Author(s): Sergio Zubelzu; Sara E. Matendo; Victor Galan; Andrea Zanella; Mehdi Bennis

Linked Author(s): Sergio Zubelzu

Keywords: Urban hydrology; Flooding; Data processing

Abstract: Watershed based hydrological phenomena are affected by extreme spatial and temporal variability. This complicates the accurate modelling and forecasting particularly in urban environments were specific local conditions add further complexity. In this paper we address the spatial and temporal relationships of a set of weather variables with data collected from a weather station network located in a highly urbanized environmental as Madrid city. We mainly focus on precipitation seeking to give an accurate insight on valuable information for hydrology analysis. We address this study with data-driven models by analysing both precipitation spatial and temporal self-correlations and causal relationships between precipitation and primary variables.

DOI: https://doi.org/10.3850/IAHR-39WC2521711920221534

Year: 2022