Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions

The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for the development of state-of-the-art early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km2) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.

Flood Risk Management In Small Urban River Using A Sustainable Urban Drainage System: Wortley Beck, Leeds, Uk

In the UK, urban river basins are particularly vulnerable to flash floods due to short and intense rainfall. This paper presents potential flood resilience approaches for the highly urbanised Wortley Beck river basin, south west of the Leeds city centre. The reach of Wortley Beck is approximately 6km long with contributing catchment area of 30km2 that drain into the River Aire. Lower Wortley has experienced regular flooding over the last few years from a range of sources, including Wortley Beck and surface and ground water, that affects properties both upstream and downstream of Farnley Lake as well as Wortley Ring Road. This has serious implications for society, the environment and economy activity in the City of Leeds. The first stage of the study involves systematically incorporating Wortley Beck’s land scape features on an Arc-GIS platform to identify existing green features in the region. This process also enables the exploration of potential blue green features: green spaces, green roofs, water retention ponds and swales at appropriate locations and connect them with existing green corridors to maximize their productivity. The next stage is involved in developing a detailed 2D urban flood inundation model for the Wortley Beck region using the CityCat model. CityCat is capable to model the effects of permeable/impermeable ground surfaces and buildings/roofs to generate flood depth and velocity maps at 1m caused by design storm events. The final stage of the study is involved in simulation of range of rainfall and flood event scenarios through CityCat model with different blue green features. Installation of other hard engineering individual property protection measures through water butts and flood walls are also incorporated in the CityCat model. This enables an integrated sustainable flood resilience strategy for this region.

Desenvolvimento de um sistema de alerta de enchente aplicado aos planos de defesa civil em áreas de risco no estado do Pará utilizando Sistema de Informações Geográficas (SIG), caso: cidade de Marabá

A presente dissertação desenvolveu um Sistema de Alerta de Enchentes para a Cidade de Marabá, localizada na confluência dos rios Itacaiúnas e Tocantins, a 440 km da cidade de Belém, capital do Estado do Pará. O Sistema de Alerta de Enchentes foi desenvolvido com base no modelo hidrológico MOD-4B incorporado a um Sistema de Informações Geográficas. Esse sistema permite prever as variações do nível do Rio Tocantins ao longo do ano, de modo a acompanhar a evolução da cheia com antecedência de 4 dias, o que torna possível uma ação eficiente da defesa civil. O modelo de previsão utilizou como referência as réguas linimétricas localizadas nos rios Tocantins e Araguaia nas cidades de Carolina e Conceição do Araguaia, distantes aproximadamente 225 e 270 km, respectivamente, da cidade de Marabá. O sistema utiliza o software de geoprocessamento ArcView 3.3, que teve implementada uma interface desenvolvida através da linguagem de programação orientada a objetos Avenue, com a finalidade de rodar o aplicativo do modelo hidrológico. O uso de menus e janelas customizados do sistema possibilitou o acesso a dados espaciais e tabelas de dados relacionais e/ou banco de dados cadastral, além de módulos de análise espacial e de visualização de dados geográficos em um Sistema de Informações Geográficas (SIG), possibilitando a previsão de enchentes na forma de mapas, tabelas e relatórios com a indicação das áreas inundadas para os períodos de 4, 3, 2 e 1 dia de antecedência do evento de enchente. O Sistema permitiu identificar os imóveis e as ruas atingidos, e possibilitará através de levantamentos futuros quantificar a população afetada e os prejuízos causados pelo desastre, facilitando que a defesa civil execute planos de ação para enfrentamento eficiente antes, durante e depois da ocorrência da enchente.

Study of a wind-wave numerical model and its integration with ocean and oil-spill numerical models

The ability to represent the transport and fate of an oil slick at the sea surface is a formidable task. By using an accurate numerical representation of oil evolution and movement in seawater, the possibility to asses and reduce the oil-spill pollution risk can be greatly improved. The blowing of the wind on the sea surface generates ocean waves, which give rise to transport of pollutants by wave-induced velocities that are known as Stokes’ Drift velocities. The Stokes’ Drift transport associated to a random gravity wave field is a function of the wave Energy Spectra that statistically fully describe it and that can be provided by a wave numerical model. Therefore, in order to perform an accurate numerical simulation of the oil motion in seawater, a coupling of the oil-spill model with a wave forecasting model is needed. In this Thesis work, the coupling of the MEDSLIK-II oil-spill numerical model with the SWAN wind-wave numerical model has been performed and tested. In order to improve the knowledge of the wind-wave model and its numerical performances, a preliminary sensitivity study to different SWAN model configuration has been carried out. The SWAN model results have been compared with the ISPRA directional buoys located at Venezia, Ancona and Monopoli and the best model settings have been detected. Then, high resolution currents provided by a relocatable model (SURF) have been used to force both the wave and the oil-spill models and its coupling with the SWAN model has been tested. The trajectories of four drifters have been simulated by using JONSWAP parametric spectra or SWAN directional-frequency energy output spectra and results have been compared with the real paths traveled by the drifters.

