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1.
This paper demonstrates the utility of satellite remote sensing data in water management, and particularly, for flood monitoring and impact analysis. Satellite-derived data can provide timely geographical data from which water body extent in normal and flood regimes can be ascertained. Combined with exogenous and historical data, within a GIS, these can provide information useful for flood prevention decision making. The recent French Alsation, Camargue and Vaison la Romaine floods are taken to illustrate the utility of satellite remote sensing. © 1997 John Wiley & Sons, Ltd. 相似文献
2.
High‐resolution data obtained from airborne remote sensing is increasing opportunities for representation of small‐scale structural elements (e.g. walls, buildings) in complex floodplain systems using two‐dimensional (2D) models of flood inundation. At the same time, 2D inundation models have been developed and shown to provide good predictions of flood inundation extent, with respect to both full solution of the depth‐averaged Navier–Stokes equations and simplified diffusion‐wave models. However, these models have yet to be applied extensively to urban areas. This paper applies a 2D raster‐based diffusion‐wave model to determine patterns of fluvial flood inundation in urban areas using high‐resolution topographic data and explores the effects of spatial resolution upon estimated inundation extent and flow routing process. Model response shows that even relatively small changes in model resolution have considerable effects on the predicted inundation extent and the timing of flood inundation. Timing sensitivity would be expected, given the relatively poor representation of inertial processes in a diffusion‐wave model. Sensitivity to inundation extent is more surprising, but is associated with: (1) the smoothing effect of mesh coarsening upon input topographical data; (2) poorer representation of both cell blockage and surface routing processes as the mesh is coarsened, where the flow routing is especially complex; and (3) the effects of (1) and (2) upon water levels and velocities, which in turn determine which parts of the floodplain the flow can actually travel to. It is shown that the combined effects of wetting and roughness parameters can compensate in part for a coarser mesh resolution. However, the coarser the resolution, the poorer the ability to control the inundation process, as these parameters not only affect the speed, but also the direction of wetting. Thus, high‐resolution data will need to be coupled to a more sophisticated representation of the inundation process in order to obtain effective predictions of flood inundation extent. This is explored in a companion paper. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
3.
Self‐organizing maps (SOMs) have been successfully accepted widely in science and engineering problems; not only are their results unbiased, but they can also be visualized. In this study, we propose an enforced SOM (ESOM) coupled with a linear regression output layer for flood forecasting. The ESOM re‐executes a few extra training patterns, e.g. the peak flow, as recycling input data increases the mapping space of peak flow in the topological structure of SOM, and the weighted sum of the extended output layer of the network improves the accuracy of forecasting peak flow. We have investigated an ESOM neural network by using the flood data of the Da‐Chia River, Taiwan, and evaluated its performance based on the results obtained from a commonly used back‐propagation neural network. The results demonstrate that the ESOM neural network has great efficiency for clustering, especially for the peak flow, and super capability of modelling the flood forecast. The topology maps created from the ESOM are interesting and informative. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
4.
The use of spatial patterns of flood inundation (often obtained from remotely sensed imagery) to calibrate flood inundation models has been widespread over the last 15 years. Model calibration is most often achieved by employing one or even several performance measures derived from the well‐known confusion matrix based on a binary classification of flooding. However, relatively early on, it has been recognized that the use of commonly reported performance measures for calibrating flood inundation models (such as the F measure) is hampered because the calibration procedure commonly utilizes only one possible solution of a wet/dry classification of a remote sensing image [most often acquired by a synthetic aperture radar (SAR)] to calibrate or validate models and are biased towards either over‐prediction or under‐prediction of flooding. Despite the call in several studies for an alternative statistic, to this date, very few, if any, unbiased performance measure based on the confusion matrix has been proposed for flood model calibration/validation studies. In this paper, we employ a robust statistical measure that operates in the receiver operating characteristics (ROC) space and allows automated model calibration with high identifiability of the best model parameter set but without the need of a classification of the SAR image. The ROC‐based method for flood model calibration is demonstrated using two different flood event test cases with flood models of varying degree of complexity and boundary conditions with varying degree of accuracy. Verification of the calibration results and optional SAR classification is successfully performed with independent observations of the events. We believe that this proposed alternative approach to flood model calibration using spatial patterns of flood inundation should be employed instead of performance measures commonly used in conjunction with a binary flood map. © 2013 California Institute of Technology. Hydrological Processes © 2013 John Wiley & Sons, Ltd. 相似文献
5.
