Frequency analysis, infilling and trends for extreme precipitation for Jamaica (1895–2100)

Burgess, Christopher P.; Taylor, Michael A.; Stephenson, Tannecia S.; Mandal, Arpita

doi:10.1016/j.ejrh.2014.10.004

Cited by 17 publications

(17 citation statements)

References 33 publications

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“…This may be capturing the impact of floods which are a relatively frequent occurrence in Jamaica; see Burgess et al . (). Note also that not including the full set of time‐varying controls does not change our estimates on the hurricane indices noticeably, as shown in the last column of Table C1.…”

Section: Econometric Estimation and Resultsmentioning

confidence: 97%

The Impact of Tropical Storms on Households: Evidence from Panel Data on Consumption

2019

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This paper investigates the impact of tropical storms on Jamaican household consumption. We build a panel data set that follows individual households over time thus enabling us to take account of time invariant household and location unobservables that could be correlated with mean tropical storm exposure. Our results show that while the average damaging hurricane reduces per capita consumption by approximately 1.1%, more destructive events can cause losses multiple times this amount. There are, however, heterogeneous impacts across households, where only those that live in buildings with less wind resistant walls are affected. Additionally, we find that households are able to partially buffer the negative impact on consumption through remittances and savings, as well as by shifting funds away from non-regular expenditures. Again, households differ in the nature of this buffering according to the wind resistance of their buildings.

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Section: Econometric Estimation and Resultsmentioning

confidence: 97%

The Impact of Tropical Storms on Households: Evidence from Panel Data on Consumption

2019

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“…Water resource has become a prime concern for any development activities and planning including effective water resources management [1][2][3][4]. In recent years, the frequent occurrence of extreme climatic events such as flooding and drought became a global concern [5].…”

Section: Introductionmentioning

confidence: 99%

Innovative Trend Analysis of Annual and Seasonal Rainfall Variability in Amhara Regional State, Ethiopia

et al. 2018

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This study investigated the annual and seasonal rainfall variability at five selected stations of Amhara Regional State, by using the innovative trend analysis method (ITAM), Mann-Kendall (MK) and Sen’s slope estimator test. The result showed that the trend of annual rainfall was increasing in Gondar (Z = 1.69), Motta (Z = 0.93), and Bahir Dar (Z = 0.07) stations. However, the trends in Dangla (Z = −0.37) and Adet (Z = −0.32) stations showed a decreasing trend. As far as monthly and seasonal variability of rainfall are concerned, all the stations exhibited sensitivity of change. The trend of rainfall in May, June, July, August, and September was increasing. However, the trend on the rest of other months showed a decreasing trend. The increase in rainfall during Kiremt season, along with the decrease in number of rainy days, leads to an increase of extreme rainfall events over the region during 1980–2016. The consistency in rainfall trends over the study region confirms the robustness of the change in trends. Innovative trend analysis method is very crucial method for detecting the trends in rainfall time series data due to its potential to present the results in graphical format as well. The findings of this paper could help researchers to understand the annual and seasonal variability of rainfall over the study region and become a foundation for further studies.

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“…The derived rainfall values of shorter durations serve as representative values of the various durations from the statistical population of the annual daily extreme values for the gauge station [26]. The IMD method was applied by [27,28] to develop IDF models for Cities in Iraq while [29] applied a modified version of the empirical formula for frequency analysis, infilling and trends for extreme precipitation for Jamaica (1895-2100).…”

Section: Indian Meteorological Department (Imd) Methodsmentioning

confidence: 99%

A Review Study on Stationary and Non-Stationary IDF Models Used in Rainfall Data Analysis around the World from 1951-2020

Nwaogazie

Sam

2020

IJECC

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This article focuses on an overview of the processes of generating rainfall intensity-duration-frequency (IDF) models, the different types and applications. IDF model is an important tool applied in the design of either hydrologic or hydraulic design such as prediction of rainfall intensities to estimate peak runoff volumes for mitigation of flooding. IDF models evolved from stationary – parametric (empirical) and non-parametric (stochastic) models, to non-stationary models in which variables vary with time. Each category controls the ways models predict rainfall intensities, and reveals their strength and weaknesses. IDF models must therefore, be chosen in terms of the project objective, data availability, size of the study, location, output needed, and the desired simplicity. For instance, while the parametric model predicts better for shorter durations and return periods only, the non-parametric models predict better for both shorter and longer durations and return periods. For projects requiring change of input data over time and evaluation of uncertainty bounds, risk assessment, including incorporation of changes in extreme precipitation, the non-stationary model approach must be selected. Also, of importance for catchments without rainfall amount and corresponding duration records but has daily (24-hourly) record of rainfall depth, the Indian Meteorological Department (IMD) method of shorter duration disaggregation can be adopted to generate in-put data for the development of IDF curves for such a location. Therefore, each model type has limitations that may make it unsuitable for some projects. Reviewing input data and output requirements, and simplicity are all necessary to decide on which model type should be selected.

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Frequency analysis, infilling and trends for extreme precipitation for Jamaica (1895–2100)

Cited by 17 publications

References 33 publications

The Impact of Tropical Storms on Households: Evidence from Panel Data on Consumption

The Impact of Tropical Storms on Households: Evidence from Panel Data on Consumption

Innovative Trend Analysis of Annual and Seasonal Rainfall Variability in Amhara Regional State, Ethiopia

A Review Study on Stationary and Non-Stationary IDF Models Used in Rainfall Data Analysis around the World from 1951-2020

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