RainyDay: An Online, Open-Source Tool for Physically-based Rainfall and Flood Frequency Analysis

Science.gov (United States)

Wright, D.; Yu, G.; Holman, K. D.

2017-12-01

Flood frequency analysis in ungaged or changing watersheds typically requires rainfall intensity-duration-frequency (IDF) curves combined with hydrologic models. IDF curves only depict point-scale rainfall depth, while true rainstorms exhibit complex spatial and temporal structures. Floods result from these rainfall structures interacting with watershed features such as land cover, soils, and variable antecedent conditions as well as river channel processes. Thus, IDF curves are traditionally combined with a variety of "design storm" assumptions such as area reduction factors and idealized rainfall space-time distributions to translate rainfall depths into inputs that are suitable for flood hydrologic modeling. The impacts of such assumptions are relatively poorly understood. Meanwhile, modern precipitation estimates from gridded weather radar, grid-interpolated rain gages, satellites, and numerical weather models provide more realistic depictions of rainfall space-time structure. Usage of such datasets for rainfall and flood frequency analysis, however, are hindered by relatively short record lengths. We present RainyDay, an open-source stochastic storm transposition (SST) framework for generating large numbers of realistic rainfall "scenarios." SST "lengthens" the rainfall record by temporal resampling and geospatial transposition of observed storms to extract space-time information from regional gridded rainfall data. Relatively short (10-15 year) records of bias-corrected radar rainfall data are sufficient to estimate rainfall and flood events with much longer recurrence intervals including 100-year and 500-year events. We describe the SST methodology as implemented in RainyDay and compare rainfall IDF results from RainyDay to conventional estimates from NOAA Atlas 14. Then, we demonstrate some of the flood frequency analysis properties that are possible when RainyDay is integrated with a distributed hydrologic model, including robust estimation of flood

Dynamic Critical Rainfall-Based Flash Flood Early Warning and Forecasting for Medium-Small Rivers

Science.gov (United States)

Liu, Z.; Yang, D.; Hu, J.

2012-04-01

China is extremely frequent food disasters hit countries, annual flood season flash floods triggered by rainfall, mudslides, landslides have caused heavy casualties and property losses, not only serious threaten the lives of the masses, but the majority of seriously restricting the mountain hill areas of economic and social development and the people become rich, of building a moderately prosperous society goals. In the next few years, China will focus on prevention and control area in the flash flood disasters initially built "for the surveillance, communications, forecasting, early warning and other non-engineering measure based, non-engineering measures and the combinations of engineering measures," the mitigation system. The latest progresses on global torrential flood early warning and forecasting techniques are reviewed in this paper, and then an early warning and forecasting approach is proposed on the basis of a distributed hydrological model according to dynamic critical rainfall index. This approach has been applied in Suichuanjiang River basin in Jiangxi province, which is expected to provide valuable reference for building a national flash flood early warning and forecasting system as well as control of such flooding.

Analyses of the temporal and spatial structures of heavy rainfall from a catalog of high-resolution radar rainfall fields

DEFF Research Database (Denmark)

Thorndahl, Søren; Smith, James A.; Baeck, Mary Lynn

2014-01-01

that relate to size, structure and evolution of heavy rainfall. Extreme rainfall is also linked with severe weather (tornados, large hail and damaging wind). The diurnal cycle of rainfall for heavy rain days is characterized by an early peak in the largest rainfall rates, an afternoon-evening peak in rain...

Extreme flood event analysis in Indonesia based on rainfall intensity and recharge capacity

Science.gov (United States)

Narulita, Ida; Ningrum, Widya

2018-02-01

Indonesia is very vulnerable to flood disaster because it has high rainfall events throughout the year. Flood is categorized as the most important hazard disaster because it is causing social, economic and human losses. The purpose of this study is to analyze extreme flood event based on satellite rainfall dataset to understand the rainfall characteristic (rainfall intensity, rainfall pattern, etc.) that happened before flood disaster in the area for monsoonal, equatorial and local rainfall types. Recharge capacity will be analyzed using land cover and soil distribution. The data used in this study are CHIRPS rainfall satellite data on 0.05 ° spatial resolution and daily temporal resolution, and GSMap satellite rainfall dataset operated by JAXA on 1-hour temporal resolution and 0.1 ° spatial resolution, land use and soil distribution map for recharge capacity analysis. The rainfall characteristic before flooding, and recharge capacity analysis are expected to become the important information for flood mitigation in Indonesia.

Hurricane Agnes rainfall and floods, June-July 1972

Science.gov (United States)

Bailey, James F.; Patterson, James Lee; Paulhus, Joseph Louis Hornore

1975-01-01

Hurricane Agnes originated in the Caribbean Sea region in mid-June. Circulation barely reached hurricane intensity for a brief period in the Gulf of Mexico. The storm crossed the Florida Panhandle coastline on June 19, 1972, and followed an unusually extended overland trajectory combining with an extratropical system to bring very heavy rain from the Carolinas northward to New York. This torrential rain followed the abnormally wet May weather in the Middle Atlantic States and set the stage for the subsequent major flooding. The record-breaking floods occurred in the Middle Atlantic States in late June and early July 1972. Many streams in the affected area experienced peak discharges several times the previous maxima of record. Estimated recurrence intervals of peak flows at many gaging stations on major rivers and their tributaries exceeded 100 years. The suspended-sediment concentration and load of most flooded streams were also unusually high. The widespread flooding from this storm caused Agnes to be called the most destructive hurricane in United States history, claiming 117 lives and causing damage estimated at $3.1 billion in 12 States. Damage was particularly high in New York, Pennsylvania, Maryland, and Virginia. The detailed life history of Hurricane Agnes, including the tropical depression and tropical storm stages, is traced. Associated rainfalls are analyzed and compared with climatologic recurrence values. These are followed by a detailed description of the flood and streamflows of each affected basin. A summary of peak stages and discharges and comparison data for previous floods at 989 stations are presented. Deaths and flood damage estimates are compiled.

Assessment of vulnerability to extreme flash floods in design storms.

Science.gov (United States)

Kim, Eung Seok; Choi, Hyun Il

2011-07-01

There has been an increase in the occurrence of sudden local flooding of great volume and short duration caused by heavy or excessive rainfall intensity over a small area, which presents the greatest potential danger threat to the natural environment, human life, public health and property, etc. Such flash floods have rapid runoff and debris flow that rises quickly with little or no advance warning to prevent flood damage. This study develops a flash flood index through the average of the same scale relative severity factors quantifying characteristics of hydrographs generated from a rainfall-runoff model for the long-term observed rainfall data in a small ungauged study basin, and presents regression equations between rainfall characteristics and the flash flood index. The aim of this study is to develop flash flood index-duration-frequency relation curves by combining the rainfall intensity-duration-frequency relation and the flash flood index from probability rainfall data in order to evaluate vulnerability to extreme flash floods in design storms. This study is an initial effort to quantify the flash flood severity of design storms for both existing and planned flood control facilities to cope with residual flood risks due to extreme flash floods that have ocurred frequently in recent years.

Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

Science.gov (United States)

Costa, Veber; Fernandes, Wilson

2017-11-01

Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods

A Bayesian decision approach to rainfall thresholds based flood warning

Directory of Open Access Journals (Sweden)

M. L. V. Martina

2006-01-01

Full Text Available Operational real time flood forecasting systems generally require a hydrological model to run in real time as well as a series of hydro-informatics tools to transform the flood forecast into relatively simple and clear messages to the decision makers involved in flood defense. The scope of this paper is to set forth the possibility of providing flood warnings at given river sections based on the direct comparison of the quantitative precipitation forecast with critical rainfall threshold values, without the need of an on-line real time forecasting system. This approach leads to an extremely simplified alert system to be used by non technical stakeholders and could also be used to supplement the traditional flood forecasting systems in case of system failures. The critical rainfall threshold values, incorporating the soil moisture initial conditions, result from statistical analyses using long hydrological time series combined with a Bayesian utility function minimization. In the paper, results of an application of the proposed methodology to the Sieve river, a tributary of the Arno river in Italy, are given to exemplify its practical applicability.

Joint impact of rainfall and tidal level on flood risk in a coastal city with a complex river network: a case study of Fuzhou City, China

Directory of Open Access Journals (Sweden)

J. J. Lian

2013-02-01

Full Text Available Coastal cities are particularly vulnerable to flood under multivariable conditions, such as heavy precipitation, high sea levels, and storms. The combined effect of multiple sources and the joint probability of extremes should be considered to assess and manage flood risk better. This paper aims to study the combined effect of rainfall and the tidal level of the receiving water body on flood probability and severity in Fuzhou City, which has a complex river network. Flood severity under a range of precipitation intensities, with return periods (RPs of 5 yr to 100 yr, and tidal levels was assessed through a hydrodynamic model verified by data observed during Typhoon Longwang in 2005. According to the percentages of the river network where flooding occurred, the threshold conditions for flood severity were estimated in two scenarios: with and without working pumps. In Fuzhou City, working pumps efficiently reduce flood risk from precipitation within a 20-yr RP. However, the pumps may not work efficiently when rainfall exceeds a 100-yr RP because of the limited conveyance capacity of the river network. Joint risk probability was estimated through the optimal copula. The joint probability of rainfall and tidal level both exceeding their threshold values is very low, and the greatest threat in Fuzhou comes from heavy rainfall. However, the tidal level poses an extra risk of flood. Given that this extra risk is ignored in the design of flood defense in Fuzhou, flood frequency and severity may be higher than understood during design.

Simple Method for Assessing Spread of Flood Prone Areas under Historical and Future Rainfall in the Upper Citarum Watershed

Directory of Open Access Journals (Sweden)

Bambang Dwi Dasanto

2014-06-01

Full Text Available From 1931 to 2010 the flood frequency in Upper Citarum Watershed had increased sharply indicating the decline of the wateshed quality. With the change of climate, risk of the flood may get worse. This study aims to determine effective rainfall that caused flooding and to evaluate the impact of future rainfall changes on the flood prone areas. Effective rainfall which contributes to direct runoff (DRO and leads to flooding was determined using regression equation relating the DRO and cumulative rainfall of a number of consecutive days. Mapping the flood prone areas was developed using the GIS techniques. Results showed that the effective rainfall which caused flooding was the rainfall accumulation for four consecutive days before occurrence of peak of DRO. The percentage of accuracy between estimated and actual flood maps was about 76.9%. According to historical rainfall, the flood prone areas spreaded at right and left directions of the Upstream Citarum River. If this area experiences the climate change, the frequency and flood extents will increase. This study can only identify locations and possibility of flood occurrence but it cannot demonstrate widespread of flood inundation precisely. However, this simple approach can evaluate the flood frequency and intensity quite well.

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan.

Science.gov (United States)

Tsai, Kuang-Jung; Chiang, Jie-Lun; Lee, Ming-Hsi; Chen, Yie-Ruey

2017-04-01

Analysis on the Critical Rainfall Value For Predicting Large Scale Landslides Caused by Heavy Rainfall In Taiwan. Kuang-Jung Tsai 1, Jie-Lun Chiang 2,Ming-Hsi Lee 2, Yie-Ruey Chen 1, 1Department of Land Management and Development, Chang Jung Christian Universityt, Tainan, Taiwan. 2Department of Soil and Water Conservation, National Pingtung University of Science and Technology, Pingtung, Taiwan. ABSTRACT The accumulated rainfall amount was recorded more than 2,900mm that were brought by Morakot typhoon in August, 2009 within continuous 3 days. Very serious landslides, and sediment related disasters were induced by this heavy rainfall event. The satellite image analysis project conducted by Soil and Water Conservation Bureau after Morakot event indicated that more than 10,904 sites of landslide with total sliding area of 18,113ha were found by this project. At the same time, all severe sediment related disaster areas are also characterized based on their disaster type, scale, topography, major bedrock formations and geologic structures during the period of extremely heavy rainfall events occurred at the southern Taiwan. Characteristics and mechanism of large scale landslide are collected on the basis of the field investigation technology integrated with GPS/GIS/RS technique. In order to decrease the risk of large scale landslides on slope land, the strategy of slope land conservation, and critical rainfall database should be set up and executed as soon as possible. Meanwhile, study on the establishment of critical rainfall value used for predicting large scale landslides induced by heavy rainfall become an important issue which was seriously concerned by the government and all people live in Taiwan. The mechanism of large scale landslide, rainfall frequency analysis ,sediment budge estimation and river hydraulic analysis under the condition of extremely climate change during the past 10 years would be seriously concerned and recognized as a required issue by this

Rainfall characteristics and occurrence of floods in Gombe ...

African Journals Online (AJOL)

Gombe metropolis has been experiencing urban flooding particular in the last two decades. The flood disasters of 2004, 2012 and 2014 in the metropolis were alarming. This paper is aimed at analyzing the rainfall characteristics of Gombe metropolis in order to examine the implications on the occurrence of flooding in the ...

Heavy daily-rainfall characteristics over the Gauteng Province

African Journals Online (AJOL)

2009-02-09

Feb 9, 2009 ... the lowest number of heavy and very heavy rainfall days. The highest 24-h ... With regard to seasonal rainfall, the 1995/96 summer rainfall season had ..... The Gauteng Province is approximately 16 500 km2 in size. When the ...

Diagnosing Possible Anthropogenic Contributions to Heavy Colorado Rainfall in September 2013

Science.gov (United States)

Pall, Pardeep; Patricola, Christina; Wehner, Michael; Stone, Dáithí; Paciorek, Christopher; Collins, William

2015-04-01

Unusually heavy rainfall occurred over the Colorado Front Range during early September 2013, with record or near-record totals recorded in several locations. It was associated predominantly with a stationary large-scale weather pattern (akin to the North American Monsoon, which occurs earlier in the year) that drove a strong plume of deep moisture inland from the Gulf of Mexico against the Front Range foothills. The resulting floods across the South Platte River basin impacted several thousands of people and many homes, roads, and businesses. To diagnose possible anthropogenic contributions to the odds of such heavy rainfall, we adapt an existing event attribution paradigm of modelling an 'event that was' for September 2013 and comparing it to a modelled 'event that might have been' for that same time but for the absence of historical anthropogenic drivers of climate. Specifically, we first perform 'event that was' simulations with the regional Weather Research and Forecasting (WRF) model at 12 km resolution over North America, driven by NCEP2 re-analysis. We then re-simulate, having adjusted the re-analysis to 'event that might have been conditions' by modifying atmospheric greenhouse gas and other pollutant concentrations, temperature, humidity, and winds, as well as sea ice coverage, and sea-surface temperatures - all according to estimates from global climate model simulations. Thus our findings are highly conditional on the driving re-analysis and adjustments therein, but the setup allows us to elucidate possible mechanisms responsible for heavy Colorado rainfall in September 2013. Our model results suggests that, given an insignificant change in the pattern of large-scale driving weather, there is an increase in atmospheric water vapour under anthropogenic climate warming leading to a substantial increase in the probability of heavy rainfall occurring over the South Platte River basin in September 2013.

An Advanced Method to Apply Multiple Rainfall Thresholds for Urban Flood Warnings

Directory of Open Access Journals (Sweden)

Jiun-Huei Jang

2015-11-01

Full Text Available Issuing warning information to the public when rainfall exceeds given thresholds is a simple and widely-used method to minimize flood risk; however, this method lacks sophistication when compared with hydrodynamic simulation. In this study, an advanced methodology is proposed to improve the warning effectiveness of the rainfall threshold method for urban areas through deterministic-stochastic modeling, without sacrificing simplicity and efficiency. With regards to flooding mechanisms, rainfall thresholds of different durations are divided into two groups accounting for flooding caused by drainage overload and disastrous runoff, which help in grading the warning level in terms of emergency and severity when the two are observed together. A flood warning is then classified into four levels distinguished by green, yellow, orange, and red lights in ascending order of priority that indicate the required measures, from standby, flood defense, evacuation to rescue, respectively. The proposed methodology is tested according to 22 historical events in the last 10 years for 252 urbanized townships in Taiwan. The results show satisfactory accuracy in predicting the occurrence and timing of flooding, with a logical warning time series for taking progressive measures. For systems with multiple rainfall thresholds already in place, the methodology can be used to ensure better application of rainfall thresholds in urban flood warnings.

Should seasonal rainfall forecasts be used for flood preparedness?

NARCIS (Netherlands)

Coughlan, E.R.; Stephens, E.; Bischiniotis, K.; van Aalst, M.; van den Hurk, B.J.J.M.; Mason, S.; Nissan, H.; Pappenberger, F.

2017-01-01

In light of strong encouragement for disaster managers to use climate services for flood preparation, we question whether seasonal rainfall forecasts should indeed be used as indicators of the likelihood of flooding. Here, we investigate the primary indicators of flooding at the seasonal timescale

The Use of Water Vapor for Detecting Environments that Lead to Convectively Produced Heavy Precipitation and Flash Floods

Science.gov (United States)

Scofield, Rod; Vicente, Gilberto; Hodges, Mike

2000-01-01

This Tech Report summarizes years of study and experiences on using GOES Water vapor (6.7 micron and precipitable water) and Special Sensor Microwave Imager (SSM/1) from the Defense Meteorological Satellite Program (DMSP) derived Precipitable Water (PNAI) for detecting environments favorable for convectively produced flash floods. An emphasis is on the moisture. upper air flow, and equivalent potential temperature (Theta(sub e)) patterns that lead to devastating flood events. The 15 minute 6.7 micron water vapor imagery is essential for tracking middle to upper tropospheric disturbances that produce upward vertical motion and initiate flash flood producing systems. Water vapor imagery at 6.7 micron is also used to detect surges of upper level moisture (called tropical water vapor plumes) that have been associated with extremely heavy rainfall. Since the water vapor readily depicts lifting mechanisms and upper level moisture, water vapor imagery is often an excellent source of data for recognizing patterns of heavy precipitation and flash floods. In order to analyze the depth of the moisture, the PW aspects of the troposphere must be measured. The collocation (or nearby location) of high values ofP\\V and instability are antecedent conditions prior to the flash flood or heavy rainfall events. Knowledge of PW magnitudes have been used as thresholds for impending flash flood events, PW trends are essential in flash flood prediction. Conceptual models and water vapor products are used to study some of the characteristics of convective systems that occurred over the United States of America (USA) during the summer of 1997 and the 1997-1998 El Nino. P\\V plumes were associated with most of the \\vest coast heavy precipitation events examined during the winter season of 1997 - 1998, In another study, conducted during the summer season of 1997. results showed that the collocation of water vapor (6.7 micron) and P\\N' plumes possessed higher correlations with predicted

Real-time Extremely Heavy Rainfall Forecast and Warning over Rajasthan During the Monsoon Season (2016)

Science.gov (United States)

Srivastava, Kuldeep; Pradhan, D.

2018-01-01

Two events of extremely heavy rainfall occurred over Rajasthan during 7-9 August 2016 and 19-21 August 2016. Due to these events, flooding occurred over east Rajasthan and affected the normal life of people. A low-pressure area lying over northwest Madhya Pradesh on 7 August 2016 moved north-westward and lay near east Rajasthan and adjoining northwest Madhya Pradesh on 8 and 9 August 2016. Under the influence of this low-pressure system, Chittorgarh district and adjoining areas of Rajasthan received extremely heavy rainfall of 23 cm till 0300 UTC of 8 August 2016 and 34 cm on 0300 UTC of 9 August 2016. A deep depression lying over extreme south Uttar Pradesh and adjoining northeast Madhya Pradesh on 19 August 2016 moved westward and gradually weakened into a depression on 20 August 2016. It further weakened into a low-pressure area and lay over east Rajasthan on 21 and 22 August 2016. Under the influence of this deep depression, Jhalawar received 31 cm and Baran received 25 cm on 19 August. On 20 August 2016, extremely heavy rainfall (EHR) occurred over Banswara (23.5 cm), Pratapgarh (23.2 cm) and Chittorgarh (22.7 cm) districts. In this paper, the performance of the National Centers for Environmental Prediction (NCEP) global forecast system (GFS) model for real-time forecast and warning of heavy to very heavy/EHR that occurred over Rajasthan during 7-9 August 2016 and 19-21 August 2016 has been examined. The NCEP GFS forecast rainfall (Day 1, Day 2 and Day 3) was compared with the corresponding observed gridded rainfall. Based on the predictions given by the NCEP GFS model for heavy rainfall and with their application in real-time rainfall forecast and warnings issued by the Regional Weather Forecasting Center in New Delhi, it is concluded that the model has predicted the wind pattern and EHR event associated with the low-pressure system very accurately on day 1 and day 2 forecasts and with small errors in intensity and space for day 3.

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

OpenAIRE

Carolien Toté; Domingos Patricio; Hendrik Boogaard; Raymond van der Wijngaart; Elena Tarnavsky; Chris Funk

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Cl...

ANALYSIS OF RAINFALL PATTERN AND FLOOD INCIDENCES IN WARRI METROPOLIS, NIGERIA

Directory of Open Access Journals (Sweden)

R. Olanrewaju

2017-01-01

Full Text Available Climate change has led to changes in the known patterns of rainfall and other climatic variables as well as increase in the frequency and magnitude of natural disasters including floods in different parts of the world; and flood is indeed a global environmental issue that had destroyed lives and property amidst other untold hardships. The study examined rainfall characteristics in Warri metropolis for the past 30 years (1986-2015 vis-à-vis the flood situation in the metropolis; as well as the factors responsible and adaptation strategies to flood in the area. Dividing the study area into four zones after Sada (1977, the researchers collected rainfall data from the archives of Nigerian Meteorological Agency; 268 copies of questionnaire and oral interview were used. The result of the correlation analysis performed showed a negative relationship of -0.156 between rainfall and time (years, this implies that rainfall is decreasing over time. The trend line regression equation Y=243.75-0.4572X, confirms that rainfall in Warri Metropolis is decreasing at the rate of -0.45 per year. However, the p-value 0.412 is greater than 0.05, hence, the trend is not statistically significant at 95% level of confidence. It was discovered that rainfall, absence of drainage and poor urban planning practices (as factor 1 contributed 51.09% while overflowing of rivers, blocked/ poor drainage and untarred roads (as factor 2 contributed 44.10% variance to flood occurrence in the metropolis. Recommendations given included continual monitoring and study of rainfall characteristics and other climatic data and dissemination of such information for planning purposes; construction of integrated drainage system and river rechannelisation, legislation against dumping of refuse on roads and drainages; proper urban planning including implementation of the metropolitan urban drainage master plan. 

Development of Radar-Satellite Blended QPF (Quantitative Precipitation Forecast) Technique for heavy rainfall

Science.gov (United States)

Jang, Sangmin; Yoon, Sunkwon; Rhee, Jinyoung; Park, Kyungwon

2016-04-01

Due to the recent extreme weather and climate change, a frequency and size of localized heavy rainfall increases and it may bring various hazards including sediment-related disasters, flooding and inundation. To prevent and mitigate damage from such disasters, very short range forecasting and nowcasting of precipitation amounts are very important. Weather radar data very useful in monitoring and forecasting because weather radar has high resolution in spatial and temporal. Generally, extrapolation based on the motion vector is the best method of precipitation forecasting using radar rainfall data for a time frame within a few hours from the present. However, there is a need for improvement due to the radar rainfall being less accurate than rain-gauge on surface. To improve the radar rainfall and to take advantage of the COMS (Communication, Ocean and Meteorological Satellite) data, a technique to blend the different data types for very short range forecasting purposes was developed in the present study. The motion vector of precipitation systems are estimated using 1.5km CAPPI (Constant Altitude Plan Position Indicator) reflectivity by pattern matching method, which indicates the systems' direction and speed of movement and blended radar-COMS rain field is used for initial data. Since the original horizontal resolution of COMS is 4 km while that of radar is about 1 km, spatial downscaling technique is used to downscale the COMS data from 4 to 1 km pixels in order to match with the radar data. The accuracies of rainfall forecasting data were verified utilizing AWS (Automatic Weather System) observed data for an extreme rainfall occurred in the southern part of Korean Peninsula on 25 August 2014. The results of this study will be used as input data for an urban stream real-time flood early warning system and a prediction model of landslide. Acknowledgement This research was supported by a grant (13SCIPS04) from Smart Civil Infrastructure Research Program funded by

Flood Risk Regional Flood Defences : Technical report

NARCIS (Netherlands)

Kok, M.; Jonkman, S.N.; Lendering, K.T.

2015-01-01

Historically the Netherlands have always had to deal with the threat of flooding, both from the rivers and the sea as well as from heavy rainfall. The country consists of a large amount of polders, which are low lying areas of land protected from flooding by embankments. These polders require an

The use of geostationary satellite based rainfall estimation and rainfall-runoff modelling for regional flash flood assessment

OpenAIRE

Suseno, Dwi Prabowo Yuga

2013-01-01

The availability of rainfall triggered hazard information such as flash flood is crucial in the flood disaster management and mitigation. However, providing that information is mainly hampered by the shortage of data because of the sparse, uneven or absence the hydrological or meteorological observation. Remote sensing techniques that make frequent observations with continuous spatial coverage provide useful information for detecting the hydrometeorological phenomena such as rainfall and floo...

Flooding from Intense Rainfall: an overview of project SINATRA

Science.gov (United States)

Cloke, Hannah

2014-05-01

Project SINATRA (Susceptibility of catchments to INTense RAinfall and flooding) is part of the UK NERC's Flooding From Intense Rainfall (FFIR) research programme which aims to reduce the risks of damage and loss of life caused by surface water and flash floods through improved identification, characterisation and prediction of interacting meteorological, hydrological and hydro-morphological processes that contribute to flooding associated with high-intensity rainfall events. Extreme rainfall events may only last for a few hours at most, but can generate terrifying and destructive floods. Their impact can be affected by a wide range factors (or processes) such as the location and intensity of the rainfall, the shape and steepness of the catchment it falls on, how much sediment is moved by the water and the vulnerability of the communities in the flood's path. Furthermore, FFIR are by their nature rapid, making it very difficult for researchers to 'capture' measurements during events. The complexity, speed and lack of field measurements on FFIR make it difficult to create computer models to predict flooding and often we are uncertain as to their accuracy. In addition there is no consensus on how to identify how particular catchments may be vulnerable to FFIR, due to factors such as catchment area, shape, geology and soil type as well as land-use. Additionally, the catchments most susceptible to FFIR are often small and un-gauged. Project SINATRA will: (1) Increase our understanding of what factors cause FFIR and gathering new, high resolution measurements of FFIR by: assembling an archive of past FFIR events in Britain and their impacts, as a prerequisite for improving our ability to predict future occurrences of FFIR; making real time observations of flooding during flood events as well as post-event surveys and historical event reconstruction, using fieldwork and crowd-sourcing methods; and characterizing the physical drivers for UK summer flooding events by

FREQUENCY ANALYSIS OF RAINFALL FOR FLOOD CONTROL IN ...

African Journals Online (AJOL)

The Niger Delta Region of Nigeria is within the mangrove forest region and is crisscrossed by series of streams and creeks. As a result of the high rainfall volume within this region there is a tendency for severe flooding to occur. These flood events have severe consequences on lives and properties. It is therefore necessary ...

Stochastic Urban Pluvial Flood Hazard Maps Based upon a Spatial-Temporal Rainfall Generator

Directory of Open Access Journals (Sweden)

Nuno Eduardo Simões

2015-06-01

Full Text Available It is a common practice to assign the return period of a given storm event to the urban pluvial flood event that such storm generates. However, this approach may be inappropriate as rainfall events with the same return period can produce different urban pluvial flooding events, i.e., with different associated flood extent, water levels and return periods. This depends on the characteristics of the rainfall events, such as spatial variability, and on other characteristics of the sewer system and the catchment. To address this, the paper presents an innovative contribution to produce stochastic urban pluvial flood hazard maps. A stochastic rainfall generator for urban-scale applications was employed to generate an ensemble of spatially—and temporally—variable design storms with similar return period. These were used as input to the urban drainage model of a pilot urban catchment (~9 km2 located in London, UK. Stochastic flood hazard maps were generated through a frequency analysis of the flooding generated by the various storm events. The stochastic flood hazard maps obtained show that rainfall spatial-temporal variability is an important factor in the estimation of flood likelihood in urban areas. Moreover, as compared to the flood hazard maps obtained by using a single spatially-uniform storm event, the stochastic maps generated in this study provide a more comprehensive assessment of flood hazard which enables better informed flood risk management decisions.

Urban Flooding Analysis Using Radar Rainfall Data and 2-D Hydrodynamic Model: A Pilot Study of Back Cover Area, Portland, Maine

Energy Technology Data Exchange (ETDEWEB)

Yan, Eugene [Argonne National Lab. (ANL), Argonne, IL (United States); Pierce, Julia [Argonne National Lab. (ANL), Argonne, IL (United States); Mahat, Vinod [Argonne National Lab. (ANL), Argonne, IL (United States); Jared, Alissa [Argonne National Lab. (ANL), Argonne, IL (United States); Collis, Scott [Argonne National Lab. (ANL), Argonne, IL (United States); Verner, Duane [Argonne National Lab. (ANL), Argonne, IL (United States); Wall, Thomas [Argonne National Lab. (ANL), Argonne, IL (United States)

2016-11-01

This project is a part of the Regional Resiliency Assessment Program, led by the Department of Homeland Security, to address flooding hazards of regional significance for Portland, Maine. The pilot study was performed by Argonne National Laboratory to identify differences in spatial rainfall distributions between the radar-derived and rain-gauge rainfall datasets and to evaluate their impacts on urban flooding. The flooding impact analysis utilized a high-resolution 2-dimensional (2-D) hydrodynamic model (15 ft by 15 ft) incorporating the buildings, streets, stream channels, hydraulic structures, an existing city storm drain system, and assuming a storm surge along the coast coincident with a heavy rainfall event. Two historical storm events from April 16, 2007, and September 29, 2015, were selected for evaluation. The radar-derived rainfall data at a 200-m resolution provide spatially-varied rainfall patterns with a wide range of intensities for each event. The resultant maximum flood depth using data from a single rain gauge within the study area could be off (either under- or over-estimated) by more than 10% in the 2007 storm and more than 60% in the 2015 storm compared to the radar-derived rainfall data. The model results also suggest that the inundation area with a flow depth at or greater than 0.5 ft could reach 11% (2007 storm) and 17% (2015 storm) of the total study area, respectively. The lowland areas within the neighborhoods of North Deering, East Deering, East and West Baysides and northeastern Parkside, appear to be more vulnerable to the flood hazard in both storm events. The high-resolution 2-D hydrodynamic model with high-resolution radar-derived rainfall data provides an excellent tool for detailed urban flood analysis and vulnerability assessment. The model developed in this study could be potentially used to evaluate any proposed mitigation measures and optimize their effects in the future for Portland, ME.

The Complex Relationship Between Heavy Storms and Floods: Implication on Stormwater Drainage design and Management

Science.gov (United States)

Demissie, Y.; Mortuza, M. R.; Moges, E.; Yan, E.; Li, H. Y.

2017-12-01

Due to the lack of historical and future streamflow data for flood frequency analysis at or near most drainage sites, it is a common practice to directly estimate the design flood (maximum discharge or volume of stream for a given return period) based on storm frequency analysis and the resulted Intensity-Duration-Frequency (IDF) curves. Such analysis assumes a direct relationship between storms and floods with, for example, the 10-year rainfall expected to produce the 10-year flood. However, in reality, a storm is just one factor among the many other hydrological and metrological factors that can affect the peak flow and hydrograph. Consequently, a heavy storm does not necessarily always lead to flooding or a flood events with the same frequency. This is evident by the observed difference in the seasonality of heavy storms and floods in most regions. In order to understand site specific causal-effect relationship between heavy storms and floods and improve the flood analysis for stormwater drainage design and management, we have examined the contributions of various factors that affect floods using statistical and information theory methods. Based on the identified dominant causal-effect relationships, hydrologic and probability analyses were conducted to develop the runoff IDF curves taking into consideration the snowmelt and rain-on-snow effect, the difference in the storm and flood seasonality, soil moisture conditions, and catchment potential for flash and riverine flooding. The approach was demonstrated using data from military installations located in different parts of the United States. The accuracy of the flood frequency analysis and the resulted runoff IDF curves were evaluated based on the runoff IDF curves developed from streamflow measurements.

“Expect More Floods In 2013”: An analysis of flood preparedness in ...

African Journals Online (AJOL)

In 2013, the Nigerian Meteorological Agency (NIMET) issued a prediction of heavy rainfall with consequent flooding in some major cities of Nigeria particularly Ibadan. In light of the country's previous flood experiences, citizens and government were promptly alerted and advised to be fully prepared for imminent floods.

Multi-catchment rainfall-runoff simulation for extreme flood estimation

Science.gov (United States)

Paquet, Emmanuel

2017-04-01

The SCHADEX method (Paquet et al., 2013) is a reference method in France for the estimation of extreme flood for dam design. The method is based on a semi-continuous rainfall-runoff simulation process: hundreds of different rainy events, randomly drawn up to extreme values, are simulated independently in the hydrological conditions of each day when a rainy event has been actually observed. This allows generating an exhaustive set of crossings between precipitation and soil saturation hazards, and to build a complete distribution of flood discharges up to extreme quantiles. The hydrological model used within SCHADEX, the MORDOR model (Garçon, 1996), is a lumped model, which implies that hydrological processes, e.g. rainfall and soil saturation, are supposed to be homogeneous throughout the catchment. Snow processes are nevertheless represented in relation with altitude. This hypothesis of homogeneity is questionable especially as the size of the catchment increases, or in areas of highly contrasted climatology (like mountainous areas). Conversely, modeling the catchment with a fully distributed approach would cause different problems, in particular distributing the rainfall-runoff model parameters trough space, and within the SCHADEX stochastic framework, generating extreme rain fields with credible spatio-temporal features. An intermediate solution is presented here. It provides a better representation of the hydro-climatic diversity of the studied catchment (especially regarding flood processes) while keeping the SCHADEX simulation framework. It consists in dividing the catchment in several, more homogeneous sub-catchments. Rainfall-runoff models are parameterized individually for each of them, using local discharge data if available. A first SCHADEX simulation is done at the global scale, which allows assigning a probability to each simulated event, mainly based on the global areal rainfall drawn for the event (see Paquet el al., 2013 for details). Then the

A space-time hybrid hourly rainfall model for derived flood frequency analysis

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U. Haberlandt

2008-12-01

Full Text Available For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfall time series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series.

First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HEC-HMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in

Impact of the Rainfall Duration and Temporal Rainfall Distribution Defined Using the Huff Curves on the Hydraulic Flood Modelling Results

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Nejc Bezak

2018-02-01

Full Text Available In the case of ungauged catchments, different procedures can be used to derive the design hydrograph and design peak discharge, which are crucial input data for the design of different hydrotechnical engineering structures, or the production of flood hazard maps. One of the possible approaches involves using a hydrological model where one can calculate the design hydrograph through the design of a rainfall event. This study investigates the impact of the design rainfall on the combined one-dimensional/two-dimensional (1D/2D hydraulic modelling results. The Glinščica Stream catchment located in Slovenia (central Europe is used as a case study. Ten different design rainfall events were compared for 10 and 100-year return periods, where we used Huff curves for the design rainfall event definition. The results indicate that the selection of the design rainfall event should be regarded as an important step, since the hydraulic modelling results for different scenarios differ significantly. In the presented experimental case study, the maximum flooded area extent was twice as large as the minimum one, and the maximum water velocity over flooded areas was more than 10 times larger than the minimum one. This can lead to the production of very different flood hazard maps, and consequently planning very different flood protection schemes.

Dealing with rainfall forecast uncertainties in real-time flood control along the Demer river

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Vermuyten Evert

2016-01-01

Full Text Available Real-time Model Predictive Control (MPC of hydraulic structures strongly reduces flood consequences under ideal circumstances. The performance of such flood control may, however, be significantly affected by uncertainties. This research quantifies the influence of rainfall forecast uncertainties and related uncertainties in the catchment rainfall-runoff discharges on the control performance for the Herk river case study in Belgium. To limit the model computational times, a fast conceptual model is applied. It is calibrated to a full hydrodynamic river model. A Reduced Genetic Algorithm is used as optimization method. Next to the analysis of the impact of the rainfall forecast uncertainties on the control performance, a Multiple Model Predictive Control (MMPC approach is tested to reduce this impact. Results show that the deterministic MPC-RGA outperforms the MMPC and that it is inherently robust against rainfall forecast uncertainties due to its receding horizon strategy.

Integrated Urban Flood Analysis considering Optimal Operation of Flood Control Facilities in Urban Drainage Networks

Science.gov (United States)

Moon, Y. I.; Kim, M. S.; Choi, J. H.; Yuk, G. M.

2017-12-01

eavy rainfall has become a recent major cause of urban area flooding due to the climate change and urbanization. To prevent property damage along with casualties, a system which can alert and forecast urban flooding must be developed. Optimal performance of reducing flood damage can be expected of urban drainage facilities when operated in smaller rainfall events over extreme ones. Thus, the purpose of this study is to execute: A) flood forecasting system using runoff analysis based on short term rainfall; and B) flood warning system which operates based on the data from pump stations and rainwater storage in urban basins. In result of the analysis, it is shown that urban drainage facilities using short term rainfall forecasting data by radar will be more effective to reduce urban flood damage than using only the inflow data of the facility. Keywords: Heavy Rainfall, Urban Flood, Short-term Rainfall Forecasting, Optimal operating of urban drainage facilities. AcknowledgmentsThis research was supported by a grant (17AWMP-B066744-05) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport of Korean government.

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

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Carolien Toté

2015-02-01

Full Text Available Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT v2.0, Famine Early Warning System NETwork (FEWS NET Rainfall Estimate (RFE v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS are compared to independent gauge data (2001–2012. This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Evaluation of satellite rainfall estimates for drought and flood monitoring in Mozambique

Science.gov (United States)

Tote, Carolien; Patricio, Domingos; Boogaard, Hendrik; van der Wijngaart, Raymond; Tarnavsky, Elena; Funk, Christopher C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and floods and thus, an understanding of the strengths and weaknesses of different rainfall products is valuable. Three dekadal (10-day) gridded satellite rainfall products (TAMSAT African Rainfall Climatology And Time-series (TARCAT) v2.0, Famine Early Warning System NETwork (FEWS NET) Rainfall Estimate (RFE) v2.0, and Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS)) are compared to independent gauge data (2001–2012). This is done using pairwise comparison statistics to evaluate the performance in estimating rainfall amounts and categorical statistics to assess rain-detection capabilities. The analysis was performed for different rainfall categories, over the seasonal cycle and for regions dominated by different weather systems. Overall, satellite products overestimate low and underestimate high dekadal rainfall values. The RFE and CHIRPS products perform as good, generally outperforming TARCAT on the majority of statistical measures of skill. TARCAT detects best the relative frequency of rainfall events, while RFE underestimates and CHIRPS overestimates the rainfall events frequency. Differences in products performance disappear with higher rainfall and all products achieve better results during the wet season. During the cyclone season, CHIRPS shows the best results, while RFE outperforms the other products for lower dekadal rainfall. Products blending thermal infrared and passive microwave imagery perform better than infrared only products and particularly when meteorological patterns are more complex, such as over the coastal, central and south regions of Mozambique, where precipitation is influenced by frontal systems.

Grey Forecast Rainfall with Flow Updating Algorithm for Real-Time Flood Forecasting

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Jui-Yi Ho

2015-04-01

Full Text Available The dynamic relationship between watershed characteristics and rainfall-runoff has been widely studied in recent decades. Since watershed rainfall-runoff is a non-stationary process, most deterministic flood forecasting approaches are ineffective without the assistance of adaptive algorithms. The purpose of this paper is to propose an effective flow forecasting system that integrates a rainfall forecasting model, watershed runoff model, and real-time updating algorithm. This study adopted a grey rainfall forecasting technique, based on existing hourly rainfall data. A geomorphology-based runoff model can be used for simulating impacts of the changing geo-climatic conditions on the hydrologic response of unsteady and non-linear watershed system, and flow updating algorithm were combined to estimate watershed runoff according to measured flow data. The proposed flood forecasting system was applied to three watersheds; one in the United States and two in Northern Taiwan. Four sets of rainfall-runoff simulations were performed to test the accuracy of the proposed flow forecasting technique. The results indicated that the forecast and observed hydrographs are in good agreement for all three watersheds. The proposed flow forecasting system could assist authorities in minimizing loss of life and property during flood events.

ICUD-0147 Extreme event statistics of urban pluvial floods – Return period assessment and rainfall variability impacts

DEFF Research Database (Denmark)

Tuyls, Damian Murla; Nielsen, Rasmus; Thorndahl, Søren Liedtke

2017-01-01

A return period assessment of urban flood has been performed and its adhered impact of rainfall variability studied over a urban drainage catchment area in Aalborg, Denmark. Recorded rainfall from 7 rain gauges has been used, located in a range of 7.5Km and for a period varying form 18-37 years....... Return period of rainfall and flood at catchment and local scale has been estimated, its derived ambiguities analysed and the variability of rain gauge based rainfall investigated regarding to flood estimation results. Results show a clear contrast between rainfall and flood return period estimates...

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

Science.gov (United States)

Gaitan, S.; ten Veldhuis, J. A. E.

2015-06-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

FLASH-FLOOD MODELLING WITH ARTIFICIAL NEURAL NETWORKS USING RADAR RAINFALL ESTIMATES

Directory of Open Access Journals (Sweden)

Dinu Cristian

2017-09-01

Full Text Available The use of artificial neural networks (ANNs in modelling the hydrological processes has become a common approach in the last two decades, among side the traditional methods. In regard to the rainfall-runoff modelling, in both traditional and ANN models the use of ground rainfall measurements is prevalent, which can be challenging in areas with low rain gauging station density, especially in catchments where strong focused rainfall can generate flash-floods. The weather radar technology can prove to be a solution for such areas by providing rain estimates with good time and space resolution. This paper presents a comparison between different ANN setups using as input both ground and radar observations for modelling the rainfall-runoff process for Bahluet catchment, with focus on a flash-flood observed in the catchment.

Analysis and simulation of mesoscale convective systems accompanying heavy rainfall: The goyang case

Science.gov (United States)

Choi, Hyun-Young; Ha, Ji-Hyun; Lee, Dong-Kyou; Kuo, Ying-Hwa

2011-05-01

We investigated a torrential rainfall case with a daily rainfall amount of 379 mm and a maximum hourly rain rate of 77.5 mm that took place on 12 July 2006 at Goyang in the middlewestern part of the Korean Peninsula. The heavy rainfall was responsible for flash flooding and was highly localized. High-resolution Doppler radar data from 5 radar sites located over central Korea were analyzed. Numerical simulations using the Weather Research and Forecasting (WRF) model were also performed to complement the high-resolution observations and to further investigate the thermodynamic structure and development of the convective system. The grid nudging method using the Global Final (FNL) Analyses data was applied to the coarse model domain (30 km) in order to provide a more realistic and desirable initial and boundary conditions for the nested model domains (10 km, 3.3 km). The mesoscale convective system (MCS) which caused flash flooding was initiated by the strong low level jet (LLJ) at the frontal region of high equivalent potential temperature (θe) near the west coast over the Yellow Sea. The ascending of the warm and moist air was induced dynamically by the LLJ. The convective cells were triggered by small thermal perturbations and abruptly developed by the warm θe inflow. Within the MCS, several convective cells responsible for the rainfall peak at Goyang simultaneously developed with neighboring cells and interacted with each other. Moist absolutely unstable layers (MAULs) were seen at the lower troposphere with the very moist environment adding the instability for the development of the MCS.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

Directory of Open Access Journals (Sweden)

Greg Easson

2007-12-01

Full Text Available Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25o to 0.50o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA’s Tropical Rainfall Measuring Mission (TRMM Multi-satellitePrecipitation Analysis (TMPA product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

Towards large scale stochastic rainfall models for flood risk assessment in trans-national basins

Science.gov (United States)

Serinaldi, F.; Kilsby, C. G.

2012-04-01

While extensive research has been devoted to rainfall-runoff modelling for risk assessment in small and medium size watersheds, less attention has been paid, so far, to large scale trans-national basins, where flood events have severe societal and economic impacts with magnitudes quantified in billions of Euros. As an example, in the April 2006 flood events along the Danube basin at least 10 people lost their lives and up to 30 000 people were displaced, with overall damages estimated at more than half a billion Euros. In this context, refined analytical methods are fundamental to improve the risk assessment and, then, the design of structural and non structural measures of protection, such as hydraulic works and insurance/reinsurance policies. Since flood events are mainly driven by exceptional rainfall events, suitable characterization and modelling of space-time properties of rainfall fields is a key issue to perform a reliable flood risk analysis based on alternative precipitation scenarios to be fed in a new generation of large scale rainfall-runoff models. Ultimately, this approach should be extended to a global flood risk model. However, as the need of rainfall models able to account for and simulate spatio-temporal properties of rainfall fields over large areas is rather new, the development of new rainfall simulation frameworks is a challenging task involving that faces with the problem of overcoming the drawbacks of the existing modelling schemes (devised for smaller spatial scales), but keeping the desirable properties. In this study, we critically summarize the most widely used approaches for rainfall simulation. Focusing on stochastic approaches, we stress the importance of introducing suitable climate forcings in these simulation schemes in order to account for the physical coherence of rainfall fields over wide areas. Based on preliminary considerations, we suggest a modelling framework relying on the Generalized Additive Models for Location, Scale

Enhanced Orographic Tropical Rainfall: An Study of the Colombia's rainfall

Science.gov (United States)

Peñaranda, V. M.; Hoyos Ortiz, C. D.; Mesa, O. J.

2015-12-01

Convection in tropical regions may be enhanced by orographic barriers. The orographic enhancement is an intensification of rain rates caused by the forced lifting of air over a mountainous structure. Orographic heavy rainfall events, occasionally, comes along by flooding, debris flow and substantial amount of looses, either economics or human lives. Most of the heavy convective rainfall events, occurred in Colombia, have left a lot of victims and material damages by flash flooding. An urgent action is required by either scientific communities or society, helping to find preventive solutions against these kind of events. Various scientific literature reports address the feedback process between the convection and the local orographic structures. The orographic enhancement could arise by several physical mechanism: precipitation transport on leeward side, convection triggered by the forcing of air over topography, the seeder-feeder mechanism, among others. The identification of the physical mechanisms for orographic enhancement of rainfall has not been studied over Colombia. As far as we know, orographic convective tropical rainfall is just the main factor for the altitudinal belt of maximum precipitation, but the lack of detailed hydro-meteorological measurements have precluded a complete understanding of the tropical rainfall in Colombia and its complex terrain. The emergence of the multifractal theory for rainfall has opened a field of research which builds a framework for parsimonious modeling of physical process. Studies about the scaling behavior of orographic rainfall have found some modulating functions between the rainfall intensity probability distribution and the terrain elevation. The overall objective is to advance in the understanding of the orographic influence over the Colombian tropical rainfall based on observations and scaling-analysis techniques. We use rainfall maps, weather radars scans and ground-based rainfall data. The research strategy is

Characterization of rainfall events and correlation with reported disasters: A case in Cali, Colombia

Science.gov (United States)

Canon, C. C.; Tischbein, B.; Bogardi, J.

2017-12-01

Flood maps generally display the area that a river might overflow after a rainfall event takes place, under different scenarios of climate, land use/land cover, and/or failure of dams and dikes. However, rainfall is not limited to feed runoff and enlarge the river: it also causes minor disasters outside the map's highlighted area. The city of Cali in Colombia illustrates very well this situation: its flat topography and its major critical infrastructure near the river make it flood-risk prone; a heavy rainfall event would potentially deplete drinking water, electrical power and drainage capacity, and trigger outbreaks of water-borne diseases in the whole city, not only in the flooded area. Unfortunately, the government's disaster prevention strategies focus on the floodplain and usually overlook the aftermath of these minor disasters for being milder and scattered. Predicted losses in flood maps are potentially big, while those from minor disasters over the city are small but real, and citizens, utility companies and urban maintenance funds must constantly take them over. Mitigation and prevention of such minor disasters can save money for the development of the city in other aspects. This paper characterizes hundreds of rainfall events selected from 10-min step time series from 2006 to 2017, and finds their correlation with reported rainfall-related disasters throughout Cali, identified by date and neighborhood. Results show which rainfall parameters are most likely to indicate the occurrence of such disasters and their approximate location in the urban area of Cali. These results, when coupled with real-time observations of rainfall data and simulations of drainage network response, may help citizens and emergency bodies prioritize zones to assist during heavy storms. In the long term, stakeholders may also implement low impact development solutions in these zones to reduce flood risks.

A framework of integrated hydrological and hydrodynamic models using synthetic rainfall for flash flood hazard mapping of ungauged catchments in tropical zones

Directory of Open Access Journals (Sweden)

W. Lohpaisankrit

2016-05-01

Full Text Available Flash flood hazard maps provide a scientific support to mitigate flash flood risk. The present study develops a practical framework with the help of integrated hydrological and hydrodynamic modelling in order to estimate the potential flash floods. We selected a small pilot catchment which has already suffered from flash floods in the past. This catchment is located in the Nan River basin, northern Thailand. Reliable meteorological and hydrometric data are missing in the catchment. Consequently, the entire upper basin of the main river was modelled with the help of the hydrological modelling system PANTA RHEI. In this basin, three monitoring stations are located along the main river. PANTA RHEI was calibrated and validated with the extreme flood events in June 2011 and July 2008, respectively. The results show a good agreement with the observed discharge data. In order to create potential flash flood scenarios, synthetic rainfall series were derived from temporal rainfall patterns based on the radar-rainfall observation and different rainfall depths from regional rainfall frequency analysis. The temporal rainfall patterns were characterized by catchment-averaged rainfall series selected from 13 rainstorms in 2008 and 2011 within the region. For regional rainfall frequency analysis, the well-known L-moments approach and related criteria were used to examine extremely climatic homogeneity of the region. According to the L-moments approach, Generalized Pareto distribution was recognized as the regional frequency distribution. The synthetic rainfall series were fed into the PANTA RHEI model. The simulated results from PANTA RHEI were provided to a 2-D hydrodynamic model (MEADFLOW, and various simulations were performed. Results from the integrated modelling framework are used in the ongoing study to regionalize and map the spatial distribution of flash flood hazards with four levels of flood severities. As an overall outcome, the presented framework

Opportunities for multivariate analysis of open spatial datasets to characterize urban flooding risks

Directory of Open Access Journals (Sweden)

S. Gaitan

2015-06-01

Full Text Available Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to reduce flooding impacts. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall, socioeconomic characteristics, and social sensing, may help to explain probability and impacts of urban flooding. Several spatial datasets have been recently made available in the Netherlands, including rainfall-related incident reports made by citizens, spatially distributed rain depths, semidistributed socioeconomic information, and buildings age. Inspecting the potential of this data to explain the occurrence of rainfall related incidents has not been done yet. Multivariate analysis tools for describing communities and environmental patterns have been previously developed and used in the field of study of ecology. The objective of this paper is to outline opportunities for these tools to explore urban flooding risks patterns in the mentioned datasets. To that end, a cluster analysis is performed. Results indicate that incidence of rainfall-related impacts is higher in areas characterized by older infrastructure and higher population density.

