gradually filters out the short-term fluctuations of ψ and the damping effect is most significant in the upper part of the system. The fluctuations of ψ is non-stationary at early time and becomes stationary as time progresses: the larger the value of λ _I , the longer the non-stationary period. The correlation timescale of the ψ (λ _ψ ) increases with depth and approaches a constant value at depth: the larger the value of λ _I , the larger the value of λ _ψ . The results of the estimated S _ψψ is consistent with those of the variance and autocorrelation function.     

Attenuation coefficients of Rayleigh and <Emphasis Type="Italic">Lg</Emphasis> waves

Analysis of the frequency dependence of the attenuation coefficient leads to significant changes in interpretation of seismic attenuation data. Here, several published surface-wave attenuation studies are revisited from a uniform viewpoint of the temporal attenuation coefficient, denoted by χ. Theoretically, χ( f) is expected to be linear in frequency, with a generally non-zero intercept γ?=?χ(0) related to the variations of geometrical spreading, and slope dχ/df = π/Q _e caused by the effective attenuation of the medium. This phenomenological model allows a simple classification of χ( f) dependences as combinations of linear segments within several frequency bands. Such linear patterns are indeed observed for Rayleigh waves at 500–100-s and 100–10-s periods, and also for Lg from ~2 s to ~1.5 Hz. The Lg χ( f) branch overlaps with similar linear branches of body, Pn, and coda waves, which were described earlier and extend to ~100 Hz. For surface waves shorter than ~100 s, γ values recorded in areas of stable and active tectonics are separated by the levels of \(\gamma _{D} \approx 0.2 \times 10^{-3}\) s^???1 (for Rayleigh waves) and 8 ×10^???3 s^???1 (for Lg). The recently recognized discrepancy between the values of Q measured from long-period surface waves and normal-mode oscillations could also be explained by a slight positive bias in the geometrical spreading of surface waves. Similarly to the apparent χ, the corresponding linear variation with frequency is inferred for the intrinsic attenuation coefficient, χ _i , which combines the effects of geometrical spreading and dissipation within the medium. Frequency-dependent rheological or scattering Q is not required for explaining any of the attenuation observations considered in this study. The often-interpreted increase of Q with frequency may be apparent and caused by using the Q-based model of attenuation and following preferred Q( f) dependences while ignoring the true χ( f) trends within the individual frequency bands.     

The seismic wave absorption in the crust and upper mantle in the vicinity of the Kislovodsk seismic station

The Q-factor estimates of the Earth’s crust and upper mantle as the functions of frequency (Q(f)) are obtained for the seismic S-waves at frequencies up to ~35 Hz. The estimates are based on the data for ~40 earthquakes recorded by the Kislovodsk seismic station since 2000. The magnitudes of these events are M_W > 3.8, the sources are located in the depth interval from 1 to 165 km, and the epicentral distances range from ~100 to 300 km. The Q-factor estimates are obtained by the methods developed by Aki and Rautian et al., which employ the suppression of the effects of the source radiation spectrum and local site responses in the S-wave spectra by the coda waves measured at a fixed lapse time (time from the first arrival). The radiation pattern effects are cancelled by averaging over many events whose sources are distributed in a wide azimuthal sector centered at the receiving site. The geometrical spreading was specified in the form of a piecewise-continuous function of distance which behaves as 1/R at the distances from 1 to 50 km from the source, has a plateau at 1/50 in the interval from 50–70 km to 130–150 km, and decays as \({\raise0.7ex\hbox{$1$} \!\mathord{\left/ {\vphantom {1 {\sqrt R }}}\right.\kern-\nulldelimiterspace} \!\lower0.7ex\hbox{${\sqrt R }$}}\) beyond 130–150 km. For this geometrical spreading model and some of its modifications, the following Q-factor estimates are obtained: Q(f) ~ 85f^0.9 at the frequencies ranging from ~1 to 20 Hz and Q(f) ~ 75f^1.0 at the frequencies ranging from ~1 to 35 Hz.     

