Remotely mapping gullying and incision in Maryland Piedmont headwater streams using repeat airborne lidar
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Abstract
Headwater streams can contribute significant amounts of fine sediment to downstream waterways, especially when severely eroded and incised. Potential upstream sediment source identification is crucial for effective management of water quality, aquatic habitat, and sediment loads in a watershed. This study explored topographic openness (TO) derived from 1-m lidar for its ability to predict incision in headwater streams and to remotely detect changes in incision over time. Field surveys were conducted in one forested and two recently urbanized headwater watersheds in the Maryland Piedmont physiographic province, USA to characterize the level of stream channel incision (none, moderate, or severe) in the main stem of each watershed. Predictions of the severity of stream channel incision derived from TO were compared against the field surveys. Channel incision was detected with an overall accuracy of 67 %, with best performance in reaches with either severe or no incision (79–86 % accuracy). The method was also applied to repeat lidar collected over the same area to model the extent of channel incision in 2002 before urban development began and in 2008 and 2013 during active construction in the urban watersheds. Results showed increasing incision over time in all three watersheds, with similar patterns in the forested and urban watersheds. This new method of remotely measuring channel incision can be used to identify potential sediment sources across a watershed, enhance water and habitat quality predictions, and detect changes over time where multiple years of overlapping lidar are available.
Study Area
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Remotely mapping gullying and incision in Maryland Piedmont headwater streams using repeat airborne lidar |
| Series title | Geomorphology |
| DOI | 10.1016/j.geomorph.2024.109205 |
| Volume | 455 |
| Year Published | 2024 |
| Language | English |
| Publisher | Elsevier |
| Contributing office(s) | Eastern Geographic Science Center, Utah Water Science Center, Maryland-Delaware-District of Columbia Water Science Center |
| Description | 109205, 13 p. |
| Country | United States |
| State | Maryland |
| Google Analytic Metrics | Metrics page |