Meander chute cutoffs are a common and geomorphically important feature of meandering rivers. They exhibit complex dynamics and distinctive morphologic features. To date, however, the geomorphic processes governing the evolution and formation of these features are poorly understood due to limited knowledge of cutoff hydrodynamics. This paper investigates three-dimensional mean flow structure, turbulent flow structure, and bed shear stress distribution from high-resolution flow velocity data in a fixed-bed, sediment-free physical model. The results show that 1) the chute channel conveys around 1.4 times the unit-width flow discharge as the cutoff bend; 2) mean flow structure is highly three-dimensional, with strong convective acceleration throughout the bends and pronounced flow separation zones in both the chute channel and the cutoff bend; 3) turbulent kinetic energy is intense at shear layers bounding the flow separation zones at several locations in the channel; and 4) bed shear stress is elevated due to strong turbulence in the chute channel and is low in the cutoff bend. The unique hydrodynamics of meander chute cutoffs explain their distinctive morphologic behaviors, including the rapid widening and deepening of chute channels and locations of bars and pools. Moreover, this paper quantitatively compares the secondary flow structure before and after the cutoff, showing that cross-sectional redistribution of streamwise momentum by secondary flow remains largely unchanged in the presence of the chute cutoff. This provides support to the use of current 2D depth-averaged hydrodynamic models for chute cutoffs with secondary flow parameters calibrated in single-channeled meanders.

This paper presents a novel hybrid deterministic-stochastic river morphodynamics numerical modeling approach that integrates a two-dimensional (2D) hydrodynamic model (deterministic) with a bed morphodynamic model (deterministic) and a bank erosion model (Markovian stochastic). The model solves the 2D Shallow Water Equations and the standard k-epsilon turbulence model. Bedload transport is estimated using the Meyer-Peter and Muller formula, and bed evolution is solved using the Exner Equation. The Markovian stochastic bank erosion model uses a new method to evaluate bank erosion risk. The approach was applied to a meander bend cutoff event in the Maiqu River on the Tibetan Plateau. Sixteen different bank-material critical shear stress cases were considered, representing highly erodible banks to resistant banks. Ten statistical realizations were performed for each case with different bank-material erodibility to obtain ensemble-averaged results. Flow field and bed evolution in the cutoff channel suggest that the model can successfully simulate bank erosion processes during the cutoff channel evolution, and bank topographic irregularities are reasonably captured. A newly introduced calibration parameter, the ratio of mesh size to the coupling period between the bank erosion model and the hydrodynamic & morphodynamic model, is not as intuitive as the erosion resistance calibration parameters used by the traditional bank erosion model. The proposed approach necessitates estimating the size of a typical slump failure, or 10-30% of the cutbank height, to set the size of the computational mesh.

Existing models for estimating hyporheic oxygen mass transfer often require numerous parameters related to flow, bed, and channel characteristics, which are frequently unavailable. We performed a meta-analysis on existing dataset, enhanced with high Reynolds number cases from a validated Computational Fluid Dynamics model, to identify key parameters influencing effective diffusivity at the sediment water interface. We applied multiple linear regression to generate empirical models for predicting eddy diffusivity. To simplify this, we developed two single-parameter models using either a roughness or permeability-based Reynolds number. These models were validated against existing models and literature data. The model using roughness Reynolds number is easy to use and can provide an estimate of the oxygen transfer coefficient, particularly in scenarios where detailed bed characteristics such as permeability might not be readily available.

