Relevant bibliographies by topics / Rainfall extreme

Academic literature on the topic 'Rainfall extreme'

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Published: 14 March 2023

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Journal articles on the topic "Rainfall extreme"

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Nguyen, V.-T.-V., T. D. Nguyen, and F. Ashkar. "Regional frequency analysis of extreme rainfalls." Water Science and Technology 45, no. 2 (January 1, 2002): 75–81. http://dx.doi.org/10.2166/wst.2002.0030.

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This study proposes two alternative methods for estimating the distribution of extreme rainfalls for sites where rainfall data are available (gaged sites) and for locations without data (ungaged sites). The first method deals with the estimation of short-duration rainfall extremes from available rainfall data for longer durations using the “scale-invariance” concept to account for the relationship between statistical properties of extreme rainfall processes for different time scales. The second method is concerned with the estimation of extreme rainfalls for ungaged sites. This method relies on a new definition of homogeneous sites. Results of the numerical application using data from a network of 10 recording rain gauges in Quebec (Canada) indicate that the proposed methods are able to provide extreme rainfall estimates that are comparable with those based on observed at-site rainfall data.
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Indarto, Indarto. "Trend and spatial variability of 1-day extreme rainfall from 1980 - 2015: study at the adminisitrative area of UPT PSDA Pasuruan." Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) 8, no. 1 (March 31, 2019): 29. http://dx.doi.org/10.23960/jtep-l.v8i1.29-39.

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This study aims to analyze trends, shift and spatial variability of extreme-rainfall in the area of UPT PSDA Pasuruan. The daily rainfall data from 64 stations from 1980 until 2015 were used as main input. The 1-day extreem rainfall data is determined as the maximum annual of 24-hour rainfall events. The statistical analysis using Mann-Kendall, Rank-Sum, and Median Crossing Test using significance level α = 0,05. The spatial variability of extrem rainfall data is described using average annual 24-hour rainfall during the periods of record. Each station is represented by one value. The values are then interpolated using IDW interpolation methods to maps the spatial variability of extreem rainfall event. The results show the value of statistical test for each stations that show the existing trend, shift, or randomness of data. The result also produce thematic maps show the spatial variability of extreme rainfall and the value of each trend.
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Hopkins, David. "Extreme rainfall events." Weather 61, no. 1 (January 2006): 30. http://dx.doi.org/10.1002/wea.200661108.

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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences 18, no. 10 (October 15, 2014): 4065–76. http://dx.doi.org/10.5194/hess-18-4065-2014.

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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary generalised Pareto distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on intensity–frequency–duration (IFD) relationships. The methodology developed was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, 3 h and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Yilmaz, A. G., I. Hossain, and B. J. C. Perera. "Effect of climate change and variability on extreme rainfall intensity–frequency–duration relationships: a case study of Melbourne." Hydrology and Earth System Sciences Discussions 11, no. 6 (June 16, 2014): 6311–42. http://dx.doi.org/10.5194/hessd-11-6311-2014.

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Abstract. The increased frequency and magnitude of extreme rainfall events due to anthropogenic climate change, and decadal and multi-decadal climate variability question the stationary climate assumption. The possible violation of stationarity in climate can cause erroneous estimation of design rainfalls derived from extreme rainfall frequency analysis. This may result in significant consequences for infrastructure and flood protection projects since design rainfalls are essential input for design of these projects. Therefore, there is a need to conduct frequency analysis of extreme rainfall events in the context of non-stationarity, when non-stationarity is present in extreme rainfall events. A methodology consisting of, threshold selection, extreme rainfall data (peaks over threshold data) construction, trend and non-stationarity analysis, and stationary and non-stationary Generalized Pareto Distribution (GPD) models was developed in this paper to investigate trends and non-stationarity in extreme rainfall events, and potential impacts of climate change and variability on Intensity–Frequency–Duration (IFD) relationships. The developed methodology was successfully implemented using rainfall data from an observation station in Melbourne (Australia) for storm durations ranging from 6 min to 72 h. Although statistically significant trends were detected in extreme rainfall data for storm durations of 30 min, and 3 and 48 h, statistical non-stationarity tests and non-stationary GPD models did not indicate non-stationarity for these storm durations and other storm durations. It was also found that the stationary GPD models were capable of fitting extreme rainfall data for all storm durations. Furthermore, the IFD analysis showed that urban flash flood producing hourly rainfall intensities have increased over time.
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Arnbjerg-Nielsen, K., P. Harremoës, and P. S. Mikkelsen. "Dissemination of regional rainfall analysis in design and analysis of urban drainage at un-gauged locations." Water Science and Technology 45, no. 2 (January 1, 2002): 69–74. http://dx.doi.org/10.2166/wst.2002.0029.

