Trends in Precipitation Characteristics in Bangladesh from 1950 to 2008

Endo, Noritaka; Matsumoto, Jun; Hayashi, Taiichi; Terao, Toru; Murata, Fumie; Kiguchi, Masashi; Yamane, Yusuke; Alam, Md. Shah

doi:10.2151/sola.2015-027

Cited by 22 publications

(14 citation statements)

References 42 publications

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“…This perception is supported by data collected at national level on the climate in Bangladesh. Data from the Bangladesh Meteorological Department (BMD) for the periods of 1951–2011 show that for any ten-year period the temperature was higher and rainfall less predictable than in the preceding ten years [ 36 ]. Other countries such as Jamaica, Vietnam, and Nepal reported identical findings for their studies among a similar population [ 23 , 28 , 35 ].…”

Section: Discussionmentioning

confidence: 99%

Knowledge and perception about climate change and human health: findings from a baseline survey among vulnerable communities in Bangladesh

et al. 2016

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BackgroundBangladesh is one of the countries most vulnerable to climate change (CC). A basic understanding of public perception on vulnerability, attitude and the risk in relation to CC and health will provide strategic directions for government policy, adaptation strategies and development of community-based guidelines. The objective of this study was to collect community-based data on peoples’ knowledge and perception about CC and its impact on health.MethodsIn 2012, a cross-sectional survey was undertaken among 6720 households of 224 enumeration areas of rural villages geographically distributed in seven vulnerable districts of Bangladesh, with total population of 19,228,598. Thirty households were selected randomly from each enumeration area using the household listing provided by the Bangladesh Bureau of Statistics (BBS). Information was collected from all the 6720 research participants using a structured questionnaire. An observation checklist was used by the interviewers to collect household- and community-related information. In addition, we selected the head of each household as the eligible participant for an interview. Evidence of association between sociodemographic variables and knowledge of CC was explored by cross-tabulation and measured using chi-square tests. Logistic regression models were used to further explore the predictors of knowledge.ResultsThe study revealed that the residents of the rural communities selected for this study largely come from a low socioeconomic background: only 9.6 % had postsecondary education or higher, the majority worked as day labourer or farmer (60 %), and only 10 % earned a monthly income above BDT 12000 (equivalent to US $150 approx.). The majority of the participants (54.2 %) had some knowledge about CC but 45.8 % did not (p < 0.001). The majority of knowledgeable participants (n = 3645) felt excessive temperature as the change of climate (83.2 %). Among all the respondents (n = 6720), 94.5 % perceived change in climate and extreme weather events. Most of them (91.9 %) observed change in rainfall patterns in the last 10 years, and 97.8 % people think their health care expenditure increased after the extreme weather events. Age, educational qualification, monthly income, and occupation were significantly associated with the knowledge about climate change (p < 0.001). People with higher educational level or who live near a school were more knowledgeable about CC and its impact on health.ConclusionsThe knowledge level about CC in our study group was average but the perception and awareness of CC related events and its impact on health was high. The most influential factor leading to understanding of CC and its impact on health was education. School-based intervention could be explored to increase peoples’ knowledge about CC and necessary health adaptation at community level.Electronic supplementary materialThe online version of this article (doi:10.1186/s12889-016-2930-3) contains supplementary material, which is available to authorized users.

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Section: Discussionmentioning

confidence: 99%

Knowledge and perception about climate change and human health: findings from a baseline survey among vulnerable communities in Bangladesh

et al. 2016

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“…In addition, the frequency and intensity of extreme P events have shown an increasing trend in mainland China over the last few decades [35][36][37][38]. Similarly, the increasing trend of P extremes has been reported over Bangladesh in recent years [39][40][41]. In addition, Deshpande et al [42] reported a positive trend in extreme P events in India during the period of 1951-2013.…”

Section: Introductionmentioning

confidence: 95%

Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

Bhatti

Wang

Ullah

et al. 2020

Water

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Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann–Kendall, Sen’s slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 ≥1 mm), heavy precipitation days (R10 ≥ 10 mm), very heavy precipitation days (R20 ≥ 20 mm), severe precipitation (R50 ≥ 50 mm), very wet days (R95p) defining daily precipitation ≥ 95 percentile, extremely wet days (R99p) defining daily precipitation ≥ 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations’ density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann–Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.

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“…There are some regions in Bangladesh where every steps of agricultural activities from field preparation to harvesting of crops dependents on rainfall [4]. An earlier study conducted by Endo et al (2015) reported that heavy rainfall index showed no clear trend, and was dominated by inter-annual and/or decadal variations [5].…”

Section: Introductionmentioning

confidence: 99%

Rainfall Variability and Linear Trend Models on North-West Part of Bangladesh for the Last 40 Years

Rahman¹

2016

AJAM

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Rainfall has been extensively considered as one of the initial point towards the apprehension of climate change courses. Bangladesh is recently experiencing climate change impact related to hazards like cyclone, rainfall, flood, draught etc. Climate variable like rainfall is the most important parameter which is linked with agricultural aspects too for this country. Most of the rain occurred during monsoon period in Bangladesh. This study investigates temporal variability of rainfall and liner trend models on the NorthWest part of Bangladesh over the period of 1975-2014 using data from the Bangladesh Meteorological Department. We computed and analyzed the linear trend models by using least square estimation. We estimated mean with standard deviation, cross-correlation and linear trends of annual and monsoon rainfall using MS Excel and SPSS v21. The variability of rainfall between the stations was measured by correlation test. The annual and monsoon rainfall has been found in decreasing trends in recent times. In some areas in the NorthWestern part of the country, the amount of annual and monsoon mean rainfall may be decreased abruptly comparing with average normal rainfall all over the country. The linear trend analysis of rainfall reveals a bit different trend for the last four decades. The observed data and linear trend line shows the decreasing trend of annual rainfall rate is 0.102 mm per year, whereas the decreasing trend of monsoon season rainfall rate is 0.080 mm per year. The time series statistical analysis of this study also provided the information about the correlation coefficients of rainfall among the selected five stations of the SouthWest region. The result of this study would hopefully help the planners and program managers to take necessary actions and to measure disaster management, agricultural production, drought mitigation, flood control etc.

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Trends in Precipitation Characteristics in Bangladesh from 1950 to 2008

Cited by 22 publications

References 42 publications

Knowledge and perception about climate change and human health: findings from a baseline survey among vulnerable communities in Bangladesh

Knowledge and perception about climate change and human health: findings from a baseline survey among vulnerable communities in Bangladesh

Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

Rainfall Variability and Linear Trend Models on North-West Part of Bangladesh for the Last 40 Years

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