Comparison of Adaline and Multiple Linear Regression Methods for Rainfall Forecasting

Science.gov (United States)

Sutawinaya, IP; Astawa, INGA; Hariyanti, NKD

2018-01-01

Heavy rainfall can cause disaster, therefore need a forecast to predict rainfall intensity. Main factor that cause flooding is there is a high rainfall intensity and it makes the river become overcapacity. This will cause flooding around the area. Rainfall factor is a dynamic factor, so rainfall is very interesting to be studied. In order to support the rainfall forecasting, there are methods that can be used from Artificial Intelligence (AI) to statistic. In this research, we used Adaline for AI method and Regression for statistic method. The more accurate forecast result shows the method that used is good for forecasting the rainfall. Through those methods, we expected which is the best method for rainfall forecasting here.

Landsliding and flooding event triggered by heavy rains in the Rize region

Science.gov (United States)

Yalcin, Ali; Kavurmaci, M. Murat

2013-04-01

Rize province has been significantly damaged by frequent landslides and floods which are caused by severe rainfalls and result in many casualties. The area is prone to landslides because of the climate conditions, geologic, and land cover characteristics of the region. The most recent landslide occurred on August 26, 2010 in Gundogdu town. The landslides have caused large numbers of casualties and huge economic losses in the region. Thirteen people died, twenty houses collapsed, more than a hundred houses damaged, and one hundred fifty vehicles were damaged in the Gundogdu landslide. Flood event is often seen in the region of Rize, due to continuous rainfall. Floods cause huge loss of life and property in this region. Rainfall is the most frequent landslide-triggering factor in East Black Sea region, Turkey, especially Rize region. Rize is the rainiest city of Turkey. Total annual precipitation is over 2300 mm, and precipitation is equally distributed in each month. However, in August 26, 166.5 mm precipitation rained within 24 hours in the region and this rainstorm caused great damage. The intensity rainfall periods were become as an indicator of landslide activity. It is very important that the presence of suitable lithologic units for occurring landslides. There are appropriate materials to contributed constitution of landslides in the study area; completely weathered dacite. In addition, intensity land cover types as tea plantations have been blocked surface flows and rainfall is able to quickly penetrate into the soil through open tension cracks that appear in the landslide head and in stretching zones. According to the results of the analysis, the study area has been overlaid tea garden 70 % percentage approximately. Furthermore, the landslide risks have increased by devastation of land cover in this region. In this region, over-steepened slopes, slope saturation in areas of heavy rainfall, and removal of slope vegetation can also increase landslide potential

Rainfall variability and floods occurrence in the city of Bamenda (Northwest of Cameroon

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Frederic Saha

2017-06-01

Full Text Available This study is based on analysis of rainfall data from 1951-2010 collected at the climatic station of Bamenda. We also use the results of a questionnaire survey applied to 172 households in at-risk neighborhoods. The inventory of some cases of flooding that occurred in the city of Bamenda was done through focus groups. The appreciation of the socio-economic and demographic environment is based on surveys among Cameroonian Households by the National Institute of Statistics (NIS and General Census of Population and Housing. Statistical examination revealed that annual rainfall in the city of Bamenda experienced a break in 1958. This break buckled the wettest decade of the series. After three decades of worsening, rainfall is experiencing rising since early 1990. The average profile of the annual distribution of rainfall shows a concentration of over 53% in 03 months (July, August and September. During these three months, the rivers of the city know their flood flows and populations in the valleys are affected. The analysis of the annual number of rainy days shows a downward trend and an increase of extreme rainfall event frequency (≥50mm in 24h. It is also apparent that more and more years are experiencing erratic distribution of their precipitation. Then, the perception of people is significantly reduced. Subsistence activities are also affected and development is facing new subtleties. In conclusion, the rainfall experienced strong variability in the city of Bamenda. This situation reinforces the risk of flooding by increasing flood water and increasing the vulnerability of populations.

Real-time dynamic control of the Three Gorges Reservoir by coupling numerical weather rainfall prediction and flood forecasting

DEFF Research Database (Denmark)

Wang, Y.; Chen, H.; Rosbjerg, Dan

2013-01-01

In reservoir operation improvement of the accuracy of forecast flood inflow and extension of forecast lead-time can effectively be achieved by using rainfall forecasts from numerical weather predictions with a hydrological catchment model. In this study, the Regional Spectrum Model (RSM), which...... is developed by the Japan Meteorological Agency, was used to forecast rainfall with 5 days lead-time in the upper region of the Three Gorges Reservoir (TGR). A conceptual hydrological model, the Xinanjiang Model, has been set up to forecast the inflow flood of TGR by the Ministry of Water Resources Information...... season 2012 as example, real-time dynamic control of the FLWL was implemented by using the forecasted reservoir flood inflow as input. The forecasted inflow with 5 days lead-time rainfall forecast was evaluated by several performance indices, including the mean relative error of the volumetric reservoir...

Simulation of rainfall-runoff for major flash flood events in Karachi

Science.gov (United States)

Zafar, Sumaira

2016-07-01

Metropolitan city Karachi has strategic importance for Pakistan. With the each passing decade the city is facing urban sprawl and rapid population growth. These rapid changes directly affecting the natural resources of city including its drainage pattern. Karachi has three major cities Malir River with the catchment area of 2252 sqkm and Lyari River has catchment area about 470.4 sqkm. These are non-perennial rivers and active only during storms. Change of natural surfaces into hard pavement causing an increase in rainfall-runoff response. Curve Number is increased which is now causing flash floods in the urban locality of Karachi. There is only one gauge installed on the upstream of the river but there no record for the discharge. Only one gauge located at the upstream is not sufficient for discharge measurements. To simulate the maximum discharge of Malir River rainfall (1985 to 2014) data were collected from Pakistan meteorological department. Major rainfall events use to simulate the rainfall runoff. Maximum rainfall-runoff response was recorded in during 1994, 2007 and 2013. This runoff causes damages and inundation in floodplain areas of Karachi. These flash flooding events not only damage the property but also cause losses of lives

A Mediterranean nocturnal heavy rainfall and tornadic event. Part I: Overview, damage survey and radar analysis

Science.gov (United States)

Bech, Joan; Pineda, Nicolau; Rigo, Tomeu; Aran, Montserrat; Amaro, Jéssica; Gayà, Miquel; Arús, Joan; Montanyà, Joan; der Velde, Oscar van

2011-06-01

This study presents an analysis of a severe weather case that took place during the early morning of the 2nd of November 2008, when intense convective activity associated with a rapidly evolving low pressure system affected the southern coast of Catalonia (NE Spain). The synoptic framework was dominated by an upper level trough and an associated cold front extending from Gibraltar along the Mediterranean coast of the Iberian Peninsula to SE France, which moved north-eastward. South easterly winds in the north of the Balearic Islands and the coast of Catalonia favoured high values of 0-3 km storm relative helicity which combined with moderate MLCAPE values and high shear favoured the conditions for organized convection. A number of multicell storms and others exhibiting supercell features, as indicated by Doppler radar observations, clustered later in a mesoscale convective system, and moved north-eastwards across Catalonia. They produced ground-level strong damaging wind gusts, an F2 tornado, hail and heavy rainfall. Total lightning activity (intra-cloud and cloud to ground flashes) was also relevant, exhibiting several classical features such as a sudden increased rate before ground level severe damage, as discussed in a companion study. Remarkable surface observations of this event include 24 h precipitation accumulations exceeding 100 mm in four different observatories and 30 minute rainfall amounts up to 40 mm which caused local flash floods. As the convective system evolved northward later that day it also affected SE France causing large hail, ground level damaging wind gusts and heavy rainfall.

Lightning activity, rainfall and flash flooding – occasional or interrelated events? A case study in the island of Crete

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A. G. Koutroulis

2012-04-01

Full Text Available The majority of cyclones passing over Crete in late autumn to early winter originate from southwest, west and northwest and are of varying size and intensity. A number of these cyclones cause flash floods. The present study reports the possible relationships between lighting activity and high precipitation related to flash flood events. In this study an attempt was made to correlate the lightning number and location, recorded by the ZEUS lightning detection system, with the rainfall characteristics for sixteen rain events (4 flood and 12 non-flood events on the island of Crete, during the period 2008–2009. Spatiotemporal analysis of rain and rain rate with flash count was performed with respect to distance (radius of flashes from raingauge location at various temporal scales, in order to examine the correlation of accumulated rainfall and lightning activity. The maximum attained statistical significant correlation was obtained within a circular area of an average radius of 15 km around the raingauge, and an average time lag of flash count prior precipitation accumulation of 15 min. The maximum correlation between the lightning and rainfall data is obtained for shorter time lags for the flood events (15 min than the non-flood events (25 min, that could reflect the faster propagation of flood triggering storms due to high convective activity. Results show increased lightning activity occurring during flood triggering storms, by an average of four times higher. Furthermore, there is evidence that the number of flashes that occur during a precipitation event is related to precipitation depth when the latter is adequate to produce a flood event. Differences between flood and non-flood producing storms need to be further assessed by analyzing more independent parameters, including the synoptic conditions and dominant flash flood hydrological generating processes.

Heavy Tail Behavior of Rainfall Extremes across Germany

Science.gov (United States)

Castellarin, A.; Kreibich, H.; Vorogushyn, S.; Merz, B.

2017-12-01

Distributions are termed heavy-tailed if extreme values are more likely than would be predicted by probability distributions that have exponential asymptotic behavior. Heavy-tail behavior often leads to surprise, because historical observations can be a poor guide for the future. Heavy-tail behavior seems to be widespread for hydro-meteorological extremes, such as extreme rainfall and flood events. To date there have been only vague hints to explain under which conditions these extremes show heavy-tail behavior. We use an observational data set consisting of 11 climate variables at 1440 stations across Germany. This homogenized, gap-free data set covers 110 years (1901-2010) at daily resolution. We estimate the upper tail behavior, including its uncertainty interval, of daily precipitation extremes for the 1,440 stations at the annual and seasonal time scales. Different tail indicators are tested, including the shape parameter of the Generalized Extreme Value distribution, the upper tail ratio and the obesity index. In a further step, we explore to which extent the tail behavior can be explained by geographical and climate factors. A large number of characteristics is derived, such as station elevation, degree of continentality, aridity, measures for quantifying the variability of humidity and wind velocity, or event-triggering large-scale atmospheric situation. The link between the upper tail behavior and these characteristics is investigated via data mining methods capable of detecting non-linear relationships in large data sets. This exceptionally rich observational data set, in terms of number of stations, length of time series and number of explaining variables, allows insights into the upper tail behavior which is rarely possible given the typical observational data sets available.

Simulation of heavy, long-term rainfall over low mountain ranges; Simulation von Starkniederschlaegen mit langer Andauer ueber Mittelgebirgen

Energy Technology Data Exchange (ETDEWEB)

Kunz, M.

2003-03-01

A diagnostic model for the estimation of orographic precipitation during large-scale upslide motions is presented. It is based on linear theory for 3-D mountain overflow. From the simulated vertical velocities rain intensities at the ground are calculated using a model for precipitation formation. Due to the small number of free parameters and because of the simple initialisation method, e.g. with single radiosonde data, the model is used for regionalisation of precipitation from rain gauge observations as well as for deriving its statistics under dynamical constraints. For Southwest Germany and Eastern France, with the low mountain ranges of the Vosges, Black Forest and Swabian Alb, model simulations are performed for individual events with heavy rainfall. Thereby it is evaluated, how realistic rainfall patterns can be obtained with a combination of model simulations and measurement data. Mean rainfall distributions are derived from simulations of all extreme events with 24-h totals over 60 mm at selected rain gauge stations between 1971 and 2000. Furthermore the calculation of rain sums for different return periods is performed using extreme value statistics. So it is possible to quantify the hazard potential of heavy rainfall, which may cause flooding or landslides, in high spatial resolution (2.5 x 2.5 km). (orig.)

Application of flood-intensity-duration curve, rainfall-intensity-duration curve and time of concentration to analyze the pattern of storms and their corresponding floods for the natural flood events

Science.gov (United States)

Kim, Nam Won; Shin, Mun-Ju; Lee, Jeong Eun

2016-04-01

The analysis of storm effects on floods is essential step for designing hydraulic structure and flood plain. There are previous studies for analyzing the relationship between the storm patterns and peak flow, flood volume and durations for various sizes of the catchments, but they are not enough to analyze the natural storm effects on flood responses quantitatively. This study suggests a novel method of quantitative analysis using unique factors extracted from the time series of storms and floods to investigate the relationship between natural storms and their corresponding flood responses. We used a distributed rainfall-runoff model of Grid based Rainfall-runoff Model (GRM) to generate the simulated flow and areal rainfall for 50 catchments in Republic of Korea size from 5.6 km2 to 1584.2 km2, which are including overlapped dependent catchments and non-overlapped independent catchments. The parameters of the GRM model were calibrated to get the good model performances of Nash-Sutcliffe efficiency. Then Flood-Intensity-Duration Curve (FIDC) and Rainfall-Intensity-Duration Curve (RIDC) were generated by Flood-Duration-Frequency and Intensity-Duration-Frequency methods respectively using the time series of hydrographs and hyetographs. Time of concentration developed for the Korea catchments was used as a consistent measure to extract the unique factors from the FIDC and RIDC over the different size of catchments. These unique factors for the storms and floods were analyzed against the different size of catchments to investigate the natural storm effects on floods. This method can be easily used to get the intuition of the natural storm effects with various patterns on flood responses. Acknowledgement This research was supported by a grant (11-TI-C06) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

TIME SERIES CHARACTERISTIC ANALYSIS OF RAINFALL, LAND USE AND FLOOD DISCHARGE BASED ON ARIMA BOX-JENKINS MODEL

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Abror Abror

2014-01-01

Full Text Available Indonesia located in tropic area consists of wet season and dry season. However, in last few years, in river discharge in dry season is very little, but in contrary, in wet season, frequency of flood increases with sharp peak and increasingly great water elevation. The increased flood discharge may occur due to change in land use or change in rainfall characteristic. Both matters should get clarity. Therefore, a research should be done to analyze rainfall characteristic, land use and flood discharge in some watershed area (DAS quantitatively from time series data. The research was conducted in DAS Gintung in Parakankidang, DAS Gung in Danawarih, DAS Rambut in Cipero, DAS Kemiri in Sidapurna and DAS Comal in Nambo, located in Tegal Regency and Pemalang Regency in Central Java Province. This research activity consisted of three main steps: input, DAS system and output. Input is DAS determination and selection and searching secondary data. DAS system is early secondary data processing consisting of rainfall analysis, HSS GAMA I parameter, land type analysis and DAS land use. Output is final processing step that consisting of calculation of Tadashi Tanimoto, USSCS effective rainfall, flood discharge, ARIMA analysis, result analysis and conclusion. Analytical calculation of ARIMA Box-Jenkins time series used software Number Cruncher Statistical Systems and Power Analysis Sample Size (NCSS-PASS version 2000, which result in time series characteristic in form of time series pattern, mean square errors (MSE, root mean square ( RMS, autocorrelation of residual and trend. Result of this research indicates that composite CN and flood discharge is proportional that means when composite CN trend increase then flood discharge trend also increase and vice versa. Meanwhile, decrease of rainfall trend is not always followed with decrease in flood discharge trend. The main cause of flood discharge characteristic is DAS management characteristic, not change in

Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

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T. Matingo

2018-05-01

Full Text Available Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013–2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System daily model calibration Nash Sutcliffe efficiency (NSE for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015–2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized

Cyber Surveillance for Flood Disasters

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Shi-Wei Lo

2015-01-01

Full Text Available Regional heavy rainfall is usually caused by the influence of extreme weather conditions. Instant heavy rainfall often results in the flooding of rivers and the neighboring low-lying areas, which is responsible for a large number of casualties and considerable property loss. The existing precipitation forecast systems mostly focus on the analysis and forecast of large-scale areas but do not provide precise instant automatic monitoring and alert feedback for individual river areas and sections. Therefore, in this paper, we propose an easy method to automatically monitor the flood object of a specific area, based on the currently widely used remote cyber surveillance systems and image processing methods, in order to obtain instant flooding and waterlogging event feedback. The intrusion detection mode of these surveillance systems is used in this study, wherein a flood is considered a possible invasion object. Through the detection and verification of flood objects, automatic flood risk-level monitoring of specific individual river segments, as well as the automatic urban inundation detection, has become possible. The proposed method can better meet the practical needs of disaster prevention than the method of large-area forecasting. It also has several other advantages, such as flexibility in location selection, no requirement of a standard water-level ruler, and a relatively large field of view, when compared with the traditional water-level measurements using video screens. The results can offer prompt reference for appropriate disaster warning actions in small areas, making them more accurate and effective.

Duration-frequency relationships of heavy rainfall in Santa Catarina, Brazil

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Álvaro José Back

2012-06-01

Full Text Available The purpose of this study was to adjust equations that establish relationships between rainfall events with different duration and data from weather stations in the state of Santa Catarina, Brazil. In this study, the relationships between different duration heavy rainfalls from 13 weather stations of Santa Catarina were analyzed. From series of maximum annual rainfalls, and using the Gumbel-Chow distribution, the maximum rainfall for durations between 5 min and 24 h were estimated considering return periods from 2 to 100 years. The data fit to the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test at 5 % significance. The coefficients of Bell's equation were adjusted to estimate the relationship between rainfall duration t (min and the return period T (y in relation to the maximum rainfall with a duration of 1 hour and a 10 year return period. Likewise, the coefficients of Bell's equation were adjusted based on the maximum rainfall with a duration of 1 day and a 10 year return period. The results showed that these relationships are viable to estimate short-duration rainfall events at locations where there are no rainfall records.

Association of Heavy Rainfall on Genotypic Diversity in V. cholerae Isolates from an Outbreak in India

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A. K. Goel

2011-01-01

Full Text Available The outbreak of waterborne disease cholera has been associated with rainfall and flooding events by contamination of potable water with environmental Vibrio cholerae. The continuation of the epidemic in a region, however, is often due to secondary transmission of the initial outbreak strain through human waste. This paper reports, on the contrary, a rapid shift of genotype from one V. cholerae strain to another one in an epidemic region. V. cholerae isolated from patients during 2005 cholera epidemic in Chennai, India were characterized using PCR identification of toxin genes, antibiogram, and genomic fingerprinting analysis. The results showed that in spite of the similarity of toxin genes and antibiogram, the Vibrio isolates grouped into two different clusters based on the ERIC-PCR fingerprinting. Each cluster corresponded to a distinct peak of cholera outbreak, which occurred after separate heavy rainfall. The results suggest that the rainfall event can bring various genotypes of V. cholerae strains causing multiple outbreaks.

A coupled weather generator - rainfall-runoff approach on hourly time steps for flood risk analysis

Science.gov (United States)

Winter, Benjamin; Schneeberger, Klaus; Dung Nguyen, Viet; Vorogushyn, Sergiy; Huttenlau, Matthias; Merz, Bruno; Stötter, Johann

2017-04-01

The evaluation of potential monetary damage of flooding is an essential part of flood risk management. One possibility to estimate the monetary risk is to analyze long time series of observed flood events and their corresponding damages. In reality, however, only few flood events are documented. This limitation can be overcome by the generation of a set of synthetic, physically and spatial plausible flood events and subsequently the estimation of the resulting monetary damages. In the present work, a set of synthetic flood events is generated by a continuous rainfall-runoff simulation in combination with a coupled weather generator and temporal disaggregation procedure for the study area of Vorarlberg (Austria). Most flood risk studies focus on daily time steps, however, the mesoscale alpine study area is characterized by short concentration times, leading to large differences between daily mean and daily maximum discharge. Accordingly, an hourly time step is needed for the simulations. The hourly metrological input for the rainfall-runoff model is generated in a two-step approach. A synthetic daily dataset is generated by a multivariate and multisite weather generator and subsequently disaggregated to hourly time steps with a k-Nearest-Neighbor model. Following the event generation procedure, the negative consequences of flooding are analyzed. The corresponding flood damage for each synthetic event is estimated by combining the synthetic discharge at representative points of the river network with a loss probability relation for each community in the study area. The loss probability relation is based on exposure and susceptibility analyses on a single object basis (residential buildings) for certain return periods. For these impact analyses official inundation maps of the study area are used. Finally, by analyzing the total event time series of damages, the expected annual damage or losses associated with a certain probability of occurrence can be estimated for

Flood deposits and their heavy metal load - example of the Neckar river

International Nuclear Information System (INIS)

Hellmann, H.

1993-01-01

Flood deposits may develop from suspended solids under certain conditions, e.g. after the passage of a flood wave. Depending on the origin of the suspended material, the heavy metal load in these deposits varies considerably. Recent sediments deposited in the Neckar waterway after the flood of February/March 1990 are taken as an example to explain that it is necessary to consider the contamination load in relation to the grain size of the material. To this end, the heavy metal contents of the fine grain fraction (grain diameter [de

A flash flood early warning system based on rainfall thresholds and daily soil moisture indexes

Science.gov (United States)

Brigandì, Giuseppina; Tito Aronica, Giuseppe

2015-04-01

Main focus of the paper is to present a flash flood early warning system, developed for Civil Protection Agency for the Sicily Region, for alerting extreme hydrometeorological events by using a methodology based on the combined use of rainfall thresholds and soil moisture indexes. As matter of fact, flash flood warning is a key element to improve the Civil Protection achievements to mitigate damages and safeguard the security of people. It is a rather complicated task, particularly in those catchments with flashy response where even brief anticipations are important and welcomed. In this context, some kind of hydrological precursors can be considered to improve the effectiveness of the emergency actions (i.e. early flood warning). Now, it is well known how soil moisture is an important factor in flood formation, because the runoff generation is strongly influenced by the antecedent soil moisture conditions of the catchment. The basic idea of the work here presented is to use soil moisture indexes derived in a continuous form to define a first alert phase in a flash flood forecasting chain and then define a unique rainfall threshold for a given day for the subsequent alarm phases activation, derived as a function of the soil moisture conditions at the beginning of the day. Daily soil moisture indexes, representative of the moisture condition of the catchment, were derived by using a parsimonious and simply to use approach based on the IHACRES model application in a modified form developed by the authors. It is a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method and on the unit hydrograph approach that requires only rainfall, streamflow and air temperature data. It consists of two modules. In the first a non linear loss model, based on the SCS-CN method, was used to transform total rainfall into effective rainfall. In the second, a linear convolution of effective rainfall was performed using a total unit hydrograph with a configuration of

Relations Between Rainfall and Postfire Debris-Flow and Flood Magnitudes for Emergency-Response Planning, San Gabriel Mountains, Southern California

Science.gov (United States)

Cannon, Susan H.; Boldt, Eric M.; Kean, Jason W.; Laber, Jayme; Staley, Dennis M.

2010-01-01

Following wildfires, emergency-response and public-safety agencies are faced often with making evacuation decisions and deploying resources both well in advance of each coming winter storm and during storms themselves. Information critical to this process is provided for recently burned areas in the San Gabriel Mountains of southern California. The National Weather Service (NWS) issues Quantitative Precipitation Forecasts (QPFs) for the San Gabriel Mountains twice a day, at approximately 4 a.m. and 4 p.m., along with unscheduled updates when conditions change. QPFs provide estimates of rainfall totals in 3-hour increments for the first 12-hour period and in 6-hour increments for the second 12-hour period. Estimates of one-hour rainfall intensities can be provided in the forecast narrative, along with probable peak intensities and timing, although with less confidence than rainfall totals. A compilation of information on the hydrologic response to winter storms from recently burned areas in southern California steeplands was used to develop a system for classifying the magnitude of the postfire hydrologic response. The four-class system is based on a combination of the reported volume of individual debris flows, the consequences of these events in an urban setting, and the spatial extent of the response to the triggering storm. Threshold rainfall conditions associated with debris flow and floods of different magnitude classes are defined by integrating local rainfall data with debris-flow and flood magnitude information. The within-storm rainfall accumulations (A) and durations (D) above which magnitude I events are expected are defined by A=0.3D0.6. The function A=0.5D0.6 defines the within-storm rainfall accumulations and durations above which a magnitude III event will occur in response to a regional-scale storm, and a magnitude II event will occur if the storm affects only a few drainage basins. The function A=1.0D0.5defines the rainfall conditions above which

Improving the accuracy of flood forecasting with transpositions of ensemble NWP rainfall fields considering orographic effects

Science.gov (United States)

Yu, Wansik; Nakakita, Eiichi; Kim, Sunmin; Yamaguchi, Kosei

2016-08-01

The use of meteorological ensembles to produce sets of hydrological predictions increased the capability to issue flood warnings. However, space scale of the hydrological domain is still much finer than meteorological model, and NWP models have challenges with displacement. The main objective of this study to enhance the transposition method proposed in Yu et al. (2014) and to suggest the post-processing ensemble flood forecasting method for the real-time updating and the accuracy improvement of flood forecasts that considers the separation of the orographic rainfall and the correction of misplaced rain distributions using additional ensemble information through the transposition of rain distributions. In the first step of the proposed method, ensemble forecast rainfalls from a numerical weather prediction (NWP) model are separated into orographic and non-orographic rainfall fields using atmospheric variables and the extraction of topographic effect. Then the non-orographic rainfall fields are examined by the transposition scheme to produce additional ensemble information and new ensemble NWP rainfall fields are calculated by recombining the transposition results of non-orographic rain fields with separated orographic rainfall fields for a generation of place-corrected ensemble information. Then, the additional ensemble information is applied into a hydrologic model for post-flood forecasting with a 6-h interval. The newly proposed method has a clear advantage to improve the accuracy of mean value of ensemble flood forecasting. Our study is carried out and verified using the largest flood event by typhoon 'Talas' of 2011 over the two catchments, which are Futatsuno (356.1 km2) and Nanairo (182.1 km2) dam catchments of Shingu river basin (2360 km2), which is located in the Kii peninsula, Japan.

Estimation of the Relative Severity of Floods in Small Ungauged Catchments for Preliminary Observations on Flash Flood Preparedness: A Case Study in Korea

Science.gov (United States)

Kim, Eung Seok; Choi, Hyun Il

2012-01-01

An increase in the occurrence of sudden local flooding of great volume and short duration has caused significant danger and loss of life and property in Korea as well as many other parts of the World. Since such floods usually accompanied by rapid runoff and debris flow rise quite quickly with little or no advance warning to prevent flood damage, this study presents a new flash flood indexing methodology to promptly provide preliminary observations regarding emergency preparedness and response to flash flood disasters in small ungauged catchments. Flood runoff hydrographs are generated from a rainfall-runoff model for the annual maximum rainfall series of long-term observed data in the two selected small ungauged catchments. The relative flood severity factors quantifying characteristics of flood runoff hydrographs are standardized by the highest recorded maximum value, and then averaged to obtain the flash flood index only for flash flood events in each study catchment. It is expected that the regression equations between the proposed flash flood index and rainfall characteristics can provide the basis database of the preliminary information for forecasting the local flood severity in order to facilitate flash flood preparedness in small ungauged catchments. PMID:22690208

An Investigation on the Sensitivity of the Parameters of Urban Flood Model

Science.gov (United States)

M, A. B.; Lohani, B.; Jain, A.

2015-12-01

Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a

Urbanism, climate change and floods: Case of Tlemcen city

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Hayat Adjim

2018-03-01

Full Text Available After a drought during the 1990s, Tlemcen has experienced heavy rainfall in recent years which caused several floods. They have become frequent and usually cause large damage. We then asked ourselves questions about the reasons for this deregulation of rainfall and floods. We have assumed that climate change has led to deregulation of precipitation and that the urbanization and morphology of the site are the causes of the floods. For this, we analyzed the rainfall data and study the configuration of the town of Tlemcen. We noticed then that Tlemcen town undergoes the climate changes effects per a diminution of the multi-annual mean of rainfall between 1974 and 2008, and a slight displacement of the rainfall from April to November after 2008. Finally, the principal reason of floods is the thoughtless urban sprawl on the water courses also favored by an unfavourable topography.

Rainfall spatiotemporal variability relation to wetlands hydroperiods

Science.gov (United States)

Serrano-Hidalgo, Carmen; Guardiola-Albert, Carolina; Fernandez-Naranjo, Nuria

2017-04-01

Doñana natural space (Southwestern Spain) is one of the largest protected wetlands in Europe. The wide marshes present in this natural space have such ecological value that this wetland has been declared a Ramsar reserve in 1982. Apart from the extensive marsh, there are also small lagoons and seasonally flooded areas which are likewise essential to maintain a wide variety of valuable habitats. Hydroperiod, the length of time each point remains flooded along an annual cycle, is a critical ecological parameter that shapes aquatic plants and animals distribution and determines available habitat for many of the living organisms in the marshes. Recently, there have been published two different works estimating the hydroperiod of Doñana lagoons with Landsat Time Series images (Cifuentes et al., 2015; Díaz-Delgado et al., 2016). In both works the flooding cycle hydroperiod in Doñana marshes reveals a flooding regime mainly driven by rainfall, evapotranspiration, topography and local hydrological management actions. The correlation found between rainfall and hydroperiod is studied differently in both works. While in one the rainfall is taken from one raingauge (Cifuentes et al., 2015), the one performed by Díaz-Delgado (2016) uses annual rainfall maps interpolated with the inverse of the distance method. The rainfall spatiotemporal variability in this area can be highly significant; however the amount of this importance has not been quantified at the moment. In the present work the geostatistical tool known as spatiotemporal variogram is used to study the rainfall spatiotemporal variability. The spacetime package implemented in R (Pebesma, 2012) facilities its computation from a high rainfall data base of more than 100 raingauges from 1950 to 2016. With the aid of these variograms the rainfall spatiotemporal variability is quantified. The principal aim of the present work is the study of the relation between the rainfall spatiotemporal variability and the

Geotechnical hazards from large earthquakes and heavy rainfalls

CERN Document Server

Kazama, Motoki; Lee, Wei

2017-01-01

This book is a collection of papers presented at the International Workshop on Geotechnical Natural Hazards held July 12–15, 2014, in Kitakyushu, Japan. The workshop was the sixth in the series of Japan–Taiwan Joint Workshops on Geotechnical Hazards from Large Earthquakes and Heavy Rainfalls, held under the auspices of the Asian Technical Committee No. 3 on Geotechnology for Natural Hazards of the International Society for Soil Mechanics and Geotechnical Engineering. It was co-organized by the Japanese Geotechnical Society and the Taiwanese Geotechnical Society. The contents of this book focus on geotechnical and natural hazard-related issues in Asia such as earthquakes, tsunami, rainfall-induced debris flows, slope failures, and landslides. The book contains the latest information and mitigation technology on earthquake- and rainfall-induced geotechnical natural hazards. By dissemination of the latest state-of-the-art research in the area, the information contained in this book will help researchers, des...

Derivation of flood frequency curves in poorly gauged Mediterranean catchments using a simple stochastic hydrological rainfall-runoff model

Science.gov (United States)

Aronica, G. T.; Candela, A.

2007-12-01

SummaryIn this paper a Monte Carlo procedure for deriving frequency distributions of peak flows using a semi-distributed stochastic rainfall-runoff model is presented. The rainfall-runoff model here used is very simple one, with a limited number of parameters and practically does not require any calibration, resulting in a robust tool for those catchments which are partially or poorly gauged. The procedure is based on three modules: a stochastic rainfall generator module, a hydrologic loss module and a flood routing module. In the rainfall generator module the rainfall storm, i.e. the maximum rainfall depth for a fixed duration, is assumed to follow the two components extreme value (TCEV) distribution whose parameters have been estimated at regional scale for Sicily. The catchment response has been modelled by using the Soil Conservation Service-Curve Number (SCS-CN) method, in a semi-distributed form, for the transformation of total rainfall to effective rainfall and simple form of IUH for the flood routing. Here, SCS-CN method is implemented in probabilistic form with respect to prior-to-storm conditions, allowing to relax the classical iso-frequency assumption between rainfall and peak flow. The procedure is tested on six practical case studies where synthetic FFC (flood frequency curve) were obtained starting from model variables distributions by simulating 5000 flood events combining 5000 values of total rainfall depth for the storm duration and AMC (antecedent moisture conditions) conditions. The application of this procedure showed how Monte Carlo simulation technique can reproduce the observed flood frequency curves with reasonable accuracy over a wide range of return periods using a simple and parsimonious approach, limited data input and without any calibration of the rainfall-runoff model.

2002 floods by Typhoon Rusa: experience and perspectives of mitigation in South Korea

International Nuclear Information System (INIS)

Kim Hyunjun; Hong Ilpyo; Kim-Hyunjun; Hong-llpyo

2004-01-01

There are five river flood control offices, which control the five. Since 1990s the Korean Peninsula faces frequent heavy rainfalls and typhoons with severe amage. A historical maximum, 2 nd and 3 rd damage by the floods were happened after 1,990. In 2002 August, a heavy storm and typhoon R usa c aused tremendous damage more than 5 billion USD. Typhoon 'Rusa', which struck the Korean peninsula on August 31st, 2002, brought 870.8 mm of rain in Kangnung area, setting the highest daily rainfall record in Korea's historical rainfall observations. Its devastating power exerted itself throughout the country as it continued to set the regional daily rainfall records in Daekwanryung, Donghae, Chupungryung, Sangju, Jangsu, Sunchun, and Hapchun areas. During the 22 hours, it caused the property damage of more than 5 billion USD, the highest amount of damage ever caused by a single disaster in this century, and it also claimed 246 precious lives. Because of the concentration of population and properties due to urbanization and industrialization, the impact and damage of disasters are getting more severe, and recent heavy rainfalls have been worsening the situation. Especially in the case of Rusa, the heavy rainfalls far exceeding the designed frequency caused the disruption of communications and transport systems that are essential to the emergency disaster response, and thus in turn brought about the heavy death toll. This kind of severe flood damage is expected to occur again in the future as El Nino and global warming continue to progress. This paper looks into the causes of damages Typhoon Rusa brought about in the Korean peninsula during the period of August 30 - September 1, 2002, and suggests flood mitigation measures based on the experience and prospect.(Author)

Extreme Rainfall In A City

Science.gov (United States)

Nkemdirim, Lawrence

Cities contain many structures and activities that are vulnerable to severe weather. Heavy precipitation cause floods which can damage structures, compromise transportation and water supply systems, and slow down economic and social activities. Rain induced flood patterns in cities must be well understood to enable effective placement of flood control and other regulatory measures. The planning goal is not to eliminate all floods but to reduce their frequency and resulting damage. Possible approaches to such planning include probability based extreme event analysis. Precipitation is normally the most variable hydrologic element over a given area. This variability results from the distribution of clouds and in cloud processes in the atmosphere, the storm path, and the distribution of topographical features on the ground along path. Some studies suggest that point rainfall patterns are also affected by urban industrial effects hence some agreement that cities are wetter than the country surrounding them. However, there are still questions regarding the intra- urban distribution of precipitation. The sealed surfaces, urban structures, and the urban heat anomaly increase convection in cities which may enhance the generation of clouds. Increased dust and gaseous aerosols loads are effective condensation and sublimation nuclei which may also enhance the generation of precipitation. Based on these associations, the greatest amount of convection type rainfall should occur at city center. A study of summer rainfall in Calgary showed that frequencies of trace amounts of rainfall and events under 0.2mm are highest downtown than elsewhere. For amounts greater than than 0.2 mm, downtown sites were not favored. The most compelling evidence for urban-industrial precipitation enhancement came from the Metromex project around St. Loius, Missouri where maximum increases of between 5 to 30 per cent in summer rainfall downwind of the city was linked to urbanization and

Coupling Radar Rainfall Estimation and Hydrological Modelling For Flash-flood Hazard Mitigation

Science.gov (United States)

Borga, M.; Creutin, J. D.

issues are examined: advantages and caveats of using radar rainfall estimates in operational flash flood forecasting, methodological problems as- sociated to the use of hydrological models for distributed flash flood forecasting with rainfall input estimated from radar.

Return period assessment of urban pluvial floods through modelling of rainfall–flood response

DEFF Research Database (Denmark)

Tuyls, Damian Murla; Thorndahl, Søren Liedtke; Rasmussen, Michael Robdrup

2018-01-01

Intense rainfall in urban areas can often generate severe flood impacts. Consequently, it is crucial to design systems to minimize potential flood damages. Traditional, simple design of urban drainage systems assumes agreement between rainfall return period and its consequent flood return period......; however, this does not always apply. Hydraulic infrastructures found in urban drainage systems can increase system heterogeneity and perturb the impact of severe rainfall response. In this study, a surface flood return period assessment was carried out at Lystrup (Denmark), which has received the impact...... of flooding in recent years. A 35 years' rainfall dataset together with a coupled 1D/2D surface and network model was used to analyse and assess flood return period response. Results show an ambiguous relation between rainfall and flood return periods indicating that linear rainfall–runoff relationships will...

Assessment of factors contributing to flood disaster in Ibadan ...

African Journals Online (AJOL)

Climate change has brought with it some forms of extreme weather events. One of such is heavy rainfall which often leads to flood. In recent times, flood disaster has been a regular occurrence destroying lives and property. This study was carried out to identify and assess contributing factors to flood disaster in Ibadan ...

Assessing the Impacts of Flooding Caused by Extreme Rainfall Events Through a Combined Geospatial and Numerical Modeling Approach

Science.gov (United States)

Santillan, J. R.; Amora, A. M.; Makinano-Santillan, M.; Marqueso, J. T.; Cutamora, L. C.; Serviano, J. L.; Makinano, R. M.

2016-06-01

In this paper, we present a combined geospatial and two dimensional (2D) flood modeling approach to assess the impacts of flooding due to extreme rainfall events. We developed and implemented this approach to the Tago River Basin in the province of Surigao del Sur in Mindanao, Philippines, an area which suffered great damage due to flooding caused by Tropical Storms Lingling and Jangmi in the year 2014. The geospatial component of the approach involves extraction of several layers of information such as detailed topography/terrain, man-made features (buildings, roads, bridges) from 1-m spatial resolution LiDAR Digital Surface and Terrain Models (DTM/DSMs), and recent land-cover from Landsat 7 ETM+ and Landsat 8 OLI images. We then used these layers as inputs in developing a Hydrologic Engineering Center Hydrologic Modeling System (HEC HMS)-based hydrologic model, and a hydraulic model based on the 2D module of the latest version of HEC River Analysis System (RAS) to dynamically simulate and map the depth and extent of flooding due to extreme rainfall events. The extreme rainfall events used in the simulation represent 6 hypothetical rainfall events with return periods of 2, 5, 10, 25, 50, and 100 years. For each event, maximum flood depth maps were generated from the simulations, and these maps were further transformed into hazard maps by categorizing the flood depth into low, medium and high hazard levels. Using both the flood hazard maps and the layers of information extracted from remotely-sensed datasets in spatial overlay analysis, we were then able to estimate and assess the impacts of these flooding events to buildings, roads, bridges and landcover. Results of the assessments revealed increase in number of buildings, roads and bridges; and increase in areas of land-cover exposed to various flood hazards as rainfall events become more extreme. The wealth of information generated from the flood impact assessment using the approach can be very useful to the

A Probabilistic Analysis of Surface Water Flood Risk in London.

Science.gov (United States)

Jenkins, Katie; Hall, Jim; Glenis, Vassilis; Kilsby, Chris

2017-10-30

Flooding in urban areas during heavy rainfall, often characterized by short duration and high-intensity events, is known as "surface water flooding." Analyzing surface water flood risk is complex as it requires understanding of biophysical and human factors, such as the localized scale and nature of heavy precipitation events, characteristics of the urban area affected (including detailed topography and drainage networks), and the spatial distribution of economic and social vulnerability. Climate change is recognized as having the potential to enhance the intensity and frequency of heavy rainfall events. This study develops a methodology to link high spatial resolution probabilistic projections of hourly precipitation with detailed surface water flood depth maps and characterization of urban vulnerability to estimate surface water flood risk. It incorporates probabilistic information on the range of uncertainties in future precipitation in a changing climate. The method is applied to a case study of Greater London and highlights that both the frequency and spatial extent of surface water flood events are set to increase under future climate change. The expected annual damage from surface water flooding is estimated to be to be £171 million, £343 million, and £390 million/year under the baseline, 2030 high, and 2050 high climate change scenarios, respectively. © 2017 Society for Risk Analysis.

Heavy rainfall: An underestimated environmental risk for buildings?

Directory of Open Access Journals (Sweden)

Golz Sebastian

2016-01-01

Second, heavy rain may result in urban pluvial flooding due to sewer overflow that cause severe damage to buildings. A comprehensive study of the impacts and the consequences in Dresden (Germany, presented in the paper, revealed that the potential risks of flooding from sewers due to hydraulic overload can be estimated on building scale using the model approach IVART (Integrated Spatial Vulnerability and Risk Assessment Tool. Modelling results provide the basis to quantify the effectiveness and efficiency of flood resilience technologies.

Modelling and assessment of urban flood hazards based on rainfall intensity-duration-frequency curves reformation

OpenAIRE

Ghazavi, Reza; Moafi Rabori, Ali; Ahadnejad Reveshty, Mohsen

2016-01-01

Estimate design storm based on rainfall intensity–duration–frequency (IDF) curves is an important parameter for hydrologic planning of urban areas. The main aim of this study was to estimate rainfall intensities of Zanjan city watershed based on overall relationship of rainfall IDF curves and appropriate model of hourly rainfall estimation (Sherman method, Ghahreman and Abkhezr method). Hydrologic and hydraulic impacts of rainfall IDF curves change in flood properties was evaluated via Stormw...

Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range flood prediction in Australia

Science.gov (United States)

White, C. J.; Franks, S. W.; McEvoy, D.

2015-06-01

Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal). Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S) forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR) activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

Relations between Rainfall and Postfire Debris-Flow- and Flood-Event Magnitudes for Emergency-Response Planning, San Gabriel Mountains, Southern California, USA

Science.gov (United States)

Cannon, Susan; Collins, Larry; Boldt, Eric; Staley, Dennis

2010-05-01

Following wildfires, emergency-response and public-safety agencies are often faced with making evacuation decisions and deploying resources both well in advance of each coming winter storm and during storm events themselves. We here provide information critical to this process for recently burned areas in the San Gabriel Mountains of southern California. The National Weather Service (NWS) issues Quantitative Precipitation Forecasts (QPFs) for the San Gabriel Mountains twice a day, at approximately 4 am and 4 pm, along with unscheduled updates when conditions change. QPFs provide estimates of rainfall totals in 3-hour increments for the first 12-hour period and in 6-hour increments for the second. Estimates of one-hour rainfall intensities can be provided in the forecast narrative, along with probable peak intensities and timing, although with less confidence than rainfall totals. A compilation of information on the hydrologic response to winter storm events from recently burned areas in southern California was used to develop a system for classifying the magnitude of postfire hydrologic events. The three-class system is based on differences between the reported volume of individual debris flows, the consequences of these events in an urban setting, and the spatial extent of the response to the triggering storm. Threshold rainfall conditions that may lead to debris flow and floods of different magnitude classes are defined by integrating local rainfall data with debris-flow- and flood-event magnitude information. The within-storm rainfall accumulations (A) and durations (D) below which Magnitude I events are expected, and above which Magnitude II events may occur, are defined by A=0.4D0.55. The function A=0.6D0.50 defines the within-storm rainfall accumulations and durations above which a Magnitude III event will occur in response to a regional-scale storm, and a Magnitude II event will occur if the storm affects only a few drainage basins. The function A=1.1D0

Partial Least Squares Regression for Determining the Control Factors for Runoff and Suspended Sediment Yield during Rainfall Events

Directory of Open Access Journals (Sweden)

Nufang Fang

2015-07-01

Full Text Available Multivariate statistics are commonly used to identify the factors that control the dynamics of runoff or sediment yields during hydrological processes. However, one issue with the use of conventional statistical methods to address relationships between variables and runoff or sediment yield is multicollinearity. The main objectives of this study were to apply a method for effectively identifying runoff and sediment control factors during hydrological processes and apply that method to a case study. The method combines the clustering approach and partial least squares regression (PLSR models. The case study was conducted in a mountainous watershed in the Three Gorges Area. A total of 29 flood events in three hydrological years in areas with different land uses were obtained. In total, fourteen related variables were separated from hydrographs using the classical hydrograph separation method. Twenty-nine rainfall events were classified into two rainfall regimes (heavy Rainfall Regime I and moderate Rainfall Regime II based on rainfall characteristics and K-means clustering. Four separate PLSR models were constructed to identify the main variables that control runoff and sediment yield for the two rainfall regimes. For Rainfall Regime I, the dominant first-order factors affecting the changes in sediment yield in our study were all of the four rainfall-related variables, flood peak discharge, maximum flood suspended sediment concentration, runoff, and the percentages of forest and farmland. For Rainfall Regime II, antecedent condition-related variables have more effects on both runoff and sediment yield than in Rainfall Regime I. The results suggest that the different control factors of the two rainfall regimes are determined by the rainfall characteristics and thus different runoff mechanisms.

Internationally coordinated multi-mission planning is now critical to sustain the space-based rainfall observations needed for managing floods globally

International Nuclear Information System (INIS)

Reed, Patrick M; Herman, Jonathan D; Chaney, Nathaniel W; Wood, Eric F; Ferringer, Matthew P

2015-01-01

At present 4 of 10 dedicated rainfall observing satellite systems have exceeded their design life, some by more than a decade. Here, we show operational implications for flood management of a ‘collapse’ of space-based rainfall observing infrastructure as well as the high-value opportunities for a globally coordinated portfolio of satellite missions and data services. Results show that the current portfolio of rainfall missions fails to meet operational data needs for flood management, even when assuming a perfectly coordinated data product from all current rainfall-focused missions (i.e., the full portfolio). In the full portfolio, satellite-based rainfall data deficits vary across the globe and may preclude climate adaptation in locations vulnerable to increasing flood risks. Moreover, removing satellites that are currently beyond their design life (i.e., the reduced portfolio) dramatically increases data deficits globally and could cause entire high intensity flood events to be unobserved. Recovery from the reduced portfolio is possible with internationally coordinated replenishment of as few as 2 of the 4 satellite systems beyond their design life, yielding rainfall data coverages that outperform the current full portfolio (i.e., an optimized portfolio of eight satellites can outperform ten satellites). This work demonstrates the potential for internationally coordinated satellite replenishment and data services to substantially enhance the cost-effectiveness, sustainability and operational value of space-based rainfall observations in managing evolving flood risks. (letter)

Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

Science.gov (United States)

Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

2016-05-01

Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

Application of Indigenous Knowledge to Flood Prevention and ...

African Journals Online (AJOL)

In the last three decades, flooding has become a nightmare associated with rainfall in all the continents of the world, as it records heavy casualties everywhere and each time it occurred. Flooding is now a big and seemingly unstoppable environmental threat to rural and urban settlements, in both developed and developing ...

A Decadal Historical Satellite Data and Rainfall Trend Analysis (2001–2016 for Flood Hazard Mapping in Sri Lanka

Directory of Open Access Journals (Sweden)

Niranga Alahacoon

2018-03-01

Full Text Available Critical information on a flood-affected area is needed in a short time frame to initiate rapid response operations and develop long-term flood management strategies. This study combined rainfall trend analysis using Asian Precipitation—Highly Resolved Observational Data Integration towards Evaluation of Water Resources (APHRODITE gridded rainfall data with flood maps derived from Synthetic Aperture Radar (SAR and multispectral satellite to arrive at holistic spatio-temporal patterns of floods in Sri Lanka. Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR data were used to map flood extents for emergency relief operations while eight-day Moderate Resolution Imaging Spectroradiometer (MODIS surface reflectance data for the time period from 2001 to 2016 were used to map long term flood-affected areas. The inundation maps produced for rapid response were published within three hours upon the availability of satellite imagery in web platforms, with the aim of supporting a wide range of stakeholders in emergency response and flood relief operations. The aggregated time series of flood extents mapped using MODIS data were used to develop a flood occurrence map (2001–2016 for Sri Lanka. Flood hotpots identified using both optical and synthetic aperture average of 325 km2 for the years 2006–2015 and exceptional flooding in 2016 with inundation extent of approximately 1400 km2. The time series rainfall data explains increasing trend in the extreme rainfall indices with similar observation derived from satellite imagery. The results demonstrate the feasibility of using multi-sensor flood mapping approaches, which will aid Disaster Management Center (DMC and other multi-lateral agencies involved in managing rapid response operations and preparing mitigation measures.

Evaluation of critical storm duration rainfall estimates used in flood ...

African Journals Online (AJOL)

The results showed that the RMLA&SI approach can be considered as the preferred DDF relationship in future design flood estimations. The results also showed that a direct relationship exists between the catchment area and TC, thus ARFs can be explicitly expressed in terms of only the catchment area. Keywords: Rainfall ...

Using subseasonal-to-seasonal (S2S extreme rainfall forecasts for extended-range flood prediction in Australia

Directory of Open Access Journals (Sweden)

C. J. White

2015-06-01

Full Text Available Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high-impact extreme rainfall and flooding events on a range of prediction timescales (e.g. sub-daily, daily, multi-week, seasonal. Making improvements to extended-range rainfall and flood forecast models, assessing forecast skill and uncertainty, and exploring how to apply flood forecasts and communicate their benefits to decision-makers are significant challenges facing the forecasting and water resources management communities. This paper presents some of the latest science and initiatives from Australia on the development, application and communication of extreme rainfall and flood forecasts on the extended-range "subseasonal-to-seasonal" (S2S forecasting timescale, with a focus on risk-based decision-making, increasing flood risk awareness and preparedness, capturing uncertainty, understanding human responses to flood forecasts and warnings, and the growing adoption of "climate services". The paper also demonstrates how forecasts of flood events across a range of prediction timescales could be beneficial to a range of sectors and society, most notably for disaster risk reduction (DRR activities, emergency management and response, and strengthening community resilience. Extended-range S2S extreme flood forecasts, if presented as easily accessible, timely and relevant information are a valuable resource to help society better prepare for, and subsequently cope with, extreme flood events.

