Alfred J. Kalyanapu

Evaluation of Changing Characteristics of Temporal Rainfall Distribution within 24-Hour Duration Storms and Their Influences on Peak Discharges: Case Study of Asheville, North Carolina

AbstractDesign storms are used for the sizing of urban drainage systems and for delineating floodplains. Recorded rainfall extremes are commonly used to develop design storms with the assumption of...

A probabilistic framework for comparison of dam breach parameters and outflow hydrograph generated by different empirical prediction methods

This study presents a probabilistic framework to simulate dam breach and evaluates the impact of using four empirical dam breach prediction methods on breach parameters (i.e., geometry and timing) and outflow hydrograph attributes (i.e., time to peak, hydrograph duration and peak). The methods that are assessed here include MacDonald and Langridge-Monopolis (1984), Von Thun and Gillette (1990), Froehlich (1995), 2008). Mean values and percentiles of breach parameters and outflow hydrograph attributes are compared for hypothetical overtopping failure of Burnett Dam in the state of North Carolina, USA. Furthermore, utilizing the probabilistic framework, the least and most uncertain methods alongside those giving the most critical value are identified for these parameters. The multivariate analysis also indicates that lone use of breach parameters is not necessarily sufficient to characterize outflow hydrograph attributes. However, timing characteristic of the breach is generally a more important driver than its geometric features. A probabilistic dam breach model for overtopping is presented in this study.Uncertainty of breach parameters and outflow hydrograph is estimated.Four empirical dam breach prediction methods by using this model are compared in this study.

Investigation of the Impact of Streamflow Temporal Variation on Dam Overtopping Risk: Case Study of a High-Hazard Dam

Overtopping is the leading reason of dam failure worldwide. Dam overtopping can be due to various reasons such as large inflow and extreme rainfall. Recent climate change has intensified the risk of extreme hydrologic events such as floods, which can potentially increase the dam overtopping risk. Thus, it is essential to analyze how the overtopping risk changes over the years. In the US, there are up to 15000 high-hazard dams, and this number is on the rise due to the population growth and urbanization. While there are up to 15000 high-hazard dams in the US, the state of North Carolina ranks second among the US states. Burnett Dam is one of these high-hazard dams, which is located in the upstream of the city of Asheville, in the state of North Carolina. An inspection report on 1980, showed that the dam cannot pass the Probable Maximum Flood (PMF) without overtopping due to inadequate spillway capacity. At that time, maximum flood of 40 cms at dam location was reported, which belonged to the 1977 flood event. However, analysis of the measured annual peak streamflow in the upstream from 1989 to 2013 (time span with available observed data), shows that a greater flood magnitude than 1977 flood event occurred in more than one-third of the years. The increase is significant in most of the years, in which peak streamflow of 228.7 cms (nearly six times larger than 1977 event) can be observed. Considering the substantial increase in the streamflow and the inadequacy of the dam spillway, this study investigates the impact of streamflow temporal variation on annual overtopping risk of Burnett Dam using a risk and reliability analysis approach. Overtopping risk is defined as the probability of reservoir inflow exceeding the spillway capacity. A performance function is used to determine the annual overtopping risk, which has two primary inputs: 1) dam resistance: total spillway capacity; and 2) maximum load: highest inflow discharge. Highest inflow discharge is determined by analysis of the peak streamflow records of a gaging station upstream of the dam. At each year, the highest peak streamflow is routed through the dam upstream channel using a calibrated hydrologic model. Taking the routed inflow, the overtopping risk is determined in each year. Temporal change in the overtopping risk is finally investigated in 1989-2013 period using Mann-Kendall Test. The results indicate that: 1) annual overtopping risk has an increasing trend in the period of interest; 2) comparing to the 1977 flood event, the annual overtopping risk has been 1050 World Environmental and Water Resources Congress 2015: Floods, Droughts, and Ecosystems

A probabilistic framework to evaluate the uncertainty of design hydrograph: case study of Swannanoa River Watershed

ABSTRACT This study presents a probabilistic framework to evaluate the impact of uncertainty of design rainfall depth and temporal pattern as well as antecedent moisture condition (AMC) on design hydrograph attributes – peak, time to peak, duration and volume, as well as falling and rising limb slopes – using an event-based hydrological model in the Swannanoa River watershed in North Carolina, USA. Of the six hydrograph attributes, falling limb slope is the most sensitive to the aforementioned uncertainties, while duration is the least sensitive. In general, the uncertainty of hydrograph attributes decreases in higher recurrence intervals. Our multivariate analysis revealed that in most of the return periods, AMC is the most important driver for peak, duration and volume, while time to peak and falling limb slope are most influenced by rainfall pattern. In higher return periods, the importance of rainfall depth and pattern increases, while the importance of AMC decreases.

A probabilistic framework for floodplain mapping using hydrological modeling and unsteady hydraulic modeling

ABSTRACT Prediction of design hydrographs is key in floodplain mapping using hydraulic models, which are either steady state or unsteady. The former, which require only an input peak, substantially overestimate the volume of water entering the floodplain compared to the more realistic dynamic case simulated by the unsteady models that require the full hydrograph. Past efforts to account for the uncertainty of boundary conditions using unsteady hydraulic modeling have been based largely on a joint flood frequency–shape analysis, with only a very limited number of studies using hydrological modeling to produce the design hydrographs. This study therefore presents a generic probabilistic framework that couples a hydrological model with an unsteady hydraulic model to estimate the uncertainty of flood characteristics. The framework is demonstrated on the Swannanoa River watershed in North Carolina, USA. Given its flexibility, the framework can be applied to study other sources of uncertainty in other hydrological models and watersheds.

Benchmark Exercise for Comparing the Computational Performance of Two-Dimensional Flood Models in CPU, Multi-CPU, and GPU Frameworks

The objective of this study is to investigate the computational performance and accuracy of three different implementations of a 2D flood model: sequential (Flood2D-CPP), parallel (Flood2DPTH & Flood2D-OMP), and General Purpose Graphics Processing Unit (Flood2D-GPU). The model is based on shallow water equations (SWE) and uses an upwind-finite difference numerical formulation to simulate flood events. Two parallel versions of the model are implemented, one based on pthread and the other based on OpenMP. The GPU version has been developed using NVIDIAs CUDA library. For this study, these implementations are being applied to simulate a dam break event at the Taum Sauk pump-storage hydro-electric power plant in Missouri, which occurred on December 14, 2005. The GPU implementation provided a significant speed up, up to two orders of magnitude compared to the CPU model. As predicted, the sequential model (Flood2D-CPP) reported with the lowest performance compared to the parallel and GPGPU versions, because it would take longer for a single CPU thread to perform all the calculations as opposed to multiple threads or through multiple GPU cores . Results indicate that the computational performance of both Flood2D-PTH and Flood2D-OMP improves with increase in the number CPU threads. The speedups of Flood2D-PTH and Flood2D-OMP are maximized at 8 threads, but much less than the theoretical maximum. In general, even though Flood2D-GPU had significance performance the comparison indicated the potential for optimizing Flood2D-PTH and Flood2D-OMP models to simulate larger computational domains.