Prediction error from scale mismatch in input data: the Canoas Air Base runway flooding in the catastrophic flood of May 2024 in Ri'o Grande do Sul, Brazil

In May 2024, Rio Grande do Sul, Brazil, suffered a catastrophic flood. With the Salgado Filho International Airport flooded, the Brazilian Air Force (BAF) concentrated aerial aid operations to Porto Alegre at the Canoas Air Base (BACO). With water levels rising, the BAF asked LabGeo-ITA informally: would BACO’s runway soon flood? Two well-established model results predicted flooding, one of 10-30 cm. The Digital Surface Model (COPDEM 30 m) was corrected for the runway using a field-based topographic map, the model run and results checked with aerial photo and satellite imagery. Error in the DSM exceeded the sum of predicted water rise plus DSM error where flooding had been predicted. Flooding was unlikely. The nearest runway roughly an 1.5 h flight away, the BAF kept BACO the aid centre. Prediction error from scale mismatch in input data could have cost millions of Brazilian Reais in public money and possibly lives. Key words — Extreme flooding, Remote sensing, Hydraulic modelling, Uncertainty, Scale.