A methodology is proposed for constructing a flood forecast model using the adaptive neuro‐fuzzy inference system (ANFIS). This is based on a self‐organizing rule‐base generator, a feedforward network, and fuzzy control arithmetic. Given the rainfall‐runoff patterns, ANFIS could systematically and effectively construct flood forecast models. The precipitation and flow data sets of the Choshui River in central Taiwan are analysed to identify the useful input variables and then the forecasting model can be self‐constructed through ANFIS. The analysis results suggest that the persistent effect and upstream flow information are the key effects for modelling the flood forecast, and the watershed's average rainfall provides further information and enhances the accuracy of the model performance. For the purpose of comparison, the commonly used back‐propagation neural network (BPNN) is also examined. The forecast results demonstrate that ANFIS is superior to the BPNN, and ANFIS can effectively and reliably construct an accurate flood forecast model. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
6.
Rainfall–runoff modelling, as a surface hydrological process, on large‐scale data‐poor basins is currently a major topic of investigation that requires the model parameters be identified by using basin physical characteristics rather than calibration. This paper describes the application of the TOPMODEL framework accompanied by a kinematic wave model to the Karun River sub‐basins in southwestern Iran with just one conceptual parameter for calibration. ISLSCP1, HYDRO1K and Reynolds data sets are presented in a geographical information system and used as data sources for meteorological information, hydrological features and soil characteristics of the study area respectively. The results show that although the model developed can adequately predict flood runoff in the catchment with only one calibrated parameter, it is suggested that the effect of surface reservoirs be considered in the proposed model. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
7.
Felício Cassalho Samuel Beskow Carlos Rogrio de Mello Maíra Martim de Moura Leroi Floriano de Oliveira Marilton Sanchotene de Aguiar 《水文研究》2019,33(7):1101-1116
Due to the severity related to extreme flood events, recent efforts have focused on the development of reliable methods for design flood estimation. Historical streamflow series correspond to the most reliable information source for such estimation; however, they have temporal and spatial limitations that may be minimized by means of regional flood frequency analysis (RFFA). Several studies have emphasized that the identification of hydrologically homogeneous regions is the most important and challenging step in an RFFA. This study aims to identify state‐of‐the‐art clustering techniques (e.g., K ‐means, partition around medoids, fuzzy C‐means, K ‐harmonic means, and genetic K ‐means) with potential to form hydrologically homogeneous regions for flood regionalization in Southern Brazil. The applicability of some probability density function, such as generalized extreme value, generalized logistic, generalized normal, and Pearson type 3, was evaluated based on the regions formed. Among all the 15 possible combinations of the aforementioned clustering techniques and the Euclidian, Mahalanobis, and Manhattan distance measures, the five best were selected. Several watersheds' physiographic and climatological attributes were chosen to derive multiple regression equations for all the combinations. The accuracy of the equations was quantified with respect to adjusted coefficient of determination, root mean square error, and Nash–Sutcliffe coefficient, whereas, a cross‐validation procedure was applied to check their reliability. It was concluded that reliable results were obtained when using robust clustering techniques based on fuzzy logic (e.g., K ‐harmonic means), which have not been commonly used in RFFA. Furthermore, the probability density functions were capable of representing the regional annual maximum streamflows. Drainage area, main river length, and mean altitude of the watershed were the most recurrent attributes for modelling of mean annual maximum streamflow. Finally, an integration of all the five best combinations stands out as a robust, reliable, and simple tool for estimation of design floods. 相似文献
8.
