1,721,075 research outputs found

    Holistic Flood Risk Assessment In Coastal Areas: The PEARL Approach

    Full text link
    Coastal floods are one of the most dangerous and harmful natural hazards affecting urban areas adjacent to shorelines. The present paper discusses the FP7-ENV-2013 EU funded PEARL (Preparing for Extreme And Rare events in coastaL regions) project which brings together world leading expertise in both the domain of hydro-engineering and risk reduction and management services to pool knowledge and practical experience in order to develop more sustainable risk management solutions for coastal communities focusing on present and projected extreme hydro-meteorological events. The PEARL approach draws upon the complexity theory and the use of complex adaptive system (CAS) models as tools to identify root causes of vulnerabilities and their multi-stressors and to analyze risk and the behavior of key actors

    Modelling Of Thermal Energy Balance In Sewer Systems

    Full text link
    Recent studies have indicated that wastewater contains relatively large amounts of thermal energy. Recovering this thermal energy can be used to decrease the CO2 footprint of the water cycle. This paper describes the development of a model to simulate the heat balance and predict the temperature in a sewer system. The model can be used to estimate the recoverable thermal energy and its dynamics. The model was verified with field data. It was concluded that the model is a powerful and accurate tool to simulate the heat balance of a sewer system at the urban district level. It was found that the recoverable heat show highly dynamic patterns, directly related to water consumption patterns. The recoverable heat depends on technical aspects as well as regulations for maximum acceptable temperature differences due to heat abstraction

    Prediction Of Hydrological Models’ Uncertainty By A Committee Of Machine Learning-Models

    No full text
    In the MLUE method (reported in Shrestha et al. [1, 2]) we run a hydrological model M for multiple realizations of parameters vectors (Monte Carlo simulations), and use this data to build a machine learning model V to predict uncertainty (quantiles) of the model M output. In this paper, for model V, we employ three machine learning techniques, namely, artificial neural networks, model tree, locally weighted regression which leads to several models results. We propose to use the simple averaging method (SA) and the weighted model averaging method (WMA) to form a committee of these models. These approaches are applied to estimate uncertainty of streamflows simulation in Bagmati catchment in Nepal. Tests on the different data sets show that WMA performs a bit better than SA.Water Resource

    Precipitation Sensor Network Optimal Design Using Time-Space Varying Correlation Structure

    No full text
    Design of optimal precipitation sensor networks is a common topic in hydrological literature, however this is still an open problem due to lack of understanding of some spatially variable processes, and assumptions that often cannot be verified. Among these assumptions lies the homoscedasticity of precipitation fields, common in hydrological practice. To overcome this, it is proposed a local intensity-variant covariance structure, which in the broad extent, provides a fully updated correlation structure as long as new data are coming into the system. These considerations of intensity-variant correlation structure will be tested in the design of a precipitation sensor network for a case study, improving the estimation of precipitation fields, and thus, reducing the input uncertainty in hydrological models, especially in the scope of rainfall-runoff models.Water Resource

    Effect Of Different Hydrological Model Structures On The Assimilation Of Distributed Uncertain Observations

    No full text
    The reliable evaluation of the flood forecasting is a crucial problem for assessing flood risk and consequent damages. Different hydrological models (distributed, semi-distributed or lumped) have been proposed in order to deal with this issue. The choice of the proper model structure has been investigated by many authors and it is one of the main sources of uncertainty for a correct evaluation of the outflow hydrograph. In addition, the recent increasing of data availability makes possible to update hydrological models as response of real-time observations. For these reasons, the aim of this work it is to evaluate the effect of different structure of a semi-distributed hydrological model in the assimilation of distributed uncertain discharge observations. The study is applied in the Brue catchment, located in UK. The first methodological step is to divide the basin in different sub-basins according to topographic characteristics. Secondly, two different structures of the semi-distributed hydrological model are implemented in order to estimate the outflow hydrograph. Then, synthetic observations of uncertain value of discharge are generated as a function of the observed and simulated value of flow at the basin outlet, and assimilated in the semi-distributed models using a Kalman Filter. Finally, different spatial patterns of sensors location are assumed to update the model state as response of the uncertain discharge observations. The results of this work pointed out that different model structures can provide different improvements of model performances, and, different optimal location of the sensors.Water Resource

    Overview Of Coupling Of Data, Models And Information Through The Web Using Existing Standards

    No full text
    Assessment of environmental status and integral safety requires combination of information from many sources, coming from either databases or increasingly via live model (scenario) simulations. Many of these models require input from one another, sometimes unidirectional, but more and more two-directional as well. Many protocols and frameworks are available for model coupling, often based on open standards and implementations. Previous overviews of coupling protocols have focused on data exchange volume, data complexity, invasiveness into existing models and support for specific programming languages. We extend the overview using recent developments in web-based protocols and focus on the suitability for internet-based data exchange. We also extend the focus of previous reviews by also taking the coupling with aggregated information products for end-users into account. We propose a hierarchical ordering of all standards for specific types of end-users.Coastal EngineeringEnvironmental Fluid Mechanic

