Many cities suffer the consequences of flooding after a large amount of water
falls in a short period of time. Therefore, this project determines how urban
vegetation modifies soil structure, improving its water infiltration capacity and
reducing flood damage, putting Nature-Based Solutions (NBS) into practice.
A humidity sensor was built using Arduino and the humidity and water
infiltration capacity of soils influenced by five tree species and seven different shrub
species were measured. Analysis of the results obtained shows that areas
occupied by shrubs infiltrate a greater amount of water. In this sense, species such
as rosemary (Salvia rosmarinus) and oleander (Nerium oleander) stand out for the
development of their root system.
With this information, an image recognition model was created and trained
using LearningML, capable of identifying the studied plants in situ and indicating the
infiltration capacity of the surrounding soil. From it, a Geographic Information
System (GIS) was generated using the QGIS program, which shows the areas of our
city most vulnerable to torrential rains and flooding.
On September 11, 1891, a fatal flood struck the town of Consuegra, killing 359 people. Due to the tragic loss of my ancestors in a devastating flood, I am deeply committed to preventing future flooding events in order to save lives and minimize economic damage around the world.
