Recent Development of the Hong Kong Landslip Warning System

2021 ◽  
Author(s):  
Raymond Cheung ◽  
Edward Chu ◽  
Rachel Law ◽  
Philip Chung
Keyword(s):  
Hong Kong ◽  
Heavy Rainfall ◽  
Warning System ◽  
Extreme Rainfall ◽  
Safety System ◽  
Landslide Risk ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Public ◽  
Landslide Hazards

<p>Hong Kong is situated at the south-eastern tip of China.  It has a sub-tropical climate, with a rainy season from April to October each year.  Rainfall intensities can be high, with 50 mm to 100 mm per hour and 250 mm to 350 mm in 24 hours being not uncommon.  Because of its mountainous terrain, Hong Kong is susceptible to landsliding during the periods of heavy rainfall.  As part of the Slope Safety System, the Geotechnical Engineering Office (GEO) of the Hong Kong Special Administrative Region Government has been operating a territory-wide Landslip Warning System for over 40 years.  The primary objective of the Landslip Warning is to forewarn the public of possible landslide risk during periods of heavy rainfall.  This paper summarises the major components of the current GEO Landslip Warning System as a landslide risk management tool.  Hong Kong has an extensive network of automatic raingauges and comprehensive records of landslides.  With this, rainfall-landslide correlation models have been established and updated regularly through statistical means to facilitate the prediction of the severity of landslide based on real-time rainfall recorded in the raingauge network and the rainfall forecast by the Hong Kong Observatory (HKO).  The System has been continuously enhanced and upgraded along with the development of novel technology and analytical techniques.  Currently, Internet of Things (IoT) technology are used in the automatic raingauge network jointly operated by the GEO and the HKO to ensure reliable data transmission.  The collected rainfall data are stored and processed using cloud computing service that predicts the severity of landslide at every five-minute intervals.  The prediction allows the GEO and the HKO to determine the necessity of issuing a Landslip Warning.  Apart from technology, the effectiveness of the Landslip Warning also depends on the actions taken by the public when it is in force.  The GEO has ongoing public education campaigns to raise the public awareness and preparedness to reduce vulnerability to landslide hazards.   In recent years, occurrence of severe landslides and casualties in landslide have been significantly reduced, which is attributed largely to the successful implementation of the Slope Safety System and partly to the absence of extreme rainfall events.  As a result, there is a genuine concern that the public is becoming complacent to the potential landslide hazards.  The GEO has enhanced the efforts in maintaining public participation in combating landslide hazards and improved the public perception of the landslide risk of a rainstorm by using a quantitative Landslide Potential Index.   Besides providing public warning, the GEO also endeavours to enhance the emergency response to landslide incidents through innovative solutions.  Selected debris barriers are installed with IoT sensors for providing immediate alert of the occurrence of sizable landslides and quadrupled robots are being studied and tested for inspecting landslide sites.  It is anticipated that innovation and technology have great potential in improving the GEO’s capability in emergency management, in particular in the case of extreme rainfall events that are expected be more frequent and intense in future.</p>

scholarly journals ­Trends and Zonal Variability of Extreme Rainfall Events Over East Africa During 1960-2017

