Flood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model

Frequent flood is a concern for most of the coastal regions of India. The importance of flood maps in governing strategies for flood risk management is of prime importance. Flood inundation maps are considered dependable output generated from simulation results from hydraulic models in evaluating flood risks. In the present work, a continuous hydrologic-hydraulic model has been implemented for mapping the flood, caused by the Baitarani River of Odisha, India. A rainfall time-series data were fed into the hydrologic model and the runoff generated from the model was given as an input into the hydraulic model. The study was performed using the HEC-HMS model and the FLO-2D model to map the extent of flooding in the area. Shuttle Radar Topographic Mission (SRTM) 90 m Digital Elevation Model (DEM) data, Land use/Land cover map (LULC), soil texture data of the basin area were used to compute the topographic and hydraulic parameters. Flood inundation was simulated using the FLO-2D model and based on the flow depth, hazard zones were specified using the MAPPER tool of the hydraulic model. Bhadrak District was found to be the most hazard-prone district affected by the flood of the Baitarani River. The result of the study exhibited the hydraulic model as a utile tool for generating inundation maps. An approach for assessing the risk of flooding and proper management could help in mitigating the flood. The automated procedure for mapping and the details of the study can be used for planning flood disaster preparedness in the worst affected area.

     

MERLIN: a flood hazard forecasting system for coastal river reaches

Natural Hazards - This study presents MERLIN, an innovative flood hazard forecasting system for predicting discharges and water levels at flood prone areas of coastal catchments. Discharge...     

分布式水文模型构建理论与方法述评

回顾了分布式水文模型的发展历程,分析总结了分布式水文模型的构建理论与方法,并对其关键内核——“物理基础”的含义做了深入而新颖的分析。分析了两类当前比较活跃的模型——分布式物理模型与分布式概念性模型中存在的问题及发展前景,并探讨了综合二者之长的具有物理基础的松散型分布式水文模型的构建思路,以及学者们期待中的基于确定性与随机性耦合的分布式水文模型。     

Sinkhole hazard assessment in Minnesota using a decision tree model

An understanding of what influences sinkhole formation and the ability to accurately predict sinkhole hazards is critical to environmental management efforts in the karst lands of southeastern Minnesota. Based on the distribution of distances to the nearest sinkhole, sinkhole density, bedrock geology and depth to bedrock in southeastern Minnesota and northwestern Iowa, a decision tree model has been developed to construct maps of sinkhole probability in Minnesota. The decision tree model was converted as cartographic models and implemented in ArcGIS to create a preliminary sinkhole probability map in Goodhue, Wabasha, Olmsted, Fillmore, and Mower Counties. This model quantifies bedrock geology, depth to bedrock, sinkhole density, and neighborhood effects in southeastern Minnesota but excludes potential controlling factors such as structural control, topographic settings, human activities and land-use. The sinkhole probability map needs to be verified and updated as more sinkholes are mapped and more information about sinkhole formation is obtained.     

山区小流域洪水分布模式模拟与危险性评估

流域暴雨山洪过程时空异质性强,准确评估雨洪变化特性和洪水危险性对山洪灾害防治具有重要意义。以7个降雨特征指标和6个洪水特征指标刻画流域场次雨洪特性,采用中国山洪水文模型和洪水频率指标相结合,模拟和评估口前流域洪水过程及其危险性。结果表明：场次洪水洪峰模数、洪峰时间偏度、高脉冲历时占比、涨落洪速率与降雨总量、平均雨量、最大雨强、雨峰位置系数、基尼系数等降雨特征指标显著相关,三场致灾洪水过程的降雨均呈现量级大、强度大、历时短、暴雨中心偏中下游的特点;率定期和验证期的平均径流深相对误差均在9%以内,平均洪峰流量相对误差均在11%以内,平均峰现时间误差均在1.7 h以内,平均Nash-Sutcliffe系数为0.80和0.76;各场次洪水有0.0%～93.3%的河段流量达到一般危险及以上等级,三场致灾洪水过程的危险性等级最高,分别有80.0%、35.0%和1.7%的小流域河段流量达到高危险及以上等级。研究可为山区小流域暴雨洪水危险性评估、灾害响应和复盘等提供技术支撑。     

Characterizing flood hazard risk in data-scarce areas,using a remote sensing and GIS-based flood hazard index

The frequency in occurrence and severity of floods has increased globally. However, many regions around the globe, especially in developing countries, lack the necessary field monitoring data to characterize flood hazard risk. This paper puts forward methodology for developing flood hazard maps that define flood hazard risk, using a remote sensing and GIS-based flood hazard index (FHI), for the Nyamwamba watershed in western Uganda. The FHI was compiled using analytical hierarchy process and considered slope, flow accumulation, drainage network density, distance from drainage channel, geology, land use/cover and rainfall intensity as the flood causative factors. These factors were derived from Landsat, SRTM and PERSIANN remote sensing data products, except for geology that requires field data. The resultant composite FHI yielded a flood hazard map pointing out that over 11 and 18% of the study area was very highly and highly susceptible to flooding, respectively, while the remaining area ranged from medium to very low risk. The resulting flood hazard map was further verified using inundation area of a historical flood event in the study area. The proposed methodology was effective in producing a flood hazard map at the watershed local scale, in a data-scarce region, useful in devising flood mitigation measures.     

