scholarly journals Levee Breaching: A New Extension to the LISFLOOD-FP Model

Water ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 942
Author(s):  
Iuliia Shustikova ◽  
Jeffrey C. Neal ◽  
Alessio Domeneghetti ◽  
Paul D. Bates ◽  
Sergiy Vorogushyn ◽  
...  
Keyword(s):  
Large Scale ◽  
Extreme Event ◽  
Flood Hazard ◽  
Maximum Flow ◽  
Small Scale ◽  
Economic Damage ◽  
Computationally Efficient ◽  
Po River ◽  
Efficient Manner ◽  
Critical Success

Levee failures due to floods often cause considerable economic damage and life losses in inundated dike-protected areas, and significantly change flood hazard upstream and downstream the breach location during the event. We present a new extension for the LISFLOOD-FP hydrodynamic model which allows levee breaching along embankments in fully two-dimensional (2D) mode. Our extension allows for breach simulations in 2D structured grid hydrodynamic models at different scales and for different hydraulic loads in a computationally efficient manner. A series of tests performed on synthetic and historic events of different scale and magnitude show that the breaching module is numerically stable and reliable. We simulated breaches on synthetic terrain using unsteady flow as an upstream boundary condition and compared the outcomes with an identical setup of a full-momentum 2D solver. The synthetic tests showed that differences in the maximum flow through the breach between the two models were less than 1%, while for a small-scale flood event on the Secchia River (Italy), it was underestimated by 7% compared to a reference study. A large scale extreme event simulation on the Po River (Italy) resulted in 83% accuracy (critical success index).

scholarly journals Large-scale stochastic flood hazard analysis applied to the Po River

2020 ◽  
Vol 104 (3) ◽  
pp. 2027-2049
Author(s):  
A. Curran ◽  
Karin De Bruijn ◽  
Alessio Domeneghetti ◽  
Federica Bianchi ◽  
M. Kok ◽  
...  
Keyword(s):  
Risk Management ◽  
Flood Risk ◽  
Large Scale ◽  
Extreme Event ◽  
Flood Hazard ◽  
Hazard Analysis ◽  
Flood Risk Management ◽  
Water Levels ◽  
Stochastic Methods ◽  
Po River

Abstract Reliable hazard analysis is crucial in the flood risk management of river basins. For the floodplains of large, developed rivers, flood hazard analysis often needs to account for the complex hydrology of multiple tributaries and the potential failure of dikes. Estimating this hazard using deterministic methods ignores two major aspects of large-scale risk analysis: the spatial–temporal variability of extreme events caused by tributaries, and the uncertainty of dike breach development. Innovative stochastic methods are here developed to account for these uncertainties and are applied to the Po River in Italy. The effects of using these stochastic methods are compared against deterministic equivalents, and the methods are combined to demonstrate applications for an overall stochastic hazard analysis. The results show these uncertainties can impact extreme event water levels by more than 2 m at certain channel locations, and also affect inundation and breaching patterns. The combined hazard analysis allows for probability distributions of flood hazard and dike failure to be developed, which can be used to assess future flood risk management measures.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2018 ◽  
Author(s):  
Feng Jie Zheng ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Pressure Fluctuation ◽  
Large Scale ◽  
Three Dimensional ◽  
Industrial Process ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial process. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operation such as rapid valve opening/closing. To investigate the pressure especially the pressure fluctuation in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled by a zero-dimensional virtual point, the pipe is modeled by a one-dimensional MOC, and the valve is modeled by a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted, in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve are obtained. The results show that the proposed model is in good agreement with the full CFD model in both large-scale and small-scale spaces. Moreover, the proposed model is more computationally efficient than the CFD model, which provides a feasibility in the analysis of complex RPV system within an affordable computational time.

scholarly journals A Multidimensional and Multiscale Model for Pressure Analysis in a Reservoir-Pipe-Valve System

2019 ◽  
Vol 141 (5) ◽  
Author(s):  
Feng Jie Zheng ◽  
Chao Yong Zong ◽  
William Dempster ◽  
Fu Zheng Qu ◽  
Xue Guan Song
Keyword(s):  
Large Scale ◽  
Pressure Fluctuations ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Computational Time ◽  
Small Scale ◽  
Dimensional System ◽  
Cfd Model ◽  
Computationally Efficient ◽  
Proposed Model

