Slope Curvature Research Articles

On generation and evolution of seaward propagating internal solitary waves in the northwestern South China Sea

In this paper, the generation and evolution of seaward propagating internal solitary waves (ISWs) detected by satellite image in the northwestern South China Sea (SCS) are investigated by a fully nonlinear, non-hydrostatic, three-dimensional Massachusetts Institute of Technology general circulation model (MITgcm). The three-dimensional (3D) modeled ISWs agree favorably with those by satellite image, indicating that the observed seaward propagating ISWs may be generated by the interaction of barotropic tidal flow with the arc-like continental slope south of Hainan Island. Though the tidal current is basically in east–west direction, different types of internal waves are generated by tidal currents flowing over the slopes with different shaped shorelines. Over the slope where the shoreline is straight, only weak internal tides are generated; over the slope where the shoreline is seaward concave, large-amplitude internal bores are generated, and since the concave isobaths of the arc-like continental slope tend to focus the baroclinic tidal energy which is conveyed to the internal bores, the internal bores can efficiently disintegrate into a train of rank-ordered ISWs during their propagation away from the slope; while over the slope where the shoreline is seaward convex, no distinct internal tides are generated. It is also implied that the internal waves over the slope are generated due to mixed lee wave mechanism. Furthermore, the effects of 3D model, continental slope curvature, stratification, rotation and tidal forcing on the generation of ISWs are discussed, respectively. It is shown that, the amplitude and phase speed of ISWs derived from a two-dimensional (2D) model are smaller than those from the 3D one, and the 3D model has an advantage over 2D one in simulating the ISWs generated by the interaction between tidal currents and 3D curved continental slope; the reduced continental slope curvature hinders the extension of ISW crestline; both weaker stratification and rotation suppress the generation of ISWs; and the width of ISW crestline generated by K1 tidal harmonic is longer than that by M2 tidal harmonic.

Asymptotic curves on B-surfaces according to type-2 bishop frame in the sol space

In this paper, we study B— surfaces of biharmonic constant Π2— slope curves according to type-2 Bishop in the . We characterize asymptotic curves on B— surfaces of biharmonic constant Π2— slope curves in terms of their Bishop curvatures. Finally, we find out their explicit parametric equations in the .

High resolution characterization of the soil organic carbon depth profile in a soil landscape affected by erosion

The identification of soil management strategies as well as the evaluation of their effectiveness requires detailed information on the spatial and temporal patterns of soil organic carbon storage. High-resolution SOC profile data are generally not available and traditional methods for collecting these are time consuming and costly. Recent studies use geo-statistical approaches to assess the three-dimensional patterns of SOC storage. However, there is still a large discrepancy between the continuous and high resolution mapping of the horizontal SOC variability on the one hand, and the coarse and discontinuous mapping of the vertical SOC profile on the other. In this study, we combine spectroscopic techniques with spatial modeling in a small, cultivated catchment in Germany and we evaluate the contribution of soil redistribution processes and topographical parameters to the observed spatial and vertical patterns. Using high-resolution data from soil cores, we evaluated the robustness of a third order polynomial function to model the vertical SOC profile. Using a crossvalidation, our results show that this approach results in a robust model (RSME=0.24%) and performs better than the widely used exponential depth model (RMSE=0.39%). In a next step, we evaluated the relationship between the parameters of the SOC depth model and co-variables including soil redistribution (inferred from 137Cs data) and topographical indices using a multiple linear regression model. The performance was calculated by cross-validation and we found a low robustness of the models because of the low number of profiles (i.e. n=19). A statistical evaluation of the co-variables highlighted two key factors influencing the SOC vertical distribution. Soil redistribution processes mainly influenced the surface SOC content (first centimeters) whereas the shape of the depth distribution was controlled by slope curvature alone. The mapping of polynomial parameters was validated using an external SOC profile dataset and showed a poor prediction of the surface content but a good prediction of the depth distribution once the surface SOC content is known (RMSE=0.15–0.25%C). This suggests that estimating the vertical SOC profile from topsoil data by applying remote sensing data, in combination with our SOC profile model, is promising and can will result in an accurate mapping of 3D SOC patterns at a very high resolution.