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A research program in Denmark on statistical modelling of rainfall has resulted in a model for regional distribution of rainfall extremes. The results show that extreme rainfalls critical to the hydraulic function of urban drainage systems and the pollution discharge are subject to a significant regional variation of extreme rainfalls throughout the country. This has implications for design and analysis of all practical problems related to urban drainage, since the rainfall data so far recommended as input to engineering analyses underestimates the problems. Consequently, the Danish Water Pollution Control Committee has issued a statement recommending a new engineering practice. The dissemination of the research results proved to be difficult due to lack of understanding of the concepts of the new paradigm by practitioners. The traditional means of communication was supplemented by user-friendly spreadsheets and easy access to rainfall data as well as giving courses on the new paradigm. This has eased the implementation of the new concepts greatly.
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Williams, C. J. R., D. R. Kniveton, and R. Layberry. "Influence of South Atlantic Sea Surface Temperatures on Rainfall Variability and Extremes over Southern Africa." Journal of Climate 21, no. 24 (December 15, 2008): 6498–520. http://dx.doi.org/10.1175/2008jcli2234.1.

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Abstract It is generally agreed that changing climate variability, and the associated change in climate extremes, may have a greater impact on environmentally vulnerable regions than a changing mean. This research investigates rainfall variability, rainfall extremes, and their associations with atmospheric and oceanic circulations over southern Africa, a region that is considered particularly vulnerable to extreme events because of numerous environmental, social, and economic pressures. Because rainfall variability is a function of scale, high-resolution data are needed to identify extreme events. Thus, this research uses remotely sensed rainfall data and climate model experiments at high spatial and temporal resolution, with the overall aim being to investigate the ways in which sea surface temperature (SST) anomalies influence rainfall extremes over southern Africa. Extreme rainfall identification is achieved by the high-resolution microwave/infrared rainfall algorithm dataset. This comprises satellite-derived daily rainfall from 1993 to 2002 and covers southern Africa at a spatial resolution of 0.1° latitude–longitude. Extremes are extracted and used with reanalysis data to study possible circulation anomalies associated with extreme rainfall. Anomalously cold SSTs in the central South Atlantic and warm SSTs off the coast of southwestern Africa seem to be statistically related to rainfall extremes. Further, through a number of idealized climate model experiments, it would appear that both decreasing SSTs in the central South Atlantic and increasing SSTs off the coast of southwestern Africa lead to a demonstrable increase in daily rainfall and rainfall extremes over southern Africa, via local effects such as increased convection and remote effects such as an adjustment of the Walker-type circulation.
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PASUPALAK, S., G. PANIGRAHI, T. PANIGRAHI, S. MOHANTY, and K. K. SINGH. "Extreme rainfall events over Odisha state, India." MAUSAM 68, no. 1 (November 30, 2021): 131–38. http://dx.doi.org/10.54302/mausam.v68i1.442.

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Extreme rainfall events are a significant cause of loss of life and livelihoods in Odisha. Objectives of the present study are to determine the trend of the extreme rainfall events during 1991-2014 and to compare the events between two periods before and after 1991. Block level daily rainfall data were used in identifying the extreme rainfall events, while district level aggregation was used in analysing the trend in three categories, viz., heavy, very heavy and extremely heavy rainfall as per criteria given by India Meteorological Department (IMD). The state as a whole received one extremely heavy, nine very heavy, and forty heavy rainfall events in a year. When percentage of occurrence of each category out of the total extreme events over different districts was considered, maximum % of extremely heavy rainfall occurred in Kalahandi (5.8%), very heavy rainfall in Bolangir (23.8%) and heavy rainfall in Keonjhargarh (85.4%). Trend analysis showed that number of extreme rainfall events increased in a few districts, namely, Bolangir, Nuapada, Keonjhargarh, Koraput, Malkangiri, and Nawarangapur and did not change in other districts. In Puri district, extremely heavy rainfall frequency decreased. New all-time record high one-day rainfall events were observed in twenty districts during 1992 to 2014, surpassing the earlier records, which could be attributed to climate change induced by global warming. Interior south Odisha was found as the hot spot for extreme rainfalls.
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Cross, David, Christian Onof, Hugo Winter, and Pietro Bernardara. "Censored rainfall modelling for estimation of fine-scale extremes." Hydrology and Earth System Sciences 22, no. 1 (January 26, 2018): 727–56. http://dx.doi.org/10.5194/hess-22-727-2018.

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Abstract. 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.
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Agilan, V., and N. V. Umamahesh. "Rainfall Generator for Nonstationary Extreme Rainfall Condition." Journal of Hydrologic Engineering 24, no. 9 (September 2019): 04019027. http://dx.doi.org/10.1061/(asce)he.1943-5584.0001821.

