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Application of data-based mechanistic modelling for flood forecasting at multiple locations in the Eden catchment in the National Flood Forecasting System (England and Wales)
D. Leedal, A. H. Weerts, P. J. Smith,K. J. Beven
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2013,
Abstract: The Delft Flood Early Warning System provides a versatile framework for real-time flood forecasting. The UK Environment Agency has adopted the Delft framework to deliver its National Flood Forecasting System. The Delft system incorporates new flood forecasting models very easily using an "open shell" framework. This paper describes how we added the data-based mechanistic modelling approach to the model inventory and presents a case study for the Eden catchment (Cumbria, UK).
Calibration of Channel Roughness for Mahanadi River, (India) Using HEC-RAS Model  [PDF]
Prabeer Kumar Parhi, R. N. Sankhua, G. P. Roy
Journal of Water Resource and Protection (JWARP) , 2012, DOI: 10.4236/jwarp.2012.410098
Abstract: Channel roughness is the most sensitive parameter in development of hydraulic model for flood forecasting and flood plane mapping. Hence, in the present study it is attempted to calibrate the channel roughness coefficient (Manning’s “n” value) along the river Mahanadi, Odisha through simulation of floods using HEC-RAS. For calibration of Manning’s “n” value the flood of year 2003 has been considered. The calibrated model, in terms of channel roughness, has been used to simulate the flood for year 2006 in the same river reach. The performance of the calibrated and validated HEC-RAS based model is tested using Nash and Sutcliffe efficiency. It is concluded from the simulation study that Mannnig’s “n” value of 0.032 gives best result for Khairmal to Munduli reach of Mahanadi River.
Flood forecasting in the Tiber catchment area: a methodological analysis
G. Calenda,M. Casaioli,C. Cosentino,R. Mantovani
Annals of Geophysics , 2000, DOI: 10.4401/ag-3680
Abstract: The most difficult step in hydrological forecasting is precipitation forecast, since rain is the most irregular and least predictable meteorological field. Numerical meteorological models are the main tool to forecast the precipitation field over river basins where floods may be expected. Object of this paper is a preliminary analysis of the appropriate methodological approach to flood forecasting in the Tiber River basin. An assessment of the flood forecasting skill of a meteorological limited area model, coupled with a lumped rainfall-runoff model, is performed. The main indications which seem to arise are that integral precipitation over the catchment area is adequately forecast in its time-evolution, but the total rainfall shows a systematic deficit with respect to observations.
FLOOD RISK FOR ROADS IN R MNA’S CATCHMENT  [PDF]
Elena Oana OLTEANU
Geographia Napocensis , 2011,
Abstract: Flood risk for roads in Ramna’s catchment. The article presents the flood risk for roads in Ramna’s catchment. The main analysis is conducted in an area that includes Gura Cali ei and Dragosloveni villages and which has been severely affected by July 2005 floods. In sub-Carpathian catchment area roads are underdeveloped, with high vulnerability due to the materials that they are constructed of (many of earth), their narrowness, their areas with subcalibrated bridges. The risk analysis was performed taking into account the historical flood of 2005. Hazard maps, flood vulnerability and flood risk maps have been made for road infrastructure. They are fundamental in making emergency management plans. With the help of this maps the most vulnerable points of the roads in that area, were found. They are represented by the areas of bridges.
