Multivariate spatial analysis of hydrological extremes in urban watersheds

Understanding hydrological extremes and the factors that condition them is crucial to 
promoting the adaptability of urban watersheds. Furthermore, few studies investigate 
the spatial variability of these factors and their explanatory power. This study analyzed 
the Tamanduateí River Basin, located in São Paulo, Brazil, using data from multiple 
sources to explore the spatial relationships between inundation points occurrence and 
geo-environmental factors. Spatial autocorrelation models, as Global and Local 
Moran’s Index were applied in these points to identify patterns and areas most 
susceptible to these events. To assess the explanatory power and interaction among 
11 geo-environmental factors - including Topographic Position Index (TPI), Terrain 
Roughness Index (TRI), Sediment Transport Index (STI), Stream Power Index (SPI), 
Topographic Wetness Index (TWI), Drainage Density (DD), Height Above Nearest 
Drain (HAND), Slope, Hillshade, Distance to River (DR) and Cumulative Expanded 
Area (AEXPAND) - the Geodetector geostatistical tool was used. Subsequently, the 
Multiscale Geographically Weighted Regression (MGWR) algorithm was used to 
examine the most relevant factors, allowing a detailed analysis of the spatial interaction 
among them. The results indicated a strong spatial dependence of inundation points 
occurrence and showed significant simultaneous effects of the factors analyzed. Flat 
areas with consolidated anthropogenic use had a higher incidence of these events, 
with variables such as HAND and AEXPAND standing out. These findings reinforce the 
importance of topography and land use in the dynamics of hydrological extremes. This 
study offers an integrated approach to understanding the spatial heterogeneity of 
hydrological extremes in urban areas, contributing to the mapping of these events. In 
addition, the proposed methodology can be replicated in other regions, especially 
those with scarce spatial data, expanding the possibilities for preventing and adapting 
to extreme events in different urban contexts.