A key aspect of large river basins partially neglected in large‐scale hydrological models is river hydrodynamics. Large‐scale hydrologic models normally simulate river hydrodynamics using simplified models that do not represent aspects such as backwater effects and flood inundation, key factors for some of the largest rivers of the world, such as the Amazon. In a previous paper, we have described a large‐scale hydrodynamic approach resultant from an improvement of the MGB‐IPH hydrological model. It uses full Saint Venant equations, a simple storage model for flood inundation and GIS‐based algorithms to extract model parameters from digital elevation models. In the present paper, we evaluate this model in the Solimões River basin. Discharge results were validated using 18 stream gauges showing that the model is accurate. It represents the large delay and attenuation of flood waves in the Solimões basin, while simplified models, represented here by Muskingum Cunge, provide hydrographs are wrongly noisy and in advance. Validation against 35 stream gauges shows that the model is able to simulate observed water levels with accuracy, representing their amplitude of variation and timing. The model performs better in large rivers, and errors concentrate in small rivers possibly due to uncertainty in river geometry. The validation of flood extent results using remote sensing estimates also shows that the model accuracy is comparable to other flood inundation modelling studies. Results show that (i) river‐floodplain water exchange and storage, and (ii) backwater effects play an important role for the Amazon River basin hydrodynamics. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
9.
Giuliano Di Baldassarre Guy Schumann Luigia Brandimarte Paul Bates 《Surveys in Geophysics》2011,32(3):255-269
It is widely recognised that remote sensing can support flood monitoring, modelling and management. In particular, satellites carrying Synthetic Aperture Radar (SAR) sensors are valuable as radar wavelengths can penetrate cloud cover and are insensitive to daylight. However, given the strong inverse relationship between spatial resolution and revisit time, monitoring floods from space in near real time is currently only possible through low resolution (about 100 m pixel size) SAR imagery. For instance, ENVISAT-ASAR (Advanced Synthetic Aperture Radar) in WSM (wide swath mode) revisit times are of the order of 3 days and the data can be obtained within 24 h at no (or low) cost. Hence, this type of space-borne data can be used for monitoring major floods on medium-to-large rivers. This paper aims to discuss the potential for, and uncertainties of, coarse resolution SAR imagery to monitor floods and support hydraulic modelling. The paper first describes the potential of globally and freely available space-borne data to support flood inundation modelling in near real time. Then, the uncertainty of SAR-derived flood extent maps is discussed and the need to move from deterministic binary maps (wet/dry) of flood extent to uncertain flood inundation maps is highlighted. 相似文献
10.
The further development of two-dimensional finite element models of river flood flow is currently constrained by a lack of data for rigorous parameterization and validation. Remote sensing techniques have the potential to overcome a number of these constraints thereby allowing a research design for model development. This is illustrated with reference to a case study of a two-dimensional finite element model applied to the Missouri River, Nebraska and compared with a synchronous Landsat TM image of flood inundation extent. The case study allows research needs for the integration of hydraulic modelling and remote sensing to be defined. © 1997 John Wiley & Sons, Ltd. 相似文献
11.
Numerical modelling of flood inundation over large and complex floodplains often requires mesh resolutions coarser than the structural features (e.g. buildings) that are known to influence the inundation process. Recent research has shown that this mismatch is not well represented by conventional roughness treatments, but that finer‐scale features can be represented through porosity‐based subgrid‐scale treatments. This paper develops this work by testing the interactions between feature representation, subgrid‐scale resolution and mesh resolution. It uses as the basis for this testing a 2D diffusion‐based flood inundation model which is applied to a 2004 flood event in a topologically complex upland floodplain in northern England. This study formulated simulations with different grid mesh resolution and subgrid mesh ratio. The sensitivity of the model to mesh resolution and roughness specification was investigated. Model validation and verification suggest that the subgrid treatment with higher subgrid mesh ratio can give much improved predictions of flood propagation, in particular, in terms of the predicted water depth. This study also highlighted the limitation of using at‐a‐point in time inundation extent for validation of flood models of this type. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
12.
Have applications of continuous rainfall–runoff simulation realized the vision for process‐based flood frequency analysis? 
