Estimation of Rainwater Quality Using GPS-derived Atmospheric Propagation Delay and Meteorological Data

We investigated GPS-derived atmospheric propagation delays and meteorological data for estimating rainwater quality by creating a regression model using the combinatorial group method of the datahandling algorithm (COMBI GMDH). The dependent variable was the daily wet deposition, while the independent variables were zenith hydrostatic delay, zenith wet delay, daily rainfall, and daily average wind speed. The model had a coefficient of determination (R-2) of 0.70 and a correlation coefficient of 0.84. The mean absolute error (MAE) was 30.20, mu mol/m(2)-day and the root mean square error (RMSE) was 40.94 mu mol/m(2)-day. Accuracy testing to validate the model revealed an R-2 of 0.95 with a correlation coefficient of 0.98. The MAE was 12.14 mu mol/m(2)-day and the RMSE 15.35 mu mol/m(2)-day. Rainwater quality could be estimated using GPS-derived atmospheric propagation delay (APD) and meteorological data.