DEVELOPMENT OF A FLOOD FORECASTING SYSTEM USING REGIONAL ENSEMBLE PREDICTION – APPLICATION TO THE KINUGAWA FLOOD IN 2015

Abstract. Landslide forecasting and early warning has a long tradition in landslide research and is primarily carried out based on empirical and statistical approaches, e.g., landslide-triggering rainfall thresholds. In the last decade, flood forecasting started the operational mode of so-called ensemble prediction systems following the success of the use of ensembles for weather forecasting. These probabilistic approaches acknowledge the presence of unavoidable variability and uncertainty when larger areas are considered and explicitly introduce them into the model results. Now that highly detailed numerical weather predictions and high-performance computing are becoming more common, physically based landslide forecasting for larger areas is becoming feasible, and the landslide research community could benefit from the experiences that have been reported from flood forecasting using ensemble predictions. This paper reviews and summarizes concepts of ensemble prediction in hydrology and discusses how these could facilitate improved landslide forecasting. In addition, a prototype landslide forecasting system utilizing the physically based TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability) model is presented to highlight how such forecasting systems could be implemented. The paper concludes with a discussion of challenges related to parameter variability and uncertainty, calibration and validation, and computational concerns.

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Potential application of hydrological ensemble prediction in forecasting flood and its components over the Yarlung Zangbo River Basin, China

10.5194/hess-2018-179 ◽

2018 ◽

Author(s):

Li Liu ◽

Su L. Pan ◽

Zhi X. Bai ◽

Yue P. Xu

Keyword(s):

River Basin ◽

Lead Time ◽

Flood Forecasting ◽

Ensemble Prediction ◽

Infiltration Capacity ◽

Weather Forecasts ◽

Flood Volume ◽

Yarlung Zangbo River ◽

Forecasting System

Abstract. In recent year, flood becomes a serious issue in Tibetan Plateau (TP) due to climate change. Many studies have shown that ensemble flood forecasting based on numerical weather predictions can provide early warning with extended lead time. However, the role of hydrological ensemble prediction in forecasting flood volume and its components over the Yarlung Zangbo River Basin (YZR), China has not been systematically investigated. This study adopts Variable Infiltration Capacity (VIC) model to forecast annual maximum floods (MF) and annual first floods (FF) in YZR based on precipitation, maximum and minimum temperature from European Centre for Medium-Range Weather Forecasts (ECMWF). N-simulations is proposed to account for more scenarios of parameters in VIC and shows improved flood simulation. Ensemble flood forecasting system can skilfully predict MF with a lead time of more than10 days, and has skill in forecasting the snowmelt-related components in about 7 days ahead. The accuracy of forecasts for FF is inferior with a lead time of only 5 days. The performance in 7-day accumulated flood volumes is better than the peak flows. The components in baseflow for FF are irrelevant to lead time, whilst for MF an obvious deterioration in performance with lead time can be perceived. The snowmelt-induced surface runoff is the most poorly captured component by the system, and the well-predicted rainfall-related components are the major contributor for good performance. From this study, it is concluded that snowmelt-induced flood volume plays an important role in YZR Basin especially in FF.

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DEVELOPMENT OF A FLOOD FORECASTING SYSTEM USING REGIONAL ENSEMBLE PREDICTION – APPLICATION TO KINUGAWA FLOOD IN 2015

Journal of Japan Society of Civil Engineers Ser B1 (Hydraulic Engineering) ◽

10.2208/jscejhe.73.i_193 ◽

2017 ◽

Vol 73 (4) ◽

pp. I_193-I_198 ◽

Cited By ~ 1

Author(s):

Tomoki USHIYAMA ◽

Takahiro SAYAMA ◽

Yoichi IWAMI

Keyword(s):

Flood Forecasting ◽

Ensemble Prediction ◽

Forecasting System

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Ensemble Flood Forecasting of Typhoons Talas and Roke at Hiyoshi Dam Basin

Journal of Disaster Research ◽

10.20965/jdr.2016.p1032 ◽

2016 ◽

Vol 11 (6) ◽

pp. 1032-1039 ◽

Cited By ~ 5

Author(s):

Tomoki Ushiyama ◽

◽

Takahiro Sayama ◽

Yoichi Iwami ◽

◽

...