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下载免费PDF全文 Keith Beven was amongst the first to propose and demonstrate a combination of conceptual rainfall–runoff modelling and stochastically generated rainfall data in what is known as the ‘continuous simulation’ approach for flood frequency analysis. The motivations included the potential to establish better links with physical processes and to avoid restrictive assumptions inherent in existing methods applied in design flood studies. Subsequently, attempts have been made to establish continuous simulation as a routine method for flood frequency analysis, particularly in the UK. The approach has not been adopted universally, but numerous studies have benefitted from applications of continuous simulation methods. This paper asks whether industry has yet realized the vision of the pioneering research by Beven and others. It reviews the generic methodology and illustrates applications of the original vision for a more physically realistic approach to flood frequency analysis through a set of practical case studies, highlighting why continuous simulation was useful and appropriate in each case. The case studies illustrate how continuous simulation has helped to offer users of flood frequency analysis more confidence about model results by avoiding (or exposing) bad assumptions relating to catchment heterogeneity, inappropriateness of assumptions made in (UK) industry‐standard design event flood estimation methods, and the representation of engineered or natural dynamic controls on flood flows. By implementing the vision for physically realistic analysis of flood frequency through continuous simulation, each of these examples illustrates how more relevant and improved information was provided for flood risk decision‐making than would have been possible using standard methods. They further demonstrate that integrating engineered infrastructure into flood frequency analysis and assessment of environmental change are also significant motivations for adopting the continuous simulation approach in practice. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
13.
Although artificial neural networks (ANNs) have been applied in rainfall runoff modelling for many years, there are still many important issues unsolved that have prevented this powerful non‐linear tool from wide applications in operational flood forecasting activities. This paper describes three ANN configurations and it is found that a dedicated ANN for each lead‐time step has the best performance and a multiple output form has the worst result. The most popular form with multiple inputs and single output has the average performance. In comparison with a linear transfer function (TF) model, it is found that ANN models are uncompetitive against the TF model in short‐range predictions and should not be used in operational flood forecasting owing to their complicated calibration process. For longer range predictions, ANN models have an improved chance to perform better than the TF model; however, this is highly dependent on the training data arrangement and there are undesirable uncertainties involved, as demonstrated by bootstrap analysis in the study. To tackle the uncertainty issue, two novel approaches are proposed: distance analysis and response analysis. Instead of discarding the training data after the model's calibration, the data should be retained as an integral part of the model during its prediction stage and the uncertainty for each prediction could be judged in real time by measuring the distances against the training data. The response analysis is based on an extension of the traditional unit hydrograph concept and has a very useful potential to reveal the hydrological characteristics of ANN models, hence improving user confidence in using them in real time. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
14.
Seree Supharatid 《水文研究》2006,20(2):307-318
Hat Yai, the largest commercial and tourist city in southern Thailand, is subjected to regular flood events, primarily during the northeast monsoon period. Flooding in this region is recognized as a serious disaster in terms of frequency, rate of risk, and affected areas. The monsoon of 21–25 November 2000 caused extremely heavy rain in the southern part of Thailand, resulting in a great flood occupying Hat Yai. This caused significant damage. Therefore, the use of both structural and non‐structural measures is mandatory to reduce the economic losses and the risk for society. This paper investigates two modelling approaches for flood prevention and mitigation of Hat Yai city. First, a hard computing approach by a physically distributed model was applied to study the flood behaviour in a two‐dimensional floodplain flow. Second, a soft computing approach using a neuro‐genetic algorithm was used to develop a flood‐forecasting tool. It was found that the great flood of 2000 can be simulated well by the FLO‐2D model. Computed discharges and flood level in the floodplain are close to the observed data. Countermeasures using diversion canals are guaranteed to accelerate the floodwater drainage to Songkla Lake, significantly reducing the flood impact to the people. In addition, the flood forecasting technique developed in this study can give satisfactory results. This would be very useful as a flood‐warning tool for the community Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
15.
