scholarly journals Evaluation of the Uncertainty of Flash Flood Prediction Using the RRI Model in Mountainous Rivers

10.29007/n72w ◽  
2018 ◽  
Author(s):  
Yosuke Nakamura ◽  
Koji Ikeuchi ◽  
Shiori Abe ◽  
Toshio Koike ◽  
Shinji Egashira
Keyword(s):  
Water Level ◽  
Lead Time ◽  
Hydrological Model ◽  
Flash Flood ◽  
Flood Damage ◽  
Water Levels ◽  
Uncertainty Distribution ◽  
Flood Prediction ◽  
The Mean ◽  
Level 2

In recent years, flood damage caused by flash floods in mountainous rivers has been frequently reported in Japan. In order to ensure a sufficient lead time for safe evacuation, it is necessary to predict river water levels in real time utilizing a hydrological model. In this study, we conducted flood prediction using the RRI model and rainfall forecasted for the next 6 hours in the Kagetsu River basin (136.1 km2) in July 2017, evaluated the uncertainty regarding the prediction, and illustrated the results using a box-plot. The evaluation found that the mean error of the forecasted water level was approximately - 0.3 m in the prediction for the initial 3 hours and -0.97 m at the 6th hour. Also, the study investigated the possibility of correcting water levels forecasted by clarifying an uncertainty distribution. As a result, the water level forecasted was found to be underestimated because it was predicted to rise as high as Warning Level 2, while the water level forecasted with bias correction was predicted to reach Warning Level 4. Moreover, the lead time was estimated to prolong by 2 hours. Overall, the study suggested that flood forecasting can be improved by considering the uncertainty involved in prediction.

scholarly journals Flood Forecasting and Warning System Structures: Procedure and Application to a Small Urban Stream in South Korea

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1571 ◽  
Author(s):  
Song ◽  
Park ◽  
Lee ◽  
Park ◽  
Song
Keyword(s):  
Decision Making ◽  
Water Level ◽  
Real Time ◽  
Lead Time ◽  
Flash Flood ◽  
Warning System ◽  
Flood Forecasting ◽  
Urban Stream ◽  
Forecasting And Warning ◽  
Flood Warnings

The runoff from heavy rainfall reaches urban streams quickly, causing them to rise rapidly. It is therefore of great importance to provide sufficient lead time for evacuation planning and decision making. An efficient flood forecasting and warning method is crucial for ensuring adequate lead time. With this objective, this paper proposes an analysis method for a flood forecasting and warning system, and establishes the criteria for issuing urban-stream flash flood warnings based on the amount of rainfall to allow sufficient lead time. The proposed methodology is a nonstructural approach to flood prediction and risk reduction. It considers water level fluctuations during a rainfall event and estimates the upstream (alert point) and downstream (confluence) water levels for water level analysis based on the rainfall intensity and duration. We also investigate the rainfall/runoff and flow rate/water level relationships using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS) and the HEC’s River Analysis System (HEC-RAS) models, respectively, and estimate the rainfall threshold for issuing flash flood warnings depending on the backwater state based on actual watershed conditions. We present a methodology for issuing flash flood warnings at a critical point by considering the effects of fluctuations in various backwater conditions in real time, which will provide practical support for decision making by disaster protection workers. The results are compared with real-time water level observations of the Dorim Stream. Finally, we verify the validity of the flash flood warning criteria by comparing the predicted values with the observed values and performing validity analysis.

scholarly journals Dynamics of fortnightly water level variations along a tide-dominated estuary with negligible river discharge

2021 ◽  
Author(s):  
Erwan Garel ◽  
Ping Zhang ◽  
Huayang Cai
Keyword(s):  
Water Level ◽  
Phase Difference ◽  
River Discharge ◽  
Water Levels ◽  
Level Increase ◽  
Upstream Direction ◽  
Water Level Variations ◽  
Mean Water Level ◽  
The Mean ◽  
Guadiana Estuary

