Computation of influence functions for automatic mining subsidence prediction

This paper presents a computer tool that automatically predicts mining subsidence using the generalized n-k-g influence function detailed in (González Nicieza et al. Int J Rock Mech Min Sci 42(3):372–387, 2005). This function depends on two physical concepts: the first is gravity, which characterizes the forces acting on the ground, and the second, the convergence of the roof and floor of the mine workings due to the stress state of the ground. The developed tool also allows other influence functions to be used to predict subsidence, namely the spatial influence function (Ramírez Oyanguren et al. 2000) and the normal-type classical (Knothe, Arch Gór Hut 1, 1952) and modified (González Nicieza et al. Bull Eng Geol Environ 66(3):319–329, 2007) time functions. Moreover, the inputting and periodic updating of data from subsidence monitoring surveys is controlled by one of the tool’s modules using a method that minimizes errors resulting from time discontinuities in landmarks measurements. In addition, when actual landmarks measurements exist, the developed tool allows calibration of the subsidence parameters, minimizing the errors between actual measurements and those obtained by prediction. The tool includes a viewer, developed using OpenGL, which enables the results of the calculations carried out to be viewed, allowing the point of view to be varied. It also includes the option of viewing and saving the results of the calculations carried out over the original topographic plane defined in the AutoCAD DXF data file format. The efficacy of the tool is demonstrated via its application to a real case of mining work carried out in a village in the Principality of Asturias, Spain.     

Self-Similar and Self-Affine Properties of Two-Dimensional Fracture Patterns in Rocks

In this paper, we investigate the fractal properties of binary maps of rock fractures at different scales and different geological types, as well as different families of fracture patterns obtained from a two-dimensional Laplacian growth model (LGM). From these analyses we figure out which families of the LGM patterns match the structural properties of the fracture binary maps. The LGM is defined in terms of a nonlinear map that depends on two parameters, λ and \mathfraka\mathfrak{a}, that respectively define the area and shape of the elements of the aggregate that conforms the patterns. The fractal dimension and roughness exponent of the LGM patterns are found to depend on \mathfraka\mathfrak{a}, with 0 < \mathfrak a < 10<\mathfrak {a}<1. From a detailed statistical analysis of these patterns we found that the fractal dimensions of capacity, correlation and information decrease monotonically as \mathfraka\mathfrak{a} increases. We also found that the values of these three fractal dimensions tend to collapse on top of each other as \mathfraka\lessapprox1\mathfrak{a}\lessapprox1. Remarkably, the fractal properties of rock fractures in the scales from millimeters up to a few meters appear to be well represented by the fractal structure of the LGM families of patterns with \mathfraka=0.15\mathfrak{a}=0.15 and 0.30, while the fractal properties of rock fractures in the scale of kilometers seems to be well represented by the LGM family with \mathfraka=0.90\mathfrak{a}=0.90. In addition, the three fractal dimension values of fracture binary maps in the scales from millimeters up to meters were found to be different between them. Nonetheless, for fractures in the scale of kilometers, the values of the three fractal dimensions are very close to each other as an indication of self-similar behavior. Analysis of the corrections to the scaling of the roughness exponent, ζ, suggests that they are negligible for the LGM family of fracture patterns with \mathfraka=0.9\mathfrak{a}=0.9. This finding points to a self-affine structure for this family of patterns. In fact, the calculated roughness exponent results are in the range of values characteristic of rock fractures.     

