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The Artificial Neural Network (ANN) has been widely used in flood modeling and has proven to be good accuracy. This research aims to flash flood modeling using ANN. The flash flood modeling was conducted at Welang Watershed, Pasuruan District, East Java, Indonesia. The input of flash flood using ANN consists of rainfall and runoff coefficient. The runoff coefficient was derived by the Normalized Difference Vegetation Index (NDVI) value from the Landsat 8 Operational Land Imager (OLI). The output ANN model was flash flood discharge. The ANN architecture model uses a backpropagation neural network. The period of training and testing model ANN using data from January to February 2017 period and November to December 2017 period, respectively. The Result of flash flood modeling with ANN showed the good of fitness pattern between output model and observation data.

Flash flood modeling using the artificial neural network (Case study: Welang Watershed, Pasuruan District, Indonesia