Stima dei parametri di modelli idrologici mediante ottimizzazione dell’utilità

Tradizionalmente, l'obiettivo della calibrazione di un modello afflussi-deflussi è sempre stato quello di ottenere un set di parametri (o una distribuzione di probabilità dei parametri) che massimizzasse l'adattamento dei dati simulati alla realtà osservata, trattando parzialmente le finalità applicative del modello. Nel lavoro di tesi viene proposta una metodologia di calibrazione che trae spunto dell'evidenza che non sempre la corrispondenza tra dati osservati e simulati rappresenti il criterio più appropriato per calibrare un modello idrologico. Ai fini applicativi infatti, può risultare maggiormente utile una miglior rappresentazione di un determinato aspetto dell'idrogramma piuttosto che un altro. Il metodo di calibrazione che viene proposto mira a valutare le prestazioni del modello stimandone l'utilità nell'applicazione prevista. Tramite l'utilizzo di opportune funzioni, ad ogni passo temporale viene valutata l'utilità della simulazione ottenuta. La calibrazione viene quindi eseguita attraverso la massimizzazione di una funzione obiettivo costituita dalla somma delle utilità stimate nei singoli passi temporali. Le analisi mostrano come attraverso l'impiego di tali funzioni obiettivo sia possibile migliorare le prestazioni del modello laddove ritenute di maggior interesse per per le finalità applicative previste.

Dynamic SLA management with forecasting using multi-objective optimization

Cost-efficient operation while satisfying performance and availability guarantees in Service Level Agreements (SLAs) is a challenge for Cloud Computing, as these are potentially conflicting objectives. We present a framework for SLA management based on multi-objective optimization. The framework features a forecasting model for determining the best virtual machine-to-host allocation given the need to minimize SLA violations, energy consumption and resource wasting. A comprehensive SLA management solution is proposed that uses event processing for monitoring and enables dynamic provisioning of virtual machines onto the physical infrastructure. We validated our implementation against serveral standard heuristics and were able to show that our approach is significantly better.

Sensitivity of the WRF model to PBL parametrisations and nesting techniques: evaluation of wind storms over complex terrain

Simulating surface wind over complex terrain is a challenge in regional climate modelling. Therefore, this study aims at identifying a set-up of the Weather Research and Forecasting Model (WRF) model that minimises system- atic errors of surface winds in hindcast simulations. Major factors of the model configuration are tested to find a suitable set-up: the horizontal resolution, the planetary boundary layer (PBL) parameterisation scheme and the way the WRF is nested to the driving data set. Hence, a number of sensitivity simulations at a spatial resolution of 2 km are carried out and compared to observations. Given the importance of wind storms, the analysis is based on case studies of 24 historical wind storms that caused great economic damage in Switzerland. Each of these events is downscaled using eight different model set-ups, but sharing the same driving data set. The results show that the lack of representation of the unresolved topography leads to a general overestimation of wind speed in WRF. However, this bias can be substantially reduced by using a PBL scheme that explicitly considers the effects of non-resolved topography, which also improves the spatial structure of wind speed over Switzerland. The wind direction, although generally well reproduced, is not very sensitive to the PBL scheme. Further sensitivity tests include four types of nesting methods: nesting only at the boundaries of the outermost domain, analysis nudging, spectral nudging, and the so-called re-forecast method, where the simulation is frequently restarted. These simulations show that restricting the freedom of the model to develop large-scale disturbances slightly increases the temporal agreement with the observations, at the same time that it further reduces the overestimation of wind speed, especially for maximum wind peaks. The model performance is also evaluated in the outermost domains, where the resolution is coarser. The results demonstrate the important role of horizontal resolution, where the step from 6 to 2 km significantly improves model performance. In summary, the combination of a grid size of 2 km, the non-local PBL scheme modified to explicitly account for non-resolved orography, as well as analysis or spectral nudging, is a superior combination when dynamical downscaling is aimed at reproducing real wind fields.

Flood plain information, Spring Valley Creek, San Diego County, California /

Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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"ILENR/RE-94/08."