Flood Modeller在河流洪水风险管理中的应用

本文构建了某河流的洪水建模器(Flood Modeller)一维、二模模型,通过与实际洪水数据对比,校准模型的曼宁系数n值以提高模拟准确性。使用50年、100年和200年一遇的洪水重现期模拟洪水事件,评估潜在淹没区域,为洪水风险评估提供科学的可视化工具。

Spatial diversion and coordination of flood water for an urban flood control project in Suzhou, China

Suzhou City,located in the Yangtze River Delta in China,is prone to flooding due to a complex combination of natural factors,including its monsoon climate,low elevation,and tidally influenced position,as well as intensive human activities.The Large Encirclement Flood Control Project(LEFCP)was launched to cope with serious floods in the urban area.This project changed the spatiotemporal pattern of flood processes and caused spatial diversion of floods from the urban area to the outskirts of the city.Therefore,this study developed a distributed flood simulation model in order to understand this transition of flood processes.The results revealed that the LEFCP effectively protected the urban areas from floods,but the present scheduling schemes resulted in the spatial diversion of floods to the outskirts of the city.With rainstorm frequencies of 10.0%to 0.5%,the water level differences between two representative water level stations(Miduqiao(MDQ)and Fengqiao(FQ))located inside and outside the LEFCP area,ranged from 0.75 m to 0.24 m and from 1.80 m to 1.58 m,respectively.In addition,the flood safety margin at MDQ and the duration with the water level exceeding the warning water level at FQ ranged from 0.95 m to 0.43 m and from 4 h to 22 h,respectively.Rational scheduling schemes for the hydraulic facilities of the LEFCP in extreme precipitation cases were developed ac-cording to food simulations under seven scheduling scenarios.This helps to regulate the spatial flood diversion caused by the LEFCP during extreme precipitation.

The Selection and Breeding of a Novel Microorganism Strain I and Investigation of Core Model Experiment for MEOR

This paper introduces the results of selecting and breeding a micro-organism, Strain I, and its core model experiment investigation for microbial enhanced oil recovery (MEOR). Strain I was separated from the formation water of the Dagang oil field, with analytical results showing that Strain I is a gram-positive bacillus. A further study revealed that this strain has an excellent tolerance of environmental stresses: It can survive in conditions of 70℃, 30 wt% salinity and pH3.5-9.4. Strain I can metabolize biosurfactants that could increase the oil recovery ratio, use crude oil as the single carbon source, and decompose long-chain paraffin with a large molecular weight into short-chain paraffin with a small molecular weight. The core model experiment shows that Strain I enhances oil recovery well. Using 2 vol% of the fermentation solution of Strain I to displace the crude oil in the synthetic plastic bonding core could increase the recovery ratio by 21.6%.

Analysis of dynamic wave model for flood routing in natural rivers

Flooding is a common natural disaster that causes enormous economic, social, and human losses. Of various flood routing methods, the dynamic wave model is one of the best approaches for the prediction of the characteristics of floods during their propagations in natural rivers because all of the terms of the momentum equation are considered in the model. However, no significant research has been conducted on how the model sensitivity affects the accuracy of the downstream hydrograph. In this study, a comprehensive analysis of the input parameters 9f the dynamic wave model was performed through field applications in natural rivers and routing experiments in artificial channels using the graphical multi-parametric sensitivity analysis （GMPSA）. The results indicate that the effects of input parameter errors on the output results are more significant in special situations, such as lower values of Manning＇s roughness coefficient and/or a steeper bed slope on the characteristics of a design hydrograph, larger values of the skewness factor and/or time to peak on the channel characteristics, larger values of Manning＇s roughness coefficient and/or the bed slope on the space step, and lower values of Manning＇s roughness coefficient and/or a steeper bed slope on the time step and weighting factor.

Field based index of flood vulnerability (IFV): A new validation technique for flood susceptible models

The flood hazard management is one of the major challenges in the floodplain regions worldwide.With the rise in population growth and the spread of infrastructural development,the level of risk has increased over time.Therefore,the prediction of flood susceptible area is a key challenge for the adoption of management plans.Flood susceptibility modeling is technically a common work,but it is still a very tough job to validate flood susceptible models in a very rigorous and scientific manner.Therefore,the present work in the Atreyee River Basin of India and Bangladesh was planned to establish artificial neural network(ANN),radial basis function(RBF),random forest(RF)and their ensemble-based flood susceptibility models.The flood susceptible models were constructed based on nine flood conditioning parameters.The flood susceptibility models were validated in a conventional way using the receiver operating curve(ROC).To validate the flood-susceptible models,a two dimensional(2D)hydraulic flood simulation model was developed.Also,the index of flood vulnerability model was developed and applied for validating the flood susceptible models,which was a very unique way to validate the predictive models.Friedman test and Wilcoxon Signed rank test were employed to compare the generated flood susceptible models.Results showed that 11.95%-12.99%of the entire basin area(10188.4 km^(2))comes under very high flood-susceptible zones.Accuracy evaluation results have shown that the performance of ensemble flood susceptible models outperforms other standalone machine learning models.The flood simulation model and IFV model were also spatially adjusted with the flood susceptibility models.Therefore,the present study recommended for the ensemble flood susceptibility prediction and IFV based validation along with conventional ways.

