scholarly journals Quasi-online flood forecasting downstream of dams based on rainfall thresholds

2013 ◽  
Vol 45 (4-5) ◽  
pp. 519-528 ◽  
Author(s):  
Bahram Saghafian ◽  
Saeed Golian ◽  
Hossein Khodadadi
Keyword(s):  
Cross Sections ◽  
Flood Control ◽  
Flood Forecasting ◽  
Rainfall Threshold ◽  
Risk Tolerance ◽  
Initial Water ◽  
Reservoir Routing ◽  
Prone Area ◽  
Southwestern Iran ◽  
Water Elevation

Dams are built to supply water to users and often to protect people and properties against floods in downstream areas. Efficiency of dams for flood control is improved substantially if a flood forecasting system is implemented. Rainfall threshold (RT) depths correspond to the occurrence of critical discharge at given cross-sections for given rainfall durations and initial soil moisture conditions of the upstream watershed. Here, we present an RT-based approach for offline flood forecasting downstream of dams. The proposed methodology incorporates rainfall-runoff and reservoir routing models while the spatial distribution of rainfall is probabilistically modeled based on a Monte Carlo approach. The RT curves are derived as a function of initial water elevation in the reservoir. The algorithm is implemented for a flood-prone area downstream of a dam in southwestern Iran. The results showed a clear rise in the RT values compared to the no-dam case, which is mainly due to the reservoir routing effect. The rate of rise in the RT values decreased with higher initial water elevation in the reservoir. The proposed method also provides the operator with the flexibility of adopting one of the various RT curves subject to different probabilities based on risk tolerance.

scholarly journals Dependable Flow and Flood Control Performance of Logung Dam, Central Java Province, Indonesia

2017 ◽  
Vol 3 (2) ◽  
pp. 343 ◽  
Author(s):  
Faza Ramadhani
Keyword(s):  
Cross Sections ◽  
Water Availability ◽  
Water Demand ◽  
Flood Control ◽  
Flow Characteristics ◽  
Low Flow ◽  
Control Performance ◽  
Central Java ◽  
Irrigation Water Demand ◽  
Reservoir Routing

The change of land use in Mt. Muria area Central Java has been resulting in the significant sheet erosion of upstream watershed around Mt. Muria, followed by considerably high sedimentation on rivers downstream that lead to the reduction of cross sections of the rivers including Logung River. Such situation has been contributing the condition that downstream of Logung River is very potential to experience over flow and inundation to its surrounding area. An idea of constructing the Logung Dam was introduced in 1986 that aimed at reducing the aforementioned inundation. Besides, the development of Logung Dam was also aimed at fulfilling both irrigation and non-irrigation water demand. This paper presents the results of the analysis of the water availability and flood control performance of the Logung Dam. The dependable flow was analyzed by applying the National Rural Electric Cooperative Association (NRECA) method in order to determine the low flow characteristics, whereas the identification of the high flow characteristics was carried out by using the Synthetic Unit Hydrograph (SUH) methods, i.e., the GAMA I and Nakayasu modeling approach. At a certain reservoir characteristic and a defined geometry of spillway, several reservoir routing simulations were carried out on both dependable flows and high flows. Results of the reservoir routing showed the promising water availability of the Logung Dam to fulfill water demand for both irrigation and non-irrigation, whereas the reservoir routing could reduce the probable maximum flood from QPMF from 1,031 m3/s to approximately 950 m3/s or damping efficiency at 7.86%. Further analysis suggests necessary operation and maintenance of Logung Dam to sustain its function and to mitigate possible problems related to reservoir sedimentation.

scholarly journals Flood Forecasting Based on an Improved Extreme Learning Machine Model Combined with the Backtracking Search Optimization Algorithm