Regeneration and utilization of nutrients during collapse of a <Emphasis Type="Italic">Mesodinium rubrum</Emphasis> red tide and its influence on phytoplankton species composition

High-biomass red tides occur frequently in some semi-enclosed bays of Hong Kong where ambient nutrients are not high enough to support such a high phytoplankton biomass. These high-biomass red tides release massive inorganic nutrients into local waters during their collapse. We hypothesized that the massive inorganic nutrients released from the collapse of red tides would fuel growth of other phytoplankton species. This could influence phytoplankton species composition. We tested the hypothesis using a red tide event caused by Mesodinium rubrum (M. rubrum) in a semi-enclosed bay, Port Shelter. The red tide patch had a cell density as high as 5.0×10⁵ cells L^?1, and high chlorophyll a (63.71 μg L^?1). Ambient inorganic nutrients (nitrate: \(\rm{NO}_3^-\), ammonium: \(\rm{NH}_4^+\), phosphate: \(\rm{PO}_4^{3-}\), silicate: \(\rm{SiO}_4^{3-}\)) were low both in the red tide patch and the non-red-tide patch (clear waters outside the red tide patch). Nutrient addition experiments were conducted by adding all the inorganic nutrients to water samples from the two patches followed by incubation for 9 days. The results showed that the addition of inorganic nutrients did not sustain high M. rubrum cell density, which collapsed after day 1, and did not drive M. rubrum in the non-red-tide patch sample to the same high-cell density in the red tide patch sample. This confirmed that nutrients were not the driving factor for the formation of this red tide event, or for its collapse. The death of M. rubrum after day 1 released high concentrations of \(\rm{NO}_3^-\), \(\rm{PO}_4^{3-}\), \(\rm{SiO}_4^{3-}\), \(\rm{NH}_4^+\), and urea. Bacterial abundance and heterotrophic activity increased, reaching the highest on day 3 or 4, and decreased as cell density of M. rubrum declined. The released nutrients stimulated growth of diatoms, such as Chaetoceros affinis var. circinalis, Thalassiothrix frauenfeldii, and Nitzschia sp., particularly with additions of \(\rm{SiO}_4^{3-}\) treatments, and other species. These results demonstrated that initiation of M. rubrum red tides in the bay was not directly driven by nutrients. However, the massive inorganic nutrients released from the collapse of the red tide could induce a second bloom in low-ambient nutrient water, influencing phytoplankton species composition.     

Contrasted turbulence intensities in the Indonesian Throughflow: a challenge for parameterizing energy dissipation rate

Microstructure measurements were performed along two sections through the Halmahera Sea and the Ombai Strait and at a station in the deep Banda Sea. Contrasting dissipation rates (??) and vertical eddy diffusivities (K _z ) were obtained with depth-averaged ranges of \(\sim [9 \times 10^{-10}-10^{-5}]\) W kg^??1 and of \(\sim [1 \times 10^{-5}-2 \times 10^{-3}]\) m² s^??1, respectively. Similarly, turbulence intensity, \(I={\epsilon }/(\nu N^{2})\) with ν the kinematic viscosity and N the buoyancy frequency, was found to vary seven orders of magnitude with values up to \(10^{7}\). These large ranges of variations were correlated with the internal tide energy level, which highlights the contrast between regions close and far from internal tide generations. Finescale parameterizations of ?? induced by the breaking of weakly nonlinear internal waves were only relevant in regions located far from any generation area (“far field”), at the deep Banda Sea station. Closer to generation areas, at the “intermediate field” station of the Halmahera Sea, a modified formulation of MacKinnon and Gregg (2005) was validated for moderately turbulent regimes with 100 < I < 1000. Near generation areas marked by strong turbulent regimes such as “near field” stations within strait and passages, ?? is most adequately inferred from horizontal velocities provided that part of the inertial subrange is resolved, according to Kolmogorov scaling.     