Recent years have been marked by a continuous availability of spatial SAR data since the launch of the European remote sensing satellite (ERS-1) in 1991. Consequently, remote sensing techniques now offer an opportunity to map flood inundation fields caused by river overflow or waterlogging in environments characterized by frequent cloud cover. Indeed, inundation fields can clearly be seen on ERS-1 SAR images taken during flooding periods. However, such an identification can be constrained by the similarity in behaviour between water surfaces and other features of the landscape such as extended asphalt areas, permanent water bodies and less illuminated slopes. For consistent flood inundation extent mapping a more robust approach is required. This is provided by a conceptual flood inundation index that is physically sound in relation to radar imaging. Moreover, this index has proved to be useful for highlighting soils located within inundation fields and having significantly different internal drainage. The results achieved in the framework of the research must be seen in the context of intensive use of remote sensing data to support decision methods for sustainable management of land and water resources. Such decision support methods could be provided by river hydraulic models aimed at assessing environmental effects of inundation floods and at early flood warning systems. © 1997 John Wiley & Sons, Ltd. 相似文献
16.
This paper focuses mainly on the investigation of water reserve changes in Salt Lake, Turkey, using remote‐sensing data. The study is performed in two stages: (1) correlation analysis for real‐time ground and satellite data and (2) assessment of water reserve changes using multi‐temporal Landsat imagery. First, correlation analysis is conducted to investigate the relationship between digital data from Landsat‐5 TM and spectral (in situ) measurements collected using a field spectroradiometer on the same day and time. A radiometric correction procedure, including conversions from digital numbers to radiance and from radiance to at‐satellite reflectance, is executed to make satellite data comparable to in situ measurements. This procedure show that simultaneous ground and satellite remote‐sensing data are highly correlated (0·84 > R2 > 97) and the near‐infrared region (for this study TM4‐Landsat‐5 TM, band 4) is the best spectral range to distinguish salt and water on the satellite data for the multi‐temporal analysis of the water reserve in Salt Lake. It also shows that the use of shortwave infrared band(s) will result in confusion for the determination of the water reserve in this water‐covered study area. In a second and last phase, the water reserve change in the lake is examined using multi‐temporal Landsat imagery collected in 1990, 2001 and 2005. The remotely sensed, sampled and treated data show that the water reserve in the lake has decreased markedly between 1990 and 2005 due to drought and uncontrolled water usage. It is suggested that the use of water supplies around Salt Lake should be controlled and that the lake should regularly be monitored by up‐to‐date remote‐sensing data (at least annually) for better management of water resources. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
17.
Effect of permafrost thaw on the dynamics of lakes recharged by ice‐jam floods: case study of Yukon Flats,Alaska 下载免费PDF全文
下载免费PDF全文 Large river floods are a key water source for many lakes in fluvial periglacial settings. Where permeable sediments occur, the distribution of permafrost may play an important role in the routing of floodwaters across a floodplain. This relationship is explored for lakes in the discontinuous permafrost of Yukon Flats, interior Alaska, using an analysis that integrates satellite‐derived gradients in water surface elevation, knowledge of hydrogeology, and hydrologic modelling. We observed gradients in water surface elevation between neighbouring lakes ranging from 0.001 to 0.004. These high gradients, despite a ubiquitous layer of continuous shallow gravel across the flats, are consistent with limited groundwater flow across lake basins resulting from the presence of permafrost. Permafrost impedes the propagation of floodwaters in the shallow subsurface and constrains transmission to ‘fill‐and‐spill’ over topographic depressions (surface sills), as we observed for the Twelvemile‐Buddy Lake pair following a May 2013 ice‐jam flood on the Yukon River. Model results indicate that permafrost table deepening of 1–11 m in gravel, depending on watershed geometry and subsurface properties, could shift important routing of floodwater to lakes from overland flow (fill‐and‐spill) to shallow groundwater flow (‘fill‐and‐seep’). Such a shift is possible in the next several hundred years of ground surface warming and may bring about more synchronous water level changes between neighbouring lakes following large flood events. This relationship offers a potentially useful tool, well suited to remote sensing, for identifying long‐term changes in shallow groundwater flow resulting from thawing of permafrost. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
18.