Correcting the radar rainfall forcing of a hydrological model with data assimilation: application to flood forecasting in the Lez catchment in Southern France
E. Harader, V. Borrell-Estupina, S. Ricci, M. Coustau, O. Thual, A. Piacentini,C. Bouvier
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2012,
Abstract: The present study explores the application of a data assimilation (DA) procedure to correct the radar rainfall inputs of an event-based, distributed, parsimonious hydrological model. An extended Kalman filter algorithm was built on top of a rainfall-runoff model in order to assimilate discharge observations at the catchment outlet. This work focuses primarily on the uncertainty in the rainfall data and considers this as the principal source of error in the simulated discharges, neglecting simplifications in the hydrological model structure and poor knowledge of catchment physics. The study site is the 114 km2 Lez catchment near Montpellier, France. This catchment is subject to heavy orographic rainfall and characterised by a karstic geology, leading to flash flooding events. The hydrological model uses a derived version of the SCS method, combined with a Lag and Route transfer function. Because the radar rainfall input to the model depends on geographical features and cloud structures, it is particularly uncertain and results in significant errors in the simulated discharges. This study seeks to demonstrate that a simple DA algorithm is capable of rendering radar rainfall suitable for hydrological forecasting. To test this hypothesis, the DA analysis was applied to estimate a constant hyetograph correction to each of 19 flood events. The analysis was carried in two different modes: by assimilating observations at all available time steps, referred to here as reanalysis mode, and by using only observations up to 3 h before the flood peak to mimic an operational environment, referred to as pseudo-forecast mode. In reanalysis mode, the resulting correction of the radar rainfall data was then compared to the mean field bias (MFB), a corrective coefficient determined using rain gauge measurements. It was shown that the radar rainfall corrected using DA leads to improved discharge simulations and Nash-Sutcliffe efficiency criteria compared to the MFB correction. In pseudo-forecast mode, the reduction of the uncertainty in the rainfall data leads to a reduction of the error in the simulated discharge, but uncertainty from the model parameterisation diminishes data assimilation efficiency. While the DA algorithm used is this study is effective in correcting uncertain radar rainfall, model uncertainty remains an important challenge for flood forecasting within the Lez catchment.
Short period forecasting of catchment-scale precipitation. Part II: a water-balance storm model for short-term rainfall and flood forecasting
V. A. Bell,R. J. Moore
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2000,
Abstract: A simple two-dimensional rainfall model, based on advection and conservation of mass in a vertical cloud column, is investigated for use in short-term rainfall and flood forecasting at the catchment scale under UK conditions. The model is capable of assimilating weather radar, satellite infra-red and surface weather observations, together with forecasts from a mesoscale numerical weather prediction model, to obtain frequently updated forecasts of rainfall fields. Such data assimilation helps compensate for the simplified model dynamics and, taken together, provides a practical real-time forecasting scheme for catchment scale applications. Various ways are explored for using information from a numerical weather prediction model (16.8 km grid) within the higher resolution model (5 km grid). A number of model variants is considered, ranging from simple persistence and advection methods used as a baseline, to different forms of the dynamic rainfall model. Model performance is assessed using data from the Wardon Hill radar in Dorset for two convective events, on 10 June 1993 and 16 July 1995, when thunderstorms occurred over southern Britain. The results show that (i) a simple advection-type forecast may be improved upon by using multiscan radar data in place of data from the lowest scan, and (ii) advected, steady-state predictions from the dynamic model, using 'inferred updraughts', provides the best performance overall. Updraught velocity is inferred at the forecast origin from the last two radar fields, using the mass-balance equation and associated data and is held constant over the forecast period. This inference model proves superior to the buoyancy parameterisation of updraught employed in the original formulation. A selection of the different rainfall forecasts is used as input to a catchment flow forecasting model, the IH PDM (Probability Distributed Moisture) model, to assess their effect on flow forecast accuracy for the 135 km2 Brue catchment in Somerset. Keywords: rainfall forecasting, flood forecasting, weather radar, satellite, storm model
Coupling Green-Ampt infiltration method and two-dimensional kinematic wave theory for flood forecast in semi-arid catchment
L.-L. Wang,D.-H. Chen,Z.-J. Li,L.-N. Zhao
Hydrology and Earth System Sciences Discussions , 2011, DOI: 10.5194/hessd-8-8035-2011
Abstract: Due to the specific characteristics of semi-arid catchments, this paper aims to establish a grid-and-Green-Ampt-and-two-dimensional-kinematic-wave-based distributed hydrological physical model (Grid-GA-2D model) coupling Green-Ampt infiltration method and two dimensional overland flow routing model based on kinematic wave theory for flood simulation and forecasting with using GIS technology and digital elevation model (DEM). Taking into consideration the soil moisture redistribution at hillslope, Green-Ampt infiltration physical method is applied for grid-based runoff generation and two-dimensional implicit finite difference kinematic wave model is introduced to solve depressions water storing for grid-based overland flow concentration routing in the Grid-GA-2D model. The Grid-GA-2D model, the Grid-GA model with coupling Green-Ampt infiltration method and one-dimension kinematic wave theory, and Shanbei model were employed to the upper Kongjiapo catchment in Qin River, a tributary of the Yellow River, with an area of 1454 km2 for flood simulation. Results show that two grid-based distributed hydrological models perform better in flood simulation and can be used for flood forecasting in semi-arid catchments. Comparing with the Grid-GA model, the flood peak simulation accuracy of the newly developed model is higher.