Crustal stress field in Yunnan: implication for crust-mantle coupling

We applied the g CAP algorithm to determine239 focal mechanism solutions 3:0 M We 6:0T with records of dense Chin Array stations deployed in Yunnan,and then inverted 686 focal mechanisms(including 447 previous results) for the regional crustal stress field with a damped linear inversion. The results indicate dominantly strike-slip environment in Yunnan as both the maximum(r1) and minimum(r3) principal stress axes are sub-horizontal. We further calculated the horizontal stress orientations(i.e., maximum and minimum horizontal compressive stress axes: S H and S h, respectively) accordingly and found an abrupt change near *26°N. To the north, S H aligns NW-SE to nearly E-W while S h aligns nearly N-S. In contrast, to the south, both S H and S h rotate laterally and show dominantly fan-shaped patterns. The minimum horizontal stress(i.e., maximum strain axis) S h rotates from NW-SE to the west of Tengchong volcano gradually to nearly E-W in west Yunnan, and further toNE-SW in the South China block in the east. The crustal strain field is consistent with the upper mantle strain field indicated by shear-wave splitting observations in Yunnan but not in other regions. Therefore, the crust and upper mantle in Yunnan are coupled and suffering vertically coherent pure-shear deformation in the lithosphere.     

Wave boundary layers in rotating stratified fluid and near-inertial oscillations

Theory of wave boundary layers (WBLs) developed by Reznik (J Mar Res 71: 253–288, 2013, J Fluid Mech 747: 605–634, 2014, J Fluid Mech 833: 512–537, 2017) is extended to a rotating stratified fluid. In this case, the WBLs arise in the field of near-inertial oscillations (NIOs) driven by a tangential wind stress of finite duration. Near-surface Ekman layer is specified in the most general form; tangential stresses are zero at the lower boundary of Ekman layer and viscosity is neglected below the boundary. After the wind ceases, the Ekman pumping at the boundary becomes a linear superposition of inertial oscillations with coefficients dependent on the horizontal coordinates. The solution under the Ekman layer is obtained in the form of expansions in the vertical wave modes. We separate from the solution a part representing NIO and demonstrate development of a WBL near the Ekman layer boundary. With increasing time t, the WBL width decays inversely proportional to \( \sqrt{t} \) and gradients of fields in the WBL grow proportionally to \( \sqrt{t} \); the most part of NIO is concentrated in the WBL. Structure of the WBL depends strongly on its horizontal scale L determined by scale of the wind stress. The shorter the NIO is, the thinner and sharper the WBL is; the short-wave NIO with L smaller than the baroclinic Rossby scale L_R does not penetrate deep into the ocean. On the contrary, for L?≥?L_R, the WBL has a smoother vertical structure; a significant long-wave NIO signal is able to reach the oceanic bottom. An asymptotic theory of the WBL in rotating stratified fluid is suggested.     

Stochastic modelling of relative water permeability in vegetative soils with implications on stability of bioengineered slope