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Dissertations / Theses on the topic "Rainfall extreme"

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HELLIES, MATTEO. "Extreme rainfall regime characterization in Sardinia using daily rainfall data." Doctoral thesis, Università degli Studi di Cagliari, 2016. http://hdl.handle.net/11584/266863.

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For the design of hydraulic structures for flood conveyance and discharge, or protection of territory against flood is fundamental the knowledge of the ``extreme rainfall regime'' in the area where the hydraulic structures must be set up. Indeed the design flood is commonly evaluated as output of rainfall-runoff models that receive as input the quantitative description of a rainfall extreme event with a given exceedance probability. This dissertation assesses the performance of different statistical approaches in characterizing extreme rainfall in the island of Sardinia (Italy). After a detailed review of the theoretical bases of existing methodologies, we compare the results obtained from the use of: a) a Generalized Extreme value (GEV) distribution model, and a Two component Extreme Value (TCEV) distribution model, both applied to yearly maxima of daily rainfall, and b) a Generalized Pareto (GP) distribution model applied to rainfall excesses above a properly specified threshold. For the latter purpose, we use the Multiple Threshold Method (MTM) developed by Deidda(2010), which demonstrate good performance also in the case of quantized records. In order to describe the spatial variation of TCEV, GEV and GP model parameters a regional approach based on homogeneous regions, and two versions of Kriging (a commonly used geostatistical approach) i.e. ordinary Kriging (OK), and Kriging for uncertain Data (KUD), are compared. The obtained results are very promising, pointing towards the use of: a)a GEV distribution model for yearly rainfall maxima, and a KUD model to describe the spatial variation of model parameters, and b)a GP model for rainfall excesses and either an OK or a KUD model for the spatial variation of model parameters. The reason why the OK and KUD approaches lead to the same results in the GP case, is attributed to the robustness of the MTM method.
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Nguyen, Tan Danh. "Regional estimation of extreme rainfall events." Thesis, McGill University, 2003. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=84300.

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The first part of the research deals with the estimation of extreme rainfalls for locations where rainfall records are sufficiently available (gaged sites); the second part is concerned with cases where rainfall data are limited (partially-gaged sites); and finally the third part involves the most complex situation where rainfall data are unavailable (ungaged sites).
For gaged sites, two methods were developed for estimating the annual extreme (AE) rainfalls based on the simple scaling behaviour of the first three non-central moments (NCMs) of the AE rainfall processes and using the Generalized Extreme Value (GEV) distribution as the parent distribution. The first estimation method was called one-moment (OM) method since it only relied on the first-order NCM of AE rainfall series in the computation of the rainfall quantiles, while the second method was called three-moment (TM) procedure since it used all first three NCMs of AE rainfalls in the estimation of the quantiles.
For partially-gaged and ungaged sites, a new approach to defining rainfall homogeneous regions has been proposed based on the similarity of rainfall occurrences at different raingage stations. In addition, a Principal Component Analysis technique was used to assess the similarity of raingages and to delineate homogeneous regions.
On the basis of the proposed method for identifying rainfall homogeneous regions, two new methods (PG-1 and PG-2) were developed for estimating annual maximum (AM) rainfalls at partially gauged sites. These methods were also based on the scaling properties of AM rainfall series for different durations.
For ungaged sites, three methods (UG-1, UG-2, and NR) were proposed for estimating AM rainfalls. Method UG-1 was based on the NCMs of AM rainfalls at an ungaged site that were computed by direct interpolation of the corresponding NCM values from the gaged sites within the same homogeneous region. Method UG-2 used the pooled data set from all gaged sites in the homogeneous region for this computation. On the other hand, the NR method estimated the NCMs of AM rainfalls for an ungaged site using the regional regression between the first three NCMs and the number of rainfall occurrence (NR) values that were interpolated from the NR values of the gaged sites.
Finally, to assess the uncertainty of extreme rainfall estimates, two new methods (CI-1 and CI-2) were developed for computing the confidence limits (CLs) based on these estimated values. The proposed methods were based on the bootstrap technique and the scaling properties of the NCMs of extreme rainfall series.
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Smith, Elizabeth. "Bayesian modelling of extreme rainfall data." Thesis, University of Newcastle Upon Tyne, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.424142.

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Zhou, Chen. "On extreme value statistics : maximum likelihood, portfolio optimization, extremal rainfall, Internet auctions = Over extreme waarden statistiek /." Rotterdam : Erasmus Universiteit, 2008. http://opac.nebis.ch/cgi-bin/showAbstract.pl?u20=9789051709124.

