Forecasting for flood warning

Advances in flood forecasting have been constrained by the difficulty of estimating rainfall continuously over space, for catchment-, national- and continental-scale areas. This has had a concomitant impact on the choice of appropriate model formulations for given flood-forecasting applications. Whilst weather radar used in combination with raingauges – and extended to utilise satellite remote-sensing and numerical weather prediction models – have offered the prospect of progress, there have been significant problems to be overcome. These problems have curtailed the development and adoption of more complete distributed model formulations that aim to increase forecast accuracy. Advanced systems for weather radar display and processing, and for flood forecast construction, are now available to ease the task of implementation. Applications requiring complex networks of models to make forecasts at many locations can be undertaken without new code development and be readily revised to take account of changing requirements. These systems make use of forecast-updating procedures that assimilate data from telemetry networks to improve flood forecast performance, at the same time coping with the possibility of data loss. Flood forecasting systems that integrate rainfall monitoring and forecasting with flood forecasting and warning are now operational in many areas. Present practice in flood modelling and forecast updating is outlined from a UK perspective. Challenges for improvement are identified, particularly against a background of greater access to spatial datasets on terrain, soils, geology, land-cover, and weather variables. Representing the effective runoff production and translation processes operating at a given grid or catchment scale may prove key to improved flood simulation, and robust application to ungauged basins through physics-based linkages with these spatial datasets. The need to embrace uncertainty in flood-warning decision-making is seen as a major challenge for the future. To cite this article: R.J. Moore et al., C. R. Geoscience 337 (2005).     

The human component in flood warning and flood response system

The disign of flood warning — flood response systems is often performed as part of the overall engineering analysis of flood damage mitigation schemes. However, an important part of the flood response component of such systems is human perception of the flood hazard and its implication for the responses undertaken. This human dimension is examined from three viewpoints, the perception of the flood, the issues in the warning dissemination process, and the implications for the actions undertaken by individual flood plain occupants in response to a warning. Evidence is provided to show how the human characteristics of the flood plain occupants can signigicantly affect the benefits derived from a flood warning — flood response system. The importance of these non-engineering aspects of the problem leads to recommendations for closer collaboration between traditional technical experts and social scientists. The cooperation should extend beyond the assessment of the reduction in flood damages expected from a particular flood warning scheme into actual design of the dissemination process and response mechanisms.     

山洪预报预警技术研究进展

山洪预报预警研究是实施山洪灾害防治的重要科学支撑。目前国内外学者对山洪预报预警技术的研究主要集中在山洪预警指标、山洪预报预警模型以及山洪灾害风险分析等方面,本文对山洪预报预警技术相关研究进展进行了总结,并指出未来在山洪灾害监测、山洪预报预警模型研制、多元信息融合技术、结合山洪特点和区划有针对性进行预报预警等方面还应进行更深入的研究。     

An extended STIRPAT model-based methodology for evaluating the driving forces affecting carbon emissions in existing public building sector: evidence from China in 2000–2015

In recent decades, population growth associated with unplanned urban occupation has increased the vulnerability of the Brazilian population to natural disasters. In susceptible regions, early flood forecasting is essential for risk management. Still, in Brazil, most flood forecast and warning systems are based either on simplified models of flood wave propagation through the drainage network or on stochastic models. This paper presents a methodology for flood forecasting aiming to an operational warning system that proposes to increase the lead time of a warning through the use of an ensemble of meteorological forecasts. The chosen configuration was chosen so it would be feasible for an operational flood forecast and risk management. The methodology was applied to the flood forecast for the Itajaí-Açu River basin, a region which comprises a drainage area of approximately 15,500 km² in the state of Santa Catarina, Brazil, historically affected by floods. Ensemble weather forecasts were used as input to the MHD-INPE hydrological model, and the performance of the methodology was assessed through statistical indicators. Results suggest that flood warnings can be issued up to 48 h in advance, with a low rate of false warnings. Streamflow forecasting through the use of hydrological ensemble prediction systems is still scarce in Brazil. To the best of our knowledge, this is the first time this methodology aiming to an operational flood risk management system has been tested in Brazil.     

