This article outlines a methodology for assessing landslide susceptibility and puts forth a monitoring and alert system based on computational modeling. The highlighted area is notorious region for recurring landslide incidents, resulting in both material and occasionally human losses due to extensive human settlement. Employing finite element analysis (FEA) and the limit equilibrium method (LEM) a comprehensive approach to evaluate landslide susceptibility in the specified region was developed. The analyses, incorporating stress and strain considerations and determining the factor of safety, were integrated with rainfall-induced infiltrations. The introduction of soil mass creep concepts into computational analyses aids in establishing alert and emergency thresholds for both horizontal and vertical displacements, both on the surface and at depth. Instruments were recommended for reading these parameters, generating a continuous on-site monitoring associated to several levels of alerts. A sensitivity analysis with variations in the friction angle, elastic modulus and permeability values of the unstable soil mass was performed in order to parametrically evaluate these parameters influence.
Contaminant leaching from asphalt pavements poses a significant environmental concern, potentially damaging soil and groundwater quality. The growing interest in incorporating recycled materials in asphalt pavements has further raised concerns over the potential environmental hazards due to contaminant leaching. Consequently, this paper offers a comprehensive review of the literature over the past three decades structured into six sections: groundwater contamination via leaching, methodologies for evaluating leaching, analysis of contaminants, contaminants and leaching from road materials incorporating recycled waste, other factors affecting leaching of pollutants from asphalt pavements, and mathematical models to predict leaching from asphalt pavements. Despite the importance of addressing leaching issues, there is a lack of standardised leaching tests and guidelines specific to asphalt materials, limited attention to evaluating contaminants beyond heavy metals and PAHs in asphalt leachates, insufficient understanding of optimal instrument parameters for asphalt leachate analysis, and a scarcity of mathematical models to predict future leaching potential.
The city of Arequipa, the second most important city in Per & uacute;, faces numerous daunting challenges, including high-intensity but short-induration rainfalls that leads to floods and the swelling of the Chili River (mud and landslides). This situation aggravates the vulnerability of the population settled on the margins of the gorges and gullies, due to little or no territorial planning from public institutions. The local news evidence negligence every year, both in terms of human lives and infrastructure loss. The frequency of these events has increased with time and that is the reason for prompting the establishment of rainfall thresholds and the compilation of a 41-year record (1981-2021), with the aim of informing about the dangerousness of an adverse meteorological phenomenon, either predicted or in progress. For the hydrological model, the authors used the highest 24-hour precipitation data from the SENAMHI's stations (National Service of Meteorology and Hydrology of Peru) to generate the liquid hydrograph for different return periods with the Hydrologic model of HEC-HMS. Soil mechanics studies were also carried out to determine the rheological parameters of the non-Newtonian flow and then calibrate through historical events in a hydraulic model of HEC-RAS. Finally, cartographic maps in QGIS were prepared to evaluate the hazard zones flooding in the Del Pato, San L & aacute;zaro, Venezuela and Los Incas gullies.
Synthetic Aperture Radar Interferometry (InSAR), which can map subtle ground displacement over large areas, has been widely utilized to recognize active landslides. Nevertheless, due to various origins of subtle ground displacement, their presence on slopes may not always reflect the occurrence of active landslides. Therefore, interpretation of exact landslide-correlated deformation from InSAR results can be very challenging, especially in mountainous areas, where natural phenomenon like soil creep, anthropogenic activities and erroneous deformational signals accumulated during InSAR processing can easily lead to misinterpretation. In this paper, a two-phase interpretation method applicable to regional-scale active landslide recognition utilizing InSAR results is presented. The first phase utilizes statistical threshold and clustering analysis to detect unstable regions mapped by InSAR. The second phase introduces landslide susceptibility combined with empirical rainfall threshold, which are considered as causative factors for active landslides triggered by rainfall, to screen unstable regions indicative of active landslides. A case study validated by field survey indicates that the proposed interpretation method, when compared to a baseline model reported in the literature, can achieve better interpretation accuracy and miss rate.
Vegetation growth is adversely impacted by multiple climate extremes related to the water and thermal stress over the Tibetan Plateau (TP). However, it remains unknown at which stress level these climate extremes can trigger the abrupt shifts of vegetation response to climate extremes and result in the maximum vegetation response across TP. To fill this knowledge gap, we combined the hydrometeorological data and the satellite-derived vegetation index to detect two critical thresholds that determine the response of vegetation productivity to droughts, high-temperature extremes, and low-temperature extremes, respectively, during 2001-2018. Our results show that the response of vegetation productivity to droughts rapidly increases once crossing -1.41 +/- 0.6 standard deviation (sigma) below the normal conditions of soil moisture. When crossing -2.98 sigma +/- 0.9 sigma, vegetation productivity is maximum damaged by droughts. High-temperature extremes, which have the two thresholds of 1.34 sigma +/- 0.4 sigma and 2.31 sigma +/- 0.4 sigma over TP, are suggested to trigger the strong response of vegetation productivity at a milder stress level than low-temperature extremes (two thresholds: -1.44 sigma +/- 0.5 sigma and -2.53 sigma +/- 0.8 sigma). Moreover, we found the compounded effects of soil moisture deficit in reducing the threshold values of both high- and low-temperature extremes. Based on the derived thresholds of climate extremes that impact vegetation productivity, Earth System Models project that southwestern TP and part of the northeastern TP will become the hotspots with a high exposure risk to climate extremes by 2100. This study deciphers the high-impact extreme climates using two important thresholds across TP, which advances the understanding of the vegetation response to different climate extremes and provides a paradigm for assessing the impacts of climate extremes on regional ecosystems.
In boreal and arctic regions, forest fires exert great influences on biogeochemical processes, hydrothermal dynamics of the active layer and near-surface permafrost, and subsequent nutrient cycles. In this article, the studies on impacts of forest fires on the permafrost environment are reviewed. These studies indicate that forest fires could result in an irreversible degradation of permafrost, successions of boreal forests, rapid losses of soil carbon stock, and increased hazardous periglacial landforms. After forest fires, soil temperatures rise; active layer thickens; the release of soil carbon and nitrogen enhances, and; vegetation changes from coniferous forests to broad-leaved forests, shrublands or grasslands. It may take decades or even centuries for the fire-disturbed ecosystems and permafrost environment to return to pre-fire conditions, if ever possible. In boreal forest, the thickness of organic layer has a key influence on changes in permafrost and vegetation. In addition, climate warming, change of vegetation, shortening of fire return intervals, and extent of fire range and increasing of fire severity may all modify the change trajectory of the fire-impacted permafrost environment. However, the observations and research on the relationships and interactive mechanisms among the forest fires, vegetation, carbon cycle and permafrost under a changing climate are still inadequate for a systematic impact evaluation. Using the chronosequence approach of evaluating the temporal changes by measuring changes in the permafrost environment at different stages at various sites (possibly representing varied stages of permafrost degradation and modes), multi-source data assimilation and model predictions and simulations should be integrated with the results from long- and short-term field investigations, geophysical investigations and airborne surveys, laboratory testing and remote sensing. Future studies may enable quantitatively assess and predict the feed-back relationship and influence mechanism among organic layer, permafrost and active layer processes, vegetation and soil carbon under a warming climate at desired spatial and temporal scales. The irreversible changes in the boreal and artic forest ecosystem and their ecological and hydrothermal thresholds, such as those induced by forest fires, should be better and systematically studied.