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Langousis, Andreas 1981. "Extreme rainfall intensities and long-term rainfall risk from tropical cyclones." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/47737.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2009.
Includes bibliographical references (leaves 78-85).
We develop a methodology for the frequency of extreme rainfall intensities caused by tropical cyclones (TCs) in coastal areas. The mean rainfall field associated with a TC with maximum tangential wind speed Vmax, radius of maximum winds Rmax, and translation speed Vmax, is obtained using a physically-based model, whereas rainfall variability at both large scales (from storm to storm) and small scales (due to rainbands and local convection) is modeled statistically. The statistical component is estimated using precipitation radar (PR) data from the TRMM mission. Taylor's hypothesis is used to convert spatial rainfall intensity fluctuations to temporal fluctuations at a given location A. The combined physical-statistical model gives the distribution of the maximum rainfall intensity at A during a period of duration D for a TC with characteristics (Vmax, Rmax, Vt) that passes at a given distance from A. To illustrate the use of the model for long-term rainfall risk analysis, we formulate a recurrence model for tropical cyclones in the Gulf of Mexico that make landfall between longitudes 85°-95°W. We then use the rainfall and recurrence models to assess the rainfall risk for New Orleans. For return periods of 100 years or more and long averaging durations (D around 12-24 hours), tropical cyclones dominate over other rainfall event types, whereas the reverse is true for shorter return periods or shorter averaging durations.
by Andreas Langousis.
Ph.D.
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Guthrie, James Harold. "Extreme rainfall in the greater Calgary area." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ64957.pdf.

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Zhou, Chen. "On extreme value statistics maximum likelihood portfolio optimation extremal rainfall Internet auctions /." [Amsterdam] : Rotterdam : Thela Thesis ; Erasmus University [Host], 2008. http://hdl.handle.net/1765/14290.

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Keef, Caroline. "Spatial dependence of river flooding and extreme rainfall." Thesis, Lancaster University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.485231.

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The extent of spatial dependence of flooding and extreme rainfall in Britain is unknown. In this thesis we develop existing extreme value theory to study this phenomenon. It is important to know the level of spatial dependence of flooding because if a flood occurs at multiple sites at the same time the consequences for (for example) the emergency services and the insurance industry can be more severe than if these floods occurred at different times. There are various features of river flow and rainfall data that complicate the estimation of extremal dependence. The two main features are the presence of missing data and the temporal dependence of the individual time series. Heffernan and Tawn (2004) developed a flexible method for modelling multivariate extreme values that can be used for a large number of variables. In this thesis we develop and extend this method to handle the presence of missing data and temporal dependence. We apply this extended method separately to river flow and rainfall data to estimate the level of spatial dependence of flooding and extreme rainfall over Britain. We find that heterogeneous regions in terms of the geology and soil types show low levels of spatial dependence. As we would expect we also find that connected rivers show a high level of dependence between them. We also find that the upland regions of Britain have low levels of spatial dependence of extreme rainfall.
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Atyeo, Jonathan. "Models for trends and dependence in extreme rainfall." Thesis, University of Newcastle Upon Tyne, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440569.

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De, Waal Jan Hofmeyr. "Extreme rainfall distributions : analysing change in the Western Cape." Thesis, Stellenbosch : Stellenbosch University, 2012. http://hdl.handle.net/10019.1/71654.

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Thesis (MSc)--Stellenbosch University, 2012.
Severe floods in the Western Cape have caused significant damage to hydraulic structures, roads and other infrastructure over the past decade. The current design criteria for these structures and flood return level calculations are based on the concept of stationarity, which assumes that natural systems vary within an envelope of variability that does not change with time. In the context of regional climate change and projected changes in rainfall intensity, the basis for these calculations may become unrealistic with the passage of time. Hydraulic structures and other infrastructure may become more vulnerable to damaging floods because of changing hydroclimatic conditions. This project assesses the changes in extreme rainfall values over time across the Western Cape, South Africa. Using a Generalised Pareto Distribution, this study examines the changes in return levels across the Western Cape region for the periods 1900-1954 and 1955-2010. Of the 137 rainfall stations used in this research, 85 (62%) showed an increase in 50-year return level, 30 (22%) a decrease in 50-year return level and 22 (16%) stations displayed little change in rainfall intensity over time. While there were no clear spatial patterns to the results, they clearly indicate an increase in frequency of intense rainfalls in the latter half of the 20th and early 21st century. The changes in return level are also accompanied by a change in the frequency of high intensity 2-3 day long storms. 115 (84%) of the 137 rainfall stations showed an increase in the frequency of long duration, high intensity storms over the data record. This change generates a shifting risk profile of extreme rainfalls, which, in turn, creates challenges for the design of hydraulic structures and any infrastructure exposed to the resulting damaging floods. It can therefore be argued that it is inappropriate to design structures or manage water resources assuming stationarity of climate and that these principles should be assessed in order to reduce the risk of flood damage owing to increasing storm intensity. KEY WORDS Flood Risk, Stationarity, Disaster Risk, Hazard, Extreme Rainfall, Generalized Pareto Distribution, Climate
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Books on the topic "Rainfall extreme"

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Dr, Nazrul Islam Md, and SAARC Meteorological Research Centre, eds. Understanding the rainfall climatology and detection of extreme weather events in SAARC region. Dhaka: SAARC Meteorological Research Centre, 2008.