Catchment parameter analysis in flood hydrology using GIS applications  [cached]
O J Gericke,J A du Plessis
Journal of the South African Institution of Civil Engineering , 2012,
Abstract: The use of Geographical Information Systems (GIS) has permeated almost every field in the engineering, natural and social sciences, offering accurate, efficient, reproducible methods for collecting, viewing and analysing spatial data. GIS do not inherently have all the hydrological simulation capabilities that complex hydrological models do, but are used to determine many of the catchment parameters that hydrological models or design flood estimation methods require. The purpose of this study was to perform catchment parameter analysis using GIS applications available in the ArcGIS TM environment. The paper will focus on the deployment of special GIS spatial modelling tools versus conventional manual methods used in conjunction with standard GIS tools to estimate typical catchment parameters, e.g. area, average catchment and watercourse slopes, main watercourse lengths and the catchment centroid. The manual catchment parameter estimation methods with GIS-based input parameters demonstrated an acceptable degree of association with the special GIS spatial modelling tools, but proved to be sensitive to biased user-input at different scale resolutions. GIS applications in an ArcGIS TM environment for the purpose of catchment parameter analyses are recommended to be used as the standard procedure in any proposed hydrological assessment.
The role of a dambo in the hydrology of a catchment and the river network downstream  [PDF]
C. J. von der Heyden,M. G. New
Hydrology and Earth System Sciences (HESS) & Discussions (HESSD) , 2003,
Abstract: Dambos are shallow, seasonally inundated wetlands and are a widespread landform in Central and Southern Africa. Owing to their importance in local agriculture and as a water resource, the hydrology of dambos is of considerable interest: varied, and sometimes contradictory, hydrological characteristics have been described in the literature. The issues in contention focus on the role of the dambo in (i) the catchment evapotranspiration (ET) budget, (ii) flood flow retardation and attenuation, and (iii) sustaining dry season flow to the river down-stream. In addition, both rainfall and groundwater have been identified as the dominant source of water to the dambo and various hydrogeological models have been proposed to describe the hydrological functions of the landform. In this paper, hydrological and geochemical data collected over a full hydrological year are used to investigate and describe the hydrological functions of a dambo in north-western Zambia. The Penman estimate of wetland ET was less than the ET from the miombo-wooded interfluve and the wetland has been shown to have little effect on flood flow retardation or attenuation. Discharge of water stored within the wetland contributed little to the dry season flow from the dambo, which was sustained primarily by groundwater discharge. Flow in a perched aquifer within the catchment soils contributed a large portion of baseflow during the rains and early dry season. This source ceased by the mid dry season, implying that the sustained middle to late dry season streamflow from the wetland is through discharge of a deeper aquifer within the underlying regolith or bedrock. This hypothesis is tested through an analysis of groundwater and wetland geochemistry. Various physical parameters, PHREEQC model results and end member mixing analysis (EMMA) suggest strongly that the deep Upper Roan dolomite aquifer is the source of sustained discharge from the wetland. Keywords: dambo, hydrology, hydrogeology, stormflow, evapotranspiration, baseflow, sponge effect, Zambia
Flash-flood forecasting by means of neural networks and nearest neighbour approach – a comparative study  [PDF]
A. Piotrowski,J. J. Napiórkowski,P.M. Rowiński
Nonlinear Processes in Geophysics (NPG) , 2006,
Abstract: In this paper, Multi-Layer Perceptron and Radial-Basis Function Neural Networks, along with the Nearest Neighbour approach and linear regression are utilized for flash-flood forecasting in the mountainous Nysa Klodzka river catchment. It turned out that the Radial-Basis Function Neural Network is the best model for 3- and 6-h lead time prediction and the only reliable one for 9-h lead time forecasting for the largest flood used as a test case.
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