Determination and prediction of standardized precipitation index (SPI) using TRMM data in arid ecosystems

Drought over a period threatens the water resources, agriculture, and socioeconomic activities. Therefore, it is crucial for decision makers to have a realistic anticipation of drought events to mitigate its impacts. Hence, this research aims at using the standardized precipitation index (SPI) to predict drought through time series analysis techniques. These adopted techniques are autoregressive integrating moving average (ARIMA) and feed-forward backpropagation neural network (FBNN) with different activation functions (sigmoid, bipolar sigmoid, and hyperbolic tangent). After that, the adequacy of these two techniques in predicting the drought conditions has been examined under arid ecosystems. The monthly precipitation data used in calculating the SPI time series (SPI 3, 6, 12, and 24 timescales) have been obtained from the tropical rainfall measuring mission (TRMM). The prediction of SPI was carried out and compared over six lead times from 1 to 6 using the model performance statistics (coefficient of correlation (R), mean absolute error (MAE), and root mean square error (RMSE)). The overall results prove an excellent performance of both predicting models for anticipating the drought conditions concerning model accuracy measures. Despite this, the FBNN models remain somewhat better than ARIMA models with R?≥?0.7865, MAE?≤?1.0637, and RMSE?≤?1.2466. Additionally, the FBNN based on hyperbolic tangent activation function demonstrated the best similarity between actual and predicted for SPI 24 by 98.44%. Eventually, all the activation function of FBNN models has good results respecting the SPI prediction with a small degree of variation among timescales. Therefore, any of these activation functions can be used equally even if the sigmoid and bipolar sigmoid functions are manifesting less adjusted R² and higher errors (MAE and RMSE). In conclusion, the FBNN can be considered a promising technique for predicting the SPI as a drought monitoring index under arid ecosystems.     

The transfer of oxygen isotopic signals from precipitation to drip water and modern calcite on the seasonal time scale in Yongxing Cave,central China

Stable isotope data of precipitation (δ¹⁸O_p and deuterium excess), drip water (δ¹⁸O_d), and modern calcite precipitates (δ¹⁸O_c and δ¹³C_c) from Yongxing Cave, central China, are presented, with monthly sampling intervals from June 2013 to September 2016. Moderate correlations between the monthly variation of δ¹⁸O_p values (from ??11.5 to ??0.7‰) and precipitation amount (r = ??0.59, n?=?34, p?<?0.01) and deuterium excess (r?=?0.39, n?=?31, p?<?0.01) imply a combined effect of changes in precipitation amount and atmospheric circulation. At five drip sites, the δ¹⁸O_d values have a much smaller variability (from ??9.1 to ??7.5‰), without seasonal signals, probably a consequence of the mixing in the karst reservoir with a deep aquifer. The mean δ¹⁸O_d value (??8.4‰) for all drip waters is significantly more negative than the mean δ¹⁸O_p value (??6.9‰) weighted by precipitation amount, but close to the wet season (May to September) mean value (??8.3‰), suggesting that a threshold of precipitation amount must be exceeded to provide recharge. Calculation based on the equilibrium fractionation factor indicates that the δ¹⁸O_c values are not in isotopic equilibrium with their corresponding drip waters, with a range of disequilibrium effects from 0.4 to 1.4‰. The δ¹⁸O_c and δ¹³C_c values generally increase progressively away from the locus of precipitation on glass plates. The disequilibrium effects in the cave are likely caused by progressive calcite precipitation and CO₂ degassing related to a high gradient of CO₂ concentration between drip waters and cave air. Our study provides an important reference to interpret δ¹⁸O_c records from the monsoon region of China.     