Vegetation is known to influence the hydrological state variables, suction \( \left( \psi \right) \) and volumetric water content (\( \theta_{w} \)) of soil. In addition, vegetation induces heterogeneity in the soil porous structure and consequently the relative permeability (\( k_{r} \)) of water under unsaturated conditions. The indirect method of utilising the soil water characteristic curve (SWCC) is commonly adopted for the determination of \( k_{r} \). In such cases, it is essential to address the stochastic behaviour of SWCC, in order to conduct a robust analysis on the \( k_{r} \) of vegetative cover. The main aim of this study is to address the uncertainties associated with \( k_{r} \), using probabilistic analysis, for vegetative covers (i.e., grass and tree species) with bare cover as control treatment. We propose two approaches to accomplish the aforesaid objective. The univariate suction approach predicts the probability distribution functions of \( {\text{k}}_{\text{r}} \), on the basis of identified best probability distribution of suction. The bivariate suction and water content approach deals with the bivariate modelling of the water content and suction (SWCC), in order to capture the randomness in the permeability curves, due to presence of vegetation. For this purpose, the dependence structure of \( \psi \) and \( \theta_{w} \) is established via copula theory, and the \( k_{r} \) curves are predicted with respect to varying levels of \( \psi - \theta_{w} \) correlation. The results showed that the \( k_{r} \) of vegetative covers is substantially lower than that in bare covers. The reduction in \( k_{r} \) with drying is more in tree cover than grassed cover, since tree roots induce higher levels of suction. Moreover, the air entry value of the soil depends on the magnitude of \( \psi - \theta_{w} \) correlation, which in turn, is influenced by the type of vegetation in the soil. \( k_{r} \) is found to be highly uncertain in the desaturation zone of the relative permeability curve. The stochastic behaviour of \( k_{r} \) is found to be most significant in tree covers. Finally, a simplified case study is also presented in order to demonstrate the impact of the uncertainty in \( k_{r} \), on the stability of vegetates slopes. With an increment in the parameter \( \alpha \), factor of safety (FS) is found to decrease. The trend of FS is reverse of this with parameter \( n \). Overall FS is found to vary around 4–5%, for both bare and vegetative slopes.     

Spatial inhomogeneity of variations in the <Emphasis Type="Italic">F</Emphasis><Subscript>2</Subscript> layer critical frequencies under the conditions of winter 1995

The daily samples of the hourly measurements of the foF2 critical frequency, obtained on January 5–21, 1995, at the midlatitude and high-latitude automated ionospheric stations (geographic latitude higher than 60°), are considered. The {fo} sets are transformed into the {δfoF2} sets of relative variations, for which asymmetry (A) and excess (E) are calculated. The selected stations are grouped into 20 pairs of automated ionospheric stations (AISs) located at distances of 200–10 000 km from one another. Sign estimates of the cross-correlation coefficients between the sets of 16 A and E values for different pairs of stations are used. Two types of structures of the statistical invariant spatial distribution are established: the structures with a scale of about 300 km, invariant with respect to latitude, and with a scale of about 6000 km (for only high latitudes).     

Generous statistical tests

A common statistical problem is deciding which of two possible sources, A and B, of a contaminant is most likely the actual source. The situation considered here, based on an actual problem of polychlorinated biphenyl contamination discussed below, is one in which the data strongly supports the hypothesis that source A is responsible. The problem approach here is twofold: One, accurately estimating this extreme probability. Two, since the statistics involved will be used in a legal setting, estimating the extreme probability in such a way as to be as generous as is possible toward the defendant’s claim that the other site B could be responsible; thereby leaving little room for argument when this assertion is shown to be highly unlikely. The statistical testing for this problem is modeled by random variables {X _i } and the corresponding sample mean the problem considered is providing a bound ɛ for which for a given number a ₀. Under the hypothesis that the random variables {X _i } satisfy E(X _i ) ≤ μ, for some 0  < μ < 1, statistical tests are given, described as “generous”, because ɛ is maximized. The intent is to be able to reject the hypothesis that a ₀ is a value of the sample mean while eliminating any possible objections to the model distributions chosen for the {X _i } by choosing those distributions which maximize the value of ɛ for the test used.     

Stochastic finite-fault simulation of ground motion from the August 11, 2012, <Emphasis Type="Italic">M</Emphasis><Subscript><Emphasis Type="Italic">w</Emphasis></Subscript> 6.4 Ahar earthquake,northwestern Iran