Influence of weak layer heterogeneity and slab properties on slab tensile failure propensity and avalanche release area

Abstract. Dry-snow slab avalanches are generally caused by a sequence of fracture processes, including failure initiation in a weak snow layer underlying a cohesive slab followed by crack propagation within the weak layer (WL) and tensile fracture through the slab. During past decades, theoretical and experimental work has gradually increased our knowledge of the fracture process in snow. However, our limited understanding of crack propagation and fracture arrest propensity prevents the evaluation of avalanche release sizes and thus impedes hazard assessment. To address this issue, slab tensile failure propensity is examined using a mechanically based statistical model of the slab–WL system based on the finite element method. This model accounts for WL heterogeneity, stress redistribution by slab elasticity and possible tensile failure of the slab. Two types of avalanche release are distinguished in the simulations: (1) full-slope release if the heterogeneity is not sufficient to stop crack propagation and trigger a tensile failure within the slab; (2) partial-slope release if fracture arrest and slab tensile failure occur due to the WL heterogeneity. The probability of these two release types is presented as a function of the characteristics of WL heterogeneity and the slab. One of the main outcomes is that, for realistic values of the parameters, the tensile failure propensity is mainly influenced by slab properties. Hard and thick snow slabs are more prone to wide-scale crack propagation and thus lead to larger avalanches (full-slope release). In this case, the avalanche size is mainly influenced by topographical and morphological features such as rocks, trees, slope curvature and the spatial variability of the snow depth as often claimed in the literature.

Analysis of the spatial differentiation of the soil cover in the south of the Far East of Russia by the example of the Komarovka River basin

A digital elevation model and a soil map of the basin of the Komarovka River (the Far East region of Russia) were developed using the methods of digital mapping on a scale of 1: 50000. The legend to the soil map was based on the regional soil classification system developed by G.I. Ivanov, in which the character of the water exchange of the soils serves as one of the major differentiating criteria. The analysis of the territory was consecutively performed for its mountain and plain parts and for floodplain landscapes. The morphometric parameters of the relief (height, slope steepness, and slope curvature) were analyzed with the help of overlay functions of geographic information systems for the areas of the main soils of the studied territory and compared with the major soil cover characteristics in order to find stable combinations of the factors explaining the spatial distribution of the soil areas. As a result, we determined the major elements of the relief controlling the spatial differentiation of the soil cover.

Term structure of interest rates estimation using rational Chebyshev functions

We present a novel method for modeling yield curves using rational Chebyshev functions. Our motivation is based on both their suitable mathematical properties as well as their successful application record, mainly in nonfinancial areas. We provide an interpretation of the proposed model in terms of a level–slope–curvature perspective, and we indicate methods for identifying the model’s parameters based on this interpretation. We present the results of in-sample and out-of-sample tests of the proposed model in comparison with popular parsimonious models. The tests indicate that the proposed model is competitive in terms of its performance as well as its properties.

Landslide susceptibility mapping along Kolli hills Ghat road section (India) using frequency ratio, relative effect and fuzzy logic models

This article emphasizes landslide susceptibility mapping along Ghat road of Kolli hills, Tamil Nadu, India, using frequency ratio, relative effect and fuzzy gamma operator models with the help of remote sensing data and GIS technique. The purpose of the study is to generate, compare and validate landslide susceptibility zones. Landslide inventory was done with data collected from the State Highways department. There are nine landslide-influencing parameters such as slope gradient, slope aspect, slope curvature, relief, lithology, land use and land cover, proximity to road, proximity to drainage, and proximity to lineament, analyzed with help of topo map, existing geology map and satellite data to produce landslide susceptibility maps. Landslide susceptibility maps were generated by calculating relationship between the landslide-influencing factors with past landslide locations using frequency ratio, relative effect and fuzzy gamma operator models. These landslide susceptibility maps were verified and compared using the existing landslide inventory data. The prediction accuracy of frequency ratio model was 87.93 %, for fuzzy gamma operator model was 87.33 %, and for relative effect model it was 85.26 %. Out of which, the frequency ratio model provide maximum prediction accuracy on landslide susceptibility.