2021 ◽  
Author(s):  
Moses.A Ojara ◽  
Yunsheng Lou ◽  
Hasssen Babaousmail ◽  
Peter Wasswa
Keyword(s):  
Extreme Events ◽  
Heavy Rainfall ◽  
Rainwater Harvesting ◽  
Southern Oscillation ◽  
Extreme Rainfall ◽  
Mitigation Measures ◽  
Fluctuation Analysis ◽  
Positive Trend ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract East African countries (Uganda, Kenya, Tanzania, Rwanda, and Burundi) are prone to weather extreme events. In this regard; the past occurrence of extreme rainfall events is analyzed for 25 stations following the Expert Team on Climate Change Detection and Indices (ETCCDI) regression method. Detrended Fluctuation Analysis (DFA) is used to show the future development of extreme events. Pearson’s correlation analysis is performed to show the relationship of extreme events between different rainfall zones and their association with El Niño -Southern Oscillation (ENSO and Indian Ocean dipole (IOD) IOD-DMI indices. Results revealed that the consecutive wet day's index (CWD) was decreasing trend in 72% of the stations analyzed, moreover consecutive dry days (CDD) index also indicated a positive trend in 44% of the stations analyzed. Heavy rainfall days index (R10mm) showed a positive trend at 52% of the stations and was statistically significant at a few stations. In light of the extremely heavy rainfall days (R25mm) index, 56% of the stations revealed a decreasing trend for the index and statistically significant trend at some stations. Further, a low correlation coefficient of extreme rainfall events in the regions; and between rainfall extreme indices with the atmospheric teleconnection indices (Dipole Mode Index-DMI and Nino 3.4) (r = -0.1 to r = 0.35). Most rainfall zones showed a positive correlation between the R95p index and DMI, while 5/8 of the rainfall zones experienced a negative correlation between Nino 3.4 index and the R95p. In light of the highly variable trends of extremes events, we recommend planning adaptation and mitigation measures that consider the occurrence of such high variability. Measures such as rainwater harvesting, stored and used during needs, planned settlement, and improved drainage systems management supported by accurate climate and weather forecasts is highly advised.

scholarly journals Assessment of the Weather Research and Forecasting (WRF) model for simulation of extreme rainfall events in the upper Ganga Basin

2018 ◽  
Vol 22 (2) ◽  
pp. 1095-1117 ◽  
Author(s):  
Ila Chawla ◽  
Krishna K. Osuri ◽  
Pradeep P. Mujumdar ◽  
Dev Niyogi
Keyword(s):  
Land Surface ◽  
Heavy Rainfall ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Ganga Basin ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Heavy Rainfall Events

Abstract. Reliable estimates of extreme rainfall events are necessary for an accurate prediction of floods. Most of the global rainfall products are available at a coarse resolution, rendering them less desirable for extreme rainfall analysis. Therefore, regional mesoscale models such as the advanced research version of the Weather Research and Forecasting (WRF) model are often used to provide rainfall estimates at fine grid spacing. Modelling heavy rainfall events is an enduring challenge, as such events depend on multi-scale interactions, and the model configurations such as grid spacing, physical parameterization and initialization. With this background, the WRF model is implemented in this study to investigate the impact of different processes on extreme rainfall simulation, by considering a representative event that occurred during 15–18 June 2013 over the Ganga Basin in India, which is located at the foothills of the Himalayas. This event is simulated with ensembles involving four different microphysics (MP), two cumulus (CU) parameterizations, two planetary boundary layers (PBLs) and two land surface physics options, as well as different resolutions (grid spacing) within the WRF model. The simulated rainfall is evaluated against the observations from 18 rain gauges and the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) 3B42RT version 7 data. From the analysis, it should be noted that the choice of MP scheme influences the spatial pattern of rainfall, while the choice of PBL and CU parameterizations influences the magnitude of rainfall in the model simulations. Further, the WRF run with Goddard MP, Mellor–Yamada–Janjic PBL and Betts–Miller–Janjic CU scheme is found to perform best in simulating this heavy rain event. The selected configuration is evaluated for several heavy to extremely heavy rainfall events that occurred across different months of the monsoon season in the region. The model performance improved through incorporation of detailed land surface processes involving prognostic soil moisture evolution in Noah scheme compared to the simple Slab model. To analyse the effect of model grid spacing, two sets of downscaling ratios – (i) 1 : 3, global to regional (G2R) scale and (ii) 1 : 9, global to convection-permitting scale (G2C) – are employed. Results indicate that a higher downscaling ratio (G2C) causes higher variability and consequently large errors in the simulations. Therefore, G2R is adopted as a suitable choice for simulating heavy rainfall event in the present case study. Further, the WRF-simulated rainfall is found to exhibit less bias when compared with the NCEP FiNaL (FNL) reanalysis data.