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1362 ◽  
Author(s):  
Lu Chen ◽  
Na Sun ◽  
Chao Zhou ◽  
Jianzhong Zhou ◽  
Yanlai Zhou ◽  
...  
Keyword(s):  
Extreme Learning Machine ◽  
Flood Control ◽  
Search Algorithm ◽  
Flood Forecasting ◽  
Data Driven ◽  
General Regression Neural Network ◽  
Promising Alternative ◽  
Backtracking Search ◽  
Learning Machine ◽  
Population Based Algorithm

Flood forecasting plays an important role in flood control and water resources management. Recently, the data-driven models with a simpler model structure and lower data requirement attract much more attentions. An extreme learning machine (ELM) method, as a typical data-driven method, with the advantages of a faster learning process and stronger generalization ability, has been taken as an effective tool for flood forecasting. However, an ELM model may suffer from local minima in some cases because of its random generation of input weights and hidden layer biases, which results in uncertainties in the flood forecasting model. Therefore, we proposed an improved ELM model for short-term flood forecasting, in which an emerging dual population-based algorithm, named backtracking search algorithm (BSA), was applied to optimize the parameters of ELM. Thus, the proposed method is called ELM-BSA. The upper Yangtze River was selected as a case study. Several performance indexes were used to evaluate the efficiency of the proposed ELM-BSA model. Then the proposed model was compared with the currently used general regression neural network (GRNN) and ELM models. Results show that the ELM-BSA can always provide better results than the GRNN and ELM models in both the training and testing periods. All these results suggest that the proposed ELM-BSA model is a promising alternative technique for flood forecasting.

scholarly journals Development and Integration of Sub-Daily Flood Modelling Capability within the SWAT Model and a Comparison with XAJ Model

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1263 ◽  
Author(s):  
Dachen Li ◽  
Simin Qu ◽  
Peng Shi ◽  
Xueqiu Chen ◽  
Feng Xue ◽  
...  
Keyword(s):  
Time Scale ◽  
Flood Control ◽  
Assessment Tool ◽  
Spatial Scales ◽  
Swat Model ◽  
Flood Forecasting ◽  
Base Flow ◽  
Flood Simulation ◽  
Promising Tool ◽  
Daily Time

To date, floods have become one of the most severe natural disasters on Earth. Flood forecasting with hydrological models is an important non-engineering measure for flood control and disaster reduction. The Xin’anjiang (XAJ) model is the most widely used hydrological model in China for flood forecasting, while the Soil and Water Assessment Tool (SWAT) model is widely applied for daily and monthly simulation and has shown its potential for flood simulation. The objective of this paper is to evaluate the performance of the SWAT model in simulating floods at a sub-daily time-scale in a slightly larger basin and compare that with the XAJ model. Taking Qilijie Basin (southeast of China) as a study area, this paper developed the XAJ model and SWAT model at a sub-daily time-scale. The results showed that the XAJ model had a better performance than the sub-daily SWAT model regarding relative runoff error (RRE) but the SWAT model performed well according to relative peak discharge error (RPE) and error of occurrence time of peak flow (PTE). The SWAT model performed unsatisfactorily in simulating low flows due to the daily calculation of base flow but behaved quite well in simulating high flows. We also evaluated the effect of spatial scale on the SWAT model. The results showed that the SWAT model had a good applicability at different spatial scales. In conclusion, the sub-daily SWAT model is a promising tool for flood simulation though more improvements remain to be studied further.

A Numerical Study of Tsunami Generation by Horizontal Displacement of Sloping Seafloor

2020 ◽  
Vol 14 (04) ◽  
pp. 2050018 ◽  
Author(s):  
Chentong Hu ◽  
Yifan Wu ◽  
Chao An ◽  
Hua Liu
Keyword(s):  
Numerical Study ◽  
Horizontal Displacement ◽  
Vertical Displacement ◽  
Horizontal Motion ◽  
Generation Process ◽  
Tsunami Generation ◽  
Initial Water ◽  
Horizontal Momentum ◽  
The Difference ◽  
Water Elevation

