scholarly journals Monthly extreme rainfall risk envelope graph method development and application in Algeria

Author(s):  
Sara Zeroual ◽  
Zekâi Şen ◽  
Hamouda Boutaghane ◽  
Mahmoud Hasbaia

Abstract Rainfall patterns are bound to change as a result of global warming and climate change impacts. Rainfall events are dependent on geographic location, geomorphology, coastal area closeness and general circulation air movements. Accordingly, there are increases and decreases at different meteorology station time-series records leading to extreme events such as droughts and floods. This paper suggests a methodology in terms of envelope curves for monthly extreme rainfall event occurrences at a set of risk levels or return periods that may trigger the extreme occurrences at meteorology station catchments. Generally, in many regions, individual storm rainfall records are not available for intensity–duration–frequency (IDF) curve construction. The main purpose of this paper is, in the absence of individual storm rainfall records, to suggest monthly envelope curves, which provide a relationship between return period and monthly extreme rainfall values. The first step is to identify each monthly extreme rainfall records probability distribution function (PDF) for risk level and return period calculations. Subsequently, the return period rainfall amount relationships are presented on double-logarithmic graphs with the best power model as a set of envelope curves. The applications of these methodologies are implemented for three Hodna drainage basin meteorology station rainfall records in northern Algeria. It is concluded that the most extreme rainfall risk months are June, August and September, which may lead to floods or flash floods in the study area. A new concept is presented for the possible extreme value triggering months through the envelope curves as ‘low’, ‘medium’ and ‘high’ class potentials.

2017 ◽  
Vol 8 (3) ◽  
pp. 388-411 ◽  
Author(s):  
Hamed Tavakolifar ◽  
Ebrahim Shahghasemi ◽  
Sara Nazif

Climate change has impacted all phenomena in the hydrologic cycle, especially extreme events. General circulation models (GCMs) are used to investigate climate change impacts but because of their low resolution, downscaling methods are developed to provide data with high enough resolution for regional studies from GCM outputs. The performance of rainfall downscaling methods is commonly acceptable in preserving average characteristics, but they do not preserve the extreme event characteristics especially rainfall amount and distribution. In this study, a novel downscaling method called synoptic statistical downscaling model is proposed for daily precipitation downscaling with an emphasis on extreme event characteristics preservation. The proposed model is applied to a region located in central Iran. The results show that the developed model can downscale all percentiles of precipitation events with an acceptable performance and there is no assumption about the similarity of future rainfall data with the historical observations. The outputs of CCSM4 GCM for two representative concentration pathways (RCPs) of RCP4.5 and RCP8.5 are used to investigate the climate change impacts in the study region. The results show 40% and 30% increase in the number of extreme rainfall events under RCP4.5 and RCP8.5, respectively.


2018 ◽  
Vol 77 (8) ◽  
pp. 2146-2154 ◽  
Author(s):  
Manfred Kleidorfer ◽  
Franz Tscheikner-Gratl ◽  
Tanja Vonach ◽  
Wolfgang Rauch

Abstract Urban drainage systems are designed to capture the runoff for a certain return period of a design rainfall event. Typically, numerical models are used, which are calibrated by comparing model response and measured system performance. The applicability of such models to predict the system behaviour under extreme events is unclear, as usually then no data are available. This paper describes the analysis of an extreme rainfall event in the year 2016. The event is characterized by a very short duration and very high rainfall intensities. The maximum-recorded rainfall peak was 47.1 mm rainfall within 10 min, which corresponds to a return period of 500 years. The event caused local flooding on streets, interruptions of traffic and damages in buildings. In order to improve the flood resilience of the city, the event was analysed with an existing 1D hydrodynamic model of the sewer system. Model results were compared to water level measurements in the drainage system and citizen observations of surface flooding (gathered from social media and citizen reports). Although the hydrodynamic model could reproduce water level measurements in parts of the system, the plausibility check using descriptive data showed that the model failed to predict flooding in some areas.


2016 ◽  
Vol 96 (4) ◽  
pp. 504-514 ◽  
Author(s):  
Wenjing Chen ◽  
Xin Jia ◽  
Chunyi Li ◽  
Haiqun Yu ◽  
Jing Xie ◽  
...  

Extreme rainfall events are infrequent disturbances that affect urban environments and soil respiration (Rs). Using data measured in an urban forest ecosystem in Beijing, China, we examined the link between gross primary production (GPP) and soil respiration on a diurnal scale during an extreme rainfall event (i.e., the “21 July 2012 event”), and we examined diel and seasonal environmental controls on Rs. Over the seasonal cycle, Rs increased exponentially with soil temperature (Ts). In addition, Rs was hyperbolically related to soil volumetric water content (VWC), increasing with VWC below a threshold of 0.17 m3 m−3, and then decreasing with further increases in VWC. Following the extreme rainfall event (177 mm), Rs showed an abrupt decrease and then maintained a low value of ∼0.3 μmol m−2 s−1 for about 8 h as soil VWC reached the field capacity (0.34 m3 m−3). Rs became decoupled from Ts and increased very slowly, while GPP showed a greater increase. A bivariate Q10-hyperbolical model, which incorporates both Ts and VWC effects, better fits Rs than the Q10 model in summer but not for whole year.


2011 ◽  
Vol 24 (7) ◽  
pp. 1913-1921 ◽  
Author(s):  
Mateus da Silva Teixeira ◽  
Prakki Satyamurty

Abstract A new approach to define heavy and extreme rainfall events based on cluster analysis and area-average rainfall series is presented. The annual frequency of the heavy and extreme rainfall events is obtained for the southeastern and southern Brazil regions. In the 1960–2004 period, 510 (98) and 466 (77) heavy (extreme) rainfall events are identified in the two regions. Monthly distributions of the events closely follow the monthly climatological rainfall in the two regions. In both regions, annual heavy and extreme rainfall event frequencies present increasing trends in the 45-yr period. However, only in southern Brazil is the trend statistically significant. Although longer time series are necessary to ensure the existence of long-term trends, the positive trends are somewhat alarming since they indicate that climate changes, in terms of rainfall regimes, are possibly under way in Brazil.


2021 ◽  
Vol 134 (1) ◽  
Author(s):  
Manas Pant ◽  
Soumik Ghosh ◽  
Shruti Verma ◽  
Palash Sinha ◽  
R. K. Mall ◽  
...  

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