COMPARISON OF 1-D AND 2-D MODELING OF OVERLAND RUNOFF AND SEDIMENT TRANSPORT1

ABSTRACT: One-dimensional and two-dimensional modeling approaches were compared for their abilities in predicting overland runoff and sediment transport. Both 1-D and 2-D models were developed to test the hypothesis that the 2-D modeling approach could improve the model predictions over the 1-P approach, based on the same mathematical representations of physical processes for runoff and sediment transport. The models developed in this study were applied to overland areas with cross slopes. A hypothetical case and an experimental study reported by Storm (1991) were used. Based on the simulation results from the selected hypothetical case and experimental study, the 2-D model provided better representation of spatial distribution of flow depths and sediment concentrations than the 1-D model. However, no significant differences in predictions of total runoff volume and sediment yield at the outlet area were found between the 1-D and 2-D models.     

Comparison of Unsteady and Quasi‐Unsteady Flow Models in Simulating Sediment Transport in an Ephemeral Arizona Stream1

Hummel, Ryan, Jennifer G. Duan, and Shiyan Zhang, 2012. Comparison of Unsteady and Quasi‐Unsteady Flow Models in Simulating Sediment Transport in an Ephemeral Arizona Stream. Journal of the American Water Resources Association (JAWRA) 48(5): 987‐998. DOI: 10.1111/j.1752‐1688.2012.00663.x Abstract: Hydrodynamic and sediment transport models are useful engineering tools for predicting unsteady flood flow and sediment transport. Many models such as HEC‐RAS, HEC‐6, and IALLUVIAL apply quasi‐unsteady flow model, whereas others apply the unsteady flow model. It remains unknown if a quasi‐unsteady flow model is sufficiently accurate for simulating sediment transport in rapidly varied unsteady flood events, especially in ephemeral rivers in arid and semiarid regions. This study compared the quasi‐unsteady HEC‐RAS 4.1 model with one‐dimensional (1D) Finite Volume Method (FVM) based model in simulating flood flow and sediment transport in the Pantano Wash, a dryland river in the state of Arizona. The objective is to determine which sediment transport method is appropriate in predicting bed elevation changes in an ephemeral stream, Pantano Wash, and if an unsteady model is more accurate than a quasi‐unsteady flow model in predicting sediment transport. Results showed that the quasi‐unsteady HEC‐RAS model and the 1D FVM yielded similar results of bed degradation and aggradation for this dryland stream, although the FVM model predicted better flood hydrographs. Among the seven sediment transport formulas embedded in HEC‐RAS, Yang’s and Engelund‐Hansen’s equations gave the best matches with the field measurements for this particular case study.     

Comparison of Morphodynamic Models for the Lower Yellow River1

Xia, Junqiang, Zhengbing Wang, Yanping Wang, and Xin Yu, 2012. Comparison of Morphodynamic Models for the Lower Yellow River. Journal of the American Water Resources Association (JAWRA) 1‐18. DOI: 10.1111/jawr.12002 Abstract: Significant channel adjustments often occur during flood seasons in the Lower Yellow River (LYR), and it is a challenging work to accurately simulate the morphodynamic processes in the LYR using numerical models. A comparison of two morphodynamic models (Delft3D and 2DLLCDM) for the LYR is presented herein to identify critical improvements for these models. The concepts of these models are first compared with each other. The models were then used to simulate the processes of flood routing, sediment transport, and morphological changes occurring in a braided reach of the LYR. The differences were investigated between the simulated results from these models and corresponding field measurements, and the results indicate that: (1) the hydrodynamic processes calculated by both models agree closely with the measurements if an appropriate Manning’s roughness coefficient is used; (2) the concentrations of suspended load at the downstream boundary calculated by the models agree reasonably with the observed data; and (3) the predicted cross‐sectional profiles obtained from these models do not correspond well with the measurements. Based on these findings, the weak aspects of the models are clarified, and three critical improvements are recommended, including: (1) the development of roughness predictor; (2) the refinement of graded sediment transport capacity formulation; and (3) the consideration of bank erosion module. These improvements need to be implemented in the future.     

Release,Dispersion, and Resuspension of Escherichia coli From Direct Fecal Deposits Under Controlled Flows1

Abstract: Water‐quality standards have been placed on fecal indicator organisms such as Escherichia coli in an attempt to limit the concentrations in water bodies. Cattle can be a significant source of bacteria to water systems, particularly when they are allowed direct access to streams. A flume study was conducted to quantify the effect and understand the transport of E. coli from directly deposited cattle manure. Five steady‐state flows, ranging from 0.00683 to 0.0176 m³/s, were studied and loads from a single cowpie exceeded the U.S. Environmental Protection Agency’s recommended water‐quality standards (235 CFU/100 ml) at each flow over the hour study period. Average E. coli concentrations ranged from 10² to 10⁵ CFU/100 ml over the hour sampling period for all flows. High spatial variations in E. coli concentrations were often seen at each sampling time, with higher concentrations typically at the bottom of the flume. E. coli resuspension was initially greater at 0.5 min after deposition, for the lowest flow (10⁵ CFU/m²/s); however, resuspension rates became similar over time, on the order of 10³ CFU/m²/s. This study demonstrates that the concentrations of E. coli can vary over the water column, and therefore grab samples may inaccurately measure bacteria concentrations and loads in streams. In addition, resuspension rates were often high, so the incorporation of this process into water‐quality models is important for bacteria prediction.