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Khaladkar, R. M. Alarming rise in the number and intensity of extreme point rainfall events over the Indian region under climate change scenario. Pune: Indian Institute of Tropical Meteorology, 2009.

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Daoo, V. J. Extreme value analysis of meteorological parameters and long term (1959-1996) rainfall statistics at Trombay. Mumbai, India: Bhabha Atomic Research Centre, 1999.

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Lam, Ching-chi. Extreme rainfall statistics and design rainstorm profiles at selected locations in Hong Kong. Kowloon, Hong Kong: Royal Observatory, 1994.

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Dr, Nazrul Islam Md, and SAARC Meteorological Research Centre, eds. Understanding the rainfall climatology and detection of extreme weather events in SAARC region. Dhaka: SAARC Meteorological Research Centre, 2008.

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Tattelman, Paul. Model vertical profiles of extreme rainfall rate, liquid water content, and drop-size distribution. Hanscom AFB, MA: Atmospheric Sciences Division, Air Force Geophysics Laboratory, 1985.

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Lanning-Rush, Jennifer. Extreme precipitation depths for Texas, excluding the Trans-Pecos region. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1998.

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Lanning-Rush, Jennifer. Extreme precipitation depths for Texas, excluding the Trans-Pecos region. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1998.

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Lanning-Rush, Jennifer. Extreme precipitation depths for Texas, excluding the Trans-Pecos region. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1998.

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Lanning-Rush, Jennifer. Extreme precipitation depths for Texas, excluding the Trans-Pecos region. Austin, Tex: U.S. Dept. of the Interior, U.S. Geological Survey, 1998.

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Book chapters on the topic "Rainfall extreme"

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Olaguera, Lyndon Mark P., Faye Abigail T. Cruz, Julie Mae B. Dado, and Jose Ramon T. Villarin. "Complexities of Extreme Rainfall in the Philippines." In Extreme Natural Events, 129–46. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2511-5_5.

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Sharma, R. S., and B. K. Mandal. "Rainfall Variability and Extreme Rainfall Events Over Jharkhand State." In Wastewater Reuse and Watershed Management, 401–14. Includes bibliographical references and index.: Apple Academic Press, 2019. http://dx.doi.org/10.1201/9780429433986-34.

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Mason, John, Paul R. Brown, Jonathan D. C. Webb, and Robert K. Doe. "Extreme Rainfall and Flash Floods in the United Kingdom and Ireland." In Extreme Weather, 261–82. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118949986.ch14.

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Veress, Márton. "Intense Rainfall and Karst Doline Evolution." In Geomorphological impacts of extreme weather, 327–45. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-6301-2_21.

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Williams, Charles J. R., Dominic R. Kniveton, and R. Layberry. "Extreme Rainfall Events over Southern Africa." In Advances in Global Change Research, 71–100. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-3842-5_4.

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Prat, Olivier P., and Brian R. Nelson. "Satellite Precipitation Measurement and Extreme Rainfall." In Advances in Global Change Research, 761–90. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-35798-6_16.

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El Adlouni, Salaheddine, and Taha B. M. J. Ouarda. "Frequency analysis of extreme rainfall events." In Geophysical Monograph Series, 171–88. Washington, D. C.: American Geophysical Union, 2010. http://dx.doi.org/10.1029/2010gm000976.

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Anandh, P. C., Naresh Krishna Vissa, and Bhishma Tyagi. "Statistical Characteristics of Extreme Rainfall Events Over the Indian Subcontinent." In Extreme Natural Events, 109–27. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2511-5_4.

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Balogun, R. Ayodeji, E. Adesanya Adefisan, Z. Debo Adeyewa, and E. Chilekwu Okogbue. "Thermodynamic Environment During the 2009 Burkina Faso and 2012 Nigeria Flood Disasters: Case Study." In African Handbook of Climate Change Adaptation, 1705–20. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_143.