Estimation of the water–oil–gas relative permeability curve from immiscible WAG coreflood experiments using the cubic B-spline model

Immiscible water-alternating-gas（WAG） flooding is an EOR technique that has proven successful for water drive reservoirs due to its ability to improve displacement and sweep efficiency.Nevertheless,considering the complicated phase behavior and various multiphase flow characteristics,gas tends to break through early in production wells in heterogeneous formations because of overriding,fingering,and channeling,which may result in unfavorable recovery performance.On the basis of phase behavior studies,minimum miscibility pressure measurements,and immiscible WAG coreflood experiments,the cubic B-spline model（CBM） was employed to describe the three-phase relative permeability curve.Using the Levenberg-Marquardt algorithm to adjust the vector of unknown model parameters of the CBM sequentially,optimization of production performance including pressure drop,water cut,and the cumulative gas-oil ratio was performed.A novel numerical inversion method was established for estimation of the water-oil-gas relative permeability curve during the immiscible WAG process.Based on the quantitative characterization of major recovery mechanisms,the proposed method was validated by interpreting coreflood data of the immiscible WAG experiment.The proposed method is reliable and can meet engineering requirements.It provides a basic calculation theory for implicit estimation of oil-water-gas relative permeability curve.

Application of Muskingum routing method with variable parameters in ungauged basin

This paper describes a flood routing method applied in an ungauged basin, utilizing the Muskingum model with variable parameters of wave travel time K and weight coefficient of discharge x based on the physical characteristics of the river reach and flood, including the reach slope, length, width, and flood discharge. Three formulas for estimating parameters of wide rectangular, triangular, and parabolic cross sections are proposed. The influence of the flood on channel flow routing parameters is taken into account. The HEC-HMS hydrological model and the geospatial hydrologic analysis module HEC-GeoHMS were used to extract channel or watershed characteristics and to divide sub-basins. In addition, the initial and constant-rate method, user synthetic unit hydrograph method, and exponential recession method were used to estimate runoff volumes, the direct runoff hydrograph, and the baseflow hydrograph, respectively. The Muskingum model with variable parameters was then applied in the Louzigou Basin in Henan Province of China, and of the results, the percentages of flood events with a relative error of peak discharge less than 20% and runoff volume less than 10% are both 100%. They also show that the percentages of flood events with coefficients of determination greater than 0.8 are 83.33%, 91.67%, and 87.5%, respectively, for rectangular, triangular, and parabolic cross sections in 24 flood events. Therefore, this method is applicable to ungauged basins.

A Framework for a Subwatershed-Scale Screening Tool to Support Development of Resiliency Solutions and Flood Protection Priority Areas in a Low-Lying Coastal Community

Flood risk analysis is the instrument for local officials to create a sound strategy and adaptation plans for the impacts of inundation due to heavy rains, climate change and sea level rise. Hence, cities with aging infrastructure are retrofitting their stormwater management systems to mitigate the impacts. However determining the most at risk areas and the options for corrections is more challenging. As a result, there is an urgent need to develop a screening tool to analyze watersheds and identify the most at-risk areas. High-quality, open source data and sophisticated spatial analysis techniques allow engineers to create innovative ways to conduct watershed wide inundation analysis. In this study, the investigators developed a screening tool to identify at-risk properties by combining readily available data on topography, groundwater, surface water, tidal information for coastal communities, soils, open space, and rainfall data. Once the screening tool is developed, the means to identify and prioritize improvements to be funded with scarce capital funds is the next step. A tool box of solutions was developed to address flood risk and vulnerability. Testing of the screening tool was conducted in Broward County, Florida and shows encouraging results. Comparison with FEMA Flood maps and repetitive loss mapping indicates that the process works in a coastal community. The framework appears to be viable across cities that may be inundated with water due to sea-level rise, rainfall, runoff upstream, and other natural events.