Soil-precipitation feedbacks during the South American Monsoon as simulated by a regional climate model

We summarize the recent progress in regional climate modeling in South America with the Rossby Centre regional atmospheric climate model (RCA3-E), with emphasis on soil moisture processes. A series of climatological integrations using a continental scale domain nested in reanalysis data were carried out for the initial and mature stages of the South American Monsoon System (SAMS) of 1993–92 and were analyzed on seasonal and monthly timescales. The role of including a spatially varying soil depth, which extends to 8 m in tropical forest, was evaluated against the standard constant soil depth of the model of about 2 m, through two five member ensemble simulations. The influence of the soil depth was relatively weak, with both beneficial and detrimental effects on the simulation of the seasonal mean rainfall. Secondly, two ensembles that differ in their initial state of soil moisture were prepared to study the influence of anomalously dry and wet soil moisture initial conditions on the intraseasonal development of the SAMS. In these simulations the austral winter soil moisture initial condition has a strong influence on wet season rainfall over feed back upon the monsoon, not only over the Amazon region but in subtropical South America as well. Finally, we calculated the soil moisture–precipitation coupling strength through comparing a ten member ensemble forced by the same space–time series of soil moisture fields with an ensemble with interactive soil moisture. Coupling strength is defined as the degree to which the prescribed boundary conditions affect some atmospheric quantity in a climate model, in this context a quantification of the fraction of atmospheric variability that can be ascribed to soil moisture anomalies. La Plata Basin appears as a region where the precipitation is partly controlled by soil moisture, especially in November and January. The continental convective monsoon regions and subtropical South America appears as a region with relatively high coupling strength during the mature phase of monsoon development.     

Relationship between olive flowering and latitude in two Mediterranean countries (Italy and Tunisia)

In phenological studies, the plant developments are analysed considering their relationships with seasonal meteorological conditions; moreover, the influences of geographical features on biological responses have to be also considered. Different studies analysed the influence of latitude on phenological phases to investigate the possible different magnitude of biological response. In our experience, this type of geographic evaluation was conducted considering one of the more important plant species of Mediterranean shrub, the olive (Olea europaea L.) in fifteen olive monitoring stations, four located in Tunisia and eleven in Italy, from the southern Zarzis area at 33° to the northern Perugia area at 43° of latitude. The olive flowering phenomenon was studied, utilising an aerobiological monitoring method through appropriate pollen traps located inside olive groves from 1999 to 2008. The olive monitored pollen grains were recognised and evaluated to obtain daily pollen concentrations to define the flowering dates in the different study areas. The biometeorological statistical analysis showed the 7°C threshold temperature and the single triangle method for growing degree days (GDD) yearly computing as the better ones in comparison to others. Moreover, the regression analysis between the dates of full flowering and the GDD amounts at the different monitoring latitudes permitted us to evidence the biological response of olive species in geographic regions with different climate patterns. The specific biological response at different latitude was investigated, the slope results, as flowering days per heat amounts, evidenced that olive species behaviours are very constant in consequence to similar meteorological conditions independently to latitude variations. Averagely, the relationships between plant’s phenology, temperature trends and geographical features are very close, even if the yearly mesoscale meteorological variations force to consider, year by year, phenological advances or delays as local events.     

Determination of the optimal size of area to be sampled by use of the moss biomonitoring technique

The aim of the present study was to determine the optimal size of the sampling area that should be used in the moss biomonitoring technique, in relation to the spatial variation in the concentrations of contaminants determined in samples collected within short distances (<30 m). For this, the spatial structure in the concentrations of various metals and metalloids was explored by use of semivariograms calculated by use of a robust estimator of the variance. In each of the 3 sampling sites considered in the study (one sampled on two occasions), 50 samples of the moss Pseudoscleropodium purum were collected and the tissue concentrations of As, Cd, Cu, Hg, K, Ni, Pb, Se and Zn were determined. The results obtained show that in most cases (25 out of 32), there was no spatial structure in the concentrations of the elements and that the semivariograms were subject to the nugget effect. For those elements for which spatial independence or a linear spatial structure was observed, the size of the sampling area did not affect the results, and the dimensions were irrelevant within the range studied. The existence of spatial structure, which can be fitted to a spherical model, enabled a range of autocorrelation to be defined, which corresponded to an area of diameter >16 m. The proposed method must be applied to other species and in other regions, in order to standardize the size of the sampling sites in the moss biomonitoring technique.     

