Data-Driven Regionalization of Surface Discharge in Unmonitored Catchments of the Baltic Sea Drainage Basin

A significant share of freshwater discharge from Baltic Sea drainage basin (BSDB) originates from unmonitored or poorly monitored coastal catchments, which increases uncertainty in regional water balance assessments and in estimates of nutrient and pollutant loads to the Baltic Sea. This study presents a data-driven regionalization framework designed to estimate surface discharge in unmonitored Baltic Sea catchments at monthly, seasonal, and annual scales for the period 2001-2020. A large-sample dataset for about 720 monitored basins is compiled using Global Runoff Data Centre discharge records together with hydro-meteorological and land-surface predictors, including precipitation, evapotranspiration and temperature, topographic attributes, and land-cover fractions. Predictors are selected based on the catchment water balance and processed consistently across all basins using zonal statistics. Multiple linear Regression (MLR) and Random Forest (RF) models are trained on specific discharge, and several modelling configurations are evaluated, including temporal grouping, geographical neighbouring strategies, clustering approaches and the inclusion of correlated variables. A hybrid correction method helps identify which parts of each BSDB are monitored and which are not, making sure discharge is predicted only for the unmonitored areas. The most effective configuration was combined temporal grouping with geographical neighbouring, and it achieved satisfactory performance (NSE > 0.5) for roughly 75% of basins and very good performance (NSE > 0.75) for more than half of basins. Median absolute percentage errors were below 30%. Land use characteristics (e.g. crop land, forest, waterbodies) provide important explanatory power alongside climatic and topographical variables.  The framework provides consistent discharge estimates for ungauged coastal basins in the Baltic Sea region and can be applied in other areas where data is limited to support regional water balance and pollutant load assessment.