Author(s): Geoffrey Fouad; Terrie Lee

Linked Author(s): Geoffrey Fouad, Terrie Lee

Keywords: Wetland; Streamflow; LiDAR

Abstract: Small, depressional wetlands are known to outflow and contribute to streamflow, but the discharge rates of these wetlands are not well-defined in the literature. Physical modeling methods have grid-cell resolutions that can mask the contributions of small wetland features. Therefore, the present study proposes an empirical approach to predict wetland discharge rates based on a combination of very high-resolution (0.8 × 0.8-meter) light detection and ranging (LiDAR) terrain data and streamflow data collected at existing stream-gage locations far downstream from headwater wetlands. The grid-based calculations predict discharge rates at wetland perimeters by month, season, and year, and over different time periods to assess how discharge rates have changed due to external factors, such as groundwater pumping and changes in precipitation. Because discharge rates are not gauged at small wetlands, the present study validates the methodology at stream gages excluded from the process of predicting wetland discharge rates. The results of this study demonstrate the effectiveness of this approach in areas where surface-water runoff is not heavily modified by humans. In areas of human modification, additional data of surface-water runoff from specific units of land and stormwater management systems are required to augment predictions. Overall though, the method shows promise as a means of predicting wetland discharge rates in natural drainage systems subject to climatic changes and the effects of groundwater pumping.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022954

Year: 2022