Prediction of Stable Isotopes (18O and 2H) in the Bangkok Metropolitan Area’s Precipitation Using an Artificial Neural Network

• Published in: ECAS 2022
• Main Authors: Mojtaba Heydarizad, Nathsuda Pumijumnong
• Format: Text
• Language: English
• Published: Multidisciplinary Digital Publishing Institute 2022
• Subjects: precipitation; Bangkok; stable isotopes; prediction; artificial neural network; Indian; Soi; North Atlantic; North Atlantic oscillation
• Online Access: https://doi.org/10.3390/ecas2022-12792

The role of local (wind speed, potential evaporation, vapor pressure, air temperature, and precipitation amount) and regional parameters (teleconnection indices such as Indian Ocean Dipole (IOD), Bivariate ENSO index (BEST), North Atlantic Oscillation (NAO), Southern Oscillation index (SOI), and Quasi Biennial Oscillation (QBO) on the stable isotope content in the precipitation in Bangkok was investigated. First, a simple artificial neural network (ANN) and a Deep Learning Neural Network (DNN) were used to predict the stable isotope content in precipitation. Second, studying the fractional importance of various parameters on the stable isotope content of precipitation demonstrated that among the local and regional parameters, precipitation amount and potential evaporation (local) and the BEST teleconnection index (regional) had dominant roles in controlling the stable isotope content of the precipitation.