Meandering channels display complex planform configurations with upstream- and downstream- skewed bends. Bend orientation is linked to near-field hydrodynamics, bed morphodynamic regime, bank characteristics, riparian vegetation, and geological environment, which are the modulating factors that act specially in high-amplitude and high-sinuosity conditions. Based on the interaction between hydrodynamics and morphodynamics, previous studies have suggested that sub- (β < βR) and super-resonant (β > βR) morphodynamic regimes (where β is the half width-to-depth ratio of the channel, and βR is the resonance condition) may trigger a particular bend orientation (upstream- and downstream-skewed, respectively). However, natural rivers exhibit both US-skewed and DS-skewed bend patterns along the same reach, independently of the morphodynamic regime. Little is known about the hydrogeomorphology (forced and free morphodynamic patterns) under these bend orientations. Herein, using the asymmetric Kinoshita laboratory channel, experiments under sub- and super-resonant conditions (with presence or absence of free bars) for upstream-and downstream-skewed conditions are performed. Additional, detailed field measurements at US-skewed and DS-skewed bends of different skewness along the Tigre River in Peru are presented. Conditions at field scale at high-sinuosity and high-amplitude bends filter out the influence of the morphodynamic regime, where nonlinear processes (e.g. width variation) directly the development of the three-dimensional flow structure, then to the erosional and depositional patterns, and then to the lateral migration patterns.

Localized and severe storms can cause citywide flooding, leading drainage systems to surcharge and overflow to nearby water courses. Urban catchments feature high degrees of imperviousness and heterogeneity, often resulting in highly nonlinear hydrologic responses with shorter time of concentration, lag times, and sharper peak flows. Additionally, due to population and economic growth, urban drainage systems have attempted to evolve to more efficiently drain surface waters and reduce vulnerabilities. A critical outcome of this evolution is the need for finer spatio-temporal resolution rainfall measurements and hydrological modeling. As the major driving mechanism, the spatio-temporal variability in rainfall is acknowledged as a key source of uncertainty for urban hydrological modeling. The objective of this research is to revisit the impact of the temporal and spatial resolution of rainfall measurements on urban hydrological applications. We first provide a quantitative analysis of the spatiotemporal structure and variability of rainfall using both a 9-member hourly rain gauge network spaced ~10 km apart and a single WSR-88D dual-polarimetric weather radar with precipitation resolved every 5 minutes at ~500 m. Precipitation data from each observing system extracted at different time steps is aggregated within urban catchments and compared for three typical intense storms over a set of urban catchments located in Chicago Metropolitan area. Then the rain-runoff dynamics for 9 geographically-diverse (relative to the underneath sewer system) and differently-sized catchments are examined utilizing MetroFlow – a coupled hydrologic and hydraulic modeling system. Finally, city-wide flooding risks are simulated by routing the predicted surface runoff through the as-built sewer system. Additional mitigating storage capacity is also considered by numerical modeling the deep tunnel and reservoir in construction. The sensitivity of urban flood variables (i.e., mean and peak depth as well as duration) to rainfall spatiotemporal resolution is analyzed. Our results complement and advance the limited literature attempting to resolve the ideal resolution of rainfall data relevant for urban hydrology and stormwater management.

Localized and severe storms can cause citywide flooding, leading drainage systems to surcharge and overflow to nearby water courses. Urban catchments feature high degrees of imperviousness and heterogeneity, often resulting in highly nonlinear hydrologic responses with shorter time of concentration, lag times, and sharper peak flows. Additionally, due to population and economic growth, urban drainage systems have attempted to evolve to more efficiently drain surface waters and reduce vulnerabilities. A critical outcome of this evolution is the need for finer spatio-temporal resolution rainfall measurements and hydrological modeling. As the major driving mechanism, the spatio-temporal variability in rainfall is acknowledged as a key source of uncertainty for urban hydrological modeling. The objective of this research is to revisit the impact of the temporal and spatial resolution of rainfall measurements on urban hydrological applications. We first provide a quantitative analysis of the spatiotemporal structure and variability of rainfall using both a 9-member hourly rain gauge network spaced ~10 km apart and a single WSR-88D dual-polarimetric weather radar with precipitation resolved every 5 minutes at ~500 m. Precipitation data from each observing system extracted at different time steps is aggregated within urban catchments and compared for three typical intense storms over a set of urban catchments located in Chicago Metropolitan area. Then the rain-runoff dynamics for 9 geographically-diverse (relative to the underneath sewer system) and differently-sized catchments are examined utilizing MetroFlow – a coupled hydrologic and hydraulic modeling system. Finally, city-wide flooding risks are simulated by routing the predicted surface runoff through the as-built sewer system. Additional mitigating storage capacity is also considered by numerical modeling the deep tunnel and reservoir in construction. The sensitivity of urban flood variables (i.e., mean and peak depth as well as duration) to rainfall spatio-temporal resolution is analyzed. Our results complement and advance the limited literature attempting to resolve the ideal resolution of rainfall data relevant for urban hydrology and stormwater management.