scholarly journals Association of geopotential height patterns with heavy rainfall events in Cyprus

2010 ◽  
Vol 23 ◽  
pp. 73-78 ◽  
Author(s):  
F. Tymvios ◽  
K. Savvidou ◽  
S. C. Michaelides
Keyword(s):  
Geopotential Height ◽  
Heavy Rainfall ◽  
Eastern Mediterranean ◽  
Statistical Processing ◽  
Extreme Rainfall ◽  
Classification Performance ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
The Relationship ◽  
Heavy Rainfall Events

Abstract. Dynamically induced rainfall is strongly connected with synoptic atmospheric circulation patterns at the upper levels. This study investigates the relationship between days of high precipitation volume events in the eastern Mediterranean and the associated geopotential height patterns at 500 hPa. To reduce the number of different patterns and to simplify the statistical processing, the input days were classified into clusters of synoptic cases having similar characteristics, by utilizing Kohonen Self Organizing Maps (SOM) architecture. Using this architecture, synoptic patterns were grouped into 9, 18, 27 and 36 clusters which were subsequently used in the analysis. The classification performance was tested by applying the method to extreme rainfall events in the eastern Mediterranean. The relationship of the synoptic upper air patterns (500 hPa height) and surface features (heavy rainfall events) was established, while the 36 member classification proved to be the most efficient.

Startegic framework for integrated flood Disaster modelling over Bangalore city of India

2021 ◽  
Author(s):  
Smrati Purwar ◽  
Gyanendranath Mohapatra ◽  
Rakesh Vasudevan
Keyword(s):  
Urban Landscape ◽  
Flash Flood ◽  
Warning System ◽  
Extreme Rainfall ◽  
High Elevation ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Bangalore City ◽  
Societal Relevance ◽  
The Impact

<p>Hydro-meteorological disasters, particularly the extreme rainfall events (EREs) and associated flash floods, are very frequent in the major metro cities in India during recent years and in many occasions they cause massive destruction to life and property which in long run make adverse socio-economic impacts over the country. Hence, it makes formost importance and has great societal relevance to modellers working such area to develop an advance prediction system for such disasters in India.A strategic framework combining modelling and data analytics is integral part of developing advanced warning system for preparedness during such disasters. In this study, the role of landuse/landcover like built-up, vegetation, barrenland and waterbodies over the Bangalore city in flash flood occurrence is examined using multispectral spatio-temporal satellite data.The recent LULC map evidences a drastic changes in urban landscape that resulted in loss of natural drainage and waterbeds causing frequent floods. Digital Elevation Map (DEM) is analysed to know the  low-lying and high elevation topography compared with  Mean Sea Level(MSL)to quantify the impact of flooding during Extreme Rainfall Events(ERE) on the different part of the Bangalore city. Using Triangular Irregular Network (TIN), flood simulation is carried out for highland and lowlandarea  to study immediate affected areas during EREs Storm Water Modelling  is carried out for different regions in the city to obtain flood pattern, time and volume during selected EREs. The framework developed and simulation results are very useful in generation of management and mitigation strategy by various user agencies.</p>

scholarly journals Extreme rainfall events over Odisha state, India

MAUSAM ◽  
2021 ◽  
Vol 68 (1) ◽  
pp. 131-138
Author(s):  
S. PASUPALAK ◽  
G. PANIGRAHI ◽  
T. PANIGRAHI ◽  
S. MOHANTY ◽  
K. K. SINGH
Keyword(s):  
Heavy Rainfall ◽  
Hot Spot ◽  
Daily Rainfall ◽  
India Meteorological Department ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Rainfall Frequency ◽  
Before And After ◽  
Block Level