Influences of Appalachian orography on heavy rainfall and rainfall variability associated with the passage of hurricane Isabel by ensemble simulations

Science.gov (United States)

Oldaker, Guy; Liu, Liping; Lin, Yuh-Lang

2017-12-01

This study focuses on the heavy rainfall event associated with hurricane Isabel's (2003) passage over the Appalachian mountains of the eastern United States. Specifically, an ensemble consisting of two groups of simulations using the Weather Research and Forecasting model (WRF), with and without topography, is performed to investigate the orographic influences on heavy rainfall and rainfall variability. In general, the simulated ensemble mean with full terrain is able to reproduce the key observed 24-h rainfall amount and distribution, while the flat-terrain mean lacks in this respect. In fact, 30-h rainfall amounts are reduced by 75% with the removal of topography. Rainfall variability is also significantly increased with the presence of orography. Further analysis shows that the complex interaction between the hurricane and terrain along with contributions from varied microphysics, cumulus parametrization, and planetary boundary layer schemes have a pronounced effect on rainfall and rainfall variability. This study follows closely with a previous study, but for a different TC case of Isabel (2003). It is an important sensitivity test for a different TC in a very different environment. This study reveals that the rainfall variability behaves similarly, even with different settings of the environment.

Estimation of return levels against different return periods of extreme annual rainfall over Baluchistan

International Nuclear Information System (INIS)

Ali, M.; Jan, B.; Iqbal, J.

2012-01-01

Unprecedented heavy monsoon rainfall began in the last week of July 2010 in the Northern part of our country, causes floods in Baluchistan and Sindh. As the high frequency rainfall events are a significant cause of current severe flooding in Pakistan and any fluctuation in the level of such events may cause huge economic losses as well as social problem, urban structures (i.e. dams, urban drainage systems and flood). Statistical distributions are used to identify extremes of annual rainfall of different cities of Baluchistan (Quetta, Sibbi, Khuzdar, Lasbella, Dalbandin and Pasni) with their return periods. Analysis predicts that Gumbel Max. (GM) Distribution is the best fitted distribution for Sibbi and Lasbella while the GEV distribution is the best fitted for Quetta, Khuzdar, Dalbandin and Pasni. The analysis also suggests that different cities of Baluchistan have 30-years return period for getting more than 90 mm average daily rainfall while they have 100-years return period for receiving more than 118 mm daily rainfall. This suggests for suitable flood forecasting and improving the river structure in Baluchistan, Pakistan. (author)

Monitoring the variability of precipitable water vapor over the Klang Valley, Malaysia during flash flood

International Nuclear Information System (INIS)

Suparta, W; Rahman, R; Singh, M S J

2014-01-01

Klang Valley is a focal area of Malaysian economic and business activities where the local weather condition is very important to maintain its reputation. Heavy rainfalls for more than an hour were reported up to 40 mm in September 2013 and 35 mm in October 2013. Both events are monitored as the first and second cases of flash flood, respectively. Based on these cases, we investigate the water vapor, rainfall, surface meteorological data (surface pressure, relative humidity, and temperature) and river water level. The precipitable water vapor (PWV) derived from Global Positioning System (GPS) is used to indicate the impact of flash flood on the rainfall. We found that PWV was dropped 4 mm in 2 hours before rainfall reached to 40 mm and dropped 3 mm in 3 hours before 35 mm of rainfall in respective cases. Variation of PWV was higher in September case compared to October case of about 2 mm. We suggest the rainfall phenomena can disturb the GPS propagation and therefore, the impact of PWV before, during and after the flash flood event at three selected GPS stations in Klang Valley is investigated for possible mitigation in the future

The Integration of the Adaptation Approach into EU and Dutch Legislation on Flood Risk Management

NARCIS (Netherlands)

Gilissen, Herman Kasper

2015-01-01

Climate change, worldwide, gives rise to multifarious issues concerning water management. This will lead to both an increase of flood risks and risks related to drought and water scarcity, mostly as a result of sea level rise, increasing river discharges and heavy rainfall, respectively longer, more

Heavy rain prediction using deterministic and probabilistic models - the flash flood cases of 11-13 October 2005 in Catalonia (NE Spain)

Science.gov (United States)

Barrera, A.; Altava-Ortiz, V.; Llasat, M. C.; Barnolas, M.

2007-09-01

Between the 11 and 13 October 2005 several flash floods were produced along the coast of Catalonia (NE Spain) due to a significant heavy rainfall event. Maximum rainfall achieved values up to 250 mm in 24 h. The total amount recorded during the event in some places was close to 350 mm. Barcelona city was also in the affected area where high rainfall intensities were registered, but just a few small floods occurred, thanks to the efficient urban drainage system of the city. Two forecasting methods have been applied in order to evaluate their capability of prediction regarding extreme events: the deterministic MM5 model and a probabilistic model based on the analogous method. The MM5 simulation allows analysing accurately the main meteorological features with a high spatial resolution (2 km), like the formation of some convergence lines over the region that partially explains the maximum precipitation location during the event. On the other hand, the analogous technique shows a good agreement among highest probability values and real affected areas, although a larger pluviometric rainfall database would be needed to improve the results. The comparison between the observed precipitation and from both QPF (quantitative precipitation forecast) methods shows that the analogous technique tends to underestimate the rainfall values and the MM5 simulation tends to overestimate them.

INVESTIGATION OF QUANTIFICATION OF FLOOD CONTROL AND WATER UTILIZATION EFFECT OF RAINFALL INFILTRATION FACILITY BY USING WATER BALANCE ANALYSIS MODEL

OpenAIRE

文, 勇起; BUN, Yuki

2013-01-01

In recent years, many flood damage and drought attributed to urbanization has occurred. At present infiltration facility is suggested for the solution of these problems. Based on this background, the purpose of this study is investigation of quantification of flood control and water utilization effect of rainfall infiltration facility by using water balance analysis model. Key Words : flood control, water utilization , rainfall infiltration facility

Comparison between 3D-Var and 4D-Var data assimilation methods for the simulation of a heavy rainfall case in central Italy

Science.gov (United States)

Mazzarella, Vincenzo; Maiello, Ida; Capozzi, Vincenzo; Budillon, Giorgio; Ferretti, Rossella

2017-08-01

This work aims to provide a comparison between three dimensional and four dimensional variational data assimilation methods (3D-Var and 4D-Var) for a heavy rainfall case in central Italy. To evaluate the impact of the assimilation of reflectivity and radial velocity acquired from Monte Midia Doppler radar into the Weather Research Forecasting (WRF) model, the quantitative precipitation forecast (QPF) is used.The two methods are compared for a heavy rainfall event that occurred in central Italy on 14 September 2012 during the first Special Observation Period (SOP1) of the HyMeX (HYdrological cycle in Mediterranean EXperiment) campaign. This event, characterized by a deep low pressure system over the Tyrrhenian Sea, produced flash floods over the Marche and Abruzzo regions, where rainfall maxima reached more than 150 mm 24 h-1.To identify the best QPF, nine experiments are performed using 3D-Var and 4D-Var data assimilation techniques. All simulations are compared in terms of rainfall forecast and precipitation measured by the gauges through three statistical indicators: probability of detection (POD), critical success index (CSI) and false alarm ratio (FAR). The assimilation of conventional observations with 4D-Var method improves the QPF compared to 3D-Var. In addition, the use of radar measurements in 4D-Var simulations enhances the performances of statistical scores for higher rainfall thresholds.

Heavy rainfalls, floods and landslides in the small catchment of the Bend Carpathians and Subcarpathians (Romania)

International Nuclear Information System (INIS)

Balteanu, Dan; Serban, Mihaela

2004-01-01

The small catchments of the Bend Carpathians and of the adjacent hilly region are affected by a great diversity of geomorphic processes differing in terms of geological structure, terrain configuration, seismic activity and human pressure. The region is developed on Paleogene flysch and Neogene molasse deposits and is characterised by an intense tectonic mobility (neotectonic uplift movements, strong earthquakes). We have chosen two catchments with a surface of 20-30 km 2 in which we tried to evaluate the sediments transfers during extreme events on the slope, from the slope downwards the channels and along the channels. The two catchments are characterised by some of the highest sediment yield in the region. Long-term measurements carried out in the region have revealed that landslides and mud flows are the most common processes of sediment transfer on the slopes. The reactivation of the mass movements is related to heavy rainfalls (over 100 mm in 24 hours) to long lasting rainy periods and to combined rainfalls and rapid snow melting. The denudation rates through mass movements were estimated in 6 experimental plots, indicating values between 1-10 mm in the years with high amount of,precipitations with a return period of 5-7 years and 40-70 mm in extreme conditions with a return period of 50 years. Sediment delivery ratios are controlled by rock erodibility and the runoff regime. A sediment yield multivariate statistical analysis of 27 third order drainage basins on flysch and molasse deposits indicates that total erosion is four times higher in the hilly region than in the flysch mountains (Ichim, Raldoane, 1987).(Author)

Probabilistic Rainfall Intensity-Duration-Frequency Curves for the October 2015 Flooding in South Carolina

Science.gov (United States)

Phillips, R.; Samadi, S. Z.; Meadows, M.

2017-12-01

The potential for the intensity of extreme rainfall to increase with climate change nonstationarity has emerged as a prevailing issue for the design of engineering infrastructure, underscoring the need to better characterize the statistical assumptions underlying hydrological frequency analysis. The focus of this study is on developing probabilistic rainfall intensity-duration-frequency (IDF) curves for the major catchments in South Carolina (SC) where the October 02-05, 2015 floods caused infrastructure damages and several lives to be lost. Continuous to discrete probability distributions including Weibull, the generalized extreme value (GEV), the Generalized Pareto (GP), the Gumbel, the Fréchet, the normal, and the log-normal functions were fitted to the short duration (i.e., 24-hr) intense rainfall. Analysis suggests that the GEV probability distribution provided the most adequate fit to rainfall records. Rainfall frequency analysis indicated return periods above 500 years for urban drainage systems with a maximum return level of approximately 2,744 years, whereas rainfall magnitude was much lower in rural catchments. Further, the return levels (i.e., 2, 20, 50,100, 500, and 1000 years) computed by Monte Carlo method were consistently higher than the NOAA design IDF curves. Given the potential increase in the magnitude of intense rainfall, current IDF curves can substantially underestimate the frequency of extremes, indicating the susceptibility of the storm drainage and flood control structures in SC that were designed under assumptions of a stationary climate.

Estimation of initiating event frequency for external flood events by extreme value theorem

International Nuclear Information System (INIS)

Chowdhury, Sourajyoti; Ganguly, Rimpi; Hari, Vibha

2017-01-01

External flood is an important common cause initiating event in nuclear power plants (NPPs). It may potentially lead to severe core damage (SCD) by first causing the failure of the systems required for maintaining the heat sinks and then by contributing to failures of engineered systems designed to mitigate such failures. The sample NPP taken here is twin 220 MWe Indian standard pressurized heavy water reactor (PHWR) situated inland. A comprehensive in-house Level-1 internal event PSA for full power had already been performed. External flood assessment was further conducted in area of external hazard risk assessment in response to post-Fukushima measures taken in nuclear industries. The present paper describes the methodology to calculate initiating event (IE) frequency for external flood events for the sample inland Indian NPP. General extreme value (GEV) theory based on maximum likelihood method (MLM) and order statistics approach (OSA) is used to analyse the rainfall data for the site. Thousand-year return level and necessary return periods for extreme rainfall are evaluated. These results along with plant-specific topographical calculations quantitatively establish that external flooding resulting from upstream dam break, river flooding and heavy rainfall (flash flood) would be unlikely for the sample NPP in consideration.

Ensemble flood simulation for a small dam catchment in Japan using 10 and 2 km resolution nonhydrostatic model rainfalls

Science.gov (United States)

Kobayashi, Kenichiro; Otsuka, Shigenori; Apip; Saito, Kazuo

2016-08-01

This paper presents a study on short-term ensemble flood forecasting specifically for small dam catchments in Japan. Numerical ensemble simulations of rainfall from the Japan Meteorological Agency nonhydrostatic model (JMA-NHM) are used as the input data to a rainfall-runoff model for predicting river discharge into a dam. The ensemble weather simulations use a conventional 10 km and a high-resolution 2 km spatial resolutions. A distributed rainfall-runoff model is constructed for the Kasahori dam catchment (approx. 70 km2) and applied with the ensemble rainfalls. The results show that the hourly maximum and cumulative catchment-average rainfalls of the 2 km resolution JMA-NHM ensemble simulation are more appropriate than the 10 km resolution rainfalls. All the simulated inflows based on the 2 and 10 km rainfalls become larger than the flood discharge of 140 m3 s-1, a threshold value for flood control. The inflows with the 10 km resolution ensemble rainfall are all considerably smaller than the observations, while at least one simulated discharge out of 11 ensemble members with the 2 km resolution rainfalls reproduces the first peak of the inflow at the Kasahori dam with similar amplitude to observations, although there are spatiotemporal lags between simulation and observation. To take positional lags into account of the ensemble discharge simulation, the rainfall distribution in each ensemble member is shifted so that the catchment-averaged cumulative rainfall of the Kasahori dam maximizes. The runoff simulation with the position-shifted rainfalls shows much better results than the original ensemble discharge simulations.

Why continuous simulation? The role of antecedent moisture in design flood estimation

Science.gov (United States)

Pathiraja, S.; Westra, S.; Sharma, A.

2012-06-01

Continuous simulation for design flood estimation is increasingly becoming a viable alternative to traditional event-based methods. The advantage of continuous simulation approaches is that the catchment moisture state prior to the flood-producing rainfall event is implicitly incorporated within the modeling framework, provided the model has been calibrated and validated to produce reasonable simulations. This contrasts with event-based models in which both information about the expected sequence of rainfall and evaporation preceding the flood-producing rainfall event, as well as catchment storage and infiltration properties, are commonly pooled together into a single set of "loss" parameters which require adjustment through the process of calibration. To identify the importance of accounting for antecedent moisture in flood modeling, this paper uses a continuous rainfall-runoff model calibrated to 45 catchments in the Murray-Darling Basin in Australia. Flood peaks derived using the historical daily rainfall record are compared with those derived using resampled daily rainfall, for which the sequencing of wet and dry days preceding the heavy rainfall event is removed. The analysis shows that there is a consistent underestimation of the design flood events when antecedent moisture is not properly simulated, which can be as much as 30% when only 1 or 2 days of antecedent rainfall are considered, compared to 5% when this is extended to 60 days of prior rainfall. These results show that, in general, it is necessary to consider both short-term memory in rainfall associated with synoptic scale dependence, as well as longer-term memory at seasonal or longer time scale variability in order to obtain accurate design flood estimates.

Flood simulation model using XP-SWMM along Terengganu River ...

African Journals Online (AJOL)

Malaysia is one of the tropical countries in the world with heavy rainfall throughout the year and floods are the most common disaster in Malaysia. Flood simulation model was carried out along Terengganu River for dry and rainy seasons. The result of the simulation shows the water level reached its maximum level at the 1st ...

Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

Science.gov (United States)

Haberlandt, U.; Radtke, I.

2014-01-01

Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the

Application of Flood Nomograph for Flood Forecasting in Urban Areas

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Eui Hoon Lee

2018-01-01

Full Text Available Imperviousness has increased due to urbanization, as has the frequency of extreme rainfall events by climate change. Various countermeasures, such as structural and nonstructural measures, are required to prepare for these effects. Flood forecasting is a representative nonstructural measure. Flood forecasting techniques have been developed for the prevention of repetitive flood damage in urban areas. It is difficult to apply some flood forecasting techniques using training processes because training needs to be applied at every usage. The other flood forecasting techniques that use rainfall data predicted by radar are not appropriate for small areas, such as single drainage basins. In this study, a new flood forecasting technique is suggested to reduce flood damage in urban areas. The flood nomograph consists of the first flooding nodes in rainfall runoff simulations with synthetic rainfall data at each duration. When selecting the first flooding node, the initial amount of synthetic rainfall is 1 mm, which increases in 1 mm increments until flooding occurs. The advantage of this flood forecasting technique is its simple application using real-time rainfall data. This technique can be used to prepare a preemptive response in the process of urban flood management.

Flood hazards for nuclear power plants

International Nuclear Information System (INIS)

Yen, B.C.

1988-01-01

Flooding hazards for nuclear power plants may be caused by various external geophysical events. In this paper the hydrologic hazards from flash floods, river floods and heavy rain at the plant site are considered. Depending on the mode of analysis, two types of hazard evaluation are identified: 1) design hazard which is the probability of flooding over an expected service period, and 2) operational hazard which deals with real-time forecasting of the probability of flooding of an incoming event. Hazard evaluation techniques using flood frequency analysis can only be used for type 1) design hazard. Evaluation techniques using rainfall-runoff simulation or multi-station correlation can be used for both types of hazard prediction. (orig.)

Understanding the Unusual 2017 Monsoon and Floods in South Asia

Science.gov (United States)

Akanda, A. S.; Palash, W.; Hasan, M. A.; Nusrat, F.

2017-12-01

Driven primarily by the South Asian Monsoon, the Ganges-Brahmaputra-Meghna (GBM) river basin system collectively drains intense precipitation for an area of more than 1.5 million square kilometers during the wet summer season. Bangladesh, being the lowest riparian country in the system, experiences recurrent floods and immense suffering to its population. The 2017 monsoon season was quite unusual in terms of the characteristics of the precipitation received in the basin. The monsoon was spread out over a much larger time span (April-October) compared to the average monsoon season (June-September). Although the monsoon does not typically start until June in Bangladesh, the 2017 season started much earlier in April with unusually heavy precipitation in the Meghna basin region and caused major damage to agriculture in northeastern Bangladesh. The rainfall continued in several record-breaking pulses, compared to the typical one or two large waves. One of the largest pulses occurred in early August with very high in intensity and volume, causing ECMWF to issue a major warning about widespread flooding in Bangladesh, Northern India, and Eastern Nepal. This record flood event impacted over 40 million people in the above regions, causing major damage to life and infrastructure. Although the Brahmaputra rose above the danger level several times this season, the Ganges was unusually low, thus sparing downstream areas from disastrous floods. However, heavy precipitation continued until October, causing urban flooding in Dhaka and Chittagong - and worsening sanitation and public health conditions in southern Bangladesh - currently undergoing a terrible humanitarian crisis involving Rohingya refugees from the Myanmar. Despite marked improvement in flood forecasting systems in recent years, the 2017 floods identified critical gaps in our understanding of the flooding phenomena and limitations of dissemination in these regions. In this study, we investigate 1) the unusual

Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique

NARCIS (Netherlands)

Tote, C.; Patricio, D.; Boogaard, H.L.; Wijngaart, van der R.; Tarnavsky, E.; Funk, C.

2015-01-01

Satellite derived rainfall products are useful for drought and flood early warning and overcome the problem of sparse, unevenly distributed and erratic rain gauge observations, provided their accuracy is well known. Mozambique is highly vulnerable to extreme weather events such as major droughts and

Flash floods in Europe: state of the art and research perspectives

Science.gov (United States)

Gaume, Eric

2014-05-01

Flash floods, i.e. floods induced by severe rainfall events generally affecting watersheds of limited area, are the most frequent, destructive and deadly kind of natural hazard known in Europe and throughout the world. Flash floods are especially intense across the Mediterranean zone, where rainfall accumulations exceeding 500 mm within a few hours may be observed. Despite this state of facts, the study of extremes in hydrology has essentially gone unexplored until the recent past, with the exception of some rare factual reports on individual flood events, with the sporadic inclusion of isolated estimated peak discharges. Floods of extraordinary magnitude are in fact hardly ever captured by existing standard measurement networks, either because they are too heavily concentrated in space and time or because their discharges greatly exceed the design and calibration ranges of the measurement devices employed (stream gauges). This situation has gradually evolved over the last decade for two main reasons. First, the expansion and densification of weather radar networks, combined with improved radar quantitative precipitation estimates, now provide ready access to rainfall measurements at spatial and temporal scales that, while not perfectly accurate, are compatible with the study of extreme events. Heavy rainfall events no longer fail to be recorded by existing rain gauge and radar networks. Second, pioneering research efforts on extreme floods, based on precise post-flood surveys, have helped overcome the limitations imposed by a small base of available direct measured data. This activity has already yielded significant progress in expanding the knowledge and understanding of extreme flash floods. This presentation will provide a review of the recent research progresses in the area of flash flood studies, mainly based on the outcomes of the European research projects FLOODsite, HYDRATE and Hymex. It will show how intensive collation of field data helped better define

A rainfall distribution and their influence on flood generation in the eastern Slovakia

Directory of Open Access Journals (Sweden)

Lenka Gaňová

2013-01-01

Full Text Available This paper aims to geographically assess the flood occurrence in eastern Slovakia by using one of the methods of multi-criteria analysis – rank sum method. Flood risk assessment is conducted in three specific cases: the long term period 1989–2009, the extremely wet 2010 year, and the extremely dry 2011 year. In the analyses, some of the causative factors for flooding in a basin area are taken into account. We use set of causative factors concerning mostly hydrological and physio-geographical characteristic of the target area that can be measured and evaluated such as soil type, daily precipitation (for the years 1989–2009, 2010, 2011, land use, catchment area and basin slope. For recommendation which causative factors should be preferred we use method of multicriteria analysis – ranking method. In the ranking method (RM, every factor/criterion under consideration is ranked in the order of the decision-maker’s preference. Geographic approach to flood risk assessment provides a descriptive presentation of the results obtained. Geographic information systems as a visualization tool is presented in a manner that aids understanding in a user friendly way.Regarding our task of flood risk assessment, the partial results are three composite maps, which present comparison of flood risk zones in percentage of the area in years 1989–2009, 2010, and 2011. The composite maps are background for risk assessment of the impact of rainfall on flood generation.This study of hydrological data and physio-geographical characteristic was carried out with the purpose of the identification of flood risk occurrence in eastern Slovakia. Results from our study shows, that rainfall distribution has high influence on flood risk of the area. Area percentage with very high flood risk index was calculated for “wet” year 2010 as 11.73 %, for “dry” year 2011 as 0.01 % and for period 1989–2009 as 0.28 %.

Debris-flow and flooding hazards associated with the December 1999 storm in coastal Venezuela and strategies for mitigation

Science.gov (United States)

Wieczorek, G.F.; Larsen, M.C.; Eaton, L.S.; Morgan, B.A.; Blair, J.L.

2001-01-01

Heavy rainfall from the storm of December 14-16, 1999 triggered thousands of landslides on steep slopes of the Sierra de Avila north of Caracas, Venezuela. In addition to landslides, heavy rainfall caused flooding and massive debris flows that damaged coastal communities in the State of Vargas along the Caribbean Sea. Examination of the rainfall pattern obtained from the GOES-8 satellite showed that the pattern of damage was generally consistent with the area of heaviest rainfall. Field observations of the severely affected drainage basins and historical records indicate that previous flooding and massive debris-flow events of similar magnitude to that of December 1999 have occurred throughout this region. The volume of debris-flow deposits and the large boulders that the flows transported qualifies the 1999 event amongst the largest historical rainfall-induced debris flows documented worldwide.

Heavy rainfall in Mediterranean cyclones. Part I: contribution of deep convection and warm conveyor belt

Science.gov (United States)

Flaounas, Emmanouil; Kotroni, Vassiliki; Lagouvardos, Konstantinos; Gray, Suzanne L.; Rysman, Jean-François; Claud, Chantal

2018-04-01

In this study, we provide an insight to the role of deep convection (DC) and the warm conveyor belt (WCB) as leading processes to Mediterranean cyclones' heavy rainfall. To this end, we use reanalysis data, lighting and satellite observations to quantify the relative contribution of DC and the WCB to cyclone rainfall, as well as to analyse the spatial and temporal variability of these processes with respect to the cyclone centre and life cycle. Results for the period 2005-2015 show that the relationship between cyclone rainfall and intensity has high variability and demonstrate that even intense cyclones may produce low rainfall amounts. However, when considering rainfall averages for cyclone intensity bins, a linear relationship was found. We focus on the 500 most intense tracked cyclones (responsible for about 40-50% of the total 11-year Mediterranean rainfall) and distinguish between the ones producing high and low rainfall amounts. DC and the WCB are found to be the main cause of rainfall for the former (producing up to 70% of cyclone rainfall), while, for the latter, DC and the WCB play a secondary role (producing up to 50% of rainfall). Further analysis showed that rainfall due to DC tends to occur close to the cyclones' centre and to their eastern sides, while the WCBs tend to produce rainfall towards the northeast. In fact, about 30% of rainfall produced by DC overlaps with rainfall produced by WCBs but this represents only about 8% of rainfall produced by WCBs. This suggests that a considerable percentage of DC is associated with embedded convection in WCBs. Finally, DC was found to be able to produce higher rain rates than WCBs, exceeding 50 mm in 3-h accumulated rainfall compared to a maximum of the order of 40 mm for WCBs. Our results demonstrate in a climatological framework the relationship between cyclone intensity and processes that lead to heavy rainfall, one of the most prominent environmental risks in the Mediterranean. Therefore, we set

Propagation of radar rainfall uncertainty in urban flood simulations

Science.gov (United States)

Liguori, Sara; Rico-Ramirez, Miguel

2013-04-01

hydrodynamic sewer network model implemented in the Infoworks software was used to model the rainfall-runoff process in the urban area. The software calculates the flow through the sewer conduits of the urban model using rainfall as the primary input. The sewer network is covered by 25 radar pixels with a spatial resolution of 1 km2. The majority of the sewer system is combined, carrying both urban rainfall runoff as well as domestic and trade waste water [11]. The urban model was configured to receive the probabilistic radar rainfall fields. The results showed that the radar rainfall ensembles provide additional information about the uncertainty in the radar rainfall measurements that can be propagated in urban flood modelling. The peaks of the measured flow hydrographs are often bounded within the uncertainty area produced by using the radar rainfall ensembles. This is in fact one of the benefits of using radar rainfall ensembles in urban flood modelling. More work needs to be done in improving the urban models, but this is out of the scope of this research. The rainfall uncertainty cannot explain the whole uncertainty shown in the flow simulations, and additional sources of uncertainty will come from the structure of the urban models as well as the large number of parameters required by these models. Acknowledgements The authors would like to acknowledge the BADC, the UK Met Office and the UK Environment Agency for providing the various data sets. We also thank Yorkshire Water Services Ltd for providing the urban model. The authors acknowledge the support from the Engineering and Physical Sciences Research Council (EPSRC) via grant EP/I012222/1. References [1] Browning KA, 1978. Meteorological applications of radar. Reports on Progress in Physics 41 761 Doi: 10.1088/0034-4885/41/5/003 [2] Rico-Ramirez MA, Cluckie ID, Shepherd G, Pallot A, 2007. A high-resolution radar experiment on the island of Jersey. Meteorological Applications 14: 117-129. [3] Villarini G, Krajewski WF

Climate change and flood hazard: Evaluation of the SCHADEX methodology in a non-stationary context

International Nuclear Information System (INIS)

Brigode, Pierre

2013-01-01

Since 2006, Electricite de France (EDF) applies a new hydro-climatological approach of extreme rainfall and flood predetermination - the SCHADEX method - for the design of dam spillways. In a context of potential increase of extreme event intensity and frequency due to climate change, the use of the SCHADEX method in non-stationary conditions is a main interest topic for EDF hydrologists. Thus, the scientific goal of this Ph.D. thesis work has been to evaluate the ability of the SCHADEX method to take into account future climate simulations for the estimation of future extreme floods. The recognized inabilities of climate models and down-scaling methods to simulate (extreme) rainfall distribution at the catchment-scale have been avoided, by developing and testing new methodological approaches. Moreover, the decomposition of the flood-producing factors proposed by the SCHADEX method has been used for considering different simulated climatic evolutions and for quantifying the relative impact of these factors on the extreme flood estimation. First, the SCHADEX method has been applied in present time over different climatic contexts (France, Austria, Canada and Norway), thanks to several colorations with academic and industrial partners. A sensitivity analysis allowed to quantify the extreme flood estimation sensitivity to rainfall hazard, catchment saturation hazard and rainfall-runoff transformation, independently. The results showed a large sensitivity of SCHADEX flood estimations to the rainfall hazard and to the rainfall-runoff transformation. Using the sensitivity analysis results, tests have been done in order to estimate the future evolution of 'key' variables previously identified. New climate model outputs (done within the CMIP5 project) have been analyzed and used for determining future frequency of rainfall events and future catchment saturation conditions. Considering these simulated evolutions within the SCHADEX method lead to a significant decrease of

Towards flash flood prediction in the dry Dead Sea region utilizing radar rainfall information

Science.gov (United States)

Morin, E.; Jacoby, Y.; Navon, S.; Bet-Halachmi, E.

2009-04-01

Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model utilizing radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on five years of data for one of the catchments. Validation was performed for a subsequent five-year period for the same catchment and then for an entire ten year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood-warning model is feasible for catchments in the area studied.

Towards flash-flood prediction in the dry Dead Sea region utilizing radar rainfall information

Science.gov (United States)

Morin, Efrat; Jacoby, Yael; Navon, Shilo; Bet-Halachmi, Erez

2009-07-01

Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash-flood models. This paper presents a flash-flood warning model which utilizes radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipitation estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on the 5 years of data for one of the catchments. Validation was performed for a subsequent 5-year period for the same catchment and then for an entire 10-year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood warning model is feasible for catchments in the area studied.

Influence of Oil Viscosity on Alkaline Flooding for Enhanced Heavy Oil Recovery

Directory of Open Access Journals (Sweden)

Yong Du

2013-01-01

Full Text Available Oil viscosity was studied as an important factor for alkaline flooding based on the mechanism of “water drops” flow. Alkaline flooding for two oil samples with different viscosities but similar acid numbers was compared. Besides, series flooding tests for the same oil sample were conducted at different temperatures and permeabilities. The results of flooding tests indicated that a high tertiary oil recovery could be achieved only in the low-permeability (approximately 500 mD sandpacks for the low-viscosity heavy oil (Zhuangxi, 390 mPa·s; however, the high-viscosity heavy oil (Chenzhuang, 3450 mPa·s performed well in both the low- and medium-permeability (approximately 1000 mD sandpacks. In addition, the results of flooding tests for the same oil at different temperatures also indicated that the oil viscosity put a similar effect on alkaline flooding. Therefore, oil with a high-viscosity is favorable for alkaline flooding. The microscopic flooding test indicated that the water drops produced during alkaline flooding for oils with different viscosities differed significantly in their sizes, which might influence the flow behaviors and therefore the sweep efficiencies of alkaline fluids. This study provides an evidence for the feasibility of the development of high-viscosity heavy oil using alkaline flooding.

Rainfall thresholds and flood warning: an operative case study

Directory of Open Access Journals (Sweden)

V. Montesarchio

2009-02-01

Full Text Available An operative methodology for rainfall thresholds definition is illustrated, in order to provide at critical river section optimal flood warnings. Threshold overcoming could produce a critical situation in river sites exposed to alluvial risk and trigger the prevention and emergency system alert. The procedure for the definition of critical rainfall threshold values is based both on the quantitative precipitation observed and the hydrological response of the basin. Thresholds values specify the precipitation amount for a given duration that generates a critical discharge in a given cross section and are estimated by hydrological modelling for several scenarios (e.g.: modifying the soil moisture conditions. Some preliminary results, in terms of reliability analysis (presence of false alarms and missed alarms, evaluated using indicators like hit rate and false alarm rate for the case study of Mignone River are presented.

Censored rainfall modelling for estimation of fine-scale extremes

Science.gov (United States)

Cross, David; Onof, Christian; Winter, Hugo; Bernardara, Pietro

2018-01-01

Reliable estimation of rainfall extremes is essential for drainage system design, flood mitigation, and risk quantification. However, traditional techniques lack physical realism and extrapolation can be highly uncertain. In this study, we improve the physical basis for short-duration extreme rainfall estimation by simulating the heavy portion of the rainfall record mechanistically using the Bartlett-Lewis rectangular pulse (BLRP) model. Mechanistic rainfall models have had a tendency to underestimate rainfall extremes at fine temporal scales. Despite this, the simple process representation of rectangular pulse models is appealing in the context of extreme rainfall estimation because it emulates the known phenomenology of rainfall generation. A censored approach to Bartlett-Lewis model calibration is proposed and performed for single-site rainfall from two gauges in the UK and Germany. Extreme rainfall estimation is performed for each gauge at the 5, 15, and 60 min resolutions, and considerations for censor selection discussed.

Long term variations of extreme rainfall in Denmark and southern Sweden

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan

2015-01-01

A high number of studies have detected changes in the observed heavy rainfall in Northern and Central Europe, all adding to the debate on anthropogenic climate change and its potential impact on rainfall extremes. However, it is equally relevant to understand natural variations on which...... the anthropogenic changes are imposed. This study identifies multi-decadal variations in daily rainfall extremes from Denmark and southern Sweden, with a recurrence level relevant for flood hazard analysis. Based on smoothed series it is concluded that the frequency of the extreme events shows both a general...

The Spatial Scaling of Global Rainfall Extremes

Science.gov (United States)

Devineni, N.; Xi, C.; Lall, U.; Rahill-Marier, B.

2013-12-01

Floods associated with severe storms are a significant source of risk for property, life and supply chains. These property losses tend to be determined as much by the duration of flooding as by the depth and velocity of inundation. High duration floods are typically induced by persistent rainfall (upto 30 day duration) as seen recently in Thailand, Pakistan, the Ohio and the Mississippi Rivers, France, and Germany. Events related to persistent and recurrent rainfall appear to correspond to the persistence of specific global climate patterns that may be identifiable from global, historical data fields, and also from climate models that project future conditions. A clear understanding of the space-time rainfall patterns for events or for a season will enable in assessing the spatial distribution of areas likely to have a high/low inundation potential for each type of rainfall forcing. In this paper, we investigate the statistical properties of the spatial manifestation of the rainfall exceedances. We also investigate the connection of persistent rainfall events at different latitudinal bands to large-scale climate phenomena such as ENSO. Finally, we present the scaling phenomena of contiguous flooded areas as a result of large scale organization of long duration rainfall events. This can be used for spatially distributed flood risk assessment conditional on a particular rainfall scenario. Statistical models for spatio-temporal loss simulation including model uncertainty to support regional and portfolio analysis can be developed.

The “Maya Express”: Floods in the U.S. Midwest

Science.gov (United States)

Dirmeyer, Paul A.; Kinter, James L.

2009-03-01

The 2008 floods in the U.S. Midwest culminated in severe river flooding, with many rivers in the region cresting at record levels during May and particularly June. Twenty-four people were killed and more than 140 were injured as a result of the floods. Nine states were affected: Illinois, Indiana, Iowa, Kansas, Minnesota, Missouri, Nebraska, South Dakota, and Wisconsin. In Iowa, 83 of the state's 99 counties were declared disaster areas. Cedar Rapids, Iowa, was among the cities hardest hit by flooding. At one point, water covered 1300 city blocks across 24 square kilometers, inundating 3900 homes and most of the city's infrastructure and municipal facilities. The flood, which also damaged the Midwest's corn and soybean crops, was presaged by unusually heavy snowpack the preceding winter and by anomalously heavy rainfall during the spring.

Return period curves for extreme 5-min rainfall amounts at the Barcelona urban network

Science.gov (United States)

Lana, X.; Casas-Castillo, M. C.; Serra, C.; Rodríguez-Solà, R.; Redaño, A.; Burgueño, A.; Martínez, M. D.

2018-03-01

Heavy rainfall episodes are relatively common in the conurbation of Barcelona and neighbouring cities (NE Spain), usually due to storms generated by convective phenomena in summer and eastern and south-eastern advections in autumn. Prevention of local flood episodes and right design of urban drainage have to take into account the rainfall intensity spread instead of a simple evaluation of daily rainfall amounts. The database comes from 5-min rain amounts recorded by tipping buckets in the Barcelona urban network along the years 1994-2009. From these data, extreme 5-min rain amounts are selected applying the peaks-over-threshold method for thresholds derived from both 95% percentile and the mean excess plot. The return period curves are derived from their statistical distribution for every gauge, describing with detail expected extreme 5-min rain amounts across the urban network. These curves are compared with those derived from annual extreme time series. In this way, areas in Barcelona submitted to different levels of flood risk from the point of view of rainfall intensity are detected. Additionally, global time trends on extreme 5-min rain amounts are quantified for the whole network and found as not statistically significant.

Commonalities and Differences in Flood-Generating Processes across the US

Science.gov (United States)

Li, X.; Troy, T. J.

2017-12-01

There is significant damage caused by flood, and the flood risk is increasing in the future, but there is large uncertainty in future decadal projections of flooding. In order to improve these projections, we must first turn to the past to understand the physical mechanisms that lead to flooding in basins across spatial scales and elevation ranges. To do this, we calculated the seasonality of annual maximum flows and other climatic factors to identify the flood-generating process in 2566 basins across the continental US. For most regions, the seasonality of heavy precipitation is not in phase with the seasonality of flooding, pointing to the importance of antecedent soil moisture and snow in determining flooding over much of the US. To determine the characteristic conditions leading to a flood, we classified all floods into those with different rainfall durations and with/without snow presence. Analyzing the influence of elevation, slope and drainage area, we identified patterns: the probability of flooding due to long duration precipitation increases as drainage area increases and snow present during a flood becomes increasingly likely as average basin elevation increases. To better understand the relationship between heavy rainfall and high streamflow, we calculated conditioned probability of occurrence. The southeastern US has a higher probability of occurrence for extreme Q with the same level of extreme precipitation in winter and spring than the northern US. This work is the first to look at how flood mechanisms vary across the continental US with drainage area, climate, and elevation.

Meteorological analysis of flash floods in Artvin (NE Turkey on 24 August 2015

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H. Baltaci

2017-07-01

Full Text Available On 24 August 2015 intense rainfall episodes generated flash floods and landslides on the eastern Black Sea coast of Turkey. As a consequence of the heavy rainstorm activity over Artvin and its surroundings (NE Turkey, 11 people died and economic losses totaled a million dollars. Over the 6 h of the event (from 05:00 to 11:00 UTC, total accumulated rainfall amounts of 136, 64, and 109 mm were measured in the Hopa, Arhavi, and Borçka settlements of Artvin city, respectively. This study comprehensively investigates the meteorological characteristics of those flash floods. In terms of synoptic mechanisms, the cutoff surface low from the summer Asian monsoon settled over the eastern Black Sea. After two days of quasistationary conditions of this cyclone, sea surface temperatures (SSTs reached 27.5 °C (1.5 °C higher than normal and low-level moisture convergence developed. In addition, transfer of moisture by warm northerly flows from the Black Sea and relatively cool southerly flows from the land coasts of the Artvin district exacerbated the unstable conditions and thus played a significant role in the development of deep convective cells. Severe rainstorms as well as the slope instability of the region triggered landslides and worsened flood damages in the Artvin area. This study supports conventional weather analysis, satellite images, and forecast model output to alert forecasters to the potential for heavy rainfall.

Evaluation of Stochastic Rainfall Models in Capturing Climate Variability for Future Drought and Flood Risk Assessment

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Chowdhury, A. F. M. K.; Lockart, N.; Willgoose, G. R.; Kuczera, G. A.; Kiem, A.; Nadeeka, P. M.

2016-12-01

One of the key objectives of stochastic rainfall modelling is to capture the full variability of climate system for future drought and flood risk assessment. However, it is not clear how well these models can capture the future climate variability when they are calibrated to Global/Regional Climate Model data (GCM/RCM) as these datasets are usually available for very short future period/s (e.g. 20 years). This study has assessed the ability of two stochastic daily rainfall models to capture climate variability by calibrating them to a dynamically downscaled RCM dataset in an east Australian catchment for 1990-2010, 2020-2040, and 2060-2080 epochs. The two stochastic models are: (1) a hierarchical Markov Chain (MC) model, which we developed in a previous study and (2) a semi-parametric MC model developed by Mehrotra and Sharma (2007). Our hierarchical model uses stochastic parameters of MC and Gamma distribution, while the semi-parametric model uses a modified MC process with memory of past periods and kernel density estimation. This study has generated multiple realizations of rainfall series by using parameters of each model calibrated to the RCM dataset for each epoch. The generated rainfall series are used to generate synthetic streamflow by using a SimHyd hydrology model. Assessing the synthetic rainfall and streamflow series, this study has found that both stochastic models can incorporate a range of variability in rainfall as well as streamflow generation for both current and future periods. However, the hierarchical model tends to overestimate the multiyear variability of wet spell lengths (therefore, is less likely to simulate long periods of drought and flood), while the semi-parametric model tends to overestimate the mean annual rainfall depths and streamflow volumes (hence, simulated droughts are likely to be less severe). Sensitivity of these limitations of both stochastic models in terms of future drought and flood risk assessment will be discussed.

Physical Responses of Convective Heavy Rainfall to Future Warming Condition: Case Study of the Hiroshima Event

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Kenshi Hibino

2018-04-01

Full Text Available An extreme precipitation event happened at Hiroshima in 2014. Over 200 mm of total rainfall was observed on the night of August 19th, which caused floods and many landslides. The rainfall event was estimated to be a rare event happening once in approximately 30 years. The physical response of this event to the change of the future atmospheric condition, which includes a temperature increase on average and convective stability change, is investigated in the present study using a 27-member ensemble experiment and pseudo global warming downscaling method. The experiment is integrated using the Japan Meteorological Research Institute non-hydrostatic regional climate model. A very high-resolution horizontal grid, 500 m, is used to reproduce dense cumulonimbus cloud formation causing heavy rainfall in the model. The future climate condition determined by a higher greenhouse gas concentration is prescribed to the model, in which the surface air temperature globally averaged is 4 K warmer than that in the preindustrial era. The total amounts of precipitation around the Hiroshima area in the future experiments are closer to or slightly lower than in the current experiments in spite of the increase in water vapor due to the atmospheric warming. The effect of the water vapor increase on extreme precipitation is found to be canceled out by the suppression of convection due to the thermal stability enhancement. The fact that future extreme precipitation like the Hiroshima event is not intensified is in contrast to the well-known result that extreme rainfall tends to be intensified in the future. The results in the present study imply that the response of extreme precipitation to global warming differs for each rainfall phenomenon.

Derived flood frequency analysis using different model calibration strategies based on various types of rainfall-runoff data - a comparison

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Haberlandt, U.; Radtke, I.

2013-08-01

Derived flood frequency analysis allows to estimate design floods with hydrological modelling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices about precipitation input, discharge output and consequently regarding the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets. Event based and continuous observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in Northern Germany with the hydrological model HEC-HMS. The results show that: (i) the same type of precipitation input data should be used for calibration and application of the hydrological model, (ii) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, (iii) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the application for derived flood frequency analysis.

Modeling jointly low, moderate, and heavy rainfall intensities without a threshold selection

KAUST Repository

Naveau, Philippe

2016-04-09

In statistics, extreme events are often defined as excesses above a given large threshold. This definition allows hydrologists and flood planners to apply Extreme-Value Theory (EVT) to their time series of interest. Even in the stationary univariate context, this approach has at least two main drawbacks. First, working with excesses implies that a lot of observations (those below the chosen threshold) are completely disregarded. The range of precipitation is artificially shopped down into two pieces, namely large intensities and the rest, which necessarily imposes different statistical models for each piece. Second, this strategy raises a nontrivial and very practical difficultly: how to choose the optimal threshold which correctly discriminates between low and heavy rainfall intensities. To address these issues, we propose a statistical model in which EVT results apply not only to heavy, but also to low precipitation amounts (zeros excluded). Our model is in compliance with EVT on both ends of the spectrum and allows a smooth transition between the two tails, while keeping a low number of parameters. In terms of inference, we have implemented and tested two classical methods of estimation: likelihood maximization and probability weighed moments. Last but not least, there is no need to choose a threshold to define low and high excesses. The performance and flexibility of this approach are illustrated on simulated and hourly precipitation recorded in Lyon, France.

Calibration of a rainfall-runoff hydrological model and flood simulation using data assimilation

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Piacentini, A.; Ricci, S. M.; Thual, O.; Coustau, M.; Marchandise, A.

2010-12-01

Rainfall-runoff models are crucial tools for long-term assessment of flash floods or real-time forecasting. This work focuses on the calibration of a distributed parsimonious event-based rainfall-runoff model using data assimilation. The model combines a SCS-derived runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The SCS-derived runoff model is parametrized by the initial water deficit, the discharge coefficient for the soil reservoir and a lagged discharge coefficient. The Lag and Route routing model is parametrized by the velocity of travel and the lag parameter. These parameters are assumed to be constant for a given catchment except for the initial water deficit and the velocity travel that are event-dependent (landuse, soil type and moisture initial conditions). In the present work, a BLUE filtering technique was used to calibrate the initial water deficit and the velocity travel for each flood event assimilating the first available discharge measurements at the catchment outlet. The advantages of the BLUE algorithm are its low computational cost and its convenient implementation, especially in the context of the calibration of a reduced number of parameters. The assimilation algorithm was applied on two Mediterranean catchment areas of different size and dynamics: Gardon d'Anduze and Lez. The Lez catchment, of 114 km2 drainage area, is located upstream Montpellier. It is a karstic catchment mainly affected by floods in autumn during intense rainstorms with short Lag-times and high discharge peaks (up to 480 m3.s-1 in September 2005). The Gardon d'Anduze catchment, mostly granite and schistose, of 545 km2 drainage area, lies over the departements of Lozère and Gard. It is often affected by flash and devasting floods (up to 3000 m3.s-1 in September 2002). The discharge observations at the beginning of the flood event are assimilated so that the BLUE algorithm provides optimal values for the initial water deficit and the

Analysis and GIS Mapping of Flooding Hazards on 10 May 2016, Guangzhou, China

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Hai-Min Lyu

2016-10-01

Full Text Available On 10 May 2016, Guangdong Province, China, suffered a heavy rainstorm. This rainstorm flooded the whole city of Guangzhou. More than 100,000 people were affected by the flooding, in which eight people lost their lives. Subway stations, cars, and buses were submerged. In order to analyse the influential factors of this flooding, topographical characteristics were mapped using Digital Elevation Model (DEM by the Geographical Information System (GIS and meteorological conditions were statistically summarised at both the whole city level and the district level. To analyse the relationship between flood risk and urbanization, GIS was also adopted to map the effect of the subway system using the Multiple Buffer operator over the flooding distribution area. Based on the analyses, one of the significant influential factors of flooding was identified as the urbanization degree, e.g., construction of a subway system, which forms along flood-prone areas. The total economic loss due to flooding in city centers with high urbanization has become very serious. Based on the analyses, the traditional standard of severity of flooding hazards (rainfall intensity grade was modified. Rainfall intensity for severity flooding was decreased from 50 mm to 30 mm in urbanized city centers. In order to protect cities from flooding, a “Sponge City” planning approach is recommended to increase the temporary water storage capacity during heavy rainstorms. In addition, for future city management, the combined use of GIS and Building Information Modelling (BIM is recommended to evaluate flooding hazards.

Prediction of heavy rainfall over Chennai Metropolitan City, Tamil Nadu, India: Impact of microphysical parameterization schemes

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Singh, K. S.; Bonthu, Subbareddy; Purvaja, R.; Robin, R. S.; Kannan, B. A. M.; Ramesh, R.

2018-04-01

This study attempts to investigate the real-time prediction of a heavy rainfall event over the Chennai Metropolitan City, Tamil Nadu, India that occurred on 01 December 2015 using Advanced Research Weather Research and Forecasting (WRF-ARW) model. The study evaluates the impact of six microphysical (Lin, WSM6, Goddard, Thompson, Morrison and WDM6) parameterization schemes of the model on prediction of heavy rainfall event. In addition, model sensitivity has also been evaluated with six Planetary Boundary Layer (PBL) and two Land Surface Model (LSM) schemes. Model forecast was carried out using nested domain and the impact of model horizontal grid resolutions were assessed at 9 km, 6 km and 3 km. Analysis of the synoptic features using National Center for Environmental Prediction Global Forecast System (NCEP-GFS) analysis data revealed strong upper-level divergence and high moisture content at lower level were favorable for the occurrence of heavy rainfall event over the northeast coast of Tamil Nadu. The study signified that forecasted rainfall was more sensitive to the microphysics and PBL schemes compared to the LSM schemes. The model provided better forecast of the heavy rainfall event using the logical combination of Goddard microphysics, YSU PBL and Noah LSM schemes, and it was mostly attributed to timely initiation and development of the convective system. The forecast with different horizontal resolutions using cumulus parameterization indicated that the rainfall prediction was not well represented at 9 km and 6 km. The forecast with 3 km horizontal resolution provided better prediction in terms of timely initiation and development of the event. The study highlights that forecast of heavy rainfall events using a high-resolution mesoscale model with suitable representations of physical parameterization schemes are useful for disaster management and planning to minimize the potential loss of life and property.

Relationship of Rainfall Distribution and Water Level on Major Flood 2014 in Pahang River Basin, Malaysia

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Nur Hishaam Sulaiman

2017-01-01

Full Text Available Climate change gives impact on extreme hydrological events especially in extreme rainfall. This article discusses about the relationship of rainfall distribution and water level on major flood 2014 in Pahang River Basin, Malaysia in helping decision makers to flood management system. Based on DID Malaysia rainfall station, 56 stations have being use as point in this research and it is including Pahang, Terengganu, Kelantan and Perak. Data set for this study were analysed with GIS analysis using interpolation method to develop Isohyet map and XLstat statistical software for PCA and SPC analyses. The results that were obtained from the Isohyet Map for three months was mid-November, rainfall started to increase about in range of 800mm-1200mm and the intensity keep increased to 2200mm at mid-December 2014. The high rainfall intensity sense at highland that is upstream of Pahang River. The PCA and SPC analysis also indicates the high relationship between rainfall and water level of few places at Pahang River. The Sg. Yap station and Kg. Serambi station obtained the high relationship of rainfall and water level with factor loading value at 0.9330 and 0.9051 for each station. Hydrological pattern and trend are extremely affected by climate such as north east monsoon season that occurred in South China Sea and affected Pahang during November to March. The findings of this study are important to local authorities by providing basic data as guidelines to the integrated river management at Pahang River Basin.

