942 resultados para flood reports


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A high resolution quantitative granulometric record for site Uchediya 21A degrees 43'2.22aEuro(3) N, 73A degrees 6'26.22aEuro(3) E; 10 m a. s. l.] gives understanding towards accretion history of the late Holocene flood plain in the lower reaches of Narmada River. Two sediment facies (sandy and muddy) and seven subfacies (sandy subfacies: St(MS+FS+CS), SmFS+MS, Sl(FS+VFS), and St(MS + CS); muddy subfacies: FmSILT+VFS+FS, FmSILT+VFS (O) and FmSILT+VFS (T)) are identified based on cluster analysis supplemented with sedimentary structures observed in field and other laboratory data. Changes in hydrodynamics are further deduced based on various sedimentological parameters and their ratios leading to arrive at a depositional model.

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This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

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Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

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Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

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Scaling approaches are widely used by hydrologists for Regional Frequency Analysis (RFA) of floods at ungauged/sparsely gauged site(s) in river basins. This paper proposes a Recursive Multi-scaling (RMS) approach to RFA that overcomes limitations of conventional simple- and multi-scaling approaches. The approach involves identification of a separate set of attributes corresponding to each of the sites (being considered in the study area/region) in a recursive manner according to their importance, and utilizing those attributes to construct effective regional regression relationships to estimate statistical raw moments (SMs) of peak flows. The SMs are then utilized to arrive at parameters of flood frequency distribution and quantile estimate(s) corresponding to target return period(s). Effectiveness of the RMS approach in arriving at flood quantile estimates for ungauged sites is demonstrated through leave-one-out cross-validation experiment on watersheds in Indiana State, USA. Results indicate that the approach outperforms index-flood based Region-of-Influence approach, simple- and multi-scaling approaches and a multiple linear regression method. (C) 2015 Elsevier B.V. All rights reserved.

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Index-flood related regional frequency analysis (RFA) procedures are in use by hydrologists to estimate design quantiles of hydrological extreme events at data sparse/ungauged locations in river basins. There is a dearth of attempts to establish which among those procedures is better for RFA in the L-moment framework. This paper evaluates the performance of the conventional index flood (CIF), the logarithmic index flood (LIF), and two variants of the population index flood (PIF) procedures in estimating flood quantiles for ungauged locations by Monte Carlo simulation experiments and a case study on watersheds in Indiana in the U.S. To evaluate the PIF procedure, L-moment formulations are developed for implementing the procedure in situations where the regional frequency distribution (RFD) is the generalized logistic (GLO), generalized Pareto (GPA), generalized normal (GNO) or Pearson type III (PE3), as those formulations are unavailable. Results indicate that one of the variants of the PIF procedure, which utilizes the regional information on the first two L-moments is more effective than the CIF and LIF procedures. The improvement in quantile estimation using the variant of PIF procedure as compared with the CIF procedure is significant when the RFD is a generalized extreme value, GLO, GNO, or PE3, and marginal when it is GPA. (C) 2015 American Society of Civil Engineers.

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By introducing a water depth connecting formula, the hydraulic equations in the dividing channel system were coupled and the relation of discharge distribution between the branches of the dividing channels can be yielded. In this manner, a numerical model for the confluent channels was established to study the variation of backwater effects with the parameters in the channel junction. The meeting of flood peaks in the mainstream and tributary can be analyzed with this model. The flood peak meeting is found to be a major factor for the extremely high water level in the mainstream during the 1998 Yangtze River flood. Subsequently the variations of discharge distribution and water level with channel parameters between each branch in this system were studied as well. As a result, flood evolution caused by Jingjiang River shortcut and sediment deposition in the entrance of dividing channels of the Yangtze River may be qualitatively elucidated. It is suggested to be an effective measure for flood mitigation to enhance regulation capability of reservoirs available upstream of the tributaries and harness branch entrance channels.

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黄河下游花园口至夹河滩河段系典型的游荡型河段.在该河段,黄河大堤内范围宽广,一般洪水频率年份,水流主要限制在主槽内,因此大堤内分布有不少居民点以及纵横交错的保护居民点的生产堤和不少高于地面的灌溉渠堤和公路,使洪水行洪范围受到了很大的限制.当洪峰流量很大时,洪水将造成生产堤溃决,极大地危害滩区居民的生活.因此,设计模拟模型计算网格时需要考虑大堤、生产堤、明显高于地面的道路等阻水建筑物的影响,使这些堤及公路成为计算格网的边.不规则四边形网格能够很好地拟合黄河这种复杂的计算域.数值模拟时采用有限体积法,为确保通量的单向性,文中使用Osher格式计算通量.通过对1982年洪水的模拟,模拟结果表明了模型的合理性.

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This paper describes a new technology for solonchak soil reclamation in which surface flood irrigation of fresh water and pumped wells drainage of salty groundwater are combined. The comprehensive investigation of water and salt movement has been conducted through field test, laboratory simulation and numerical calculation. The dependence of desalination on irrigation water quantity, drainage quantity, leaching time and other parameters is obtained based on the field tests. The entire desalination process under the flood-irrigation and well-drainage operations was experimentally simulated in a vertical soil column. The water and salt movement has been numerically analysed for both the field and laboratory conditions. The present work indicates that this new technology can greatly improve the effects of desalination.

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The Carr Lake Project aims to convert Carr Lake’s 450 acres of agriculture fields into a regional multi-use park that will benefit flood protection, water quality, and wildlife habitat, while also providing additional recreational areas for the local community. The Project is represented by an informal consortium of interested parties including the Watershed Institute of California State University Monterey Bay, The City of Salinas, 1000 Friends of Carr Lake, and the Big Sur Land Trust. (Document contains 54 pages)

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The center of low pressure of a tropical disturbance which moved northward in the Gulf of Mexico, reached land between Panama City and Port St. Joe, Florida, on September 20, 1969. This system was nearly stationary for 48 hours producing heavy rainfall in the Quincy-Havana area, 70-80 miles northeast of the center. Rainfall associated with the tropical disturbance exceeded 20 inches over a part of Gadsden County, Florida, during September 20 through 23, 1969, and the maximum rainfall of record occurred at Quincy with 10.87 inches during a 6-hour period on September 21. The 48-hour maximum of 17.71 inches exceeded the 1 in 100-year probability of 16 inches for a 7-day period. The previous maximum rainfall of record at Quincy (more than 12 inches) was on September 14-15, 1924. The characteristics of this historical storm were similar in path and effect to the September 1969 tropical disturbance. Peak runoff from a 1.4-square mile area near Midway, Florida, was 1,540 cfs (cubic feet per second) per square mile. A peak discharge of 45,600 cfs on September 22 at the gaging station on the Little River near Quincy exceeded the previous peak of 25,400 cfs which occurred on December 4, 1964. The peak discharge of 89,400 cfs at Ochlockonee River near Bloxham exceeded the April 1948 peak of 50,200 cfs, which was the previous maximum of record, by 1.8 times. Many flood-measurement sites had peak discharges in excess of that of a 50-year flood. Nearly $200,000 was spent on emergency repairs to roads. An additional $520,000 in contractual work was required to replace four bridges that were destroyed. Agricultural losses were estimated at $1,000,000. (44 page document)