scholarly journals Learning Case Study of a Shallow-Water Model to Assess an Early-Warning System for Fast Alpine Muddy-Debris-Flow

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 750
Author(s):  
Antonio Pasculli ◽  
Jacopo Cinosi ◽  
Laura Turconi ◽  
Nicola Sciarra
Keyword(s):  
Debris Flow ◽  
Shallow Water ◽  
Early Warning ◽  
Debris Flows ◽  
Early Warning System ◽  
Warning System ◽  
Extreme Weather Events ◽  
Water Model ◽  
Computational Time ◽  
Processing Unit

The current climate change could lead to an intensification of extreme weather events, such as sudden floods and fast flowing debris flows. Accordingly, the availability of an early-warning device system, based on hydrological data and on both accurate and very fast running mathematical-numerical models, would be not only desirable, but also necessary in areas of particular hazard. To this purpose, the 2D Riemann–Godunov shallow-water approach, solved in parallel on a Graphical-Processing-Unit (GPU) (able to drastically reduce calculation time) and implemented with the RiverFlow2D code (version 2017), was selected as a possible tool to be applied within the Alpine contexts. Moreover, it was also necessary to identify a prototype of an actual rainfall monitoring network and an actual debris-flow event, beside the acquisition of an accurate numerical description of the topography. The Marderello’s basin (Alps, Turin, Italy), described by a 5 × 5 m Digital Terrain Model (DTM), equipped with five rain-gauges and one hydrometer and the muddy debris flow event that was monitored on 22 July 2016, were identified as a typical test case, well representative of mountain contexts and the phenomena under study. Several parametric analyses, also including selected infiltration modelling, were carried out in order to individuate the best numerical values fitting the measured data. Different rheological options, such as Coulomb-Turbulent-Yield and others, were tested. Moreover, some useful general suggestions, regarding the improvement of the adopted mathematical modelling, were acquired. The rapidity of the computational time due to the application of the GPU and the comparison between experimental data and numerical results, regarding both the arrival time and the height of the debris wave, clearly show that the selected approaches and methodology can be considered suitable and accurate tools to be included in an early-warning system, based at least on simple acoustic and/or light alarms that can allow rapid evacuation, for fast flowing debris flows.

scholarly journals Application and analysis of debris-flow early warning system in Wenchuan earthquake-affected area

2016 ◽  
Vol 16 (2) ◽  
pp. 483-496 ◽  
Author(s):  
D. L. Liu ◽  
S. J. Zhang ◽  
H. J. Yang ◽  
L. Q. Zhao ◽  
Y. H. Jiang ◽  
...  
Keyword(s):  
Debris Flow ◽  
Wenchuan Earthquake ◽  
Early Warning ◽  
Early Warning System ◽  
Prediction Accuracy ◽  
Warning System ◽  
Sichuan Province ◽  
Affected Area ◽  
The Wenchuan Earthquake ◽  
New System

Abstract. The activities of debris flow (DF) in the Wenchuan earthquake-affected area significantly increased after the earthquake on 12 May 2008. The safety of the lives and property of local people is threatened by DFs. A physics-based early warning system (EWS) for DF forecasting was developed and applied in this earthquake area. This paper introduces an application of the system in the Wenchuan earthquake-affected area and analyzes the prediction results via a comparison to the DF events triggered by the strong rainfall events reported by the local government. The prediction accuracy and efficiency was first compared with a contribution-factor-based system currently used by the weather bureau of Sichuan province. The storm on 17 August 2012 was used as a case study for this comparison. The comparison shows that the false negative rate and false positive rate of the new system is, respectively, 19 and 21 % lower than the system based on the contribution factors. Consequently, the prediction accuracy is obviously higher than the system based on the contribution factors with a higher operational efficiency. On the invitation of the weather bureau of Sichuan province, the authors upgraded their prediction system of DF by using this new system before the monsoon of Wenchuan earthquake-affected area in 2013. Two prediction cases on 9 July 2013 and 10 July 2014 were chosen to further demonstrate that the new EWS has high stability, efficiency, and prediction accuracy.