Rossi XTE monitoring of 4U 1636–53 – I. Long-term evolution and kHz quasi-periodic oscillations

We have monitored the atoll-type neutron star low-mass X-ray binary 4U 1636−53 with the Rossi X-ray Timing Explorer ( RXTE ) for more than 1.5 yr. Our campaign consisted of short (∼2 ks) pointings separated by 2 d, regularly monitoring the spectral and timing properties of the source. During the campaign we observed a clear long-term oscillation with a period of ∼30–40 d, already seen in the light curves from the RXTE All-Sky Monitor, which corresponded to regular transitions between the hard (island) and soft (banana) states. We detected kilohertz (kHz) quasi-periodic oscillations (QPOs) in about a third of the observations, most of which were in the soft (banana) state. The distribution of the frequencies of the peak identified as the lower kHz QPO is found to be different from that previously observed in an independent data set. This suggests that the kHz QPOs in the system shows no intrinsically preferred frequency.     

The role of small‐scale fold and fault development in seismogenic zones: example of the western Huércal‐Overa Basin (eastern Betic Cordillera,Spain)

The NW–SE shortening between the African and the Eurasian plates is accommodated in the eastern Betic Cordillera along a broad area that includes large N‐vergent folds and kilometric NE–SW sinistral faults with related seismicity. We have selected the best exposed small‐scale tectonic structures located in the western Huércal‐Overa Basin (Betic Cordillera) to discuss the seismotectonic implications of such structures usually developed in seismogenic zones. Subvertical ESE–WNW pure dextral faults and E–W to ENE–ESW dextral‐reverse faults and folds deform the Quaternary sediments. The La Molata structure is the most impressive example, including dextral ESE–WNW Neogene faults, active southward‐dipping reverse faults and associated ENE–WSW folds. A molar M1 assigned to Mimomys savini allows for precise dating of the folded sediments (0.95–0.83 Ma). Strain rates calculated across this structure give ～0.006 mm a^?1 horizontal shortening from the Middle Pleistocene up until now. The widespread active deformations on small‐scale structures contribute to elastic energy dissipation around the large seismogenic zones of the eastern Betics, decreasing the seismic hazard of major fault zones. Copyright © 2009 John Wiley & Sons, Ltd.     

A modified multiple tension upward infiltration method to estimate the soil hydraulic properties

Determination of saturated hydraulic conductivity, K_s, and the shape parameters α and n of the water retention curve, θ(h), is of paramount importance to characterize the water flow in the vadose zone. This work presents a modified upward infiltration method to estimate K_s, α and n from numerical inverse analysis of the measured cumulative upward infiltration (CUI) at multiple constant tension lower boundary conditions. Using the HYDRUS‐2D software, a theoretical analysis on a synthetic loam soil under different soil tensions (0, 0–10, 0–50 and 0–100 cm), with and without an overpressure step of 10 cm high from the top boundary condition at the end of the upward infiltration process, was performed to check the uniqueness and the accuracy of the solutions. Using a tension sorptivimeter device, the method was validated in a laboratory experiment on five different soils: a coarse and a fine sand, and a 1‐mm sieved loam, clay loam and silt‐gypseous soils. The estimated α and n parameters were compared to the corresponding values measured with the TDR‐pressure cell method. The theoretical analysis demonstrates that K_s and θ(h) can be simultaneously estimated from measured upward cumulative infiltration when high (>50 cm) soil tensions are initially applied at the lower boundary. Alternatively, satisfactory results can be also obtained when medium tensions (<50 cm) and the K_s calculated from the overpressure step at the end of the experiment are considered. A consistent relationship was found between the α (R² = 0.86, p < 0.02) and n (R² = 0.97, p < 0.001) values measured with the TDR‐pressure cell and the corresponding values estimated with the tension sorptivimeter. The error between the α (in logarithm scale) and n values estimated with the inverse analysis and the corresponding values measured with pressure chamber were 3.1 and 6.1%, respectively. Copyright © 2016 John Wiley & Sons, Ltd.