In this study, the 11 August 2012 M _w 6.4 Ahar earthquake is investigated using the ground motion simulation based on the stochastic finite-fault model. The earthquake occurred in northwestern Iran and causing extensive damage in the city of Ahar and surrounding areas. A network consisting of 58 acceleration stations recorded the earthquake within 8–217 km of the epicenter. Strong ground motion records from six significant well-recorded stations close to the epicenter have been simulated. These stations are installed in areas which experienced significant structural damage and humanity loss during the earthquake. The simulation is carried out using the dynamic corner frequency model of rupture propagation by extended fault simulation program (EXSIM). For this purpose, the propagation features of shear-wave including \( {Q}_s \) value, kappa value \( {k}_0 \), and soil amplification coefficients at each site are required. The kappa values are obtained from the slope of smoothed amplitude of Fourier spectra of acceleration at higher frequencies. The determined kappa values for vertical and horizontal components are 0.02 and 0.05 s, respectively. Furthermore, an anelastic attenuation parameter is derived from energy decay of a seismic wave by using continuous wavelet transform (CWT) for each station. The average frequency-dependent relation estimated for the region is \( Q=\left(122\pm 38\right){f}^{\left(1.40\pm 0.16\right)}. \) Moreover, the horizontal to vertical spectral ratio \( H/V \) is applied to estimate the site effects at stations. Spectral analysis of the data indicates that the best match between the observed and simulated spectra occurs for an average stress drop of 70 bars. Finally, the simulated and observed results are compared with pseudo acceleration spectra and peak ground motions. The comparison of time series spectra shows good agreement between the observed and the simulated waveforms at frequencies of engineering interest.     

Sampling uncertainties and source <Emphasis Type="Italic">b</Emphasis> likelihood for the Gutenberg-Richter <Emphasis Type="Italic">b</Emphasis> value from the Aki-Utsu method

The Aki-Utsu method of Gutenberg-Richter (G-R) b value estimation is often misapplied so that estimations not using the G-R histogram are often meaningless because they are not based on adequate samples. We propose a method to estimate the likelihood Pr(b?b _m , N, M ₁, M ₂) that an observed b _m estimate, based on a sample of N magnitudes within an [M ₁????≤?ΔM/2,?M ₂?+?ΔM/2) range, where ΔM?=?0.1 is the usual rounding applied to magnitudes, is due to a “true” source b value, b, and use these likelihoods to estimate source b ranges corresponding to various confidence levels. As an example of application of the method, we estimate the b values before and after the occurrence of a 7.4-magnitude earthquake in the Mexican subduction zone, and find a difference of 0.82 between them with 100% confidence that the b values are different.     

A way of estimating the characteristic slip displacement

During the ruptures of an earthquake,the strain energy.△E,.will be transferred into,at least,three parts,i.e..the seismic radiation energy(E_s),fracture energy(E_g),and frictional energy(E_f),that is,△E = E_s + E_g + E_f.Friction,which is represented by a velocity- and state-dependent friction law by some researchers,controls the three parts.One of the main parameters of the law is the characteristic slip displacement.D_c.It is significant and necessary to evaluate the reliable value of D_c from observed and inverted seismic data.Since D_c controls the radiation efficiency.η_R = E_s/(E_s+ E_g),the value of η_r is a good constraint of estimating D_c.Integrating observed data and inverted results of source parameters from recorded seismograms.the values of E_s and E_g of an earthquake can be measured,thus leading to the value of η_R.The constraint used to estimate the reliable value of D_c will be described in this work.An example of estimates of D_c.based on the observed and inverted values of source parameters of the September 20,1999 M_S 7.6 Chi-Chi(Ji-Ji).Taiwan region,earthquake will be presented.     

Effect of zonal E × B plasma drift on electron density in the low-latitude ionospheric <Emphasis Type="Italic">F</Emphasis> region at a solar activity maximum near vernal equinox