Interactive statistical analysis of predisposing factors for earthquake-triggered landslides: a case study of the 2013 Lushan, China Ms7.0 earthquake

Remote sensing data and field investigations indicate that at least 3,878 landslides were induced by the 2013 Lushan, China Ms7.0 earthquake. This study selects a square area of 100 km × 100 km around the epicenter to make an interactive statistical analysis to these landslides. Percentages of landslide number and landslide concentration are calculated based on a GIS platform, so as to find out the relationship between the distribution of landslides and six predisposing factors including elevation, slope angle, slope aspect, slope curvature, geologic ages of underlying bedrocks, and peak ground acceleration (PGA). In general, the correlations from interactive statistical analysis show a good consistency with the results from the bivariate statistics. However, several abnormal values are observed. For example, the relationship between slope aspect and co-seismic landslides is more easily influenced in the areas of slope angles larger than 40o or with the PGA value range of 0.36–0.44 g. The correlation between slope angle and co-seismic landslides is stronger in areas with underlying bedrocks of the Triassic age. Interactive statistical analysis of co-seismic landslides controlled by the factors in this study can effectively compensate the results from bivariate statistical analysis, which allows us to better understand spatial distribution patterns of earthquake-triggered landslides.

Biharmonic constant Π₁-slope curves according to type-2 bishop frame in Heisenberg group Heis³

In this paper, we introduce constant Π₁- slope curves according to type-2 Bishop frame in the Heisenberg group Heis³. We characterize the biharmonic constant Π₁- slope curves in terms of their Bishop curvatures. Finally, we find out their explicit parametric equations in the Heisenberg group Heis³. Additionally, we illustrate our main theorem.

Landslide susceptibility mapping along Bhalubang — Shiwapur area of mid-Western Nepal using frequency ratio and conditional probability models

Roads constructed in fragile Siwaliks are prone to large number of instabilities. Bhalubang-Shiwapur section of Mahendra Highway lying in Western Nepal is one of them. To understand the landslide causative factor and to predict future occurrence of the landslides, landslide susceptibility mapping (LSM) of this region was carried out using frequency ratio (FR) and weights-of-evidence (W of E) models. These models are easy to apply and give good results. For this, landslide inventory map of the area was prepared based on the aerial photo interpretation, from previously published/unpublished reposts, and detailed field survey using GPS. About 332 landslides were identified and mapped, among which 226 (70%) were randomly selected for model training and the remaining 106 (30%) were used for validation purpose. A spatial database was constructed from topographic, geological, and land cover maps. The reclassified maps based on the weight values of frequency ratio and weights-of-evidence were applied to get final susceptibility maps. The resultant landslide susceptibility maps were verified and compared with the training data, as well as with the validation data. From the analysis, it is seen that both the models were equally capable of predicting landslide susceptibility of the region (W of E model (success rate = 83.39%, prediction rate = 79.59%); FR model (success rate = 83.31%, prediction rate = 78.58%)). In addition, it was observed that the distance from highway and lithology, followed by distance from drainage, slope curvature, and slope gradient played major role in the formation of landsides. The landslide susceptibility maps thus produced can serve as basic tools for planners and engineers to carry out further development works in this landslide prone area.

Day-to-day dynamics of associations between sleep, napping, fatigue, and the cortisol diurnal rhythm in women diagnosed as having breast cancer.

