Landslide disaster risks increase worldwide, particularly in urban areas. To design and implement more effective and democratic risk reduction programs, calls for transdisciplinary approaches have recently increased. However, little attention has been paid to the actual articulation of transdisciplinary methods and their associated challenges. To fill this gap, we draw on the case of the 1993 Quebrada de Macul disaster, Chile, to propose what we label as the Geo-Social Model. This experimental methodology aims at integrating recursive interactions between geological and social factors configuring landslide for more robust and inclusive analyses and interventions. It builds upon three analytical blocks or site-specific environments in constant co-determination: (1) The geology and geomorphology of the study area; (2) the built environment, encompassing infrastructural, urban, and planning conditions; and (3) the sociocultural environment, which includes community memory, risk perceptions, and territorial organizing. Our results are summarized in a geo-social map that systematizes the complex interactions between the three environments that facilitated the Quebrada de Macul flow-type landslide. While our results are specific to this event, we argue that the Geo-Social Model can be applied to other territories. In our conclusions, we suggest, first, that landslides in urban contexts are often the result of anthropogenic disruptions of natural balances and systems, often related to the lack of place-sensitive urban planning. Second, that transdisciplinary approaches are critical for sustaining robust and politically effective landslide risk prevention plans. Finally, that inter- and trans-disciplinary approaches to landslide risk prevention need to be integrated into municipal-level planning for a better understanding of—and prevention of—socio-natural hazards.

In the world, the hazards of intense rainfall are recurrent and increasing. In addition, they are one of the natural hazards that cause the most severe damage to infrastructure and even cause deaths every year. Flow-type landslides are capable of develop in areas with different geomorphological, geological and climatic characteristics. In hyper-arid zones such as the Atacama Desert, these hazards are capable of develop in a timely manner, causing catastrophes. This study analyzes the flow-type landslide in a hyper-arid mountainous area in La Chimba basin of Antofagasta city (Chile). For this, a hydrometeorological analysis is carried out through a pluviometric analysis, statistical analysis of frequencies through the Gumbel probabilistic method of extreme values and determination of maximum flows by obtaining IDF (intensity-duration-frequency) curves and design rainfall intensity as a function of concentration time. To obtain the maximum flows of liquid runoff and debris, for different return periods, the rational method was used with the method proposed by O’Brien. For the determination in the impact zone, the modeling software HEC-RAS (Hydrologic Engineering Center's River Analysis System) and RAMMS (Rapid Mass Movements). Hydrographs are used for a return period of about 200 years, considered the most unfavorable scenario with the Voellmy–Salm model. To validate the modeling, a morphometric, sedimentological and comparative analysis is carried out between real impact zones of 1991 event and those generated in this study. It is concluded that the sedimentological and morphometric characteristics indicate that the type of flow that it can originate would have a rapid response to rainfall events of great intensity or duration. The modeling provided by HEC-RAS represents a fluvial-type flow, while the RAMMS modeling is closer to the consistency of a flow-type landslide, which is estimated to be closer to reality. The results show that despite being in a hyper-arid zone, the rainfall factor is capable of landslides triggering in mountainous areas.

In multivariate analysis, a predictive model is a mathematical/statistical model that relates a set of independent variables to dependent or response variable(s). This work presents a descriptive model that explains copper recovery from secondary sulfide minerals (chalcocite) taking into account the effects of time, heap height, superficial velocity of leaching flow, chloride concentration, particle size, porosity, and effective diffusivity of the solute within particle pores. Copper recovery is then modelled by a system of first-order differential equations. The results indicated that the heap height and superficial velocity of leaching flow are the most critical independent variables while the others are less influential under operational conditions applied. In the present study representative adjustment parameters are obtained, so that the model could be used to explore copper recovery in chloride media as a part of the extended value chain of the copper sulfides processing.