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Abstract The hydrologic connectivity of non-floodplain wetlands (NFWs) with downstream water (DW) has gained increased importance, but connectivity via groundwater (GW) is largely unknown owing to the high complexity of hydrological processes and climatic seasonality. In this study, a causal inference method, convergent cross mapping (CCM), was applied to detect the hydrologic causality between upland NFW and DW through GW. CCM is a nonlinear inference method for detecting causal relationships among environmental variables with weak or moderate coupling in nonlinear dynamical systems. We assumed that causation would exist when the following conditions were observed: (1) the presence of two direct causal (NFW → GW and GW → DW) and one indirect causal (NFW → DW) relationship; (2) a nonexistent opposite causal relationship (DW → NFW); (3) the two direct causations with shorter lag times relative to indirect causation; and (4) similar patterns not observed with pseudo DW. The water levels monitored by a well and piezometer represented NFW and GW measurements, respectively, and the DW was indicated by the baseflow at the outlet of the drainage area, including NFW. To elucidate causality, the DW taken at the adjacent drainage area with similar climatic seasonality was also tested as pseudo DW. The CCM results showed that the water flow from NFW to GW and then DW was only present, and any opposite flows did not exist. In addition, direct causations had shorter lag time than indirect causation, and 3-day lag time was shown between NFW and DW. Interestingly, the results with pseudo DW did not show any lagged interactions, indicating non-causation. These results provide the signals for the hydrologic connectivity of NFW and DW with GW. Therefore, this study would support the importance of NFW protection and management.

Objectives This study aims to assess the applicability of the SWAT-C water quality model recently developed to predict in-stream Total Organic Carbon (TOC) in a watershed within South Korea. Methods The SWAT-C model was tested in the Hwangryong River Watershed. SWAT-C is an advanced version of Soil and Water Assessment Tool (SWAT) to simulate carbon cycling at the watershed scale. The model was simulated for 11 years (2010-2020) consisting of 2-year warm-up (2010-2011), 6-year calibration (2012-2017), and 3-year validation (2018-2020) periods. SWAT-C was calibrated and validated against monthly streamflow and TOC loads. The model performance was evaluated using NSE (Nash-Sutcliffe efficiency), KGE (Kling-Gupta efficiency), and PBIAS (percent bias) Simulated Dissolve Organic Carbon (DOC) and Particulate Organic Carbon (POC) loads were also presented to see the major caron type loaded to the downstream. Results and Discussion The calibration results showed that SWAT-C could depict streamflow and TOC loads with acceptance model performances (NSE > 0.5, KGE > 0.5 and PBIAS =< 25%). Especially, the seasonal variations of TOC loads were well simulated by SWAT-C. The TOC load was predicted to increase in the summer season with high precipitation and slightly lower in the other seasons. This seasonal pattern is likely caused by frequent heavy rainfall events in summer. Conclusion This study demonstrated that SWAT-C model is applicable in South Korea with sufficient prediction accuracy. Thus, SWAT-C would serve as an efficient tool to monitor TOC loads in South Korea.