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

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 Qua...

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Bibliographic Details
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
Description
Summary: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.

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