A framework of numerical simulation on moraine-dammed glacial lake outburst floods

Glacial outburst floods（GLOFs） in alpine regions tend to be relatively complicated, multi-stage catastrophes, capable of causing significant geomorphologic changes in channel surroundings and posing severe threats to infrastructure and the safety and livelihoods of human communities. GLOF disasters have been observed and potential hazards can be foreseen due to the newly formed glacial lakes or the expansion of existing ones in the Poiqu River Basin in Tibet, China. Here we presented a synthesis of GLOF-related studies including triggering mechanism（s）, dam breach modeling, and flood routing simulation that have been employed to reconstruct or forecast GLOF hydrographs. We provided a framework for probability-based GLOFs simulation and hazard mapping in the Poiqu River Basin according to available knowledge. We also discussed the uncertainties and challenges in the model chains, which may form the basis for further research.

Numerical investigation of wave propagation in the Liverpool Bay,NW England

The computer model for near shore wave propagation,SWAN,was used to study wave climates in Liverpool Bay,northwest England with various input parameters,including bottom friction factor,white capping,wind drag formulation and effects of tidal modulations.Results were compared with in-situ measurements and reveal the impacts from these inputs on the predictions of wave height and propagation distributions.In particular,the model results were found very sensitive to different input formulations,and tend to underestimate the wave parameters under storm conditions in comparison with the observations.It is therefore important to further validate the model against detailed field measurements,particularly under large storms that are often of the primary concern.

Flood Hazard Mapping of Lower Indus Basin Using Multi-Criteria Analysis

Flooding has been one of the recurring occurred natural disasters that induce detrimental impacts on humans, property and environment. Frequent floods is a severe issue and a complex natural phenomenon in Pakistan with respect to population affected, environmental degradations, and socio-economic and property damages. The Super Flood, which hit Sindh in 2010, has turned out to be a wakeup call and has underlined the overwhelming challenge of natural calamities, as 2010 flood and the preceding flood in 2011 caused a huge loss to life, property and land use. These floods resulted in disruption of power, telecommunication, and water utilities in many districts of Pakistan, including 22 districts of Sindh. These floods call for risk assessment and hazard mapping of Lower Indus Basin flowing in the Sindh Province as such areas were also inundated in 2010 flood, which were not flooded in the past in this manner. This primary focus of this paper is the use of Multi-criteria Evaluation (MCE) methods in integration with the Geographical Information System (GIS) for the analysis of areas prone to flood. This research demonstrated how GIS tools can be used to produce map of flood vulnerable areas using MCE techniques. Slope, Aspect, Curvature, Soil, and Distance from Drainage, Land use, Precipitation, Flow Direction, and Flow Accumulation are taken as the causative factors for flooding in Lower Indus Basin. Analytical Hierarchy Process-AHP was used for the calculation of weights of all these factors. Finally, a flood hazard Map of Lower Indus Basin was generated which delineates the flood prone areas in the Sindh province along Indus River Basin that could be inundated by potential flooding in future. It is aimed that flood hazard mapping and risk assessment using open source geographic information system can serve as a handy tool for the development of land-use strategies so as to decrease the impact from flooding.

Multiple time scales of fluvial processes—theory and applications

Fluvial processes comprise water flow,sediment transport and bed evolution,which normally feature distinct time scales.The time scales of sediment transport and bed deformation relative to the flow essentially measure how fast sediment transport adapts to capacity region in line with local flow scenario and the bed deforms in comparison with the flow,which literally dictates if a capacity based and/or decoupled model is justified.This paper synthesizes the recently developed multiscale theory for sediment-laden flows over erodible bed,with bed load and suspended load transport,respectively.It is unravelled that bed load transport can adapt to capacity sufficiently rapidly even under highly unsteady flows and thus a capacity model is mostly applicable,whereas a non-capacity model is critical for suspended sediment because of the lower rate of adaptation to capacity.Physically coupled modelling is critical for fluvial processes characterized by rapid bed variation.Applications are outlined on very active bed load sediment transported by flash floods and landslide dam break floods.

Prediction of the future flood severity in plain river network region based on numerical model: A case study

Suzhou is one of China＇s most developed regions, located in the eastern part of the Yangtze Delta. Due to its location and river features, it may at a high risk of flood under the climate change background in the future. In order to investigate the flood response to the extreme scenario in this region, 1-D hydrodynamic model with real-time operations of sluices and pumps is established. The rain-runoff processes of the urban and rural areas are simulated by two lumped hydrologic models, respectively. Indicators for a quantitative assessment of the flood severity in this region are proposed. The results indicate that the existing flood control system could prevent the Suzhou Downtown from inundation in the future. The difficulty of draining the Taihu Lake floods should be given attention to avoid the flood hazard. The modelling approach based on the in-bank model and the evaluation parameters could be effective for the flood severity estimation in the plain river network catchment. The insights from this study of the possible future extreme flood events may assist the policy making and the flood control planning.