An integrated system for forecasting Arno River flash floods

A system for effectively forecasting flash floods of the Arno River (Tuscany, Italy) should provide a flood warning with 10–12 h of lead time, primarily in order to evacuate the city of Florence. This goal may be achieved by acquiring and processing meteorological and hydrological data in real-time and, accordingly, by releasing alarms at different levels of reliability and concern. Through the application of both procedural language and expert system techniques, a prototype was developed which can readily handle a variety of relevant information and make predictions on flood hazard in Florence. The system was fairly successfully tested by processing simple meteorological data which enable a 24 hour forewarning to be released.     

中小河流山洪预警预报系统开发设计及应用

我国中小河流众多,山洪频发,洪灾损失严重,是造成人员伤亡的主要灾种。目前,我国中小河流山洪预报预警技术研究还处于初步阶段,山洪监测预警系统尚在试点建设中。介绍水利部公益性项目"中小河流突发性洪水监测与预警预报技术研究"开发的中小河流山洪预警预报原型系统,包括基于分布式水文模型、动态临界雨量的山洪预警预报方法,山洪预警预报原型系统的总体结构、软件设计与功能实现,以及在其中一个示范区江西遂川江的试运行情况,并对其实际应用进行了分析,以期为当前所开展的中小河流洪水易发区水文监测预警项目及全国山洪灾害防御非工程措施建设等工作提供参考。     

Real-time flood forecasting of the Tiber river in Rome

An adaptive, conceptual model for real-time flood forecasting of the Tiber river in Rome is proposed. This model simulates both rainfall-runoff transformations, to reproduce the contributions of 37 ungauged sub-basins that covered about 30% of the catchment area, and flood routing processes in the hydrographic network. The adaptive component of the model concerns the rainfall-runoff analysis: at any time step the whole set of the model parameters is recalibrated by minimizing the objective function constituted by the sum of the squares of the differences between observed and computed water surface elevations (or discharges). The proposed model was tested through application under real-time forecasting conditions for three historical flood events. To assess the forecasting accuracy, to support the decision maker and to reduce the possibility of false or missed warnings, confidence intervals of the forecasted water surface elevations (or discharges), computed according to a Monte Carlo procedure, are provided. The evaluation of errors in the prediction of peak values, of coefficients of persistence and of the amplitude of confidence intervals of prediction shows the possibility to develop a flood forecast model with a lead time of 12 h, which is useful for civil protection actions.     

洪水影响预报和风险预警理念与业务实践

我国是世界上洪涝灾害频繁而严重的国家之一,洪水预报预警是防汛减灾工作中重要的非工程措施和洪水防御工作的耳目和参谋。从水文行业的视角,回顾了近年来我国洪水预报预警技术与业务进展,分析了当前洪水预报预警工作面临的新形势和新要求,对比国内外同类行业发展查找了存在的差距,阐述了洪水影响预报和风险预警的定义和理念,从顶层对基于影响预报和风险预警的新一代洪水预报预警系统("国家洪水预报预警系统")总体框架进行了研究和设计,一些关键技术成果在大范围洪水早期预警业务实践中得到了探索应用,取得了较好的效果。     

河道洪水实时概率预报模型与应用

通过数据同化方法合理地将实时水文观测数据融入到洪水预报模型中,可提高洪水预报模型的实时性和精确度。选取沿程断面流量、水位和糙率系数作为代表水流状态的基本粒子,以监测断面实测水位数据作为观测信息,建立了基于粒子滤波数据同化算法的河道洪水实时概率预报模型。模型应用于黄河中下游河道洪水预报计算的结果表明,采用粒子滤波方法同化观测水位后,不仅可以直接校正水位,同时也可以有效地校正流量和糙率,为未来时刻模型预报计算提供更准确的水流初始条件和糙率取值区间,进而有效地提高模型预报结果的精度,给出合理的概率预报区间。不同预报期的预报结果表明,随着预报期的增长,同化效果减弱,模型预报结果的精度会有所降低,水位概率预报结果受粒子间糙率不同的影响不确定性增加,而流量概率预报结果受给定模型边界条件的影响不确定性降低。所提出模型可以有效同化真实水位观测数据,适合应用于实际的洪水预报工作中。     

National flood discharge mapping in Austria

This article presents the approach and the results of a study in which 30, 100 and 200 year return period flood discharges were estimated for 26,000 km of Austrian streams. Three guiding principles were adopted: combination of automatic methods and manual assessments by hydrologists to allow speedy processing and account for the local hydrological situation; combination of various sources of information including flood peak samples, rainfall data, runoff coefficients and historical flood data; and involvement of the Hydrographic Services to increase the accuracy and enhance the acceptance of results. The flood discharges for ungauged catchments were estimated by the Top-kriging approach with manual adjustment to the local flood characteristics. The adopted combination approach proved to be very efficient both in terms of the project time required and in terms of the accuracy and acceptability of the estimated flood discharges of given return periods.     

