Effect of multiple climate change scenarios and predicted land-cover on soil erosion: a way forward for the better land management.

The ecosystem, biodiversity, and anthropological existence in the Chitral district are in danger due to the sediments and soil erosion stemming from the changes in the land-cover and climate. This research aims to practice the RUSLE model with the changes in the land-cover and climate in upcoming situations for 2030 and 2040 to evaluate soil erosion annually as per the spatial dissemination and the tendency of sediment yield. The multilayer perceptron (MLP), an artificial neural network (ANN), besides the Markov chain analysis was used to model upcoming land-cover.