    Committees Of Specialized Conceptual Hydrological Models: Comparative Study

    No full text
    Single hydrological model or model calibrated on single objective function often cannot capture all components of a water motion process. One possibility is building several specialized models each of which responsible for a particular sub-process (e.g., high flows or low flows), and combining them using dynamic weights – thus forming a committee model. In this study, we test two different committee models: one uses fuzzy memberships function andanother one - weights calculated from hydrological states. Specialized models are calibrated using Adaptive Cluster Covering Algorithm with different objective functions. The performances of the two different committee models are illustrated and compared.Water Resource

    Merging Top-View Lidar Data With Street-View SFM Data To Enhance Urban Flood Simulation

    No full text
    Top-view data obtainedfrom LiDAR systemshas long been used as topographic-input data for urban flood modelling applications. This high-resolution input data has considerable potential to improve urban flood modelling predictions with more detail. However, the difficulty of employing top-view data is that it may create some missing urban features because this type ofdata cannot represent anyurban features,which are hiddenunderneath other objects. These hidden featuresmay play a substantial part in diverting floodwater flowing through,especially in complex urban areas. The recent advances in Photogrammetry and Computer Vision techniques offer an opportunity to create high-resolution topographic data. By using a consumer digital camera, 2D digital photoscan betaken from different viewpoints. The so-called Structure from Motion (SfM) techniquecan usethese overlappingphotos and reconstruct theminto3D pointcloud data with a high level of accuracy and resolution,usinga cost effective approach. In this work, we create street-view SfM point-cloud data obtained from street viewpoints. We also introduce a new multi-view approach by merging top-view LiDAR data withstreet-view SfM data. This new multi-view data can be used as topographic input data for a coupled 1D-2D model. When applyingsuch newdata, the flood simulation results can highlight some flood propagations much better than using the traditional top-view LiDAR data. Therefore, it has the potential toenhance the multi-view approach into practicable flood-modelling applications for the present and future urbanizing areas.Environmental Fluid Mechanic

    Software Tools For Large Scale Interactive Hydrodynamic Modeling

    Full text link
    Developing easy-to-use software that combines components for simultaneous visualization, simulation and interaction is a great challenge. Mainly, because it involves a number of disciplines, like computational fluid dynamics, computer graphics, high-performance computing. One of the main characteristics of an interactive model is that it should provide immediate feedback to the user, for example respond to changes in model state or view settings. Features involving interaction during simulation are usually available for models with a relatively small number of computational cells and are used mainly for demonstration and educational purposes. The reason for that is that the time required to compute a single time step and render model results become significant when comparing to a simple model. It would be useful if interactive modeling would also work for models typically used in consultancy projects involving large scale simulations. This results in a number of technical challenges related to the combination of the model itself and the visualization tools (scalability, implementation of an appropriate API for control and access to the internal state). While model parallelization is increasingly addressed by the environmental modeling community, little effort has been spent on developing a highperformance interactive environment. What can we learn from the other domains where visualizations plays crucial role, such as 3D animation, gaming, virtual globes (Autodesk 3ds Max, Google Earth) that also focus on efficient interaction with 3D environments? In these domains high efficiency is usually achieved by the use of computer graphics algorithms such as surface simplification depending on current view, distance to objects, and efficient caching of the aggregated representation of object meshes. We investigate how these algorithms can be re-used in the context of interactive hydrodynamic modeling without significant changes to the model code and allowing model operation on both multi-core CPU personal computers and high-performance computer clusters

    Assimilation Of Heterogeneous Uncertain Data, Having Different Observational Errors, In Hydrological Models

    No full text
    Accurate real-time forecasting of river water level is an important issue that has to be addressed in order to prevent and mitigate water-related risk. To this end, data assimilation methods have been used to improve the forecasts ability of water model merging observations coming from stations and model simulations. As a consequence of the increasing availability of dynamic and cheap sensors, having variable life-span, space and temporal coverage, the citizens are becoming an active part in information capturing, evaluation and communication. On the other hand, it is difficult to assess the uncertain related to the observation coming from such sensors. The main objective of this work is to evaluate the influence of the observational error in the proposed assimilation methodologies used to update the hydrological model as response of distributed observations of water discharge. We tested the developed approaches on a test study area - the Brue catchment, located in the South West of England, UK. The Ensemble Kalman filter is applied to the semi-distributed hydrological model. Distributed observations of discharge are synthetically generated. Different types of observational error are introduced assuming diverse sets of probability distributions, first and second order moments. The results of this work show how the assimilation of distributed observations, can improve the hydrologic model performance with a better forecast of flood events. It is found that different observational error types can affects the model accuracy.Water Resource
    corecore