Extreme rainfall events are a significant cause of loss of life and livelihoods in Odisha. Objectives of the present study are to determine the trend of the extreme rainfall events during 1991-2014 and to compare the events between two periods before and after 1991. Block level daily rainfall data were used in identifying the extreme rainfall events, while district level aggregation was used in analysing the trend   in three categories, viz., heavy, very heavy and extremely heavy rainfall as per criteria given by India Meteorological Department (IMD). The state as a whole received one extremely heavy, nine very heavy, and forty heavy rainfall events in a year. When percentage of occurrence of each category out of the total extreme events over different districts was considered, maximum % of extremely heavy rainfall occurred in Kalahandi (5.8%), very heavy rainfall in Bolangir (23.8%) and heavy rainfall in Keonjhargarh (85.4%). Trend analysis showed that number of extreme rainfall events increased in a few districts, namely, Bolangir, Nuapada, Keonjhargarh, Koraput, Malkangiri, and Nawarangapur and did not change in other districts. In Puri district, extremely heavy rainfall frequency decreased. New all-time record high one-day rainfall events were observed in twenty districts during 1992 to 2014, surpassing the earlier records, which could be attributed to  climate change induced by  global warming. Interior south Odisha was found as the hot spot for extreme rainfalls.

Use of Normalized Anomaly Fields to Anticipate Extreme Rainfall in the Mountains of Northern California

2008 ◽  
Vol 23 (3) ◽  
pp. 336-356 ◽  
Author(s):  
Norman W. Junker ◽  
Richard H. Grumm ◽  
Robert Hart ◽  
Lance F. Bosart ◽  
Katherine M. Bell ◽  
...  
Keyword(s):  
Geopotential Height ◽  
Heavy Rainfall ◽  
Extreme Rainfall ◽  
The United States ◽  
Height Anomaly ◽  
Geopotential Height Anomaly ◽  
Northern California ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Heavy Rainfall Events

Abstract Extreme rainfall events contribute a large portion of wintertime precipitation to northern California. The motivations of this paper were to study the observed differences in the patterns between extreme and more commonly occurring lighter rainfall events, and to study whether anomaly fields might be used to discriminate between them. Daily (1200–1200 UTC) precipitation amounts were binned into three progressively heavier categories (12.5–50.0 mm, light; 50–100 mm, moderate; and >100 mm, heavy) in order to help identify the physical processes responsible for extreme precipitation in the Sierra Nevada range between 37.5° and 41.0°N. The composite fields revealed marked differences between the synoptic patterns associated with the three different groups. The heavy composites showed a much stronger, larger-scale, and slower-moving negative geopotential height anomaly off the Pacific coast of Oregon and Washington than was revealed in either of the other two composites. The heavy rainfall events were also typically associated with an atmospheric river with anomalously high precipitable water (PW) and 850-hPa moisture flux (MF) within it. The standardized PW and MF anomalies associated with the heavy grouping were higher and were slower moving than in either of the lighter bins. Three multiday heavy rainfall events were closely examined in order to ascertain whether anomaly patterns could provide forecast utility. Each of the multiday extreme rainfall events investigated was associated with atmospheric rivers that contained highly anomalous 850-hPa MF and PW within it. Each case was also associated with an unusually intense negative geopotential height anomaly that was similarly located off of the west coast of the United States. The similarities in the anomaly pattern among the three multiday extreme events suggest that standardized anomalies might be useful in predicting extreme multiday rainfall events in the northern Sierra range.