Tsunamis are generated primarily by the vertical displacement of the seafloor if the seafloor is flat. If the seafloor is slanted, the horizontal motion also contributes to the generation of tsunamis. A previous study proposed that such effects can be estimated by simply calculating the elevation of water due to the horizontal displacement of the slope. Two more studies later argued that the horizontal motion also results in horizontal momentum of the water, which amplifies the tsunami generation. In this study, we numerically simulate the tsunami generation process of flat and sloping seafloor. It is found that, for the flat seafloor, the initial water elevation equals the vertical seafloor displacement. For the sloping seafloor, the initial water elevation deviates from the vertical seafloor displacement, and the difference can be accurately evaluated by the horizontal seafloor displacement. Thus, the initial horizontal momentum of the water is negligible for tsunami generation.

Uncertainty Analysis of Flood Forecasting in River Channel

2012 ◽  
Vol 550-553 ◽  
pp. 2489-2492
Author(s):  
Qun Hao ◽  
Ying Na Sun ◽  
Ning Jiang
Keyword(s):  
Uncertainty Analysis ◽  
Normal Distribution ◽  
Flood Control ◽  
Random Variable ◽  
Flood Forecasting ◽  
River Channel ◽  
Statistical Characteristics ◽  
Forecasting Model ◽  
Forward Algorithm ◽  
Linear Characteristic

In this paper, the stochastic differential equations theory was used to analyze the uncertainty of flood forecasting in river channel based on the forward algorithm of linear characteristic. And then a river channel flood forecasting model, in which the coefficient of storage and discharge was regarded as a random variable, was built. The statistical characteristics of outflow process could be taken part in theory by the built river channel flood forecasting model when the coefficient of storage obeyed a kind of normal distribution. Storage coefficient is random variable in the model. The results showed that the uncertainty degree of outflow process could be made through considering the uncertainty of river channel flood forecasting, which would provide some references for making decision in flood control.

scholarly journals Towards sustainable community: Effort to reduce flood risk and increase well-being in a densely populated flood-prone area

2021 ◽  
Vol 930 (1) ◽  
pp. 012096
Author(s):  
L Sedyowati ◽  
G Chandrarin ◽  
G I K Nugraha
Keyword(s):  
Community Involvement ◽  
Flood Risk ◽  
Flood Control ◽  
Local Community ◽  
Well Being ◽  
Economic Benefits ◽  
Prone Area ◽  
Community Effort ◽  
Flood Prone Area ◽  
Almost All

Abstract Dealing with flooding in a densely populated flood-prone area poses complex challenges. Almost all residents realize that living in the area is hazardous. However, they choose to stay there. Therefore, flood risk management should be applied in the area. This study aims to: 1) develop facts of the local community in a flood-prone area in decreasing the flood risk while improving well-being through modifying drainage channels used for fish and vegetable farming; 2) evaluate all benefits of drainage investments include the social and economic benefits. The research method consists of a quantitative approach through the distribution of questionnaires and a qualitative approach through in-depth interviews and field surveys. In this study, a concerted community effort was developed as a design parameter. At the same time, the observation parameters include knowledge of the causes of flooding, knowledge of flood risk, community involvement, and government flood control programs. The results showed that the strength of concerted community effort was significantly influenced by the knowledge of flood risk and the local community involvement. This effort can decrease the flood risk by up to 30% and serve direct financial benefits of IDR 48 million in a year.

scholarly journals Operational flood-forecasting in the Piemonte region – development and verification of a fully distributed physically-oriented hydrological model

2009 ◽  
Vol 17 ◽  
pp. 111-117 ◽  
Author(s):  
D. Rabuffetti ◽  
G. Ravazzani ◽  
S. Barbero ◽  
M. Mancini
Keyword(s):  
Cross Sections ◽  
System Reliability ◽  
Hydrological Model ◽  
Warning System ◽  
Flood Forecasting ◽  
Large River ◽  
Distributed Hydrological Model ◽  
Flood Events ◽  
Discharge Time ◽  
Po River

