Mathematical modelling for formation and propagation of floods in a data-deficient basin

Prasad, Triyugi; Wakhlu, Omkar N.

doi:10.1016/0022-1694(84)90218-x

Cited by 3 publications

(2 citation statements)

References 3 publications

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“…In contrast to the above stringent data requirements, in many basins in developing countries (Prasad & Wakhlu, 1984) and even in developed countries a common situation consists of the following: first, a network of non-continuously recording devices has been providing data for a long period (e.g. 20-30 years or more) at a low sampling frequency, mostly once daily, and at relatively high spatial density; second, a few recording devices have been operated at inadequate spatial density and for short periods that are usually related to flood studies.…”

Section: Open For Discussion Until 1 October 2000mentioning

confidence: 99%

Real-time flood forecasting with the use of inadequate data

Nalbantis

2000

Hydrological Sciences Journal

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A modelling scheme is developed for real-time flood forecasting. It is composed of (a) a rainfall forecasting model, (b) a conceptual rainfall-runoff model, and (c) a stochastic error model of the ARMA family for forecast error correction. Initialization of the rainfall-runoff model is based on running this model on a daily basis for a certain period prior to the flood onset while parameters of the error model are updated through the Recursive Least Squares algorithm. The scheme is suitable for the early stages of operation of flood forecasting systems in the presence of inadequate historical data. A validation framework is set up which simulates real-time flood forecasting conditions. Thus, the effects of the procedures for rainfall-runoff model initialization, forecast error correction and rainfall forecasting are assessed. Two wellknown conceptual rainfall-runoff models (the Soil Moisture Accounting model of the US National Weather Service River Forecast Service^SMA-NWSRFS and TANK) together with data from a Greek basin are used for illustration purposes. Prévision de crues en temps réel à l'aide de données inadéquatesRésumé Nous avons développé un schéma de modélisation ayant pour but la prévision des crues en temps réel. Ce schéma comprend: (a) un modèle de prévision des précipitations, (b) un modèle conceptuel pluie-débit, et (c) un modèle stochastique de la famille ARMA pour corriger les erreurs de prévision. L'initialisation du modèle pluie-débit est réalisée par le modèle lui même exécuté au pas de temps journalier pour une certaine durée de temps précédant la crue. Les paramètres du modèle d'erreur sont mis à jour grâce à l'algorithme des moindres carrés récursif. Le schéma est utile pendant la première phase de l'exploitation d'un système de prévision lorsque les données historiques sont inadéquates. On a défini un cadre de validation permettant de reproduire les conditions de prévision en temps réel. Les effets des procédures d'initialisation du modèle pluie-débit, de correction des erreurs et de prévision des précipitations ont ainsi pu être évaluées. Deux modèles pluie-débit conceptuels (SMA-NWSRFS et TANK) et des données provenant d'un bassin de Grèce ont été utilisés pour illustrer le schéma proposé.

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Section: Open For Discussion Until 1 October 2000mentioning

confidence: 99%

Real-time flood forecasting with the use of inadequate data

Nalbantis

2000

Hydrological Sciences Journal

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“…However, this coefficient depends on so many factors that it is difficult to accurately determine its value (Chow, 1959). This coefficient is usually considered as a calibration parameter for many models (Schumann et al, 2007) rather than as a parameter having physical meaning (Prasad et al, 1984). In fact, this coefficient is a model parameter that needs calibration in order to fit simulations to observations.…”

Section: Model Descriptionmentioning

confidence: 99%

Delineation of the Flood Prone Zones Along the Medjerda River Downstream of Sidi Salem Dam in Tunisia

Djebbi

2017

JSWSM

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The surge of extreme flooding events in the lower valley of the Medjerda between 1993 and 2005 raised people’s awareness to their effects. The main goal of this study is to delineate flood prone zones in response to the release of water volumes from Sidi Salem Dam, Tunisia. In order to achieve this goal, it was necessary to quantify the inflow flood hydrograph and characterise the geomorphology of the Medjerda River downstream the dam. The US Army Corps of Engineers HEC-RAS program was used to estimate the extent of floodplains associated with the released waters from the dam of Sidi Salem during historical and potential flooding events. The flood conveyances were calculated using surveyed topography, and HEC-RAS which was calibrated using site specific field data. The model output included water surface profiles. These profiles, coupled with a digital elevation model, were utilized to generate flood maps. Results showed a reduction of the main channel conveyance and overflows even for modest discharges. Data analysis proved that there were minor changes in the riverbed profile and the shape of the river’s cross-sections resulting in slower flow rates and larger sediment load depositions. This variability in the geomorphology of the river suggests that the flow friction factor varied as well. It is therefore crucial to monitor this friction factor variability in order to adjust the hydraulic models for better performances and forecasting capabilities with respect to standard models forced with static friction parameters. The produced flood maps are of great importance for several end-users particularly those in charge of: i) flood control and mitigation, ii) hydraulic structure design and deployment along major rivers, and iii) urban planning in order to avoid construction in flood-prone areas. The accuracy of these maps can be further improved by taking into account the morphological changes of the riverbed during each flooding event.

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Use of multiple-time-step information in rainfall-runoff modelling

Nalbantis

1995

Journal of Hydrology

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Mathematical modelling for formation and propagation of floods in a data-deficient basin

Cited by 3 publications

References 3 publications

Real-time flood forecasting with the use of inadequate data

Real-time flood forecasting with the use of inadequate data

Delineation of the Flood Prone Zones Along the Medjerda River Downstream of Sidi Salem Dam in Tunisia

Use of multiple-time-step information in rainfall-runoff modelling

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