The Deep Dirt Farm Institute (DDFI), founded and directed by Kate Tirion, comprises 34 acres with deep agricultural soils, bisected by an ephemeral stream/wildlife corridor. The farm lies within a folded topography of hills, small sheltered valleys & broad meadow. A deep gully has diverted flows and needs repair.
The Deep Dirt Farm Institute (DDFI), founded and directed by Kate Tirion, comprises 34 acres with deep agricultural soils, bisected by an ephemeral stream/wildlife corridor. The farm lies within a folded topography of hills, small sheltered valleys & broad meadow. A deep gully has diverted flows and needs repair.
Working with colleagues from Borderlands Restoration (BR) and Cuenca los Ojos (CLO), we asked the question: Can satellite imagery, watershed models, and in-situ data guide riparian gully restoration efforts? Specifically:
- How much sediment might we expect for any given rainstorm?
- What is the estimated peak flow at the outlet and potential restoration sites?
- How big do structures have to be?
- Where is the best place to put them
We used a Terrestrial Light Detection and Ranging (T-LiDAR) scanner to acquire high-speed laser measurements to produce highly accurate three-dimensional maps of the riparian environment. Using the high-resolution channel dimensions, we created a bare-earth DEM to acquire the cross-sections for each portion of the gully bed (Fig. 1).
- Ephemeral stream restoration with rock structures is monitored over 3-years using T-Lidar
- Terrestrial lidar change detection shows erosion and deposition through time
These data were used to design rock detention structures, with the expert opinion of Valer Austin (CLO) and David Seibert (BR). Check dams, gabion dams and one-rock dams were installed according to the dimensions of the spillway. We then used the data tas input to watershed and hydraulic models to simulate land surface changes and how structures impact geomorphology.
- Watershed model (KINEROS) predict peak flow discharges and are input to 2D flow models
- 2D hydraulic model (iRIC Nays2DH) predict changes in flow velocity, depth, and channel topography
Point of contact: Laura M. Norman, Ph.D. (520-670-5510)
Publications
Norman, L. M., Sankey, J. B., Dean, D., Caster, J., DeLong, S., DeLong, W., & Pelletier, J. D. (2017). Quantifying geomorphic change at ephemeral stream restoration sites using a coupled-model approach. Geomorphology, 283, 1–16. https://doi.org/10.1016/j.geomorph.2017.01.017
Petrakis, R. E., Norman, L. M., Vaughn, K., Pritzlaff, R., Weaver, C., Rader, A., & Pulliam, H. R. (2021a). Watershed Pairing of Sub-Basins within Smith Canyon Watershed using a Hierarchical Clustering Approach Vector Data Products and Scripts. U.S. Geological Survey Data Release. https://doi.org/10.5066/P97TQI85
Petrakis, R. E., Norman, L. M., Vaughn, K., Pritzlaff, R., Weaver, C., Rader, A., & Pulliam, H. R. (2021b). Hierarchical Clustering for Paired Watershed Experiments: Case Study in Southeastern Arizona, U.S.A. Water, 13(21), 2955. https://doi.org/10.3390/w13212955
- Overview
The Deep Dirt Farm Institute (DDFI), founded and directed by Kate Tirion, comprises 34 acres with deep agricultural soils, bisected by an ephemeral stream/wildlife corridor. The farm lies within a folded topography of hills, small sheltered valleys & broad meadow. A deep gully has diverted flows and needs repair.
The Deep Dirt Farm Institute (DDFI), founded and directed by Kate Tirion, comprises 34 acres with deep agricultural soils, bisected by an ephemeral stream/wildlife corridor. The farm lies within a folded topography of hills, small sheltered valleys & broad meadow. A deep gully has diverted flows and needs repair.
Working with colleagues from Borderlands Restoration (BR) and Cuenca los Ojos (CLO), we asked the question: Can satellite imagery, watershed models, and in-situ data guide riparian gully restoration efforts? Specifically:
- How much sediment might we expect for any given rainstorm?
- What is the estimated peak flow at the outlet and potential restoration sites?
- How big do structures have to be?
- Where is the best place to put them
We used a Terrestrial Light Detection and Ranging (T-LiDAR) scanner to acquire high-speed laser measurements to produce highly accurate three-dimensional maps of the riparian environment. Using the high-resolution channel dimensions, we created a bare-earth DEM to acquire the cross-sections for each portion of the gully bed (Fig. 1).
Sources/Usage: Public Domain.Figure 1. Joel Sankey, David Dean (BRD), Steve Delong (GD)(Public domain.) - Ephemeral stream restoration with rock structures is monitored over 3-years using T-Lidar
- Terrestrial lidar change detection shows erosion and deposition through time
These data were used to design rock detention structures, with the expert opinion of Valer Austin (CLO) and David Seibert (BR). Check dams, gabion dams and one-rock dams were installed according to the dimensions of the spillway. We then used the data tas input to watershed and hydraulic models to simulate land surface changes and how structures impact geomorphology.
- Watershed model (KINEROS) predict peak flow discharges and are input to 2D flow models
- 2D hydraulic model (iRIC Nays2DH) predict changes in flow velocity, depth, and channel topography
Sources/Usage: Public Domain.Maps depict depth of water (color range) and velocity (arrows) when greater than 1.5 m/s as arrows pointing in the direction of flow of Nays2DH predictions run on terrestrial lidar surveys in 2013 with simulated gabion and rock structures and 2015. Location of rock detention structures are shown by black circles. Arrows show where velocity is predicted to be > 1.0 m/s.
Sources/Usage: Public Domain.Figure 3. Maps depict BC erosion/deposition results from a.) the Nays2DH model iteration run on 2013 DEM with predicted elevation change overlain on the 2015 hillshade; b.) the raw unfiltered lidar 2013-2016 change detection results; and c.) the lidar 2013-2016 95% confidence threshold change detection results, where rock detention structures are portrayed inside black circles.
Point of contact: Laura M. Norman, Ph.D. (520-670-5510)
Publications
Norman, L. M., Sankey, J. B., Dean, D., Caster, J., DeLong, S., DeLong, W., & Pelletier, J. D. (2017). Quantifying geomorphic change at ephemeral stream restoration sites using a coupled-model approach. Geomorphology, 283, 1–16. https://doi.org/10.1016/j.geomorph.2017.01.017
Petrakis, R. E., Norman, L. M., Vaughn, K., Pritzlaff, R., Weaver, C., Rader, A., & Pulliam, H. R. (2021a). Watershed Pairing of Sub-Basins within Smith Canyon Watershed using a Hierarchical Clustering Approach Vector Data Products and Scripts. U.S. Geological Survey Data Release. https://doi.org/10.5066/P97TQI85
Petrakis, R. E., Norman, L. M., Vaughn, K., Pritzlaff, R., Weaver, C., Rader, A., & Pulliam, H. R. (2021b). Hierarchical Clustering for Paired Watershed Experiments: Case Study in Southeastern Arizona, U.S.A. Water, 13(21), 2955. https://doi.org/10.3390/w13212955