OCCUPATION OF FLOODPLAIN SPACES AND URBAN PERMANENT PRESERVATION AREAS IN FLORIANO - PI: PROPOSALS TO MITIGATE THE EFFECTS OF FLOODING

Abstract

Urban growth leads to the occupation of spaces that, due to their importance and ecological fragility, are unsuitable for human occupation, especially floodplains and/or permanent preservation areas (APPs). Municipal master plans do not always include them in their non-edificandi zones, limiting monitoring against their occupation. With geotechnologies, it is possible to map these areas and simulate the risks associated with their occupation due, for example, to water variations, especially with ongoing climate change. This study aimed to characterize the occupation of urban floodplains and/or APPs and propose approaches to mitigate the effects of occupations in areas sensitive to flooding. Supervised classification techniques (MaxVer) were applied to analyze the occupation of the urban network of Floriano-PI, including its flood-prone areas and/or APPs. Relief analysis (HAND) and scenario simulation (LCM/Change Allocation) algorithms were used to estimate areas at risk of flooding. The combination of these techniques has made it possible to advance in the identification of areas at risk due to inadequate occupation, which in the case under study can cover up to 579 ha (hectares). The occupation of APP spaces in the municipality increased by 54.75% between 2004 and 2020, mainly in areas with herbaceous vegetation, which decreased by 92.09%, while only 08.65% have relatively preserved vegetation. Many of the areas close to the banks of the Parnaíba River are at high risk of flooding if the 8-meter flood level is reached. The simulation of the scenario until 2050 indicates progress in the occupation of the most sensitive areas already identified. The risks of flooding can have their effects mitigated by the protection/restoration of APPs, floodplains and other green areas, mainly on the peri-urban banks of the Parnaíba River, which are still without consolidated occupations.