THE SYSTEM OF MODEL CONTROL AND DATA ACQUISITION IN THE HUAIHE RIVER FLOOD CONTROL MODEL

The area of the Huaihe river flood control model is 4000m2. A computer system is employed to control models and collect experimental data.It can control 7 inflows which simulating 9 typical years flood process, a tail water level, 6 sluices, 11 outlets of breaking dike, and collect the water level of 37 points and velocity of 32 points.After running long time,the system has ben proved that it possesses steady character and exact accuracy.It is essential precondition for the experimental study of the Huaibe river find control model.

Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains

The frequency of coastal flood damages is expected to increase significantly during the twenty-first century as sea level rises in the coastal floodplain.Coastal digital elevation model(DEM)data describing coastal topography are essential for assessing future flood-related damages and understanding the impacts of sea-level rise.The Shuttle Radar Topography Mission(SRTM)and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM)are currently the most accurate and freely available DEM data.However,an accuracy assessment specifically targeted at DEMs over low elevation coastal plains is lacking.The present study focuses on these areas to assess the vertical accuracy of SRTM and ASTER GDEM using Ice,Cloud,and land Elevation Satellite,Geoscience Laser Altimeter System(ICESat/GLAS)and Real Time Kinematic(RTK)Global Positioning System(GPS)field survey data.The findings show that DEM accuracy is much better than the mission specifications over coastal plains.In addition,optical remote sensing image analysis further reveals the relationship between DEM vertical accuracy and land cover in these areas.This study provides a systematic approach to assess the accuracy of DEMs in coastal zones,and the results highlight the limitations and potential of these DEMs in coastal applications.

MODELING AND PREDICTION CONCERNING TIME SERIES OF FLOOD/DROUGHT RUNS USING THE SELF-EXCITING THRESHOLD AUTOREGRESSIVE MODEL

When linear regressive models such as AR or ARMA model are used for fitting and predicting climatic time series,results are often not sufficiently good because nonlinear variations in the time series.In this paper, a nonlinear self-exciting threshold autoregressive(SETAR)model is applied to modeling and predicting the time series of flood/drought runs in Beijing,which were derived from the graded historical flood/drought records in the last 511 years(1470—1980).The results show that the modeling and predicting with the SETAR model are much better than that of the AR model.The latter can predict the flood/drought runs with a length only less than two years,while the formal can predict more than three-year length runs.This may be due to the fact that the SETAR model can renew the model according to the run-turning points in the process of predic- tion,though the time series is nonstationary.

Quantitative analysis of impact of green stormwater infrastructures on combined sewer overflow control and urban flooding control

Stimulated by the recent USEPA＇s green stormwater infrastructure （GSI） guidance and policies, GS1 systems have been widely implemented in the municipal area to control the combined sewer overflows （CSOs）, also known as low impact development （LID） approaches. To quantitatively evaluate the performance of GSI systems on CSO and urban flooding control, USEPA-Stormwater Management Model （SWMM） model was adopted in this study to simulate the behaviors of GSI systems in a well- developed urban drainage area, PSW45, under different circumstances. The impact of different percentages of stormwater runoff transported from impervious surfaces to the GSI systems on CSO and urban flooding control has also been investigated. Results show that with current buildup, GSI systems in PSW45 have the best performance for low intensity and short duration events on both volume and peak flow reductions, and have the worst pertbrmance tor high intensity and long durataon events. Since the low intensity and short duration events are dominant from a long-term perspective, utilizing GSI systems is considered as an effective measure of CSO control to meet the long-term controlstrategy for PSW45 watershed. However, GSI systems are not suitable for the flooding control purpose in PSW45 due to the high occurrence possibility of urban flooding during or after high intensity events where GSI systems have relatively poor performance no matter for a short or long duration event,

New prospects for computational hydraulics by leveraging high-performance heterogeneous computing techniques

In the last two decades, computational hydraulics has undergone a rapid development following the advancement of data acquisition and computing technologies. Using a finite-volume Godunov-type hydrodynamic model, this work demonstrates the promise of modern high-performance computing technology to achieve real-time flood modeling at a regional scale. The software is implemented for high-performance heterogeneous computing using the OpenCL programming framework, and developed to support simulations across multiple GPUs using a domain decomposition technique and across multiple systems through an efficient implementation of the Message Passing Interface （MPI） standard. The software is applied for a convective storm induced flood event in Newcastle upon Tyne, demonstrating high computational performance across a GPU cluster, and good agreement against crowd- sourced observations. Issues relating to data availability, complex urban topography and differences in drainage capacity affect results for a small number of areas.