Decadal features of heavy rainfall events in eastern China

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Chen, Huopo; Sun, Jianqi; Fan, Ke

2012-06-01

Based on daily precipitation data, the spatial-temporal features of heavy rainfall events (HREs) during 1960-2009 are investigated. The results indicate that the HREs experienced strong decadal variability in the past 50 years, and the decadal features varied across regions. More HRE days are observed in the 1960s, 1980s, and 1990s over Northeast China (NEC); in the 1960s, 1970s, and 1990s over North China (NC); in the early 1960s, 1980s, and 2000s over the Huaihe River basin (HR); in the 1970s-1990s over the mid-lower reaches of the Yangtze River valley (YR); and in the 1970s and 1990s over South China (SC). These decadal changes of HRE days in eastern China are closely associated with the decadal variations of water content and stratification stability of the local atmosphere. The intensity of HREs in each sub-region is also characterized by strong decadal variability. The HRE intensity and frequency co-vary on the long-term trend, and show consistent variability over NEC, NC, and YR, but inconsistent variability over SC and HR. Further analysis of the relationships between the annual rainfall and HRE frequency as well as intensity indicates that the HRE frequency is the major contributor to the total rainfall variability in eastern China, while the HRE intensity shows only relative weak contribution.

The Significance of the Spatial Variability of Rainfall on the Numerical Simulation of Urban Floods

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Laurent Guillaume Courty

2018-02-01

Full Text Available The growth of urban population, combined with an increase of extreme events due to climate change call for a better understanding and representation of urban floods. The uncertainty in rainfall distribution is one of the most important factors that affects the watershed response to a given precipitation event. However, most of the investigations on this topic have considered theoretical scenarios, with little reference to case studies in the real world. This paper incorporates the use of spatially-variable precipitation data from a long-range radar in the simulation of the severe floods that impacted the city of Hull, U.K., in June 2007. This radar-based rainfall field is merged with rain gauge data using a Kriging with External Drift interpolation technique. The utility of this spatially-variable information is investigated through the comparison of computed flooded areas (uniform and radar against those registered by public authorities. Both results show similar skills at reproducing the real event, but differences in the total precipitated volumes, water depths and flooded areas are illustrated. It is envisaged that in urban areas and with the advent of higher resolution radars, these differences will be more important and call for further investigation.

Causes and Model Skill of the Persistent Intense Rainfall and Flooding in Paraguay during the Austral Summer 2015-2016

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Doss-Gollin, J.; Munoz, A. G.; Pastén, M.

2017-12-01

During the austral summer 2015-16 severe flooding displaced over 150,000 people on the Paraguay River system in Paraguay, Argentina, and Southern Brazil. This flooding was out of phase with the typical seasonal cycle of the Paraguay River, and was driven by repeated intense rainfall events in the Lower Paraguay River basin. Using a weather typing approach within a diagnostic framework, we show that enhanced moisture inflow from the low-level jet and local convergence associated with baroclinic systems favored the development of mesoscale convective activity and enhanced precipitation. The observed circulation patterns were made more likely by the cross-timescale interactions of multiple climate mechanisms including the strong, mature El Niño event and an active Madden-Julien Oscillation in phases four and five. We also perform a comparison of the rainfall predictability using seasonal forecasts from the Latin American Observatory of Climate Events (OLE2) and sub-seasonal forecasts produced by the ECMWF. We find that the model output precipitation field exhibited limited skill at lead times beyond the synoptic timescale, but that a Model Output Statistics (MOS) approach, in which the leading principal components of the observed rainfall field are regressed on the leading principal components of model-simulated rainfall fields, substantially improves spatial representation of rainfall forecasts. Possible implications for flood preparedness are briefly discussed.

Increasing risk of compound flooding from storm surge and rainfall for major US coastal cities

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Wahl, Thomas; Jain, Shaleen; Bender, Jens; Meyers, Steven; Luther, Mark

2016-04-01

Flood risk is a well-known facet of natural hazards along the US coastline where nearly 40% of the population resides in coastal counties. Given the heavy reliance on the coastal zone for natural resources and economic activity, flood preparedness and safety is a key element of long-term resilience. A clear understanding of the various flood types and changes in the frequency of their occurrence is critical towards reliable estimates of vulnerability and potential impacts in the near-term as well as into the future. When the two main flood drivers for coastal areas storm surge and heavy precipitation occur in tandem the potential for significant flooding is much greater than from either in isolation. Exploring the probability of these 'compound events' and understanding the processes driving them is essential to mitigate the associated high impact risks. For the contiguous US the likelihood of the joint occurrence of the two phenomena is largely unknown. Here we show - using storm surge and precipitation records spanning the last century - that the risk of compound flooding is higher for the US east and Gulf coasts, relative to the west coast. We also show that the number of compound events has increased significantly over the last century along large coastline stretches including many of the major coastal cities. For New York City - as an example - this increase is attributed to a shift towards storm surge weather patterns also favouring high precipitation. Preliminary analyses reveal that these synoptic scale changes are closely linked to large scale and low frequency climate variations. Our results demonstrate the importance of assessing the risk of compound flooding within the design process of coastal and urban infrastructure in a non-stationary framework and to explore the potential effects of climate change on these high impact events.

Rainfall estimation in the context of post-event flash flood analysis

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Delrieu, Guy; Boudevillain, Brice; Bouilloud, Ludovic

2010-05-01

Due to their spatial coverage and space-time resolution, operational weather radar networks offer unprecedented opportunities for the observation of flash flood generating storms. However, the radar rainfall estimation quality highly depends on the relative locations of the event and the radar(s). A mountainous environment obviously adds to the complexity of the radar quantitative precipitation estimation (QPE). A pragmatic methodology was developed within the EC-funded HYDRATE project to take the best benefit of the existing rainfall observations (radar and raingauge data) for given flash-flood cases: 1) A precise documentation of the radar characteristics (location, parameters, operating protocol, data archives and processing) needs first to be established. The radar(s) detection domain(s) can then be characterized using the "hydrologic visibility" concepts (Pellarin et al. J Hydrometeor 3(5) 539-555 2002). 2) Rather dense raingauge observations (operational, amateur) are usually available at the event time scale while few raingauge time series exist at the hydrologic time steps. Such raingauge datasets need to be critically analysed; a geostatistical approach is proposed for this task. 3) A number of identifications can be implemented prior to the radar data re-processing: a) Special care needs to be paid to (residual) ground clutter which has a dramatic impact of radar QPE. Dry-weather maps and rainfall accumulation maps may help in this task. b) Various sources of power losses such as screening, wet radome, attenuation in rain need to be identified and quantified. It will be shown that mountain returns can be used to quantify attenuation effects at C-band. c) Radar volume data is required to characterize the vertical profile of reflectivity (VPR), eventually conditioned on rain type (convective, widespread). When such data is not available, knowledge of the 0°C isotherm and the scanning protocol may help detecting bright-band contaminations that critically

Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps

Science.gov (United States)

Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter

2017-04-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.

Cloud structure evolution of heavy rain events from the East-West Pacific Ocean: a combined global observation analysis

Science.gov (United States)

Sekaranom, A. B.; Nurjani, E.; Pujiastuti, I.

2018-04-01

Heavy rain events are often associated with flood hazards as one of the most devastating events across the globe. It is therefore essential to identify the evolution of heavy rainfall cloud structures, primarily from global satellite observation, as a tool to provide better disaster early warning systems. To identify the mechanism of heavy rainfall systems and its relationship with cloud development, especially over The Pacific Ocean, we aim to study the westward evolution of the convective systems over this area. Several datasets from Tropical Rainfall Measuring Mission (TRMM), CloudSat GEOPROF product, and ECMWF-reanalysis (ERA) interim were utilized to characterize the evolution. Geolocation and orbital time-lag analysis of the three different datasets for more than 8 years (2006-2014) could provide information related to the evolution of cloud structures associated with heavy rain events. In the first step, a heavy rainfall database was generated from TRMM. The CloudSat coordinate and time position were then matched with TRMM coordinate and time position. All of the processes were programatically conducted in fortran programming language. The result shows a transition between East and West Pacific ocean for TMI data.

Estimates of peak flood discharge for 21 sites in the Front Range in Colorado in response to extreme rainfall in September 2013

Science.gov (United States)

Moody, John A.

2016-03-21

Extreme rainfall in September 2013 caused destructive floods in part of the Front Range in Boulder County, Colorado. Erosion from these floods cut roads and isolated mountain communities for several weeks, and large volumes of eroded sediment were deposited downstream, which caused further damage of property and infrastructures. Estimates of peak discharge for these floods and the associated rainfall characteristics will aid land and emergency managers in the future. Several methods (an ensemble) were used to estimate peak discharge at 21 measurement sites, and the ensemble average and standard deviation provided a final estimate of peak discharge and its uncertainty. Because of the substantial erosion and deposition of sediment, an additional estimate of peak discharge was made based on the flow resistance caused by sediment transport effects.Although the synoptic-scale rainfall was extreme (annual exceedance probability greater than 1,000 years, about 450 millimeters in 7 days) for these mountains, the resulting peak discharges were not. Ensemble average peak discharges per unit drainage area (unit peak discharge, [Qu]) for the floods were 1–2 orders of magnitude less than those for the maximum worldwide floods with similar drainage areas and had a wide range of values (0.21–16.2 cubic meters per second per square kilometer [m3 s-1 km-2]). One possible explanation for these differences was that the band of high-accumulation, high-intensity rainfall was narrow (about 50 kilometers wide), oriented nearly perpendicular to the predominant drainage pattern of the mountains, and therefore entire drainage areas were not subjected to the same range of extreme rainfall. A linear relation (coefficient of determination [R2]=0.69) between Qu and the rainfall intensity (ITc, computed for a time interval equal to the time-of-concentration for the drainage area upstream from each site), had the form: Qu=0.26(ITc-8.6), where the coefficient 0.26 can be considered to be an

Floods in Central Texas, September 7-14, 2010

Science.gov (United States)

Winters, Karl E.

2012-01-01

Severe flooding occurred near the Austin metropolitan area in central Texas September 7–14, 2010, because of heavy rainfall associated with Tropical Storm Hermine. The U.S. Geological Survey, in cooperation with the Upper Brushy Creek Water Control and Improvement District, determined rainfall amounts and annual exceedance probabilities for rainfall resulting in flooding in Bell, Williamson, and Travis counties in central Texas during September 2010. We documented peak streamflows and the annual exceedance probabilities for peak streamflows recorded at several streamflow-gaging stations in the study area. The 24-hour rainfall total exceeded 12 inches at some locations, with one report of 14.57 inches at Lake Georgetown. Rainfall probabilities were estimated using previously published depth-duration frequency maps for Texas. At 4 sites in Williamson County, the 24-hour rainfall had an annual exceedance probability of 0.002. Streamflow measurement data and flood-peak data from U.S. Geological Survey surface-water monitoring stations (streamflow and reservoir gaging stations) are presented, along with a comparison of September 2010 flood peaks to previous known maximums in the periods of record. Annual exceedance probabilities for peak streamflow were computed for 20 streamflow-gaging stations based on an analysis of streamflow-gaging station records. The annual exceedance probability was 0.03 for the September 2010 peak streamflow at the Geological Survey's streamflow-gaging stations 08104700 North Fork San Gabriel River near Georgetown, Texas, and 08154700 Bull Creek at Loop 360 near Austin, Texas. The annual exceedance probability was 0.02 for the peak streamflow for Geological Survey's streamflow-gaging station 08104500 Little River near Little River, Texas. The lack of similarity in the annual exceedance probabilities computed for precipitation and streamflow might be attributed to the small areal extent of the heaviest rainfall over these and the other gaged

A Review on Flood Events for Kelantan River Watershed in Malaysia for Last Decade (2001-2010)

Science.gov (United States)

Aminah Shakirah, J.; Sidek, L. M.; Hidayah, B.; Nazirul, M. Z.; Jajarmizadeh, M.; Ros, F. C.; Roseli, ZA

2016-03-01

Malaysia is located at tropical zone and high precipitation area that frequently hit by flood events when it is near monsoon season. This hydro hazard has been one of the main concerns for governmental and non-governmental sectors. High floods lead in financial damages and they are related with human’s life. Kelantan watershed is one of the challenging watersheds which mostly suffer from flood events and heavy rainfall events. Flood in Kelantan watershed is related with monetary misfortunes and lives. Clearly, flood have significant influence on various water sectors such water supply, agriculture, human health and ecosystems therefore study of this topic and presentation of available of any data and information can be a valuable baseline for upcoming research in vulnerable case studies. In this study, Kelantan watershed is selected because it is prone to flooding and urban areas classified as vulnerable districts. This overview is discussed on the last decade (2001-2010) floods events in Kelantan.

Simulation of Flash-Flood-Producing Storm Events in Saudi Arabia Using the Weather Research and Forecasting Model

KAUST Repository

Deng, Liping

2015-05-01

The challenges of monitoring and forecasting flash-flood-producing storm events in data-sparse and arid regions are explored using the Weather Research and Forecasting (WRF) Model (version 3.5) in conjunction with a range of available satellite, in situ, and reanalysis data. Here, we focus on characterizing the initial synoptic features and examining the impact of model parameterization and resolution on the reproduction of a number of flood-producing rainfall events that occurred over the western Saudi Arabian city of Jeddah. Analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data suggests that mesoscale convective systems associated with strong moisture convergence ahead of a trough were the major initial features for the occurrence of these intense rain events. The WRF Model was able to simulate the heavy rainfall, with driving convective processes well characterized by a high-resolution cloud-resolving model. The use of higher (1 km vs 5 km) resolution along the Jeddah coastline favors the simulation of local convective systems and adds value to the simulation of heavy rainfall, especially for deep-convection-related extreme values. At the 5-km resolution, corresponding to an intermediate study domain, simulation without a cumulus scheme led to the formation of deeper convective systems and enhanced rainfall around Jeddah, illustrating the need for careful model scheme selection in this transition resolution. In analysis of multiple nested WRF simulations (25, 5, and 1 km), localized volume and intensity of heavy rainfall together with the duration of rainstorms within the Jeddah catchment area were captured reasonably well, although there was evidence of some displacements of rainstorm events.

Floods in Colorado

Science.gov (United States)

Follansbee, Robert; Sawyer, Leon R.

1948-01-01

The first records of floods in Colorado antedated the settlement of the State by about 30 years. These were records of floods on the Arkansas and Republican Rivers in 1826. Other floods noted by traders, hunters and emigrants, some of whom were on their way to the Far West, occurred in 1844 on the Arkansas River, and by inference on the South Platte River. Other early floods were those on the Purgatoire, the Lower Arkansas, and the San Juan Rivers about 1859. The most serious flood since settlement began was that on the Arkansas River during June 1921, which caused the loss of about 100 lives and an estimated property loss of $19,000,000. Many floods of lesser magnitude have occurred, and some of these have caused loss of life and very considerable property damage. Topography is the chief factor in determining the location of storms and resulting floods. These occur most frequently on the eastern slope of the Front Range. In the mountains farther west precipitation is insufficient to cause floods except during periods of melting snow, in June. In the southwestern part of the State, where precipitation during periods of melting snow is insufficient to cause floods, the severest floods yet experienced resulted from heavy rains in September 1909 and October 1911. In the eastern foothills region, usually below an altitude of about 7,500 feet and extending for a distance of about 50 miles east of the mountains, is a zone subject to rainfalls of great intensity known as cloudbursts. These cloudbursts are of short duration and are confined to very small areas. At times the intensity is so great as to make breathing difficult for those exposed to a storm. The areas of intense rainfall are so small that Weather Bureau precipitation stations have not been located in them. Local residents, being cloudburst conscious, frequently measure the rainfall in receptacles in their yards, and such records constitute the only source of information regarding the intensity. A flood

Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

KAUST Repository

Viswanadhapalli, Yesubabu; Srinivas, C.V.; Langodan, Sabique; Hoteit, Ibrahim

2015-01-01

The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011

Occurrence of heavy rainfall around the confluence line in monsoon ...

Indian Academy of Sciences (India)

that when the disturbance-centre is away from the basin, heavy rainfall may also occur in the basin area close to ... Lal 1958; Bedekar and Benarjee 1969) extending .... 13. 26.8.1977. 23.3. D around C.L.. 14. 18.8.1978. 40.5. D around C.L.. 15.

Including local rainfall dynamics and uncertain boundary conditions into a 2-D regional-local flood modelling cascade

Science.gov (United States)

Bermúdez, María; Neal, Jeffrey C.; Bates, Paul D.; Coxon, Gemma; Freer, Jim E.; Cea, Luis; Puertas, Jerónimo

2016-04-01

Flood inundation models require appropriate boundary conditions to be specified at the limits of the domain, which commonly consist of upstream flow rate and downstream water level. These data are usually acquired from gauging stations on the river network where measured water levels are converted to discharge via a rating curve. Derived streamflow estimates are therefore subject to uncertainties in this rating curve, including extrapolating beyond the maximum observed ratings magnitude. In addition, the limited number of gauges in reach-scale studies often requires flow to be routed from the nearest upstream gauge to the boundary of the model domain. This introduces additional uncertainty, derived not only from the flow routing method used, but also from the additional lateral rainfall-runoff contributions downstream of the gauging point. Although generally assumed to have a minor impact on discharge in fluvial flood modeling, this local hydrological input may become important in a sparse gauge network or in events with significant local rainfall. In this study, a method to incorporate rating curve uncertainty and the local rainfall-runoff dynamics into the predictions of a reach-scale flood inundation model is proposed. Discharge uncertainty bounds are generated by applying a non-parametric local weighted regression approach to stage-discharge measurements for two gauging stations, while measured rainfall downstream from these locations is cascaded into a hydrological model to quantify additional inflows along the main channel. A regional simplified-physics hydraulic model is then applied to combine these inputs and generate an ensemble of discharge and water elevation time series at the boundaries of a local-scale high complexity hydraulic model. Finally, the effect of these rainfall dynamics and uncertain boundary conditions are evaluated on the local-scale model. Improvements in model performance when incorporating these processes are quantified using observed

Diurnal Variation of Rainfall Associated with Tropical Depression in South China and its Relationship to Land-Sea Contrast and Topography

Directory of Open Access Journals (Sweden)

Yuchun Zhao

2013-12-01

Full Text Available Convective precipitation associated with tropical depression (TD is one primary type of post-flooding season rainfall in South China (SC. Observations of the Tropical Rainfall Measuring Mission (TRMM satellite have shown specific diurnal features of convective rainfall in South China, which is somewhat different from that in other seasons or regions of China. Convective precipitation is usually organized into a rainfall band along the southeastern coast of South China in the early morning hours. The rainfall band develops and intensifies quickly in the morning, then moves inland in the afternoon and, finally, diminishes at night. The daily convective rainfall along the coast is much more than that in the inland region, and heavy rainfall is often found along the coast. A long-duration heavy rainfall event associated with tropical depression “Fitow” during the period from 28 August to 6 September 2001, is selected in this study to explore the diurnal feature of convective rainfall and its formation mechanism. Modeling results of the 10-day heavy rainfall event are compared with both rain-gauge observation and satellite-retrieved rainfall. Total precipitation and its spatial distribution, as well as diurnal variations are reasonably simulated and agree well with observations. Further analysis reveals that the development and movement of convective precipitation is mainly related to the land and sea breezes. The anomalous height-latitudinal circulation in the morning-to-noon hours is completely reversed in the afternoon-to-late-evening hours, with the convective rainfall swinging back and forth, following its updraft branch. Sensitivity experiments show that the afternoon convective rainfall in the inland region of SC is caused by the diurnal variation of solar radiation forcing. The mountain range along the coast and the complex topography in the inland region of SC plays a critical role in the enhancement of diurnal convective rainfall

Uncertainty of Flood Forecasting Based on Radar Rainfall Data Assimilation

Directory of Open Access Journals (Sweden)

Xinchi Chen

2016-01-01

Full Text Available Precipitation is the core data input to hydrological forecasting. The uncertainty in precipitation forecast data can lead to poor performance of predictive hydrological models. Radar-based precipitation measurement offers advantages over ground-based measurement in the quantitative estimation of temporal and spatial aspects of precipitation, but errors inherent in this method will still act to reduce the performance. Using data from White Lotus River of Hubei Province, China, five methods were used to assimilate radar rainfall data transformed from the classified Z-R relationship, and the postassimilation data were compared with precipitation measured by rain gauges. The five sets of assimilated rainfall data were then used as input to the Xinanjiang model. The effect of precipitation data input error on runoff simulation was analyzed quantitatively by disturbing the input data using the Breeding of Growing Modes method. The results of practical application demonstrated that the statistical weight integration and variational assimilation methods were superior. The corresponding performance in flood hydrograph prediction was also better using the statistical weight integration and variational methods compared to the others. It was found that the errors of radar rainfall data disturbed by the Breeding of Growing Modes had a tendency to accumulate through the hydrological model.

Flood impacts in Keppel Bay, southern great barrier reef in the aftermath of cyclonic rainfall.

Directory of Open Access Journals (Sweden)

Alison M Jones

Full Text Available In December 2010, the highest recorded Queensland rainfall associated with Tropical Cyclone 'Tasha' caused flooding of the Fitzroy River in Queensland, Australia. A massive flood plume inundated coral reefs lying 12 km offshore of the Central Queensland coast near Yeppoon and caused 40-100% mortality to coral fringing many of the islands of Keppel Bay down to a depth of ∼8 m. The severity of coral mortality was influenced by the level of exposure to low salinity seawater as a result of the reef's distance from the flood plume and to a lesser extent, water depth and whether or not the reef faced the plume source. There was no evidence in this study of mortality resulting from pollutants derived from the nearby Fitzroy Catchment, at least in the short term, suggesting that during a major flood, the impact of low salinity on corals outweighs that of pollutants. Recovery of the reefs in Keppel Bay from the 2010/2011 Fitzroy River flood is likely to take 10-15 years based on historical recovery periods from a similar event in 1991; potentially impacting visitor numbers for tourism and recreational usage. In the meantime, activities like snorkeling, diving and coral viewing will be focused on the few shallow reefs that survived the flood, placing even further pressure on their recovery. Reef regeneration, restoration and rehabilitation are measures that may be needed to support tourism in the short term. However, predictions of a warming climate, lower rainfall and higher intensity summer rain events in the Central and Coastal regions of Australia over the next decade, combined with the current anthropogenic influences on water quality, are likely to slow regeneration with consequent impact on long-term reef resilience.

The Energy Budget of a Southwest Vortex With Heavy Rainfall over South China

Institute of Scientific and Technical Information of China (English)

FU Shenming; SUN Jianhua; ZHAO Sixiong; LI Wanli

2011-01-01

Energy budgets were analyzed to study the development of an eastward propagating southwest vortex (SWV) associated with heavy rainfall over southern China (11-13 June 2008). The results show that kinetic energy (KE) generation and a dvection were the most important KE sources, while friction and sub-grid processes were the main KE sinks. There was downward conversion from divergent to rotational wind KE consistent with the downward stretching of SWVs. The Coriolis force was important for the formation and maintenance of the SWV. Convergence was also an important factor for maintenance, as was vertical motion during the mature stage of the SWV and the formation stage of a newly formed vortex (vortex B). The conversion from available potential energy (APE) to KE of divergent wind can lead to strong convection. Vertical motion influenced APE by dynamical and thermal processes which had opposite effects.The variation of APE was related to the heavy rainfall and convection; in this case, vertical motion with direct thermal circulation was the most important way in which APE was released, while latent heat release and vertical temperature advection were important for APE generation.

The Energy Budget of a Southwest Vortex With Heavy Rainfall over South China

Institute of Scientific and Technical Information of China (English)

无

2011-01-01

Energy budgets were analyzed to study the development of an eastward propagating southwest vortex （SWV） associated with heavy rainfall over southern China（11-13 June 2008）.The results show that kinetic energy（KE） generation and advection were the most important KE sources,while friction and sub-grid processes were the main KE sinks.There was downward conversion from divergent to rotational wind KE consistent with the downward stretching of SWVs.The Coriolis force was important for the formation and maintenance of the SWV.Convergence was also an important factor for maintenance,as was vertical motion during the mature stage of the SWV and the formation stage of a newly formed vortex（vortex B）.The conversion from available potential energy（APE） to KE of divergent wind can lead to strong convection.Vertical motion influenced APE by dynamical and thermal processes which had opposite effects. The variation of APE was related to the heavy rainfall and convection;in this case,vertical motion with direct thermal circulation was the most important way in which APE was released,while latent heat release and vertical temperature advection were important for APE generation.

Early Detection of Baby-Rain-Cell Aloft in a Severe Storm and Risk Projection for Urban Flash Flood

Directory of Open Access Journals (Sweden)

Eiichi Nakakita

2017-01-01

Full Text Available In July 2008, five people were killed by a tragic flash flood caused by a local torrential heavy rainfall in a short time in Toga River. From this tragic accident, we realized that a system which can detect hazardous rain-cells in the earlier stage is strongly needed and would provide an additional 5 to 10 min for evacuation. By analyzing this event, we verified that a first radar echo aloft, by volume scan observation, is a practical and important sign for early warning of flash flood, and we named a first echo as a “baby-rain-cell” of Guerrilla-heavy rainfall. Also, we found a vertical vorticity criterion for identifying hazardous rain-cells and developed a heavy rainfall prediction system that has the important feature of not missing any hazardous rain-cell. Being able to detect heavy rainfall by 23.6 min on average before it reaches the ground, this system is implemented in XRAIN in the Kinki area. Additionally, to resolve the relationship between baby-rain-cell growth and vorticity behavior, we carried out an analysis of vorticity inside baby-rain-cells and verified that a pair of positive and negative vertical vortex tubes as well as an updraft between them existed in a rain-cell in the early stage.

Analyses of flooding tolerance of soybean varieties at emergence and varietal differences in their proteomes.

Science.gov (United States)

Nanjo, Yohei; Jang, Hee-Young; Kim, Hong-Sig; Hiraga, Susumu; Woo, Sun-Hee; Komatsu, Setsuko

2014-10-01

Flooding of fields due to heavy and/or continuous rainfall influences soybean production. To identify soybean varieties with flooding tolerance at the seedling emergence stage, 128 soybean varieties were evaluated using a flooding tolerance index, which is based on plant survival rates, the lack of apparent damage and lateral root development, and post-flooding radicle elongation rate. The soybean varieties were ranked according to their flooding tolerance index, and it was found that the tolerance levels of soybean varieties exhibit a continuum of differences between varieties. Subsequently, tolerant, moderately tolerant and sensitive varieties were selected and subjected to comparative proteomic analysis to clarify the tolerance mechanism. Proteomic analysis of the radicles, combined with correlation analysis, showed that the ratios of RNA binding/processing related proteins and flooding stress indicator proteins were significantly correlated with flooding tolerance index. The RNA binding/processing related proteins were positively correlated in untreated soybeans, whereas flooding stress indicator proteins were negatively correlated in flooded soybeans. These results suggest that flooding tolerance is regulated by mechanisms through multiple factors and is associated with abundance levels of the identified proteins. Copyright © 2014 Elsevier Ltd. All rights reserved.

On the nature of rainfall in dry climate: Space-time patterns of convective rain cells over the Dead Sea region and their relations with synoptic state and flash flood generation

Science.gov (United States)

Belachsen, Idit; Marra, Francesco; Peleg, Nadav; Morin, Efrat

2017-04-01

Space-time patterns of rainfall are important climatic characteristics that influence runoff generation and flash flood magnitude. Their derivation requires high-resolution measurements to adequately represent the rainfall distribution, and is best provided by remote sensing tools. This need is further emphasized in dry climate regions, where rainfall is scarce and, often, local and highly variable. Our research is focused on understanding the nature of rainfall events in the dry Dead Sea region (Eastern Mediterranean) by identifying and characterizing the spatial structure and the dynamics of convective storm cores (known as rain cells). To do so, we take advantage of 25 years of corrected and gauge-adjusted weather radar data. A statistical analysis of convective rain-cells spatial and temporal characteristics was performed with respect to synoptic pattern, geographical location, and flash flood generation. Rain cells were extracted from radar data using a cell segmentation method and a tracking algorithm and were divided into rain events. A total of 10,500 rain cells, 2650 cell tracks and 424 rain events were elicited. Rain cell properties, such as mean areal and maximal rain intensity, area, life span, direction and speed, were derived. Rain events were clustered, according to several ERA-Interim atmospheric parameters, and associated with three main synoptic patterns: Cyprus Low, Low to the East of the study region and Active Red Sea Trough. The first two originate from the Mediterranean Sea, while the third is an extension of the African monsoon. On average, the convective rain cells in the region are 90 km2 in size, moving from West to East in 13 ms-1 and living 18 minutes. Several significant differences between rain cells of the various synoptic types were observed. In particular, Active Red Sea Trough rain cells are characterized by higher rain intensities and lower speeds, suggesting a higher flooding potential for small catchments. The north

Modeling rainfall infiltration on hillslopes using Flux-concentration relation and time compression approximation

Science.gov (United States)

Wang, Jie; Chen, Li; Yu, Zhongbo

2018-02-01

Rainfall infiltration on hillslopes is an important issue in hydrology, which is related to many environmental problems, such as flood, soil erosion, and nutrient and contaminant transport. This study aimed to improve the quantification of infiltration on hillslopes under both steady and unsteady rainfalls. Starting from Darcy's law, an analytical integral infiltrability equation was derived for hillslope infiltration by use of the flux-concentration relation. Based on this equation, a simple scaling relation linking the infiltration times on hillslopes and horizontal planes was obtained which is applicable for both small and large times and can be used to simplify the solution procedure of hillslope infiltration. The infiltrability equation also improved the estimation of ponding time for infiltration under rainfall conditions. For infiltration after ponding, the time compression approximation (TCA) was applied together with the infiltrability equation. To improve the computational efficiency, the analytical integral infiltrability equation was approximated with a two-term power-like function by nonlinear regression. Procedures of applying this approach to both steady and unsteady rainfall conditions were proposed. To evaluate the performance of the new approach, it was compared with the Green-Ampt model for sloping surfaces by Chen and Young (2006) and Richards' equation. The proposed model outperformed the sloping Green-Ampt, and both ponding time and infiltration predictions agreed well with the solutions of Richards' equation for various soil textures, slope angles, initial water contents, and rainfall intensities for both steady and unsteady rainfalls.

Continuous Sub-daily Rainfall Simulation for Regional Flood Risk Assessment - Modelling of Spatio-temporal Correlation Structure of Extreme Precipitation in the Austrian Alps

Science.gov (United States)

Salinas, J. L.; Nester, T.; Komma, J.; Bloeschl, G.

2017-12-01

Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of observed rainfall characteristics, such as regional intensity-duration-frequency curves, and spatial and temporal correlations is necessary to adequately model the magnitude and frequency of the flood peaks, by reproducing antecedent soil moisture conditions before extreme rainfall events, and joint probability of flood waves at confluences. In this work, a modification of the model presented by Bardossy and Platte (1992), where precipitation is first modeled on a station basis as a multivariate autoregressive model (mAr) in a Normal space. The spatial and temporal correlation structures are imposed in the Normal space, allowing for a different temporal autocorrelation parameter for each station, and simultaneously ensuring the positive-definiteness of the correlation matrix of the mAr errors. The Normal rainfall is then transformed to a Gamma-distributed space, with parameters varying monthly according to a sinusoidal function, in order to adapt to the observed rainfall seasonality. One of the main differences with the original model is the simulation time-step, reduced from 24h to 6h. Due to a larger availability of daily rainfall data, as opposite to sub-daily (e.g. hourly), the parameters of the Gamma distributions are calibrated to reproduce simultaneously a series of daily rainfall characteristics (mean daily rainfall, standard deviations of daily rainfall, and 24h intensity-duration-frequency [IDF] curves), as well as other aggregated rainfall measures (mean annual rainfall, and monthly rainfall). The calibration of the spatial and temporal correlation parameters is performed in a way that the catchment-averaged IDF curves aggregated at different temporal scales fit the measured ones. The rainfall model is used to generate 10.000 years of synthetic

Comparison of radar and numerical weather model rainfall forecasts in the perspective of urban flood prediction

DEFF Research Database (Denmark)

Lovring, Maite Monica; Löwe, Roland; Courdent, Vianney Augustin Thomas

An early flood warning system has been developed for urban catchments and is currently running in online operation in Copenhagen. The system is highly dependent on the quality of rainfall forecast inputs. An investigation of precipitation inputs from Radar Nowcast (RN), Numerical Weather Prediction...

Impact of Assimilation on Heavy Rainfall Simulations Using WRF Model: Sensitivity of Assimilation Results to Background Error Statistics

Science.gov (United States)

Rakesh, V.; Kantharao, B.

2017-03-01

Data assimilation is considered as one of the effective tools for improving forecast skill of mesoscale models. However, for optimum utilization and effective assimilation of observations, many factors need to be taken into account while designing data assimilation methodology. One of the critical components that determines the amount and propagation observation information into the analysis, is model background error statistics (BES). The objective of this study is to quantify how BES in data assimilation impacts on simulation of heavy rainfall events over a southern state in India, Karnataka. Simulations of 40 heavy rainfall events were carried out using Weather Research and Forecasting Model with and without data assimilation. The assimilation experiments were conducted using global and regional BES while the experiment with no assimilation was used as the baseline for assessing the impact of data assimilation. The simulated rainfall is verified against high-resolution rain-gage observations over Karnataka. Statistical evaluation using several accuracy and skill measures shows that data assimilation has improved the heavy rainfall simulation. Our results showed that the experiment using regional BES outperformed the one which used global BES. Critical thermo-dynamic variables conducive for heavy rainfall like convective available potential energy simulated using regional BES is more realistic compared to global BES. It is pointed out that these results have important practical implications in design of forecast platforms while decision-making during extreme weather events

Analysis and modelling of spatio-temporal properties of daily rainfall over the Danube basin

Science.gov (United States)

Serinaldi, F.; Kilsby, C. G.

2012-04-01

Central and Eastern Europe are prone to severe floods due to heavy rainfall that cause societal and economic damages, ranging from agriculture to water resources, from the insurance/reinsurance sector to the energy industry. To improve the flood risk analysis, a better characterisation and modelling of the rainfall patterns over this area, which involves the Danube river watershed, is strategically important. In this study, we analyse the spatio-temporal properties of a large data set of daily rainfall time series from 15 countries in the Central Eastern Europe through different lagged and non-lagged indices of associations that quantify both the overall dependence and extreme dependence of pairwise observations. We also show that these measures are linked to each other and can be written in a unique and coherent notation within the copula framework. Moreover, the lagged version of these measures allows exploring some important spatio-temporal properties of the rainfall fields. The exploratory analysis is complemented by the preliminary results of a spatio-temporal rainfall simulation performed via a compound model based upon the Generalized Additive Models for Location, Scale and Shape (GAMLSS) and meta-elliptical multivariate distributions.

Flood Risk Management in Iowa through an Integrated Flood Information System

Science.gov (United States)

Demir, Ibrahim; Krajewski, Witold

2013-04-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, flood-related data, information and interactive visualizations for communities in Iowa. The key element of the system's architecture is the notion of community. Locations of the communities, those near streams and rivers, define basin boundaries. The IFIS provides community-centric watershed and river characteristics, weather (rainfall) conditions, and streamflow data and visualization tools. Interactive interfaces allow access to inundation maps for different stage and return period values, and flooding scenarios with contributions from multiple rivers. Real-time and historical data of water levels, gauge heights, and rainfall conditions are available in the IFIS by streaming data from automated IFC bridge sensors, USGS stream gauges, NEXRAD radars, and NWS forecasts. Simple 2D and 3D interactive visualizations in the IFIS make the data more understandable to general public. Users are able to filter data sources for their communities and selected rivers. The data and information on IFIS is also accessible through web services and mobile applications. The IFIS is optimized for various browsers and screen sizes to provide access through multiple platforms including tablets and mobile devices. The IFIS includes a rainfall-runoff forecast model to provide a five-day flood risk estimate for around 1100 communities in Iowa. Multiple view modes in the IFIS accommodate different user types from general public to researchers and decision makers by providing different level of tools and details. River view mode allows users to visualize data from multiple IFC bridge sensors and USGS stream gauges to follow flooding condition along a river. The IFIS will help communities make better-informed decisions on the occurrence of floods, and will alert

Assessing future climatic changes of rainfall extremes at small spatio-temporal scales

DEFF Research Database (Denmark)

Gregersen, Ida Bülow; Sørup, Hjalte Jomo Danielsen; Madsen, Henrik

2013-01-01

Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type...... in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated...... from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases...

Inferring the flood frequency distribution for an ungauged basin using a spatially distributed rainfall-runoff model

Directory of Open Access Journals (Sweden)

G. Moretti

2008-08-01

Full Text Available The estimation of the peak river flow for ungauged river sections is a topical issue in applied hydrology. Spatially distributed rainfall-runoff models can be a useful tool to this end, since they are potentially able to simulate the river flow at any location of the watershed drainage network. However, it is not fully clear to what extent these models can provide reliable simulations over a wide range of spatial scales. This issue is investigated here by applying a spatially distributed, continuous simulation rainfall-runoff model to infer the flood frequency distribution of the Riarbero River. This is an ungauged mountain creek located in northern Italy, whose drainage area is 17 km². The hydrological model is first calibrated by using a 1-year record of hourly meteorological data and river flows observed at the outlet of the 1294 km² wide Secchia River basin, of which the Riarbero is a tributary. The model is then validated by performing a 100-year long simulation of synthetic river flow data, which allowed us to compare the simulated and observed flood frequency distributions at the Secchia River outlet and the internal cross river section of Cavola Bridge, where the basin area is 337 km². Finally, another simulation of hourly river flows was performed by referring to the outlet of the Riarbero River, therefore allowing us to estimate the related flood frequency distribution. The results were validated by using estimates of peak river flow obtained by applying hydrological similarity principles and a regional method. The results show that the flood flow estimated through the application of the distributed model is consistent with the estimate provided by the regional procedure as well as the behaviors of the river banks. Conversely, the method based on hydrological similarity delivers an estimate that seems to be not as reliable. The analysis highlights interesting perspectives for the application of

Gastrointestinal illness among triathletes swimming in non-polluted versus polluted seawater affected by heavy rainfall, Denmark, 2010-2011.

Directory of Open Access Journals (Sweden)

Nina Majlund Harder-Lauridsen

Full Text Available Recent years have seen an increase in the frequency of extreme rainfall and subsequent flooding across the world. Climate change models predict that such flooding will become more common, triggering sewer overflows, potentially with increased risks to human health. In August 2010, a triathlon sports competition was held in Copenhagen, Denmark, shortly after an extreme rainfall. The authors took advantage of this event to investigate disease risks in two comparable cohorts of physically fit, long distance swimmers competing in the sea next to a large urban area. An established model of bacterial concentration in the water was used to examine the level of pollution in a spatio-temporal manner. Symptoms and exposures among athletes were examined with a questionnaire using a retrospective cohort design and the questionnaire investigation was repeated after a triathlon competition held in non-polluted seawater in 2011. Diagnostic information was collected from microbiological laboratories. The results showed that the 3.8 kilometer open water swimming competition coincided with the peak of post-flooding bacterial contamination in 2010, with average concentrations of 1.5x10(4 E. coli per 100 ml water. The attack rate of disease among 838 swimmers in 2010 was 42% compared to 8% among 931 swimmers in the 2011 competition (relative risk (RR 5.0; 95% CI: 4.0-6.39. In 2010, illness was associated with having unintentionally swallowed contaminated water (RR 2.5; 95% CI: 1.8-3.4; and the risk increased with the number of mouthfuls of water swallowed. Confirmed aetiologies of infection included Campylobacter, Giardia lamblia and diarrhoeagenic E. coli. The study demonstrated a considerable risk of illness from water intake when swimming in contaminated seawater in 2010, and a small but measureable risk from non-polluted water in 2011. This suggests a significant risk of disease in people ingesting small amounts of flood water following extreme rainfall in

Gastrointestinal illness among triathletes swimming in non-polluted versus polluted seawater affected by heavy rainfall, Denmark, 2010-2011.

Science.gov (United States)

Harder-Lauridsen, Nina Majlund; Kuhn, Katrin Gaardbo; Erichsen, Anders Christian; Mølbak, Kåre; Ethelberg, Steen

2013-01-01

Recent years have seen an increase in the frequency of extreme rainfall and subsequent flooding across the world. Climate change models predict that such flooding will become more common, triggering sewer overflows, potentially with increased risks to human health. In August 2010, a triathlon sports competition was held in Copenhagen, Denmark, shortly after an extreme rainfall. The authors took advantage of this event to investigate disease risks in two comparable cohorts of physically fit, long distance swimmers competing in the sea next to a large urban area. An established model of bacterial concentration in the water was used to examine the level of pollution in a spatio-temporal manner. Symptoms and exposures among athletes were examined with a questionnaire using a retrospective cohort design and the questionnaire investigation was repeated after a triathlon competition held in non-polluted seawater in 2011. Diagnostic information was collected from microbiological laboratories. The results showed that the 3.8 kilometer open water swimming competition coincided with the peak of post-flooding bacterial contamination in 2010, with average concentrations of 1.5x10(4) E. coli per 100 ml water. The attack rate of disease among 838 swimmers in 2010 was 42% compared to 8% among 931 swimmers in the 2011 competition (relative risk (RR) 5.0; 95% CI: 4.0-6.39). In 2010, illness was associated with having unintentionally swallowed contaminated water (RR 2.5; 95% CI: 1.8-3.4); and the risk increased with the number of mouthfuls of water swallowed. Confirmed aetiologies of infection included Campylobacter, Giardia lamblia and diarrhoeagenic E. coli. The study demonstrated a considerable risk of illness from water intake when swimming in contaminated seawater in 2010, and a small but measureable risk from non-polluted water in 2011. This suggests a significant risk of disease in people ingesting small amounts of flood water following extreme rainfall in urban areas.

The influence of the net rainfall mixed Curve Number – Green Ampt procedure in flood hazard mapping: a case study in Central Italy

Directory of Open Access Journals (Sweden)

Andrea Petroselli

2013-09-01

Full Text Available A net rainfall estimation procedure, referred to as Curve-Number For Green-Ampt (CN4GA, combining the Soil Conservation Service - Curve Number (SCS-CN method and the Green and Ampt (GA infiltration equation was recently developed, aiming to distribute at subdaily time resolution the information provided by the SCS-CN method. The initial abstraction and the total volume of rainfall provided by the SCS-CN method are used to identify the ponding time and to quantify the hydraulic conductivity parameter of the GA equation, whereas the GA infiltration model distributes the total volume of the rainfall excess provided by the SCS-CN method. In this study we evaluate the proposed procedure with reference to a real case comparing the flood mapping obtained applying the event-based approach for two different net rainfall scenarios: the proposed CN4GA and the common SCS-CN. Results underline that the net rainfall estimation step can affect the final flood mapping result.

Analysis of rainfall related to landslide activity during January-February 2003, South-Eastern Sector of Italy

International Nuclear Information System (INIS)

Fiorillo, Francesco

2004-01-01

On 24-26 th January 2003 a heavy storm struck the South-Eastern sector of the Italian peninsula, causing severe damage to agriculture and roads of the Abruzzo, Molise, Campania and Puglia regions. The areas involved are characterised by hilly morphology, up to 900m a.s.l. inland, and are made up of mainly argillaceous sequences of Flysch and fore deep deposits of the Apennine chain. Thousands of landslides occurred along hilly areas, generally characterized by shallow movements which ceased after some meters; deep-seated landslides also occurred and with reactivations of previous instabilities. Flood phenomena occurred in several places, mainly along the high-order drainage lines. The area is known to fall within a Mediterranean climate, with a long, hot 'dry season' between June and September and a temperate-wet season between October and May. Thus, the 24-26 January 2003 storm occurred in the mid-wet season, during winter; moreover, neither solid precipitation nor snow melt phenomena occurred. The first available hydrological data show that the 24-26 th January 2003 storm was the maximum in the historical series of some rain gauges, considering 24-hour and 2-day cumulative rainfall; return time reaches values exceeding 70 years, with usual distribution function (Gumbel, GEV, Lognormal). The storm occurred after a wet period, characterized by previous storms, which most likely caused the reaching of field capacity of the soil. All shallow landslides occurred during or immediately after this storm and, thus, were most likely caused by positive pore pressure development. At least 10 continuous rainy days after the storm (until 6th February 2003) were recorded, though they were characterized by low rainfall; it is important to highlight that it was mainly during these rainy days that some deep seated landslides were reactivated. On the bases of historical hydrological data and landslide activity, this study analyses the possible relation between rainfall and

Texas floods of 1940

Science.gov (United States)

Breeding, Seth D.

1948-01-01

Floods occurred in Texas during, June, July, and November 1940 that exceeded known stages on many small streams and at a few places on the larger streams. Stages at several stream-gaging stations exceeded the maximum known at those places since the collection of daily records began. A storm, haying its axis generally on a north-south line from Cameron to Victoria and extending across the Brazos, Colorado, Lavaca, and Guadalupe River Basins, caused heavy rainfall over a large part of south-central Texas. The maximum recorded rain of 22.7 inches for the 2-day period June 29-30 occurred at Engle. Of this amount, 17.5 inches fell in the 12-hour period between 8 p.m. June 29, and 8 a.m. June 30. Light rains fell at a number of places on June 28, and additional light rains fell at many places within the area from July 1 to 4. During the period June 28 to July 4 more than 20 inches of rain fell over an area of 300 square miles, more than 15 inches over 1,920 square miles, and more than 10 inches over 5,100 square miles. The average annual rainfall for the area experiencing the heaviest rainfall during this storm is about 35 inches. Farming is largely confined to the fertile flood plains in much of the area subjected to the record-breaking floods in June and July. Therefore these floods, coming at the height of the growing season, caused severe losses to crops. Much damage was done also to highways and railways. The city of Hallettsville suffered the greatest damage of any urban area. The Lavaca River at that place reached a stage 8 feet higher than ever known before, drowned several people, destroyed many homes, and submerged almost the entire business district. The maximum discharge there was 93,100 second-feet from a drainage area of 101 square miles. Dry Creek near Smithville produced a maximum discharge of 1,879 second-feet from an area of 1.48 square miles and a runoff of 11.3 inches in a 2-day period from a rainfall of 19.5 inches. The area in the Colorado River

Projected changes of rainfall event characteristics for the Czech Republic

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Svoboda Vojtěch

2016-12-01

Full Text Available Projected changes of warm season (May–September rainfall events in an ensemble of 30 regional climate model (RCM simulations are assessed for the Czech Republic. Individual rainfall events are identified using the concept of minimum inter-event time and only heavy events are considered. The changes of rainfall event characteristics are evaluated between the control (1981–2000 and two scenario (2020–2049 and 2070–2099 periods. Despite a consistent decrease in the number of heavy rainfall events, there is a large uncertainty in projected changes in seasonal precipitation total due to heavy events. Most considered characteristics (rainfall event depth, mean rainfall rate, maximum 60-min rainfall intensity and indicators of rainfall event erosivity are projected to increase and larger increases appear for more extreme values. Only rainfall event duration slightly decreases in the more distant scenario period according to the RCM simulations. As a consequence, the number of less extreme heavy rainfall events as well as the number of long events decreases in majority of the RCM simulations. Changes in most event characteristics (and especially in characteristics related to the rainfall intensity depend on changes in radiative forcing and temperature for the future periods. Only changes in the number of events and seasonal total due to heavy events depend significantly on altitude.

Integration of rainfall/runoff and geomorphological analyses flood hazard in small catchments: case studies from the southern Apennines (Italy)

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Palumbo, Manuela; Ascione, Alessandra; Santangelo, Nicoletta; Santo, Antonio

2017-04-01

We present the first results of an analysis of flood hazard in ungauged mountain catchments that are associated with intensely urbanized alluvial fans. Assessment of hydrological hazard has been based on the integration of rainfall/runoff modelling of drainage basins with geomorphological analysis and mapping. Some small and steep, ungauged mountain catchments located in various areas of the southern Apennines, in southern Italy, have been chosen as test sites. In the last centuries, the selected basins have been subject to heavy and intense precipitation events, which have caused flash floods with serious damages in the correlated alluvial fan areas. Available spatial information (regional technical maps, DEMs, land use maps, geological/lithological maps, orthophotos) and an automated GIS-based procedure (ArcGis tools and ArcHydro tools) have been used to extract morphological, hydrological and hydraulic parameters. Such parameters have been used to run the HEC (Hydrologic Engineering Center of the US Army Corps of Engineers) software (GeoHMS, GeoRAS, HMS and RAS) based on rainfall-runoff models, which have allowed the hydrological and hydraulic simulations. As the floods occurred in the studied catchments have been debris flows dominated, the solid load simulation has been also performed. In order to validate the simulations, we have compared results of the modelling with the effects produced by past floods. Such effects have been quantified through estimations of both the sediment volumes within each catchment that have the potential to be mobilised (pre-event) during a sediment transfer event, and the volume of sediments delivered by the debris flows at basins' outlets (post-event). The post-event sediment volume has been quantified through post-event surveys and Lidar data. Evaluation of the pre-event sediment volumes in single catchments has been based on mapping of sediment storages that may constitute source zones of bed load transport and debris flows. For

ISSUES CONCERNING OCCURRENCE OF FLOODS ON THE VEDEA RIVER

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TOMA FLORENTINA-MARIANA

2011-03-01

Full Text Available Aspects of flood occurrence on the Vedea River. This study addresses several aspects of floods on the Vedea River, located in the Central Romanian Plain, located between Olt and Argeş rivers. Data recorded in the most important hydrological stations (Buzeşti, Văleni, Alexandria along the Vedea River were used, for a period of 40 years (1970-2009. Flood generating conditions, their typology and parameters were analyzed. Cavis software developed by specialists from INHGA Bucharest was employed, in order to draft the flood hydrographs and calculate the floods parameters. Also, we calculated the multi-annual and seasonal frequencies of flood occurrence. There are two main conclusions emerging from specific analysis. First, the most floods occur in late winter and early spring while the least are specific to autumn season. Second conclusion is that the highest flash floods recorded along the Vedea River are associated to heavy rainfall periods and they occurred in late spring and early summer.

