scholarly journals Dynamic Flood Inundation Forecast for the City of Kulmbach Using Offline Two-Dimensional Hydrodynamic Models

10.29007/c4gq ◽  
2018 ◽  
Author(s):  
Punit Bhola ◽  
Jorge Leandro ◽  
Iris Konnerth ◽  
Kanwal Amin ◽  
Markus Disse
Keyword(s):  
Real Time ◽  
Dynamic Models ◽  
Water Levels ◽  
Flood Inundation ◽  
Hydrological Models ◽  
Hydrodynamic Models ◽  
Database Queries ◽  
Inundation Maps ◽  
Inundation Map ◽  
The City

The paper presents a new methodology for hydrodynamic-based flood forecast focusing on sce- nario generation and database queries to select the appropriate flood inundation map in real-time. In operational flood forecasting, discharges are forecast at specific gauges using hydrological models. The water levels are obtained from a rating curve designed for each respective gauge. Particularly for higher discharges when the flow over-spills the side banks, these curves are highly uncertain. Hy- drodynamic models are then required to produce realistic inundation maps and water levels. Hydro- dynamic models are computationally expensive and therefore not feasible for real-time forecasting. Alternatively, pre-calculated inundation maps can be stored in a database which contains a substantial number of scenarios, and used for extracting the most likely map in real-time. This study investigates the application of offline inundation forecast in the city Kulmbach in Germany.

scholarly journals Framework for Offline Flood Inundation Forecasts for Two-Dimensional Hydrodynamic Models

Geosciences ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 346 ◽  
Author(s):  
Punit Bhola ◽  
Jorge Leandro ◽  
Markus Disse
Keyword(s):  
Real Time ◽  
Warning System ◽  
Flood Inundation ◽  
Hydrological Models ◽  
Hydrodynamic Models ◽  
Database Queries ◽  
Inundation Maps ◽  
Online Maps ◽  
The City ◽  
Selection Of

The paper presents a new methodology for hydrodynamic-based flood forecast that focuses on scenario generation and database queries to select appropriate flood inundation maps in real-time. In operational flood forecasting, only discharges are forecasted at specific gauges using hydrological models. Hydrodynamic models, which are required to produce inundation maps, are computationally expensive, hence not feasible for real-time inundation forecasting. In this study, we have used a substantial number of pre-calculated inundation maps that are stored in a database and a methodology to extract the most likely maps in real-time. The method uses real-time discharge forecast at upstream gauge as an input and compares it with the pre-recorded scenarios. The results show satisfactory agreements between offline inundation maps that are retrieved from a pre-recorded database and online maps, which are hindcasted using historical events. Furthermore, this allows an efficient early warning system, thanks to the fast run-time of the proposed offline selection of inundation maps. The framework is validated in the city of Kulmbach in Germany.

scholarly journals A 2D Real-Time Flood Forecast Framework Based on a Hybrid Historical and Synthetic Runoff Database

Water ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 114
Author(s):  
Giampaolo Crotti ◽  
Jorge Leandro ◽  
Punit Kumar Bhola
Keyword(s):  
Real Time ◽  
River Discharge ◽  
Hybrid Approach ◽  
Flood Forecast ◽  
Hydrological Models ◽  
Hydrodynamic Models ◽  
Inundation Maps ◽  
Natural Streams ◽  
Historical Database ◽  
Non Gaussian

Operational real-time flood forecast is often done on the prediction of discharges at specific gauges using hydrological models. Hydrodynamic models, which can produce inundation maps, are computationally demanding and often cannot be used directly for that purpose. The FloodEvac framework has been developed in order to enable 2D flood inundations map to be forecasted at real-time. The framework is based on a database of pre-recorded synthetic events. In this paper, the framework is improved by generating a database based on rescaled historical river discharge events. This historical database includes a wider variety of runoff curves, including non-Gaussian and multi-peak shapes that better reflect the characteristics and the behavior of the natural streams. Hence, a hybrid approach is proposed by joining the historical and the existing synthetic database. The increased number of scenarios in the hybrid database allows reliable predictions, thus improving the robustness and applicability of real-time flood forecasts.