Reservoir-pipe-valve (RPV) systems are widely used in many industrial processes. The pressure in an RPV system plays an important role in the safe operation of the system, especially during the sudden operations such as rapid valve opening or closing. To investigate the pressure response, with particular interest in the pressure fluctuations in an RPV system, a multidimensional and multiscale model combining the method of characteristics (MOC) and computational fluid dynamics (CFD) method is proposed. In the model, the reservoir is modeled as a zero-dimensional virtual point, the pipe is modeled as a one-dimensional system using the MOC, and the valve is modeled using a three-dimensional CFD model. An interface model is used to connect the multidimensional and multiscale model. Based on the model, a transient simulation of the turbulent flow in an RPV system is conducted in which not only the pressure fluctuation in the pipe but also the detailed pressure distribution in the valve is obtained. The results show that the proposed model is in good agreement when compared with a high fidelity CFD model used to represent both large-scale and small-scale spaces. As expected, the proposed model is significantly more computationally efficient than the CFD model. This demonstrates the feasibility of analyzing complex RPV systems within an affordable computational time.

scholarly journals Filtering the Stochastic Skeleton Model for the Madden–Julian Oscillation

2016 ◽  
Vol 144 (2) ◽  
pp. 501-527 ◽  
Author(s):  
Nan Chen ◽  
Andrew J. Majda
Keyword(s):  
Large Scale ◽  
Warm Pool ◽  
Model Error ◽  
Small Scale ◽  
Fast Wave ◽  
Madden Julian Oscillation ◽  
Computationally Efficient ◽  
Skeleton Model ◽  
Spatially Extended ◽  
Novel Strategy

Abstract The filtering and prediction of the Madden–Julian oscillation (MJO) and relevant tropical waves is a contemporary issue with significant implications for extended range forecasting. This paper examines the process of filtering the stochastic skeleton model for the MJO with noisy partial observations. A nonlinear filter, which captures the inherent nonlinearity of the system, is developed and judicious model error is included. Despite its nonlinearity, the special structure of this filter allows closed analytical formulas for updating the posterior states and is thus computationally efficient. A novel strategy for adding nonlinear observational noise to the envelope of convective activity is designed to guarantee its nonnegative property. Systematic calibration based on a cheap single-column version of the stochastic skeleton model provides a practical guideline for choosing the parameters in the full spatially extended system. With these column-tuned parameters, the full filter has a high overall filtering skill for Rossby waves but fails to recover the small-scale fast-oscillating Kelvin and moisture modes. An effectively balanced reduced filter involving a simple fast-wave averaging strategy is then developed, which greatly improves the skill of filtering the moisture modes and other fast-oscillating modes and enhances the total computational efficiency. Both the full and the reduced filters succeed in filtering the MJO and other large-scale features with both homogeneous and warm pool cooling/moistening backgrounds. The large bias in filtering the solutions by running the perfect model with noisy forcing is due to the noise accumulation, which indicates the importance of including judicious model error in designing filters.

scholarly journals Impact Assessment of Orography on the Extreme Precipitation Event of July 2010 over Pakistan: A Numerical Study

2015 ◽  
Vol 2015 ◽  
pp. 1-20 ◽  
Author(s):  
Khan Muhammad Tahir ◽  
Yan Yin ◽  
Yong Wang ◽  
Zaheer A. Babar ◽  
Dong Yan
Keyword(s):  
Large Scale ◽  
Extreme Event ◽  
Numerical Study ◽  
Deep Convection ◽  
Temporal Distribution ◽  
Precipitation Event ◽  
Windward Side ◽  
Small Scale ◽  
Extreme Rainfall Event ◽  
Synoptic Conditions

The topography influences monsoon precipitation and gives rise to significant rainfall events in South Asia. The physical mechanism involved in such events includes mechanical uplifting, thermodynamics, small scale cloud processes, and large scale atmospheric circulations. The investigation into orographic precipitation is pursued by synoptic and model analysis. Deep convection occurs as warm moist airflow is channeling over steep mountains. WRF model coupled with Morrison double moment scheme is used to assess the relative impact of topography on extreme rainfall event of 26–30 July 2010 in Pakistan. Two sensitivity tests with full topography (CTL) and reduced topography by 50% (LOW) are carried out. Two distinct precipitation zones over Hindukush and Himalaya mountains are identified. The topographic changes significantly affect moisture divergence and spatial and temporal distribution of precipitation. A low level jet is created on windward side of big mountains, yielding enhanced moisture flux and instability. Eddy kinetic energy significantly changes with orographic height. Energy flux created further unstabilized atmosphere and deep convection, producing wide spread heavy rainfall in the area in Himalaya foothills. Under the set synoptic conditions, orographic orientation enhanced the moisture accumulation and deep convection, resulting in occurrence of this extreme event.