Adrián Pedrozo‐Acuña I Mariño‐Tapia C Enriquez Gabriela Medellín Mayoral Fernando J. González Villareal 《水文研究》2012,26(5):687-704
This investigation comprises the hydraulic characterisation of a river located in the Mexican State of Tabasco, including the performance of its flood plain under the action of an extreme river discharge. This is done through the combination of a high‐quality validation dataset, remote sensing information, and a standard 2D numerical model. The dataset was collected during an intensive field campaign that took place in August 2009. In particular, in situ measurements of river discharge, bathymetry, water level, and velocities through a whole tidal cycle are employed along with multi‐spectral satellite imagery. The purpose of this study is twofold. Firstly, the integrated approach comprising the combination of a 2D hydrodynamic model, high‐quality in situ measurements and satellite imagery reduce the uncertainty in the model parameterisation and results. Secondly, it is shown that freely available sources of information, such as the Shuttle Radar Topographic Mission (SRTM) data can be processed and utilized in 2D hydraulic models. This is particularly important in countries where high‐resolution elevation data is not yet available. It is demonstrated that the selected approach is useful when the study of possible consequences in a flood plain induced by an extreme flood discharge are sought. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
19.
Willem H. J. Toonen Hans Middelkoop Tiuri Y. M. Konijnendijk Mark G. Macklin Kim M. Cohen 《地球表面变化过程与地形》2016,41(9):1266-1275
Climate change is expected to significantly affect flooding regimes of river systems in the future. For Western Europe, flood risk assessments generally assume an increase in extreme events and flood risk, and as a result major investments are planned to reduce their impacts. However, flood risk assessments for the present day and the near future suffer from uncertainty, coming from short measurements series, limited precision of input data, arbitrary choices for particular statistical and modelling approaches, and climatic non‐stationarities. This study demonstrates how historical and sedimentary information can extend data records, adds important information on extremes, and generally improves flood risk assessments. The collection of specific data on the occurrence and magnitude of extremes and the natural variability of the floods is shown to be of paramount importance to reduce uncertainty in our understanding of flooding regime changes in a changing climate. For the Lower Rhine (the Netherlands and Germany) estimated recurrence times and peak discharges associated with the current protection levels correlate poorly with historical and sedimentary information and seem biased towards the recent multi‐decadal period of increased flood activity. Multi‐decadal and centennial variability in flood activity is recorded in extended series of discharge data, historical information and sedimentary records. Over the last six centuries that variability correlates with components of the Atlantic climate system such as the North Atlantic Oscillation (NAO) and Atlantic Multi‐decadal Oscillation (AMO). These climatic non‐stationarities importantly influence flood activity and the outcomes of flood risk assessments based on relatively short measurement series. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
20.
A hydro‐economic modelling framework for flood damage estimation and the role of riparian vegetation
A modelling framework for the quick estimate of flood inundation and the resultant damages is developed in this paper. The model, called the flood economic impact analysis system (FEIAS), can be applied to a river reach of any hydrogeological river basin. For the development of the integrated modelling framework, three models were employed: (1) a modelling scheme based on the Hydrological Simulation Program FORTRAN model that was developed for any geomorphological river basin, (2) a river flow/floodplain model, and (3) a flood loss estimation model. The first sub‐model of the flood economic impact analysis system simulates the hydrological processes for extended periods of time, and its output is used as input to a second component, the river/floodplain model. The hydraulic model MIKE 11 (quasi‐2D) is the river/floodplain model employed in this study. The simulated flood parameters from the hydraulic model MIKE 11 (quasi‐2D) are passed, at the end of each time step, to a third component, the flood loss model for the estimation of flood damage. In the present work, emphasis was given to the seasonal variation of Manning's coefficient (n), which is an important parameter for the determination of the flood inundation in hydraulic modelling. High values of Manning's coefficient for a channel indicate high flow resistance. The riparian vegetation can have a large impact on channel resistance. The modelling framework developed in this paper was used to investigate the role of riparian vegetation in reducing flood damage. Moreover, it was used to investigate the influence of cutting riparian vegetation scenarios on the flow characteristics. The proposed framework was applied to the downstream part of the Koiliaris River basin in Crete, Greece, and was tested and validated with historical data. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献