Community vulnerability to hazards: introducing local expert knowledge into the equation

The accuracies of three different evolutionary artificial neural network (ANN) approaches, ANN with genetic algorithm (ANN-GA), ANN with particle swarm optimization (ANN-PSO) and ANN with imperialist competitive algorithm (ANN-ICA), were compared in estimating groundwater levels (GWL) based on precipitation, evaporation and previous GWL data. The input combinations determined using auto-, partial auto- and cross-correlation analyses and tried for each model are: (i) GWL _t?1 and GWL _t?2; (ii) GWL _t?1, GWL _t?2 and P _t ; (iii) GWL _t?1, GWL _t?2 and E _t ; (iv) GWL _t?1, GWL _t?2, P _t and E _t ; (v) GWL _t?1, GWL _t?2 and P _t?1 where GWL _t , P _t and E _t indicate the GWL, precipitation and evaporation at time t, individually. The optimal ANN-GA, ANN-PSO and ANN-ICA models were obtained by trying various control parameters. The best accuracies of the ANN-GA, ANN-PSO and ANN-ICA models were obtained from input combination (i). The mean square error accuracies of the ANN-GA and ANN-ICA models were increased by 165 and 124% using ANN-PSO model. The results indicated that the ANN-PSO model performed better than the other models in modeling monthly groundwater levels.     

Prediction of longitudinal dispersion coefficient using multivariate adaptive regression splines

In this paper, multivariate adaptive regression splines (MARS) was developed as a novel soft-computing technique for predicting longitudinal dispersion coefficient (D_L) in rivers. As mentioned in the literature, experimental dataset related to D_L was collected and used for preparing MARS model. Results of MARS model were compared with multi-layer neural network model and empirical formulas. To define the most effective parameters on D_L, the Gamma test was used. Performance of MARS model was assessed by calculation of standard error indices. Error indices showed that MARS model has suitable performance and is more accurate compared to multi-layer neural network model and empirical formulas. Results of the Gamma test and MARS model showed that flow depth (H) and ratio of the mean velocity to shear velocity (u/u^?) were the most effective parameters on the D_L.     

Biogeochemistry of a River-Dominated Estuary Influenced by Drought and Storms

Increased frequency and severity of droughts, as well as growing human freshwater demands, in the Apalachicola-Chattahoochee-Flint River Basin are expected to lead to a long-term decrease in freshwater discharge to Apalachicola Bay (Florida). To date, no long-term studies have assessed how river discharge variability affects the Bay’s phytoplankton community. Here a 14-year time series was used to assess the influence of hydrologic variability on the biogeochemistry and phytoplankton biomass in Apalachicola Bay. Data were collected at 10 sites in the bay along the salinity gradient and include drought and storm periods. Riverine dissolved inorganic nitrogen and phosphate inputs were correlated to river discharge, but chlorophyll a (Chl a) was similar between periods of drought and average/above-average river discharge in most of the Bay. Results suggest that the potentially negative impact of decreased riverine nutrient input on Bay phytoplankton biomass is mitigated by the nutrient buffering capacity of the estuary. Additionally, increased light availability, longer residence time, and decreased grazing pressures may allow more Chl a biomass to accumulate during drought. In contrast to droughts, tropical cyclones and subsequent increases in river discharge increased flushing and reduced light penetration, leading to reduced Chl a in the Bay. Analysis of the time series revealed that Chl a concentrations in the Bay do not directly mirror the effect of riverine nutrient input, which is masked by multiple interacting mechanisms (i.e., nutrient loading and retention, grazing, flushing, light penetration) that need to be considered when projecting the response of Bay Chl a to changes in freshwater input.     

Compressibility of Sands of Various Geologic Origins at Pre-crushing Stress Levels

This study quantifies the influence of various intrinsic soil properties including particle roundness, R, sphericity, S, 50% size by weight, D ₅₀, coefficient of uniformity, C _u, and the state property of relative density, D _r, on the compression and recompression indices, C _c and C _r, of sands of various geologic origins at pre-crushing stress levels. Twenty-four sands exhibiting a wide range of particle shapes, gradations, and geologic origins were collected for the study. The particle shapes were determined using a computational geometry algorithm which allows characterization of a statistically large number of particles in specimens. One dimensional oedometer tests were performed on the soils. The new data was augmented with many previously published results. Through statistical analyses, simple functional relationships are developed for C _c and C _r. In both cases, the models utilized only R and D _r since other intrinsic properties proved to have lesser direct influence on the compression indices. However, previous studies showed that the contributions of S and C _u are felt through their effects on index packing void ratios and thus on D _r. The accuracy of the models was confirmed by comparison of predicted and observed C _c and C _r values.     