Keyword(s):

Weather Prediction ◽

Flood Forecasting ◽

Quantitative Prediction ◽

Ensemble Prediction ◽

Distributed Hydrological Model ◽

Ensemble Prediction System ◽

Forecasting System ◽

Flood Warnings ◽

Better Than ◽

Small Basin

In order to be able to issue flood warnings not hours but days in advance, numerical weather prediction (NWP) is essential to the forecasting of flood-producing rainfall. The regional ensemble prediction system (EPS), advanced NWP on a local scale, has a high potential to improve flood forecasting through the quantitative prediction of precipitation. In this study, the predictability of floods using the ensemble flood forecasting system, which is composed of regional EPS and a distributed hydrological model, was investigated. Two flood events which took place in a small basin in Japan in 2010 and which were caused by typhoons Talas and Roke were examined. As the forecasting system predicted the probability of flood occurrence at least 24 h beforehand in the case of both typhoons, these forecasts were better than deterministic forecasts. However, the system underestimated the peak of the flooding in the typhoon Roke event, and it was too early in its prediction of the appearance of the peak of the flooding in the Talas event. Although the system has its limitations, it has proved to have the potential to produce early flood warnings.

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Potential application of hydrological ensemble prediction in forecasting floods and its components over the Yarlung Zangbo River basin, China

Hydrology and Earth System Sciences ◽

10.5194/hess-23-3335-2019 ◽

2019 ◽

Vol 23 (8) ◽

pp. 3335-3352 ◽

Cited By ~ 6

Author(s):

Li Liu ◽

Yue Ping Xu ◽

Su Li Pan ◽

Zhi Xu Bai

Keyword(s):

Lead Time ◽

Flood Forecasting ◽

Base Flow ◽

Ensemble Prediction ◽

The Tibetan Plateau ◽

Infiltration Capacity ◽

Trade Offs ◽

Yarlung Zangbo River ◽

Forecasting System ◽

Flow Components

Abstract. In recent year, floods becomes a serious issue in the Tibetan Plateau (TP) due to climate change. Many studies have shown that ensemble flood forecasting based on numerical weather predictions can provide an early warning with extended lead time. However, the role of hydrological ensemble prediction in forecasting flood volume and its components over the Yarlung Zangbo River (YZR) basin, China, has not been investigated. This study adopts the variable infiltration capacity (VIC) model to forecast the annual maximum floods and annual first floods in the YZR based on precipitation and the maximum and minimum temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF). N simulations are proposed to account for parameter uncertainty in VIC. Results show that when trade-offs between multiple objectives are significant, N simulations are recommended for better simulation and forecasting. This is why better results are obtained for the Nugesha and Yangcun stations. Our ensemble flood forecasting system can skillfully predict the maximum floods with a lead time of more than 10 d and can predict about 7 d ahead for meltwater-related components. The accuracy of forecasts for the first floods is inferior, with a lead time of only 5 d. The base-flow components for the first floods are insensitive to lead time, except at the Nuxia station, whilst for the maximum floods an obvious deterioration in performance with lead time can be recognized. The meltwater-induced surface runoff is the most poorly captured component by the forecast system, and the well-predicted rainfall-related components are the major contributor to good performance. The performance in 7 d accumulated flood volumes is better than the peak flows.

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A pan-African medium-range ensemble flood forecast system

Hydrology and Earth System Sciences ◽

10.5194/hess-19-3365-2015 ◽

2015 ◽

Vol 19 (8) ◽

pp. 3365-3385 ◽

Cited By ~ 28

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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