According to studies by the Intergovernmental Panel on Climate Change (IPCC), tropical mountainous areas are experiencing increasingly unfavorable climatic conditions regarding geohazards due to a heightened occurrence of intense rainfall events. These climatic shifts contribute to heightened geological risks, notably an elevated frequency of landslides, exacerbating the challenges faced by these regions. There is an urgent need to understand and measure how rainfall variability affects geo-hydrological hazards, which remain difficult to determine and predict. The complex and non-linear space-time relationships and dynamics of rainfall, El Niño-Southern Oscillation (ENSO), and landslides in the Tropical Andean Mountain region in Colombia require an adequate analysis and understanding of their link in terms of its spatial and temporal component at different scales. By evaluation in annual, seasonal, and monthly scales, additional insights on the relationships using a wavelet spectral analysis and a space-time permutation scan statistics method using SaTScan^™ are provided. In this study, a space-time and frequency analysis of landslides using a 42-year (1981–2022) rainfall and Multivariate ENSO Index v2.0 time series is presented. According to the results, landslides closely aligned with rainfall patterns, exhibiting a bimodal annual cycle. The ENSO added complexity, with La Niña years leading to more frequent landslides throughout the year and El Niño years showing concentrated occurrences in specific months. This study highlights the influence of rainfall patterns and antecedent rainfall on landslide occurrence, the impact of ENSO phases on rainfall and landslides, and the increasing trend of landslides in Colombia.

Landslides are a significant global hazard, especially prevalent in regions with high rainfall, active tectonic processes, and rugged topography, such as the Colombian Andean region. Therefore, it is crucial to identify areas prone to landslides in order to protect human lives and mitigate the adverse impacts on national economies, especially in developing countries situated in tropical and mountainous regions. Assessing landslide hazard and susceptibility is a fundamental step in comprehending the fundamental characteristics of slopes susceptible to failure, particularly under extreme rainfall conditions. Various researchers have devised methods and techniques to assess and map landslides, employing heuristic, statistical, and deterministic approaches. This study carried out a geographic information system-based approach for shallow landslides, with the objective to compare different methods for a landslide-event hazard mapping using the landslide records on May 18, 2015, triggered by a rainstorm in the La Liboriana basin (Colombia). In the first place, a fuzzy logic gamma model was applied using landslide conditioning factors. Then, the deterministic model TRIGRS was applied to assess shallow landslides. Finally, a support vector machine (SVM) model was used to obtain an intermediate scale solution. All models consider the rainfall that triggered the aforementioned landslide event. The results indicated that the SVM (radial basis function) model permits to obtain a better performance (AUC = 0.95) in landslide hazard zonation rather than quantitative heuristic fuzzy gamma model (AUC = 0.86) and the deterministic TRIGRS model (AUC = 0.60), obtaining best accurate at predicting the landslide hazard in the study area.

Brick is one of the most common building materials, and it is also one of the largest components of waste generated from both construction and demolition. Reuse of this waste would reduce the environmental and social impacts of construction. One potential bulk use of such waste is as a cementing agent for soil stabilization. However, this is currently limited by the need to mill the residue to a particle size below 0.035 mm. In this study, the behavior of two soil types stabilized using alkali-activated brick dust was investigated. The unconfined compression strength at different curing temperatures and moistures and the use of different types and concentrations of alkaline activators were investigated. It was found that the addition of brick dust resulted in an increase in the soil strength between 1.7–2.3 times with respect to the non-stabilized material, suggesting that the resulting materials will find practical applications in construction.

In several countries, brick and ceramic tile are the most important construction materials; therefore, associated waste generation is common in construction and demolitions. An alternative use for waste is to incorporate it into road construction. However, the biggest limitation to use it as structural pavement layers is that strength and durability regulatory requirements are not met for highways when it is used. As an alternative, construction and demolition waste (CDW) soil mixtures are proposed as subgrade improvements which require less of a thickness increase of pavement structures to meet highway standards. The results of this article present the behavior of silty soil, brick residues, and ceramic tile mixtures in different added material ratios. Laboratory evaluations were conducted and included material characterization, compaction tests, obtaining CBR values, and obtaining resilient moduli. A parametric thicknesses evaluation was performed on flexible pavement structures with different traffic conditions and CDW ratios. It was concluded that CDW material addition increases strength and the resilient modulus similarly to granular subbase (AASHTO M147-65). Therefore, the pavement thickness can be reduced, and costs can be decreased by more than 7%.