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AbstractCritical or extreme atmospheric conditions which could result in flood disasters are important output for numerical weather forecast. This research applied thermodynamic variables to investigate the environment of two flood scenarios in West Africa as captured by the Tropical Rainfall Measurement Mission (TRMM) satellite. Results from the two case studies of flood events, in (i) Burkina Faso and (ii) Nigeria savannah, investigated in this research work, indicated that the September 1st 2009 flood, which was as a result of a single volumetric rainfall event of 408,070.60 ((mm/h)*km2) with 65% convective region in Burkina Faso, was initiated by interactions between extremely large lower tropospheric wind shear and cold pool dynamics. The case of the Nigeria savannah floods between July and September, 2012, was triggered by both continuous rainfall and release of water from the lagdo dam in Cameroon, which affected most of the communities in the river Benue axis. The continuous rainfalls were found to be as a result of extremely high convergence of moisture in the river Benue axis at different locations and periods. One of such rainfall events, as captured by TRMM satellite during September 29, 2012 in the Nigeria rainforest zone, indicated that the volumetric rainfall is 351,310.9 ((mm/h)*km2) with only 34% convective portion. From these results, it can be deduced that a combination of thermodynamic environmental variables, volume rainfall, and other satellite-derived convective parameters could provide important information for flood forecasting.
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Hsu, Kuo-Lin, Ali Behrangi, Bisher Imam, and Soroosh Sorooshian. "Extreme Precipitation Estimation Using Satellite-Based PERSIANN-CCS Algorithm." In Satellite Rainfall Applications for Surface Hydrology, 49–67. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-2915-7_4.

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Conference papers on the topic "Rainfall extreme"

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Radi, Noor Fadhilah Ahmad, Roslinazairimah Zakaria, Siti Zanariah Satari, and Muhammad Az-zuhri Azman. "Spatial dependence of extreme rainfall." In THE 3RD ISM INTERNATIONAL STATISTICAL CONFERENCE 2016 (ISM-III): Bringing Professionalism and Prestige in Statistics. Author(s), 2017. http://dx.doi.org/10.1063/1.4982833.

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Buliah, Nur Amirah, and Wendy Ling Shin Yie. "Modelling of extreme rainfall using copula." In PROCEEDINGS OF INTERNATIONAL CONFERENCE ON ADVANCES IN MATERIALS RESEARCH (ICAMR - 2019). AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0018617.

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Xi, Dazhi, Ning Lin, and Norberto C. Nadal-Caraballo. "A Joint-Probability Model for Tropical Cyclone Rainfall Hazard Assessment." In Geo-Extreme 2021. Reston, VA: American Society of Civil Engineers, 2021. http://dx.doi.org/10.1061/9780784483695.001.

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Patil, Ujwalkumar D., Giordan Kho, Maegan Catahay, Victoria Lopez, Shahram Khosrowpanah, and John Jenson. "Effect of Antecedent Rainfall on Slope Failures in Tropical Mountainous Environmental Setting." In Geo-Extreme 2021. Reston, VA: American Society of Civil Engineers, 2021. http://dx.doi.org/10.1061/9780784483695.002.

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BEILICCI, Erika Beata Maria, and Robert BEILICCI. "Influence of Rainfall Characteristics on Runoff in a Small Watershed." In Air and Water – Components of the Environment 2021 Conference Proceedings. Casa Cărţii de Ştiinţă, 2021. http://dx.doi.org/10.24193/awc2021_13.

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Due to climate change, extreme rainfall is more frequent, and the phenomenon of drought and desertification in some parts of the world is accentuated. Scientists forecast that these trends to continue as the planet continue to warm. An increasingly common phenomenon is the occurrence of flash floods in areas where human intervention on natural conditions has been significant. Over this intervention is superimposed the modification of the characteristics of extreme rainfalls (duration, intensity, height), resulting a series of negative consequences on the ecosystems of the watersheds. For their protection, a more accurate forecast of the size and times of occurrence of the maximum water flows and levels in different sections are needed. This forecast must be made with appropriate methods, such as the use of advanced hydroinformatic tools. This paper analyses the influence of rainfall characteristics on runoff in a small watershed, using rainfall-runoff phenomenon modelling. The modelling is realized using advanced hydroinformatic tool MIKE11, developed by Danish Hydraulic Institute (DHI).
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Hadipour, Sahar, Shamsuddin Shahid, Sobri Bin Harun, and Xiao-Jun Wang. "Genetic Programming for Downscaling Extreme Rainfall Events." In 2013 1st International Conference on Artificial Intelligence, Modelling & Simulation (AIMS). IEEE, 2013. http://dx.doi.org/10.1109/aims.2013.61.

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Puspaningrum, Laksmita, and Ayundyah Kesumawati. "Implementation Extreme Learning Machine for Rainfall Forecasting." In Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia. EAI, 2020. http://dx.doi.org/10.4108/eai.2-8-2019.2290495.