The variations in the density of the ionospheric F2 layer maximum (NmF2) under the action of the zonal plasma drift perpendicularly to the magnetic (B) and electric (E) fields in the direction geomagnetic west-geomagnetic east have been studied using the three-dimensional nonstationary theoretical model of electron and ion densities (N _e and N _i ) and temperatures (T _e and T _i ) in the low-latitude and midlatitude ionospheric F region and plasmasphere. The method of numerical calculations of N _e , N _i , T _e , and T _i , including the advantages of the Lagrangian and Eulerian methods, is used in the model. A dipole approximation of the geomagnetic field (B), taking into account the non-coincidence of the geographic and geomagnetic poles and differences between the positions of the Earth’s and geomagnetic dipole centers, is accepted in the calculations. The calculated NmF2 and altitudes of the F2 layer maximum (hmF2) have been compared with these quantities measured at 16 low-latitude ionospheric sounding stations during the geomagnetically quiet period October 11–12, 1958. This comparison made it possible to correct the input model parameters: the NRLMSISE-00 model [O], the meridional component of the neutral wind velocity according to the HWW90 model, and the meridional component of the equatorial plasma drift due to the electric field specified by the empirical model. It has been indicated that the effect of the zonal E × B plasma drift on NmF2 can be neglected under daytime conditions and changes in NmF2 and hmF2 under the action of this drift are insignificant under nighttime conditions north of 25° and south of ?26° geomagnetic latitude. The effect of the zonal E × B plasma drift on NmF2 and hmF2 is most substantial in the nightside ionosphere approximately from ?20° to 20° geomagnetic latitude, and the neglect of this drift results in an up to 2.4-fold underestimation of NmF2. The found dependence of the effect of the zonal E × B plasma drift on NmF2 and hmF2 on geomagnetic latitude is related to the longitudinal asymmetry of B, asymmetry of the neutral wind about the geomagnetic equator, and changes in the meridional E × B plasma drift at a change in geomagnetic longitude.     

Application of the dynamic calibration method to international monitoring system stations in Central Asia using natural seismicity data

The dynamic calibration method (DCM), using natural seismicity data and initially elaborated in [Kedrov, 2001; Kedrov et al., 2001; Kedrov and Kedrov, 2003], is applied to International Monitoring System (IMS) stations in Central Asia. The algorithm of the method is refined and a program is designed for calibrating diagnostic parameters (discriminants) that characterize a seismic source on the source-station traces. The DCM calibration of stations in relation to the region under study is performed by the choice of attenuation coefficients that adapt the diagnostic parameters to the conditions in a reference region. In this method, the stable Eurasia region is used as the latter. The calibration used numerical data samples taken from the archive of the International Data Centre (IDC) for the IMS stations MKAR, BVAR, EIL, ASF, and CMAR. In this paper, we used discriminants in the spectral and time domains that have the form

$D_i = X_i - a_m m_b - b_\Delta \log \Delta $

and are independent of the magnitude m _b and the epicentral distance Δ; these discriminants were elaborated in [Kedrov et al., 1990; Kedrov and Lyuke, 1999] on the basis of a method used for identification of events at regional distances in Eurasia. Prerequisites of the DCM are the assumptions that the coefficient a _m is regionindependent and the coefficient b _Δ depends only on the geotectonic characteristics of the medium and does not depend on the source type. Thus, b _Δ can be evaluated only from a sample of earthquakes in the region studied; it is used for adapting the discriminants D(X _i ) in the region studied to the reference region. The algorithm is constructed in such a way that corrected values of D(X i) are calculated from the found values of the calibration coefficients b _Δ, after which natural events in the region under study are selected by filtering. Empirical estimates of the filtering efficiency as a function of a station vary in a range of 95–100%. The DCM was independently tested using records obtained at the IRIS (Incorporated Research Institutions for Seismology) stations BRVK and MAKZ from explosions detonated in India on May 11, 1998, and Pakistan on May 28, 1998; these stations are similar in location and recording instrumentation characteristics to the IMS stations BVAR and MKAR. This test resulted in correct recognition of the source type and thereby directly confirmed the validity of the proposed calibration method of stations with the use of natural seismicity data. It is shown that the calibration coefficients b _Δ for traces similar in the conditions of signal propagation (e.g., the traces from Iran to the stations EIL and ASF) are comparable for nearly all diagnostic parameters. We arrive at the conclusion that the method of dynamic calibration of stations using natural seismicity data in a region where no explosions were detonated can be significant for a rapid and inexpensive calibration of IMS stations. The DCM can also be used for recognition of industrial chemical explosions that are sometimes erroneously classified in regional catalogs as earthquakes.