Shallow landslide hazard assessment using a physically based model and digital elevation data

 A model for the analysis of topographic influence on shallow landslide initiation is applied to an experimental mountain basin where high-resolution digital elevation data are available: the Cordon catchment (5 km²) located in northern Italy. The model delineates those areas most prone to shallow landsliding due to surface topographic effects on hydrologic response. The model is composed of two parts: a steady-state model for shallow sub-surface runoff and an infinite-slope Coulomb failure model which assumes that the soil is cohesionless at failure. An inventory of landslide scars is used to document sites of instability and to provide a test of model performance by comparing observed landslide locations with model predictions. The model reproduces the observed distribution of landslide locations in a consistent way, although spatial variations in soil strength and transmissivity, which are not accounted for in the model, influence specific distribution of landslide areas within regions of similar topographic control. Received: 15 October 1996 · Accepted: 25 June 1997     

Shallow landslide hazard assessment using a three-dimensional deterministic model in a mountainous area

Shallow landslides are common in mountainous areas after intense rainfall. Of all landslide hazard assessment methods, deterministic methods provide the best quantitative information on landslide hazard. However, they require a large amount of detailed in situ data, derived from laboratory tests and field measurements, and therefore it is difficult to apply them over large areas. One of the most important input parameters is soil depth. For large areas, it is impossible to obtain soil depth through field measurements. To overcome this difficulty, a statistics-based regression analysis is used to evaluate soil depths. All the terrain attributes that control soil depths are selected as influential factors. By using multi-linear regression, the soil depths at each location can be predicted. Slope stability analysis can then be performed using deterministic methods with the evaluated soil depths. The study area is divided into slope units. For each slope unit, Monte-Carlo simulation and a GIS-based 3D limit equilibrium model are used to locate the critical slip surface and calculate the corresponding safety factor. The effectiveness of the proposed method has been tested by applying it to a mountainous area in Japan.     

Shallow landslides in pyroclastic soils: a distributed modelling approach for hazard assessment

An effective assessment of shallow landslide hazard requires spatially distributed modelling of triggering processes. This is possible by using physically based models that allow us to simulate the transient hydrological and geotechnical processes responsible for slope instability. Some simplifications are needed to address the lack of data and the difficulty of calibration over complex terrain at the catchment's scale. We applied two simple hydrological models, coupled with the infinite slope stability analysis, to the May 1998 landslide event in Sarno, Southern Italy. A quasi-dynamic model (Barling et al., 1994) was used to model the contribution to instability of lateral flow by simulating the time-dependent formation of a groundwater table in response to rainfall. A diffusion model [Water Resour. Res. 36 (2000) 1897] was used to model the role of vertical flux by simulating groundwater pressures that develop in response to heavy rainstorms. The quasi-dynamic model overestimated the slope instability over the whole area (more than 16%) but was able to predict correctly slope instability within zero order basins where landslides occurred and developed into large debris flows. The diffusion model simulated correctly the triggering time of more than 70% of landslides within an unstable area amounting to 7.3% of the study area. These results support the hypothesis that both vertical and lateral fluxes were responsible for landslide triggering during the Sarno event, and confirm the utility of such models as tools for hazard planning and land management.     

Hurricane flood risk assessment for the Yucatan and Campeche State coastal area

Natural Hazards - In this study, the first ever Sea, Lake, Overland Surges from Hurricanes (SLOSH) grid was built for the Yucatan Peninsula. The SLOSH model was used to simulate storm surges in the...     

Vulnerability assessment for preliminary flood risk mapping and management in coastal areas

Despite continuing technological advancement in hazard and vulnerability assessment, risk modelling and hazard mitigation techniques, losses to disasters associated with natural hazards continue and in some cases are increasing across Europe and worldwide. This paper focuses on the need to bridge the gap between technical solutions and the sociopolitical contexts in which these are produced, to better understand and create more effective risk management regimes. We do so with application of the science–policy co-production frame to landslide risk management in Italy. The methodology deployed included a desk study informed by semi-structured interviews carried out with selected key stakeholders at national, regional and municipal level. We propose a normative and analytical framework for transferring co-production into natural hazard research by presenting a matrix identifying four contexts within which co-production may unfold. The matrix is based on two axes, which distinguish between innovation and its absence in science and policy domains. We examine several examples of co-production, such as the water–soil integrated approach to risk management or the implementation of hazard/risk assessment. The results highlight that the insulation of science from the institutional context within which knowledge is produced and used is a very problematic issue. This often hinders the implementation of desirable policies and undermines the effectiveness of interventions. Moreover, innovation in science and policy does not automatically result in successful solutions for landslide risk management. Finally, results confirm the utility of co-production but also highlight methodological challenges associated with the introduction of this new conceptual paradigm into the well-structured communities of scientists and policy-makers.     

