Swept Away: Flooding and landslides in Mexican poverty nodes

Natural disasters should be examined within a risk-perspective framework where both natural threat and vulnerability are considered as intricate components of an extremely complex equation. The trend toward more frequent floods and landslides in Mexico in recent decades is not only the result of more intense rainfall, but also a consequence of increased vulnerability. As a multifactorial element, vulnerability is a low-frequency modulating factor of the risk dynamics to intense rainfall. It can be described in terms of physical, social, and economical factors. For instance, deforested or urbanized areas are the physical and social factors that lead to the deterioration of watersheds and an increased vulnerability to intense rains. Increased watershed vulnerability due to land-cover changes is the primary factor leading to more floods, particularly over pacific Mexico. ln some parts of the country, such as Colima, the increased frequency of intense rainfall (i.e., natural hazard) associated with high-intensity tropical cyclones and hurricanes is the leading cause of more frequent floods.

 

In this research an intelligent rain management-system is presented. The object is built to forecast and to simulate the components of risk, to stablish communication between rescue/aid teams and to help in preparedness activities (training). Detection, monitoring, analysis and forecasting of the hazards and scenarios that promote floods and landslides, is the main task. The developed methodology is based on a database that permits to relate heavy rainfall measurements with changes in land cover and use, terrain slope, basin compactness and communities’ resilience as key vulnerability factors. A neural procedure is used for the spatial definition of exposition and susceptibility (intrinsic and extrinsic parameters) and Machine Learning techniques are applied to find the If-Then relationships. The capability of the intelligent model for Colima, Mexico was tested by comparing the observed and modeled frequency of landslides and floods for ten years period. It was found that over most of the Mexican territory, more frequent floods are the result of a rapid deforestation process and that landslides and their impact on communities are directly related to the unauthorized growth of populations in high geo-risk areas (due to forced migration because of violence or extreme poverty) and the development of civil infrastructure (mainly roads) with a high impact on the natural environment. Consequently, the intelligent rain-management system offers the possibility to redesign and to plan the land use and the spatial distribution of poorest communities.