Abstract. Observations indicate that the fortnightly fluctuations in mean water level increase in amplitude along the lower half of a tide-dominated estuary (The Guadiana estuary) with negligible river discharge but remain constant upstream. Analytical solutions reproducing the semi-diurnal wave propagation shows that this pattern results from reflection effects at the estuary head. The phase difference between velocity and elevation increases from the mouth to the head (where the wave has a standing nature) as the high and low water levels get progressively closer to slack water. Thus, the tidal (flood-ebb) asymmetry in discharge is reduced in the upstream direction. It becomes negligible along the upper estuary half, as the mean sea level remains constant despite increased friction due to wave shoaling. Observations of a flat mean water level along a significant portion of an upper estuary, easier to obtain than the phase difference, can therefore indicate significant reflection of the propagating semi-diurnal wave at the head. Details of the analytical model shows that changes in the mean depth or length of semi-arid estuaries, in particular for macrotidal locations, affect the fortnightly tide amplitude, and thus the upstream mass transport and inundation regime. This has significant potential impacts on the estuarine environment.

scholarly journals The Coupling of NSSL Warn-on-Forecast and FLASH Systems for Probabilistic Flash Flood Prediction

2020 ◽  
Vol 21 (1) ◽  
pp. 123-141
Author(s):  
Nusrat Yussouf ◽  
Katie A. Wilson ◽  
Steven M. Martinaitis ◽  
Humberto Vergara ◽  
Pamela L. Heinselman ◽  
...  
Keyword(s):  
Lead Time ◽  
Flash Flood ◽  
Spatial Scales ◽  
Initial Assessment ◽  
Flood Events ◽  
Short Term ◽  
Flood Prediction ◽  
Decision Making Processes ◽  
Operational Decision Making ◽  
Temporal And Spatial

AbstractThe goal of the National Oceanic and Atmospheric Administration’s (NOAA) Warn-on-Forecast (WoF) program is to provide frequently updating, probabilistic model guidance that will enable National Weather Service (NWS) forecasters to produce more continuous communication of hazardous weather threats (e.g., heavy rainfall, flash floods, damaging wind, large hail, and tornadoes) between the watch and warning temporal and spatial scales. To evaluate the application of this WoF concept for probabilistic short-term flash flood prediction, the 0–3-h rainfall forecasts from NOAA National Severe Storms Laboratory’s (NSSL) experimental WoF System (WoFS) were integrated as the forcing to the NWS operational hydrologic modeling core within the Flooded Locations and Simulated Hydrographs (FLASH) system. Initial assessment of the potential impacts of probabilistic short-term flash flood forecasts from this coupled atmosphere–hydrology (WoFS-FLASH) modeling system were evaluated in the 2018 Hydrometeorology Testbed Multi-Radar Multi-Sensor Hydrology experiment held in Norman, Oklahoma. During the 3-week experiment period, a total of nine NWS forecasters analyzed three retrospective flash flood events in archive mode. This study will describe specifically what information participants extracted from the WoFS-FLASH products during these three archived events, and how this type of information is expected to impact operational decision-making processes. Overall feedback from the testbed participants’ evaluations show promise for the coupled NSSL WoFS-FLASH system probabilistic flash flood model guidance to enable earlier assessment and detection of flash flood threats and to advance the current warning lead time for these events.

http://method.meteorf.ru/publ/tr/tr380/htm/02.htm

2021 ◽  
Vol 2 ◽  
pp. 77-94
Author(s):  
S.V. Borsch ◽  
◽  
V.M/ Koliy ◽  
N.K. Semenova ◽  
Yu.A., Simonov ◽  
...  
Keyword(s):  
Water Level ◽  
Lead Time ◽  
Water Levels ◽  
Extrapolation Method ◽  
Automated System ◽  
Forecast Verification ◽  
Time Period ◽  
Linear Formula ◽  
Daily Discharge ◽  
Self Learning

