Developing Surface Water Quality Modeling Framework Considering Spatial Resolution of Pollutant Load Estimation for Saemangeum Using HSPF

This study presented a surface water quality modeling framework considering the spatial resolution of pollutant load estimation to better represent stream water quality characteristics in the Saemangeum watershed which has been focused on keeping its water resources sustainable after the Saemangeum embankment construction. The watershed delineated into 804 sub-watersheds in total based on the administrative districts, which were units for pollutant load estimation and counted as 739 in the watershed, Digital Elevation Model (DEM), and agricultural structures such as drainage canal. The established model consists of 7 Mangyung (MG) sub-models, 7 Dongjin (DJ) sub-models, and 3 Reclaimed sub-models, and the sub-models were simulated in a sequence of upstream to downstream based on its connectivity. The hydrologic calibration and validation of the model were conducted from 14 flow stations for the period of 2009 and 2013 using an automatic calibration scheme. The model performance to the hydrologic stations for calibration and validation showed that the Nash-Sutcliffe coefficient (NSE) ranged from 0.66 to 0.97, PBIAS were -31.0~16.5 %, and R2 were from 0.75 to 0.98, respectively in a monthly time step and therefore, the model showed its hydrological applicability to the watershed. The water quality calibration and validation were conducted based on the 29 stations with the water quality constituents of DO, BOD, TN, and TP during the same period with the flow. The water quality model were manually calibrated, and generally showed an applicability by resulting reasonable variability and seasonality, although some exceptional simulation results were identified in some upstream stations under low-flow conditions. The spatial subdivision in the model framework were compared with previous studies to assess the consideration of administrative boundaries for watershed delineation, and this study outperformed in flow, but showed a similar level of model performance in water quality. The framework presented here can be applicable in a regional scale watershed as well as in a need of fine-resolution simulation.