Assessing the extent and impact of past extreme weather events within cities can help identify vulnerabilities, map potential solutions, and prevent future calamities. Modern urban environments are particularly vulnerable to hydrological extremes due to high population densities, expansive impermeable surfaces, more intense precipitation extremes, and infrastructure designed for a now obsolete climate. Intense rainfall in urban environments can lead to impacts ranging from nuisance flooding to overloading of sewage and drainage systems to neighborhood inundation. In the flood-prone city of Chicago, storm waters are contained in a network of tunnels and reservoirs until treated and released to the waterways. Management decisions for a 600 km^2 metropolitan area are made based on precipitation data collected at just 9 gauge sites. Here, we combine high-resolution radar-derived precipitation data with urban-scale hydrological models to improve our understanding of water flow, advance stormwater management practices, and potentially mitigate flood risks. Proximity of the NEXRAD system to Chicago allows us to improve the spatial resolution of rainfall estimates to 500m, which will be used to produce neighborhood-scale rainfall hindcasts. Different dual-polarimetric radar-rainfall retrieval methods, e.g., rainfall from reflectivity, attenuation, specific differential phase, and differential reflectivity will be examined to determine the most accurate representation of rainfall estimates. This suite of rainfall estimates will be used to derive catchment-level precipitation, and serve as input in a coupled hydrological-hydraulic MetroFlow model. To verify the utility of our radar precipitation data, we examine an April 2013 event that delivered a record-breaking 7 inches of rain in 2 days in some areas. We compare our highly-resolved precipitation-driven hydrological model predictions with those made using the 9 gauge stations. This research is conducted under the premise that hydrological extremes are expected to be exacerbated by climate change. Understanding drivers of urban flooding using high-resolution precipitation data and models can be used to improve resiliency-focused infrastructure design in Chicago neighborhoods.

A substantial body of research has addressed the equilibrium cross-sectional geometry of straight noncohesive channels, along with bends having fixed outer banks. However, development of a characteristic cross-section during active migration has been confounded by inaccurate treatment of noncohesive bank erosion processes. This analysis characterizes a steady-state migrating cross-section and the associated migration rate for the highly conceptualized case of an infinite bend of constant centerline radius with noncohesive lower banks consisting of uniform-sized grains mobilized as bedload. Analytical, numerical, and field analyses are presented to rationally constrain the geometry and obtain a physically based migration rate equation dependent on the following dimensionless groupings: excess Shields stress, flow depth to radius of curvature ratio, and noncohesive bank thickness to grain size ratio. Migration rate is shown to be dictated by transverse sediment flux at the thalweg due to secondary flow, not bank slope as in previous formulations developed from similar principles. Simple outward translation can result without the characteristic cyclic process observed in cohesive banks (fluvial erosion, oversteepening, and mass failure). This suggests that the linear excess shear stress formulation that applies to cohesive soils misrepresents noncohesive bank erosion processes. A numerical model of cross-sectional evolution to steady-state migration is developed; when applied to the lower Mackinaw River in Illinois, it reveals that the river behaves as if the critical shear stress is considerably larger than that indicated by the grain size distribution. This conceptualized treatment is intended to provide a canonical basis of comparison for actual meander bend geometries.