Development of the Jamuneswari Flood Forecasting System: Case Study in Bangladesh

2012 ◽  
Vol 17 (10) ◽  
pp. 1123-1140 ◽  
Author(s):  
M. M. Rahman ◽  
N. K. Goel ◽  
D. S. Arya
Keyword(s):  
Flood Forecasting ◽  
Forecasting System

scholarly journals 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)

2013 ◽  
Vol 17 (1) ◽  
pp. 177-185 ◽  
Author(s):  
D. Leedal ◽  
A. H. Weerts ◽  
P. J. Smith ◽  
K. J. Beven
Keyword(s):  
Warning System ◽  
Open Shell ◽  
Flood Forecasting ◽  
Mechanistic Modelling ◽  
Forecasting Models ◽  
Forecasting System ◽  
Environment Agency ◽  
The Uk ◽  
Modelling Approach

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).

Real-Time Flood Forecasting System: Case Study of Hsia-Yun Watershed, Taiwan

2016 ◽  
Vol 21 (4) ◽  
pp. 05015031 ◽  
Author(s):  
Jen-Kuo Huang ◽  
Ya-Hsin Chan ◽  
Kwan Tun Lee
Keyword(s):  
Real Time ◽  
Flood Forecasting ◽  
Forecasting System

scholarly journals Case Study: A Real-Time Flood Forecasting System with Predictive Uncertainty Estimation for the Godavari River, India

Water ◽  
2016 ◽  
Vol 8 (10) ◽  
pp. 463 ◽  
Author(s):  
Silvia Barbetta ◽  
Gabriele Coccia ◽  
Tommaso Moramarco ◽  
Ezio Todini
Keyword(s):  
Real Time ◽  
Flood Forecasting ◽  
Uncertainty Estimation ◽  
Predictive Uncertainty ◽  
Godavari River ◽  
Forecasting System

scholarly journals Hydraulic Model for Flood Forecasting of Tajabad Khwar in Hayatabad Phase III Peshawar, Pakistan: A Case Study

2021 ◽  
Vol 89 (1) ◽  
pp. 160-174
Author(s):  
Mujahid Khan ◽  
Uzair Ali ◽  
Nayab Khan ◽  
Sida Hussain ◽  
Afnan Ahmad
Keyword(s):  
Research Work ◽  
Flood Forecasting ◽  
Hydraulic Model ◽  
Phase Iii ◽  
Return Periods ◽  
Residential Areas ◽  
Flood Zone ◽  
Close Proximity ◽  
Forecasting System

Among all other natural disasters occurring throughout the world, floods are considered to be the worst and most devastating catastrophe as it causes loss of billions of lives. Flooding is caused due to inundation of water over the areas which are in close proximity of river or natural waterways resulting in severe damages to commercial and residential areas in the surrounding. Thus, an efficient flood forecasting system through the development of a combined hydrological and hydraulic model for the prediction of future flood events through marking the potential high-risk zone is required to minimize the damages. Due to large number of encroachments made in the waterway of Tajabad khwar located near Deans Residential Apartment of Hayatabad Phase III, a hydraulic model is developed for its flood forecasting as the floods in this khwar may cause severe damages to the inhabitants of the adjacent areas. In this research work, Flood zone maps are developed for 10 years, 20 years, 50 years, and 100 years flood return periods in order for deterring extent of the inundation as a result of these encroachments and to identify the areas at potential risk. Flood discharge for each return period was estimated using HEC-HMS software and was found to be 772, 1036, 1392 and 1666 m^3/sec for 10 years, 20 years, 50 years, and 100 years flood return periods respectively. The corresponding water surface elevation determine using HEC-RAS and was found to be 196 m, 197m, 201m, 202m. This model provides a basic idea for developing flood zone maps of a given period of return for the assessment of areas that can get adversely pretentious by floods.

Development of a flood forecasting system using IFAS: a case study of scarcely gauged Jhelum and Chenab river basins

2018 ◽  
Vol 11 (14) ◽  
Author(s):  
Aamir Shahzad ◽  
Hamza Farooq Gabriel ◽  
Sajjad Haider ◽  
Ammara Mubeen ◽  
Muhammad Junaid Siddiqui
Keyword(s):  
River Basins ◽  
Flood Forecasting ◽  
Forecasting System ◽  
Chenab River

scholarly journals A pan-African medium-range ensemble flood forecast system

2015 ◽  
Vol 19 (8) ◽  
pp. 3365-3385 ◽  
Author(s):  
V. Thiemig ◽  
B. Bisselink ◽  
F. Pappenberger ◽  
J. Thielen
Keyword(s):  
Large Scale ◽  
Practical Implication ◽  
River Basins ◽  
Flood Forecasting ◽  
Small Scale ◽  
Flood Forecast ◽  
Flood Events ◽  
Forecast System ◽  
Pan African ◽  
Forecasting System

Abstract. The African Flood Forecasting System (AFFS) is a probabilistic flood forecast system for medium- to large-scale African river basins, with lead times of up to 15 days. The key components are the hydrological model LISFLOOD, the African GIS database, the meteorological ensemble predictions by the ECMWF (European Centre for Medium-Ranged Weather Forecasts) and critical hydrological thresholds. In this paper, the predictive capability is investigated in a hindcast mode, by reproducing hydrological predictions for the year 2003 when important floods were observed. Results were verified by ground measurements of 36 sub-catchments as well as by reports of various flood archives. Results showed that AFFS detected around 70 % of the reported flood events correctly. In particular, the system showed good performance in predicting riverine flood events of long duration (> 1 week) and large affected areas (> 10 000 km2) well in advance, whereas AFFS showed limitations for small-scale and short duration flood events. The case study for the flood event in March 2003 in the Sabi Basin (Zimbabwe) illustrated the good performance of AFFS in forecasting timing and severity of the floods, gave an example of the clear and concise output products, and showed that the system is capable of producing flood warnings even in ungauged river basins. Hence, from a technical perspective, AFFS shows a large potential as an operational pan-African flood forecasting system, although issues related to the practical implication will still need to be investigated.

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