Analysis of types and changes of village-level economy in rural Gongyi city,Henan Province since 1990

Based on the research on the rural living standard in China in terms of annual net income per capita, we define six types of village-level economy, i.e. ＂to be extremely poor＂, ＂to make a basic living＂, ＂to dress warmly and eat one＇s fill＂, ＂to try to enrich （to disengage poverty）＂, ＂to be well-off＂ and ＂to be affluent＂. The data of average annual net income of all the 292 villages between 1990 and 2004 in rural Gongyi City, Henan Province were collected, verified and classified. By using standard deviation, coefficient of variation and regression analysis, it is found that the Gongyi＇s rural economy has boosted up remarkably from the relative-poverty and absolute-poverty stages in 1990 to the well-off in 2004. However, the absolute differences between villages present a trend of enlargement, while the relative differences fluctuating. On the other hand, spatial analysis of village-level economy shows that most villages with relatively high economic development level were located along national expressway and most villages with absolute-poverty lay in remote mountainous areas in 1990. Since the 1990s, the rapid urbanization and industrialization have had strongly positive effects on rural economic growth. Initial economic foundation, natural resources and traditional techniques also contribute to village economy. From the perspective of geography, villages with location advantages, such as near urban center or industrial parks, have more chances for their economic development and the ＂core-periphery＂ economic structure has been presented in the process of rural development.     

A comparative study of sequential minimal optimization-based support vector machines,vote feature intervals,and logistic regression in landslide susceptibility assessment using GIS

Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas.     

Surface and groundwater quality characterization of Deoria District,Ganga Plain,India

A water quality investigation was carried out in the Deoria district, Ganga plain, to assess the suitability of surface and groundwaters for domestic, agricultural, and industrial purposes. As much as 50 representative samples from river and groundwater were collected from various stations to monitor the water chemistry of various ions, comprising Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃ ⁻, SO₄ ²⁻, NO₃ ⁻, Cl⁻, F⁻, and trace metals, such as Fe, Cu, Mn, Zn, Cd, and Pb. The results showed that electrical conductance (EC), total dissolved solids (TDS), HCO₃ ⁻, Mg²⁺, Na⁺, and total hardness (TH) are above the maximum desirable limit, and apart from Fe and Mn all other trace metals are within the maximum permissible limit for drinking water. The calculated values for sodium absorption ratio (SAR), salinity, residual sodium carbonate (RSC), and permeability index (PI) indicate well to permissible use of water for irrigation. High values of Na%, RSC, and Mg-hazard (MH) at some stations restrict its use for agricultural purpose. Anthropogenic activities affect the spatial variation of water quality. Economic and social developments of the study area is closely associated with the characteristics of the hydrological network.     

Assessment of rock slope stability by probabilistic-based Slope Stability Probability Classification method along highway cut slopes in Adilcevaz-Bitlis (Turkey)

Rock slope stability is of great concern along highway routes as stability problems on cut slopes may cause fatal events as well as loss of property. In rock slope engineering, stability evaluations are commonly performed by means of analytical or numerical analyses, principally considering the factor of safety concept. As a matter of fact, the probabilistic assessment of slope stability is progressively getting popularity due to difficulties in assigning the most appropriate values to design parameters in analytical or numerical methods. Additionally, the effect of heterogeneities in rock masses and discontinuities on the analysis results is minimized through the probabilistic concept. In this study, slope stability of high and steep sedimentary rock cut slopes along a state highway in Adilcevaz-Bitlis (Turkey) was evaluated on the basis of probabilistic approach using the Slope Stability Probability Classification (SSPC) system. The probabilistic assessment indicates major slope stability problems because of discontinuity controlled and discontinuity orientation independent mass movements. Almost all studied cut slopes suffer from orientation-independent stability problems with very low stability probabilities. Additionally, the probability of planar and toppling failures is significantly high with respect to the SSPC system. The stability problems along the investigated rock slopes were also verified by field reconnaissance. Remedial measures such as slope re-design and reinforcement at the studied locations should be taken to prevent hazardous events along the highway. On the other hand, the probabilistic approach may be a useful tool during rock slope engineering to overcome numerous uncertainties when probabilistic and analytic results are compared.     

