Reconstruction of Urban Rainfall Measurements to Estimate the Spatiotemporal Variability of Extreme Rainfall

In recent decades, the impact of climate change on urban flooding has increased, along with an increase in population and areas. Hence, historical design storms require revisions based robust intensity–duration–frequency (IDF) relationships. To this end, development rain-gauge network is essential to yield spatiotemporal attributes rainfall. The present study addresses two objectives: (a) reconstruct sub-daily rainfall time series for period over gauge network, (b) investigate variation extreme distribution within a city. This considers Bangalore, India, where been historically monitored by stations but dense recently developed. applies random forest regression reconstruction, finding that performance model better when predictand predictor are near one another. Robust IDF relationships confirm significant spatial variations at station city-region levels. areal reduction factor (ARF) also estimated order understand likely reconstructed hydrological modeling. A decrease ARF observed as area grows beyond 450 km2, indicating substantial volume floods.