Multi-time-scale analysis of hydrological drought forecasting using support vector regression (SVR) and artificial neural networks (ANN)

In this study, the preprocessing of the gamma test was used to select the appropriate input combination into two models including the support vector regression (SVR) model and artificial neural networks (ANNs) to predict the stream flow drought index (SDI) of different timescales (i.e., 3, 6, 9, 12, and 24 months) in Latian watershed, Iran, which is one of the most important sources of water for the large metropolitan Tehran. The variables used included SDI _t , SDI _t ? 1, SDI _t ? 2, SDI _t ? 3, and SDI _t ? 4 monthly delays. Two variables including SDI _t and SDI _t ? 1 with lower gamma values were identified as the most optimal combination of variables in all drought timescales. The results showed that the gamma test was able to correctly identify the right combination for the forecasting of 6, 9, and 12 months SDI using the ANN model. Also, the gamma test was considered in selecting the appropriate inputs for identifying the values of 9, 12, and 24 months SDI in SVR. The support vector machine approach showed a better efficiency in the forecast of long-term droughts compared to the artificial neural network. In total, among forecasts made for 30 scenarios, the support vector machine model only in scenario 3 of SDI₃, scenario 1 of SDI₆, and scenarios 2 and 3 of SDI₂₄ represented poorer efficiency compared to the artificial neural network (MLP layer), but in other scenarios, the results of SVR had better efficiency.     

Global solar magnetology and reference points of the solar cycle

The solar cycle can be described as a complex interaction of large-scale/global and local magnetic fields. In general, this approach agrees with the traditional dynamo scheme, although there are numerous discrepancies in the details. Integrated magnetic indices introduced earlier are studied over long time intervals, and the epochs of the main reference points of the solar cycles are refined. A hypothesis proposed earlier concerning global magnetometry and the natural scale of the cycles is verified. Variations of the heliospheric magnetic field are determined by both the integrated photospheric i(B _r )_ph and source surface i(B _r )_ss indices, however, their roles are different. Local fields contribute significantly to the photospheric index determining the total increase in the heliospheric magnetic field. The i(B _r )_ss index (especially the partial index ZO, which is related to the quasi-dipolar field) determines narrow extrema. These integrated indices supply us with a “passport” for reference points, making it possible to identify them precisely. A prominent dip in the integrated indices is clearly visible at the cycle maximum, resulting in the typical double-peak form (the Gnevyshev dip), with the succeeding maximum always being higher than the preceding maximum. At the source surface, this secondary maximum significantly exceeds the primary maximum. Using these index data, we can estimate the progression expected for the 23rd cycle and predict the dates of the ends of the 23rd and 24th cycles (the middle of 2007 and December 2018, respectively).     

Is NGC 7006 a globular cluster with a primarily red horizontal branch?

A CCD BV R photometric study of the central region (15″ ≤ r ≤ 100″) of the globular cluster NGC 7006 based on color-magnitude diagrams is presented. We find for the main parameters of the cluster [Fe/H] = ?1.62, Y = 0.21, E _B?V = 0.15 ^m , V _HB = 18.84 ^m , M _V ^HB =+0.56 ^m , R _⊙ = 37.1 kpc). Two previously unknown RR Lyr variables were discovered in the central region of the cluster. The morphological index of the horizontal branch for the entire region studied indicates that the red stellar population dominates, consistent with previous studies: HB _mi = ?0.13. Such anomalously negative morphological indices are possessed by a whole group of Ool clusters with intermediate metallicities, which also display a characteristic distribution of stars along the horizontal branch. There is a radial dependence for the horizontal-branch morphology, with the color becoming primarily blue with approach toward the cluster center. One possible origin for this behavior could be the effect of inner dynamical processes on the spatial distribution of hot stars.     