Non-Linear Theory and Power-Law Models for Information Integration and Mineral Resources Quantitative Assessments

Singular physical or chemical processes may result in anomalous amounts of energy release or mass accumulation that, generally, are confined to narrow intervals in space or time. Singularity is a property of different types of non-linear natural processes including cloud formation, rainfall, hurricanes, flooding, landslides, earthquakes, wildfires, and mineralization. The end products of these non-linear processes can be modeled as fractals or multifractals. Hydrothermal processes in the Earth’s crust can result in ore deposits characterized by high concentrations of metals with fractal or multifractal properties. Here we show that the non-linear properties of the end products of singular mineralization processes can be applied for prediction of undiscovered mineral deposits and for quantitative mineral resource assessment, whether for mineral exploration or for regional, national and global planning for mineral resource utilization. In addition to the general theory and framework for the non-linear mineral resources assessment, this paper focuses on several power-law models proposed for characterizing non-linear properties of mineralization and for geoinformation extraction and integration. The theories, methods, and computer system discussed in this paper were validated using a case study dealing with hydrothermal Au mineral potential in southern Nova Scotia, Canada.     

Electrical and electromagnetic surveys to locate possible causes of water seepage to ground surface at a quarry open pit near Helwan city,Egypt

Water seepage to ground surface at a limestone quarry located at Wadi Garawy about 20 km south-east of Helwan city in Egypt posed a real threat to the mining activity at the quarry. The quarry area is known to be very dry for decades and away from water utilities and infrastructures that may cause water leaks to the quarry. Geophysical investigation including 1D Vertical Electrical Sounding (VES), 2D Electrical Resistivity Tomography (ERT) and 1D Transient Electromagnetic (TEM) surveys were conducted to characterize the rock sequence and locate what could be a possible source of water seepage to the quarry. The resistivity profiles generated from the VES and TEM surveys mapped the rock units in the area down to depths exceeded 100 m. The ERT profiles acquired from the quarrying zone close to the water seepage spot have imaged the top of groundwater level at few meters below the ground surface at the quarry open pit. The spot of groundwater seepage seemed to occur at an area of limestone dissolution that were filled by finer sediments. The finer sediments acted as a hydrological conduit that allowed an upward seepage of groundwater to ground surface under the capillary action effect.     

Uncertainty as the overlap of alternate conditional distributions

An important task in modern geostatistics is the assessment and quantification of resource and reserve uncertainty. This uncertainty is valuable support information for many management decisions. Uncertainty at specific locations and uncertainty in the global resource is of interest. There are many different methods to build models of uncertainty, including Kriging, Cokriging, and Inverse Distance. Each method leads to different results. A method is proposed to combine local uncertainties predicted by different models to obtain a combined measure of uncertainty that combines good features of each alternative. The new estimator is the overlap of alternate conditional distributions.     

Simplification and Validation of a Spectral-Tensor Model for Turbulence Including Atmospheric Stability

A spectral-tensor model of non-neutral, atmospheric-boundary-layer turbulence is evaluated using Eulerian statistics from single-point measurements of the wind speed and temperature at heights up to 100 m, assuming constant vertical gradients of mean wind speed and temperature. The model has been previously described in terms of the dissipation rate \(\epsilon \), the length scale of energy-containing eddies \(\mathcal {L}\), a turbulence anisotropy parameter \(\varGamma \), the Richardson number Ri, and the normalized rate of destruction of temperature variance \(\eta _\theta \equiv \epsilon _\theta /\epsilon \). Here, the latter two parameters are collapsed into a single atmospheric stability parameter z / L using Monin–Obukhov similarity theory, where z is the height above the Earth’s surface, and L is the Obukhov length corresponding to \(\{Ri,\eta _\theta \}\). Model outputs of the one-dimensional velocity spectra, as well as cospectra of the streamwise and/or vertical velocity components, and/or temperature, and cross-spectra for the spatial separation of all three velocity components and temperature, are compared with measurements. As a function of the four model parameters, spectra and cospectra are reproduced quite well, but horizontal temperature fluxes are slightly underestimated in stable conditions. In moderately unstable stratification, our model reproduces spectra only up to a scale \(\sim \) 1 km. The model also overestimates coherences for vertical separations, but is less severe in unstable than in stable cases.     