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Adnan, Noor Izyan Mohamad, Mohd Bakri Adam, Noor Akma Ibrahim, Mohd Yusoff Ishak, and Mohammad Noor Amal Azmai. "Functional extreme rainfall data in Petaling Jaya." In THE 3RD ISM INTERNATIONAL STATISTICAL CONFERENCE 2016 (ISM-III): Bringing Professionalism and Prestige in Statistics. Author(s), 2017. http://dx.doi.org/10.1063/1.4982842.

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McAleer, Michael, and Lanfen Chu. "Statistical Modelling of Extreme Rainfall in Taiwan." In 2nd International Conference on Computer and Information Applications (ICCIA 2012). Paris, France: Atlantis Press, 2012. http://dx.doi.org/10.2991/iccia.2012.345.

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Nobahar, M., M. S. Khan, J. Ivoke, N. M. Shuman, and F. Amini. "Coupled Hydro-Mechanical Analysis of Highway Slope on Expansive Soil Subjected to Rainfall." In Geo-Extreme 2021. Reston, VA: American Society of Civil Engineers, 2021. http://dx.doi.org/10.1061/9780784483695.017.

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Reports on the topic "Rainfall extreme"

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Skahill, Brian, and Joseph Kanney. Probabilistic flood hazard assessment framework development : extreme rainfall analysis. Engineer Research and Development Center (U.S.), August 2019. http://dx.doi.org/10.21079/11681/33883.

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Melo-Velandia, Luis Fernando, Camilo Andrés Orozco-Vanegas, and Daniel Parra-Amado. Extreme weather events and high Colombian food prices: A non-stationary extreme value approach. Banco de la República, December 2021. http://dx.doi.org/10.32468/be.1189.

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Given the importance of climate change and the increase of its severity under extreme weather events, we analyze the main drivers of high food prices in Colombia between 1985 and 2020 focusing on extreme weather shocks like a strong El Ni˜no.We estimate a non-stationary extreme value model for Colombian food prices. Our findings suggest that perishable foods are more exposed to extreme weather conditions in comparison to processed foods. In fact, an extremely low precipitation level explains only high prices in perishable foods. The risk of high perishable food prices is significantly larger for low rainfall levels (dry seasons) compared to high precipitation levels (rainy seasons). This risk gradually results in higher perishable food prices. It is non linear and is also significantly larger than the risk related to changes in the US dollar-Colombian peso exchange rate and fuel prices. Those covariates also explain high prices for both perishable and processed foods. Finally, we find that the events associated with the strongest El Ni˜no in 1988 and 2016 are expected to reoccur once every 50 years.
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Weber, A. H. Tornado, Maximum Wind Gust, and Extreme Rainfall Event Recurrence Frequencies at the Savannah River Site. Office of Scientific and Technical Information (OSTI), December 1998. http://dx.doi.org/10.2172/4876.

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Knight, Lynn, and Suzy Hodgson. Irrigation Pays in Protecting Vegetable Crop Revenues in the Northeast U.S. USDA Northeast Climate Hub, September 2017. http://dx.doi.org/10.32747/2017.6956538.ch.

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Climate records show that the Northeast is experiencing more rainfall. However, much of the additional precipitation is occurring as heavy events, leaving intervening periods of hot and dry weather. With this extreme and variable wet weather taking its toll on farms, a key question is: Does crop irrigation make sense as a farm resilience strategy given_name the overall increased precipitation in the Northeast?
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McNulty, Steven, Sarah Wiener, Emrys Treasure, Jennifer Moore Myers, Hamid Farahani, Lisa Fouladbash, David Marshall, and Rachel F. Steele. Southeast Regional Climate Hub Assessment of Climate Change Vulnerability and Adaptation and Mitigation Strategies. United States. Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7279978.ch.

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Climate-related variability in rainfall, temperature, and extreme weather (e.g., drought, flood, unseasonal frost) pose significant challenges to working land (i.e., range, forest, and agricultural) managers across the southeastern United States. This document outlines the type of risks that southeastern agriculture and forestry currently face and, in some cases, options to address these risks. Finally, this document looks forward to providing direction on the priority needs of Southeast working land managers and an outline of how the USDA Southeast Climate Hub will address those needs.
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Bourne, E., Jack Milazzo, and Burton Suedel. Realizing multiple benefits in a southeast Louisana urban flood control project through application of Engineering With Nature principles. Engineer Research and Development Center (U.S.), August 2022. http://dx.doi.org/10.21079/11681/45021.

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The application of Engineering With Nature® (EWN®) principles in urban environments and watersheds within and outside the US Army Corps of Engineers (USACE) is increasing. Extreme rainfall events have triggered the need and development of more sustainable urban infrastructure in urban areas such as New Orleans, Louisiana. This technical note documents a USACE–New Orleans District (MVN) project that successfully applied EWN principles in an urban landscape to reduce flood risk while providing other environmental, social, economic, and engineering benefits to both the community and the environment.
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Pradeep Kumar, Kaavya. Reporting in a Warming World: A Media Review. Indian Institute for Human Settlements, 2021. http://dx.doi.org/10.24943/rwwmr08.2021.

