Could climate change exacerbate droughts in Bangladesh in the future? | |
Rahman, Mahfuzur11,12,13; Tumon, Md Sakib Hasan11,13; Islam, Md Monirul11,13; Chen, Ningsheng9,10,14; Pham, Quoc Bao8; Ullah, Kashif7; Ahammed, Sumaiya Jarin11,13; Liza, Sharmina Naznin6; Aziz, Md Abdul5; Chakma, Salit4 | |
刊名 | JOURNAL OF HYDROLOGY |
2023-10-01 | |
卷号 | 625页码:18 |
关键词 | Coupled model intercomparison project 6 Drought Genetic algorithm Multilayer perceptron Artificial neural network Bangladesh |
ISSN号 | 0022-1694 |
DOI | 10.1016/j.jhydrol.2023.130096 |
英文摘要 | Droughts are one of the most complex, common, and catastrophic natural disasters, causing severe damage to agriculture and the economy. However, drought susceptibility must be measured and predicted in a systematic way, especially in light of potential climate change scenarios. This study aimed to predict current and future drought susceptibility in Bangladesh using historical climate data (1991-2020) and coupled model intercomparison project 6 data for three seasons: pre-monsoon, monsoon, and post-monsoon. We applied an advanced machine-learning algorithm of artificial neural network (ANN) with a genetic algorithm (GA) optimizer to predict drought-prone areas. Nine hydrological parameters-rainfall, temperature, humidity, cloud coverage, wind speed, sunshine, potential evapotranspiration, and solar radiation-were used to develop drought susceptibility maps. Receiver operating characteristic curves and statistical metrics were used to validate the models. The results of a multilayer perceptron ANN coupled with a GA-based optimizer showed that the relevant statistical measures for training and testing datasets were the root mean square error (RMSE = 0.127 and 0.160) and coefficient of determination (R2 = 0.967 and 0.949) for the pre-monsoon season, monsoon season (RMSE = 0.023 and 0.035; R2 = 0.998 and 0.997), and post-monsoon season (RMSE = 0.083 and 0.142; R2 = 0.986 and 0.959), respectively. Further, drought-prone areas in the baseline drought period of 2020 for pre-monsoon season represented 23.86%, 14.24%, 12.85%, 29.92%, and 19.13% of the total area, respectively; similarly, for monsoon corresponding values were 1.83%, 44.18%, 4.99%, 8.76%, and 40.24%; and for post-monsoon drought they were 24.43%, 20.94%, 16.04%, 37.79%, and 0.80% of the total landmass of Bangladesh. These results can help reduce future drought impacts and be of value in assisting policy responses in the country. |
资助项目 | National Natural Science Foundation of China[U20A20110] ; Second Tibetan Plateau Scientific Expedition and Research Program[2019QZKK0902] ; Transboundary land and water resource management and water disaster prevention in Koshi River[131C11KYSB20200033] ; National Research Foundation of Korea[NRF-2021R1A6A1A03045185] |
WOS关键词 | VULNERABILITY ASSESSMENT ; NAMAKKAL DISTRICT ; NEURAL-NETWORKS ; INTEGRATION ; INDEX ; PRECIPITATION ; TEMPERATURE ; PREDICTION ; VEGETATION ; EVENTS |
WOS研究方向 | Engineering ; Geology ; Water Resources |
语种 | 英语 |
出版者 | ELSEVIER |
WOS记录号 | WOS:001106735100001 |
资助机构 | National Natural Science Foundation of China ; Second Tibetan Plateau Scientific Expedition and Research Program ; Transboundary land and water resource management and water disaster prevention in Koshi River ; National Research Foundation of Korea |
内容类型 | 期刊论文 |
源URL | [http://ir.imde.ac.cn/handle/131551/57773] |
专题 | 中国科学院水利部成都山地灾害与环境研究所 |
通讯作者 | Rahman, Mahfuzur; Chen, Ningsheng |
作者单位 | 1.Curtin Univ, Sch Earth & Planetary Sci, Bentley, WA 6102, Australia 2.Int Univ Business Agr & Technol IUBAT, Dept Comp Sci & Engn, Dhaka 1230, Bangladesh 3.Training & Technol Transfer, Sr Program Officer, Dhaka 1215, Bangladesh 4.Bangladesh Univ Profess, Dept Disaster Management & Resilience, Mirpur Cantonment, Dhaka 1216, Bangladesh 5.Govt Peoples Republ Bangladesh, Minist Planning, Dhaka 1207, Bangladesh 6.Dhaka Univ Engn & Technol DUET, Dept Civil Engn, Gazipur 1707, Bangladesh 7.China Univ Geosci, Inst Geophys & Geomatics, Wuhan 430074, Peoples R China 8.Univ Siles Katowice, Inst Earth Sci, Fac Nat Sci, Bedzinska St 60, PL-41200 Sosnowiec, Poland 9.Acad Plateau Sci & Sustainabil, Xining 810016, Peoples R China 10.Tribhuvan Univ, Chinese Acad Sci, Kathmandu Ctr Res & Educ, Beijing 100101, Peoples R China |
推荐引用方式 GB/T 7714 | Rahman, Mahfuzur,Tumon, Md Sakib Hasan,Islam, Md Monirul,et al. Could climate change exacerbate droughts in Bangladesh in the future?[J]. JOURNAL OF HYDROLOGY,2023,625:18. |
APA | Rahman, Mahfuzur.,Tumon, Md Sakib Hasan.,Islam, Md Monirul.,Chen, Ningsheng.,Pham, Quoc Bao.,...&Dewan, Ashraf.(2023).Could climate change exacerbate droughts in Bangladesh in the future?.JOURNAL OF HYDROLOGY,625,18. |
MLA | Rahman, Mahfuzur,et al."Could climate change exacerbate droughts in Bangladesh in the future?".JOURNAL OF HYDROLOGY 625(2023):18. |
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