Temporal and Spatial Dynamics of Diel-Cycling Hypoxia in Estuarine Tributaries

The distribution and intensity of hypoxia (low dissolved oxygen) in estuaries is increasing worldwide due to cultural eutrophication. This study quantifies the strength of associations between the duration of diel-cycling severe hypoxia (≤2 mg O₂ l⁻¹) in bottom water (∼15 cm above bottom) of a shallow (<2 m) coastal lagoon estuary (Delaware, USA) and abiotic environmental variables (water temperature, insolation, tide, streamflow, and wind) and predicts the duration of severe hypoxia given different combinations of these variables. The intensity and spatial extent and dynamics of diel-cycling severe hypoxia events were defined. Vertical variability in dissolved oxygen (DO) concentration during the daytime was also determined. During the summers of 2001–2005, bottom DO data were collected for periods of weeks to months at multiple sites using automated sondes. Multiple linear regression (MLR) and regression tree analysis (RTA) were used to determine the relative importance of the environmental variables in predicting the number of hours of severe hypoxia per day. Key findings of the study were that severe hypoxia events of minutes to hours in duration occurred frequently in all four tributaries sampled, primarily between 0200 and 1000 hours. Severe hypoxia duration and diel-cycling amplitudes of DO concentration increased in the up-tributary direction. Hierarchically, the duration of severe hypoxia was influenced mostly by the mean daily water temperature, then by preceding days’ total insolation, percentage of morning hours (02:00 to 10:00 a.m.) ebb tide, and daily streamflow. Collectively, the variables examined by the MLR and the RTA approaches accounted for 62% and 65% of the variability in the duration of severe hypoxia, respectively. RTA demonstrated that daily mean water temperature above 26.3°C and previous day’s total insolation below 13.6 kW m⁻² were associated with the longest lasting severe hypoxic events (9.56 h). The environmental variables and combinations of conditions that modulate or augment diel-cycling hypoxia presented in this paper enhance understanding of this widespread and growing phenomenon and provide additional insight regarding the extent to which it can impact food webs in very shallow estuarine waters that often serve as nursery habitat.     

Relation between temperature changes of the mid-upper troposphere over Eurasian mid-high latitudes and solar irradiance in the twentieth century

The δ¹⁸O data obtained from an 18.7 m ice core drilled in Chongce Ice Cap at an elevation of 6,530 m a.s.l. in the West Kunlun Mountains on the northern Tibetan Plateau show a strong correlation with the summer temperature of the middle to upper troposphere over the mid-high latitudes of Eurasia. Based on this, the δ¹⁸O record can be used as a proxy of the June–September mean temperature of the mid-upper troposphere (MUT) from 1903 to 1992. The time span of the ice core record is much longer than the meteorological data available only after 1948. Using the empirical mode decomposition method (EMD), the δ¹⁸O record is decomposed into various frequency components and compared with the solar irradiance variations of the same period. The results show that (1) The June–September mean temperature of the MUT over Eurasian mid-high latitudes is completely decomposed into four IMF (intrinsic mode function) components and an increasing trend. (2) Solar irradiance is decomposed into the Schwabe cycle, the Hale cycle, the Gleissberg cycle, and an increasing trend. (3) The correlation coefficients between the June and September mean temperatures of the MUT over Eurasian mid-high latitudes and solar irradiance on the longer timescales (at least more than 11-year) show the significant correlations; their phase changes are basically identical in general, and (4) the 11-year Schwabe cycle exists in the June–September mean temperature of the MUT over Eurasian mid-high latitudes during most of the time from 1903 to 1992, and only in the two high-temperature phases (1929–1944 and from 1975 to the present) may global warming disturb this relation. A full understanding of this phenomenon would shed insight into the potential consequence of global warming on the MUT.