Integrated real-time flood forecasting and inundation analysis in small-medium streams

2019 ◽  
Author(s):  
Byunghyun Kim ◽  
Seung-Yong Choi ◽  
Kun-Yeun Han
Keyword(s):  
Real Time ◽  
Fuzzy Inference ◽  
Flood Forecasting ◽  
Water Levels ◽  
Subtractive Clustering ◽  
Lead Times ◽  
Hydrodynamic Models ◽  
Inference System ◽  
Neuro Fuzzy ◽  
Input Variables

This study presents the application of an adaptive neuro-fuzzy inference system (ANFIS) and one dimensional (1-D) and two dimensional (2-D) hydrodynamic models to improve the problems of hydrological models currently used for flood forecasting in small-medium streams of South Korea. The optimal combination of input variables (e.g., rainfall and water level) in ANFIS was selected based on a statistical analysis of the observed and forecasted values. Two membership functions (MFs) and two ANFIS rules were determined by the subtractive clustering (SC) approach in the processes of training and checking. The developed ANFIS was applied to Jungrang Stream and water levels for six lead times (0.5, 1.0, 1.5, 2.0, 2.5 and 3.0 hour) were forecasted. Based on point forecasted water levels by ANFIS, 1-D section flood forecast and 2-D spatial inundation analysis were carried out. This study demonstrated that the proposed methodology can forecast flooding based only on observed data without abundant physical, and can be performed in real time by integrating point- and section flood forecasting and spatial inundation analysis.

scholarly journals Using radar altimetry to update a large-scale hydrological model of the Brahmaputra river basin

2013 ◽  
Vol 45 (1) ◽  
pp. 148-164 ◽  
Author(s):  
Flemming Finsen ◽  
Christian Milzow ◽  
Richard Smith ◽  
Philippa Berry ◽  
Peter Bauer-Gottwein
Keyword(s):  
Real Time ◽  
River Basin ◽  
Large Scale ◽  
Hydrological Model ◽  
Water Levels ◽  
Hydrological Models ◽  
Altimetry Data ◽  
Brahmaputra River ◽  
Radar Altimetry ◽  
Rating Curves

Measurements of river and lake water levels from space-borne radar altimeters (past missions include ERS, Envisat, Jason, Topex) are useful for calibration and validation of large-scale hydrological models in poorly gauged river basins. Altimetry data availability over the downstream reaches of the Brahmaputra is excellent (17 high-quality virtual stations from ERS-2, 6 from Topex and 10 from Envisat are available for the Brahmaputra). In this study, altimetry data are used to update a large-scale Budyko-type hydrological model of the Brahmaputra river basin in real time. Altimetry measurements are converted to discharge using rating curves of simulated discharge versus observed altimetry. This approach makes it possible to use altimetry data from river cross sections where both in-situ rating curves and accurate river cross section geometry are not available. Model updating based on radar altimetry improved model performance considerably. The Nash–Sutcliffe model efficiency increased from 0.77 to 0.83. Real-time river basin modelling using radar altimetry has the potential to improve the predictive capability of large-scale hydrological models elsewhere on the planet.

scholarly journals Real-time forecasting of typhoon inundation extent in a partially-gauged area through the integration of ARX-based models and a geographic information system

2016 ◽  
Author(s):  
Huei-Tau Ouyang ◽  
Yi-Chun Chen
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Real Time ◽  
Geographic Information ◽  
Water Levels ◽  
Terrain Analysis ◽  
Inundation Maps ◽  
Inundation Extent ◽  
Elevation Model ◽  
Representative Points

Abstract. This study presents a methodology for forecasting the extent of inundation and depth of distribution during typhoons in real-time. The proposed approach involves the construction of ARX and ARMAX models capable of predicting water-levels at the locations of on-site gauging stations and representative points located at the outlets of the sub-areas obtained by terrain analysis using a geographic information system. The models are constructed based on historical typhoon data and the results of numerical simulations related to inundation. A database comprising layers of inundation maps related to water-levels in each sub-area based on the assumption of flat-water and the digital elevation model (DEM) of the area were assembled prior to the typhoon. Water-levels during the typhoon are forecast using the constructed models, whereupon inundation sub-maps associated with the forecasted water-levels are extracted from the database. The resulting inundation map is comparable to that obtained using Synthetic Aperture Radar. Processing can be conducted in real-time and requires very little computational resources. This provides valuable lead time in which to conduct efforts aimed at damage mitigation during a typhoon.