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

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Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

Exploring public databases to characterize urban flood risks in Amsterdam

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Gaitan, Santiago; ten Veldhuis, Marie-claire; van de Giesen, Nick

2015-04-01

Cities worldwide are challenged by increasing urban flood risks. Precise and realistic measures are required to decide upon investment to reduce their impacts. Obvious flooding factors affecting flood risk include sewer systems performance and urban topography. However, currently implemented sewer and topographic models do not provide realistic predictions of local flooding occurrence during heavy rain events. Assessing other factors such as spatially distributed rainfall and socioeconomic characteristics may help to explain probability and impacts of urban flooding. Several public databases were analyzed: complaints about flooding made by citizens, rainfall depths (15 min and 100 Ha spatio-temporal resolution), grids describing number of inhabitants, income, and housing price (1Ha and 25Ha resolution); and buildings age. Data analysis was done using Python and GIS programming, and included spatial indexing of data, cluster analysis, and multivariate regression on the complaints. Complaints were used as a proxy to characterize flooding impacts. The cluster analysis, run for all the variables except the complaints, grouped part of the grid-cells of central Amsterdam into a highly differentiated group, covering 10% of the analyzed area, and accounting for 25% of registered complaints. The configuration of the analyzed variables in central Amsterdam coincides with a high complaint count. Remaining complaints were evenly dispersed along other groups. An adjusted R2 of 0.38 in the multivariate regression suggests that explaining power can improve if additional variables are considered. While rainfall intensity explained 4% of the incidence of complaints, population density and building age significantly explained around 20% each. Data mining of public databases proved to be a valuable tool to identify factors explaining variability in occurrence of urban pluvial flooding, though additional variables must be considered to fully explain flood risk variability.

Landslides, floods and sinkholes in a karst environment: the 1-6 September 2014 Gargano event, southern Italy

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Martinotti, Maria Elena; Pisano, Luca; Marchesini, Ivan; Rossi, Mauro; Peruccacci, Silvia; Brunetti, Maria Teresa; Melillo, Massimo; Amoruso, Giuseppe; Loiacono, Pierluigi; Vennari, Carmela; Vessia, Giovanna; Trabace, Maria; Parise, Mario; Guzzetti, Fausto

2017-03-01

In karst environments, heavy rainfall is known to cause multiple geohydrological hazards, including inundations, flash floods, landslides and sinkholes. We studied a period of intense rainfall from 1 to 6 September 2014 in the Gargano Promontory, a karst area in Puglia, southern Italy. In the period, a sequence of torrential rainfall events caused severe damage and claimed two fatalities. The amount and accuracy of the geographical and temporal information varied for the different hazards. The temporal information was most accurate for the inundation caused by a major river, less accurate for flash floods caused by minor torrents and even less accurate for landslides. For sinkholes, only generic information on the period of occurrence of the failures was available. Our analysis revealed that in the promontory, rainfall-driven hazards occurred in response to extreme meteorological conditions and that the karst landscape responded to the torrential rainfall with a threshold behaviour. We exploited the rainfall and the landslide information to design the new ensemble-non-exceedance probability (E-NEP) algorithm for the quantitative evaluation of the possible occurrence of rainfall-induced landslides and of related geohydrological hazards. The ensemble of the metrics produced by the E-NEP algorithm provided better diagnostics than the single metrics often used for landslide forecasting, including rainfall duration, cumulated rainfall and rainfall intensity. We expect that the E-NEP algorithm will be useful for landslide early warning in karst areas and in other similar environments. We acknowledge that further tests are needed to evaluate the algorithm in different meteorological, geological and physiographical settings.

Iowa Flood Information System

Science.gov (United States)

Demir, I.; Krajewski, W. F.; Goska, R.; Mantilla, R.; Weber, L. J.; Young, N.

2011-12-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, flood-related data, information and interactive visualizations for communities in Iowa. The key element of the system's architecture is the notion of community. Locations of the communities, those near streams and rivers, define basin boundaries. The IFIS provides community-centric watershed and river characteristics, weather (rainfall) conditions, and streamflow data and visualization tools. Interactive interfaces allow access to inundation maps for different stage and return period values, and flooding scenarios with contributions from multiple rivers. Real-time and historical data of water levels, gauge heights, and rainfall conditions are available in the IFIS by streaming data from automated IFC bridge sensors, USGS stream gauges, NEXRAD radars, and NWS forecasts. Simple 2D and 3D interactive visualizations in the IFIS make the data more understandable to general public. Users are able to filter data sources for their communities and selected rivers. The data and information on IFIS is also accessible through web services and mobile applications. The IFIS is optimized for various browsers and screen sizes to provide access through multiple platforms including tablets and mobile devices. The IFIS includes a rainfall-runoff forecast model to provide a five-day flood risk estimate for around 500 communities in Iowa. Multiple view modes in the IFIS accommodate different user types from general public to researchers and decision makers by providing different level of tools and details. River view mode allows users to visualize data from multiple IFC bridge sensors and USGS stream gauges to follow flooding condition along a river. The IFIS will help communities make better-informed decisions on the occurrence of floods, and will alert communities

Extreme value analysis of rainfall data for Kalpakkam

International Nuclear Information System (INIS)

Sharma, Pramod Kumar; John Arul, A.; Ramkrishnan, M.; Bhuvana, V.

2016-01-01

Flood hazard evaluation is an important safety study for a Nuclear Power Plant. In the present study flood hazard at PFBR site due to rainfall is evaluated. Hazard estimation is a statistical procedure by which rainfall intensity versus occurrence frequency is estimated from historical records of rainfall data and extrapolated with asymptotic extreme value distribution. Rainfall data needed for flood hazard assessment is daily annual maximum rainfall (24 hrs data). The observed data points have been fitted using Gumbel, power law, and exponential distribution and return period has been estimated. The predicted 100 yrs return period rainfall for Kalpakkam ranges from 240 mm to 365 mm in a day and 1000 yrs return period rainfall ranges from 320 mm to 790 min in a day. To study the stationarity of rainfall data a moving window estimate of the parameters (exponential distribution) have also been performed. (author)

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System) for Sicily

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Brigandì, Giuseppina; Tito Aronica, Giuseppe; Bonaccorso, Brunella; Gueli, Roberto; Basile, Giuseppe

2017-09-01

The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System), specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF). The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA) model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall-streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall-runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall-runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015) have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002-2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall threshold models to produce

Flood Simulation Using WMS Model in Small Watershed after Strong Earthquake -A Case Study of Longxihe Watershed, Sichuan province, China

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Guo, B.

2017-12-01

Mountain watershed in Western China is prone to flash floods. The Wenchuan earthquake on May 12, 2008 led to the destruction of surface, and frequent landslides and debris flow, which further exacerbated the flash flood hazards. Two giant torrent and debris flows occurred due to heavy rainfall after the earthquake, one was on August 13 2010, and the other on August 18 2010. Flash floods reduction and risk assessment are the key issues in post-disaster reconstruction. Hydrological prediction models are important and cost-efficient mitigation tools being widely applied. In this paper, hydrological observations and simulation using remote sensing data and the WMS model are carried out in the typical flood-hit area, Longxihe watershed, Dujiangyan City, Sichuan Province, China. The hydrological response of rainfall runoff is discussed. The results show that: the WMS HEC-1 model can well simulate the runoff process of small watershed in mountainous area. This methodology can be used in other earthquake-affected areas for risk assessment and to predict the magnitude of flash floods. Key Words: Rainfall-runoff modeling. Remote Sensing. Earthquake. WMS.

Flood risk assessment in France: comparison of extreme flood estimation methods (EXTRAFLO project, Task 7)

Science.gov (United States)

Garavaglia, F.; Paquet, E.; Lang, M.; Renard, B.; Arnaud, P.; Aubert, Y.; Carre, J.

2013-12-01

In flood risk assessment the methods can be divided in two families: deterministic methods and probabilistic methods. In the French hydrologic community the probabilistic methods are historically preferred to the deterministic ones. Presently a French research project named EXTRAFLO (RiskNat Program of the French National Research Agency, https://extraflo.cemagref.fr) deals with the design values for extreme rainfall and floods. The object of this project is to carry out a comparison of the main methods used in France for estimating extreme values of rainfall and floods, to obtain a better grasp of their respective fields of application. In this framework we present the results of Task 7 of EXTRAFLO project. Focusing on French watersheds, we compare the main extreme flood estimation methods used in French background: (i) standard flood frequency analysis (Gumbel and GEV distribution), (ii) regional flood frequency analysis (regional Gumbel and GEV distribution), (iii) local and regional flood frequency analysis improved by historical information (Naulet et al., 2005), (iv) simplify probabilistic method based on rainfall information (i.e. Gradex method (CFGB, 1994), Agregee method (Margoum, 1992) and Speed method (Cayla, 1995)), (v) flood frequency analysis by continuous simulation approach and based on rainfall information (i.e. Schadex method (Paquet et al., 2013, Garavaglia et al., 2010), Shyreg method (Lavabre et al., 2003)) and (vi) multifractal approach. The main result of this comparative study is that probabilistic methods based on additional information (i.e. regional, historical and rainfall information) provide better estimations than the standard flood frequency analysis. Another interesting result is that, the differences between the various extreme flood quantile estimations of compared methods increase with return period, staying relatively moderate up to 100-years return levels. Results and discussions are here illustrated throughout with the example

Predicting extreme rainfall events over Jeddah, Saudi Arabia: Impact of data assimilation with conventional and satellite observations

KAUST Repository

Viswanadhapalli, Yesubabu

2015-08-20

The impact of variational data assimilation for predicting two heavy rainfall events that caused devastating floods in Jeddah, Saudi Arabia is studied using the Weather Research and Forecasting (WRF) model. On 25 November 2009 and 26 January 2011, the city was deluged with more than double the annual rainfall amount caused by convective storms. We used a high resolution, two-way nested domain WRF model to simulate the two rainfall episodes. Simulations include control runs initialized with National Center for Environmental Prediction (NCEP) Global Forecasting System (GFS) data and 3-Dimensional Variational (3DVAR) data assimilation experiments conducted by assimilating NCEP prepbufr and radiance observations. Observations from Automated Weather Stations (AWS), synoptic charts, radar reflectivity and satellite pictures from the Presidency of Meteorology and Environment (PME), Jeddah, Saudi Arabia are used to assess the forecasting results. To evaluate the impact of the different assimilated observational datasets on the simulation of the major flooding event of 2009, we conducted 3DVAR experiments assimilating individual sources and a combination of all data sets. Results suggest that while the control run had a tendency to predict the storm earlier than observed, the assimilation of profile observations greatly improved the model\\'s thermodynamic structure and lead to better representation of simulated rainfall both in timing and amount. The experiment with assimilation of all available observations compared best with observed rainfall in terms of timing of the storm and rainfall distribution, demonstrating the importance of assimilating different types of observations. Retrospective experiments with and without data assimilation, for three different model lead times (48, 72 and 96-h), were performed to examine the skill of WRF model to predict the heavy rainfall events. Quantitative rainfall analysis of these simulations suggests that 48-h lead time runs with

Study of atmospheric condition during the heavy rain event in Bojonegoro using weather research and forecasting (WRF) model: case study 9 February 2017

Science.gov (United States)

Saragih, I. J. A.; Meygatama, A. G.; Sugihartati, F. M.; Sidauruk, M.; Mulsandi, A.

2018-03-01

During 2016, there are frequent heavy rains in the Bojonegoro region, one of which is rain on 9 February 2016. The occurrence of heavy rainfall can cause the floods that inundate the settlements, rice fields, roads, and public facilities. This makes it important to analyze the atmospheric conditions during the heavy rainfall events in Bojonegoro. One of the analytical methods that can be used is using WRF-Advanced Research WRF (WRF-ARW) model. This study was conducted by comparing the rain analysis from WRF-ARW model with the Himawari-8 satellite imagery. The data used are Final Analysis (FNL) data for the WRF-ARW model and infrared (IR) channel for Himawari-8 satellite imagery. The data are processed into the time-series images and then analyzed descriptively. The meteorological parameters selected to be analyzed are relative humidity, vortices, divergences, air stability index, and precipitation. These parameters are expected to indicate the existence of a convective activity in Bojonegoro during the heavy rainfall event. The Himawari-8 satellite imagery shows that there is a cluster of convective clouds in Bojonegoro during the heavy rainfall event. The lowest value of the cloud top temperature indicates that the cluster of convective clouds is a cluster of Cumulonimbus cloud (CB).

Development of Integrated Flood Analysis System for Improving Flood Mitigation Capabilities in Korea

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Moon, Young-Il; Kim, Jong-suk

2016-04-01

Recently, the needs of people are growing for a more safety life and secure homeland from unexpected natural disasters. Flood damages have been recorded every year and those damages are greater than the annual average of 2 trillion won since 2000 in Korea. It has been increased in casualties and property damages due to flooding caused by hydrometeorlogical extremes according to climate change. Although the importance of flooding situation is emerging rapidly, studies related to development of integrated management system for reducing floods are insufficient in Korea. In addition, it is difficult to effectively reduce floods without developing integrated operation system taking into account of sewage pipe network configuration with the river level. Since the floods result in increasing damages to infrastructure, as well as life and property, structural and non-structural measures should be urgently established in order to effectively reduce the flood. Therefore, in this study, we developed an integrated flood analysis system that systematized technology to quantify flood risk and flood forecasting for supporting synthetic decision-making through real-time monitoring and prediction on flash rain or short-term rainfall by using radar and satellite information in Korea. Keywords: Flooding, Integrated flood analysis system, Rainfall forecasting, Korea Acknowledgments This work was carried out with the support of "Cooperative Research Program for Agriculture Science & Technology Development (Project No. PJ011686022015)" Rural Development Administration, Republic of Korea

Evaluating extreme flood characteristics of small mountainous basins of the Black Sea coastal area, Northern Caucasus

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L. S. Lebedeva

2015-06-01

Full Text Available The probability of heavy rains and river floods is expected to increase with time in the Northern Caucasus region. Densely populated areas in the valleys of small mountainous watersheds already frequently suffer from catastrophic peak floods caused by intense rains at higher elevations. This study aimed at assessing the flood characteristics of several small basins in the piedmont area of the Caucasus Mountains adjacent to the Black Sea coast including ungauged Cemes River in the Novorossiysk city. The Deterministic-Stochastic Modelling System which consists of hydrological model Hydrograph and stochastic weather generator was applied to evaluate extreme rainfall and runoff characteristics of 1% exceedance probability. Rainfall intensity is shown to play more significant role than its depth in formation of extreme flows within the studied region.

Flood modelling with a distributed event-based parsimonious rainfall-runoff model: case of the karstic Lez river catchment

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M. Coustau

2012-04-01

Full Text Available Rainfall-runoff models are crucial tools for the statistical prediction of flash floods and real-time forecasting. This paper focuses on a karstic basin in the South of France and proposes a distributed parsimonious event-based rainfall-runoff model, coherent with the poor knowledge of both evaporative and underground fluxes. The model combines a SCS runoff model and a Lag and Route routing model for each cell of a regular grid mesh. The efficiency of the model is discussed not only to satisfactorily simulate floods but also to get powerful relationships between the initial condition of the model and various predictors of the initial wetness state of the basin, such as the base flow, the Hu2 index from the Meteo-France SIM model and the piezometric levels of the aquifer. The advantage of using meteorological radar rainfall in flood modelling is also assessed. Model calibration proved to be satisfactory by using an hourly time step with Nash criterion values, ranging between 0.66 and 0.94 for eighteen of the twenty-one selected events. The radar rainfall inputs significantly improved the simulations or the assessment of the initial condition of the model for 5 events at the beginning of autumn, mostly in September–October (mean improvement of Nash is 0.09; correction in the initial condition ranges from −205 to 124 mm, but were less efficient for the events at the end of autumn. In this period, the weak vertical extension of the precipitation system and the low altitude of the 0 °C isotherm could affect the efficiency of radar measurements due to the distance between the basin and the radar (~60 km. The model initial condition S is correlated with the three tested predictors (R² > 0.6. The interpretation of the model suggests that groundwater does not affect the first peaks of the flood, but can strongly impact subsequent peaks in the case of a multi-storm event. Because this kind of model is based on a limited

Rapid proliferation of Vibrio parahaemolyticus, Vibrio vulnificus, and Vibrio cholerae during freshwater flash floods in French Mediterranean coastal lagoons.

Science.gov (United States)

Esteves, Kevin; Hervio-Heath, Dominique; Mosser, Thomas; Rodier, Claire; Tournoud, Marie-George; Jumas-Bilak, Estelle; Colwell, Rita R; Monfort, Patrick

2015-11-01

Vibrio parahaemolyticus, Vibrio vulnificus, and Vibrio cholerae of the non-O1/non-O139 serotype are present in coastal lagoons of southern France. In these Mediterranean regions, the rivers have long low-flow periods followed by short-duration or flash floods during and after heavy intense rainstorms, particularly at the end of the summer and in autumn. These floods bring large volumes of freshwater into the lagoons, reducing their salinity. Water temperatures recorded during sampling (15 to 24°C) were favorable for the presence and multiplication of vibrios. In autumn 2011, before heavy rainfalls and flash floods, salinities ranged from 31.4 to 36.1‰ and concentrations of V. parahaemolyticus, V. vulnificus, and V. cholerae varied from 0 to 1.5 × 10(3) most probable number (MPN)/liter, 0.7 to 2.1 × 10(3) MPN/liter, and 0 to 93 MPN/liter, respectively. Following heavy rainstorms that generated severe flash flooding and heavy discharge of freshwater, salinity decreased, reaching 2.2 to 16.4‰ within 15 days, depending on the site, with a concomitant increase in Vibrio concentration to ca. 10(4) MPN/liter. The highest concentrations were reached with salinities between 10 and 20‰ for V. parahaemolyticus, 10 and 15‰ for V. vulnificus, and 5 and 12‰ for V. cholerae. Thus, an abrupt decrease in salinity caused by heavy rainfall and major flooding favored growth of human-pathogenic Vibrio spp. and their proliferation in the Languedocian lagoons. Based on these results, it is recommended that temperature and salinity monitoring be done to predict the presence of these Vibrio spp. in shellfish-harvesting areas of the lagoons. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Assimilation of flood extent data with 2D flood inundation models for localised intense rainfall events

Science.gov (United States)

Neal, J. C.; Wood, M.; Bermúdez, M.; Hostache, R.; Freer, J. E.; Bates, P. D.; Coxon, G.

2017-12-01

Remote sensing of flood inundation extent has long been a potential source of data for constraining and correcting simulations of floodplain inundation. Hydrodynamic models and the computing resources to run them have developed to the extent that simulation of flood inundation in two-dimensional space is now feasible over large river basins in near real-time. However, despite substantial evidence that there is useful information content within inundation extent data, even from low resolution SAR such as that gathered by Envisat ASAR in wide swath mode, making use of the information in a data assimilation system has proved difficult. He we review recent applications of the Ensemble Kalman Filter (EnKF) and Particle Filter for assimilating SAR data, with a focus on the River Severn UK and compare these with complementary research that has looked at the internal error sources and boundary condition errors using detailed terrestrial data that is not available in most locations. Previous applications of the EnKF to this reach have focused on upstream boundary conditions as the source of flow error, however this description of errors was too simplistic for the simulation of summer flood events where localised intense rainfall can be substantial. Therefore, we evaluate the introduction of uncertain lateral inflows to the ensemble. A further limitation of the existing EnKF based methods is the need to convert flood extent to water surface elevations by intersecting the shoreline location with a high quality digital elevation model (e.g. LiDAR). To simplify this data processing step, we evaluate a method to directly assimilate inundation extent as a EnKF model state rather than assimilating water heights, potentially allowing the scheme to be used where high-quality terrain data are sparse.

The heavy rains and floods on 17 and 18 December 2016 in the Region of Murcia, with particular focus on the Mar Menor Watershed

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D. Espín Sánchez

2017-10-01

Full Text Available The heavy rains on December 17-18, 2016 were one of the most significant events that have occurred in southeastern Spain over the last two decades. In the present study the incidence of these rains in the Region of Murcia, and especially in the Mar Menor watershed, is analyzed, with particular focus on the flooded areas. The synoptic situation and the atmospheric dynamics were studied through monitoring of different METEOSAT´s satellite bands, images from weather radars and data from atmospheric soundings. A map showing the accumulated rainfall during the event and another one concerning the pluviometric anomaly of December 2016 in comparison with the average for this month in the period from 1981 to 2010 were produced using precipitation data of 129 weather stations belonging to different organizations. The maximum precipitation reached in 1 and 12 hours for a total of 64 stations was also analyzed, in relation to the thresholds and alarm levels which are established by AEMET. Finally, two hydrometeorological methods, the SCS Dimensionless Unit Hydrograph -SCS DUH- and the Témez’s Unit Hydrograph Method -TUH-, were used in order to estimate the flood-peak discharges in ephemeral streams flowing to the Mar Menor, which led to flooding in the Alcazares area. In accordance with the more consistent results of SCS DUH, the flood-peak discharges caused in this area by the Albujón and Maraña ramblas were estimated to be around 820 and 258 m3/s respectively.

Validation of Satellite Estimates (Tropical Rainfall Measuring Mission, TRMM for Rainfall Variability over the Pacific Slope and Coast of Ecuador

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Bolívar Erazo

2018-02-01

Full Text Available A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC. A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC dataset, the Climatic Research Unit–University of East Anglia (CRU dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7 dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7% but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%. The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7% and CRU (102.3 and −2.3% products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event over the EPSC and specifically towards the center-south of the EPSC (Guayas basin but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.

Exploring the potential of multivariate depth-damage and rainfall-damage models

DEFF Research Database (Denmark)

van Ootegem, Luc; van Herck, K.; Creten, T.

2018-01-01

In Europe, floods are among the natural catastrophes that cause the largest economic damage. This article explores the potential of two distinct types of multivariate flood damage models: ‘depth-damage’ models and ‘rainfall-damage’ models. We use survey data of 346 Flemish households that were...... victim of pluvial floods complemented with rainfall data from both rain gauges and weather radars. In the econometrical analysis, a Tobit estimation technique is used to deal with the issue of zero damage observations. The results show that in the ‘depth-damage’ models flood depth has a significant...... impact on the damage. In the ‘rainfall-damage’ models there is a significant impact of rainfall accumulation on the damage when using the gauge rainfall data as predictor, but not when using the radar rainfall data. Finally, non-hazard indicators are found to be important for explaining pluvial flood...

Impacts of traffic and rainfall characteristics on heavy metals build-up and wash-off from urban roads.

Science.gov (United States)

Mahbub, Parvez; Ayoko, Godwin A; Goonetilleke, Ashantha; Egodawatta, Prasanna; Kokot, Serge

2010-12-01

An investigation into the effects of changes in urban traffic characteristics due to rapid urbanisation and the predicted changes in rainfall characteristics due to climate change on the build-up and wash-off of heavy metals was carried out in Gold Coast, Australia. The study sites encompassed three different urban land uses. Nine heavy metals commonly associated with traffic emissions were selected. The results were interpreted using multivariate data analysis and decision making tools, such as principal component analysis (PCA), fuzzy clustering (FC), PROMETHEE, and GAIA. Initial analyses established high, low, and moderate traffic scenarios as well as low, low to moderate, moderate, high, and extreme rainfall scenarios for build-up and wash-off investigations. GAIA analyses established that moderate to high traffic scenarios could affect the build-up, while moderate to high rainfall scenarios could affect the wash-off of heavy metals under changed conditions. However, in wash-off, metal concentrations in 1-75 μm fraction were found to be independent of the changes to rainfall characteristics. In build-up, high traffic activities in commercial and industrial areas influenced the accumulation of heavy metal concentrations in particulate size range from 75 - >300 μm, whereas metal concentrations in finer size range of 300 μm can be targeted for removal of Ni, Cu, Pb, Cd, Cr, and Zn from build-up, while organic matter from 300 μm can be targeted for removal of Cd, Cr, Pb, and Ni from wash-off. Cu and Zn need to be removed as free ions from most fractions in wash-off.

The Use of Geospatial Technologies in Flood Hazard Mapping and Assessment: Case Study from River Evros

Science.gov (United States)

Mentzafou, Angeliki; Markogianni, Vasiliki; Dimitriou, Elias

2017-02-01

Many scientists link climate change to the increase of the extreme weather phenomena frequency, which combined with land use changes often lead to disasters with severe social and economic effects. Especially floods as a consequence of heavy rainfall can put vulnerable human and natural systems such as transboundary wetlands at risk. In order to meet the European Directive 2007/60/EC requirements for the development of flood risk management plans, the flood hazard map of Evros transboundary watershed was produced after a grid-based GIS modelling method that aggregates the main factors related to the development of floods: topography, land use, geology, slope, flow accumulation and rainfall intensity. The verification of this tool was achieved through the comparison between the produced hazard map and the inundation maps derived from the supervised classification of Landsat 5 and 7 satellite imageries of four flood events that took place at Evros delta proximity, a wetland of international importance. The comparison of the modelled output (high and very high flood hazard areas) with the extent of the inundated areas as mapped from the satellite data indicated the satisfactory performance of the model. Furthermore, the vulnerability of each land use against the flood events was examined. Geographically Weighted Regression has also been applied between the final flood hazard map and the major factors in order to ascertain their contribution to flood events. The results accredited the existence of a strong relationship between land uses and flood hazard indicating the flood susceptibility of the lowlands and agricultural land. A dynamic transboundary flood hazard management plan should be developed in order to meet the Flood Directive requirements for adequate and coordinated mitigation practices to reduce flood risk.

Climate-change driven increase in high intensity rainfall events: Analysis of development in the last decades and towards an extrapolation of future progression

Science.gov (United States)

Müller, Eva; Pfister, Angela; Gerd, Büger; Maik, Heistermann; Bronstert, Axel

2015-04-01

Hydrological extreme events can be triggered by rainfall on different spatiotemporal scales: river floods are typically caused by event durations of between hours and days, while urban flash floods as well as soil erosion or contaminant transport rather result from storms events of very short duration (minutes). Still, the analysis of climate change impacts on rainfall-induced extreme events is usually carried out using daily precipitation data at best. Trend analyses of extreme rainfall at sub-daily or even sub-hourly time scales are rare. In this contribution two lines of research are combined: first, we analyse sub-hourly rainfall data for several decades in three European regions.Second, we investigate the scaling behaviour of heavy short-term precipitation with temperature, i.e. the dependence of high intensity rainfall on the atmospheric temperature at that particular time and location. The trend analysis of high-resolution rainfall data shows for the first time that the frequency of short and intensive storm events in the temperate lowland regions in Germany has increased by up to 0.5 events per year over the last decades. I.e. this trend suggests that the occurrence of these types of storms have multiplied over only a few decades. Parallel to the changes in the rainfall regime, increases in the annual and seasonal average temperature and changes in the occurrence of circulation patterns responsible for the generation of high-intensity storms have been found. The analysis of temporally highly resolved rainfall records from three European regions further indicates that extreme precipitation events are more intense with warmer temperatures during the rainfall event. These observations follow partly the Clausius-Clapeyron relation. Based on this relation one may derive a general rule of maximum rainfall intensity associated to the event temperature, roughly following the Clausius-Clapeyron (CC) relation. This rule might be used for scenarios of future maximum

Unusual rainfall shift during monsoon period of 2010 in Pakistan ...

African Journals Online (AJOL)

Floods due to “blocking event” in the jet stream during 2010 caused intense rainfall and flash floods in northern Pakistan which resulted to riverine flooding in southern Pakistan. In the beginning of July 2010, changes in summer monsoon rainfall patterns caused the most severe flooding in Pakistan history. Process control ...

Statistics and Analysis of the Relations between Rainstorm Floods and Earthquakes

Directory of Open Access Journals (Sweden)

Baodeng Hou

2016-01-01

Full Text Available The frequent occurrence of geophysical disasters under climate change has drawn Chinese scholars to pay their attention to disaster relations. If the occurrence sequence of disasters could be identified, long-term disaster forecast could be realized. Based on the Earth Degassing Effect (EDE which is valid, this paper took the magnitude, epicenter, and occurrence time of the earthquake, as well as the epicenter and occurrence time of the rainstorm floods as basic factors to establish an integrated model to study the correlation between rainstorm floods and earthquakes. 2461 severe earthquakes occurred in China or within 3000 km from China and the 169 heavy rainstorm floods occurred in China over the past 200+ years as the input data of the model. The computational results showed that although most of the rainstorm floods have nothing to do with the severe earthquakes from a statistical perspective, some floods might relate to earthquakes. This is especially true when the earthquakes happen in the vapor transmission zone where rainstorms lead to abundant water vapors. In this regard, earthquakes are more likely to cause big rainstorm floods. However, many cases of rainstorm floods could be found after severe earthquakes with a large extent of uncertainty.

Local influence of south-east France topography and land cover on the distribution and characteristics of intense rainfall cells

Science.gov (United States)

Renard, Florent

2017-04-01

The Greater Lyon area is strongly built up, grouping 58 communes and a population of 1.3 million in approximately 500 km2. The flood risk is high as the territory is crossed by two large watercourses and by streams with torrential flow. Floods may also occur in case of runoff after heavy rain or because of a rise in the groundwater level. The whole territory can therefore be affected, and it is necessary to possess in-depth knowledge of the depths, causes and consequences of rainfall to achieve better management of precipitation in urban areas and to reduce flood risk. This study is thus focused on the effects of topography and land cover on the occurrence, intensity and area of intense rainfall cells. They are identified by local radar meteorology (C-band) combined with a processing algorithm running in a geographic information system (GIS) which identified 109,979 weighted mean centres of them in a sample composed of the five most intense rainfall events from 2001 to 2005. First, analysis of spatial distribution at an overall scale is performed, completed by study at a more detailed scale. The results show that the distribution of high-intensity rainfall cells is spread in cluster form. Subsequently, comparison of intense rainfall cells with the topography shows that cell density is closely linked with land slope but that, above all, urbanised zones feature nearly twice as many rainfall cells as farm land or forest, with more intense intensity.

Urbanization and climate change implications in flood risk management: Developing an efficient decision support system for flood susceptibility mapping.

Science.gov (United States)

Mahmoud, Shereif H; Gan, Thian Yew

2018-04-26

The effects of urbanization and climate change impact to the flood risk of two governorates in Egypt were analyzed. Non-parametric change point and trend detection algorithms were applied to the annual rainfall, rainfall anomaly, and temperature anomaly of both study sites. Next, change points and trends of the annual and monthly surface runoff data generated by the Curve Number method over 1948-2014 were also analyzed to detect the effects of urbanization on the surface runoff. Lastly, a GIS decision support system was developed to delineate flood susceptibility zones for the two governorates. The significant decline in annual rainfall and rainfall anomaly after 1994 at 8.96 and 15.3 mm/decade respectively was likely due to climate change impact, especially significant warming trend since 1976 at 0.16 °C/decade, though that could partly be attributed to rapid urbanization. Since 1970, effects of urbanization to flood risk are clear, because despite a decline in rainfall, the annual surface runoff and runoff anomaly show positive trends of 12.7 and of 14.39 mm/decade, respectively. Eleven flood contributing factors have been identified and used in mapping flood susceptibility zones of both sites. In the El-Beheira governorate, 9.2%, 17.9%, 32.3%, 28.3% and 12.3% of its area are categorized as very high, high, moderate, low and very low susceptibility to flooding, respectively. Similarly, in Alexandria governorate, 15.9%, 33.5%, 41%, 8.8% and 0.8% of its area are categorized as very high, high, moderate, low and very low susceptibility to flooding, respectively. Very high and high susceptible zones are located in the northern, northwestern and northeastern parts of the Beheira governorates, and in the northeastern and northwestern parts of Alexandria. The flood related information obtained in this study will be useful to assist mitigating potential flood damages and future land use planning of both governorates of Egypt. Copyright © 2018 Elsevier B.V. All

Hydraulic Geometry, GIS and Remote Sensing, Techniques against Rainfall-Runoff Models for Estimating Flood Magnitude in Ephemeral Fluvial Systems

Directory of Open Access Journals (Sweden)

Rafael Garcia-Lorenzo

2010-11-01

Full Text Available This paper shows the combined use of remotely sensed data and hydraulic geometry methods as an alternative to rainfall-runoff models. Hydraulic geometric data and boolean images of water sheets obtained from satellite images after storm events were integrated in a Geographical Information System. Channel cross-sections were extracted from a high resolution Digital Terrain Model (DTM and superimposed on the image cover to estimate the peak flow using HEC-RAS. The proposed methodology has been tested in ephemeral channels (ramblas on the coastal zone in south-eastern Spain. These fluvial systems constitute an important natural hazard due to their high discharges and sediment loads. In particular, different areas affected by floods during the period 1997 to 2009 were delimited through HEC-GeoRAs from hydraulic geometry data and Landsat images of these floods (Landsat‑TM5 and Landsat-ETM+7. Such an approach has been validated against rainfall-surface runoff models (SCS Dimensionless Unit Hydrograph, SCSD, Témez gamma HU Tγ and the Modified Rational method, MRM comparing their results with flood hydrographs of the Automatic Hydrologic Information System (AHIS in several ephemeral channels in the Murcia Region. The results obtained from the method providing a better fit were used to calculate different hydraulic geometry parameters, especially in residual flood areas.

Flood and landslide warning based on rainfall thresholds and soil moisture indexes: the HEWS (Hydrohazards Early Warning System for Sicily

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G. Brigandì

2017-09-01

Full Text Available The main focus of the paper is to present a flood and landslide early warning system, named HEWS (Hydrohazards Early Warning System, specifically developed for the Civil Protection Department of Sicily, based on the combined use of rainfall thresholds, soil moisture modelling and quantitative precipitation forecast (QPF. The warning system is referred to 9 different Alert Zones in which Sicily has been divided into and based on a threshold system of three different increasing critical levels: ordinary, moderate and high. In this system, for early flood warning, a Soil Moisture Accounting (SMA model provides daily soil moisture conditions, which allow to select a specific set of three rainfall thresholds, one for each critical level considered, to be used for issue the alert bulletin. Wetness indexes, representative of the soil moisture conditions of a catchment, are calculated using a simple, spatially-lumped rainfall–streamflow model, based on the SCS-CN method, and on the unit hydrograph approach, that require daily observed and/or predicted rainfall, and temperature data as input. For the calibration of this model daily continuous time series of rainfall, streamflow and air temperature data are used. An event based lumped rainfall–runoff model has been, instead, used for the derivation of the rainfall thresholds for each catchment in Sicily characterised by an area larger than 50 km2. In particular, a Kinematic Instantaneous Unit Hydrograph based lumped rainfall–runoff model with the SCS-CN routine for net rainfall was developed for this purpose. For rainfall-induced shallow landslide warning, empirical rainfall thresholds provided by Gariano et al. (2015 have been included in the system. They were derived on an empirical basis starting from a catalogue of 265 shallow landslides in Sicily in the period 2002–2012. Finally, Delft-FEWS operational forecasting platform has been applied to link input data, SMA model and rainfall

Geomorphology-based unit hydrograph models for flood risk management: case study in Brazilian watersheds with contrasting physiographic characteristics

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SAMUEL BESKOW

2018-05-01

Full Text Available ABSTRACT Heavy rainfall in conjunction with an increase in population and intensification of agricultural activities have resulted in countless problems related to flooding in watersheds. Among the techniques available for direct surface runoff (DSR modeling and flood risk management are the Unit Hydrograph (UH and Instantaneous Unit Hydrograph (IUH. This study focuses on the evaluation of predictive capability of two conceptual IUH models (Nash and Clark, considering their original (NIUH and CIUH and geomorphological approaches (NIUHGEO and CIUHGEO, and their advantages over two traditional synthetics UH models - Triangular (TUH and Dimensionless (DUH, to estimate DSR hydrographs taking as reference two Brazilian watersheds with contrasting geomorphological and climatic characteristics. The main results and conclusions were: i there was an impact of the differences in physiographical characteristics between watersheds, especially those parameters associated with soil; the dominant rainfall patterns in each watershed had an influence on flood modeling; and ii CIUH was the most satisfactory model for both watersheds, followed by NIUH, and both models had substantial superiority over synthetic models traditionally employed; iii although geomorphological approaches for IUH had performances slightly better than TUH and DUH, they should not be considered as standard tools for flood modeling in these watersheds.

Flood Hazard and Risk Analysis in Urban Area

Science.gov (United States)

Huang, Chen-Jia; Hsu, Ming-hsi; Teng, Wei-Hsien; Lin, Tsung-Hsien

2017-04-01

Typhoons always induce heavy rainfall during summer and autumn seasons in Taiwan. Extreme weather in recent years often causes severe flooding which result in serious losses of life and property. With the rapid industrial and commercial development, people care about not only the quality of life, but also the safety of life and property. So the impact of life and property due to disaster is the most serious problem concerned by the residents. For the mitigation of the disaster impact, the flood hazard and risk analysis play an important role for the disaster prevention and mitigation. In this study, the vulnerability of Kaohsiung city was evaluated by statistics of social development factor. The hazard factors of Kaohsiung city was calculated by simulated flood depth of six different return periods and four typhoon events which result in serious flooding in Kaohsiung city. The flood risk can be obtained by means of the flood hazard and social vulnerability. The analysis results provide authority to strengthen disaster preparedness and to set up more resources in high risk areas.

Design and implementation of a caustic flooding EOR pilot at Court Bakken heavy oil reservoir

Energy Technology Data Exchange (ETDEWEB)

Xie, J.; Chung, B.; Leung, L. [Society of Petroleum Engineers, Canadian Section, Calgary, AB (Canada)]|[Nexen Inc., Calgary, AB (Canada)

2008-10-15

Successful waterflooding has been ongoing since 1988 at the Court Bakken heavy oil field in west central Saskatchewan. There are currently 20 injectors and 28 active oil producers in the Court main unit which is owned by Nexen and Pengrowth. The Court pool has an estimated 103.8 mmbbl of original oil in place (OOIP), of which 24 per cent has been successfully recovered after 20 years of waterflooding. A high-level enhanced oil recovery (EOR) screening study was conducted to evaluate other EOR technologies for a heavy oil reservoir of this viscosity range (17 degrees API). Laboratory studies showed that caustic flooding may enhance oil recovery after waterflooding at the Court Bakken heavy oil pool. A single well test demonstrated that caustic injection effectively reduced residual oil saturation. A sector model reservoir simulation revealed that caustic flood could achieve 9 per cent incremental oil recovery in the pilot area. Following the promising laboratory results, a successful caustic flood pilot was implemented at Court heavy oil pool where the major challenges encountered were low reservoir pressure and water channeling. 6 refs., 2 tabs., 6 figs.

Mesoscale processes for super heavy rainfall of Typhoon Morakot (2009 over Southern Taiwan

Directory of Open Access Journals (Sweden)

C.-Y. Lin

2011-01-01

Full Text Available Within 100 h, a record-breaking rainfall, 2855 mm, was brought to Taiwan by typhoon Morakot in August 2009 resulting in devastating landslides and casualties. Analyses and simulations show that under favorable large-scale situations, this unprecedented precipitation was caused first by the convergence of the southerly component of the pre-existing strong southwesterly monsoonal flow and the northerly component of the typhoon circulation. Then the westerly component of southwesterly flow pushed the highly moist air (mean specific humidity >16 g/kg between 950 and 700 hPa from NCEP GFS data set eastward against the Central Mountain Range, and forced it to lift in the preferred area. From the fine-scale numerical simulation, not only did the convergence itself provide the source of the heavy rainfall when it interacted with the topography, but also convective cells existed within the typhoon's main rainband. The convective cells were in the form of small rainbands perpendicular to the main one, and propagated as wave trains downwind. As the main rainband moved northward and reached the southern CMR, convective cells inside the narrow convergence zone to the south and those to the north as wave trains, both rained heavily as they were lifted by the west-facing mountain slopes. Those mesoscale processes were responsible for the unprecedented heavy rainfall total that accompanied this typhoon.

Leptospirosis following a major flood in Central Queensland, Australia.

Science.gov (United States)

Smith, J K G; Young, M M; Wilson, K L; Craig, S B

2013-03-01

Throughout December 2010 and January 2011, Queensland experienced widespread flooding due to unusually protracted and heavy rainfalls. In mid-January 2011, four individuals from a small community in Central Queensland were hospitalized with leptospirosis. A further five cases were subsequently identified from around Central Queensland, bringing the total to nine. Microscopic agglutination testing found that serovar Arborea (Leptospira borgpetersenii serovar Arborea) was presumptively responsible for leptospirosis in seven of nine confirmed cases. Serovars Hardjo and Australis were identified in samples from two remaining cases. All cases had exposure to flood water. No single exposure source was identified. This is the first reported outbreak of leptospirosis in Central Queensland and the first report of leptospirosis cases associated with flood water inundation in Queensland. Public health authorities should continue to promote awareness of leptospirosis in flood-affected populations. Healthcare providers must maintain a high level of suspicion for leptospirosis during and after flood events.

Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

Science.gov (United States)

Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2017-03-01

The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

Calibration of commercial microwave link derived- rainfall and its relevance to flash flood occurrence in the Dead Sea area

Science.gov (United States)

Eshel, Adam; Alpert, Pinhas; Raich, Roi; Laronne, Jonathan; Merz, Ralf; Geyer, Stefan; Corsmeier, Ulrich

2016-04-01

Flash floods are a common phenomenon in arid and semi-arid areas such as the Dead Sea. These floods are generated due to a combination of short lasting, yet intense rainfall and typical low infiltration rates. The rare flow events in ephemeral rivers have significant importance in the replenishment of groundwater via transmission losses and in sustaining the vivid ecology of drylands. In some cases, flash floods cause severe damage to infrastructure as well as to private property, constituting a threat to human life. The temporal variation of rainfall intensity is the main driver generating the majority of flash floods in the Judean Desert, hence its monitoring is crucial in this area as in other remote arid areas worldwide. Cellular communication towers are profusely located. Commercial Microwave Links (CML) attenuation data obtained by cellular companies can be used for environmental monitoring. Rain is one of the most effective meteorological phenomena to attenuate a CML signal which, unlike radar backscatter, relates to near-surface conditions and is, therefore, suitable for surface hydrology. A 16 km CML crosses the Wadi Ze'elim drainage basin (~250 square kilometers), at the outlet of which the discharge is calculated using the Manning formula. The hydrometric data include accurate longitudinal and cross sectional measurements, water level and importantly mean water surface velocity when present during a flash flood. The latter is first-ever obtained in desert flash floods by portable, radar-based surface velocimetry. Acquisition of water velocity data is essential to avoid assuming a constant roughness coefficient, thereby more accurately calculating water discharge. Calibrating the CML-rain intensity, derived from the International Telecommunication Union (ITU)'s power law, is necessary to correlate the surface hydrologic response to the link. Our calibration approach is as follows: all the Israel Meteorological Service C-band radar cells over the CML

Flood Foresight: A near-real time flood monitoring and forecasting tool for rapid and predictive flood impact assessment

Science.gov (United States)

Revilla-Romero, Beatriz; Shelton, Kay; Wood, Elizabeth; Berry, Robert; Bevington, John; Hankin, Barry; Lewis, Gavin; Gubbin, Andrew; Griffiths, Samuel; Barnard, Paul; Pinnell, Marc; Huyck, Charles

2017-04-01

The hours and days immediately after a major flood event are often chaotic and confusing, with first responders rushing to mobilise emergency responders, provide alleviation assistance and assess loss to assets of interest (e.g., population, buildings or utilities). Preparations in advance of a forthcoming event are becoming increasingly important; early warning systems have been demonstrated to be useful tools for decision markers. The extent of damage, human casualties and economic loss estimates can vary greatly during an event, and the timely availability of an accurate flood extent allows emergency response and resources to be optimised, reduces impacts, and helps prioritise recovery. In the insurance sector, for example, insurers are under pressure to respond in a proactive manner to claims rather than waiting for policyholders to report losses. Even though there is a great demand for flood inundation extents and severity information in different sectors, generating flood footprints for large areas from hydraulic models in real time remains a challenge. While such footprints can be produced in real time using remote sensing, weather conditions and sensor availability limit their ability to capture every single flood event across the globe. In this session, we will present Flood Foresight (www.floodforesight.com), an operational tool developed to meet the universal requirement for rapid geographic information, before, during and after major riverine flood events. The tool provides spatial data with which users can measure their current or predicted impact from an event - at building, basin, national or continental scales. Within Flood Foresight, the Screening component uses global rainfall predictions to provide a regional- to continental-scale view of heavy rainfall events up to a week in advance, alerting the user to potentially hazardous situations relevant to them. The Forecasting component enhances the predictive suite of tools by providing a local

Near Real Time Flood Warning System for National Capital Territory of Delhi

Science.gov (United States)

Goyal, A.; Yadav, H.; Tyagi, H.; Gosain, A. K.

2017-12-01

Extreme floods are common phenomena during Indian Monsoons. The National Capital Territory area of India, Delhi, frequently experiences fluvial as well as pluvial inundation due to its proximity to river Yamuna and poor functioning of its stormwater drainage system. The urban floods result in severe waterlogging and heavy traffic snarls, bringing life in this megapolis to a halt. The city has witnessed six major floods since 1900 and thus its residents are well conscious of potential flood risks but the city still lacks a flood warning system. The flood related risks can be considerably reduced, if not eliminated, by issuing timely warnings and implementing adaptive measures. Therefore, the present study attempts to develop a web based platform that integrates Web-GIS technology and mathematical simulation modelling to provide an effective and reliable early flood warning service for Delhi. The study makes use of India Metorological Department's Doppler radar-derived near real time rainfall estimates of 15 minutes time step. The developed SWMM model has been validated using information from gauges, monitoring sensors and crowd sourcing techniques and utilises capabilities of cloud computing on server side for fast processing. This study also recommends safe evacuation policy and remedial measures for flooding hotspots as part of flood risk management plan. With heightened risk of floods in fast urbanizing areas, this work becomes highly pertinent as flood warning system with adequate lead time can not only save precious lives but can also substantially reduce flood damages.

Development of a precipitation-area curve for warning criteria of short-duration flash flood

Science.gov (United States)

Bae, Deg-Hyo; Lee, Moon-Hwan; Moon, Sung-Keun

2018-01-01

This paper presents quantitative criteria for flash flood warning that can be used to rapidly assess flash flood occurrence based on only rainfall estimates. This study was conducted for 200 small mountainous sub-catchments of the Han River basin in South Korea because South Korea has recently suffered many flash flood events. The quantitative criteria are calculated based on flash flood guidance (FFG), which is defined as the depth of rainfall of a given duration required to cause frequent flooding (1-2-year return period) at the outlet of a small stream basin and is estimated using threshold runoff (TR) and antecedent soil moisture conditions in all sub-basins. The soil moisture conditions were estimated during the flooding season, i.e., July, August and September, over 7 years (2002-2009) using the Sejong University Rainfall Runoff (SURR) model. A ROC (receiver operating characteristic) analysis was used to obtain optimum rainfall values and a generalized precipitation-area (P-A) curve was developed for flash flood warning thresholds. The threshold function was derived as a P-A curve because the precipitation threshold with a short duration is more closely related to basin area than any other variables. For a brief description of the P-A curve, generalized thresholds for flash flood warnings can be suggested for rainfall rates of 42, 32 and 20 mm h-1 in sub-basins with areas of 22-40, 40-100 and > 100 km2, respectively. The proposed P-A curve was validated based on observed flash flood events in different sub-basins. Flash flood occurrences were captured for 9 out of 12 events. This result can be used instead of FFG to identify brief flash flood (less than 1 h), and it can provide warning information to decision-makers or citizens that is relatively simple, clear and immediate.

Correlations between reinfall data and insurance damage data related to sewer flooding for the case of Aarhus, Denmark

NARCIS (Netherlands)

Spekkers, M.H.; Zhou, Q.; Arnbjerg-Nielsen, K.; Clemens, F.H.L.R.; ten Veldhuis, J.A.E.

2013-01-01

Sewer flooding due to extreme rainfall may result in considerable damage. Damage data to quantify costs of cleaning, drying, and replacing materials and goods are rare in literature. In this study, insurance claim data related to property damages were analysed for the municipality of Aarhus,

Flood analyses for Department of Energy Y-12, ORNL and K-25 Plants. Flood analyses in support of flood emergency planning

International Nuclear Information System (INIS)

1995-05-01

The study involved defining the flood potential and local rainfall depth and duration data for the Department of Energy's (DOE) Y-12, Oak Ridge National Laboratory (ORNL), and K-25 plants. All three plants are subject to flooding from the Clinch River. In addition, the Y-12 plant is subject to flooding from East Fork Poplar and Bear Creeks, the ORNL plant from Whiteoak Creek and Melton Branch, and the K-25 plant from Poplar Creek. Determination of flood levels included consideration of both rainfall events and postulated failures of Norris and Melton Hill Dams in seismic events

Impacts of climate change on rainfall, seasonal flooding, and evapotranspiration in the Okavango Delta, Botswana

Science.gov (United States)

Konecky, B. L.; Noone, D.; Mosimanyana, E.; Gondwe, M.