To examine whether day-to-day variations in sleep behaviors, ongoing sleep disturbance, and fatigue predict the cortisol diurnal rhythm in women recently diagnosed as having early-stage breast cancer. Women (N = 130, mean [standard deviation] age = 55.6 [9.4] years) collected saliva 5×/day/2 days for cortisol. Diaries were used to assess prior-day nap duration, nocturnal awakenings, sleep latency, and morning restfulness. Ongoing fatigue and sleep disturbance were measured using the Multidimensional Fatigue Symptom Inventory and the Pittsburg Sleep Quality Inventory. Data were analyzed using a multilevel growth curve modeling. Greater ongoing fatigue (b = 0.035, p = .032), or sleep disturbance (b = 0.026, p = .006) predicted a slower cortisol decline. Greater ongoing fatigue also predicted higher awakening cortisol (b = 0.154, p = .030) and lower cortisol awakening response (CAR; b = -0.146, p = .005). Longer prior-day naps predicted higher CAR (b = 0.042, p = .050) and a steeper cortisol decline (b = -0.035, p = .003). Longer sleep latency predicted both a greater cortisol linear decline (b = -0.013, p < .001) and a greater quadratic slope curvature (b = 0.0007, p < .001). Feeling less rested in the morning predicted lower awakening cortisol (b = -0.187, p = .004), higher CAR (b = 0.124, p = .016), and a slower cortisol decline (b = 0.023, p = .042). Both daily variations in sleep behaviors and ongoing sleep disturbance and fatigue are associated with a disrupted cortisol rhythm. In contrast, prior-day napping is associated with a more robust cortisol rhythm. These findings are particularly relevant to women with breast cancer who often experience sleep disturbance and fatigue. Additional research is needed to determine causal pathways between sleep disturbance and dysregulation of the hypothalamic-pituitary-adrenal axis in patients with breast cancer.

An automated approach to vertical road characterisation using mobile LiDAR systems: Longitudinal profiles and cross-sections

The characterisation the vertical profiles and cross-sections of roads is important for the verification of proper construction and road safety assessment. The goal of this paper is the extraction of geometric parameters through the automatic processing of mobile LiDAR system (MLS) point clouds. Massive and complex datasets provided by the MLS are processed using a hierarchical strategy that includes segmentation, principal component analysis (PCA)-based orthogonal regression, filtering and parameter extraction procedures. Best-fit geometric parameters act as a vertical road model for both linear parameters (slope and vertical curves) and cross-sections (superelevations). The proposed automatic processing approach gives satisfactory results for the analysed scenario.

Earthquake-induced rockfall hazard zoning

A methodology for quantitative probabilistic hazard zonation for earthquake-induced rockfalls is presented and demonstrated in the area of Friuli (Eastern Italian Alps) affected by the 1976 Mw 6.5 earthquake. Four rockfall datasets have been prepared both from historical data analysis and field surveys. The methodology relies on a three-dimensional hazard vector, whose components include the rockfall kinetic energy, the fly height, and the annual frequency. The values of the first two components are calculated for each location along the slope using the 3D rockfall runout simulator Hy-STONE. The rockfall annual frequency is assessed by multiplying the annual onset frequency by the simulated transit frequency. The annual onset frequency is calculated through a procedure that combines the extent of unstable areas, calculated for 10 different seismic-hazard scenarios with different annual frequencies of occurrence, and the magnitude relative–frequency relationship of blocks as derived from the collected field data. For each annual frequency of occurrence, the unstable area is calculated as a function of morphometric and earthquake characteristics. A series of discriminant-analysis models, using the rockfall datasets and DEMs of different resolution (1 and 10m), identified the controlling variables and verified the model robustness. In contrast with previously published relationships, we show that the slope curvature plays a relevant role in the computation of the unstable area.

Landslides triggered by the 12 January 2010 Port-au-Prince, Haiti, &amp;lt;i&amp;gt;M&amp;lt;/i&amp;gt;&amp;lt;sub&amp;gt;w&amp;lt;/sub&amp;gt; = 7.0 earthquake: visual interpretation, inventory compiling, and spatial distribution statistical analysis