Forecasting the flow of Russian rivers by hydrograph extrapolation / Borsch S.V., Koliy V.M., Semenova N.K., Simonov Yu.A., Khristoforov A.V. // Hydrometeorological Research and Forecasting, 2021, no. 2 (380), pp. 77-94. An automated system has been developed based on the hydrograph extrapolation method, which allows the year-round daily forecasting of water level and streamflow for the Russian rivers with up to 10-day lead time. The forecast of discharges or water levels is expressed by a linear formula depending on their values on the date of the forecast issue and five previous days. The forecasting scheme limits the possible minimum and maximum values of the discharge or water level based on historical data. Forecast schemes were obtained for 2776 river gauges. The time period from 2010 to 2019 with daily observations of discharge and water level was used. The forecast verification shows that this method can be successfully applied to large rivers with smooth hydrographs. Keywords: daily discharge and water levels, short- and medium-term forecasts, hydrograph extrapolation method, forecast verification, maximum lead time of satisfactory forecasts, self-learning of an automated system for preparing and issuing forecasts

scholarly journals Modelling the Mara River Basin with data uncertainty using water levels for calibration

2017 ◽  
Author(s):  
Petra Hulsman ◽  
Thom A. Bogaard ◽  
Hubert H. G. Savenije
Keyword(s):  
Time Series ◽  
Water Level ◽  
River Basin ◽  
Hydrological Model ◽  
Water Levels ◽  
Rating Curve ◽  
Discharge Time ◽  
Discharge Data ◽  
Single Station ◽  
Rating Curves

Abstract. Hydrological models play an important role in Water Resources Management. In hydrological modelling, discharge data is generally required for calibration. To obtain continuous time series, water levels are usually converted into discharge by using a rating curve. However with this methodology, uncertainties are introduced in the discharge data due to insufficient observations, inadequate rating curve fitting procedures, extrapolation or temporal changes in the river geometry. Unfortunately, this is often the case in many African river basins. In this study, a semi-distributed rainfall runoff model has been applied to the Mara River Basin for the assessment of the water availability. To reduce the effect of discharge uncertainties in this model, water levels instead of discharge time series were used for calibration. In this model, seven sub-catchments are distinguished and four hydrological response units: forest, shrubs, cropland and grassland. To calibrate the model on water level data, modelled discharges have been converted into water levels using cross-section observations and the Strickler formula. In addition, new geometric rating curves have been obtained based on modelled discharge, observed water level and the Strickler formula. This procedure resulted in good and consistent model results during calibration and validation. The hydrological model was able to reproduce the water depths for the entire basin as well as for the Nyangores sub-catchment in the north. The geometric and recorded (i.e. existing) rating curves were significantly different at Mines, the catchment outlet, probably due to uncertainties in the recorded discharge time series. At Nyangores however, the geometric and recorded discharge were almost identical. In addition, it has been found that the precipitation estimation methodology influenced the model results significantly. Application of a single station for each sub-catchment resulted in flashier responses whereas Thiessen averaged precipitation resulted in more dampened responses. In conclusion, by using water level time series for calibrating the hydrological model of the Mara River Basin promising model results were obtained. For this river basin, the main limitation for obtaining an accurate hydrograph representation was the inadequate knowledge on the spatial distribution of the precipitation.

scholarly journals Integrated model projections of climate change impacts on water-level dynamics in the large Poyang Lake (China)

2019 ◽  
Author(s):  
Yunliang Li ◽  
Qi Zhang ◽  
Hui Tao ◽  
Jing Yao
Keyword(s):  
Climate Change ◽  
Water Level ◽  
Lake Water ◽  
Hydrological Model ◽  
Poyang Lake ◽  
Baseline Period ◽  
Global Climate Models ◽  
Water Levels ◽  
Future Climate Change ◽  
Increased Risk