Prediction of strength parameters of sedimentary rocks using artificial neural networks and regression analysis

Accurate laboratory measurement of geo-engineering properties of intact rock including uniaxial compressive strength (UCS) and modulus of elasticity (E) involves high costs and a substantial amount of time. For this reason, it is of great necessity to develop some relationships and models for estimating these parameters in rock engineering. The present study was conducted to forecast UCS and E in the sedimentary rocks using artificial neural networks (ANNs) and multivariable regression analysis (MLR). For this purpose, a total of 196 rock samples from four rock types (i.e., sandstone, conglomerate, limestone, and marl) were cored and subjected to comprehensive laboratory tests. To develop the predictive models, physical properties of studied rocks such as P wave velocity (V_p), dry density (γ_d), porosity, and water absorption (A_b) were considered as model inputs, while UCS and E were the output parameters. We evaluated the performance of MLR and ANN models by calculating correlation coefficient (R), mean absolute error (MAE), and root-mean-square error (RMSE) indices. The comparison of the obtained results revealed that ANN outperforms MLR when predicting the UCS and E.     

High-pressure displacive phase transition of a natural Mg-rich pigeonite

A high-pressure single-crystal X-ray diffraction study has been carried out on a P2₁/c natural Mg-rich pigeonite sample with composition ca. Wo₆En₇₆Fs₁₈ using a diamond anvil-cell. The unit-cell parameters were determined at 14 different pressures to 7.14 GPa. The sudden disappearance of the b-type reflections (h + k = odd) and a strong discontinuity (about 2.8%) in the unit-cell volume indicated a first-order P2₁/c–C2/c phase transition between 4.66 and 4.88 GPa. The P(V) data of the P2₁/c phase were fitted to 4.66 GPa by a third-order Birch–Murnaghan equation of state (BM3 EoS), whereas the limited number of experimental data collected within the C2/c phase between 4.88 and 7.14 GPa were fitted using the same equation of state but with K′ constrained to the value obtained for the P2₁/c fitting. The equation of state coefficients are V ₀ = 424.66(6) ų, K _T0 = 104(2) GPa and K′ = 8(1) for the P2₁/c phase, and V ₀ = 423.6(1) ų, K _T0 = 112.4(8) GPa, and K′ fixed to 8(1) for the C2/c phase. The axial moduli for a, b, and c for the P2₁/c phase were obtained using also a BM3-EoS, while for the C2/c phase only a linear calculation could be performed, and therefore the same approach was applied for comparison also to the P2₁/c phase. In general the C2/c phase exhibits axial compressibilities (β _c > β _a >> β _b) lower than those of the P2₁/c phase (β _b > β _c ≈ β _a; similar to those found in previous studies in clinopyroxenes and orthopyroxenes). The lower compressibility of the C2/c phase compared with that of the P2₁/c could be ascribed to the greater stiffness along the b direction. A previously published relationship between P _c and M2 average cation radius (i.r.) has been updated using all the literature data on P2₁/c clinopyroxene containing large cations at M2 site and our new data. The following weighted regression was obtained: P _c (GPa) = 26(4) ? 28(5) ×  i.r (Å), R ² = 0.97. This improved equation can be used to predict the critical pressure of natural P2₁/c clinopyroxene samples just knowing the composition at M2 site.     

Masses of the visual components and black holes in X-ray novae: Effects of proximity of the components

It is shown that the approximation of the complex, tidally distorted shape of a star as a circular disc with local line profiles and a linear limb-darkening law, which is usually applied when deriving equatorial stellar rotation velocities from line profiles, leads to overestimation of the equatorial velocity V _rot sin i and underestimation of the component mass ratio q = M _x /M _v . A formula enabling correction of the effect of these simplifying assumptions on the shape of a star is used to re-determine the mass ratios q and the masses of the black holes M _x and visual components M _v in low-mass X-ray binary systems containing black holes. Taking into account the tidal–rotational distortion of the stellar shape can significantly increase the mass ratios q = M _x /M _v , reducing M _v , while M _x changes only slightly. The resulting distribution of M _v attains its maximum near M _v ? 0.35M _⊙, in disagreement with the results of population synthesis computations realizing standard models for Galactic X-ray novae with black holes. Possible ways to overcome this inconsistency are discussed. The derived distribution of M _x also differs strongly from the mass distribution for massive stars in the Galaxy.     