2016-12-01

The Okavango Delta in northern Botswana is one of the world's richest biodiversity hotspots. A UNESCO World Heritage Site, the Delta is known for its unique annual flood pulse, whereby the wetland and its neighboring river systems are inundated with waters that travel nearly 1000 km before reaching this subtropical, semi-arid destination. The livelihoods of northern Botswana's ecosystems and human populations rely on these floods to supplement the short and variable rainy season, which in many years is too minimal to ameliorate regional drought. However, anthropogenic climate change is reducing the amount of water that reaches the delta by increasing evaporation from soils and rivers, and transpiration by vegetation, during its long transit to Botswana. Future changes in rainfall patterns, extreme events, and increased upstream water use could exacerbate this water stress. Unfortunately, it remains difficult to assess the impacts of climate change on the delta because few data exist to constrain its complex climatic and seasonal water cycling regimes. This study presents a novel characterization of the water cycle in and around the Okavango Delta based on a survey of free-flowing surface waters, stagnant pools, precipitation, and groundwater carried out during the 2016 rainy and early-flood season. We use stable isotope and water quality data to assess local moisture sources, transport, evaporation, wetland flushing, and land-atmosphere exchanges, all of which are subject to change under global warming. We find a strong evaporation gradient and a progressive flushing of stagnant swamp waters along the northeastern and northwestern channels of the Delta. The evaporation gradient is more limited in nearby rivers with more limited wetlands. We contrast results with a survey of the Delta performed in the 1970's in order to assess changes over the past 40 years. Since some of these changes may arise from rainfall supply, we also present new analysis of rainfall moisture

Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

Science.gov (United States)

Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

2017-04-01

Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

Flash floods along the Italian coastal areas: examples from Pozzuoli city, Campania, Italy

Science.gov (United States)

Esposito, Giuseppe; Grimaldi, Giuseppe; Matano, Fabio; Mazzola, Salvatore; Sacchi, Marco

2014-05-01

The Italian western coastal areas are the most exposed in the country to low-pressure systems coming from the central-western Mediterranean Sea and Atlantic Ocean. In the last years, many Italian coastal villages were struck by floods and flow processes triggered by high-intensity and short-duration rainfall, typical of flash flood events. In the Campania region (SW Italy) a series of events has caused several fatalities and heavy damages in the last decades, i.e. the flash floods of Casamicciola - Ischia Island (10/11/2009 - 1 fatality) and Atrani (9/9/2010 - 1 fatality). In this work we describe the rainfall properties and the ground effects of the 2009, 2010 and 2011 flash floods which involved the city of Pozzuoli, along the Campi Flegrei coast, where a catastrophic flood event (13 fatalities) is reported in 1918 in the AVI Project database. Rainfall data were measured at a sampling rate of 10 minutes by a regional Civil Protection rain gauge located in the city of Pozzuoli near the areas struck by the flash flood effects. In order to analyze the extreme features of the rainstorms and compare them, we have considered the 1-hour maximum rainfall amount and the 10-min peak storm intensity value for each event. The first rainstorm occurred on 14 September 2009; it was characterized by a 1-hour maximum rainfall amount of 34.4 mm and a 10-min peak storm intensity of 57.6 mm/h. The second rainstorm occurred on 30 July 2010; it was characterized by a 1-hour maximum rainfall amount of 40.6 mm and a 10-min peak storm intensity of 126 mm/h. The third rainstorm occurred on 06 November 2011; it was characterized by a 1-hour maximum rainfall amount of 44.2 mm and a 10-min peak storm intensity of 67.2 mm/h. The three described rainstorms all triggered erosional processes and shallow landslides in the upper part of the Pozzuoli drainage basin that supplied sheet flows and hyperconcentrated flows downstream, with severe damage to the human structures built near or inside the

Climate change track in river floods in Europe

Directory of Open Access Journals (Sweden)

Z. W. Kundzewicz

2015-06-01

Full Text Available A holistic perspective on changing river flood risk in Europe is provided. Economic losses from floods have increased, principally driven by the expanding exposure of assets at risk. Climate change (i.e. observed increase in precipitation intensity, decrease of snowpack and other observed climate changes might already have had an impact on floods. However, no gauge-based evidence had been found for a climate-driven, widespread change in the magnitude/frequency of floods during the last decades. There are strong regional and sub-regional variations in the trends. Moreover, it has not been generally possible to attribute rain-generated peak streamflow trends to anthropogenic climate change. Physical reasoning suggests that projected increases in the frequency and intensity of heavy rainfall would contribute to increases in rain-generated local floods, while less snowmelt flooding and earlier spring peak flows in snowmelt-fed rivers are expected. However, there is low confidence in future changes in flood magnitude and frequency resulting from climate change. The impacts of climate change on flood characteristics are highly sensitive to the detailed nature of those changes. Discussion of projections of flood hazard in Europe is offered. Attention is drawn to a considerable uncertainty - over the last decade or so, projections of flood hazard in Europe have largely changed.

Rainfall-runoff modelling and palaeoflood hydrology applied to reconstruct centennial scale records of flooding and aquifer recharge in ungauged ephemeral rivers

Directory of Open Access Journals (Sweden)

G. Benito

2011-04-01

Full Text Available In this study we propose a multi-source data approach for quantifying long-term flooding and aquifer recharge in ungauged ephemeral rivers. The methodology is applied to the Buffels River, at 9000 km² the largest ephemeral river in Namaqualand (NW South Africa, a region with scarce stream flow records limiting research investigating hydrological response to global change. Daily discharge and annual flood series (1965–2006 were estimated from a distributed rainfall-runoff hydrological model (TETIS using rainfall gauge records located within the catchment. The model was calibrated and validated with data collected during a two year monitoring programme (2005–2006 at two stream flow stations, one each in the upper and lower reaches of the catchment. In addition to the modelled flow records, non-systematic flood data were reconstructed using both sedimentary and documentary evidence. The palaeoflood record identified at least 25 large floods during the last 700 yr; with the largest floods reaching a minimum discharge of 255 m³ s⁻¹ (450 yr return period in the upper basin, and 510 m³ s⁻¹ (100 yr return period in the lower catchment. Since AD 1925, the flood hydrology of the Buffels River has been characterised by a decrease in the magnitude and frequency of extreme floods, with palaeoflood discharges (period 1500–1921 five times greater than the largest modelled floods during the period 1965–2006. Large floods generated the highest hydrograph volumes, however their contribution to aquifer recharge is limited as this depends on other factors such as flood duration and storage capacity of the unsaturated zone prior to the flood. Floods having average return intervals of 5–10 yr (120–140 m³ s⁻¹ and flowing for 12 days are able to fully saturate the Spektakel aquifer in the lower Buffels River basin. Alluvial aquifer storage capacity limiting potential recharge

Meteorological Conditions of Floods In The Chilean Andes Mountains

Science.gov (United States)

Vergara, J.

Catastrophic floods occurred on mountains River during 2000 and 2001. The meteo- rological conditions of flood during the last five years have analyzed. For example, the flood of June 29 of 2000 occurred after one of extremely wettest June of the last 40 years were snowfall was 991cm in the Aconcagua Valley. Infrequently storms activ- ity generated a huge snowfall and rainfall over the Andes mountains on June of 2000 (1525mm in El Maule Valley) and the end of the unusually period, the flood was trig- gered by rising temperatures on the mountains and heavy rain (199mm in 24 hours) fall over the fresh snow on the morning of June 29 and floods wave developed and moved down along of the all river located on Central part of Chile, the foods peak was 2970.5m3/s on the El Maule basin in the morning of June 29. The regional meteoro- logical models with the hydrological forecasting was used for alert of the floods.

Simulation of an extreme heavy rainfall event over Chennai, India using WRF: Sensitivity to grid resolution and boundary layer physics

KAUST Repository

Srinivas, C.V.

2018-05-04

In this study, the heavy precipitation event on 01 December 2015 over Chennai located on the southeast coast of India was simulated using the Weather Research and Forecast (WRF) model. A series of simulations were conducted using explicit convection and varying the planetary boundary layer (PBL) parameterization schemes. The model results were compared with available surface, satellite and Doppler Weather Radar observations. Simulations indicate strong, sustained moist convection associated with development of a mesoscale upper air cyclonic circulation, during the passage of a synoptic scale low-pressure trough caused heavy rainfall over Chennai and its surroundings. Results suggest that veering of wind with height associated with strong wind shear in the layer 800–400 hPa together with dry air advection facilitated development of instability and initiation of convection. The 1-km domain using explicit convection improved the prediction of rainfall intensity of about 450 mm and its distribution. The PBL physics strongly influenced the rainfall prediction by changing the location of upper air circulation, energy transport, moisture convergence and intensity of convection in the schemes YSU, MYJ and MYNN. All the simulations underestimated the first spell of the heavy rainfall. While YSU and MYJ schemes grossly underestimated the rainfall and dislocated the area of maximum rainfall, the higher order MYNN scheme simulated the rainfall pattern in better agreement with observations. The MYNN showed lesser mixing and simulated more humid boundary layer, higher convective available potential energy (CAPE) and stronger winds at mid-troposphere than did the other schemes. The MYNN also realistically simulated the location of upper air cyclonic flow and various dynamic and thermodynamic features. Consequently it simulated stronger moisture convergence and higher precipitation.

Simulation of an extreme heavy rainfall event over Chennai, India using WRF: Sensitivity to grid resolution and boundary layer physics

KAUST Repository

Srinivas, C.V.; Yesubabu, V.; Hari Prasad, D.; Hari Prasad, K.B.R.R.; Greeshma, M.M.; Baskaran, R.; Venkatraman, B.

2018-01-01

In this study, the heavy precipitation event on 01 December 2015 over Chennai located on the southeast coast of India was simulated using the Weather Research and Forecast (WRF) model. A series of simulations were conducted using explicit convection and varying the planetary boundary layer (PBL) parameterization schemes. The model results were compared with available surface, satellite and Doppler Weather Radar observations. Simulations indicate strong, sustained moist convection associated with development of a mesoscale upper air cyclonic circulation, during the passage of a synoptic scale low-pressure trough caused heavy rainfall over Chennai and its surroundings. Results suggest that veering of wind with height associated with strong wind shear in the layer 800–400 hPa together with dry air advection facilitated development of instability and initiation of convection. The 1-km domain using explicit convection improved the prediction of rainfall intensity of about 450 mm and its distribution. The PBL physics strongly influenced the rainfall prediction by changing the location of upper air circulation, energy transport, moisture convergence and intensity of convection in the schemes YSU, MYJ and MYNN. All the simulations underestimated the first spell of the heavy rainfall. While YSU and MYJ schemes grossly underestimated the rainfall and dislocated the area of maximum rainfall, the higher order MYNN scheme simulated the rainfall pattern in better agreement with observations. The MYNN showed lesser mixing and simulated more humid boundary layer, higher convective available potential energy (CAPE) and stronger winds at mid-troposphere than did the other schemes. The MYNN also realistically simulated the location of upper air cyclonic flow and various dynamic and thermodynamic features. Consequently it simulated stronger moisture convergence and higher precipitation.

First evaluation of the utility of GPM precipitation in global flood monitoring

Science.gov (United States)

Wu, H.; Yan, Y.; Gao, Z.

2017-12-01

The Global Flood Monitoring System (GFMS) has been developed and used to provide real-time flood detection and streamflow estimates over the last few years with significant success shown by validation against global flood event data sets and observed streamflow variations (Wu et al., 2014). It has become a tool for various national and international organizations to appraise flood conditions in various areas, including where rainfall and hydrology information is limited. The GFMS has been using the TRMM Multi-satellite Precipitation Analysis (TMPA) as its main rainfall input. Now, with the advent of the Global Precipitation Measurement (GPM) mission there is an opportunity to significantly improve global flood monitoring and forecasting. GPM's Integrated Multi-satellitE Retrievals for GPM (IMERG) multi-satellite product is designed to take advantage of various technical advances in the field and combine that with an efficient processing system producing "early" (4 hrs) and "late" (12 hrs) products for operational use. Specifically, this study is focused on (1) understanding the difference between the new IMERG products and other existing satellite precipitation products, e.g., TMPA, CMORPH, and ground observations; (2) addressing the challenge in the usage of the IMERG for flood monitoring through hydrologic models, given that only a short period of precipitation data record has been accumulated since the lunch of GPM in 2014; and (3) comparing the statistics of flood simulation based on the DRIVE model with IMERG, TMPA, CMORPH etc. as precipitation inputs respectively. Derivation of a global threshold map is a necessary step to define flood events out of modelling results, which requires a relatively longer historic information. A set of sensitivity tests are conducted by adjusting IMERG's light, moderate, heavy rain to existing precipitation products with long-term records separately, to optimize the strategy of PDF matching. Other aspects are also examined

A web-based Tamsui River flood early-warning system with correction of real-time water stage using monitoring data

Science.gov (United States)

Liao, H. Y.; Lin, Y. J.; Chang, H. K.; Shang, R. K.; Kuo, H. C.; Lai, J. S.; Tan, Y. C.

2017-12-01

Taiwan encounters heavy rainfalls frequently. There are three to four typhoons striking Taiwan every year. To provide lead time for reducing flood damage, this study attempt to build a flood early-warning system (FEWS) in Tanshui River using time series correction techniques. The predicted rainfall is used as the input for the rainfall-runoff model. Then, the discharges calculated by the rainfall-runoff model is converted to the 1-D river routing model. The 1-D river routing model will output the simulating water stages in 487 cross sections for the future 48-hr. The downstream water stage at the estuary in 1-D river routing model is provided by storm surge simulation. Next, the water stages of 487 cross sections are corrected by time series model such as autoregressive (AR) model using real-time water stage measurements to improve the predicted accuracy. The results of simulated water stages are displayed on a web-based platform. In addition, the models can be performed remotely by any users with web browsers through a user interface. The on-line video surveillance images, real-time monitoring water stages, and rainfalls can also be shown on this platform. If the simulated water stage exceeds the embankments of Tanshui River, the alerting lights of FEWS will be flashing on the screen. This platform runs periodically and automatically to generate the simulation graphic data of flood water stages for flood disaster prevention and decision making.

Heavy Precipitation impacts and emergency planning - developing applicable strategies for a metropolitan area

Science.gov (United States)

Kutschker, Thomas; Glade, Thomas

2016-04-01

Heavy rainfall in central Europe is one of the assumed effects of climate change, which occurs with large seasonal and regional differences in its magnitude. The extent of loss depends on natural parameters (e.g. topography and vegetation) as well as on socio-economic factors like urbanized and industrialized areas and population density. Dangerous cascade effects appear, if critical infrastructure like the electrical power supply is affected. In some cases mudflows and flash floods cause inundated or undercut roads and cause a high demand for fast and effective assistance of the authorities. The civil protection in Germany is based on a federal system with a bottom-up command-structure and responsibility to the local community. Commonly this responsibility is taken by the fire brigades and civil protection units of the community or district. After heavy rainfall in an urban area, numerous incidents and emergency calls appearing at a time are overstressing the human and technical resources of the fire brigades within the local authority frequently. In this study, a method of comprehensive evaluation of meteorological data and the operation data from local fire brigades shall be developed for the Rhine-Main-Area in order to identify particular affected spots of heavy rain and bundle resources of the fire brigades. It is to be found out if the study area contains regions with a particularly high exposure to heavy rain and high application numbers of the fire department and whether there is a relationship of rainfall and frequency of use. To evaluate particular local effects on the fire brigades capability, a brief analysis of the meteorological data provided by the German Meteorological Service (DWD) as well as the evaluation of the incident data of the affected fire brigades, is used to frame a realistic approach. In particular fire brigade operation data can be used accordingly to describe the intensity of the aftermath when heavy precipitation strikes a certain

2 Dimensional Hydrodynamic Flood Routing Analysis on Flood Forecasting Modelling for Kelantan River Basin

Directory of Open Access Journals (Sweden)

Azad Wan Hazdy

2017-01-01

Full Text Available Flood disaster occurs quite frequently in Malaysia and has been categorized as the most threatening natural disaster compared to landslides, hurricanes, tsunami, haze and others. A study by Department of Irrigation and Drainage (DID show that 9% of land areas in Malaysia are prone to flood which may affect approximately 4.9 million of the population. 2 Dimensional floods routing modelling demonstrate is turning out to be broadly utilized for flood plain display and is an extremely viable device for evaluating flood. Flood propagations can be better understood by simulating the flow and water level by using hydrodynamic modelling. The hydrodynamic flood routing can be recognized by the spatial complexity of the schematization such as 1D model and 2D model. It was found that most of available hydrological models for flood forecasting are more focus on short duration as compared to long duration hydrological model using the Probabilistic Distribution Moisture Model (PDM. The aim of this paper is to discuss preliminary findings on development of flood forecasting model using Probabilistic Distribution Moisture Model (PDM for Kelantan river basin. Among the findings discuss in this paper includes preliminary calibrated PDM model, which performed reasonably for the Dec 2014, but underestimated the peak flows. Apart from that, this paper also discusses findings on Soil Moisture Deficit (SMD and flood plain analysis. Flood forecasting is the complex process that begins with an understanding of the geographical makeup of the catchment and knowledge of the preferential regions of heavy rainfall and flood behaviour for the area of responsibility. Therefore, to decreases the uncertainty in the model output, so it is important to increase the complexity of the model.

A Study on Integrated Community Based Flood Mitigation with Remote Sensing Technique in Kota Bharu, Kelantan

International Nuclear Information System (INIS)

Ainullotfi, A A; Ibrahim, A L; Masron, T

2014-01-01

This study is conducted to establish a community based flood management system that is integrated with remote sensing technique. To understand local knowledge, the demographic of the local society is obtained by using the survey approach. The local authorities are approached first to obtain information regarding the society in the study areas such as the population, the gender and the tabulation of settlement. The information about age, religion, ethnic, occupation, years of experience facing flood in the area, are recorded to understand more on how the local knowledge emerges. Then geographic data is obtained such as rainfall data, land use, land elevation, river discharge data. This information is used to establish a hydrological model of flood in the study area. Analysis were made from the survey approach to understand the pattern of society and how they react to floods while the analysis of geographic data is used to analyse the water extent and damage done by the flood. The final result of this research is to produce a flood mitigation method with a community based framework in the state of Kelantan. With the flood mitigation that involves the community's understanding towards flood also the techniques to forecast heavy rainfall and flood occurrence using remote sensing, it is hope that it could reduce the casualties and damage that might cause to the society and infrastructures in the study area

Going beyond the flood insurance rate map: insights from flood hazard map co-production

Science.gov (United States)

Luke, Adam; Sanders, Brett F.; Goodrich, Kristen A.; Feldman, David L.; Boudreau, Danielle; Eguiarte, Ana; Serrano, Kimberly; Reyes, Abigail; Schubert, Jochen E.; AghaKouchak, Amir; Basolo, Victoria; Matthew, Richard A.

2018-04-01

Flood hazard mapping in the United States (US) is deeply tied to the National Flood Insurance Program (NFIP). Consequently, publicly available flood maps provide essential information for insurance purposes, but they do not necessarily provide relevant information for non-insurance aspects of flood risk management (FRM) such as public education and emergency planning. Recent calls for flood hazard maps that support a wider variety of FRM tasks highlight the need to deepen our understanding about the factors that make flood maps useful and understandable for local end users. In this study, social scientists and engineers explore opportunities for improving the utility and relevance of flood hazard maps through the co-production of maps responsive to end users' FRM needs. Specifically, two-dimensional flood modeling produced a set of baseline hazard maps for stakeholders of the Tijuana River valley, US, and Los Laureles Canyon in Tijuana, Mexico. Focus groups with natural resource managers, city planners, emergency managers, academia, non-profit, and community leaders refined the baseline hazard maps by triggering additional modeling scenarios and map revisions. Several important end user preferences emerged, such as (1) legends that frame flood intensity both qualitatively and quantitatively, and (2) flood scenario descriptions that report flood magnitude in terms of rainfall, streamflow, and its relation to an historic event. Regarding desired hazard map content, end users' requests revealed general consistency with mapping needs reported in European studies and guidelines published in Australia. However, requested map content that is not commonly produced included (1) standing water depths following the flood, (2) the erosive potential of flowing water, and (3) pluvial flood hazards, or flooding caused directly by rainfall. We conclude that the relevance and utility of commonly produced flood hazard maps can be most improved by illustrating pluvial flood hazards

Toward seamless high-resolution flash flood forecasting over Europe based on radar nowcasting and NWP: An evaluation with case studies

Science.gov (United States)

Park, Shinju; Berenguer, Marc; Sempere-Torres, Daniel; Baugh, Calum; Smith, Paul

2017-04-01

Flash floods induced by heavy rain are one of the hazardous natural events that significantly affect human lives. Because flash floods are characterized by their rapid onset, forecasting flash flood to lead an effective response requires accurate rainfall predictions with high spatial and temporal resolution and adequate representation of the hydrologic and hydraulic processes within a catchment that determine rainfall-runoff accumulations. We present extreme flash flood cases which occurred throughout Europe in 2015-2016 that were identified and forecasted by two real-time approaches: 1) the European Rainfall-Induced Hazard Assessment System (ERICHA) and 2) the European Runoff Index based on Climatology (ERIC). ERICHA is based on the nowcasts of accumulated precipitation generated from the pan-European radar composites produced by the EUMETNET project OPERA. It has the advantage of high-resolution precipitation inputs and rapidly updated forecasts (every 15 minutes), but limited forecast lead time (up to 8 hours). ERIC, on the other hand, provides 5-day forecasts based on the COSMO-LEPS NWP simulations updated 2 times a day but is only produced at a 7 km resolution. We compare the products from both systems and focus on showing the advantages, limitations and complementarities of ERICHA and ERIC for seamless high-resolution flash flood forecasting.

An overview of road damages due to flooding: Case study in Kedah state, Malaysia

Science.gov (United States)

Ismail, Muhd Shahril Nizam; Ghani, Abdul Naser Abdul

2017-10-01

Flooding occurs frequently in many countries including Malaysia. Floods in Malaysia are usually due to heavy and prolonged rainfall, uncontrolled development, and drainage systems that are not being monitored. Road damage due to flooding event can cause huge expenditures for the post-flooding rehabilitation and maintenance. The required maintenance and rehabilitation could upset the original life cycle cost estimations. Data on road statistics were obtained from the Highway Planning Division, Ministry of Works Malaysia and data on flooding was collected from the Department of Irrigation and Drainage Malaysia for events between 2012 and 2015. The pilot sites were selected based on its historical cases of floods that caused road damages in Kedah. The pilot site indicated that the impact of flooding on road infrastructures systems can be used to plan better road design and maintenances. It also revealed that it costs more than RM 1 million to reinstate roads damaged by flooding in a typical district annually.

Unjust waters. Climate change, flooding and the protection of poor urban communities. Experiences from six African cities

International Nuclear Information System (INIS)

2007-02-01

Floods are natural phenomena, but damage and losses from floods are the consequence of human action. The increasing climatic variability, storminess and more frequent flooding driven by climate change will affect poor urban communities far more than other people living in towns and cities. Although driven by human activities ranging from modernisation and development to land degradation by poor farmers and grazing flocks, climate change in Africa has uneven impacts, affecting the poor severely. Flooding in urban areas is not just related to heavy rainfall and extreme climatic events; it is also related to changes in the built-up areas themselves. Urbanisation aggravates flooding by restricting where floods waters can go, by covering large parts of the ground with roofs, roads and pavements, by obstructing sections of natural channels, and by building drains that ensure that water moves to rivers more rapidly than it did under natural conditions. As people crowd into African cities, these human impacts on urban land surfaces and drainage intensify. The proportions of small stream and river catchment areas that are urbanised will increase. As a result, even quite moderate storms now produce quite high flows in rivers because much more of the catchment area supplies direct surface runoff from its hard surfaces and drains. Where streams flow through a series of culverts and concrete channels, they cannot adjust to changes in the frequency of heavy rain as natural streams do. They often get obstructed by silt and urban debris, particularly when houses are built close to the channels. Such situations frequently arise where poor people build their shelters on low-lying flood plains, over swamps or above the tidewater on the coast. The effects of climate change are superimposed on these people-driven local land surface modifications. The links between changes in land use and in heavy rainfall patterns, the frequency and depth of flooding and the problems of the urban poor

Leaching variations of heavy metals in chelator-assisted phytoextraction by Zea mays L. exposed to acid rainfall.

Science.gov (United States)

Lu, Yayin; Luo, Dinggui; Liu, Lirong; Tan, Zicong; Lai, An; Liu, Guowei; Li, Junhui; Long, Jianyou; Huang, Xuexia; Chen, Yongheng

2017-11-01

Chelant-enhanced phytoextraction method has been put forward as an effective soil remediation method, whereas the heavy metal leaching could not be ignored. In this study, a cropping-leaching experiment, using soil columns, was applied to study the metal leaching variations during assisted phytoextraction of Cd- and Pb-polluted soils, using seedlings of Zea mays, applying three different chelators (EDTA, EDDS, and rhamnolipid), and artificial rainfall (acid rainfall or normal rainfall). It showed that artificial rainfall, especially artificial acid rain, after chelator application led to the increase of heavy metals in the leaching solution. EDTA increased both Cd and Pb concentrations in the leaching solution, obviously, whereas EDDS and rhamnolipid increased Cd concentration but not Pb. The amount of Cd and Pb decreased as the leaching solution increased, the patterns as well matched LRMs (linear regression models), with R-square (R 2 ) higher than 90 and 82% for Cd and Pb, respectively. The maximum cumulative Cd and Pb in the leaching solutions were 18.44 and 16.68%, respectively, which was amended by EDTA and acid rainwater (pH 4.5), and followed by EDDS (pH 4.5), EDDS (pH 6.5), rhamnolipid (0.5 g kg -1 soil, pH 4.5), and rhamnolipid (pH 6.5).

Climatological studies on precipitation features and large-scale atmospheric fields on the heavy rainfall days in the eastern part of Japan from the Baiu to midsummer season

Science.gov (United States)

Matsumoto, Kengo; Kato, Kuranoshin; Otani, Kazuo

2017-04-01

In East Asia the significant subtropical frontal zone called the Meiyu (in China) / Baiu (in Japan) appears in early summer (just before the midsummer) and the huge rainfall is brought due to the frequent appearance of the "heavy rainfall days" (referred to as HRDs hereafter) mainly in that western part. On the other hand, large-scale fields around the front in eastern Japan is rather different from that in western Japan but the total precipitation in the eastern Japan is still considerable compared to that in the other midlatitude regions. Thus, it is also interesting to examine how the rainfall characteristics and large-scale atmospheric fields on HRDs (with more than 50 mm/day) in the eastern Japan in the mature stage of the Baiu season (16 June 15 July), together with those in midsummer (1 31 August). Based on such scientific background, further analyses were performed in this study mainly with the daily and the hourly precipitation data and the NCEP/NCAR re-analysis date from 1971 to 2010, succeeding to our previous results (e.g., EGU2015). As reported at EGU2014 and 2015, about half of HRDs at Tokyo (eastern Japan) were related to the typhoon even in the Baiu season. Interestingly, half of HRDs were characterized by the large contribution of moderate rain less than 10 mm/h. While, the precipitation on HRDs at Tokyo in midsummer was mainly brought by the intense rainfall with more than 10 mm/h, in association with the typhoons. In the present study, we examined the composite meridional structure of the rainfall area along 140E. In the pattern only associated with a typhoons in the Baiu season (Pattern A), the heavy rainfall area (more than 50 mm/day) with large contribution of the intense rain (stronger than 10 mm/h) showed rather wide meridional extension. The area was characterized by the duration of the intermittent enhancement of the rainfall. In the pattern associated with a typhoon and a front (Pattern B), while the contribution ratio of the rainfall

Event-based rainfall-runoff modelling of the Kelantan River Basin

Science.gov (United States)

Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

2014-02-01

Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

Event-based rainfall-runoff modelling of the Kelantan River Basin

International Nuclear Information System (INIS)

Basarudin, Z; Adnan, N A; Latif, A R A; Syafiqah, N; Tahir, W

2014-01-01

Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area

American Samoa Watershed and Coastal Community Data Layers, Utulei, Fagaalu, Fatumafuti 2014

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Data Layers include the following.Flooding: Regions that flood during heavy rainfall.Intermittent Streams: Areas flow as streams during heavy rainfall.Community...

Interdisciplinary Approach for Assessment of Continental River Flood Risk: A Case Study of the Czech Republic

Science.gov (United States)

Ushiyama, Tomoki; Kwak, Youngjoo; Ledvinka, Ondřej; Iwami, Yoichi; Danhelka, Jan

2017-04-01

In this research, GIS-based hydrological model-driven approach produces the distribution of continent-level flood risk based on national-level GIS data. In order to reveal flood hazard, exposure, and vulnerability in a large river basin, the system employs the simplified model such as GFiD2M (Global Flood inundation Depth 2-dimension Model) to calculate the differential inundation depth and the economic loss by pixel-based statistical processing, considering climate and socioeconomic scenarios, the representative concentration pathways emissions and the shared socioeconomic pathways, despite current limitations of data collections and poor data availability. We need new approaches to seek the possibility of its national-scale application, so that the framework can bring (1) improved flood inundation map (i.e., discharge, depth, velocity) using rainfall runoff inundation model, based on the in-situ data (rain-gauge and water level), validated with Earth Observation data, i.e., MODIS, (2) advanced flood forecasting using radar and satellite observed rainfall for national-level operational hydrological observations, (3) potential economic impact with the effect of flood hazard and risk under climate and socioeconomic changes based on rainfall from general circulation model. The preliminary examinations showed the better possibility of a nation-wide application for integrated flood risk management. At the same time, the hazard and risk model were also validated against event-based flood inundation of a national-level flood in the Czech Republic. Within the Czech Republic, although radar rainfall data have been used in operational hydrology for some time, there are also other products capable of warning us about the potential risk of floods. For instance, images from Europe's Sentinel satellites have not been evaluated for their use in Czech hydrology. This research is at the very beginning of a validation and its evaluation, focusing mainly on heavy rainfall and

Evaluation of a compound distribution based on weather pattern subsampling for extreme rainfall in Norway

Directory of Open Access Journals (Sweden)

J. Blanchet

2015-12-01

SCHADEX method for extreme flood estimation. Regional scores of evaluation are used in a split sample framework to compare the MEWP distribution with more general heavy-tailed distributions, in this case the Multi Generalized Pareto Weather Pattern (MGPWP distribution. The analysis shows the clear benefit obtained from seasonal and weather pattern-based subsampling for extreme value estimation. The MEWP distribution is found to have an overall better performance as compared with the MGPWP, which tends to overfit the data and lacks robustness. Finally, we take advantage of the split sample framework to present evidence for an increase in extreme rainfall in the southwestern part of Norway during the period 1979–2009, relative to 1948–1978.

Forecasting Global Rainfall for Points Using ECMWF's Global Ensemble and Its Applications in Flood Forecasting

Science.gov (United States)

Pillosu, F. M.; Hewson, T.; Mazzetti, C.

2017-12-01

Prediction of local extreme rainfall has historically been the remit of nowcasting and high resolution limited area modelling, which represent only limited areas, may not be spatially accurate, give reasonable results only for limited lead times (based statistical post-processing software ("ecPoint-Rainfall, ecPR", operational in 2017) that uses ECMWF Ensemble (ENS) output to deliver global probabilistic rainfall forecasts for points up to day 10. Firstly, ecPR applies a new notion of "remote calibration", which 1) allows us to replicate a multi-centennial training period using only one year of data, and 2) provides forecasts for anywhere in the world. Secondly, the software applies an understanding of how different rainfall generation mechanisms lead to different degrees of sub-grid variability in rainfall totals, and of where biases in the model can be improved upon. A long-term verification has shown that the post-processed rainfall has better reliability and resolution at every lead time if compared with ENS, and for large totals, ecPR outputs have the same skill at day 5 that the raw ENS has at day 1 (ROC area metric). ecPR could be used as input for hydrological models if its probabilistic output is modified accordingly to the inputs requirements for hydrological models. Indeed, ecPR does not provide information on where the highest total is likely to occur inside the gridbox, nor on the spatial distribution of rainfall values nearby. "Scenario forecasts" could be a solution. They are derived from locating the rainfall peak in sensitive positions (e.g. urban areas), and then redistributing the remaining quantities in the gridbox modifying traditional spatial correlation characterization methodologies (e.g. variogram analysis) in order to take account, for instance, of the type of rainfall forecast (stratiform, convective). Such an approach could be a turning point in the field of medium-range global real-time riverine flood forecasts. This presentation will

SHYREG, a national database of flood frequency estimation

Directory of Open Access Journals (Sweden)

Arnaud Patrick

2016-01-01

Full Text Available SHYREG method is a regionalized method for rainfall and flood frequency analysis (FFA. It is based on processes simulation. It couples an hourly rainfall generator with a rainfall-runoff model, simplified enough to be regionalized. The method has been calibrated using all hydro meteorological data available at the national level. In France, that represents about 2800 raingauges of the French Weather Service network and about 1800 stations of the hydrometric National Bank network. Then, the method has been regionalized to provide a rainfall and flow quantiles database. An evaluation of the method was carried out during different thesis works and more recently during the ANR project Extraflo, with the aim of comparing different FFA approaches. The accuracy of the method in estimating rainfall and flow quantiles has been proved, as well as its stability due to a parameterization based on average values. The link with rainfall seems preferable to extrapolation based solely on the flow. Thus, another interest of the method is to take into account extreme flood behaviour with help of rainfall frequency estimation. In addition, the approach is implicitly multi-durational, and only one regionalization meets all the needs in terms hydrological hazards characterisation. For engineering needs and to avoid repeating the method implementation, this method has been applied throughout a 50 meters resolution mesh to provide a complete flood quantiles database over the French territory providing regional information on hydrological hazards. However, it is subject to restrictions related to the nature of the method: the SHYREG flows are “natural”, and do not take into account specific cases like the basins highly influenced by presence of hydraulic works, flood expansion areas, high snowmelt or karsts. Information about these restrictions and uncertainty estimation is provided with this database, which can be consulted via web access.

The dynamics of cultivation and floods in arable lands of Central Argentina

Directory of Open Access Journals (Sweden)

E. F. Viglizzo

2009-04-01

Full Text Available Although floods in watersheds have been associated with land-use change since ancient times, the dynamics of flooding is still incompletely understood. In this paper we explored the relations between rainfall, groundwater level, and cultivation to explain the dynamics of floods in the extremely flat and valuable arable lands of the Quinto river watershed, in central Argentina. The analysis involved an area of 12.4 million hectare during a 26-year period (1978–2003, which comprised two extensive flooding episodes in 1983–1988 and 1996–2003. Supported by information from surveys as well as field and remote sensing measurements, we explored the correlation among precipitation, groundwater levels, flooded area and land use. Flood extension was associated to the dynamics of groundwater level. While no correlation with rainfall was recorded in lowlands, a significant correlation (P<0.01 between groundwater and rainfall in highlands was found when estimations comprise a time lag of one year. Correlations between groundwater level and flood extension were positive in all cases, but while highly significant relations (P<0.01 were found in highlands, non significant relations (P>0.05 predominate in lowlands. Our analysis supports the existence of a cyclic mechanism driven by the reciprocal influence between cultivation and groundwater in highlands. This cycle would involve the following stages: (a cultivation boosts the elevation of groundwater levels through decreased evapotranspiration; (b as groundwater level rises, floods spread causing a decline of land cultivation; (c flooding propitiates higher evapotranspiration favouring its own retraction; (d cultivation expands again following the retreat of floods. Thus, cultivation would trigger a destabilizing feedback self affecting future cultivation in the highlands. It is unlikely that such sequence can work in lowlands. The results suggest that rather than responding directly

A new flooding scheme by horizontal well in thin heavy oil reservoirs

Energy Technology Data Exchange (ETDEWEB)

Liu, H.; Zhang, H.; Wang, M. [China Univ. of Petroleum, Beijing (China). MOE Key Laboratory of Petroleum Engineering ; Wang, Z. [Shengli Oil Field Co. (China). Dept. of Science and Technology]|[SINOPEC, Shengli (China)

2008-10-15

This paper presented a new flooding scheme for single horizontal wells that could improve recovery from thin marginal heavy oil reservoirs or from offshore reservoirs. The scheme involved the use of a multiple tubing string completion in a single wellbore. Special packers were installed within the long completion horizontal interval to establish an injection zone and a production zone. The new flooding scheme also involved simultaneous injection and production. Numerical simulation of the reservoir was used to determine the thickness of the formation and the lower limitation for different viscosities and the optimum time to start steam flooding after steam soaking by economic oil/steam ratio. The peak recovery efficiency of steam flooding was shown to occur when the length of separation section ratio is 0.15 to 0.2. It was concluded that high thermal efficiency in horizontal wells with long completion intervals can be maintained by alternating between steam soaking and steam flooding. Suitable alternation time to steam flooding is a seventh cycle for horizontal wells. Water cut and pressure difference will increase the steam injection rate, and thereby improve the oil production rate. The suitable injection rate for steam flooding is 2.4 t/d.ha.h because of its slow pressure change. 11 refs., 7 figs.

Characterizing fluvial heavy metal pollutions under different rainfall conditions: Implication for aquatic environment protection.

Science.gov (United States)

Zhang, Lixun; Zhao, Bo; Xu, Gang; Guan, Yuntao

2018-09-01

Globally, fluvial heavy metal (HM) pollution has recently become an increasingly severe problem. However, few studies have investigated the variational characteristics of fluvial HMs after rain over long periods (≥1 year). The Dakan River in Xili Reservoir watershed (China) was selected as a case study to investigate pollution levels, influencing factors, and sources of HMs under different rainfall conditions during 2015 and 2016. Fluvial HMs showed evident spatiotemporal variations attributable to the coupled effects of pollution generation and rainfall diffusion. Fluvial HM concentrations were significantly associated with rainfall characteristics (e.g., rainfall intensity, rainfall amount, and antecedent dry period) and river flow, which influenced the generation and the transmission of fluvial HMs in various ways. Moreover, this interrelationship depended considerably on the HM type and particle size distribution. Mn, Pb, Cr, and Ni were major contributors to high values of the comprehensive pollution index; therefore, they should be afforded special attention. Additionally, quantitative source apportionment of fluvial HMs was conducted by combining principal component analysis with multiple linear regression and chemical mass balance models to obtain comprehensive source profiles. Finally, an environment-friendly control strategy coupling "source elimination" and "transport barriers" was proposed for aquatic environment protection. Copyright © 2018 Elsevier B.V. All rights reserved.

Hydrodynamic modelling of extreme flood events in the Kashmir valley in India

Science.gov (United States)

Jain, Manoj; Parvaze, Sabah

2017-04-01

Floods are one of the most predominant, costly and deadly hazards of all natural vulnerabilities. Every year, floods exert a heavy toll on human life and property in many parts of the world. The prediction of river stages and discharge during flood extremes plays a vital role in planning structural and non-structural measures of flood management. The predictions are also valuable to prepare the flood inundation maps and river floodplain zoning. In the Kashmir Valley, floods occur mainly and very often in the Jhelum Basin mostly due to extreme precipitation events and rugged mountainous topography of the basin. These floods cause extreme damage to life and property in the valley from time to time. Excessive rainfall, particularly in higher sub-catchments causes the snow to melt resulting in excessive runoff downhill to the streams causing floods in the Kashmir Valley where Srinagar city is located. However, very few hydrological studies have been undertaken for the Jhelum Basin mainly due to non-availability of hydrological data due to very complex mountainous terrain. Therefore, the present study has been conducted to model the extreme flood events in the Jhelum Basin in Kashmir Valley. An integrated NAM and MIKE 11 HD model has been setup for Jhelum basin up to Ram Munshi Bagh gauging site and then four most extreme historical flood events in the time series has been analyzed separately including the most recent and most extreme flood event of 2014. In September 2014, the Kashmir Valley witnessed the most severe flood in the past 60 years due to catastrophic rainfall from 1st to 6th September wherein the valley received unprecedented rainfall of more than 650 mm in just 3 days breaking record of many decades. The MIKE 11 HD and NAM model has been calibrated using 21 years (1985-2005) data and validated using 9 years (2006-2014) data. The efficiency indices of the model for calibration and validation period is 0.749 and 0.792 respectively. The model simulated

On the use of Cox regression to examine the temporal clustering of flooding and heavy precipitation across the central United States

Science.gov (United States)

Mallakpour, Iman; Villarini, Gabriele; Jones, Michael P.; Smith, James A.

2017-08-01

The central United States is plagued by frequent catastrophic flooding, such as the flood events of 1993, 2008, 2011, 2013, 2014 and 2016. The goal of this study is to examine whether it is possible to describe the occurrence of flood and heavy precipitation events at the sub-seasonal scale in terms of variations in the climate system. Daily streamflow and precipitation time series over the central United States (defined here to include North Dakota, South Dakota, Nebraska, Kansas, Missouri, Iowa, Minnesota, Wisconsin, Illinois, West Virginia, Kentucky, Ohio, Indiana, and Michigan) are used in this study. We model the occurrence/non-occurrence of a flood and heavy precipitation event over time using regression models based on Cox processes, which can be viewed as a generalization of Poisson processes. Rather than assuming that an event (i.e., flooding or precipitation) occurs independently of the occurrence of the previous one (as in Poisson processes), Cox processes allow us to account for the potential presence of temporal clustering, which manifests itself in an alternation of quiet and active periods. Here we model the occurrence/non-occurrence of flood and heavy precipitation events using two climate indices as time-varying covariates: the Arctic Oscillation (AO) and the Pacific-North American pattern (PNA). We find that AO and/or PNA are important predictors in explaining the temporal clustering in flood occurrences in over 78% of the stream gages we considered. Similar results are obtained when working with heavy precipitation events. Analyses of the sensitivity of the results to different thresholds used to identify events lead to the same conclusions. The findings of this work highlight that variations in the climate system play a critical role in explaining the occurrence of flood and heavy precipitation events at the sub-seasonal scale over the central United States.

Persistent after-effects of heavy rain on concentrations of ice nuclei and rainfall suggest a biological cause

Science.gov (United States)

Bigg, E. K.; Soubeyrand, S.; Morris, C. E.

2015-03-01

Rainfall is one of the most important aspects of climate, but the extent to which atmospheric ice nuclei (IN) influence its formation, quantity, frequency, and location is not clear. Microorganisms and other biological particles are released following rainfall and have been shown to serve as efficient IN, in turn impacting cloud and precipitation formation. Here we investigated potential long-term effects of IN on rainfall frequency and quantity. Differences in IN concentrations and rainfall after and before days of large rainfall accumulation (i.e., key days) were calculated for measurements made over the past century in southeastern and southwestern Australia. Cumulative differences in IN concentrations and daily rainfall quantity and frequency as a function of days from a key day demonstrated statistically significant increasing logarithmic trends (R2 > 0.97). Based on observations that cumulative effects of rainfall persisted for about 20 days, we calculated cumulative differences for the entire sequence of key days at each site to create a historical record of how the differences changed with time. Comparison of pre-1960 and post-1960 sequences most commonly showed smaller rainfall totals in the post-1960 sequences, particularly in regions downwind from coal-fired power stations. This led us to explore the hypothesis that the increased leaf surface populations of IN-active bacteria due to rain led to a sustained but slowly diminishing increase in atmospheric concentrations of IN that could potentially initiate or augment rainfall. This hypothesis is supported by previous research showing that leaf surface populations of the ice-nucleating bacterium Pseudomonas syringae increased by orders of magnitude after heavy rain and that microorganisms become airborne during and after rain in a forest ecosystem. At the sites studied in this work, aerosols that could have initiated rain from sources unrelated to previous rainfall events (such as power stations) would

Numerical Simulation of Heavy Rainfall in August 2014 over Japan and Analysis of Its Sensitivity to Sea Surface Temperature

Directory of Open Access Journals (Sweden)

Yuki Minamiguchi

2018-02-01

Full Text Available This study evaluated the performance of the Weather Research and Forecasting (WRF model version 3.7 for simulating a series of rainfall events in August 2014 over Japan and investigated the impact of uncertainty in sea surface temperature (SST on simulated rainfall in the record-high precipitation period. WRF simulations for the heavy rainfall were conducted for six different cases. The heavy rainfall events caused by typhoons and rain fronts were similarly accurately reproduced by three cases: the TQW_5km case with grid nudging for air temperature, humidity, and wind and with a horizontal resolution of 5 km; W_5km with wind nudging and 5-km resolution; and W_2.5km with wind nudging and 2.5-km resolution. Because the nudging for air temperature and humidity in TQW_5km suppresses the influence of SST change, and because W_2.5km requires larger computational load, W_5km was selected as the baseline case for a sensitivity analysis of SST. In the sensitivity analysis, SST around Japan was homogeneously changed by 1 K from the original SST data. The analysis showed that the SST increase led to a larger amount of precipitation in the study period in Japan, with the mean increase rate of precipitation being 13 ± 8% K−1. In addition, 99 percentile precipitation (100 mm d−1 in the baseline case increased by 13% K−1 of SST warming. These results also indicate that an uncertainty of approximately 13% in the simulated heavy rainfall corresponds to an uncertainty of 1 K in SST data around Japan in the study period.

Constraining continuous rainfall simulations for derived design flood estimation

Science.gov (United States)

Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.

2016-11-01

Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.

Rainfall, runoff and sediment transport in a Mediterranean mountainous catchment.

Science.gov (United States)

Tuset, J; Vericat, D; Batalla, R J

2016-01-01

The relation between rainfall, runoff, erosion and sediment transport is highly variable in Mediterranean catchments. Their relation can be modified by land use changes and climate oscillations that, ultimately, will control water and sediment yields. This paper analyses rainfall, runoff and sediment transport relations in a meso-scale Mediterranean mountain catchment, the Ribera Salada (NE Iberian Peninsula). A total of 73 floods recorded between November 2005 and November 2008 at the Inglabaga Sediment Transport Station (114.5 km(2)) have been analysed. Suspended sediment transport and flow discharge were measured continuously. Rainfall data was obtained by means of direct rain gauges and daily rainfall reconstructions from radar information. Results indicate that the annual sediment yield (2.3 t km(-1) y(-1) on average) and the flood-based runoff coefficients (4.1% on average) are low. The Ribera Salada presents a low geomorphological and hydrological activity compared with other Mediterranean mountain catchments. Pearson correlations between rainfall, runoff and sediment transport variables were obtained. The hydrological response of the catchment is controlled by the base flows. The magnitude of suspended sediment concentrations is largely correlated with flood magnitude, while sediment load is correlated with the amount of direct runoff. Multivariate analysis shows that total suspended load can be predicted by integrating rainfall and runoff variables. The total direct runoff is the variable with more weight in the equation. Finally, three main hydro-sedimentary phases within the hydrological year are defined in this catchment: (a) Winter, where the catchment produces only water and very little sediment; (b) Spring, where the majority of water and sediment is produced; and (c) Summer-Autumn, when little runoff is produced but significant amount of sediments is exported out of the catchment. Results show as land use and climate change may have an important

Vulnerability assessment of Central-East Sardinia (Italy to extreme rainfall events

Directory of Open Access Journals (Sweden)

A. Bodini

2010-01-01

Full Text Available In Sardinia (Italy, the highest frequency of extreme events is recorded in the Central-East area (3–4 events per year. The presence of high and steep mountains near the sea on the central and south-eastern coast, causes an East-West precipitation gradient in autumn especially, due to hot and moist currents coming from Africa. Soil structure and utilization make this area highly vulnerable to flash flooding and landslides. The specific purpose of this work is to provide a description of the heavy rainfall phenomenon on a statistical basis. The analysis mainly focuses on i the existence of trends in heavy rainfall and ii the characterization of the distribution of extreme events. First, to study possible trends in extreme events a few indices have been analyzed by the linear regression test. The analysis has been carried out at annual and seasonal scales. Then, extreme values analysis has been carried out by fitting a Generalized Pareto Distribution (GPD to the data. As far as trends are concerned, different results are obtained at the two temporal scales: significant trends are obtained at the seasonal scale which are masked at the annual scale. By combining trend analysis and GPD analysis, the vulnerability of the study area to the occurrence of heavy rainfall has been characterized. Therefore, this work might support the improvement of land use planning and the application of suitable prevention systems. Future work will consider the extension of the analysis to all Sardinia and the application of statistical methods taking into account the spatial correlation of extreme events.

Dam pre-release as an important operation strategy in reducing flood impact in Malaysia

Science.gov (United States)

Hidayah Ishak, Nurul; Mustafa Hashim, Ahmad

2018-03-01

The 2014 flood was reported to be one of the worst natural disaster has ever affected several states in the northern part of Peninsular Malaysia. Overwhelming rainfall was noted as one of the main factors causing such impact, which was claimed to be unprecedented to some extent. The state of Perak, which is blessed with four cascading dams had also experienced flood damage at a scale that was considered the worst in history. The rainfall received had caused the dam to reach danger level that necessitated additional discharge to be released. Safety of the dams was of great importance and such unavoidable additional discharge was allowed to avoid catastrophic failure of the dam structures. This paper discusses the dam pre-release as a significant dam management strategy in reducing flood impact. An important balance between required dam storage to be maintained and the risk element that can be afforded is the crucial factor in such enhanced operation strategy. While further possibility in developing a carefully engineered dam pre-release strategy can be explored for dam operation in Malaysia, this has already been introduced in some developed countries. Australia and South Africa are examples where pre-release has been practiced and proven to reduce flood risk. The concept involves controlling the dam lake level throughout the year, in reference to the rainfall data and the hydrological properties for the catchment area of the dams. Plentiful data analysis need to be done in contemplation of producing the optimal pre-release model. The amount of heavy rainfalls received is beyond human control but the distribution of the discharge from the dams can be further managed with the appropriate pre-release strategy.

High-resolution simulation and forecasting of Jeddah floods using WRF version 3.5

KAUST Repository

Deng, Liping

2013-12-01

Modeling flash flood events in arid environments is a difficult but important task that has impacts on both water resource related issues and also emergency management and response. The challenge is often related to adequately describing the precursor intense rainfall events that cause these flood responses, as they are generally poorly simulated and forecast. Jeddah, the second largest city in the Kingdom of Saudi Arabia, has suffered from a number of flash floods over the last decade, following short-intense rainfall events. The research presented here focuses on examining four historic Jeddah flash floods (Nov. 25-26 2009, Dec. 29-30 2010, Jan. 14-15 2011 and Jan. 25-26 2011) and investigates the feasibility of using numerical weather prediction models to achieve a more realistic simulation of these flood-producing rainfall events. The Weather Research and Forecasting (WRF) model (version 3.5) is used to simulate precipitation and meteorological conditions via a high-resolution inner domain (1-km) around Jeddah. A range of different convective closure and microphysics parameterization, together with high-resolution (4-km) sea surface temperature data are employed. Through examining comparisons between the WRF model output and in-situ, radar and satellite data, the characteristics and mechanism producing the extreme rainfall events are discussed and the capacity of the WRF model to accurately forecast these rainstorms is evaluated.

High-resolution simulation and forecasting of Jeddah floods using WRF version 3.5

KAUST Repository

Deng, Liping; McCabe, Matthew; Stenchikov, Georgiy L.; Evans, Jason; Kucera, Paul

2013-01-01

Modeling flash flood events in arid environments is a difficult but important task that has impacts on both water resource related issues and also emergency management and response. The challenge is often related to adequately describing the precursor intense rainfall events that cause these flood responses, as they are generally poorly simulated and forecast. Jeddah, the second largest city in the Kingdom of Saudi Arabia, has suffered from a number of flash floods over the last decade, following short-intense rainfall events. The research presented here focuses on examining four historic Jeddah flash floods (Nov. 25-26 2009, Dec. 29-30 2010, Jan. 14-15 2011 and Jan. 25-26 2011) and investigates the feasibility of using numerical weather prediction models to achieve a more realistic simulation of these flood-producing rainfall events. The Weather Research and Forecasting (WRF) model (version 3.5) is used to simulate precipitation and meteorological conditions via a high-resolution inner domain (1-km) around Jeddah. A range of different convective closure and microphysics parameterization, together with high-resolution (4-km) sea surface temperature data are employed. Through examining comparisons between the WRF model output and in-situ, radar and satellite data, the characteristics and mechanism producing the extreme rainfall events are discussed and the capacity of the WRF model to accurately forecast these rainstorms is evaluated.