Validation of soil moisture simulation with a distributed hydrologic model (WetSpa)

The objective of this paper is to test the ability of a spatially distributed hydrologic model (WetSpa) to simulate soil moisture. The test is conducted in the Baron Fork river basin (Oklahoma, USA), where soil moisture has been recorded on a daily basis at the WEST site soil moisture monitoring station of the Oklahoma Mesonet. The model is calibrated by comparing hourly simulated and observed river flows at Eldon gaging station from October 1, 1995 to December 31, 1996. The model performance to predict hourly river flows is verified by comparing model estimates and observations from January 1, 1997 to December 31, 2000. Next, the model predictions of soil moisture are compared with observations of WEST site soil moisture monitoring station for the same validation period. The observations are well reproduced by the model with errors that are within range of the observation accuracy, although the predictions show somewhat more abrupt temporal fluctuations as the whole root zone is considered to react instantaneously to precipitation events. The good performance compared to other studies is especially attributed to the quality of the rainfall data provided by weather radars. It is concluded that the performance of the model to predict soils moisture is promising, although spatial patterns still have to be verified.     

Coastal erosion hazard and vulnerability assessment for southern coastal Tamil Nadu of India by using remote sensing and GIS

The measurement and recording of the height and spatial extent reached by coastal storm surges is fundamental to scientific progress in understanding these phenomena. Such information is required for better prediction and for risk assessment. Model-based evaluation of increasing delta vulnerability, for example, cannot be tested without long-term, consistent, and sustained observation of actual events. Also, storm surges occur within the temporal context of tidal variation, which must first be characterized through observation. Present standard approaches for measuring storm surges are not optimum. Thus, tidal gauges provide information at one point, whereas the heights reached by surges vary spatially. Also, post-surge ground surveys are expensive, laborious, and commonly lack comparison to similar data obtained for previous surges or for high tides. The advent of moderate spatial resolution, high temporal resolution remote sensing initiated by the launch of the two NASA MODIS sensors greatly reduces these constraints. For over a decade, daily coverage of most coastal land areas, though restricted by cloud cover, has systematically captured the maximum extents reached by both high tides and by storm surges. Automated water classification algorithms are now transforming the incoming image data into GIS water boundary files, again at daily or near-daily time steps. This paper provides a retrospective view of sample storm surges as mapped via these sensors and describes: (a) the present, MODIS-based surface water surveillance system, (b) the mapping enhancement to be provided by frequent-repeat, wide-swath satellite radar imaging, and (c) the emerging prospects for routine global surveillance of storm surge events. Such will be necessary if long-term trends are to be recognized, characterized, and understood, along coastal zones now being affected by both increasing subsidence and rising sea level.     

A methodology for urban micro-scale coastal flood vulnerability and risk assessment and mapping

Natural Hazards - Wind gusts are a major cause of damage to property and the natural environment and a source of noise in seismic networks such as the USArray Transportable Array. Wind gusts cause...     

Methodological study of coastal geological hazard assessment based on GIS

The current researches on risk assessment of geological disasters mainly focus on unexpected disasters such as collapses, landslides and mud-rock flows etc. As the convergence zone of land and sea, coastal zone is the most active and complex area of interactions of lithosphere, hydrosphere, atmosphere, biosphere and anthroposphere. The ecological environment of coastal zone is very fragile, so further systematical research on coastal geological hazard assessment and prevention is in urgent need. The author begins with the definition and research contents and selects three typical coastal geological disasters, namely, the seawater intrusion, coastline change and sea-level rise as the objects of study. The systematic analysis and study on assessment system and methods are conducted, hazard assessment factors are selected, and a completely set of coastal disaster assessment system is established based on the technique of GIS. We took Bao’an District of Shenzhen City as an example and carried out a case study.     

基于力学过程的蓄滞洪区洪水风险评估模型及应用

为定量评估分蓄洪工程启用过程中蓄滞洪区的洪水风险等级,创建了基于力学过程的蓄滞洪区洪水风险评估模型。该模型采用二维水动力学模块计算蓄滞洪区的洪水演进过程,利用洪水中人体跌倒失稳公式及洪水中房屋、农作物损失的计算关系式,评估各类受淹对象的洪水风险等级。然后将二维水动力学模块计算的洪水要素与两个物理模型试验值进行对比,表明二维水动力学模块的计算精度良好。最后计算了荆江分洪工程启用时分洪区内洪水的演进过程,并评估洪灾中群众的危险等级和财产损失。计算结果表明:洪水演进至140 h时,蓄滞洪区群众、房屋、水稻和棉花的平均损失率分别为85%、59%、63%和72%。模型中提出的采用基于受淹对象失稳机制的洪水风险分析方法,比以往经验水深法划分风险等级的适用性更好,不仅能为洪水风险管理及蓄滞洪区启用标准制定提供参考,也能推广应用于溃坝或堰塞湖溃决等极端洪水风险评估。