The present study tends to describe the survey of climatic changes in the case of the Bojnourd region of North Khorasan, Iran. Climate change due to a fragile ecosystem in semi-arid and arid regions such as Iran is one of the most challenging climatological and hydrological problems. Dendrochronology, which uses tree rings to their exact year of formation to analyse temporal and spatial patterns of processes in the physical and cultural sciences, can be used to evaluate the effects of climate change. In this study, the effects of climate change were simulated using dendrochronology (tree rings) and an artificial neural network (ANN) for the period from 1800 to 2015. The present study was executed using the Quercus castaneifolia C.A. Meyer. Tree-ring width, temperature, and precipitation were the input parameters for the study, and climate change parameters were the outputs. After the training process, the model was verified. The verified network and tree rings were used to simulate climatic parameter changes during the past times. The results showed that the integration of dendroclimatology and an ANN renders a high degree of accuracy and efficiency in the simulation of climate change. The results showed that in the last two centuries, the climate of the study area changed from semiarid to arid, and its annual precipitation decreased significantly.
tree ring; autoregressive standardization; temperature; precipitation; Iran
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