Abstract. A hydrological model for real time flood forecasting to Civil Protection services requires reliability and rapidity. At present, computational capabilities overcome the rapidity needs even when a fully distributed hydrological model is adopted for a large river catchment as the Upper Po river basin closed at Ponte Becca (nearly 40 000 km2). This approach allows simulating the whole domain and obtaining the responses of large as well as of medium and little sized sub-catchments. The FEST-WB hydrological model (Mancini, 1990; Montaldo et al., 2007; Rabuffetti et al., 2008) is implemented. The calibration and verification activities are based on more than 100 flood events, occurred along the main tributaries of the Po river in the period 2000–2003. More than 300 meteorological stations are used to obtain the forcing fields, 10 cross sections with continuous and reliable discharge time series are used for calibration while verification is performed on about 40 monitored cross sections. Furthermore meteorological forecasting models are used to force the hydrological model with Quantitative Precipitation Forecasts (QPFs) for 36 h horizon in "operational setting" experiments. Particular care is devoted to understanding how QPF affects the accuracy of the Quantitative Discharge Forecasts (QDFs) and to assessing the QDF uncertainty impact on the warning system reliability. Results are presented either in terms of QDF and of warning issues highlighting the importance of an "operational based" verification approach.

scholarly journals Some hydrodynamic problems for flood forecasting and flood control in the Red river system

2007 ◽  
Vol 29 (3) ◽  
pp. 271-283
Author(s):  
Nguyen Van Diep
Keyword(s):  
Flood Control ◽  
River System ◽  
Flood Forecasting ◽  
Hydraulic Model ◽  
Red River ◽  
Model Coupling ◽  
Development Activity ◽  
Dam Break Flow ◽  
Scientific Results ◽  
2D Model

My research & development activity in the field of environmental & natural fluid mechanics has been started after one year's working visit, proposed by Prof. Nguyen Van Dao, at the Laboratoire National d'Hydraulique de France in Chatou, France (1979-1980). Until now this activity is still a most important one.In the paper it is presented some selected scientific results in one of hydrodynamic problems for flood forecasting and flood control: developing of the 1D hydraulic model, 1D & quasi 2D model, 1D hydraulic model for dam break flow , 2D hydraulic model, coupling of 1D and 2D hydraulic models and some theirs applications for flood forecasting and flood control in the Red River System.This paper is dedicated to the memory of Prof. Nguyen Van Dao, with whom I had a big chance to work and to collaborate during about 30 years, to whom I would like to express my heartfelt thanks.

Flood Forecasting and Uncertainty Assessment Using Wavelet- and Bootstrap-Based Neural Networks

2018 ◽  
pp. 74-93
Author(s):  
Mukesh Kumar Tiwari ◽  
Chandranath Chatterjee
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Flood Control ◽  
Time Series Data ◽  
Flood Forecasting ◽  
Performance Comparison ◽  
Linear Regression Models ◽  
Original Time

Accurate and reliable forecasting of flood is inevitable for flood control planning and rehabilitation. There are several models available for flood forecasting, but as far as accuracy, reliability, and data scarcity are concerned, soft computing techniques (e.g., artificial neural networks) have been found to achieve the target. A wavelet-, bootstrap-, and neural-network-based framework (BWANN) is presented here for flood forecasting. Performance comparison of the proposed BWANN model is presented with wavelet-based ANN (WANN), wavelet-based MLR (WMLR), bootstrap- and wavelet-analysis-based multiple linear regression models (BWMLR), traditional ANN, and traditional multiple linear regression (MLR) models for flood forecasting. For development of WANN models, original time series data is decomposed using wavelet transformation, and wavelet sub-time series are considered to develop WANN model. A comparative analysis is carried out among different approaches of WANN model development using wavelet sub-time series.

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