scholarly journals Early warning system on extreme weather events for disaster risk reduction

2019 ◽  
pp. 80-87
Author(s):  
Jacipt Alexander Ramón-Valencia ◽  
Jordi Rafael Palacios-González ◽  
Germán Rircardo Santos-Granados ◽  
Jarol Derley Ramón-Valencia
Keyword(s):  
Risk Management ◽  
Risk Reduction ◽  
Early Warning ◽  
Early Warning System ◽  
Disaster Risk Reduction ◽  
Warning System ◽  
Disaster Risk ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events

The objective of this research was to propose a strategy based on the design and implementation of an early warning system (EWS) for extreme weather events. This project had the following phases: training for municipal and regional actors, preliminary technical diagnosis of the study areas, monitoring network, and the weather forecasts using numerical models WRF and GFS. This EWS is the result of the Macro-project EWS for Climate Events in the basins of the Pamplonita River and Zulia in the North of Santander (SATC), executed by the University of Pamplona and financed by the National Risk Management Unit (UNGRD) and the German Cooperation Agency (GIZ). The research concluded that the application of a disaster risk reduction strategy through an EWS for extreme weather events is an important tool and instrument for the planning of higher risk management because it helps anticipate disasters and consequently preserve lives.

scholarly journals Enhancing Flood Early Warning System in the HKH Region

2021 ◽  
pp. 169-200
Author(s):  
Karma Tsering ◽  
Kiran Shakya ◽  
Mir A. Matin ◽  
Jim Nelson ◽  
Birendra Bajracharya
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Natural Hazard ◽  
Environmental Changes ◽  
Warning System ◽  
Flood Forecasting ◽  
Extreme Weather ◽  
Extreme Weather Events ◽  
Weather Events ◽  
Forecasting And Warning

AbstractFlooding is a chronic natural hazard with disastrous impacts that have magnified over the last decade due to the rising trend in extreme weather events and growing societal vulnerability from global socioeconomic and environmental changes (WMO 2011 in Manual on flood forecasting and warning (WMO-No. 1072)).

scholarly journals EVALUATION ON THE IMPLEMENTATION OF EARLY WARNING SYSTEM FOR LAHAR IN MERAPI AREA (CASE STUDY AT BOYONG RIVER)

2015 ◽  
Vol 1 (3) ◽  
pp. 77
Author(s):  
Ali Cahyadi Achmad
Keyword(s):  
Debris Flow ◽  
Qualitative Analysis ◽  
Volcanic Activity ◽  
Early Warning ◽  
Early Warning System ◽  
Rainfall Intensity ◽  
Warning System ◽  
Actual Condition ◽  
Telemetry System ◽  
Debris Flood

One of disasters caused by volcanic activity of Mount Merapi is secondary disaster. The disaster usually occurs after eruption and this volcanic activity produces volcanic and pyroclastic material deposit around the top of the mountain as a result of previous eruption. This material might collapse downward in the form of debris flow as it is affected by natural event such as high intensity rainfall. Therefore, a research is needed to analyze whether existing forecasting and early warning system are capable to provide information for the people living in hazardous area before the debris flood occur. This research was carried out using field survey, observation and interview method. Data analysis used qualitative descriptive method by making description of actual condition of the researched location general condition and qualitative analysis of telemetry system installed on Mount Merapi. The qualitative analysis of telemetry system covers network, hardware, software, power supply, security system, operation and maintenance, also human resources. Research analysis used primary and secondary data. Research results revealed that mean rainfall intensity above of 60 mm/hour might trigger debris flood. Early warning should be given at the rainfall intensity level of 50-55 mm/hour, and debris flood time travel from the upstream to the observed location in Pulowatu Village is 45 minute. Based on the analysis of the present forecasting and early warning system, it is known that some of the equipment is not well functioned, so that debris flow cannot be predicted and detected. This is caused by the lack of human resource quality of the officers in operating and maintaining the equipment. Concerning that matter, it is necessary to conduct some improvement to achieve better forecasting and early warning system in order to give information regarding occurrence of debris flow.

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