Development of a technique for IR spectroscopic determination of nitrogen content and aggregation degree in diamond crystals

A technique for IR spectroscopic determination of the total nitrogen content N _S in the form of A-and B ₁-defects is suggested. It provides for the computer processing and decomposition of IR spectra into constituent bands, calculation of the total absorption band area S _N and individual areas S _A and S _B1 and their normalization with respect to the total area of the diamond intrinsic absorption S ₀, with the normalization coefficients K _S , K _A , and K _B1 being calculated. Based on the analysis of the IR spectra of 60 octahedral diamond crystals from the Mir and Yubileinaya pipes (Sakha-Yakutiya), the empirical functions N _S = 911.85 K _S ^0.9919 ppm (R ² = 0.9859), N _A = 1185.6 K _A ^1.1511 ppm (R ² = 0.8703), and N _B1 = 911.85 K _S ^0.9919 ? 1185.6 K _A ^1.1511 ppm have been defined.     

Estimating groundwater evapotranspiration rates using diurnal water-table fluctuations in a semi-arid riparian zone

In semi-arid climates, phreatophytes draw on shallow aquifers, and groundwater evapotranspiration (ET_G) is a principal component of groundwater budgets. Diurnal water table fluctuations, which often are a product of ET_G, were monitored in the riparian zone of Red Canyon Creek, Wyoming, USA. These fluctuations were higher in a riparian wetland (2–36 mm) than a grass-covered meadow (1–6 mm). The onset and cessation of water-table fluctuations correspond to daily temperatures relative to freezing. Spatial differences were due to vegetation type and specific yield, while temporal changes were due to vegetation dormancy. Ratios of ET_G to potential evapotranspiration (PET), K _c,GW, were similar to ratios of actual evapotranspiration (ET) to PET, K _c, in semi-arid rangelands. Before vegetation senescence, K _c,GW increased between precipitation events, suggesting phreatophytes pull more water from the saturated zone as soil moisture decreases. In contrast, K _c decreases with soil moisture following precipitation events as ET becomes increasingly water-limited. Error in ET_G is primarily from estimates of specific yield (S _y), which is difficult to quantify in heterogeneous sediments. ET_G values may be more reliable because the range of acceptable S _y is smaller than K _c and S _y does not change with vegetation type or soil moisture.     

Comparison of the magnetic properties of leading and following spots and the overlying ultraviolet emission

SDO/HMI and SDO/AIA data for the 24th solar-activity cycle are analyzed using a quicker and more accurate method for resolving π ambiguities in the transverse component of the photospheric magnetic field, yielding new results and confirming some earlier results on the magnetic properties of leading and following magnetically connected spots and single spots. The minimum inclination of the field lines to the positive normal to the solar surface α _min within umbrae is smaller in leading than in following spots in 78% of the spot pairs considered; the same trend is found for the mean angle 〈α〉 in 83% of the spot pairs. Positive correlations between the α _min values and the 〈α〉 values in leading and following spots are also found. On average, in umbrae, the mean values of 〈B〉, the umbra area S, and the angles α _min and 〈α〉 decrease with growth in the maximum magnetic field B _max in both leading and following spots. The presence of a positive correlation between B _max and S is confirmed, and a positive correlation between 〈B〉 and S in leading and following spots has been found. Themagnetic properties of the umbrae of magnetically connected pairs of spots are compared with the contrast of the He II 304 emission above the umbrae, C ₃₀₄. Spots satisfying certain conditions display a positive correlation between C _304?L and 〈α _L 〉 for the leading (L) spots, and between C _304?L /C _304?F and l _L /l _F , where l _L (l _F ) are the lengths of the field lines connecting leading (L) or following (F) spots from the corresponding spot umbrae to the apex of the field line.     

The impact of reflection effects on the parameters of the old pre-cataclysmic variables MS Peg and LM Com