The emerging role of satellite rainfall data in improving the hydro-political situation of flood monitoring in the under-developed regions of the world

The systematic decline of in situ networks for hydrologic measurements has been recognized as a crucial limitation to advancing hydrologic monitoring in medium to large basins, especially those that are already sparsely instrumented. As a collective response, sections of the hydrologic community have recently forged partnerships for the development of space-borne missions for cost-effective, yet global, hydrologic measurements by building upon the technological advancements since the last two decades. In this article, we review the state-of-the-art on flood monitoring in medium and large ungauged basins where satellite remote sensing can facilitate development of a cost-effective mechanism. We present our review in the context of the current hydro-political situation of flood monitoring in flood-prone developing nations situated in international river basins (IRBs). Given the large number of such basins and the difficulty in acquisition of multi-faceted geophysical data, we argue that the conventional data-intensive implementation of physically based hydrologic models that are complex and distributed is time-consuming for global assessment of the utility of proposed global satellite hydrologic missions. A more parsimonious approach is justified at the tolerable expense of accuracy before such missions begin operation. Such a parsimonious approach can subsequently motivate the identified international basins to invest greater effort in conventional and detailed hydrologic studies to design a prototype flood forecasting system in an effort to overcome the hydro-political hurdles to flood monitoring. Through a modeling exercise involving an open-book watershed concept, we demonstrate the value of a parsimonious approach in understanding the utility of NASA-derived satellite rainfall products. It is critical now that real-world operational flood forecasting agencies in the under-developed world come forward to collaborate with the research community in order to leverage satellite rainfall data for greater societal benefit for inhabitants in IRBs.     

交互式洪水预报系统及关键技术研究

介绍了交互式洪水预报系统的概念和基本结构，分析了实现交互式预报的区域拓扑连接、作业表、模型参数优化、交互修正等关键技术，并以淮河交互式洪水预报系统为例，阐述了系统的组成、实时作业预报的数据流程和应用成果。在分析我国暴雨洪水特性和自然地理条件的基础上，指出了在我国开发交互式洪水预报系统的必要性和应该注意的几个主要问题。     

Evaluation of the real-time TRMM-based multi-satellite precipitation analysis for an operational flood prediction system in Nzoia Basin,Lake Victoria,Africa

Many researchers seek to take advantage of the recently available and virtually uninterrupted supply of satellite-based rainfall information as an alternative and supplement to the ground-based observations in order to implement a cost-effective flood prediction in many under-gauged regions around the world. Recently, NASA Applied Science Program has partnered with USAID and African-RCMRD to implement an operational water-hazard warning system, SERVIR-Africa. The ultimate goal of the project is to build up disaster management capacity in East Africa by providing local governmental officials and international aid organizations a practical decision-support tool in order to better assess emerging flood impacts and to quantify spatial extent of flood risk, as well as to respond to such flood emergencies more expediently. The objective of this article is to evaluate the applicability of integrating NASA’s standard satellite precipitation product with a flood prediction model for disaster management in Nzoia, sub-basin of Lake Victoria, Africa. This research first evaluated the TMPA real-time rainfall data against gauged rainfall data from the year 2002 through 2006. Then, the gridded Xinanjiang Model was calibrated to Nzoia basin for period of 1985–2006. Benchmark streamflow simulations were produced with the calibrated hydrological model using the rain gauge and observed streamflow data. Afterward, continuous discharge predictions forced by TMPA 3B42RT real-time data from 2002 through 2006 were simulated, and acceptable results were obtained in comparison with the benchmark performance according to the designated statistic indices such as bias ratio (20%) and NSCE (0.67). Moreover, it is identified that the flood prediction results were improved with systematically bias-corrected TMPA rainfall data with less bias (3.6%) and higher NSCE (0.71). Although the results justify to suggest to us that TMPA real-time data can be acceptably used to drive hydrological models for flood prediction purpose in Nzoia basin, continuous progress in space-borne rainfall estimation technology toward higher accuracy and higher spatial resolution is highly appreciated. Finally, it is also highly recommended that to increase flood forecasting lead time, more reliable and more accurate short- or medium-range quantitative precipitation forecasts is a must.     

