Detecting causal relationship of non-floodplain wetland hydrologic connectivity using convergent cross mapping

Authors: LEE, S. - University Of Maryland; LEE, B - University Of Maryland; LEE, J - Korea University; SONG, J - Korea University; McCarty, Gregory

Submitted to: Scientific Reports
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/3/2023
Publication Date: 11/19/2023
Citation: Lee, S., Lee, B., Lee, J., Song, J., Mccarty, G.W. 2023. Detecting causal relationship of non-floodplain wetland hydrologic connectivity using convergent cross mapping. Scientific Reports. 13: Article e17220. https://doi.org/10.1038/s41598-023-44071-0.
DOI: https://doi.org/10.1038/s41598-023-44071-0

Interpretive Summary: Depressional wetlands are often considered to be isolated from the surrounding landscape and remain vulnerable in the United States because their regulatory status is dependent on the Clean Water Act (CWA). Legal protection under the CWA is currently restricted to wetlands with demonstrated connection to downstream waters. This study used a new, nonlinear approach for establishing causal connections by detecting the flow of information from the wetland to downstream waters. The measurement of this information flow is difficult because of the nonlinear nature of hydrologic flows. This approach was successful for demonstrating a causal relationship between depressional wetlands under study and downstream waters. This approach can provide a new basis for protecting depressional wetlands under current law.

Technical Abstract: The connection of geographically isolated wetlands (GIWs) with a larger landscape setting has been aggressively debated in recent years and has gained increased importance in the United States because regulatory status of GIWs has been tied establishing a certain level of hydrologic connectivity (significant nexus) between GIWs and downstream waters (DWs). Due to high complexity of hydrological processes along a hydraulic gradient and climatic seasonality, in-situ observations are limited to offer evidence that supports hydrologic connectivity between GIW and DWs through groundwater (GW). This study used convergent cross mapping (CCM) to detect information flow from GIWs to DWs via GW on the Coastal Plain using time series observations. CCM is a nonlinear inference method to detect causal relationships among environmental variables with weak or moderate coupling in nonlinear dynamical systems. This approach was used to quantify three causal relationships (“cause” toward “effect”) in a transitive causal chain from GIWs to DWs through GW. Surface water level and groundwater level of two wetlands were monitored using a set of nested pressure transducers instrumenting wells to monitor wetland surface water levels (GIW time series) and piezometers to monitor groundwater pressures (GW time series). DW time series was baseflow derived from streamflow collected at the outlet of the drainage area including the two monitored wetlands. CCM results showed that three causal relationships (GIW toward GW, GW toward DWs, and GIW toward DWs) were present, but the opposite causal relationship (DWs toward GIW/GW) did not exist. This finding indicated an indirect causal relationship (GIW toward DW) via two direct causal relationships (GIW toward GW and GW toward DW). Two direct causal relationships also exhibited stronger causality and shorter lag relative to the indirect causal relationship. This causal chain (GIW toward GW toward DW) is indicative of information flow from GIWs to DWs through GW, supporting evidence of a measurable connection between GIWs and DWs through GW on this coastal region.