We have determined the main parameters of the old precataclysmic variable stars MS Peg and LM Com. The radial velocities of the components, reflection effects in the spectra, and light curves of the systems are studied based on model stellar atmospheres subject to external irradiation. Forty-seven moderate-resolution spectra for MS Peg and 57 for LM Com obtained with the 6-m telescope of the Special Astrophysical Observatory are used to derive the refined orbital periods of 0.1736660 days and 0.2586873 days, respectively; the orbital eccentricities do not exceed e=0.04. The mass (M _w =0.49e_⊙) and radius (e _w =0.015R_⊙) of the MS Peg primary calculated using the gravitational redshift correspond to those for a cooling carbon white dwarf with a thin hydrogen envelope. The parameters of the red dwarf (M _r =0.19M_⊙, T_eff=3560 K, R _r =0.18R_⊙) are close to those derived from evolutionary tracks for main-sequence M stars with solar chemical composition. The radius (R _r =0.22R_⊙) and temperature (T_eff=3650 K) of the LM Com secondary exceed theoretical estimates for main-sequence stars with masses of M _r =0.17M_⊙. The luminosity excess of the red dwarf in LM Com can be explained by a prolonged (T>5×10⁶ yrs) relaxation of the M star to its normal state after the binary leaves the common-envelope stage. For both systems, theoretical U, B, V, and R light curves and spectra calculated using the adopted sets of parameters are generally consistent with the observations. This confirms the radiative origin of the hot spots, the unimportance of horizontal radiative transport, and the absence of large-scale velocity fields with high values (V_trans>50 km/s) at the surfaces of the secondaries. Most of the emission lines in the spectra of these objects are formed under conditions close to thermalization, enabling modeling of their pro files in an LTE approximation. A strong λ3905 Å emission line has been identified as the 3s²3p4s 1P⁰-3s²3p² 1S SiI λ3905.52 Å line formed in the atmosphere of the hot spot. The observed intensity can be explained by non-LTE “superionization” of SiI atoms by soft UV radiation from the white dwarf. We suggest a technique for identifying binaries whose cool components are subject to UV irradiation based on observations of λ3905 Å emission in their spectra.     

Physicochemical model for the crystallization of rocks of the calc-alkaline series

The Al-rich region of the CaO-MgO-Al₂O₃-SiO₂ system was experimentally studied at pressures of 1.0–2.8 GPa and temperatures of 1300–1535°C. The slopes of the lines of the monovariant reactions An + Sp = Cpx + Cor + (Ga) and L = Cpx + Ga + Cor + Sp and the compositions of the phases involved in these reactions are determined. The results are utilized in the topological analysis of the aluminous region of the CaO-MgO-Al₂O₃-SiO₂ system. On this basis, the principal structure of the phase diagram is analyzed, and a phase diagram is constructed for the junction region of the quaternary system and the CaO-Al₂O₃-SiO₂ ternary system. A continuous series of the monovariant eutectic: L = Cpx + Opx + Fo + An, L = Cpx + Opx + An + Sp, L = Cpx + (Ga) + An + Sp, L = Cpx + Cor + (Ga) + An, L = An + Ga + Cpx + Ky and L = Ga + Cpx + Ky + Qz is examined within the pressure range from atmospheric to 3.0 GPa and higher. Analogous “telescoped” eutectic series are of fundamental character for interpreting the evolution of magmatic melts. A physicochemical model is suggested for the evolution of magmatic melts that produce rocks of the calc-alkaline series, with this model underlain by the fact that a change in the composition of magmatic melt at a pressure decrease should correspond to the minimum melting temperatures, i.e., to melts in the fundamental series of eutectic reactions. The comparison of our physicochemical model and rocks of the calc-alkaline series shows that the compositions of rocks of the calc-alkaline series are close to the compositions determined for the eutectic equilibria, and the mineralogical composition of xenoliths and megacrysts in volcanic and dike varieties of the rocks are similar to the subsolidus phases of the established fundamental eutectic system.     

Towards a better understanding of the evolution of the flood risk in Mediterranean urban areas: the case of Barcelona

