Artificial Neural Networks-generated Dataset: pH, Total Alkalinity, and Hydrogen Ion Concentration in Ría de Vigo (NW Spain), 1995–2020

This dataset comprises input data from INTECMAR and the predicted outcomes. The variables and their units are as follows:

station: 'Station ID [1-6]'

year: 'Year [1995-2020]'

month: 'Month [1-12]'

day: 'Day'

latitude: 'Latitude (decimal degrees)'

longitude: 'Longitude (decimal degrees)'

depth: 'Depth (meters)'

temperature: 'Temperature (degrees Celsius)'

salinity: 'Salinity (psu)'

phosphate: 'Phosphate (umol/kg)'

nitrate: 'Nitrate (umol/kg)'

silicate: 'Silicate (umol/kg)'

cweek: 'Cosine week'

sweek: 'Sine week'

TA: 'Total Alkalinity predicted (umol/kg)'

NTA: 'Normalized Total Alkalinity (umol/kg)'

NAT_st: 'Normalized per station Total Alkalinity (umol/kg)'

NTA_gl: 'Normalized globally Total Alkalinity (umol/kg)'

pHTS_insitu: 'pH insitu (pH units)'

HT: 'Hydrogen ion concentration predicted (nmol/kg)'

The authors gratefully acknowledge the financial support by the Programa de axudas á etapa predoutoral da Xunta de Galicia (Axencia Galega de Innovación) (Grant nº IN606A-2022/025). F.F.P. and A.V. were supported by REDEIRA (TED2021-132188B-I00) project, funded by MCIN/AEI/10.13039/501100011033. The authors also express their gratitude to the Instituto Tecnolóxico para o Control do Medio Mariño de Galicia (INTECMAR), for the analyses and production of the database used to make predictions.