Abstract. The 12 January 2010 Port-au-Prince, Haiti, earthquake (Mw= 7.0) triggered tens of thousands of landslides. The purpose of this study is to investigate the correlations of the occurrence of landslides and the thicknesses of their erosion with topographic, geologic, and seismic parameters. A total of 30 828 landslides triggered by the earthquake covered a total area of 15.736 km2, distributed in an area more than 3000 km2, and the volume of landslide accumulation materials is estimated to be about 29 700 000 m3. These landslides are of various types, mostly belonging to shallow disrupted landslides and rock falls, but also include coherent deep-seated landslides and rock slides. These landslides were delineated using pre- and post-earthquake high-resolution satellite images. Spatial distribution maps and contour maps of landslide number density, landslide area percentage, and landslide erosion thickness were constructed in order to analyze the spatial distribution patterns of co-seismic landslides. Statistics of size distribution and morphometric parameters of co-seismic landslides were carried out and were compared with other earthquake events in the world. Four proxies of co-seismic landslide abundance, including landslides centroid number density (LCND), landslide top number density (LTND), landslide area percentage (LAP), and landslide erosion thickness (LET) were used to correlate co-seismic landslides with various environmental parameters. These parameters include elevation, slope angle, slope aspect, slope curvature, topographic position, distance from drainages, lithology, distance from the epicenter, distance from the Enriquillo–Plantain Garden fault, distance along the fault, and peak ground acceleration (PGA). A comparison of these impact parameters on co-seismic landslides shows that slope angle is the strongest impact parameter on co-seismic landslide occurrence. Our co-seismic landslide inventory is much more detailed than other inventories in several previous publications. Therefore, we carried out comparisons of inventories of landslides triggered by the Haiti earthquake with other published results and proposed possible reasons for any differences. We suggest that the empirical functions between earthquake magnitude and co-seismic landslides need to be updated on the basis of the abundant and more complete co-seismic landslide inventories recently available.

Predicting Functional Role and Occurrence of Whitebark Pine (Pinus albicaulis) at Alpine Treelines: Model Accuracy and Variable Importance

At some alpine treelines in the Rocky Mountains, whitebark pine (Pinus albicaulis)—a keystone species—plays a central role in tree island development through facilitation. Whitebark pine occurs both as a solitary tree and also as a component of tree islands, although relative importance of these two patterns varies geographically. We examine the utility of four predictive models to understand how the functional role of a keystone species varies spatially with biophysical conditions. We use a novel data set to predict whitebark pine's functional role, characterized by spatial association and relative position within a tree island at three North American Rocky Mountain treelines. For the study areas combined, and at a study area level, we compared prediction accuracy and variable importance among these modeling approaches: general linear models, classification and regression trees, random forests, and support vector machines. Results revealed that the keystone role of whitebark pine varied spatially. For the combined model, growing season temperature and slope curvature were the most important predictive variables for association and relative position, as revealed by overall agreement among the four models. Prediction accuracy and variable importance varied at the study area level, though, indicating that different conclusions could be drawn from each model, if examined independently. We advocate comparing results from different modeling approaches for complex, field-derived data sets because it might enable a better understanding of model and variable selection and appropriateness of input data resolution. Furthermore, comparative modeling enables assessment of the relative predictive and interpretive capacities of each modeling approach.

On the quantitative relationships between environmental parameters and heavy metals pollution in Mediterranean soils using GIS regression-trees: The case study of Lebanon

Soil heavy metal pollution has been and continues to be a worldwide phenomenon that has attracted a great deal of attention from governments and regulatory bodies. In this context, the present study used Geographic Information Systems (GIS) and regression-tree modeling (196 trees) to precisely quantify the relationships between four toxic heavy metals (Ni, Cr, Cd and As) and sixteen environmental parameters (e.g., parent material, slope gradient, proximity to roads, etc.) in the soils of northern Lebanon (as a case study of Mediterranean landscapes), and to detect the most important parameters that can be used as weighted input data in soil pollution prediction models. The developed strongest relationships were associated with Cd and As, variance being equal to 82%, followed by Ni (75%) and Cr (73%) as the weakest relationship. This study also showed that nearness to cities (with a relative importance varying between 68% and 100%), surroundings of waste areas (48–92%), proximity to roads (45–82%) and parent materials (57–73%) considerably influenced all investigated heavy metals, which is not the case of hydromorphological and soil properties. For instance, hydraulic conductivity (18–41%) and pH (23–37%) control the distribution of the investigated heavy metals more than soil type (21–32%), soil depth (5–17%), organic matter content (2–7%), and stoniness ratio (0–7%). Slope gradient affected Ni/Cr/Cd /As accumulation (10–13%), while slope length, slope aspect and slope curvature did not interfere in the building of soil heavy metals’ regression-trees and associated relationships. The latter can be extrapolated to other areas sharing similar geo-environmental conditions.

