A Community Resilience Evaluation and Optimization Strategy based on Stormwater Management

In the context of disaster normalization, the concept of “resilience” has been gradually introduced into the field of disaster prevention and mitigation in urban communities. In order to resist the increasingly frequent disasters caused by extreme weather, it is necessary to shift the focus of building resilient urban communities to the level of stormwater management. Community resilience is a disaster prevention and mitigation capability based on community resources. In order to solve the deficiency of storm and flood management in the current construction of resilient communities in China, it is necessary to establish a quantitative evaluation system to evaluate it. This paper uses the analytic hierarchy process and Delphi method to establish a community resilience evaluation system from the perspectives of community material space level, community management level and individual level. Then three communities in Hefei City, Anhui Province are selected for practical application of the system, and corresponding optimization and transformation strategies are proposed. The results show that: (1) The resilience of community stormwater management is closely related to the integrated environment of the community, the allocation of flood control facilities and the daily disaster prevention and mitigation management; (2) The ability of disaster prevention and mitigation and the awareness of public participation of the residents in all communities are relatively weak, and the communities invest less in the popularization of stormwater management wisdom; and (3) Resilient communities should not only pay attention to the construction of non-engineering disaster prevention measures, but also to the application of small-scale green infrastructure oriented toward stormwater management.     

潍坊市暴雨洪涝灾害风险区划

利用潍坊市气象数据以及统计年鉴资料、基础地理信息数据、土地利用类型数据和历史灾情数据,基于暴雨洪涝灾害风险评估模型,结合GIS技术,对潍坊市暴雨洪涝灾害进行风险评估,并绘制出潍坊市暴雨洪涝灾害风险区划图.结果表明：诸城市中北部、高密市的西南部及安丘的东南部属于高风险区,安丘的东北部、昌邑的南部属于较高风险区,昌乐的大部分、青州的东部、临朐的东北部、安丘的西部属于中风险区,青州西南部、临朐西南部、寿光东北部、昌邑东北部属于低风险区.评价结果与潍坊市的实际情况基本吻合.     

Seasonal Rainfall Forecasts for the Yangtze River Basin in the Extreme Summer of 2020※

Seasonal forecasts for Yangtze River basin rainfall in June, May–June–July (MJJ), and June–July–August (JJA) 2020 are presented, based on the Met Office GloSea5 system. The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon (EASM) index, which is transformed into regional-mean rainfall through linear regression. The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation. The forecasts verify well in terms of giving strong, consistent predictions of above-average rainfall at lead times of at least three months. However, the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period, leading to observed values that lie outside the 95％ prediction intervals of the three-month forecasts. The forecasts presented here are consistent with other studies of the 2020 EASM rainfall, whereby the enhanced mei-yu front in early summer is skillfully forecast, but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured. This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors.     

2004年汛期(5～9月)主客观降水预报检验

随着气象事业的发展，天气预报的质量越来越依赖于数值预报产品的性能。预报产品检验是评价预报质量和提高预报水平的有效手段。针对2004年汛期（5～9月）中央气象台预报员及T213、HLAFS25、MM5、GRAPES、日本及德国等国内外数值预报模式短期时效的降水预报做了详细的统计学检验。检验结果表明，对于汛期平均而言，各模式与预报员的小雨预报较好，随降水量级的增加TS评分迅速下降，国内外数值预报模式之间降水预报水平差别不大，预报员与模式相比水平略高；但对于过程预报而言，过程不同，各模式和预报员的表现不同，预报员和MM5对河南暴雨预报较好；GRAPES和日本模式对台风暴雨预报略好；T213对于四川东部暴雨的大量级降水预报较好；无论是预报员，还是数值预报模式，北京暴雨的预报是一个典型的失败个例。同时，我们也发现检验系统存在一些问题，有待今后逐步改进。     

长江黄河流域上中下游汛期重旱涝的气候特征

为了揭示长江，黄河流域汛期（6-8月）重旱涝的气候特征，首先采用墨西哥帽小波对长江，黄河流域1951-1999年汛期的降雨资料作分析，得到了两流域汛期降雨量的年际变化趋势；其次将长江流域划分为三段（上游、中游、下游段），黄河流域分为两段（上中游、下游段），以各游段逐月的平均降水量（R）为基准，计算降雨量距平面分率，从而得到逐游段，逐月49年来的重旱涝的时序资料；最后分析该时序资料，得到两流域上中下游汛期重旱涝的时空分布，其结果深化了我们对重旱涝的认识。     