scholarly journals Integrating large-scale hydrology and hydrodynamics for nested flood hazard modelling from the mountains to the coast

2019 ◽  
Author(s):  
Jannis M. Hoch ◽  
Dirk Eilander ◽  
Hiroaki Ikeuchi ◽  
Fedor Baart ◽  
Hessel C. Winsemius
Keyword(s):  
Flood Risk ◽  
Large Scale ◽  
Management Practices ◽  
Flood Hazard ◽  
Hydrologic Model ◽  
Model Coupling ◽  
Coupled Models ◽  
Critical Success ◽  
Inundation Modelling ◽  
Flood Simulations

Abstract. Fluvial flood events were, are, and will remain a major threat to people and infrastructure. Typically, flood hazard is driven by hydrologic or river routing and floodplain flow processes. Since they are often simulated by different models, coupling these models may be a viable way to increase the physicality of simulated inundation estimates. To facilitate coupling different models and integrating across flood hazard processes, we here present GLOFRIM 2.0, a globally applicable framework for integrated hydrologic-hydrodynamic modelling. We then tested the hypothesis that smart model coupling can advance inundation modelling in the Amazon and Ganges basins. By means of GLOFRIM, we coupled the global hydrologic model PCR-GLOBWB with the hydrodynamic models CaMa-Flood and LISFLOOD-FP. Results show that replacing the kinematic wave approximation of the hydrologic model with the local inertia equation of CaMa-Flood greatly enhances accuracy of peak discharge simulations as expressed by an increase of NSE from 0.48 to 0.71. Flood maps obtained with LISFLOOD-FP improved representation of observed flood extent (critical success index C = 0.46), compared to downscaled products of PCR-GLOBWB and CaMa-Flood (C = 0.30 and C = 0.25, respectively). Results confirm that model coupling can indeed be a viable way forward towards more integrated flood simulations. However, results also suggest that the accuracy of coupled models still largely depends on the model forcing. Hence, further efforts must be undertaken to improve the magnitude and timing of simulated runoff. Besides, flood risk is, particularly in delta areas, driven by coastal processes. A more holistic representation of flood processes in delta areas, for example by incorporating a tide and surge model, must therefore be a next development step of GLOFRIM, making even more physically-robust estimates possible for adequate flood risk management practices.

scholarly journals Approach and Development of Effective Models for Simulation of Thermal Stratification and Mixing Induced by Steam Injection into a Large Pool of Water

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Hua Li ◽  
Walter Villanueva ◽  
Pavel Kudinov
Keyword(s):  
Thermal Stratification ◽  
Large Scale ◽  
Steam Injection ◽  
Small Time ◽  
Small Scale ◽  
Computationally Efficient ◽  
Thermal Mixing ◽  
Large Pool ◽  
Effective Models ◽  
Contact Condensation

Steam venting and condensation in a large pool of water can lead to either thermal stratification or thermal mixing. In a pressure suppression pool (PSP) of a boiling water reactor (BWR), consistent thermal mixing maximizes the capacity of the pool while the development of thermal stratification can reduce the steam condensation capacity of the pool which in turn can lead to pressure increase in the containment and thereafter the consequences can be severe. Advanced modeling and simulation of direct contact condensation in large systems remain a challenge as evident in commercial and research codes mainly due to small time-steps necessary to resolve contact condensation in long transients. In this work, effective models, namely, the effective heat source (EHS) and effective momentum source (EMS) models, are proposed to model and simulate thermal stratification and mixing during a steam injection into a large pool of water. Specifically, the EHS/EMS models are developed for steam injection through a single vertical pipe submerged in a pool under two condensation regimes: complete condensation inside the pipe and chugging. These models are computationally efficient since small scale behaviors are not resolved but their integral effect on the large scale flow structure in the pool is taken into account.

scholarly journals Changes in the wintertime hydroclimatic regime in St. John River, Maine, USA

2021 ◽  
Author(s):  
Jong-Suk Kim ◽  
Shaleen Jain ◽  
Taesam Lee
Keyword(s):  
River Basin ◽  
Large Scale ◽  
Extreme Event ◽  
Southern Oscillation ◽  
Flood Hazard ◽  
Flow Characteristics ◽  
Teleconnection Pattern ◽  
Diagnostic Study ◽  
Atmospheric Teleconnection ◽  
Weather Events