Susceptibility assessment to different types of landslides in the coastal cliffs of Lourinhã (Central Portugal)

The coastal zone of Lourinhã (located in Central Portugal) is characterized by beach–cliff systems, where beaches are narrow and cliffs have notorious slope instability. These cliffs evolve by different types of landslides, which are one of the main sources of natural hazard and risk in this coastal region.In this work, aerial photo interpretation and a systematic field survey were performed in order to obtain an inventory of landslides of the following types: rotational slides, translational slides and debris flows. The entire coast was then split into 261 terrain mapping units. For each unit, landslide predisposing factors were derived and classified: cliff elevation, slope angle (maximum, mean and standard deviation), potential solar radiation, slope curvature (profile and plan), lithological units and geologic structure. The predictive susceptibility models were computed for each type of landslide using a bi-variate statistical method — the Information Value Method. The degree of fit and the predictive capacity of the models were assessed using the Effectiveness Ratio, the standard Receiver Operator Characteristic curves and the respective Area Under Curve.Results show that each landslide typology occurs in particular terrain conditions. Individual susceptibility models evidence better predictive capacity than susceptibility model for total landslides.

On the bounds of CKM matrix element Vcb in a potential model

Considering the allowed range of slope ρ2 and curvature C of Isgur–Wise function for B meson, we obtain an allowed range of strong coupling constant αs as well as the QCD scale parameter Λ in a specific prescription. The allowed range of Λ is then used to obtain the theoretical bounds on Vcb in a potential model. The recent available data of Vcb are found to lie within this computed range 0.0375 ≤|Vcb|≤0.0410.

The unacknowledged risk of Himalayan avalanches triggering

A “universal” model for avalanche triggering, as well as for collapse of suspended seracs, is presented based on Quantized Fracture Mechanics, considering fracture, friction, adhesion and cohesion. It unifies and extends the classical previous approaches reported in the literature, including the role of the slope curvature. A new size-effect, that on mountain height rather than the classical one on snow slab thickness, is also discussed and demonstrated thanks to glaciers data analysis from the World Glacier Inventory (http://nsidc.org/data/glacier_inventory/browse.html, 2014). The related most noteworthy result is that snow precipitation needed to trigger avalanches at 8,000 m could be up to 4 times, with a realistic value of 1.7 times, smaller than at 4,000 m. This super-strong size-effect may suggest that the risk of Himalayan avalanches is today still unacknowledged. A discussion on the recent Manaslu tragedy concludes the paper.

Multi-Temporal Detection of Rice Phenological Stages Using Canopy Spectrum

Information on rice phenology is essential for yield estimation and crop management. To test the ability of remote sensing in detecting multiple phenological stages, paddy rice canopy spectrum was measured by a hand-held radiometer. Normalized difference vegetation index (NDVI) was calculated from spectrum, and the slope of NDVI was obtained as its difference. We evaluated the response of NDVI and its slope to rice growth with a comparison of two late-season rice cultivars. The results showed that NDVI and its slope curves had distinct variation corresponding to rice development and they could be used as cultivar-independent phenological indicators. The dates of flooding and transplanting, tillering, panicle development, heading and flowering, maturity, harvest stages, and even field management practices, could be deduced from these indicators. ‘NDVI ≤ 0’ could be used as a single threshold for the detection of flooding and transplanting. The largest spike in the curve of the NDVI slope indicated the duration of tillering stage. The next spike corresponded to panicle development. The heading and flowering stage was characterized by the maximum NDVI and the change of NDVI slope from positive to negative. At the maturity stage, NDVI decreased continuously, and its slope fluctuated just below zero. When rice grains were completely mature and ready for harvest, NDVI decline was accelerated. At harvest, NDVI slope reached its minimum value. The distinction between heading and maturity stages was obscure, most likely due to NDVI saturation at high biomass. The study might provide references for paddy rice phenology determination through remote sensing images.