scholarly journals Real-time remote sensing driven river basin modelling using radar altimetry

2010 ◽  
Vol 7 (5) ◽  
pp. 8347-8385 ◽  
Author(s):  
S. J. Pereira-Cardenal ◽  
N. D. Riegels ◽  
P. A. M. Berry ◽  
R. G. Smith ◽  
A. Yakovlev ◽  
...  
Keyword(s):  
Real Time ◽  
River Basin ◽  
Reanalysis Data ◽  
Water Levels ◽  
Hydrological Models ◽  
Altimetry Data ◽  
Reservoir Water ◽  
Radar Altimetry ◽  
Modelling Approach

Abstract. Many river basins have a weak in-situ hydrometeorological monitoring infrastructure. However, water resources practitioners depend on reliable hydrological models for management purposes. Remote sensing (RS) data have been recognized as an alternative to in-situ hydrometeorological data in remote and poorly monitored areas and are increasingly used to force, calibrate, and update hydrological models. In this study, we evaluate the potential of informing a river basin model with real-time radar altimetry measurements over reservoirs. We present a lumped, conceptual, river basin water balance modelling approach based entirely on RS and reanalysis data: precipitation was obtained from the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), temperature from the European Centre for Medium-Range Weather Forecast's (ECMWF) Operational Surface Analysis dataset and reference evapotranspiration was derived from temperature data. The Ensemble Kalman Filter was used to assimilate radar altimetry (ERS2 and Envisat) measurements of reservoir water levels. The modelling approach was applied to the Syr Darya River Basin, a snowmelt-dominated basin with large topographical variability, several large reservoirs and scarce hydrometeorological data that is shared between 4 countries with conflicting water management interests. The modelling approach was tested over a historical period for which in-situ reservoir water levels were available. Assimilation of radar altimetry data significantly improved the performance of the hydrological model. Without assimilation of radar altimetry data, model performance was limited, probably because of the size and complexity of the model domain, simplifications inherent in model design, and the uncertainty of RS and reanalysis data. Altimetry data assimilation reduced the mean error of the simulated reservoir water levels from 4.7 to 1.9 m, and overall model RMSE from 10.3 m to 6.7 m. Because of its easy accessibility and immediate availability, radar altimetry lends itself to being used in real-time hydrological applications. As an impartial source of information about the hydrological system that can be updated in real time, the modelling approach described here can provide useful medium-term hydrological forecasts to be used in water resources management.

scholarly journals Risk-Based and Hydrodynamic Pluvial Flood Forecasts in Real Time

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1895
Author(s):  
Julian Hofmann ◽  
Holger Schüttrumpf
Keyword(s):  
Real Time ◽  
Flood Risk ◽  
High Efficiency ◽  
Computation Time ◽  
Warning Systems ◽  
Hydrodynamic Models ◽  
Model Concept ◽  
Urban Flood ◽  
Real Time Simulations ◽  
The City

The effective forecast and warning of pluvial flooding in real time is one of the key elements and remaining challenges of an integrated urban flood risk management. This paper presents a new methodology for integrating risk-based solutions and 2D hydrodynamic models into the early warning process. Whereas existing hydrodynamic forecasting methods are based on rigid systems with extremely high computational demands, the proposed framework builds on a multi-model concept allowing the use of standard computer systems. As a key component, a pluvial flood alarm operator (PFA-Operator) is developed for selecting and controlling affected urban subcatchment models. By distributed computing of hydrologic independent models, the framework overcomes the issue of high computational times of hydrodynamic simulations. The PFA-Operator issues warnings and flood forecasts based on a two-step process: (1) impact-based rainfall thresholds for flood hotspots and (2) hydrodynamic real-time simulations of affected urban subcatchments models. Based on the open-source development software Qt, the system can be equipped with interchangeable modules and hydrodynamic software while building on the preliminary results of flood risk analysis. The framework was tested using a historic pluvial flood event in the city of Aachen, Germany. Results indicate the high efficiency and adaptability of the proposed system for operational warning systems in terms of both accuracy and computation time.

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