Delineating flood risk areas in Greater Dhaka of Bangladesh using geoinformatics

This paper illustrates the development of flood hazard and risk maps in Greater Dhaka of Bangladesh using geoinformatics. Multi-temporal RADARSAT SAR and GIS data were employed to delineate flood hazard and risk areas for the 1998 historical flood. Flood-affected frequency and flood depth were estimated from multi-date SAR data and considered as hydrologic parameters for the evaluation of flood hazard. Using land-cover, gemorphic units and elevation data as thematic components, flood hazard maps were created by considering the interactive effect of flood frequency and flood water depth concurrently. Analysis revealed that a major portion of Greater Dhaka was exposed to high to very high hazard zones while a smaller portion (2.72%) was free from the potential flood hazard. Flood risk map according to administrative division showed that 75.35% of Greater Dhaka was within medium to very high risk areas of which 53.39% of areas are believed to be fully urbanized by the year 2010.     

Dynamic routing modeling for flash flood forecast in river system

A real-time flood-forecasting method coupled with the one-dimensional unsteady flow model was developed for the Danshuei River system in northern Taiwan. Based on the flow at current time, the flow at new time is calculated to provide the water stage forecasting during typhoons. Data, from two typhoons in 2000: Bilis and Nari, were used to validate and evaluate the model capability. First, the developed model was applied to validate and evaluate with and without discharge corrections at the Hsin-Hai Bridge in Tahan Stream, Chung-Cheng Bridge in Hsintien Stream, and Sir-Ho Bridge in the Keelung River. The results indicate that the calculated water stage profiles approach the observed data. Moreover, the water stage forecasting hydrograph with discharge correction is close to the observed water stage hydrograph and yields a better prediction than that without discharge correction. The model was then used to quantify the difference in prediction between different methods of real-time water stage correction. The model results reveal that water stages using the 1–6 h forecast with real-time stage correction exhibits the best lead times. The accuracy for 1–3 h lead time is higher than that for 4–6 h lead time, suggesting that the flash flood forecast in the river system is reasonably accurate for 1–3 h lead time only. The method developed is effective for flash flood forecasting and can be adopted for flood forecasting in complicated river systems.     

Forecasting flood disasters using an accelerated genetic algorithm: Examples of two case studies for China

This article discusses a rescaled range analysis model, titled AGA-R/S, that is based on an accelerated genetic algorithm. The parameter a, Hurst index of rescaled range analysis, and the recurrent time of disaster in the next time-period, were directly computed using an accelerated genetic algorithm developed by the authors. As case studies, using the AGA-R/S model, a forecast was made of the tendency for change in a time series of annual precipitation for the city of Jinhua, China. The model also forecast flooding-disaster in the city of Wuzhou, China. Results indicate that it is a relatively efficient technique to forecast the change-tendency of flood and disaster time series using the AGA-R/S model. When time series is utilized, forecasted error of the AGA-R/S model is less than with a linear least square method. The Hurst indexes of the two cities are from 0.23 to 0.24, which indicates that these time series are fractal and relatively long-term. Their fractional Brownian motion shows anti-persistence. AGA-R/S has application in forecasting the change-tendency of other natural disaster for specific time series.     

Using the DPFT approach to improve flash flood forecasting models

DPFT is a lumped approach for operational flash flood forecasting, based on the unit hydrograph. Using a multi-event alternating iterative algorithm, it identifies a robust and stable average transfer function and a consistent set of effective rainfall series associated with each event at the same time. This key ingredient allows an objective calibration of different loss functions, relating gauged precipitation and effective rainfall. A case study based on an operational French basin (545 km²) is presented. Three lumped production functions have been calibrated and compared. The results show that more elaborate models of loss functions must be proposed, and some possible directions for this are pointed out.     