Flash floods warning technique based on wireless communication networks data

Science.gov (United States)

David, Noam; Alpert, Pinhas; Messer, Hagit

2010-05-01

Flash floods can occur throughout or subsequent to rainfall events, particularly in cases where the precipitation is of high-intensity. Unfortunately, each year these floods cause severe property damage and heavy casualties. At present, there are no sufficient real time flash flood warning facilities found to cope with this phenomenon. Here we show the tremendous potential of flash floods advanced warning based on precipitation measurements of commercial microwave links. As was recently shown, wireless communication networks supply high resolution precipitation measurements at ground level while often being situated in flood prone areas, covering large parts of these hazardous regions. We present the flash flood warning potential of the wireless communication system for two different cases when floods occurred at the Judean desert and at the northern Negev in Israel. In both cases, an advanced warning regarding the hazard could have been announced based on this system. • This research was supported by THE ISRAEL SCIENCE FOUNDATION (grant No. 173/08). This work was also supported by a grant from the Yeshaya Horowitz Association, Jerusalem. Additional support was given by the PROCEMA-BMBF project and by the GLOWA-JR BMBF project.

Monitoring and Mapping the Hurricane Harvey Flooding in Houston, Texas.

Science.gov (United States)

Balaji Bhaskar, M. S.

2017-12-01

Monitoring and Mapping the Hurricane Harvey Flooding in Houston, Texas.Urban flooding is a hazard that causes major destruction and loss of life. High intense precipitation events have increased significantly in Houston, Texas in recent years resulting in frequent river and bayou flooding. Many of the historical storm events such as Allison, Rita and Ike have caused several billion dollars in losses for the Houston-Galveston Region. A category 4 Hurricane Harvey made landfall on South Texas resulting in heavy precipitation from Aug 25 to 29 of 2017. About 1 trillion gallons of water fell across Harris County over a 4-day period. This amount of water covers Harris County's 1,800 square miles with an average of 33 inches of water. The long rain event resulted in an average 40inch rainfall across the area in several rain gauges and the maximum rainfall of 49.6 inches was recorded near Clear Creek. The objectives of our study are to 1) Process the Geographic Information System (GIS) and satellite data from the pre and post Hurricane Harvey event in Houston, Texas and 2) Analyze the satellite imagery to map the nature and pattern of the flooding in Houston-Galveston Region. The GIS data of the study area was downloaded and processed from the various publicly available resources such as Houston Galveston Area Council (HGAC), Texas Commission of Environmental Quality (TCEQ) and Texas Natural Resource Information Systems (TNRIS). The satellite data collected soon after the Harvey flooding event were downloaded and processed using the ERDAS image processing software. The flood plain areas surrounding the Brazos River, Buffalo Bayou and the Addicks Barker reservoirs showed severe inundation. The different watershed areas affected by the catastrophic flooding in the wake of Hurricane Harvey were mapped and compared with the pre flooding event.

Analysis of rainfall distribution in Kelantan river basin, Malaysia

Science.gov (United States)

Che Ros, Faizah; Tosaka, Hiroyuki

2018-03-01

Using rainfall gauge on its own as input carries great uncertainties regarding runoff estimation, especially when the area is large and the rainfall is measured and recorded at irregular spaced gauging stations. Hence spatial interpolation is the key to obtain continuous and orderly rainfall distribution at unknown points to be the input to the rainfall runoff processes for distributed and semi-distributed numerical modelling. It is crucial to study and predict the behaviour of rainfall and river runoff to reduce flood damages of the affected area along the Kelantan river. Thus, a good knowledge on rainfall distribution is essential in early flood prediction studies. Forty six rainfall stations and their daily time-series were used to interpolate gridded rainfall surfaces using inverse-distance weighting (IDW), inverse-distance and elevation weighting (IDEW) methods and average rainfall distribution. Sensitivity analysis for distance and elevation parameters were conducted to see the variation produced. The accuracy of these interpolated datasets was examined using cross-validation assessment.

Rainfall reliability, drought and flood vulnerability in Botswana ...

African Journals Online (AJOL)

Rainfall data from 14 stations (cities, towns and major villages) spanning 26 years (1970 to 1995) were used to calculate reliability and vulnerability of rainfall in Botswana. Time series data for 72 years were generated from the long-term rainfall gauging stations and the number of wet and dry years determined. Apart from ...

Future changes in atmospheric rivers and their implications for winter flooding in Britain

International Nuclear Information System (INIS)

Lavers, David A; Allan, Richard P; Brayshaw, David J; Villarini, Gabriele; Lloyd-Hughes, Benjamin; Wade, Andrew J

2013-01-01

Within the warm conveyor belt of extra-tropical cyclones, atmospheric rivers (ARs) are the key synoptic features which deliver the majority of poleward water vapour transport, and are associated with episodes of heavy and prolonged rainfall. ARs are responsible for many of the largest winter floods in the mid-latitudes resulting in major socioeconomic losses; for example, the loss from United Kingdom (UK) flooding in summer/winter 2012 is estimated to be about $1.6 billion in damages. Given the well-established link between ARs and peak river flows for the present day, assessing how ARs could respond under future climate projections is of importance in gauging future impacts from flooding. We show that North Atlantic ARs are projected to become stronger and more numerous in the future scenarios of multiple simulations from five state-of-the-art global climate models (GCMs) in the fifth Climate Model Intercomparison Project (CMIP5). The increased water vapour transport in projected ARs implies a greater risk of higher rainfall totals and therefore larger winter floods in Britain, with increased AR frequency leading to more flood episodes. In the high emissions scenario (RCP8.5) for 2074–2099 there is an approximate doubling of AR frequency in the five GCMs. Our results suggest that the projected change in ARs is predominantly a thermodynamic response to warming resulting from anthropogenic radiative forcing. (letter)

Skill of Predicting Heavy Rainfall Over India: Improvement in Recent Years Using UKMO Global Model

Science.gov (United States)

Sharma, Kuldeep; Ashrit, Raghavendra; Bhatla, R.; Mitra, A. K.; Iyengar, G. R.; Rajagopal, E. N.

2017-11-01

The quantitative precipitation forecast (QPF) performance for heavy rains is still a challenge, even for the most advanced state-of-art high-resolution Numerical Weather Prediction (NWP) modeling systems. This study aims to evaluate the performance of UK Met Office Unified Model (UKMO) over India for prediction of high rainfall amounts (>2 and >5 cm/day) during the monsoon period (JJAS) from 2007 to 2015 in short range forecast up to Day 3. Among the various modeling upgrades and improvements in the parameterizations during this period, the model horizontal resolution has seen an improvement from 40 km in 2007 to 17 km in 2015. Skill of short range rainfall forecast has improved in UKMO model in recent years mainly due to increased horizontal and vertical resolution along with improved physics schemes. Categorical verification carried out using the four verification metrics, namely, probability of detection (POD), false alarm ratio (FAR), frequency bias (Bias) and Critical Success Index, indicates that QPF has improved by >29 and >24% in case of POD and FAR. Additionally, verification scores like EDS (Extreme Dependency Score), EDI (Extremal Dependence Index) and SEDI (Symmetric EDI) are used with special emphasis on verification of extreme and rare rainfall events. These scores also show an improvement by 60% (EDS) and >34% (EDI and SEDI) during the period of study, suggesting an improved skill of predicting heavy rains.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Science.gov (United States)

Hassan, Zulkarnain; Haidir, Ahmad; Saad, Farah Naemah Mohd; Ayob, Afizah; Rahim, Mustaqqim Abdul; Ghazaly, Zuhayr Md.

2018-03-01

The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015) data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM), as compared to Southwest monsoon (SWM). Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Spatial Interpolation of Historical Seasonal Rainfall Indices over Peninsular Malaysia

Directory of Open Access Journals (Sweden)

Hassan Zulkarnain

2018-01-01

Full Text Available The inconsistency in inter-seasonal rainfall due to climate change will cause a different pattern in the rainfall characteristics and distribution. Peninsular Malaysia is not an exception for this inconsistency, in which it is resulting extreme events such as flood and water scarcity. This study evaluates the seasonal patterns in rainfall indices such as total amount of rainfall, the frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity in Peninsular Malaysia. 40 years (1975-2015 data records have been interpolated using Inverse Distance Weighted method. The results show that the formation of rainfall characteristics are significance during the Northeast monsoon (NEM, as compared to Southwest monsoon (SWM. Also, there is a high rainfall intensity and frequency related to extreme over eastern coasts of Peninsula during the NEM season.

Downscaling of rainfall in Peru using Generalised Linear Models

Science.gov (United States)

Bergin, E.; Buytaert, W.; Onof, C.; Wheater, H.

2012-04-01

The assessment of water resources in the Peruvian Andes is particularly important because the Peruvian economy relies heavily on agriculture. Much of the agricultural land is situated near to the coast and relies on large quantities of water for irrigation. The simulation of synthetic rainfall series is thus important to evaluate the reliability of water supplies for current and future scenarios of climate change. In addition to water resources concerns, there is also a need to understand extreme heavy rainfall events, as there was significant flooding in Machu Picchu in 2010. The region exhibits a reduction of rainfall in 1983, associated with El Nino Southern Oscillation (SOI). NCEP Reanalysis 1 data was used to provide weather variable data. Correlations were calculated for several weather variables using raingauge data in the Andes. These were used to evaluate teleconnections and provide suggested covariates for the downscaling model. External covariates used in the model include sea level pressure and sea surface temperature over the region of the Humboldt Current. Relative humidity and temperature data over the region are also included. The SOI teleconnection is also used. Covariates are standardised using observations for 1960-1990. The GlimClim downscaling model was used to fit a stochastic daily rainfall model to 13 sites in the Peruvian Andes. Results indicate that the model is able to reproduce rainfall statistics well, despite the large area used. Although the correlation between individual rain gauges is generally quite low, all sites are affected by similar weather patterns. This is an assumption of the GlimClim downscaling model. Climate change scenarios are considered using several GCM outputs for the A1B scenario. GCM data was corrected for bias using 1960-1990 outputs from the 20C3M scenario. Rainfall statistics for current and future scenarios are compared. The region shows an overall decrease in mean rainfall but with an increase in variance.

A Cascading Storm-Flood-Landslide Guidance System: Development and Application in China

Science.gov (United States)

Zeng, Ziyue; Tang, Guoqiang; Long, Di; Ma, Meihong; Hong, Yang

2016-04-01

Flash floods and landslides, triggered by storms, often interact and cause cascading effects on human lives and property. Satellite remote sensing data has significant potential use in analysis of these natural hazards. As one of the regions continuously affected by severe flash floods and landslides, Yunnan Province, located in Southwest China, has a complex mountainous hydrometeorology and suffers from frequent heavy rainfalls from May through to late September. Taking Yunnan as a test-bed, this study proposed a Cascading Storm-Flood-Landslide Guidance System to progressively analysis and evaluate the risk of the multi-hazards based on multisource satellite remote sensing data. First, three standardized rainfall amounts (average daily amount in flood seasons, maximum 1h and maximum 6h amount) from the products of Topical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) were used as rainfall indicators to derive the StorM Hazard Index (SMHI). In this process, an integrated approach of the Analytic Hierarchy Process (AHP) and the Information-Entropy theory was adopted to determine the weight of each indicator. Then, land cover and vegetation cover data from the Moderate Resolution Imaging Spectroradiometer (MODIS) products, soil type from the Harmonized World Soil Database (HWSD) soil map, and slope from the Shuttle Radar Topography Mission (SRTM) data were add as semi-static geo-topographical indicators to derive the Flash Flood Hazard Index (FFHI). Furthermore, three more relevant landslide-controlling indicators, including elevation, slope angle and soil text were involved to derive the LandSlide Hazard Index (LSHI). Further inclusion of GDP, population and prevention measures as vulnerability indicators enabled to consecutively predict the risk of storm to flash flood and landslide, respectively. Consequently, the spatial patterns of the hazard indices show that the southeast of Yunnan has more possibility to encounter with storms

Going beyond the flood insurance rate map: insights from flood hazard map co-production

Directory of Open Access Journals (Sweden)

A. Luke

2018-04-01

Full Text Available Flood hazard mapping in the United States (US is deeply tied to the National Flood Insurance Program (NFIP. Consequently, publicly available flood maps provide essential information for insurance purposes, but they do not necessarily provide relevant information for non-insurance aspects of flood risk management (FRM such as public education and emergency planning. Recent calls for flood hazard maps that support a wider variety of FRM tasks highlight the need to deepen our understanding about the factors that make flood maps useful and understandable for local end users. In this study, social scientists and engineers explore opportunities for improving the utility and relevance of flood hazard maps through the co-production of maps responsive to end users' FRM needs. Specifically, two-dimensional flood modeling produced a set of baseline hazard maps for stakeholders of the Tijuana River valley, US, and Los Laureles Canyon in Tijuana, Mexico. Focus groups with natural resource managers, city planners, emergency managers, academia, non-profit, and community leaders refined the baseline hazard maps by triggering additional modeling scenarios and map revisions. Several important end user preferences emerged, such as (1 legends that frame flood intensity both qualitatively and quantitatively, and (2 flood scenario descriptions that report flood magnitude in terms of rainfall, streamflow, and its relation to an historic event. Regarding desired hazard map content, end users' requests revealed general consistency with mapping needs reported in European studies and guidelines published in Australia. However, requested map content that is not commonly produced included (1 standing water depths following the flood, (2 the erosive potential of flowing water, and (3 pluvial flood hazards, or flooding caused directly by rainfall. We conclude that the relevance and utility of commonly produced flood hazard maps can be most improved by illustrating

Population trends of antelopes in Waza National Park (Cameroon) from 1960 to 2001: The interacting effects of rainfall, flooding and human interventions

NARCIS (Netherlands)

Scholte, P.; Adam, S.; Serge, B.K.

2007-01-01

Antelopes are prominent wildlife in Waza National Park, situated in Sahelo-Sudanian Cameroon, which has witnessed dramatic changes in rainfall and flooding. To assess their impacts, we reviewed 26 aerial and terrestrial surveys, comprising total, transect and localized counts. Estimated numbers of

Modeling of the solid-solution partitioning of heavy metals and arsenic in embanked flood plain soils of the rivers Rhine and Meuse

NARCIS (Netherlands)

Schröder, T.J.; Hiemstra, T.; Vink, J.P.M.

2005-01-01

The aim of this study is to predict the solid-solution partitioning of heavy metals in river flood plain soils. We compared mechanistic geochemical modeling with a statistical approach. To characterize the heavy metal contamination of embanked river flood plain soils in The Netherlands, we collected

Linking Science of Flood Forecasts to Humanitarian Actions for Improved Preparedness and Effective Response

Science.gov (United States)

Uprety, M.; Dugar, S.; Gautam, D.; Kanel, D.; Kshetri, M.; Kharbuja, R. G.; Acharya, S. H.

2017-12-01

Advances in flood forecasting have provided opportunities for humanitarian responders to employ a range of preparedness activities at different forecast time horizons. Yet, the science of prediction is less understood and realized across the humanitarian landscape, and often preparedness plans are based upon average level of flood risk. Working under the remit of Forecast Based Financing (FbF), we present a pilot from Nepal on how available flood and weather forecast products are informing specific pre-emptive actions in the local preparedness and response plans, thereby supporting government stakeholders and humanitarian agencies to take early actions before an impending flood event. In Nepal, forecasting capabilities are limited but in a state of positive flux. Whilst local flood forecasts based upon rainfall-runoff models are yet to be operationalized, streamflow predictions from Global Flood Awareness System (GLoFAS) can be utilized to plan and implement preparedness activities several days in advance. Likewise, 3-day rainfall forecasts from Nepal Department of Hydrology and Meteorology (DHM) can further inform specific set of early actions for potential flash floods due to heavy precipitation. Existing community based early warning systems in the major river basins of Nepal are utilizing real time monitoring of water levels and rainfall together with localised probabilistic flood forecasts which has increased warning lead time from 2-3 hours to 7-8 hours. Based on these available forecast products, thresholds and trigger levels have been determined for different flood scenarios. Matching these trigger levels and assigning responsibilities to relevant actors for early actions, a set of standard operating procedures (SOPs) are being developed, broadly covering general preparedness activities and science informed anticipatory actions for different forecast lead times followed by the immediate response activities. These SOPs are currently being rolled out and

Towards Water Sensitive City: Lesson Learned From Bogor Flood Hazard in 2017

Science.gov (United States)

Ramdhan, Muhammad; Arifin, Hadi Susilo; Suharnoto, Yuli; Tarigan, Suria Darma

2018-02-01

Bogor known as rain city and it's located at an altitude range of 190-330 meters above sea level. In February 2017 Bogor experienced a series of natural disasters related to heavy rainfall that fell during that time. The hazard in the form of flash floods that cause casualties was shocked, due to the location of Bogor city that located in the foothills with a fairly steep slope. There is a problem with the drainage system in the city of Bogor. Australia Indonesia Center in cooperation with Bogor city government held a focus group discussion to seek a permanent solution for the problems and so that similar incidents do not occur in the future.

Floods of June-July 1957 in Indiana

Science.gov (United States)

Schoppenhorst, Charles E.

1958-01-01

The floods of June-July 1957 exceeded those previously known on some of the tributaries of the Wabash and White Rivers in central Indiana. Six lives were lost, 1,282 dwellings were damaged, and 125 business places were flooded. Heavy rains of June 27 and 28 resulted from remnants of Hurricane Audrey meeting a front that lay across central Indiana. Heaviest rainfall reported for the storm period at a U.S. Weather Bureau station was 10.15 inches at Rockville. Previous maximum stages during the period of record were exceeded at 12 gaging stations. The peak stage on Raccoon Creek at Mansfield exceeded the previous maximum known stage, which occurred in 1875. One of the notable rates of discharge recorded was 245 cfs per square mile from a drainage area of 440 square miles on Raccoon Creek at Coxville.

Urban pluvial flood prediction

DEFF Research Database (Denmark)

Thorndahl, Søren Liedtke; Nielsen, Jesper Ellerbæk; Jensen, David Getreuer

2016-01-01

Flooding produced by high-intensive local rainfall and drainage system capacity exceedance can have severe impacts in cities. In order to prepare cities for these types of flood events – especially in the future climate – it is valuable to be able to simulate these events numerically both...... historically and in real-time. There is a rather untested potential in real-time prediction of urban floods. In this paper radar data observations with different spatial and temporal resolution, radar nowcasts of 0–2 h lead time, and numerical weather models with lead times up to 24 h are used as inputs...... to an integrated flood and drainage systems model in order to investigate the relative difference between different inputs in predicting future floods. The system is tested on a small town Lystrup in Denmark, which has been flooded in 2012 and 2014. Results show it is possible to generate detailed flood maps...

Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling

OpenAIRE

Tramblay, Yves; Bouvier, Christophe; Martin, C.; Didon-Lescot, J. F.; Todorovik, D.; Domergue, J. M.

2010-01-01

Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture,...

Effect of catchment properties and flood generation regime on copula selection for bivariate flood frequency analysis

Science.gov (United States)

Filipova, Valeriya; Lawrence, Deborah; Klempe, Harald

2018-02-01

Applying copula-based bivariate flood frequency analysis is advantageous because the results provide information on both the flood peak and volume. More data are, however, required for such an analysis, and it is often the case that only data series with a limited record length are available. To overcome this issue of limited record length, data regarding climatic and geomorphological properties can be used to complement statistical methods. In this paper, we present a study of 27 catchments located throughout Norway, in which we assess whether catchment properties, flood generation processes and flood regime have an effect on the correlation between flood peak and volume and, in turn, on the selection of copulas. To achieve this, the annual maximum flood events were first classified into events generated primarily by rainfall, snowmelt or a combination of these. The catchments were then classified into flood regime, depending on the predominant flood generation process producing the annual maximum flood events. A contingency table and Fisher's exact test were used to determine the factors that affect the selection of copulas in the study area. The results show that the two-parameter copulas BB1 and BB7 are more commonly selected in catchments with high steepness, high mean annual runoff and rainfall flood regime. These findings suggest that in these types of catchments, the dependence structure between flood peak and volume is more complex and cannot be modeled effectively using a one-parameter copula. The results illustrate that by relating copula types to flood regime and catchment properties, additional information can be supplied for selecting copulas in catchments with limited data.

Levee reliability analyses for various flood return periods - a case study in southern Taiwan

Science.gov (United States)

Huang, W.-C.; Yu, H.-W.; Weng, M.-C.

2015-04-01

In recent years, heavy rainfall conditions have caused disasters around the world. To prevent losses by floods, levees have often been constructed in inundation-prone areas. This study performed reliability analyses for the Chiuliao First Levee in southern Taiwan. The failure-related parameters were the water level, the scouring depth, and the in situ friction angle. Three major failure mechanisms were considered: the slope sliding failure of the levee and the sliding and overturning failures of the retaining wall. When the variability of the in situ friction angle and the scouring depth are considered for various flood return periods, the variations of the factor of safety for the different failure mechanisms show that the retaining wall sliding and overturning failures are more sensitive to the change of the friction angle. When the flood return period is greater than 2 years, the levee could fail with slope sliding for all values of the water level difference. The results of levee stability analysis considering the variability of different parameters could aid engineers in designing the levee cross sections, especially with potential failure mechanisms in mind.

Hurricane Harvey Riverine Flooding: Part 1 - Reconstruction of Hurricane Harvey Flooding for Harris County, TX using a GPU-accelerated 2D flood model for post-flood hazard analysis

Science.gov (United States)

Kalyanapu, A. J.; Dullo, T. T.; Gangrade, S.; Kao, S. C.; Marshall, R.; Islam, S. R.; Ghafoor, S. K.

2017-12-01

Hurricane Harvey that made landfall in the southern Texas this August is one of the most destructive hurricanes during the 2017 hurricane season. During its active period, many areas in coastal Texas region received more than 40 inches of rain. This downpour caused significant flooding resulting in about 77 casualties, displacing more than 30,000 people, inundating hundreds of thousands homes and is currently estimated to have caused more than $70 billion in direct damage. One of the significantly affected areas is Harris County where the city of Houston, TX is located. Covering over two HUC-8 drainage basins ( 2702 mi2), this county experienced more than 80% of its annual average rainfall during this event. This study presents an effort to reconstruct flooding caused by extreme rainfall due to Hurricane Harvey in Harris County, Texas. This computationally intensive task was performed at a 30-m spatial resolution using a rapid flood model called Flood2D-GPU, a graphics processing unit (GPU) accelerated model, on Oak Ridge National Laboratory's (ORNL) Titan Supercomputer. For this task, the hourly rainfall estimates from the National Center for Environmental Prediction Stage IV Quantitative Precipitation Estimate were fed into the Variable Infiltration Capacity (VIC) hydrologic model and Routing Application for Parallel computation of Discharge (RAPID) routing model to estimate flow hydrographs at 69 locations for Flood2D-GPU simulation. Preliminary results of the simulation including flood inundation extents, maps of flood depths and inundation duration will be presented. Future efforts will focus on calibrating and validating the simulation results and assessing the flood damage for better understanding the impacts made by Hurricane Harvey.

Spillway design implications resulting from changes in rainfall extremes

International Nuclear Information System (INIS)

Muzik, I.

1999-01-01

A study was conducted in order to determine how serious implications regarding spillway design of small dams would result from changes in flood frequencies and magnitudes, because of changes in rainfall regime in turn brought on by climate change due to carbon dioxide accumulation in the atmosphere. The region selected for study was the central Alberta foothills and adjacent prairie environment. A study watershed, representative of the region, was chosen to assess the present and possible future flood frequency-magnitude relationships. A Monte Carlo simulation method was used in conjunction with rainfall-runoff modelling of the study watershed to generate data for flood frequency analysis of maximum annual flood series corresponding to the present and future climate scenarios. The impact of resulting differences in design floods for small dams on spillway design was investigated using the Prairie Farm Rehabilitation Administration small dam design method. Changes in the mean and standard deviation of rainfall depth of design storms in a region will result in new probability distributions of the maximum annual flood flows. A 25% increase in the mean and standard deviation of design rainfall depth resulted in greater increases of 1:2 and 1:100 flood flows than a 50% increase in the standard deviation alone did. Under scenario 1, the 1:2 flood flows increased more than did the 1:100 flows. Scenario 2 produced opposite results, whereby the 1:100 flows increased more than did the 1:2 flows. It seems that a climate change of the type of scenario 1 would result in a more severe increase in flood flows than scenario 2 would. Retrofitting existing spillways of small dams would in most cases require increasing flow capacities of both operating and auxilliary spillways. 23 refs

Bayesian uncertainty assessment of flood predictions in ungauged urban basins for conceptual rainfall-runoff models

Directory of Open Access Journals (Sweden)

A. E. Sikorska

2012-04-01

Full Text Available Urbanization and the resulting land-use change strongly affect the water cycle and runoff-processes in watersheds. Unfortunately, small urban watersheds, which are most affected by urban sprawl, are mostly ungauged. This makes it intrinsically difficult to assess the consequences of urbanization. Most of all, it is unclear how to reliably assess the predictive uncertainty given the structural deficits of the applied models. In this study, we therefore investigate the uncertainty of flood predictions in ungauged urban basins from structurally uncertain rainfall-runoff models. To this end, we suggest a procedure to explicitly account for input uncertainty and model structure deficits using Bayesian statistics with a continuous-time autoregressive error model. In addition, we propose a concise procedure to derive prior parameter distributions from base data and successfully apply the methodology to an urban catchment in Warsaw, Poland. Based on our results, we are able to demonstrate that the autoregressive error model greatly helps to meet the statistical assumptions and to compute reliable prediction intervals. In our study, we found that predicted peak flows were up to 7 times higher than observations. This was reduced to 5 times with Bayesian updating, using only few discharge measurements. In addition, our analysis suggests that imprecise rainfall information and model structure deficits contribute mostly to the total prediction uncertainty. In the future, flood predictions in ungauged basins will become more important due to ongoing urbanization as well as anthropogenic and climatic changes. Thus, providing reliable measures of uncertainty is crucial to support decision making.

Analysis of rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province

Science.gov (United States)

Pan, Huali; Hu, Mingjian; Ou, Guoqiang

2017-04-01

According to the geological investigation in Fujian province, the total number of geological disasters was 9513, in which the number of landslide, collapse, unstable slope and surface collapse was 5816, 1888, 1591, 103 and 115 respectively. The main geological disaster was the landslide with 61.1% of total geological disasters. Among all these geological disasters, only 6.0% was relative stable, 17.0% was basic stable, nearly 76.0% was unstable. The slope disaster was the main geological disaster, if the unstable slope was the potential landslide or collapse; the slope collapse was 98.0% of all geological disasters. The rainfall, in particular the heavy rain, was direct dynamic factor for geological disasters, but the occurrence probability of geological disasters was different because of the sensitivity of the geological environment though of the same intensity rainfall. To obtain the characteristics of soil erosion under the rainfall condition, the rainfall characteristics and its related disasters of slag disposal pit of a certain Gold-Copper Deposit in Fujian province was analyzed by the meteorological and rainfall data. According to the distribution of monitoring stations of hydrological and rainfall in Longyan city of Fujian province and the location of gold-copper deposit, the Shanghang monitoring station of hydrological and rainfall was chosen, which is the nearest one to the gold-copper deposit. Then main parameters of the prediction model, the antecedent precipitation, the rainfall on the day and the rainfall threshold, were calculated by using the rainfall data from 2002 to 2010. And the relationship between geological disasters and the rainfall characteristics were analyzed. The results indicated that there was high risk for the debris flow with landslide collapse when either the daily rainfall was more than 100.0 mm, or the total rainfall was more than 136.0mm in the gold-copper deposit and the Shanghang region. At the same time, although there was few

Assessment of flood Response Characteristics to Urbanization and extreme flood events-Typhoons at Cheongju, Chungbuk

Science.gov (United States)

Chang, HyungJoon; Lee, Hyosang; Hwang, Myunggyu; Jang, Sukhwan

2016-04-01

The changes of land use influence on the flood characteristics, which depend on rainfall runoff procedures in the catchment. This study assesses the changes of flood characteristics due to land use changes between 1997 and 2012. The catchment model (HEC-HMS) is calibrated with flood events of 1990's and 2000's respectively, then the design rainfall of 100, 200, 500year return period are applied to this model, which represent the catchment in 1990's and 2000's, to assess the flood peaks. Then the extreme flood events (i.e., 6 typhoon events) are applied to assess the flood responses. The results of comparison between 1990's and 2000's show that the flood peak and level of 2000's are increasing and time to peak of 2000's is decreasing comparing to those of 1990's :3% to 78% increase in flood peak, 3% in flood level and 10.2% to 16% decrease in time to peak in 100year return period flood. It is due to decreasing of the farmland area (2.18%), mountainous area (8.88%), and increasing of the urbanization of the area (5.86%). This study also estimates the responses to extreme flood events. The results of 2000's show that the increasing of the flood peak and time to peak comparing to 1990's. It indicates that the extreme rainfall is more responsible at unurbanized catchment ( 2000's), which resulting with a 11% increasing of the peak volume. Acknowledgement This research was supported by a grant (11-TI-C06) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Heavy Rainfall Associated with a Monsoon Depression in South China: Structure Analysis

Institute of Scientific and Technical Information of China (English)

JIANG Jianying; JIANG Jixi; BU Yalin; LIU Nianqing

2008-01-01

A heavy rainfall associated with the deepening of a monsoon depression happened in the summer of 2005.This process was first diagnostically analyzed and the 3D structure of the monsoon depression was discussed,then this structure was compared with those of the monsoon depression in South Asia and the low vortex in the Meiyu front. The results showed that the heavy rainfall directly resulted from a monsoon depression in South China, and the large-scale environment provided a favorable background for the deepening of the monsoon depression. The 3D structure of the monsoon depression was as follows. In the horizontal direction,there existed a convective cloud band to the south of the monsoon depression, which lay in a convectively instable area, with a relatively strong ascending motion in the mid and low levels of the troposphere, and the ascending motion matched well with a moist tongue, a convergence area, and a band of positive vorticity in the mid and low levels of the troposphere. In the vertical direction, the depression had an obviously cyclonic circulation in the mid and low levels of the troposphere, but no circulation from above 300 hPa. The monsoon depression corresponded to convergence and positive vorticity in the low levels, but to divergence and negative vortieity in the upper levels. The upward draft of the depression could reach the upper levels of the troposphere in the west of the depression, while the descending motion lay in the east. There was a low-level jet to the south of the depression, while the upper-level jet was not obvious. The depression was vertically warm in the upper levels and cold in the low levels, and the axis of the depression tilted southeastward with height, whose characteristics were different not only from the monsoon depression in South Asia but also from the low vortex in the Meiyu front.

BN-FLEMOps pluvial - A probabilistic multi-variable loss estimation model for pluvial floods

Science.gov (United States)

Roezer, V.; Kreibich, H.; Schroeter, K.; Doss-Gollin, J.; Lall, U.; Merz, B.

2017-12-01

Pluvial flood events, such as in Copenhagen (Denmark) in 2011, Beijing (China) in 2012 or Houston (USA) in 2016, have caused severe losses to urban dwellings in recent years. These floods are caused by storm events with high rainfall rates well above the design levels of urban drainage systems, which lead to inundation of streets and buildings. A projected increase in frequency and intensity of heavy rainfall events in many areas and an ongoing urbanization may increase pluvial flood losses in the future. For an efficient risk assessment and adaptation to pluvial floods, a quantification of the flood risk is needed. Few loss models have been developed particularly for pluvial floods. These models usually use simple waterlevel- or rainfall-loss functions and come with very high uncertainties. To account for these uncertainties and improve the loss estimation, we present a probabilistic multi-variable loss estimation model for pluvial floods based on empirical data. The model was developed in a two-step process using a machine learning approach and a comprehensive database comprising 783 records of direct building and content damage of private households. The data was gathered through surveys after four different pluvial flood events in Germany between 2005 and 2014. In a first step, linear and non-linear machine learning algorithms, such as tree-based and penalized regression models were used to identify the most important loss influencing factors among a set of 55 candidate variables. These variables comprise hydrological and hydraulic aspects, early warning, precaution, building characteristics and the socio-economic status of the household. In a second step, the most important loss influencing variables were used to derive a probabilistic multi-variable pluvial flood loss estimation model based on Bayesian Networks. Two different networks were tested: a score-based network learned from the data and a network based on expert knowledge. Loss predictions are made

Floods characterization: from impact data to quantitative assessment

Science.gov (United States)

Llasat, Maria-Carmen; Gilabert, Joan; Llasat-Botija, Montserrat; Marcos, Raül; Quintana-Seguí, Pere; Turco, Marco

2015-04-01

This study is based on the following flood databases from Catalonia: INUNGAMA (1900-2010) which considers 372 floods (Llasat et al, 2014), PRESSGAMA (1981-2010) and HISTOGAMA (from XIV Century on) - built as part of SPHERE project and recently updated. These databases store information about flood impacts (among others) and classify them by their severity (catastrophic, extraordinary and ordinary) by means of an indicators matrix based on other studies (i.e. Petrucci et al, 2013; Llasat et al, 2013). On this research we present a comparison between flood impacts, flow data and rainfall data on a Catalan scale and particularly for the basins of Segre, Muga, Ter and Llobregat (Western Mediterranean). From a bottom-up approach, a statistical methodology has been built (trend analysis, measures of position, cumulative distribution functions and geostatistics) in order to identify quantitative thresholds that will make possible to classify the floods. The purpose of this study is to establish generic thresholds for the whole Catalan region, for this we have selected rainfall maximums of flooding episodes stored at INUNGAMA and they have been related to flood categories by boxplot diagrams. Regarding the stream flow, we have established a relation between impacts and return periods at the day when the flow is maximum. The aim is to homogenize and compare the different drainage basins and to obtain general thresholds. It is also presented detailed analyses of relations between flooding episodes, flood classification and weather typing schemes - based in Jenkinson and Collison classification (applied to the Iberian Peninsula by Spellmann, 2000). In this way it could be analyzed whether patterns for the different types of floods exist or not. Finally, this work has pointed out the need of defining a new category for the most severe episodes.

Indirect Damage of Urban Flooding: Investigation of Flood-Induced Traffic Congestion Using Dynamic Modeling

Directory of Open Access Journals (Sweden)

Jingxuan Zhu

2018-05-01

Full Text Available In many countries, industrialization has led to rapid urbanization. Increased frequency of urban flooding is one consequence of the expansion of urban areas which can seriously affect the productivity and livelihoods of urban residents. Therefore, it is of vital importance to study the effects of rainfall and urban flooding on traffic congestion and driver behavior. In this study, a comprehensive method to analyze the influence of urban flooding on traffic congestion was developed. First, a flood simulation was conducted to predict the spatiotemporal distribution of flooding based on Storm Water Management Model (SWMM and TELAMAC-2D. Second, an agent-based model (ABM was used to simulate driver behavior during a period of urban flooding, and a car-following model was established. Finally, in order to study the mechanisms behind how urban flooding affects traffic congestion, the impact of flooding on urban traffic was investigated based on a case study of the urban area of Lishui, China, covering an area of 4.4 km2. It was found that for most events, two-hour rainfall has a certain impact on traffic congestion over a five-hour period, with the greatest impact during the hour following the cessation of the rain. Furthermore, the effects of rainfall with 10- and 20-year return periods were found to be similar and small, whereas the effects with a 50-year return period were obvious. Based on a combined analysis of hydrology and transportation, the proposed methods and conclusions could help to reduce traffic congestion during flood seasons, to facilitate early warning and risk management of urban flooding, and to assist users in making informed decisions regarding travel.

Surrogate modeling of joint flood risk across coastal watersheds

Science.gov (United States)

Bass, Benjamin; Bedient, Philip

2018-03-01

This study discusses the development and performance of a rapid prediction system capable of representing the joint rainfall-runoff and storm surge flood response of tropical cyclones (TCs) for probabilistic risk analysis. Due to the computational demand required for accurately representing storm surge with the high-fidelity ADvanced CIRCulation (ADCIRC) hydrodynamic model and its coupling with additional numerical models to represent rainfall-runoff, a surrogate or statistical model was trained to represent the relationship between hurricane wind- and pressure-field characteristics and their peak joint flood response typically determined from physics based numerical models. This builds upon past studies that have only evaluated surrogate models for predicting peak surge, and provides the first system capable of probabilistically representing joint flood levels from TCs. The utility of this joint flood prediction system is then demonstrated by improving upon probabilistic TC flood risk products, which currently account for storm surge but do not take into account TC associated rainfall-runoff. Results demonstrate the source apportionment of rainfall-runoff versus storm surge and highlight that slight increases in flood risk levels may occur due to the interaction between rainfall-runoff and storm surge as compared to the Federal Emergency Management Association's (FEMAs) current practices.

Journal of Earth System Science | Indian Academy of Sciences

Indian Academy of Sciences (India)

Orissa is one of the most flood prone states of India. The floods in Orissa mostly occur during monsoon season due to very heavy rainfall caused by synoptic scale monsoon disturbances. Hence a study is undertaken to find out the characteristic features of very heavy rainfall (24 hours rainfall ≥ 125mm) over Orissa during ...

Assessing flood forecast uncertainty with fuzzy arithmetic

Directory of Open Access Journals (Sweden)

de Bruyn Bertrand

2016-01-01

Full Text Available Providing forecasts for flow rates and water levels during floods have to be associated with uncertainty estimates. The forecast sources of uncertainty are plural. For hydrological forecasts (rainfall-runoff performed using a deterministic hydrological model with basic physics, two main sources can be identified. The first obvious source is the forcing data: rainfall forecast data are supplied in real time by meteorological forecasting services to the Flood Forecasting Service within a range between a lowest and a highest predicted discharge. These two values define an uncertainty interval for the rainfall variable provided on a given watershed. The second source of uncertainty is related to the complexity of the modeled system (the catchment impacted by the hydro-meteorological phenomenon, the number of variables that may describe the problem and their spatial and time variability. The model simplifies the system by reducing the number of variables to a few parameters. Thus it contains an intrinsic uncertainty. This model uncertainty is assessed by comparing simulated and observed rates for a large number of hydro-meteorological events. We propose a method based on fuzzy arithmetic to estimate the possible range of flow rates (and levels of water making a forecast based on possible rainfalls provided by forcing and uncertainty model. The model uncertainty is here expressed as a range of possible values. Both rainfall and model uncertainties are combined with fuzzy arithmetic. This method allows to evaluate the prediction uncertainty range. The Flood Forecasting Service of Oise and Aisne rivers, in particular, monitors the upstream watershed of the Oise at Hirson. This watershed’s area is 310 km2. Its response time is about 10 hours. Several hydrological models are calibrated for flood forecasting in this watershed and use the rainfall forecast. This method presents the advantage to be easily implemented. Moreover, it permits to be carried out

Hydrological model calibration for flood prediction in current and future climates using probability distributions of observed peak flows and model based rainfall

Science.gov (United States)

Haberlandt, Uwe; Wallner, Markus; Radtke, Imke

2013-04-01

Derived flood frequency analysis based on continuous hydrological modelling is very demanding regarding the required length and temporal resolution of precipitation input data. Often such flood predictions are obtained using long precipitation time series from stochastic approaches or from regional climate models as input. However, the calibration of the hydrological model is usually done using short time series of observed data. This inconsistent employment of different data types for calibration and application of a hydrological model increases its uncertainty. Here, it is proposed to calibrate a hydrological model directly on probability distributions of observed peak flows using model based rainfall in line with its later application. Two examples are given to illustrate the idea. The first one deals with classical derived flood frequency analysis using input data from an hourly stochastic rainfall model. The second one concerns a climate impact analysis using hourly precipitation from a regional climate model. The results show that: (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated on extreme conditions works quite well for average conditions but not vice versa, (III) the calibration of the hydrological model using regional climate model data works as an implicit bias correction method and (IV) the best performance for flood estimation is usually obtained when model based precipitation and observed probability distribution of peak flows are used for model calibration.

Heavy rainfall equations for Santa Catarina, Brazil

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Álvaro José Back

2011-12-01

Full Text Available Knowledge of intensity-duration-frequency (IDF relationships of rainfall events is extremely important to determine the dimensions of surface drainage structures and soil erosion control. The purpose of this study was to obtain IDF equations of 13 rain gauge stations in the state of Santa Catarina in Brazil: Chapecó, Urussanga, Campos Novos, Florianópolis, Lages, Caçador, Itajaí, Itá, Ponte Serrada, Porto União, Videira, Laguna and São Joaquim. The daily rainfall data charts of each station were digitized and then the annual maximum rainfall series were determined for durations ranging from 5 to 1440 min. Based on these, with the Gumbel-Chow distribution, the maximum rainfall was estimated for durations ranging from 5 min to 24 h, considering return periods of 2, 5, 10, 20, 25, 50, and 100 years,. Data agreement with the Gumbel-Chow model was verified by the Kolmogorov-Smirnov test, at 5 % significance level. For each rain gauge station, two IDF equations of rainfall events were adjusted, one for durations from 5 to 120 min and the other from 120 to 1440 min. The results show a high variability in maximum intensity of rainfall events among the studied stations. Highest values of coefficients of variation in the annual maximum series of rainfall were observed for durations of over 600 min at the stations of the coastal region of Santa Catarina.

A Fresh Start for Flood Estimation in Ungauged Basins

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Woods, R. A.

2017-12-01

The two standard methods for flood estimation in ungauged basins, regression-based statistical models and rainfall-runoff models using a design rainfall event, have survived relatively unchanged as the methods of choice for more than 40 years. Their technical implementation has developed greatly, but the models' representation of hydrological processes has not, despite a large volume of hydrological research. I suggest it is time to introduce more hydrology into flood estimation. The reliability of the current methods can be unsatisfactory. For example, despite the UK's relatively straightforward hydrology, regression estimates of the index flood are uncertain by +/- a factor of two (for a 95% confidence interval), an impractically large uncertainty for design. The standard error of rainfall-runoff model estimates is not usually known, but available assessments indicate poorer reliability than statistical methods. There is a practical need for improved reliability in flood estimation. Two promising candidates to supersede the existing methods are (i) continuous simulation by rainfall-runoff modelling and (ii) event-based derived distribution methods. The main challenge with continuous simulation methods in ungauged basins is to specify the model structure and parameter values, when calibration data are not available. This has been an active area of research for more than a decade, and this activity is likely to continue. The major challenges for the derived distribution method in ungauged catchments include not only the correct specification of model structure and parameter values, but also antecedent conditions (e.g. seasonal soil water balance). However, a much smaller community of researchers are active in developing or applying the derived distribution approach, and as a result slower progress is being made. A change in needed: surely we have learned enough about hydrology in the last 40 years that we can make a practical hydrological advance on our methods for

The effects of wind and rainfall on suspended sediment concentration related to the 2004 Indian Ocean tsunami

International Nuclear Information System (INIS)

Zhang Xinfeng; Tang Danling; Li Zizhen; Zhang Fengpan

2009-01-01

The effects of rainfall and wind speed on the dynamics of suspended sediment concentration (SSC), during the 2004 Indian Ocean tsunami, were analyzed using spatial statistical models. The results showed a positive effect of wind speed on SSC, and inconsistent effects (positive and negative) of rainfall on SSC. The effects of wind speed and rainfall on SSC weakened immediately around the tsunami, indicating tsunami-caused floods and earthquake-induced shaking may have suddenly disturbed the ocean-atmosphere interaction processes, and thus weakened the effects of wind speed and rainfall on SSC. Wind speed and rainfall increased markedly, and reached their maximum values immediately after the tsunami week. Rainfall at this particular week exceeded twice the average for the same period over the previous 4 years. The tsunami-affected air-sea interactions may have increased both wind speed and rainfall immediately after the tsunami week, which directly lead to the variations in SSC.

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

Science.gov (United States)

Chawla, Ila; Osuri, Krishna K.; Mujumdar, Pradeep P.; Niyogi, Dev

2018-02-01

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

Plant communities in relation to flooding and soil contamination in a lowland Rhine River floodplain

International Nuclear Information System (INIS)

Schipper, Aafke M.; Lotterman, Kim; Leuven, Rob S.E.W.; Ragas, Ad M.J.; Kroon, Hans de; Hendriks, A. Jan

2011-01-01

Using canonical correspondence analysis (CCA), relationships were investigated between plant species composition and flooding characteristics, heavy metal contamination and soil properties in a lowland floodplain of the Rhine River. Floodplain elevation and yearly average flooding duration turned out to be more important for explaining variation in plant species composition than soil heavy metal contamination. Nevertheless, plant species richness and diversity showed a significant decrease with the level of contamination. As single heavy metal concentrations seemed mostly too low for causing phytotoxic effects in plants, this trend is possibly explained by additive effects of multiple contaminants or by the concomitant influences of contamination and non-chemical stressors like flooding. These results suggest that impacts of soil contamination on plants in floodplains could be larger than expected from mere soil concentrations. In general, these findings emphasize the relevance of analyzing effects of toxic substances in concert with the effects of other relevant stressors. - Multiple contaminants and periodic flooding may pose cumulative stress to plants in lowland floodplains.

Trends analysis of rainfall and rainfall extremes in Sarawak, Malaysia using modified Mann-Kendall test

Science.gov (United States)

Sa'adi, Zulfaqar; Shahid, Shamsuddin; Ismail, Tarmizi; Chung, Eun-Sung; Wang, Xiao-Jun

2017-11-01

This study assesses the spatial pattern of changes in rainfall extremes of Sarawak in recent years (1980-2014). The Mann-Kendall (MK) test along with modified Mann-Kendall (m-MK) test, which can discriminate multi-scale variability of unidirectional trend, was used to analyze the changes at 31 stations. Taking account of the scaling effect through eliminating the effect of autocorrelation, m-MK was employed to discriminate multi-scale variability of the unidirectional trends of the annual rainfall in Sarawak. It can confirm the significance of the MK test. The annual rainfall trend from MK test showed significant changes at 95% confidence level at five stations. The seasonal trends from MK test indicate an increasing rate of rainfall during the Northeast monsoon and a decreasing trend during the Southwest monsoon in some region of Sarawak. However, the m-MK test detected an increasing trend in annual rainfall only at one station and no significant trend in seasonal rainfall at any stations. The significant increasing trends of the 1-h maximum rainfall from the MK test are detected mainly at the stations located in the urban area giving concern to the occurrence of the flash flood. On the other hand, the m-MK test detected no significant trend in 1- and 3-h maximum rainfalls at any location. On the contrary, it detected significant trends in 6- and 72-h maximum rainfalls at a station located in the Lower Rajang basin area which is an extensive low-lying agricultural area and prone to stagnant flood. These results indicate that the trends in rainfall and rainfall extremes reported in Malaysia and surrounding region should be verified with m-MK test as most of the trends may result from scaling effect.

Flood hazard assessment in areas prone to flash flooding

Science.gov (United States)

Kvočka, Davor; Falconer, Roger A.; Bray, Michaela

2016-04-01

Contemporary climate projections suggest that there will be an increase in the occurrence of high-intensity rainfall events in the future. These precipitation extremes are usually the main cause for the emergence of extreme flooding, such as flash flooding. Flash floods are among the most unpredictable, violent and fatal natural hazards in the world. Furthermore, it is expected that flash flooding will occur even more frequently in the future due to more frequent development of extreme weather events, which will greatly increase the danger to people caused by flash flooding. This being the case, there will be a need for high resolution flood hazard maps in areas susceptible to flash flooding. This study investigates what type of flood hazard assessment methods should be used for assessing the flood hazard to people caused by flash flooding. Two different types of flood hazard assessment methods were tested: (i) a widely used method based on an empirical analysis, and (ii) a new, physically based and experimentally calibrated method. Two flash flood events were considered herein, namely: the 2004 Boscastle flash flood and the 2007 Železniki flash flood. The results obtained in this study suggest that in the areas susceptible to extreme flooding, the flood hazard assessment should be conducted using methods based on a mechanics-based analysis. In comparison to standard flood hazard assessment methods, these physically based methods: (i) take into account all of the physical forces, which act on a human body in floodwater, (ii) successfully adapt to abrupt changes in the flow regime, which often occur for flash flood events, and (iii) rapidly assess a flood hazard index in a relatively short period of time.

Current and future pluvial flood hazard analysis for the city of Antwerp

Science.gov (United States)

Willems, Patrick; Tabari, Hossein; De Niel, Jan; Van Uytven, Els; Lambrechts, Griet; Wellens, Geert

2016-04-01

For the city of Antwerp in Belgium, higher rainfall extremes were observed in comparison with surrounding areas. The differences were found statistically significant for some areas and may be the result of the heat island effect in combination with the higher concentrations of aerosols. A network of 19 rain gauges but with varying records length (the longest since the 1960s) and continuous radar data for 10 years were combined to map the spatial variability of rainfall extremes over the city at various durations from 15 minutes to 1 day together with the uncertainty. The improved spatial rainfall information was used as input in the sewer system model of the city to analyze the frequency of urban pluvial floods. Comparison with historical flood observations from various sources (fire brigade and media) confirmed that the improved spatial rainfall information also improved sewer impact results on both the magnitude and frequency of the sewer floods. Next to these improved urban flood impact results for recent and current climatological conditions, the new insights on the local rainfall microclimate were also helpful to enhance future projections on rainfall extremes and pluvial floods in the city. This was done by improved statistical downscaling of all available CMIP5 global climate model runs (160 runs) for the 4 RCP scenarios, as well as the available EURO-CORDEX regional climate model runs. Two types of statistical downscaling methods were applied for that purpose (a weather typing based method, and a quantile perturbation approach), making use of the microclimate results and its dependency on specific weather types. Changes in extreme rainfall intensities were analyzed and mapped as a function of the RCP scenario, together with the uncertainty, decomposed in the uncertainties related to the climate models, the climate model initialization or limited length of the 30-year time series (natural climate variability) and the statistical downscaling (albeit limited

Ostrich recruitment dynamics in relation to rainfall in the Mara ...

African Journals Online (AJOL)

Ostrich recruitment dynamics in relation to rainfall in the Mara–Serengeti ... To understand how rainfall influences ostriches, we related changes in ostrich recruitment in the Mara–Serengeti ecosystem to rainfall. ... AJOL African Journals Online.