Abstract This study outlines a framework for examining potential impacts of future climate change in Poyang Lake water levels using linked models. The catchment hydrological model (WATLAC) was used to simulate river runoffs from a baseline period (1986–2005) and near-future (2020–2035) climate scenarios based on eight global climate models (GCMs). Outputs from the hydrological model combined with the Yangtze River's effects were fed into a lake water-level model, developing in the back-propagation neural network. Model projections indicate that spring–summer water levels of Poyang Lake are expected to increase by 5–25%, and autumn–winter water levels are likely to be lower and decrease by 5–30%, relative to the baseline period. This amounts to higher lake water levels by as much as 2 m in flood seasons and lower water levels in dry seasons in the range of 0.1–1.3 m, indicating that the lake may be wet-get-wetter and dry-get-drier. The probability of occurrence for both the extreme high and low water levels may exhibit obviously increasing trends by up to 5% more than at present, indicating an increased risk in the severity of lake floods and droughts. Projected changes also include possible shifts in the timing and magnitude of the lake water levels.

scholarly journals Forecasting annual maximum water level for Negro River at Manaus

2021 ◽  
Author(s):  
Amulya Chevuturi ◽  
Nicholas P. Klingaman ◽  
Steven J. Woolnough ◽  
Conrado M. Rudorff ◽  
Caio A. S. Coelho ◽  
...  
Keyword(s):  
Water Level ◽  
Statistical Models ◽  
Lead Time ◽  
Large Scale ◽  
Water Levels ◽  
Annual Maximum ◽  
Negro River ◽  
Operational Forecasts ◽  
Maximum Water Level ◽  
Maximum Water

<p>Variations in water levels of the Negro River, that flows through the Port of Manaus, can cause considerable regional environmental and socio-economic losses. It is therefore critical to advance predictions for water levels, especially flood levels, to provide more effective and earlier warnings to safeguard lives and livelihoods. Variations in water levels in free-flowing river systems, like the Negro follow large-scale precipitation anomalies, which offers an opportunity to predict maximum water levels using observed antecedent rainfall. This study aims to improve the performance and extend the lead time of statistical forecasts for annual maximum water level of the Negro River at Manaus, relative to operational forecasts. Multiple linear regression methods are applied to develop forecast models, that can be issued in March, February and January, with the best possible combinations potential predictors: observed antecedent catchment rainfall and water levels, large-scale modes of climate variability and the linear trend in water levels. Our statistical models gain one month of lead time against existing models, but are only moderately better than existing models at similar lead time. Using European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal reforecast data with our statistical models, further gains an additional month of lead time of skilful performance. Our models lose performance at longer lead times, as expected. Our forecast models can issue skilful operational forecasts in March or earlier and have been successfully tested for operational forecast of 2020. This method can be applied to develop statistical models for annual maximum water level over other free-flowing rivers in the Amazon basin with intact catchments and historical water level record.</p>

scholarly journals Analytical approach for determining the mean water level profile in an estuary with substantial fresh water discharge

2015 ◽  
Vol 12 (8) ◽  
pp. 8381-8417 ◽  
Author(s):  
H. Cai ◽  
H. H. G. Savenije ◽  
C. Jiang ◽  
L. Zhao ◽  
Q. Yang
Keyword(s):  
Water Level ◽  
Fresh Water ◽  
Flood Control ◽  
Analytical Approach ◽  
Water Discharge ◽  
Water Levels ◽  
Wide Range ◽  
Mean Water Level ◽  
The Mean ◽  
Fresh Water Discharge