Dam failure constitutes a grave threat to human life. However, there is still a lack of systematic and comprehensive research on the loss of life (L) caused by dam break in China. From the perspective of protecting human life, a new calculation method for L occurred in dam break floods is put forward. Fourteen dam failure cases in China are selected as the basic data by three-dimensional stratified sampling, balancing spatial, vertical elevation and temporal representations, as well as considering various conditions of the dam collapse. The method includes three progressive steps: Firstly, some impact factors of loss of life (IFL) are selected by literature survey, i.e., severity of dam break flood (S _F), population at risk (P _R), understanding of dam break (U _B), warning time (T _W) and evacuation condition (E _C). And the other IFL of weather during dam break (W _B), dam break mode (M _B), water storage (S _W), building vulnerability (V _B), dam break time (T _B) and average distance from affected area to dam (D _D) are also taken into account to get a more comprehensive consideration. According to disaster system and disaster risk, these eleven IFL are divided into four categories. Through the improved entropy method, eight key IFL are further selected out of the eleven. Secondly, four L modules are built based on four categories, which are L-causing factor module (M ₁), L-prone environment module (M ₂), affected body module (M ₃) and rescue condition module (M ₄). Eventually, by using two methods of multivariate nonlinear regression and leave-one-out cross-validation in combination with coupled four modules, the calculation method for L is established. Compared with the results of Graham method and D&M method, the result of the proposed one is much closer to the actual value and performs better in fitting effect and regional applicability. In the application, L calculation and consequence assessment are carried out in the example of Hengjiang reservoir that has already broken down. At the same time, L calculation and risk prediction are used in the analysis of Yunshan reservoir, which is under planning. The proposed method can not only be applied to estimate L and its rate (f _L ) under various types of dam break conditions in China, but also provide a reliable consequence assessment and prediction approach to reduce the risk of L.     

Accuracy assessment of near-shore bathymetry information retrieved from Landsat-8 imagery

The improvement in the capabilities of Landsat-8 imagery to retrieve bathymetric information in shallow coastal waters was examined. Landsat-8 images have an additional band named coastal/aerosol, Band 1: 435–451 nm in comparison with former generation of Landsat imagery. The selected Landsat-8 operational land image (OLI) was of Chabahar Bay, located in the southern part of Iran (acquired on February 22, 2014 in calm weather and relatively low turbidity). Accurate and high resolution bathymetric data from the study area, produced by field surveys using a single beam echo-sounder, were selected for calibrating the models and validating the results. Three methods, including traditional linear and ratio transform techniques, as well as a novel proposed integrated method, were used to determine depth values. All possible combinations of the three bands [coastal/aerosol (CB), blue (B), and green (G)] have been considered (11 options) using the traditional linear and ratio transform techniques, together with five model options for the integrated method. The accuracy of each model was assessed by comparing the determined bathymetric information with field measured values. The standard error of the estimates, correlation coefficients (R ² ) for both calibration and validation points, and root mean square errors (RMSE) were calculated for all cases. When compared with the ratio transform method, the method employing linear transformation with a combination of CB, B, and G bands yielded more accurate results (standard error = 1.712 m, R ² _calibration = 0.594, R ² _validation = 0.551, and RMSE =1.80 m). Adding the CB band to the ratio transform methodology also dramatically increased the accuracy of the estimated depths, whereas this increment was not statistically significant when using the linear transform methodology. The integrated transform method in form of Depth = b ₀  + b ₁ X _CB  + b ₂ X _B  + b ₅ ln(R _CB )/ln(R _G ) + b ₆ ln(R _B )/ln(R _G ) yielded the highest accuracy (standard error = 1.634 m, R ² _calibration = 0.634, R ² _validation = 0.595, and RMSE = 1.71 m), where R _i (i = CB, B, or G) refers to atmospherically corrected reflectance values in the i ^th band [X _i  = ln(R _i -R _{deep water})].     

Characteristic scale of heterogeneity of seismically active fault and its manifestation in scaling of earthquake source spectra

Previously, similarity of source spectra of Kamchatka earthquakes with respect to the common corner frequency f_c1 and the expressed deviations from similarity for the second f_c2 and the third f_c3 corner frequencies were revealed. The value of f_c3 reflects the characteristic size L_is of fault surface; correspondingly, L_is ≈ v_rT_is, where v_r is the rupture speed and T_is ≈ 1/f_c3 is characteristic time. The estimates of f_c3 are used for normalizing f_c1 and f_c2. In this way one obtains dimensionless rupture temporal parametres τ₁ and τ₂ and can further study the dependence τ₂ (τ₁). The growth of a rupture is considered as a process of aggregation of elementary fault spots of the size L_is. The dimensionless width of the random front of aggregation is on the order of τ₂. The relationship τ₂ (τ₁) approximately follows power law with exponent β. The estimates of β derived from earthquake populations of Kamchatka, USA and Central Asia (β = 0.35–0.6) agree with values expected from the known Eden’s theory of random aggregation growth and from its generalizations.