Rainfall threshold determination for flash flood warning in mountainous catchments with consideration of antecedent soil moisture and rainfall pattern

Flash flood disaster is a prominent issue threatening public safety and social development throughout the world, especially in mountainous regions. Rainfall threshold is a widely accepted alternative to hydrological forecasting for flash flood warning due to the short response time and limited observations of flash flood events. However, determination of rainfall threshold is still very complicated due to multiple impact factors, particular for antecedent soil moisture and rainfall patterns. In this study, hydrological simulation approach (i.e., China Flash Flood-Hydrological Modeling System: CNFF-HMS) was adopted to capture the flash flood processes. Multiple scenarios were further designed with consideration of antecedent soil moisture and rainfall temporal patterns to determine the possible assemble of rainfall thresholds by driving the CNFF-HMS. Moreover, their effects on rainfall thresholds were investigated. Three mountainous catchments (Zhong, Balisi and Yu villages) in southern China were selected for case study. Results showed that the model performance of CNFF-HMS was very satisfactory for flash flood simulations in all these catchments, especially for multimodal flood events. Specifically, the relative errors of runoff and peak flow were within?±?20%, the error of time to peak flow was within?±?2 h and the Nash–Sutcliffe efficiency was greater than 0.90 for over 90% of the flash flood events. The rainfall thresholds varied between 93 and 334 mm at Zhong village, between 77 and 246 mm at Balisi village and between 111 and 420 mm at Yu village. Both antecedent soil moistures and rainfall temporal pattern significantly affected the variations of rainfall threshold. Rainfall threshold decreased by 8–38 and 0–42% as soil saturation increased from 0.20 to 0.50 and from 0.20 to 0.80, respectively. The effect of rainfall threshold was the minimum for the decreasing hyetograph (advanced pattern) and the maximum for the increasing hyetograph (delayed pattern), while it was similar for the design hyetograph and triangular hyetograph (intermediate patterns). Moreover, rainfall thresholds with short time spans were more suitable for early flood warning, especially in small rural catchments with humid climatic characteristics. This study was expected to provide insights into flash flood disaster forecasting and early warning in mountainous regions, and scientific references for the implementation of flash flood disaster prevention in China.     

Analysis of social vulnerability of residential community to hazards in Tianjin,China

Flood management consists many aspects such as hazard assessment, vulnerability assessment, exposure assessment, risk assessment, early warning system, damage assessment as well as risk mitigation planning. Conventional flood management are depending on the ground based monitoring of rainfall and river discharge. Many parts of the world are not covered by these sensor networks in one hand and these ground based systems are costly. Most of the tropical countries have high flood risk and low financial and institutional capacity to afford ground based system. While conventional flood management is time and cost intensive, spaceborne remote sensing provides timely and low-cost data in comparison to field observation, and is the obvious choice for most developing countries affected by flooding. Many aspects of flood management are being aided with the advancement of remote sensing technology. More precise and near real time flood detection, lead time in flood early warning system, accurate and advance inputs of hydrological models are now blessed by space technology. Many methods and approaches have been developed to overcome the constrains in the application of spaceborne remote sensing in flood management. Application of satellite remote sensing in flood hazard assessment is well documented, however, the application of space technology in other aspects of the flood management is also promising. Therefore, this review paper focuses on the applicability of spaceborne remote sensing and in most of the aspects in flood management.

     

Coupling typhoon rainfall forecasting with overland-flow modeling for early warning of inundation

Taiwan suffers from an average of three or four typhoons annually, and the inundation caused by the heavy precipitation that is associated with typhoons frequently occurs in lowlands and floodplains. Potential inundation maps have been widely used as references to set up non-structural strategies for mitigating flood hazards. However, spatiotemporal rainfall distributions must be addressed to improve the accuracy of inundation forecasting for emergency response operations. This study presents a system for 24-h-ahead early warning of inundation, by coupling the forecasting of typhoon rainfall with the modeling of overland flow. A typhoon rainfall climatology model (TRCM) is introduced to forecast dynamically the spatiotemporal rainfall distribution based on typhoon tracks. The systematic scheme for early warning of inundation based on the spatiotemporal downscaling of rainfall and 2D overland-flow modeling yields not only the extent of inundation, but also the time to maximum inundation depth. The scheme is superior to traditional early warning method referring to the maximum extent and depth of inundation determined from conditional uniform rainfall. Analytical results show that coupling TRCM with an overland-flow model yields satisfactory inundation hydrographs for warning of the extent and peak time of inundation. This study also shows that the accuracy of forecasting spatiotemporal rainfall patterns determines the performance of inundation forecasting, which is critical to emergency response operations.