Abstract. Although modestly, the mean water level in estuaries rises in landward direction induced by a combination of the salinity gradient, the tidal asymmetry, and the backwater effect. The water level slope is increased by the fresh water discharge. However, the interactions between tide and river flow and their individual contributions to the rise of the mean water level along the estuary are not yet completely understood. In this study, we adopt an analytical approach to describe the tidal wave propagation under the influence of fresh water discharge, in which the friction term is approximated by a Chebyshev polynomials approach. The analytical model is used to quantify the contributions made by tide, river, and tide–river interaction to the water level slope along the estuary. Subsequently, the method is applied to the Yangtze estuary under a wide range of river discharge conditions and the influence of tidal amplitude and fresh water discharge on the longitudinal variation of mean water level is explored. The proposed method is particularly useful for accurately predicting water levels and the frequency of extreme high water, relevant for water management and flood control.

scholarly journals Dynamics of fortnightly water level variations along a tide-dominated estuary with negligible river discharge

Ocean Science ◽  
2021 ◽  
Vol 17 (6) ◽  
pp. 1605-1621
Author(s):  
Erwan Garel ◽  
Ping Zhang ◽  
Huayang Cai
Keyword(s):  
Water Level ◽  
River Discharge ◽  
Mean Amplitude ◽  
Water Levels ◽  
Level Increase ◽  
Upstream Direction ◽  
Water Level Variations ◽  
Mean Water Level ◽  
The Mean ◽  
Guadiana Estuary

Abstract. Observations indicate that the fortnightly fluctuations in the mean amplitude of water level increase in the upstream direction along the lower half of a tide-dominated estuary (the Guadiana Estuary), with negligible river discharge, but remain constant upstream. Analytical solutions reproducing the semi-diurnal wave propagation shows that this pattern results from reflection effects at the estuary head. The phase difference between velocity and elevation increases from the mouth to the head (where the wave has a standing nature) as the timing of high and low water levels come progressively closer to slack water. Thus, the tidal (flood–ebb) asymmetry in discharge is reduced in the upstream direction. It becomes negligible along the upper estuary half as the mean sea level remains constant despite increased friction due to wave shoaling. Observations of a flat mean water level along a significant portion of an upper estuary suggest a standing wave character and, thus, indicate significant reflection of the propagating semi-diurnal wave at the head. Details of the analytical model show that changes in the mean depth or length of semi-arid estuaries, in particular for macrotidal locations, affect the fortnightly tide amplitude and, thus, the upstream mass transport and inundation regime. This has significant potential impacts on the estuarine environment in terms of ecosystem management.

scholarly journals An Operational Forecasting System for Flash Floods in Mountainous Areas in Taiwan

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2100 ◽  
Author(s):  
Yung-Ming Chen ◽  
Che-Hsin Liu ◽  
Hung-Ju Shih ◽  
Chih-Hsin Chang ◽  
Wei-Bo Chen ◽  
...  
Keyword(s):  
Flash Flood ◽  
Flash Floods ◽  
Water Levels ◽  
Airborne Lidar ◽  
Mountainous Areas ◽  
Flood Prediction ◽  
Mountainous Regions ◽  
Operational Forecasting ◽  
Forecasting System ◽  
Elevation Model

Flash floods are different from common floods because they occur rapidly over short time scales, and they are considered to be one of the most devastating natural hazards worldwide. Mountainous areas with high population densities are particularly threatened by flash floods because steep slopes generate high flow velocities. Therefore, there is a great need to develop an operational forecasting system (OFS) for better flash flood prediction and warning in mountainous regions. This study developed an OFS through the integration of meteorological, hydrological, and hydrodynamic models. Airborne light detection and ranging (LiDAR) data were used to generate a digital elevation model (DEM). The OFS employs high-density and high-accuracy airborne LiDAR DEM data to simulate rapid water level rises and flooding as the result of intense rainfall within relatively small watersheds. The water levels and flood extent derived from the OFS are in agreement with the measured and surveyed data. The OFS has been adopted by the National Science and Technology Center for Disaster Reduction (NCDR) for forecasting flash floods every six hours in a mountainous floodplain in Taiwan. The 1D and 2D visualization of the OFS is performed via the National Center for Atmospheric Research Command Language (NCL).

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