Could climate change exacerbate droughts in Bangladesh in the future?
Authors:Rahman, Mahfuzur Tumon, Md Sakib Hasan Islam, Md Monirul Chen, Ningsheng Pham, Quoc Bao Ullah, Kashif Ahammed, Sumaiya Jarin Liza, Sharmina Naznin Aziz, Md Abdul Chakma, Salit Enan, Muhammad Esmat Hossain, Md. Alomgir Shufeng, Tian Dewan, Ashraf
Volume:625
DOI:10.1016/j.jhydrol.2023.130096
Published:2023
Document Type:Article
Abstract: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.
Author Information
Corresponding Author:Chen, NS (corresponding author), Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Surface Proc, Chengdu 610041, Peoples R China.;Rahman, M (corresponding author), Int Univ Business Agr & Technol IUBAT, Dept Civil Engn, Dhaka 1230, Bangladesh.
Reprint Address:Chen, NS (corresponding author), Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Surface Proc, Chengdu 610041, Peoples R China.;Rahman, M (corresponding author), Int Univ Business Agr & Technol IUBAT, Dept Civil Engn, Dhaka 1230, Bangladesh.
Addresses:[Chen, Ningsheng; Shufeng, Tian] Chinese Acad Sci, Inst Mt Hazards & Environm, Key Lab Mt Hazards & Surface Proc, Chengdu 610041, Peoples R China; [Rahman, Mahfuzur; Tumon, Md Sakib Hasan; Islam, Md Monirul; Ahammed, Sumaiya Jarin] Int Univ Business Agr & Technol IUBAT, Dept Civil Engn, Dhaka 1230, Bangladesh; [Rahman, Mahfuzur] Kunsan Natl Univ, Dept Civil Engn, Gunsan 54150, South Korea; [Rahman, Mahfuzur; Tumon, Md Sakib Hasan; Islam, Md Monirul; Ahammed, Sumaiya Jarin] Int Univ Business Agr & Technol IUBAT, Geomatics & Spatial Analyt Res Lab GSAR, Dhaka 1230, Bangladesh; [Chen, Ningsheng] Tribhuvan Univ, Chinese Acad Sci, Kathmandu Ctr Res & Educ, Beijing 100101, Peoples R China; [Chen, Ningsheng] Acad Plateau Sci & Sustainabil, Xining 810016, Peoples R China; [Pham, Quoc Bao] Univ Silesia Katowice, Inst Earth Sci, Fac Nat Sci, Bedzinska St 60, PL-41200 Sosnowiec, Poland; [Ullah, Kashif] China Univ Geosci, Inst Geophys & Geomatics, Wuhan 430074, Peoples R China; [Liza, Sharmina Naznin] Dhaka Univ Engn & Technol DUET, Dept Civil Engn, Gazipur 1707, Bangladesh; [Aziz, Md Abdul] Govt Peoples Republ Bangladesh, Minist Planning, Dhaka 1207, Bangladesh; [Chakma, Salit] Bangladesh Univ Profess, Dept Disaster Management & Resilience, Mirpur Cantonment, Dhaka 1216, Bangladesh; [Enan, Muhammad Esmat] Training & Technol Transfer, Sr Program Officer, Dhaka 1215, Bangladesh; [Hossain, Md. Alomgir] Int Univ Business Agr & Technol IUBAT, Dept Comp Sci & Engn, Dhaka 1230, Bangladesh; [Dewan, Ashraf] Curtin Univ, Sch Earth & Planetary Sci, Bentley, WA 6102, Australia
E-mail Addresses:mfz.rahman@iubat.edu; mmislam@iubat.edu; chennsh@imde.ac.cn; A.Dewan@curtin.edu.au