A Channel Network Model for Sediment Dynamics Over Watershed Management Time Scales

Abstract

A mountain watershed network model is presented for use in decadal to centurial estimation of source-to-sink sediment dynamics. The model requires limited input parameters and can be effectively applied over spatial scales relevant to management of reservoirs, lakes, streams, and watersheds (1-100 km 2 ). The model operates over a connected stream network of Strahler-ordered segments. The model is driven by streamflow from a physically based hydrology model and hillslope sediment supply from a stochastic mass wasting algorithm. For each daily time step, segment-scale sediment mass balance is computed using bedload and suspended load transport equations. Sediment transport is partitioned between grain size fractions for bedload as gravel and sand, and for suspended load as sand and mud. Bedload and suspended load can deposit and re-entrain at each segment. We demonstrated the model in the Elwha River Basin, upstream of the former Glines Canyon dam, over the dam's historic 84-year lifespan. The model predicted the lifetime reservoir sedimentation volume within the uncertainty range of the measured volume (13.7-18.5 million m 3 ) for 25 of 28 model instances. Gravel, sand, and mud fraction volumes were predicted within measurement uncertainty ranges for 18 model instances. The network model improved the prediction of sediment yields compared to at-a-station sediment transport capacity relations. The network model also provided spatially and temporally distributed information that allowed for inquiry and understanding of the physical system beyond the sediment yields at the outlet. This work advances cross-disciplinary and application-oriented watershed sediment yield modeling approaches.Plain Language Summary Predicting sediment processes in river systems is challenging. Most methods for doing so in water resource system planning and management are lacking in scientific advancement. However, approaches used in academic research for understanding river sediment processes are often not well suited for practical applications. Academic approaches are often siloed between disciplines and do not holistically address real-world needs. In this study, we developed a new computer model for predicting sediment processes in river systems. We combined academic research approaches from various disciplines to address a practical need of predicting reservoir sediment accumulation in mountainous regions. We demonstrated the model in the Elwha River Basin, upstream of the former Glines Canyon dam, over the dam's historic 84-year lifespan. Our model predicted the volume of sediment that accumulated behind the dam over its lifetime. We also predicted the reservoir sediment accumulation using a traditional approach called sediment rating curves to compare to our model performances. We demonstrated that our model predicted the reservoir sediment accumulation better than the rating curves did, and our model also provided more information about the broader river system than the curves. Overall, our work advances cross-disciplinary and appl...

A Dynamic, Network Scale Sediment (Dis)Connectivity Model to Reconstruct Historical Sediment Transfer and River Reach Sediment Budgets

“…Future studies could differentiate between deposition in the channel and on floodplains, by modeling two different sediment layer structures for each reach that store sediment independently, while interacting and exchanging materials to reproduce channel‐floodplain interactions (Beveridge et al., 2020; Gilbert & Wilcox, 2020). The representation of sediment deposition shown in Figure 2 assumes no vertical mixing is possible to guarantee proper provenance tracing.…”

Sediment transport at the network scale and its link to channel morphology in the braided Vjosa River system

“…In such circumstances, the process of initializing models such as CASCADE can be improved by measuring source‐area grain sizes, and, if possible, source‐area sediment supply (Tangi et al, 2019). In addition, hillslope sediment supply can be derived from stochastic models of mass wasting (Beveridge et al, 2020), and river bed surficial grain size availability along river networks can be inferred from empirical relationships based on slope, drainage area, and river morphology (Snelder et al, 2011). For these reasons, even in contexts where morphodynamic equilibrium cannot be assumed, models such as CASCADE, when integrated with a sensitivity analysis, allow us to test multiple hypotheses on sediment supply and transport capacity, and to select the subset of model results which best reproduce the observed data.…”

“…As presently structured, CASCADE does not model the direct influence of hillslope processes on sediment connectivity. For this reason, the integration of sediment connectivity indices with models focusing on geomorphic processes occurring on hillslopes and floodplains (Cavalli et al, 2013; Heckmann et al, 2014) represent an important next step for generating information on sediment supply from sources outside the channel (Beveridge et al, 2020; Gilbert & Wilcox, 2020). Further developments may also better integrate channel–floodplain interactions including river lateral mobility and bank erosion modeling (Gilbert & Wilcox, 2020; Lauer et al, 2016).…”

“…The availability of this new information, along with advances in data processing capabilities, has led to the development of a new generation of sediment connectivity models that are capable of simulating sediment transfer at drainage basin scales (Beveridge et al, 2020; Czuba & Foufoula‐Georgiou, 2014; Gilbert & Wilcox, 2020; Schmitt et al, 2016). These new sediment connectivity models require specification of not only the boundary conditions, and input information on hydrology, slope and channel geometry, but also formulation of computational routines for estimating source area sediment supply (both quantity and grain size).…”

“…Indeed, sediment transport formulae and consequent bedload estimations have been developed more or less independently from the interpretation of channel patterns and processes (Church, 2006; Church & Ferguson, 2015). Notably, amongst the various studies of network‐scale sediment connectivity (Beveridge et al, 2020; Czuba, 2018; Gilbert & Wilcox, 2020; Schmitt et al, 2016), none have investigated links between network sediment connectivity and reach‐scale transitions in channel patterns. This limitation presents an opportunity to use sediment connectivity models to identify thresholds in water and sediment discharge which define a transformation in channel pattern.…”