广东省汛期旱涝成因和前期影响因子探讨

根据广东省８６个气象站降水量资料，用正态化Ｚ指数对前，后汛期旱涝等级进行了划分，前汛期旱涝年对比分析表明：西太平洋副高造成的南海地区较强偏南风和较强东亚大槽以及较强垲支西风急流（有利于中纬度冷空气南侵）之间的相互作用是影响广东前汛期降水偏多的直接原因，广东前汛期偏早的主要原因是冷空气偏弱，西太平洋暖池海温变化是这种相互作用的重要影响因子，暖池海温偏高（低），广东前汛期正常偏旱（涝）。前期１２－２月西太平洋暖池海温是前汛期旱涝变化的重要强信号之一，预测前汛期旱涝时应特别关注两极极涡的强度变化和中纬度地区位势高度变化，后汛期旱斩份对比分析表明：亚洲夏季风系统偏强（弱）是造成广东省后污期偏涝（旱）的最重要因素，登陆广东的热带气施个数对后污期降水的影响也比较大，还探讨了后汛期旱涝的预测问题，提出前期５月份北太平洋东部地区５００hPa位势高度距平是预测后汛期旱涝的重要强信号，其位势高度为正距平，则广东后汛期偏早，负距平则偏涝，南半球中高纬地区大气环流变化通过对印度夏季风的影响从而影响后汛期旱涝的变化。     

Reverse flood and pollution routing with the lag-and-route model

ABSTRACT

Reverse routing can be used to transfer flood- or pollution-related information monitored at a downstream gauging station to an ungauged upstream cross-section. This signal identification problem is ill-posed and, as such, is sensitive to perturbations in the data to be inverted; therefore, the amplification of errors, e.g., those befalling measurements, must be controlled. Storage routing models are parsimonious diffusion wave substitutes and well suited for conversion to direct reverse routers. We present efficient inversion frameworks based on the lag-and-route (single reservoir plus exact reverse lag-step) and the reservoirs-in-series models. In both cases we invert a centred finite difference scheme of the reservoir storage balance equation that involves only one value of the unknown signal; signal values identified in previous reverse time steps, which would carry perturbations, are absent. This simple structure endows the reverse scheme with robustness. Procedures are verified with perfect and with error-seeded data; solution oscillations caused by the latter are damped by low-pass filtering. Both inverse routing models regain the upstream signals with high fidelity. Reverse storage routing is exemplified in a demonstration of reservoir control and in a field case of solute transport in a stream.

Editor M.C. Acreman; Associate editor X. Chen     

A distribution-free ordinal classification of floods based on moments

ABSTRACT

Classification of floods is often based on return periods of their peaks estimated from probability distributions and hence depends on assumptions. The choice of an appropriate distribution function and parameter estimation are often connected with high uncertainties. In addition, limited length of data series and the stochastic characteristic of the occurrence of extreme events add further uncertainty. Here, a distribution-free classification approach is proposed based on statistical moments. By using robust estimators the sampling effects are reduced and time series of different lengths can be analysed together. With a developed optimization procedure, locally and regionally consistent flood categories can be defined. In application, it is shown that the resulting flood categories can be used to assess the spatial extent of extreme floods and their coincidences. Moreover, groups of gauges, where simultaneous events belong to the same classes, are indicators for homogeneous groups of gauges in regionalization.     

Urban flood hazard mapping using change detection on wetness transformed images

ABSTRACT

The present study demonstrates the use of a new approach for delineating the accurate flood hazard footprint in the urban regions. The methodology involves transformation of Landsat Thematic Mapper (TM) imagery to a three-dimensional feature space, i.e. brightness, wetness and greenness, then a change detection technique is used to identify the areas affected by the flood. Efficient thresholding of the normalized difference image generated during change detection has shown promising results in identifying the flood extents which include standing water due to flood, sediment-laden water and wetness caused by the flood. Prior to wetness transformations, dark object subtraction has been used in lower wavelengths to avoid errors due to scattering in urban areas. The study shows promising results in eliminating most of the problems associated with urban flooding, such as misclassification due to presence of asphalt, scattering in lower wavelengths and delineating mud surges. The present methodology was tested on the 2010 Memphis flood event and validated on Queensland floods in 2011. The comparative analysis was carried out with the widely-used technique of delineating flood extents using thresholding of near infrared imagery. The comparison demonstrated that the present approach is more robust towards the error of omission in flood mapping. Moreover, the present approach involves less manual effort and is simpler to use.

Editor Z.W. Kundzewicz; Associate editor A. Viglione     

Empirical assessment of flood wave celerity–discharge relationships at local and reach scales

ABSTRACT

An accurate comprehension of celerity (flood wave speed) dynamics is a key step for understanding flood wave propagation in rivers. We present the results of empirically estimated celerity values in 12 Brazilian rivers, and analyse the behaviour of celerity–discharge relationships (CxQ). Celerity was estimated with a reach-scale (RS) method, based on the peak travel time between stations; and with a local-scale (LS) method, based on the derivative of discharge–cross-section area relationships surveyed at gauging stations. The results indicate that the magnitudes of celerity values obtained by the methods are reasonably comparable, and can rarely be considered constant, varying with river discharge. Three reaches presented differing CxQ relationships at local and reach scales, which suggests that in situ cross-sections at gauging stations should not be extrapolated as representative of the whole reach for flood routing studies, and that CxQ relationship assessments might provide relevant insights for hydrological modelling.