Influence of spatial variability of permeability property on steady state seepage flow and slope stability analysis

In recent years, spatial variability modeling of soil parameters using random field theory has gained distinct importance in geotechnical analysis. In the present study, commercially available finite difference numerical code FLAC 5.0 is used for modeling the permeability parameter as spatially correlated log-normally distributed random variable and its influence on the steady state seepage flow and on the slope stability analysis are studied. Considering the case of a 5.0 m high cohesive–frictional soil slope of 30°, a range of coefficients of variation (CoV%) from 60 to 90% in the permeability values, and taking different values of correlation distance in the range of 0.5–15 m, parametric studies, using Monte Carlo simulations, are performed to study the following three aspects, i.e., (i) effect of stochastic soil permeability on the statistics of seepage flow in comparison to the analytic (Dupuit′s) solution available for the uniformly constant permeability property; (ii) strain and deformation pattern, and (iii) stability of the given slope assessed in terms of factor of safety (FS). The results obtained in this study are useful to understand the role of permeability variations in slope stability analysis under different slope conditions and material properties.     

Petrology and geochemistry of greywackes from Goa-Dharwar sector,western Dharwar Craton: Implications for volcanoclastic origin

Late Archaean Supracrustals of the Goa-Dharwar sector (GDS) are composed of a thick sequence of greywacke sequence with narrow intercalations of quartzite, BIF and carbonates. Mafic volcanics occupy the base of the sequence. The greywackes are predominantly tuffacious containing chlorite-sericite and hornblende. Arkosic variations containing biotite dominate the western part of the sector. Fine-grained variations occur as isolated narrow lenses within other types of greywackes. The conglomeratic greywackes are localized along the western and the eastern margins of the sector. All of the greywackes are all typically immature containing coarser clasts of mostly plagioclase (18–23%) and quartz (32–34%). Lithic fragments of felsic volcanic rocks are common. The matrix is dominated by mafic material. Biotite and amphibole are related to metamorphic recrystallization. Chlorite, sericite, epidote, carbonate and chert are products of the interplay of diagenesis and low-grade metamorphism. Fe-Ti oxide, sphene, apatite and zircon are usual accessories. But for slight enrichment in K₂O, the major element chemistry of the GDS greywackes is similar to the chemistry of Late Archaean greywackes. They also compare in respect of V, Co, Hf contents, K₂O/Na₂O, SiO₂/Al₂O₃, Na₂O/Al₂O₃, Ba/Rb, Th/U, La/Th, Sm/Nd ratios, steep REE patterns with distinct LREE enrichment and HREE depletion. The GDS greywackes however are distinctly enriched in Rb, Ba, Sr, Th, U, Cu, Zr, Ce/Ce* and depleted in Cr, Ni, and Zn. The conglomeritic and biotite bearing verities contain considerable proportions of clasts derived from the basement tonalitic/granitic terrain. The common tuffacious greywackes containing hornblende and biotite-sericite however include only volcanic clasts and bear evidence of derivation from submarine weathering of predominantly felsic volcanics erupted on a large scale to form a magmatic arc in the later stages of geosynclinal deposition. Geochemical data suggest that the GDS greywackes were laid down in progressively changing basin geometry from a passive to active continental margin and island arc setting.     

Prediction of vegetation anomalies over an inland river basin in north‐western China

Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.     

Time-lag effects of vegetation responses to soil moisture evolution: a case study in the Xijiang basin in South China

The time-lag effects of droughts on vegetation responses vary significantly across a large-scale river basin. The spatio-temporal response characteristics obtained are important for decision making processes on the allocation and transportation of regional water resources in mitigating drought impacts. Here we consider the Xijiang (West River) basin in South China as a case study, which has experienced severe drought events since the beginning of the 21st century. A threshold level approach is employed to identify the major drought events over the basin in the first decade of this century. The vegetation responses to land soil water evolution are examined, particularly for the severe drought events occurred. The time-lag effects of the vegetation responses within the basin range within 0–96 days. The lower reaches of the headwater sub-basins in the west part of the Xijiang basin are identified as the regions with short time-lag effects. The enhanced vegetation index (EVI) shows consistent responses to the soil water evolution in conjunction with the climate aridity in this area, which is the drought-vulnerable area in the Xijiang basin.     

Earthquake hazard assessment through geospatial model and development of EaHaAsTo tool for visualization: an integrated geological and geoinformatics approach

An earthquake is a natural phenomenon which is very frequent in Himalayan region in India. In southern peninsula India, the spatial occurrence of earthquake is irregular, whereas the northeastern, the north and the northwestern Himalayan parts of India are subjected to regular occurrences of earthquakes as they mark the boundary of the Eurasian and the Indian Plate. Hence, it is important to study and develop spatial model and information tool to understand the seismic phenomenon. The geoinformatic technique plays a significant role in the analysis of geodatabase to study the natural disaster and hazard assessment. The main aim of the present study is to develop geospatial model based on earthquake hazard assessment tool (EaHaAsTo) through integrated geological and geoinformatic techniques to better understand the earthquake occurrences zones. The spatial and non-spatial data were collected and integrated in a GIS to prepare geospatial databases. The thematic and quantitative databases were generated, and analysis was carried out to understand the seismic characteristics of the study area. The geospatial model was developed by integrating thematic databases and geospatial analyzed using weighted linear combination method. Finally, the GIS based on customized EaHaAsTo was developed to visualize the output of the model in qualitative and quantitative forms.     

A physical interpretation of the deterministic fractal–multifractal method as a realization of a generalized multiplicative cascade

In this study, we attempt to offer a solid physical basis for the deterministic fractal–multifractal (FM) approach in geophysics (Puente, Phys Let A 161:441–447, 1992; J Hydrol 187:65–80, 1996). We show how the geometric construction of derived measures, as Platonic projections of fractal interpolating functions transforming multinomial multifractal measures, naturally defines a non-trivial cascade process that may be interpreted as a particular realization of a random multiplicative cascade. In such a light, we argue that the FM approach is as “physical” as any other phenomenological approach based on Richardson’s eddies splitting, which indeed lead to well-accepted models of the intermittencies of nature, as it happens, for instance, when rainfall is interpreted as a quasi-passive tracer in a turbulent flow. Although neither a fractal interpolating function nor the specific multipliers of a random multiplicative cascade can be measured physically, we show how a fractal transformation “cuts through” plausible scenarios to produce a suitable realization that reflects specific arrangements of energies (masses) as seen in nature. This explains why the FM approach properly captures the spectrum of singularities and other statistical features of given data sets. As the FM approach faithfully encodes data sets with compression ratios typically exceeding 100:1, such a property further enhances its “physical simplicity.” We also provide a connection between the FM approach and advection–diffusion processes.     

Networks: a generic theory for hydrology?

Connections are ubiquitous. The hydrologic cycle is perhaps the best example: every component of this cycle is connected to every other component, but some connections are stronger than the others. Unraveling the nature and extent of connections in hydrologic systems, as well as their interactions with others, has always been a fundamental challenge in hydrology. Despite the progress in this direction, a strong scientific theory that is suitable for studying all types of connections in hydrology continues to be elusive. In this article, I argue that the theory of networks provides a generic theory for studying all types of connections in hydrology. After presenting a general discussion of complex systems as networks, I offer a brief account of the history of development of network theory and some basic concepts and measures of complex networks, and explain the relevance of complex network theory for hydrologic systems, with three specific examples.