Abstract Changes in the flow regime in snowmelt- and ice-dominated rivers have important implications for navigation, flood hazard, recreation, and ecosystems. We investigated recent changes in the high flows of the St. John River basin in Maine, USA, with a view to quantify changes in high-flow characteristics, as well as extreme event estimates. The results analyzed herein demonstrate shifts in springtime streamflow as well as in emergent wintertime (January–February) streamflow over the past four decades. A Poisson-based regression approach was applied to develop a model for the diagnosis of weather–climate linkage. The sensitivity of episodic warm weather events to the negative phase of the Tropical–Northern Hemisphere (TNH) atmospheric teleconnection pattern is evident. Although a modest sample size of historical data on the weather–climate linkage imposes a limit in terms of reliability, the approach presented herein shows a modest role of the TNH pattern, in response to the warm phase of El Niño/Southern Oscillation, as one of the factors that contribute to hydroclimate variability in the St. John River basin. This diagnostic study sought to investigate the changes in the wintertime streamflow regime and the relative linkages with short-term concurrent weather events, as well as large-scale climatic linkages. This improved an understanding of hydrological extremes within a climatological context and offers new knowledge to inform water resources planning and decision-making.

scholarly journals Using High-Density LiDAR Data and 2D Streamflow Hydraulic Modeling to Improve Urban Flood Hazard Maps: A HEC-RAS Multi-Scenario Approach

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1832 ◽  
Author(s):  
Alin Mihu-Pintilie ◽  
Cătălin Ioan Cîmpianu ◽  
Cristian Constantin Stoleriu ◽  
Martín Núñez Pérez ◽  
Larisa Elena Paveluc
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Flood Hazard ◽  
Hydraulic Modeling ◽  
Flood Mitigation ◽  
Small Scale ◽  
Lidar Data ◽  
Hazard Maps ◽  
Urban Flood ◽  
Flood Hazard Maps

The ability to extract streamflow hydraulic settings using geoinformatic techniques, especially in high populated territories like urban and peri-urban areas, is an important aspect of any disaster management plan and flood mitigation effort. 1D and 2D hydraulic models, generated based on DEMs with high accuracy (e.g., Light Detection and Ranging (LiDAR)) and processed in geographic information systems (GIS) modeling software (e.g., HEC-RAS), can improve urban flood hazard maps. In this study, we present a small-scale conceptual approach using HEC-RAS multi-scenario methodology based on remote sensing (RS), LiDAR data, and 2D hydraulic modeling for the urban and peri-urban area of Bacău City (Bistriţa River, NE Romania). In order to test the flood mitigation capacity of Bacău 1 reservoir (rB1) and Bacău 2 reservoir (rB2), four 2D streamflow hydraulic scenarios (s1–s4) based on average discharge and calculated discharge (s1–s4) data for rB1 spillway gate (Sw1) and for its hydro-power plant (H-pp) were computed. Compared with the large-scale flood hazard data provided by regional authorities, the 2D HEC-RAS multi-scenario provided a more realistic perspective about the possible flood threats in the study area and has shown to be a valuable asset in the improvement process of the official flood hazard maps.

scholarly journals MDST-DBSCAN: A Density-Based Clustering Method for Multidimensional Spatiotemporal Data

2021 ◽  
Vol 10 (6) ◽  
pp. 391
Author(s):  
Changlock Choi ◽  
Seong-Yun Hong
Keyword(s):  
Large Scale ◽  
Complex Structure ◽  
Real Data ◽  
Spatiotemporal Data ◽  
Clustering Methods ◽  
Computationally Efficient ◽  
Clustering Method ◽  
Efficient Manner ◽  
Data Set ◽  
Urban Dynamics

The increasing use of mobile devices and the growing popularity of location-based ser-vices have generated massive spatiotemporal data over the last several years. While it provides new opportunities to enhance our understanding of various urban dynamics, it poses challenges at the same time due to the complex structure and large-volume characteristic of the spatiotemporal data. To facilitate the process and analysis of such spatiotemporal data, various data mining and clustering methods have been proposed, but there still needs to develop a more flexible and computationally efficient method. The purpose of this paper is to present a clustering method that can work with large-scale, multidimensional spatiotemporal data in a reliable and efficient manner. The proposed method, called MDST-DBSCAN, is applied to idealized patterns and a real data set, and the results from both examples demonstrate that it can identify clusters accurately within a reasonable amount of time. MDST-DBSCAN performs well on both spatial and spatiotemporal data, and it can be particularly useful for exploring massive spatiotemporal data, such as detailed real estate transactions data in Seoul, Korea.

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