基于SWMM模型的城市暴雨洪水模拟与分析

为了进行城市暴雨洪水模拟分析,以湖北省恩施市中心城区为研究区域,在河流水系分布和洪水来源分析的基础上,提出洪水分析计算方案,构建一、二维耦合SWMM模型计算典型频率(10,20,50,100年一遇)河道洪水演进和漫堤淹没过程,获得较为准确的洪水淹没范围、水深、淹没历时和洪峰到达时间等信息,并结合GIS进行洪水影响评价。结果表明,清江干流主要河段基本满足20年一遇的防洪标准,清江干流和龙洞河部分河段现状防洪能力较低。SWMM模型是一种成熟的城市雨洪径流模型,适宜于城市暴雨洪水模拟与分析应用。     

Using Landsat 7 TM data acquired days after a flood event to delineate the maximum flood extent on a coastal floodplain

In response to Hurricane Floyd, the Tar River crested at a record height of 4.30?m above the flood stage at the river gauge station of Greenville (North Carolina, USA) on 21 September 1999. This resulted in a massive flooding in the area. To delineate the maximum flood extent, an area of 238.4?km² along the Tar/Pamlico River, North Carolina, and within the overlapped area of Landsat 7 Thematic Mapper (TM) path 14/row 35 and path 15/row 35 scenes was studied. Three TM datasets of 28 July 1999 (path 15/row 35), 23 September 1999 (path 14/row 35) and 30 September 1999 (path 15/row 35) were analysed as pre-flood data, near peak data, and nine days after the peak data, respectively. The 23 and 30 September flood extent maps were derived by change detection and then verified by 85 nonflooded and flooded sites within the study area. The overall accuracies at the sites were between 82.5–99.3% on both inundation extent maps. Although the recorded river surface level fell 2.62?m from 23 to 30 September at the river gauge station of Greenville, comparison of the two flood extent maps on a pixel-by-pixel basis showed an agreement of 90.7% in terms of regular river channels and waterbodies, flooded areas and nonflooded areas. The 30 September map captured over 90% of the flood extent as identified on the 23 September map. These results suggest that it is possible to use remotely sensed data acquired days after a river's crest to capture most of the maximum extent of a flood occurring on a coastal floodplain, and should somewhat reduce the requirement to have concurrently remotely sensed data in mapping a flood extent on a coastal floodplain.     

Relating wetland inundation to river flow using Landsat TM data

Satellite imagery has been used in many studies that seek to relate river flow to floodplain inundation. However, on rivers with moderately to highly variable daily flows it is difficult to establish a reliable relationship between river stage and area of floodplain inundation. This is because the rapid downstream movement of the flood peak results in the area of maximum inundation at any time being spatially restricted. This study presents a method that accounts for rapid variation in daily discharge using before-flood and after-flood sequences of Landsat Thematic Mapper (TM) imagery in reference to a predefined wetland vector coverage. This procedure establishes a relationship between wetland inundation and river discharge. It also reduces errors of commission arising from: the retention of water on the floodplain from previous floods; the filling of wetlands from rainfall and other non-channel sources; and pixel mis-classification.     

沂沭泗水系防洪工程联合调度系统构建及验证

流域防洪工程系统实时联合调度,是行之有效的非工程防洪措施之一。基于沂沭泗水系防洪"河道泄洪—涵闸分流—湖泊蓄洪—滞洪区滞洪"的复杂大系统,采用大系统分解协调原理、马斯京根演算、水量平衡、二维水动力模型等方法,提出沂沭泗水系防洪工程联合调度系统的构建思路。基于所建模型,在现状工况条件下,对1974年暴雨洪水进行防洪工程联合模拟调度。经调度后,与1974年实测值比较,南四湖下级湖最高水位降幅为0.68 m;骆马湖最高水位降幅为0.37 m;中运河运河站洪峰流量削减90 m~3/s,削减率为2.4%。调度模型及演算结果基本合理,调度模型及采用的演算参数可以作为下一步优化调度的基础。     

Quantitative dynamic flood monitoring with NOAA AVHRR

The analysis of the spatial extent and temporal pattern of flood inundation from remotely sensed imagery is of critical importance to flood mitigation. With a high frequency of global coverage, NOAA/AVHRR has the advantage of detecting flood dynamics during devastating floods. In this paper, we describe a systematic approach to flood monitoring using AVHRR data. Four critical issues for successful flood monitoring with AVHRR were identified: correct identification of water bodies, effective reduction of cloud contamination, accurate area estimation of flood extent, and dynamic monitoring of flood processes. In accordance with the spectral characteristics of water and land in AVHRR channels, a simple but effective water identification method was developed with the ability to reduce cloud influences. The area of flooded regions was calculated with the consideration of areal distortion due to map projection, and mixed pixels at water/land boundaries. Flood dynamics were analysed from flood distributions in both space and time. The maximum spatial extent of floods, generated by compiling the time series of flood maps, was informative about flood damages. We report a successful use of this approach to monitor the Huaihe river flood, a centennial devastating disaster occurred in the Huaihe river basin of China in the summer of 1991.     

