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IN-depth SYnthetic Model for Flood Damage Estimation (INSYDE) is a model for the\udestimation of flood damage to residential buildings at the micro-scale. This study investigates the\udsensitivity of INSYDE to the accuracy of input data. Starting from the knowledge of input parameters\udat the scale of individual buildings for a case study, the level of detail of input data is progressively\uddowngraded until the condition in which a representative value is defined for all inputs at the census\udblock scale. The analysis reveals that two conditions are required to limit the errors in damage\udestimation: the representativeness of representatives values with respect to micro-scale values and\udthe local knowledge of the footprint area of the buildings, being the latter the main extensive variable\udadopted by INSYDE. Such a result allows for extending the usability of the model at the meso-scale,\udalso in different countries, depending on the availability of aggregated building data

On the Influence of Input Data Quality to Flood Damage Estimation: The Performance of the INSYDE Model