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The media plays a critical role in terms of shaping public perceptions, but they have a task on their hands in terms of effectively communicating a subject as vast and complex as climate change. India is among the countries most affected and yet reporting on the subject has been episodic, with peaks around the time of climate summits and in the immediate aftermath of disasters such as cyclones, heatwaves and extreme rainfall events. Through a media review, undertaken as part of the Earth Journalism Network Asia-Pacific Media Grant, we sought to understand patterns of representation in news coverage about urban drought and extreme weather events – predicted to occur more frequently and intensely in a warming world. This report details the methodology we followed, our findings and analyses them in the context of other work done as part of the evolving field of climate change communication.
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Ayala-García, Jhorland, and Sandy Dall’Erba. The impact of preemptive investment on natural disasters. Banco de la República, September 2021. http://dx.doi.org/10.32468/dtseru.301.

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Extreme rainfall events are expected to become more frequent and more intense in the future. Because their mitigation is a challenge and their cost to human life is large, this paper studies the impact of preemptive investment against natural disasters on the future occurrence of landslides and the losses associated with it. Based on a panel of 746 Colombian municipalities with medium and high risk of landslides and an instrumental variable approach, we find that preemptive public investment can reduce the number of landslides, the number of people who die, are injured, or disappear after a landslide, as well as the number of people affected. However, we do not find any effect on the number of houses destroyed. The results reveal that local governments focus their preventive measures on saving the lives and the physical integrity of their citizens, but they pay less attention to the direct market losses of natural disasters. These results are relevant in the presence of imperfect private insurance markets and increased informal settlements.
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Sims, Kate. Education, Girls’ Education and Climate Change. Institute of Development Studies, March 2021. http://dx.doi.org/10.19088/k4d.2021.044.

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This Emerging Issue Report (EIR) explores research and evidence on the relationship between education, girls’ education and climate change. There is scientific consensus that climate change is real, manifested through increasing temperatures, changing rainfall patterns and increasing frequency and severity of extreme weather events, including drought, flooding and cyclones. Climate change, environmental degradation and climate vulnerability are closely linked. Climate change exacerbates environmental and land degradation, especially in areas with drylands and permafrost, river deltas and low-lying coastal areas. There is high confidence that people living in areas affected by environmental degradation are experiencing an increase in the negative effects of climate change. Gender, alongside other drivers of vulnerability and exclusion, is a key determinant of an individual’s vulnerability to the effects of climate change and environmental degradation and influences how climate change is experienced. It is estimated that at least 200 million adolescent girls living in the poorest communities face a heightened risk from the effects of climate change. Evidence and commentary on the role of education, and girls’ education, to address climate change through adaptation, resilience and mitigation is limited, albeit growing. This EIR identifies and summarises the evidence and key commentary around the following themes: links between education, particularly girls’ education, and climate change; how climate and environment matter for achieving gender equality; and why securing girls’ education is an important strategy in addressing climate change. The EIR draws on academic research and literature from low- and middle-income countries (LMICs), as well as policy frameworks and grey literature, media articles and blogs from the climate, education and gender fields.
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Wagner, Anna, Christopher Hiemstra, Glen Liston, Katrina Bennett, Dan Cooley, and Arthur Gelvin. Changes in climate and its effect on timing of snowmelt and intensity-duration-frequency curves. Engineer Research and Development Center (U.S.), August 2021. http://dx.doi.org/10.21079/11681/41402.

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Snow is a critical water resource for much of the U.S. and failure to account for changes in climate could deleteriously impact military assets. In this study, we produced historical and future snow trends through modeling at three military sites (in Washington, Colorado, and North Dakota) and the Western U.S. For selected rivers, we performed seasonal trend analysis of discharge extremes. We calculated flood frequency curves and estimated the probability of occurrence of future annual maximum daily rainfall depths. Additionally, we generated intensity-duration-frequency curves (IDF) to find rainfall intensities at several return levels. Generally, our results showed a decreasing trend in historical and future snow duration, rain-on-snow events, and snowmelt runoff. This decreasing trend in snowpack could reduce water resources. A statistically significant increase in maximum streamflow for most rivers at the Washington and North Dakota sites occurred for several months of the year. In Colorado, only a few months indicated such an increase. Future IDF curves for Colorado and North Dakota indicated a slight increase in rainfall intensity whereas the Washington site had about a twofold increase. This increase in rainfall intensity could result in major flood events, demonstrating the importance of accounting for climate changes in infrastructure planning.
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