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Bottom friction is an important process in coastal and estuarine environments because it can reduce wave heights and moderate tidal currents. When modeling large systems with spatially varying hydraulic properties, bottom friction values are commonly derived from land use classification products. However, estimation of bottom friction for vegetated areas can be more challenging due to the complicated and time-varying geometry of the roughness elements. This is particularly true of flexible, buoyant submerged aquatic vegetation (SAV) species, such as seagrasses and kelps, that deform under waves and currents. In this study we incorporate a dynamic friction model that includes the temporal variation in SAV drag forces into a depth-integrated coupled circulation-wave model. In vegetated areas, the bottom friction is continuously updated based on plant geometry, water depth, and combined wave-current velocities. Taking a multi-scale approach, we use the model to investigate the impact of SAV dynamics on both the localized and the integrated bay-wide hydrodynamics of a riverine and tidally influenced estuary. First, we investigate SAV modification of velocity fields and its implications for sediment transport and circulation pathways. Then, we show how SAV can modify tidal behavior throughout the estuary. [ABSTRACT FROM AUTHOR]

We present a simple method that allows snow depth measurements to be converted to snow water equivalent (SWE) estimates. These estimates are useful to individuals interested in water resources, ecological function, and avalanche forecasting. They can also be assimilated into models to help improve predictions of total water volumes over large regions. The conversion of depth to SWE is particularly valuable since snow depth measurements are far more numerous than costlier and more complex SWE measurements. Our model regresses SWE against snow depth (h), day of water year (DOY) and climatological (30-year normal) values for winter (December, January, February) precipitation (PPTWT), and the difference (TD) between mean temperature of the warmest month and mean temperature of the coldest month, producing a power-law relationship. Relying on climatological normals rather than weather data for a given year allows our model to be applied at measurement sites lacking a weather station. Separate equations are obtained for the accumulation and the ablation phases of the snowpack. The model is validated against a large database of snow pillow measurements and yields a bias in SWE of less than 2 mm and a root-mean-squared error (RMSE) in SWE of less than 60 mm. The model is additionally validated against two completely independent sets of data: one from western North America and one from the northeastern United States. Finally, the results are compared with three other models for bulk density that have varying degrees of complexity and that were built in multiple geographic regions. The results show that the model described in this paper has the best performance for the validation data sets. [ABSTRACT FROM AUTHOR]

Extreme water levels generating flooding in estuarine and coastal environments are often driven by compound events, where many individual processes such as waves, storm surge, streamflow, and tides coincide. Despite this, extreme water levels are typically modeled in isolated open-coast or estuarine environments, potentially mischaracterizing the true risk of flooding facing coastal communities. This paper explores the variability of extreme water levels near the tribal community of La Push, within the Quileute Indian Reservation on the Washington state coast, where a river signal is apparent in tide gauge measurements during high-discharge events. To estimate the influence of multiple forcings on high water levels a hybrid modeling framework is developed, where probabilistic simulations of joint still water level and river discharge occurrences are merged with a hydraulic model that simulates along-river water levels. This methodology produces along-river water levels from thousands of combinations of events not necessarily captured in the observational records. We show that the 100-year still water level event and the 100-year discharge event do not always produce the 100-year along-river water level. Furthermore, along specific sections of river, both still water level and discharge are necessary for producing the 100-year along-river water level. Understanding the relative forcing driving extreme water levels along an ocean-to-river gradient will help communities within inlets better understand their risk to the compounding impacts of various environmental forcing, which is important for increasing their resilience to future flooding events. [ABSTRACT FROM AUTHOR]