Abstract: A server obtains a natural language query from a first user device. The server matches an intent to the natural language query using an intent matching engine. The intent represents predicted data associated with the natural language query. The server transmits the natural language query and the intent to a second user device. The server receives, from the second user device, a response indicating whether the natural language query is properly matched to the intent. The server trains the intent matching engine based on a machine learning technique and the response.

Abstract: Methods, systems, and computer programs are presented for determining flood levels within a region. One method includes an operation for detecting an alert generated by one of a riverine, a coastal, or an urban model. Further, the method includes operations for selecting one or more regions for estimating flood data based on the detected alert, and for calculating, by an inundation model, region flood data for each of the selected regions based on outputs from the riverine model, the coastal model, and the urban model. Additionally, the method includes an operation for combining the region flood data for the selected one or more regions to obtain combined flood data. The combined flood data is presented on a user interface, such as on a flood inundation map.