Extreme Rainfall Events in the Hawaiian Islands

2009 ◽  
Vol 48 (3) ◽  
pp. 502-516 ◽  
Author(s):  
Pao-Shin Chu ◽  
Xin Zhao ◽  
Ying Ruan ◽  
Melodie Grubbs
Keyword(s):  
Return Period ◽  
Heavy Rainfall ◽  
Hawaiian Islands ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Generalized Extreme Value Distribution ◽  
Economic Losses ◽  
Return Periods ◽  
Extreme Rainfall Events ◽  
Rainfall Events

Abstract Heavy rainfall and the associated floods occur frequently in the Hawaiian Islands and have caused huge economic losses as well as social problems. Extreme rainfall events in this study are defined by three different methods based on 1) the mean annual number of days on which 24-h accumulation exceeds a given daily rainfall amount, 2) the value associated with a specific daily rainfall percentile, and 3) the annual maximum daily rainfall values associated with a specific return period. For estimating the statistics of return periods, the three-parameter generalized extreme value distribution is fit using the method of L-moments. Spatial patterns of heavy and very heavy rainfall events across the islands are mapped separately based on the aforementioned three methods. Among all islands, the pattern on the island of Hawaii is most distinguishable, with a high frequency of events along the eastern slopes of Mauna Kea and a low frequency of events on the western portion so that a sharp gradient in extreme events from east to west is prominent. On other islands, extreme rainfall events tend to occur locally, mainly on the windward slopes. A case is presented for estimating return periods given different rainfall intensity for a station in Upper Manoa, Oahu. For the Halloween flood in 2004, the estimated return period is approximately 27 yr, and its true value should be no less than 13 yr with 95% confidence as determined from the adjusted bootstrap resampling technique.

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.

CLIMATOLOGY OF EXTREME RAINFALL EVENTS IN EASTERN AND NORTHERN SANTA CATARINA STATE, BRAZIL: PRESENT AND FUTURE CLIMATE

2013 ◽  
Vol 31 (3) ◽  
pp. 413 ◽  
Author(s):  
André Becker Nunes ◽  
Gilson Carlos Da Silva
Keyword(s):  
Climate Model ◽  
Climate Modeling ◽  
Linear Trend ◽  
Extreme Rainfall ◽  
Eastern Region ◽  
Santa Catarina ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
History Of ◽  
Santa Catarina State

ABSTRACT. The eastern region of Santa Catarina State (Brazil) has an important history of natural disasters due to extreme rainfall events. Floods and landslides are enhancedby local features such as orography and urbanization: the replacement of natural surface coverage causing more surface runoff and, hence, flooding. Thus, studies of this type of events – which directly influence life in the towns – take on increasing importance. This work makes a quantitative analysis of occurrences of extreme rainfall events in the eastern and northern regions of Santa Catarina State in the last 60 years, through individual analysis, considering the history of floods ineach selected town, as well as an estimate through to the end of century following regional climate modeling. A positive linear trend, in most of the towns studied, was observed in the results, indicating greater frequency of these events in recent decades, and the HadRM3P climate model shows a heterogeneous increase of events for all towns in the period from 2071 to 2100.Keywords: floods, climate modeling, linear trend. RESUMO. A região leste do Estado de Santa Catarina tem um importante histórico de desastres naturais ocasionados por eventos extremos de precipitação. Inundações e deslizamentos de terra são potencializados pelo relevo acidentado e pela urbanização das cidades da região: a vegetação nativa vem sendo removida acarretando um maior escoamento superficial e, consequentemente, em inundações. Desta forma, torna-se de suma importância os estudos acerca deste tipo de evento que influencia diretamente a sociedade em geral. Neste trabalho é realizada uma análise quantitativa do número de eventos severos de precipitação ocorridos nas regiões leste e norte de Santa Catarina dos últimos 60 anos, por meio de uma análise pontual, considerandoo histórico de inundações de cada cidade selecionada, além de uma projeção para o fim do século de acordo com modelagem climática regional. Na análise dos resultados observou-se uma tendência linear positiva na maioria das cidades, indicando uma maior frequência deste tipo de evento nas últimas décadas, e o modelo climático HadRM3P mostra um aumento heterogêneo no número de eventos para todas as cidades no período de 2071 a 2100.Palavras-chave: inundações, modelagem climática, tendência linear.

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