On operational flood forecasting system involving 1D/2D coupled hydraulic model and data assimilation

2018 ◽  
Vol 562 ◽  
pp. 623-634 ◽  
Author(s):  
S. Barthélémy ◽  
S. Ricci ◽  
T. Morel ◽  
N. Goutal ◽  
E. Le Pape ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Flood Forecasting ◽  
Hydraulic Model ◽  
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.

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.

Development of a Real-Time Flood Forecasting System by Hydraulic Flood Routing

2001 ◽  
Author(s):  
Joo Heon Lee ◽  
Do Hun Lee ◽  
Sang Man Jeong ◽  
Eun Tae Lee
Keyword(s):  
Real Time ◽  
Flood Forecasting ◽  
Flood Routing ◽  
Forecasting System

Implementation of altimeter data assimilation on a regional wave forecasting system and its impact on wave and swell surge forecast in the Indian Ocean

2021 ◽  
Vol 237 ◽  
pp. 109585
Author(s):  
M. Seemanth ◽  
P.G. Remya ◽  
Suchandra Aich Bhowmick ◽  
Rashmi Sharma ◽  
T.M. Balakrishnan Nair ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Data Assimilation ◽  
Altimeter Data ◽  
Forecasting System ◽  
The Indian Ocean ◽  
Wave Forecasting

Measuring the skill of an operational ice jam flood forecasting system

2021 ◽  
Vol 52 ◽  
pp. 102001
Author(s):  
Brandon S. Williams ◽  
Apurba Das ◽  
Peter Johnston ◽  
Bin Luo ◽  
Karl-Erich Lindenschmidt
Keyword(s):  
Flood Forecasting ◽  
Ice Jam ◽  
Forecasting System

scholarly journals A Robust Skewed Boxplot for Detecting Outliers in Rainfall Observations in Real-Time Flood Forecasting

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Chao Zhao ◽  
Jinyan Yang
Keyword(s):  
Real Time ◽  
Exponential Function ◽  
Flood Forecasting ◽  
Interquartile Range ◽  
Skewed Data ◽  
Symmetric Distributions ◽  
Contaminated Data ◽  
Forecasting System

The standard boxplot is one of the most popular nonparametric tools for detecting outliers in univariate datasets. For Gaussian or symmetric distributions, the chance of data occurring outside of the standard boxplot fence is only 0.7%. However, for skewed data, such as telemetric rain observations in a real-time flood forecasting system, the probability is significantly higher. To overcome this problem, a medcouple (MC) that is robust to resisting outliers and sensitive to detecting skewness was introduced to construct a new robust skewed boxplot fence. Three types of boxplot fences related to MC were analyzed and compared, and the exponential function boxplot fence was selected. Operating on uncontaminated as well as simulated contaminated data, the results showed that the proposed method could produce a lower swamping rate and higher accuracy than the standard boxplot and semi-interquartile range boxplot. The outcomes of this study demonstrated that it is reasonable to use the new robust skewed boxplot method to detect outliers in skewed rain distributions.

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