Rainfall and runoff Intensity-Duration-Frequency Curves for Washington State considering the change and uncertainty of observed and anticipated extreme rainfall and snow events

Science.gov (United States)

Demissie, Y. K.; Mortuza, M. R.; Li, H. Y.

2015-12-01

The observed and anticipated increasing trends in extreme storm magnitude and frequency, as well as the associated flooding risk in the Pacific Northwest highlighted the need for revising and updating the local intensity-duration-frequency (IDF) curves, which are commonly used for designing critical water infrastructure. In Washington State, much of the drainage system installed in the last several decades uses IDF curves that are outdated by as much as half a century, making the system inadequate and vulnerable for flooding as seen more frequently in recent years. In this study, we have developed new and forward looking rainfall and runoff IDF curves for each county in Washington State using recently observed and projected precipitation data. Regional frequency analysis coupled with Bayesian uncertainty quantification and model averaging methods were used to developed and update the rainfall IDF curves, which were then used in watershed and snow models to develop the runoff IDF curves that explicitly account for effects of snow and drainage characteristic into the IDF curves and related designs. The resulted rainfall and runoff IDF curves provide more reliable, forward looking, and spatially resolved characteristics of storm events that can assist local decision makers and engineers to thoroughly review and/or update the current design standards for urban and rural storm water management infrastructure in order to reduce the potential ramifications of increasing severe storms and resulting floods on existing and planned storm drainage and flood management systems in the state.

Math Fights Flooding

NARCIS (Netherlands)

Besseling, Niels; Bokhove, Onno; Kolechkina, Alla; Molenaar, Jaap; van Nooyen, Ronald; Rottschäfer, Vivi; Stein, Alfred; Stoorvogel, Anton

2008-01-01

Due to climate changes that are expected in the coming years, the characteristics of the rainfall will change. This can potentially cause flooding or have negative influences on agriculture and nature. In this research, we study the effects of this change in rainfall and investigate what can be done

Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

Science.gov (United States)

Alahmadi, F.; Rahman, N. A.; Abdulrazzak, M.

2014-09-01

Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS) in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III) and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC), Corrected Akaike Information Criterion (AICc), Bayesian Information Criterion (BIC) and Anderson-Darling Criterion (ADC). The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

Evaluation of the best fit distribution for partial duration series of daily rainfall in Madinah, western Saudi Arabia

Directory of Open Access Journals (Sweden)

F. Alahmadi

2014-09-01

Full Text Available Rainfall frequency analysis is an essential tool for the design of water related infrastructure. It can be used to predict future flood magnitudes for a given magnitude and frequency of extreme rainfall events. This study analyses the application of rainfall partial duration series (PDS in the vast growing urban Madinah city located in the western part of Saudi Arabia. Different statistical distributions were applied (i.e. Normal, Log Normal, Extreme Value type I, Generalized Extreme Value, Pearson Type III, Log Pearson Type III and their distribution parameters were estimated using L-moments methods. Also, different selection criteria models are applied, e.g. Akaike Information Criterion (AIC, Corrected Akaike Information Criterion (AICc, Bayesian Information Criterion (BIC and Anderson-Darling Criterion (ADC. The analysis indicated the advantage of Generalized Extreme Value as the best fit statistical distribution for Madinah partial duration daily rainfall series. The outcome of such an evaluation can contribute toward better design criteria for flood management, especially flood protection measures.

Regional scale flood modeling using NEXRAD rainfall, GIS, and HEC-HMS/RAS: a case study for the San Antonio River Basin Summer 2002 storm event.

Science.gov (United States)

Knebl, M R; Yang, Z-L; Hutchison, K; Maidment, D R

2005-06-01

This paper develops a framework for regional scale flood modeling that integrates NEXRAD Level III rainfall, GIS, and a hydrological model (HEC-HMS/RAS). The San Antonio River Basin (about 4000 square miles, 10,000 km2) in Central Texas, USA, is the domain of the study because it is a region subject to frequent occurrences of severe flash flooding. A major flood in the summer of 2002 is chosen as a case to examine the modeling framework. The model consists of a rainfall-runoff model (HEC-HMS) that converts precipitation excess to overland flow and channel runoff, as well as a hydraulic model (HEC-RAS) that models unsteady state flow through the river channel network based on the HEC-HMS-derived hydrographs. HEC-HMS is run on a 4 x 4 km grid in the domain, a resolution consistent with the resolution of NEXRAD rainfall taken from the local river authority. Watershed parameters are calibrated manually to produce a good simulation of discharge at 12 subbasins. With the calibrated discharge, HEC-RAS is capable of producing floodplain polygons that are comparable to the satellite imagery. The modeling framework presented in this study incorporates a portion of the recently developed GIS tool named Map to Map that has been created on a local scale and extends it to a regional scale. The results of this research will benefit future modeling efforts by providing a tool for hydrological forecasts of flooding on a regional scale. While designed for the San Antonio River Basin, this regional scale model may be used as a prototype for model applications in other areas of the country.

Study of flood defense structural measures priorities using Compromise Programming technique

Science.gov (United States)

Lim, D.; Jeong, S.

2017-12-01

Recent climate change of global warming has led to the frequent occurrence of heavy regional rainfalls. As such, inundation vulnerability increases in urban areas with high population density due to the low runoff carrying capacity. This study selects a sample area (Janghang-eup, the Republic of Korea), which is one of the most vulnerable areas to flooding, analyzing the urban flood runoff model (XP-SWMM) and using the MCDM (Multi-Criteria Decision Making) technique to establish flood protection structural measures. To this end, we compare the alternatives and choose the optimal flood defense measure: our model is utilized with three flood prevention structural measures; (i) drainage pipe construction; (ii) water detention; and (iii) flood pumping station. Dividing the target area into three small basins, we propose flood evaluations for an inundation decrease by studying the flooded area, the maximum inundation depth, the damaged residential area, and the construction cost. In addition, Compromise Programming determines the priority of the alternatives. As a consequent, this study suggests flood pumping station for Zone 1 and drainage pipe construction for Zone 2 and Zone 3, respectively, as the optimal flood defense alternative. Keywords : MCDM; Compromise Programming; Urban Flood Prevention; This research was supported by a grant [MPSS-DP-2013-62] through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.

Synoptic thermodynamic and dynamic patterns associated with Quitandinha River flooding events in Petropolis, Rio de Janeiro (Brazil)

Science.gov (United States)

da Silva, Fabricio Polifke; Justi da Silva, Maria Gertrudes Alvarez; Rotunno Filho, Otto Corrêa; Pires, Gisele Dornelles; Sampaio, Rafael João; de Araújo, Afonso Augusto Magalhães

2018-05-01

Natural disasters are the result of extreme or intense natural phenomena that cause severe impacts on society. These impacts can be mitigated through preventive measures that can be aided by better knowledge of extreme phenomena and monitoring of forecasting and alert systems. The city of Petropolis (in a mountainous region of the state of Rio de Janeiro, Brazil) is prone to heavy rain events, often leading to River overflows, landslides, and loss of life. In that context, this work endeavored to characterize the thermodynamic and dynamic synoptic patterns that trigger heavy rainfall episodes and the corresponding flooding of Quitandinha River. More specifically, we reviewed events from the time period between January 2013 and December 2014 using reanalysis data. We expect that the overall description obtained of synoptic patterns should provide adequate qualitative aid to the decision-making processes involved in operational forecasting procedures. We noticed that flooding events were related to the presence of the South Atlantic Convergence Zone (SACZ), frontal systems (FS), and convective storms (CS). These systems showed a similar behavior on high-frequency wind components, notably with respect to northwest winds before precipitation and to a strong southwest wind component during rainfall events. Clustering analyses indicated that the main component for precipitation formation with regard to CS systems comes from daytime heating, with the dynamic component presenting greater efficiency for the FS configurations. The SACZ events were influenced by moisture availability along the vertical column of the atmosphere and also due to dynamic components of precipitation efficiency and daytime heating, the latter related to the continuous transport of moisture from the Amazon region and South Atlantic Ocean towards Rio de Janeiro state.

Rainfall and snow-melt triggered glacial lake outbursts: a systematic analysis of the Kedarnath (Uttarakhand, India), June 2013 disaster

Science.gov (United States)

Allen, Simon; Rastner, Philipp; Arora, Manohar; Huggel, Christian; Stoffel, Markus

2015-04-01

Heavy rainfall in early June 2013 triggered flash flooding and landslides throughout the Indian Himalayan state of Uttarakhand, killing more than 6000 people. The destruction of roads and trekking routes left around 100,000 pilgrims and tourists stranded. Most fatalities and damages resulted directly from a lake outburst and debris flow disaster originating from above the village of Kedarnath on June 16 and 17. Here we provide a first systematic analysis of the contributing factors leading to the Kedarnath disaster, both in terms of hydro-meteorological triggering (rainfall, snowmelt, and temperature) and topographic predisposition. Specifically, the topographic characteristics of the Charobari lake watershed above Kedarnath are compared with other glacial lakes across the northwestern Indian Himalayan states of Uttarakhand and Himachal Pradesh, and implications for glacier lake outburst hazard assessment in a changing climate are discussed. Our analysis suggests that the early onset of heavy monsoon rainfall (390 mm, June 10 - 17) immediately following a prolonged four week period of unusually rapid snow cover depletion and elevated streamflow is the crucial hydro-meteorological factor, resulting in slope saturation and significant runoff into the small seasonal glacial lake. Over a four week period the MODIS-derived snow covered area above Kedarnath decreased nearly 50%, from above average coverage in mid-May to well below average coverage by the second week of June. Such a rapid decrease has not been observed in the previous 13-year record, where the average decrease in snow covered area over the same four week window is only 15%. The unusual situation of the lake being dammed in a steep, unstable paraglacial environment, but fed entirely from snow-melt and rainfall within a fluvial dominated watershed is important in the context of this disaster. A simple scheme enabling large-scale recognition of such an unfavorable topographic setting is presented, and on the

Large Scale Water Vapor Sources Relative to the October 2000 Piedmont Flood

Science.gov (United States)

Turato, Barbara; Reale, Oreste; Siccardi, Franco

2003-01-01

Very intense mesoscale or synoptic-scale rainfall events can occasionally be observed in the Mediterranean region without any deep cyclone developing over the areas affected by precipitation. In these perplexing cases the synoptic situation can superficially look similar to cases in which very little precipitation occurs. These situations could possibly baffle the operational weather forecasters. In this article, the major precipitation event that affected Piedmont (Italy) between 13 and 16 October 2000 is investigated. This is one of the cases in which no intense cyclone was observed within the Mediterranean region at any time, only a moderate system was present, and yet exceptional rainfall and flooding occurred. The emphasis of this study is on the moisture origin and transport. Moisture and energy balances are computed on different space- and time-scales, revealing that precipitation exceeds evaporation over an area inclusive of Piedmont and the northwestern Mediterranean region, on a time-scale encompassing the event and about two weeks preceding it. This is suggestive of an important moisture contribution originating from outside the region. A synoptic and dynamic analysis is then performed to outline the potential mechanisms that could have contributed to the large-scale moisture transport. The central part of the work uses a quasi-isentropic water-vapor back trajectory technique. The moisture sources obtained by this technique are compared with the results of the balances and with the synoptic situation, to unveil possible dynamic mechanisms and physical processes involved. It is found that moisture sources on a variety of atmospheric scales contribute to this event. First, an important contribution is caused by the extratropical remnants of former tropical storm Leslie. The large-scale environment related to this system allows a significant amount of moisture to be carried towards Europe. This happens on a time- scale of about 5-15 days preceding the

Raingauge-Based Rainfall Nowcasting with Artificial Neural Network

Science.gov (United States)

Liong, Shie-Yui; He, Shan

2010-05-01

Rainfall forecasting and nowcasting are of great importance, for instance, in real-time flood early warning systems. Long term rainfall forecasting demands global climate, land, and sea data, thus, large computing power and storage capacity are required. Rainfall nowcasting's computing requirement, on the other hand, is much less. Rainfall nowcasting may use data captured by radar and/or weather stations. This paper presents the application of Artificial Neural Network (ANN) on rainfall nowcasting using data observed at weather and/or rainfall stations. The study focuses on the North-East monsoon period (December, January and February) in Singapore. Rainfall and weather data from ten stations, between 2000 and 2006, were selected and divided into three groups for training, over-fitting test and validation of the ANN. Several neural network architectures were tried in the study. Two architectures, Backpropagation ANN and Group Method of Data Handling ANN, yielded better rainfall nowcasting, up to two hours, than the other architectures. The obtained rainfall nowcasts were then used by a catchment model to forecast catchment runoff. The results of runoff forecast are encouraging and promising.With ANN's high computational speed, the proposed approach may be deliverable for creating the real-time flood early warning system.

Lattice Boltzmann Method of a Flooding Accident at Gopeng, Perak, Malaysia

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Siti Habibah Shafiai

2017-01-01

Full Text Available The extraordinary flood had hit the residential area at Taman Raia Mesra, Gopeng, Perak, Malaysia, in November 2016. The event illustrated how the river basin had been fully inundated due to the heavy rainfall and caused the overflow to this affected area. It was reported that the occurrence became worst as the outlet of retention pond which connects to the river is unsuitable for the water outflow. Henceforth, this paper attempts to evaluate the causal factor of this recent disaster by using a model developed from Lattice Boltzmann Method (LBM. The model also incorporated with the rainfall and stormwater in LABSWE™. The simulation was commenced with the basic tests for model validation comprising turbulent and jet-forced flow in a circular channel, which resulted in a good agreement for both models. The simulation continued by using LABSWE model to reveal the water depth and velocity profile at the study site. These results had proven the incompatibility size of the outlet pond which is too small for the water to flow out to the river. The study is capable of providing the authorities with a sustainable design of proper drainage system, especially in Malaysia which is constantly receiving the outrageous heavy rainfall.

An Experimental System for a Global Flood Prediction: From Satellite Precipitation Data to a Flood Inundation Map

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Adler, Robert

2007-01-01

Floods impact more people globally than any other type of natural disaster. It has been established by experience that the most effective means to reduce the property damage and life loss caused by floods is the development of flood early warning systems. However, advances for such a system have been constrained by the difficulty in estimating rainfall continuously over space (catchment-. national-, continental-. or even global-scale areas) and time (hourly to daily). Particularly, insufficient in situ data, long delay in data transmission and absence of real-time data sharing agreements in many trans-boundary basins hamper the development of a real-time system at the regional to global scale. In many countries around the world, particularly in the tropics where rainfall and flooding co-exist in abundance, satellite-based precipitation estimation may be the best source of rainfall data for those data scarce (ungauged) areas and trans-boundary basins. Satellite remote sensing data acquired and processed in real time can now provide the space-time information on rainfall fluxes needed to monitor severe flood events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models, which can be parameterized by a tailored geospatial database. An example that is a key to this progress is NASA's contribution to the Tropical Rainfall Measuring Mission (TRMM), launched in November 1997. Hence, in an effort to evolve toward a more hydrologically-relevant flood alert system, this talk articulates a module-structured framework for quasi-global flood potential naming, that is 'up to date' with the state of the art on satellite rainfall estimation and the improved geospatial datasets. The system is modular in design with the flexibility that permits changes in the model structure and in the choice of components. Four major components included in the system are: 1) multi-satellite precipitation estimation; 2) characterization of

Using Seasonal Climate Forecasts to Guide Disaster Management: The Red Cross Experience during the 2008 West Africa Floods

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Arame Tall

2012-01-01

Full Text Available In 2008, the seasonal forecast issued at the Seasonal Climate Outlook Forum for West Africa (PRESAO announced a high risk of above-normal rainfall for the July–September rainy season. With probabilities for above-normal rainfall of 0.45, this forecast indicated noteworthy increases in the risk of heavy rainfall. When this information reached the International Federation of Red Cross and Red Crescent Societies (IFRC West and Central Africa Office, it led to significant changes in the organization’s flood response operations. The IFRC regional office requested funds in advance of anticipated floods, prepositioned disaster relief items in strategic locations across West Africa to benefit up to 9,500 families, updated its flood contingency plans, and alerted vulnerable communities and decision-makers across the region. This forecast-based preparedness resulted in a decrease in the number of lives, property, and livelihoods lost to floods, compared to just one year prior in 2007 when similar floods claimed above 300 lives in the region. This article demonstrates how a science-based early warning informed decisions and saved lives by triggering action in anticipation of forecast events. It analyses what it took to move decision-makers to action, based on seasonal climate information, and to overcome traditional barriers to the uptake of seasonal climate information in the region, providing evidence that these barriers can be overcome. While some institutional, communication and technical barriers were addressed in 2008, many challenges remain. Scientists and humanitarians need to build more common ground.

Mapeamento de chuvas intensas no estado de Minas Gerais Mapping of heavy rainfalls in the state of Minas Gerais

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Carlos Rogério de Mello

2013-02-01

Full Text Available Estudos associados a chuvas extremas são constituídos de eventos de interesse prático para a gestão dos recursos naturais, como manejo de bacias hidrográficas e conservação dos solos e da água. A distribuição espacial desses eventos possibilita inferir sobre áreas onde sua ocorrência é acentuada e desprovida de informações técnicas. Os objetivos deste trabalho foram promover, a partir de dados pontuais de 177 estações meteorológicas e com a utilização de técnicas geoestatísticas, o mapeamento de chuvas intensas para o Estado de Minas Gerais e identificar as áreas mais vulneráveis no tocante à ocorrência dessas chuvas nesse Estado. Foi constatado que as maiores intensidades ocorrem nas regiões leste e noroeste de Minas Gerais, o que pode ser explicado pela maior influência da Zona de Convergência do Atlântico Sul, além de ocorrência de chuvas convectivas. Foi possível, também, constatar e mapear intensidades intermediárias nas regiões sul e central e os menores valores para as regiões norte e nordeste de Minas Gerais. Para maiores durações, verificou-se, para a região sul, ocorrência de altas intensidades, o que está associado à entrada com maior frequência de frentes frias, produzindo chuvas de longa duração.Studies of heavy rainfall are of practical interest for the conservation management of natural resources such as watersheds and soil and water. The spatial distribution of these natural rainfall events allows conclusions about regions where the occurrence of heavy rain is more frequent and to estimate their magnitude for locations without rainfall data sets. Thus, the purpose of this study was to map heavy rainfall data from 177 meteorological stations, using a geostatistical approach, for Minas Gerais, identifying the most vulnerable regions in terms of the occurrence of heavy rain. The highest values were estimated for the East and Northwest regions of the state, which can be explained by the

Floods

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Floods are common in the United States. Weather such as heavy rain, thunderstorms, hurricanes, or tsunamis can ... is breached, or when a dam breaks. Flash floods, which can develop quickly, often have a dangerous ...

Inter-Seasonal and Annual Co-Variation of Smallholder Production Portfolios, Volumes and Incomes with Rainfall and Flood Levels in the Amazon Estuary: Implications for Building Livelihood Resilience to Increasing Variability of Hydro-Climatic Regimes

Science.gov (United States)

Vogt, N. D.; Fernandes, K.; Pinedo-Vasquez, M.; Brondizio, E. S.; Almeida, O.; Rivero, S.; Rabelo, F. R.; Dou, Y.; Deadman, P.

2014-12-01

In this paper we investigate inter-seasonal and annual co-variations of rainfall and flood levels with Caboclo production portfolios, and proportions of it they sell and consume, in the Amazon Estuary from August 2012 to August 2014. Caboclos of the estuary maintain a diverse and flexible land-use portfolio, with a shift in dominant use from agriculture to agroforestry and forestry since WWII (Vogt et al., 2014). The current landscape is configured for acai, shrimp and fish production. In the last decade the frequency of wet seasons with anomalous flood levels and duration has increased primarily from changes in rainfall and discharge from upstream basins. Local rainfall, though with less influence on extreme estuarine flood levels, is reported to be more sporadic and intense in wet season and variable in both wet and dry seasons, for yet unknown reasons. The current production portfolio and its flexibility are felt to build resilience to these increases in hydro-climatic variability and extreme events. What is less understood, for time and costliness of daily measures at household levels, is how variations in flood and rainfall levels affect shifts in the current production portfolio of estuarine Caboclos, and the proportions of it they sell and consume. This is needed to identify what local hydro-climatic thresholds are extreme for current livelihoods, that is, that most adversely affect food security and income levels. It is also needed identify the large-scale forcings driving those extreme conditions to build forecasts for when they will occur. Here we present results of production, rainfall and flood data collected daily in households from both the North and South Channel of the Amazon estuary over last two years to identify how they co-vary, and robustness of current production portfolio under different hydro-climatic conditions.

Investigation of Flood Risk Assessment in Inaccessible Regions using Multiple Remote Sensing and Geographic Information Systems

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Lim, J.; Lee, K. S.

2017-12-01

Flooding is extremely dangerous when a river overflows to inundate an urban area. From 1995 to 2016, North Korea (NK) experienced annual extensive damage to life and property almost each year due to a levee breach resulting from typhoons and heavy rainfall during the summer monsoon season. Recently, Hoeryeong City (2016) experienced heavy rainfall during typhoon Lionrock and the resulting flood killed and injured many people (68,900) and destroyed numerous buildings and settlements (11,600). The NK state media described it as the biggest national disaster since 1945. Thus, almost all annual repeat occurrences of floods in NK have had a serious impact, which makes it necessary to figure out the extent of floods in restoring the damaged environment. In addition, traditional hydrological model is impractical to delineate Flood Damaged Areas (FDAs) in NK due to the inaccessibility. Under such a situation, multiple optical Remote Sensing (RS) and radar RS along with a Geographic Information System (GIS)-based spatial analysis were utilized in this study (1) to develop modelling FDA delineation using multiple RS and GIS methods and (2) to conduct flood risk assessment in NK. Interpreting high-resolution web-based satellite imagery were also implemented to confirm the results of the study. From the study result, it was found that (1) on August 30th, 2016, an area of 117.2 km2 (8.6%) at Hoeryeong City was inundated. Most floods occurred in flat areas with a lower and middle stream order. (2) In the binary logistic regression model applied in this study, the distance from the nearest stream map and landform map variables are important factors to delineate FDAs because these two factors reflect heterogeneous mountainous NK topography. (3) Total annual flood risk of study area is estimated to be ₩454.13 million NKW ($504,417.24 USD, and ₩576.53 million SKW). The risk of the confluence of the Tumen River and Hoeryeong stream appears to be the highest. (4) High resolution

Subtropical westerly jet waveguide and winter persistent heavy rainfall in south China

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Ding, Feng; Li, Chun

2017-07-01

Using observed daily precipitation and National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis data, what induced winter large spatial persistent heavy rainfall (PHR) events in south China was examined, based on composite analyses of 30 large spatial PHR events during 1951-2015. The results showed that wave trains within North Africa-Asia (NAA) westerly jet existed in upper troposphere during these PHR processes. The wave trains shared the characteristic of a Rossby wave. The Rossby wave originated from northwest Europe, entered into the NAA jet through strong cold air advection to form convergence over the Mediterranean, and then propagated eastward along subtropical NAA jet. The Rossby wave propagated toward Southeast Asia and caused strong divergence in the upper troposphere. The strong divergence in the upper troposphere induced vertical convection and favored large spatial PHR events in south China. In addition, the enhanced India-Burma trough and subtropical high in the northwestern Pacific supplied enough water vapor transportation. This mechanism would be useful to the medium-range forecast of such winter rainfall processes over south China.

Small-scale (flash) flood early warning in the light of operational requirements: opportunities and limits with regard to user demands, driving data, and hydrologic modeling techniques

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Philipp, Andy; Kerl, Florian; Büttner, Uwe; Metzkes, Christine; Singer, Thomas; Wagner, Michael; Schütze, Niels

2016-05-01

In recent years, the Free State of Saxony (Eastern Germany) was repeatedly hit by both extensive riverine flooding, as well as flash flood events, emerging foremost from convective heavy rainfall. Especially after a couple of small-scale, yet disastrous events in 2010, preconditions, drivers, and methods for deriving flash flood related early warning products are investigated. This is to clarify the feasibility and the limits of envisaged early warning procedures for small catchments, hit by flashy heavy rain events. Early warning about potentially flash flood prone situations (i.e., with a suitable lead time with regard to required reaction-time needs of the stakeholders involved in flood risk management) needs to take into account not only hydrological, but also meteorological, as well as communication issues. Therefore, we propose a threefold methodology to identify potential benefits and limitations in a real-world warning/reaction context. First, the user demands (with respect to desired/required warning products, preparation times, etc.) are investigated. Second, focusing on small catchments of some hundred square kilometers, two quantitative precipitation forecasts are verified. Third, considering the user needs, as well as the input parameter uncertainty (i.e., foremost emerging from an uncertain QPF), a feasible, yet robust hydrological modeling approach is proposed on the basis of pilot studies, employing deterministic, data-driven, and simple scoring methods.

The major floods in the Amazonas river and tributaries (Western Amazon Basin) during the 1970-2012 period : a focus on the 2012 flood

OpenAIRE

Espinoza, J. C.; Ronchail, J.; Frappart, F.; Lavado, W.; Santini, William; Guyot, Jean-Loup

2013-01-01

In this work, the authors analyze the origin of the extreme floods in the Peruvian Amazonas River during the 1970-2012 period, focusing on the recent April 2012 flooding (55 400 m(3) s(-1)). Several hydrological variables, such as rainfall, terrestrial water storage, and discharge, point out that the unprecedented 2012 flood is mainly related to an early and abundant wet season over the north of the basin. Thus, the peak of the Maranon River, the northern contributor of the Amazonas, occurred...

Mesoscale and Local Scale Evaluations of Quantitative Precipitation Estimates by Weather Radar Products during a Heavy Rainfall Event

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Basile Pauthier

2016-01-01

Full Text Available A 24-hour heavy rainfall event occurred in northeastern France from November 3 to 4, 2014. The accuracy of the quantitative precipitation estimation (QPE by PANTHERE and ANTILOPE radar-based gridded products during this particular event, is examined at both mesoscale and local scale, in comparison with two reference rain-gauge networks. Mesoscale accuracy was assessed for the total rainfall accumulated during the 24-hour event, using the Météo France operational rain-gauge network. Local scale accuracy was assessed for both total event rainfall and hourly rainfall accumulations, using the recently developed HydraVitis high-resolution rain gauge network Evaluation shows that (1 PANTHERE radar-based QPE underestimates rainfall fields at mesoscale and local scale; (2 both PANTHERE and ANTILOPE successfully reproduced the spatial variability of rainfall at local scale; (3 PANTHERE underestimates can be significantly improved at local scale by merging these data with rain gauge data interpolation (i.e., ANTILOPE. This study provides a preliminary evaluation of radar-based QPE at local scale, suggesting that merged products are invaluable for applications at very high resolution. The results obtained underline the importance of using high-density rain-gauge networks to obtain information at high spatial and temporal resolution, for better understanding of local rainfall variation, to calibrate remotely sensed rainfall products.

Characterising Record Flooding in the United Kingdom

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Cox, A.; Bates, P. D.; Smith, J. A.

2017-12-01

Though the most notable floods in history have been carefully explained, there remains a lack of literature that explores the nature of record floods as a whole in the United Kingdom. We characterise the seasonality, statistical and spatial distribution, and meteorological causes of peak river flows for 521 gauging stations spread across the British Isles. We use annual maximum data from the National River Flow Archive, catchment descriptors from the Flood Estimation Handbook, and historical records of large floods. What we aim to find is in what ways, if any, the record flood for a station is different from more 'typical' floods. For each station, we calculate two indices: the seasonal anomaly and the flood index. Broadly, the seasonal anomaly is the degree to which a station's record flood happens at a different time of year compared to typical floods at that site, whilst the flood index is a station's record flood discharge divided by the discharge of the 1-in-10-year return period event. We find that while annual maximum peaks are dominated by winter frontal rainfall, record floods are disproportionately caused by summer convective rainfall. This analysis also shows that the larger the seasonal anomaly, the higher the flood index. Additionally, stations across the country have record floods that occur in the summer with no notable spatial pattern, yet the most seasonally anomalous record events are concentrated around the south and west of the British Isles. Catchment descriptors tell us little about the flood index at a particular station, but generally areas with lower mean annual precipitation have a higher flood index. The inclusion of case studies from recent and historical examples of notable floods across the UK supplements our analysis and gives insight into how typical these events are, both statistically and meteorologically. Ultimately, record floods in general happen at relatively unexpected times and with unpredictable magnitudes, which is a

DamaGIS: a multisource geodatabase for collection of flood-related damage data

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Saint-Martin, Clotilde; Javelle, Pierre; Vinet, Freddy

2018-06-01

Every year in France, recurring flood events result in several million euros of damage, and reducing the heavy consequences of floods has become a high priority. However, actions to reduce the impact of floods are often hindered by the lack of damage data on past flood events. The present paper introduces a new database for collection and assessment of flood-related damage. The DamaGIS database offers an innovative bottom-up approach to gather and identify damage data from multiple sources, including new media. The study area has been defined as the south of France considering the high frequency of floods over the past years. This paper presents the structure and contents of the database. It also presents operating instructions in order to keep collecting damage data within the database. This paper also describes an easily reproducible method to assess the severity of flood damage regardless of the location or date of occurrence. A first analysis of the damage contents is also provided in order to assess data quality and the relevance of the database. According to this analysis, despite its lack of comprehensiveness, the DamaGIS database presents many advantages. Indeed, DamaGIS provides a high accuracy of data as well as simplicity of use. It also has the additional benefit of being accessible in multiple formats and is open access. The DamaGIS database is available at https://doi.org/10.5281/zenodo.1241089" target="_blank">https://doi.org/10.5281/zenodo.1241089.

High Resolution Flash Flood Forecasting Using a Wireless Sensor Network in the Dallas-Fort Worth Metroplex

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Bartos, M. D.; Kerkez, B.; Noh, S.; Seo, D. J.

2017-12-01

In this study, we develop and evaluate a high resolution urban flash flood monitoring system using a wireless sensor network (WSN), a real-time rainfall-runoff model, and spatially-explicit radar rainfall predictions. Flooding is the leading cause of natural disaster fatalities in the US, with flash flooding in particular responsible for a majority of flooding deaths. While many riverine flood models have been operationalized into early warning systems, there is currently no model that is capable of reliably predicting flash floods in urban areas. Urban flash floods are particularly difficult to model due to a lack of rainfall and runoff data at appropriate scales. To address this problem, we develop a wide-area flood-monitoring wireless sensor network for the Dallas-Fort Worth metroplex, and use this network to characterize rainfall-runoff response over multiple heterogeneous catchments. First, we deploy a network of 22 wireless sensor nodes to collect real-time stream stage measurements over catchments ranging from 2-80 km2 in size. Next, we characterize the rainfall-runoff response of each catchment by combining stream stage data with gage and radar-based precipitation measurements. Finally, we demonstrate the potential for real-time flash flood prediction by joining the derived rainfall-runoff models with real-time radar rainfall predictions. We find that runoff response is highly heterogeneous among catchments, with large variabilities in runoff response detected even among nearby gages. However, when spatially-explicit rainfall fields are included, spatial variability in runoff response is largely captured. This result highlights the importance of increased spatial coverage for flash flood prediction.

Flood disaster and protection measures in Turkey Case Study: May 1998 flood disaster at North Western Black Sea Region of Turkey

International Nuclear Information System (INIS)

Gurer, Ibrahim; Ozguier, Hamza

2004-01-01

Due to geographical location, geology, and topography, Turkey undergoes three main types of natural disasters related to gravity flows; floods, landslides, and snow avalanches. Flooding is second important natural hazard after earthquakes with 18 floods and 23 deaths per year, on average. During 20-21 May 1998, the rainfall which was equal to about four times of long-term mean annual rainfall total of north western Black Sea geographical region of Turkey affected 35.000 m 2 , damaged 1300 km highway, 600 km roads to the villages, and 60 km railway. After the recession of the flood waters, the field survey done proved that 12 highway bridges, 91 small bridges on village roads and 6900 highway culverts, 13.800 m retaining wall and about 500 houses were severely damaged. During the last five years, with the loans and credits provided by World Bank, a series of flood protection structures were designed and built for the rehabilitation of the region. Mostly concentrating on non-structural flood protection studies, a work programme has been drafted in this framework to develop flood management and to reduce or eliminate long-term risk and damage to people and their property from natural hazards and their effects. In this case study, the factors causing the flood disaster are given, and the flood event is analyzed from hydrologic and morphologic points of view. Also the different types of the flood protection measures are exemplified and the experience gained in controlling the flood damages is presented.(Author)

Assessment of Rainfall-induced Landslide Potential and Spatial Distribution

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Chen, Yie-Ruey; Tsai, Kuang-Jung; Chen, Jing-Wen; Chiang, Jie-Lun; Hsieh, Shun-Chieh; Chue, Yung-Sheng

2016-04-01

, and elevation are the secondary important factors. Under the different rainfall, the greater the average of EAR, the more the landslide occurrence and area increments. The determination coefficients of trend lines on the charts of the average of EAR versus number and area of landslide increment are 0.83 and 0.92, respectively. The relations between landslide potential level, degree of land disturbance, and the ratio of number and area of landslide increment corresponding six heavy rainfall events are positive and the determination coefficients of trend lines are 0.82 and 0.72, respectively. The relation between the average of EAR and the area of landslide increment corresponding five heavy rainfall events (excluding Morakot) is positive and the determination coefficient of trend line is 0.98. Furthermore, the relation between the area increment of secondary landslide, average of EAR or the slope disturbance is positive. Under the same slope disturbance, the greater the EAR, the more the area increment of secondary landslide. Contrarily, under the same EAR, the greater the slope disturbance, the more the area increment of secondary landslide. The results of the analysis of this study can be a reference for the government for subsequent countermeasures for slope sediment disaster sensitive area to reduce the number of casualties and significantly reduce the social cost of post-disaster.

A probabilistic approach of the Flash Flood Early Warning System (FF-EWS) in Catalonia based on radar ensemble generation

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Velasco, David; Sempere-Torres, Daniel; Corral, Carles; Llort, Xavier; Velasco, Enrique

2010-05-01

Early Warning Systems (EWS) are commonly identified as the most efficient tools in order to improve the preparedness and risk management against heavy rains and Flash Floods (FF) with the objective of reducing economical losses and human casualties. In particular, flash floods affecting torrential Mediterranean catchments are a key element to be incorporated within operational EWSs. The characteristic high spatial and temporal variability of the storms requires high-resolution data and methods to monitor/forecast the evolution of rainfall and its hydrological impact in small and medium torrential basins. A first version of an operational FF-EWS has been implemented in Catalonia (NE Spain) under the name of EHIMI system (Integrated Tool for Hydrometeorological Forecasting) with the support of the Catalan Water Agency (ACA) and the Meteorological Service of Catalonia (SMC). Flash flood warnings are issued based on radar-rainfall estimates. Rainfall estimation is performed on radar observations with high spatial and temporal resolution (1km2 and 10 minutes) in order to adapt the warning scale to the 1-km grid of the EWS. The method is based on comparing observed accumulated rainfall against rainfall thresholds provided by the regional Intensity-Duration-Frequency (IDF) curves. The so-called "aggregated rainfall warning" at every river cell is obtained as the spatially averaged rainfall over its associated upstream draining area. Regarding the time aggregation of rainfall, the critical duration is thought to be an accumulation period similar to the concentration time of each cachtment. The warning is issued once the forecasted rainfall accumulation exceeds the rainfall thresholds mentioned above, which are associated to certain probability of occurrence. Finally, the hazard warning is provided and shown to the decision-maker in terms of exceeded return periods at every river cell covering the whole area of Catalonia. The objective of the present work includes the

Iowa Flood Information System: Towards Integrated Data Management, Analysis and Visualization

Science.gov (United States)

Demir, I.; Krajewski, W. F.; Goska, R.; Mantilla, R.; Weber, L. J.; Young, N.

2012-04-01

The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts both short-term and seasonal, flood-related data, information and interactive visualizations for communities in Iowa. The key element of the system's architecture is the notion of community. Locations of the communities, those near streams and rivers, define basin boundaries. The IFIS provides community-centric watershed and river characteristics, weather (rainfall) conditions, and streamflow data and visualization tools. Interactive interfaces allow access to inundation maps for different stage and return period values, and flooding scenarios with contributions from multiple rivers. Real-time and historical data of water levels, gauge heights, and rainfall conditions are available in the IFIS by streaming data from automated IFC bridge sensors, USGS stream gauges, NEXRAD radars, and NWS forecasts. Simple 2D and 3D interactive visualizations in the IFIS make the data more understandable to general public. Users are able to filter data sources for their communities and selected rivers. The data and information on IFIS is also accessible through web services and mobile applications. The IFIS is optimized for various browsers and screen sizes to provide access through multiple platforms including tablets and mobile devices. The IFIS includes a rainfall-runoff forecast model to provide a five-day flood risk estimate for around 500 communities in Iowa. Multiple view modes in the IFIS accommodate different user types from general public to researchers and decision makers by providing different level of tools and details. River view mode allows users to visualize data from multiple IFC bridge sensors and USGS stream gauges to follow flooding condition along a river. The IFIS will help communities make better-informed decisions on the occurrence of floods, and will alert communities

Large Scale Processes and Extreme Floods in Brazil

Science.gov (United States)

Ribeiro Lima, C. H.; AghaKouchak, A.; Lall, U.

2016-12-01

Persistent large scale anomalies in the atmospheric circulation and ocean state have been associated with heavy rainfall and extreme floods in water basins of different sizes across the world. Such studies have emerged in the last years as a new tool to improve the traditional, stationary based approach in flood frequency analysis and flood prediction. Here we seek to advance previous studies by evaluating the dominance of large scale processes (e.g. atmospheric rivers/moisture transport) over local processes (e.g. local convection) in producing floods. We consider flood-prone regions in Brazil as case studies and the role of large scale climate processes in generating extreme floods in such regions is explored by means of observed streamflow, reanalysis data and machine learning methods. The dynamics of the large scale atmospheric circulation in the days prior to the flood events are evaluated based on the vertically integrated moisture flux and its divergence field, which are interpreted in a low-dimensional space as obtained by machine learning techniques, particularly supervised kernel principal component analysis. In such reduced dimensional space, clusters are obtained in order to better understand the role of regional moisture recycling or teleconnected moisture in producing floods of a given magnitude. The convective available potential energy (CAPE) is also used as a measure of local convection activities. We investigate for individual sites the exceedance probability in which large scale atmospheric fluxes dominate the flood process. Finally, we analyze regional patterns of floods and how the scaling law of floods with drainage area responds to changes in the climate forcing mechanisms (e.g. local vs large scale).

Probabilistic Design Storm Method for Improved Flood Estimation in Ungauged Catchments

Science.gov (United States)

Berk, Mario; Å pačková, Olga; Straub, Daniel

2017-12-01

The design storm approach with event-based rainfall-runoff models is a standard method for design flood estimation in ungauged catchments. The approach is conceptually simple and computationally inexpensive, but the underlying assumptions can lead to flawed design flood estimations. In particular, the implied average recurrence interval (ARI) neutrality between rainfall and runoff neglects uncertainty in other important parameters, leading to an underestimation of design floods. The selection of a single representative critical rainfall duration in the analysis leads to an additional underestimation of design floods. One way to overcome these nonconservative approximations is the use of a continuous rainfall-runoff model, which is associated with significant computational cost and requires rainfall input data that are often not readily available. As an alternative, we propose a novel Probabilistic Design Storm method that combines event-based flood modeling with basic probabilistic models and concepts from reliability analysis, in particular the First-Order Reliability Method (FORM). The proposed methodology overcomes the limitations of the standard design storm approach, while utilizing the same input information and models without excessive computational effort. Additionally, the Probabilistic Design Storm method allows deriving so-called design charts, which summarize representative design storm events (combinations of rainfall intensity and other relevant parameters) for floods with different return periods. These can be used to study the relationship between rainfall and runoff return periods. We demonstrate, investigate, and validate the method by means of an example catchment located in the Bavarian Pre-Alps, in combination with a simple hydrological model commonly used in practice.

The flash flood of October 2011 in the Magra River basin (Italy): rainstorm characterisation and flood response analysis

Science.gov (United States)

Marchi, Lorenzo; Boni, Giorgio; Cavalli, Marco; Comiti, Francesco; Crema, Stefano; Lucía, Ana; Marra, Francesco; Zoccatelli, Davide

2013-04-01

On 25 October 2011, the Magra River, a stream of northwest Italy outflowing into the Ligurian Sea, was affected by a flash flood, which caused severe economic damage and loss of lives. The catchment covers an area of 1717 km2, of which 605 km2 are drained by the Vara River, the major tributary of the Magra River. The flood was caused by an intense rainstorm which lasted approximately 20 hours. The most intense phase lasted about 8 hours, with rainfall amounts up to around 500 mm. The largest rainfall depths (greater than 300 mm) occurred in a narrow southwest - northeast oriented belt covering an area of approximately 400 km2. This flash flood was studied by analysing rainstorm characteristics, runoff response and geomorphic effects. The rainfall fields used in the analysis are based on data from the Settepani weather radar antenna (located at around 100 km from the study basin) and the local rain gauge network. Radar observations and raingauge data were merged to obtain rainfall estimates at 30 min with a resolution of 1 km2. River stage and discharge rating curves are available for few cross-sections on the main channels. Post-flood documentation includes the reconstruction of peak discharge by means of topographic surveys and application of the slope-conveyance method in 34 cross-sections, observations on the geomorphic effects of the event - both in the channel network and on the hillslopes - and the assessment of the timing of the flood based on interviews to eyewitnesses. Regional authorities and local administrations contributed to the documentation of the flood by providing hydrometeorological data, civil protection volunteers accounts, photos and videos recorded during and immediately after the flood. A spatially distributed rainfall-runoff model, fed with rainfall estimates obtained by the radar-derived observations, was used to check the consistency of field-derived peak discharges and to derive the time evolution of the flood. The assessment of unit

The Irma-sponge Project Frhymap: Flood Risk and Hydrological Mapping

Science.gov (United States)

Hoffmann, L.; Pfister, L.

In the context of both increasing socio-economic developments in floodplains and the recent heavy floodings that have occurred in the Rhine and Meuse basins, the need for reliable hydro-climatological data, easily transposable hydrological and hydraulic models, as well as risk management tools has increased crucially. In the FRHYMAP project, some of these issues were addressed within a common mesoscale experimen- tal basin: the Alzette river basin, located in the Grand-duchy of Luxembourg. The various aspects concerning flooding events, reaching from the hydro-climatological analysis of field data to the risk assessment of socio-economic impacts, taking into account past and future climate and landuse changes were analysed by the six partici- pating research institutes (CREBS, L; CEREG, F; DLR, D; EPFL, CH; UB, D; VUB, B). Hydro-climatological data analysis over the past five decades has shown that in the study area, the increase in westerly and south-westerly atmospheric circulation patterns induced higher winter rainfall totals, leading to more frequent groundwater resurgences and ultimately also to higher daily maximum streamflow of the Alzette. The thus increased flood hazard has nonetheless a certain spatial variability, closely linked to the rainfall distribution patterns, which are strongly depending on the topo- graphical characteristics of the study area. Although the overall regime of the Alzette is more dependent on climate fluctuations, land use changes (mining activities, urbani- sation) had a marked effect on the rainfall-runoff relationship in some sub-basins over the last decades. By linking model parameters to physiographical basin characteris- tics, regionalised and thus easily transposable hydrological models were developed. Within a study area with very little long-term observation series, this technique, com- bined with the use of hydraulic models, allowed to define hydrological hazard pro- ducing and hydrological risk exposed areas. The

Predicting Coastal Flood Severity using Random Forest Algorithm

Science.gov (United States)

Sadler, J. M.; Goodall, J. L.; Morsy, M. M.; Spencer, K.

2017-12-01

Coastal floods have become more common recently and are predicted to further increase in frequency and severity due to sea level rise. Predicting floods in coastal cities can be difficult due to the number of environmental and geographic factors which can influence flooding events. Built stormwater infrastructure and irregular urban landscapes add further complexity. This paper demonstrates the use of machine learning algorithms in predicting street flood occurrence in an urban coastal setting. The model is trained and evaluated using data from Norfolk, Virginia USA from September 2010 - October 2016. Rainfall, tide levels, water table levels, and wind conditions are used as input variables. Street flooding reports made by city workers after named and unnamed storm events, ranging from 1-159 reports per event, are the model output. Results show that Random Forest provides predictive power in estimating the number of flood occurrences given a set of environmental conditions with an out-of-bag root mean squared error of 4.3 flood reports and a mean absolute error of 0.82 flood reports. The Random Forest algorithm performed much better than Poisson regression. From the Random Forest model, total daily rainfall was by far the most important factor in flood occurrence prediction, followed by daily low tide and daily higher high tide. The model demonstrated here could be used to predict flood severity based on forecast rainfall and tide conditions and could be further enhanced using more complete street flooding data for model training.

ENSO-Based Index Insurance: Approach and Peru Flood Risk Management Application

Science.gov (United States)

Khalil, A. F.; Kwon, H.; Lall, U.; Miranda, M. J.; Skees, J. R.

2006-12-01

Index insurance has recently been advocated as a useful risk transfer tool for disaster management situations where rapid fiscal relief is desirable, and where estimating insured losses may be difficult, time consuming, or subject to manipulation and falsification. For climate related hazards, a rainfall or temperature index may be proposed. However, rainfall may be highly spatially variable relative to the gauge network, and in many locations data are inadequate to develop an index due to short time-series and the spatial dispersion of stations. In such cases, it may be helpful to consider a climate proxy index as a regional rainfall index. This is particularly useful if a long record is available for the climate index through an independent source and it is well correlated with the regional rainfall hazard. Here, ENSO related climate indices are explored for use as a proxy to extreme rainfall in one of the departments of Peru -- Piura. The ENSO index insurance product may be purchased by banks or microfinance institutions (MFIs) to aid agricultural damage relief in Peru. Crop losses in the region are highly correlated with floods, but are difficult to assess directly. Beyond agriculture, many other sectors suffer as well. Basic infrastructure is destroyed during the most severe events. This disrupts trade for many micro-enterprises. The reliability and quality of the local rainfall data is variable. Averaging the financial risk across the region is desirable. Some issues with the implementation of the proxy ENSO index are identified and discussed. Specifically, we explore (a) the reliability of the index at different levels of probability of exceedance of maximum seasonal rainfall; (b) the potential for clustering of payoffs; (c) the potential that the index could be predicted with some lead time prior to the flood season; and (d) evidence for climate change or non-stationarity in the flood exceedance probability from the long ENSO record. Finally, prospects for

Application of Virtual Rain and Stream Gauge Information Service for Improved Flood Early Warning System in Lower Mekong Countries

Science.gov (United States)

Basnayake, S. B.; Jayasinghe, S.; Meechaiya, C.; Markert, K. N.; Lee, H.; Towashiraporn, P.; Anderson, E.; Okeowo, M. A.

2017-12-01

Asia is the most vulnerable region in the world to hydro-meteorological extreme events, exacerbated by climate variability and change. Impacts of floods have been on the rapid increase in the recent decades. Myanmar is one of the most vulnerable countries in the lower Mekong region due to its socioeconomic situation (eg; Nargis in 2008, monsoon floods in 2015, etc). Early warning is an effective way to prepare for hydro-meteorological hazards, to minimize disaster risks; however, early warning systems in Myanmar are seriously hampered by limited observation networks. The Virtual Rain and Stream Gauge Information Service (VRSGIS) has been developed by SERVIR-Mekong program of Asian Disaster Preparedness Center (ADPC) to address these gaps and to provide dense, satellite-based rainfall and water level data, which are calibrated and validated with available in-situ observations. This service would enhance decision making in lower Mekong countries, including Myanmar, to minimize impacts of impending disasters. This service contains rainfall data from GPM IMERG and GSMap, CMORPH, TRMM, and CHIRPS, and water levels for 15 locations using Jason-2/3 altimetry. The virtual daily rainfall data sets are being calibrated with Gamma distribution method and are made publicly accessible through a user-friendly web interface.This paper presents a case study of satellite-derived rainfall data accessed from VRSGIS for hydrological modeling in Myanmar, to estimate inundation areas in Kalay township area of Chindwin River basin during the country's worst flood in 2015. Twelve out of fourteen States of Myanmar were severely affected, 103 people were killed, and one million were displaced due to heavy rains associated with Komen cyclone. The aforementioned rainfall data products are used as inputs for HEC-HMS hydrological runoff model to calculate river flows along Chindwin River, and HEC-RAS hydraulic model is used to estimate inundation areas in downstream including Kalay township

An early warning system for flash floods in Egypt

Science.gov (United States)

Cools, J.; Abdelkhalek, A.; El Sammany, M.; Fahmi, A. H.; Bauwens, W.; Huygens, M.

2009-09-01

This paper describes the development of the Flash Flood Manager, abbreviated as FlaFloM. The Flash Flood Manager is an early warning system for flash floods which is developed under the EU LIFE project FlaFloM. It is applied to Wadi Watier located in the Sinai peninsula (Egypt) and discharges in the Red Sea at the local economic and tourist hub of Nuweiba city. FlaFloM consists of a chain of four modules: 1) Data gathering module, 2) Forecasting module, 3) Decision support module or DSS and 4) Warning module. Each module processes input data and consequently send the output to the following module. In case of a flash flood emergency, the final outcome of FlaFloM is a flood warning which is sent out to decision-makers. The ‘data gathering module’ collects input data from different sources, validates the input, visualise data and exports it to other modules. Input data is provided ideally as water stage (h), discharge (Q) and rainfall (R) through real-time field measurements and external forecasts. This project, however, as occurs in many arid flash flood prone areas, was confronted with a scarcity of data, and insufficient insight in the characteristics that release a flash flood. Hence, discharge and water stage data were not available. Although rainfall measurements are available through classical off line rain gauges, the sparse rain gauges network couldn’t catch the spatial and temporal characteristics of rainfall events. To overcome this bottleneck, we developed rainfall intensity raster maps (mm/hr) with an hourly time step and raster cell of 1*1km. These maps are derived through downscaling from two sources of global instruments: the weather research and forecasting model (WRF) and satellite estimates from the Tropical Rainfall Measuring Mission (TRMM). The ‘forecast module’ comprises three numerical models that, using data from the gathering module performs simulations on command: a rainfall-runoff model, a river flow model, and a flood model. A