重庆市智慧洪水灾害防御研究

结合重庆市洪水特点,提出重庆市智慧洪水灾害防御的总体框架和建设内容,并结合已经完工的重庆市防汛管理信息化建设项目(一期),梳理总结在智慧洪水灾害防御方面所取得的成果,提出一套集实时洪水预报、水库防洪调度、河道洪水演进、水库回水模拟、水库溃坝模拟、洪水淹没及洪灾损失计算、防汛形势分析、应急预案智能研判、水库大坝安全评估、三维动态仿真等于一体的流域洪水过程全链条分析功能体系,并以重庆市主城区为核心的6个流域43条河流、49个重要区域的洪水进行实验验证,验证结果表明,效果良好,可为重庆市防汛决策管理打造智能的信息支撑体系,具有较大的推广应用价值。     

Influence of dike breaches on flood frequency estimation

Many river floodplains and their assets are protected by dikes. In case of extreme flood events, dikes may breach and floodwater may spill over into the dike hinterland. Depending on the specific situation, e.g. time and location of breach, and the capacity of the hinterland to contain the floodwater, dike breaches may lead to significant reductions of flood peaks downstream of breach locations. However, the influence of dike breaches on flood frequency distributions along rivers has not been systematically analysed. In order to quantify this influence, a dynamic–probabilistic model is developed. This model combines simplified flood process modules in a Monte Carlo framework. The simplifications allow for the simulation of a large number of different scenarios, taking into account the main physical processes. By using a Monte Carlo approach, frequency distributions can be derived from the simulations. In this way, process understanding and the characteristics of the river–dike–floodplain system are included in the derivation of flood frequency statements. The dynamic–probabilistic model is applied to the Lower Rhine in Germany and compared to the usually used flood frequency analysis. For extreme floods, the model simulates significant retention effects due to dike breaches, which lead to significant modifications of the flood frequency curve downstream of breach locations. The resulting probabilistic statements are much more realistic than those of the flood frequency approach, since the dynamic–probabilistic model incorporates an important flood process, i.e. dike breaching, that only occurs when a certain threshold is reached. Beyond this point, the behaviour of the flood frequency curve is dominated by this process.     

重庆智慧洪水灾害防御研究

本文结合重庆市的洪水特点,即过境洪水和山洪相互叠加、受三峡水库回水顶托影响、极易引发次生地质灾害,提出了重庆市智慧洪水灾害防御的总体框架和建设内容,并结合已经完工的重庆防汛管理信息化建设项目（一期）,梳理总结了在智慧洪水灾害防御方面所取得的成果,提出了一套集实时洪水预报、水库防洪调度、河道洪水演进、水库回水模拟、水库溃坝模拟、洪水淹没及洪灾损失计算、防汛形势分析、应急预案智能研判、水库大坝安全评估、三维动态仿真等于一体的流域洪水过程全链条分析功能体系,并以重庆主城区为核心的6个流域43条河流、49个重要区域的洪水进行了实验验证,证明方法可行,效果很好,为重庆市防汛决策管理打造了智能的业务支撑体系,具有较大的推广应用价值。     

洪水沉积物对长江中游洪泛区土壤钾素营养的影响

本文对比研究了长江中游几类洪泛区 (江心洲、洲滩和圩垸等 )的洪水沉积物和剖面土壤的钾素营养状况。结果表明 ,相对于洪泛区耕层 (表层 )或剖面土壤的钾素状况 ,洪水沉积物的覆盖能丰富表土的钾素营养 ,显著增加表土的速效钾和缓效钾含量 ,且速效钾的增幅大于缓效钾 ,而对全钾无明显影响。沉积物对土壤钾素状况的影响与其颗粒组成、有机质含量、CEC和土地利用方式等因素有关。沉积物和土壤的钾素状况与粘粒含量 (<0 0 1mm)呈显著正相关 ,与砂粒部分呈负相关 ;有机质和CEC对土壤钾素的有效性有一定影响 ;而洪泛区土地利用方式与耕层土壤钾素的消耗有关     

Neural networks forecasting of flood discharge at an unmeasured station using river upstream information

Based upon information at stations upstream of a river, a back-propagation neural network model was employed in this study to forecast flood discharge at station downstream of the river which lacks measurement. The performance of the neural network model was evaluated from the indices of root mean square error, coefficient of efficiency, error of peak discharge, and error of time to peak. The verification results showed that the neural network model is preferable, which performs relatively better than that of the conventional Muskingum method. Furthermore, the developed model with different input parameters was trained to check the sensitivity of physiographical factors. The results exhibited that flood discharge and water stage, are two factors to dominate the accuracy of estimation. Meanwhile, the physiographical factors had a slight and positive influence on the accuracy of the prediction. The time varied flood discharge forecasting at an unmeasured station might provide a valuable reference for designing an engineering project in the vicinity of the investigation region.