Abstract
The unit sediment graph approach, analogous to the unit hydrograph method, was rarely applied in the past 50 years, presumably due to limitations from scaling the sediment kernel. We hypothesised that spatially explicit sediment connectivity modelling might be combined with unit sediment graph theory to estimate sediment source zones and time of mobilisation across the watershed and estimate sediment flux for hydrologic events. We formulated the model using the probability of sediment connectivity with log-normal parameterisation of the 1-h unit sediment graph. Simulations were carried out for a sediment transport application in a third-order watershed in Kentucky, USA, using a two-stage calibration procedure assisted by a high-performance computing cluster. Results showed sufficient evidence for the efficacy of the approach, including Nash-Sutcliffe Efficiency as high as 0.87 and 0.84 in Stages 1 and 2, respectively, of calibration and 0.88 for model validation. Results of the probability of connectivity showed variability across and within transport events, and 7.5% connectivity for the high flow isolated event. The log-normal distribution effectively estimated the rising limb and the falling limb of the sediment graphs. Post-processing of modelling results showed the importance of the probability of sediment connectivity, as simulations omitting it produced inadequate results. Post-processing with a shallow artificial neural network model showed that both sediment connectivity and surface runoff control sediment yield at the event scale. Results showed the ability of the hourly time step to capture the onset of sediment connectivity and peak connectivity across the ephemeral network.
| Original language | English |
|---|---|
| Article number | e70198 |
| Journal | Hydrological Processes |
| Volume | 39 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 2025 |
Bibliographical note
Publisher Copyright:© 2025 John Wiley & Sons Ltd.
Funding
We thank the University of Kentucky Center for Computational Sciences and Information Technology Services Research Computing for their support and use of the Lipscomb Compute Cluster and associated research computing resources. We thank two anonymous reviewers for comments that improved the quality of this paper. We thank one of the reviewers for their comments regarding coupling functional and structural connectivity that were reflected in the revised paper. We gratefully acknowledge the financial support of this research from the Kentucky Senate Bill 271B Water Quality programme and National Science Foundation Awards #1933779 and #2418793. Funding: This work was supported by Kentucky State Senate National Science Foundation, USA. We thank the University of Kentucky Center for Computational Sciences and Information Technology Services Research Computing for their support and use of the Lipscomb Compute Cluster and associated research computing resources. We thank two anonymous reviewers for comments that improved the quality of this paper. We thank one of the reviewers for their comments regarding coupling functional and structural connectivity that were reflected in the revised paper. We gratefully acknowledge the financial support of this research from the Kentucky Senate Bill 271B Water Quality programme and National Science Foundation Awards #1933779 and #2418793.
| Funders | Funder number |
|---|---|
| National Science Foundation Arctic Social Science Program | 2418793, 1933779 |
| Kentucky Transportation Center, University of Kentucky |
Keywords
- connectivity
- fluvial erosion
- unit sediment graph
ASJC Scopus subject areas
- Water Science and Technology