Authors : Md. Abu Bakar Siddik Farhan; Tanvir Alam; Zannatul Mawa; Tariqul Islam

Volume/Issue : Volume 11 - 2026, Issue 9 - September

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Google Scholar : https://tinyurl.com/mvwyhjfa

DOI : https://doi.org/10.38124/ijisrt/26sep1440

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : River water levels in northwest Bangladesh have fallen over recent decades, and standardised water level indices are often used to describe hydrological drought where discharge records are scarce. Whether these declines reflect a rainfall deficit, a loss of river flow or a change in the channel itself has not been tested. We combined monthly rainfall from 44 Bangladesh Water Development Board (BWDB) gauges (35 retained after relative homogeneity testing), monthly water levels at 22 river gauges and 15, discharge gaugings for 1980-2022.

Keywords : Drought Propagation; SHAP; Specific Stage; Channel Change; Barind Tract; Bangladesh.

References :

1. Alexandersson, H. (1986). A homogeneity test applied to precipitation data. Journal of Climatology, 6(6), 661-675. https://doi.org/10.1002/joc.3370060607
2. Apurv, T., & Cai, X. (2020). Drought propagation in contiguous U.S. watersheds: A process-based understanding of the role of climate and watershed properties. Water Resources Research, 56, e2020WR027755. https://doi.org/10.1029/2020WR027755
3. Barker, L. J., Hannaford, J., Chiverton, A., & Svensson, C. (2016). From meteorological to hydrological drought using standardised indicators. Hydrology and Earth System Sciences, 20(6), 2483-2505. https://doi.org/10.5194/hess-20-2483-2016
4. Binh, D. V., Kantoush, S. A., Sumi, T., Mai, N. P., Ngoc, T. A., Trung, L. V., & An, T. D. (2021). Effects of riverbed incision on the hydrology of the Vietnamese Mekong Delta. Hydrological Processes, 35, e14030. https://doi.org/10.1002/hyp.14030
5. Breiman, L. (2001). Random forests. Machine Learning, 45(1), 5-32. https://doi.org/10.1023/A:1010933404324
6. Chen, T., & Guestrin, C. (2016). XGBoost: A scalable tree boosting system. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 785-794). https://doi.org/10.1145/2939672.2939785
7. Darienzo, M., Le Coz, J., Renard, B., & Lang, M. (2021). Detection of stage-discharge rating shifts using gaugings: A recursive segmentation procedure accounting for observational and model uncertainties. Water Resources Research, 57(4), e2020WR028607. https://doi.org/10.1029/2020WR028607
8. Dikshit, A., & Pradhan, B. (2021). Explainable AI in drought forecasting. Machine Learning with Applications, 6, 100192. https://doi.org/10.1016/j.mlwa.2021.100192
9. Farahmand, A., & AghaKouchak, A. (2015). A generalized framework for deriving nonparametric standardized drought indicators. Advances in Water Resources, 76, 140-145. https://doi.org/10.1016/j.advwatres.2014.11.012
10. Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of Hydrology, 204(1-4), 182-196. https://doi.org/10.1016/S0022-1694(97)00125-X
11. Huang, S., Li, P., Huang, Q., Leng, G., Hou, B., & Ma, L. (2017). The propagation from meteorological to hydrological drought and its potential influence factors. Journal of Hydrology, 547, 184-195. https://doi.org/10.1016/j.jhydrol.2017.01.041
12. Janardhanan, S., Islam, M. M., Islam, M. T., Peña-Arancibia, J., Hodgson, G., Karim, F., Mainuddin, M., Islam, M. T., Rahman, M. A., & Kirby, J. M. (2023). Groundwater balance and long-term storage trends in the regional Indo-Gangetic aquifer in northwest Bangladesh. Journal of Hydrology: Regional Studies, 49, 101500. https://doi.org/10.1016/j.ejrh.2023.101500
13. Kamruzzaman, M., Almazroui, M., Salam, M. A., Mondol, M. A. H., Rahman, M. M., Deb, L., Kundu, P. K., Zaman, M. A. U., & Islam, A. R. M. T. (2022). Spatiotemporal drought analysis in Bangladesh using the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI). Scientific Reports, 12, 20694. https://doi.org/10.1038/s41598-022-24146-0
14. Kapoor, S., & Narayanan, A. (2023). Leakage and the reproducibility crisis in machine-learning-based science. Patterns, 4(9), 100804. https://doi.org/10.1016/j.patter.2023.100804
15. Kendall, M. G. (1975). Rank correlation methods (4th ed.). Charles Griffin.
16. Lundberg, S. M., Erion, G., Chen, H., DeGrave, A., Prutkin, J. M., Nair, B., Katz, R., Himmelfarb, J., Bansal, N., & Lee, S.-I. (2020). From local explanations to global understanding with explainable AI for trees. Nature Machine Intelligence, 2(1), 56-67. https://doi.org/10.1038/s42256-019-0138-9
17. Mann, H. B. (1945). Nonparametric tests against trend. Econometrica, 13(3), 245-259.
18. Mansanarez, V., Renard, B., Le Coz, J., Lang, M., & Darienzo, M. (2019). Shift happens! Adjusting stage-discharge rating curves to morphological changes at known times. Water Resources Research, 55, 2876-2899. https://doi.org/10.1029/2018WR023389
19. McKee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (pp. 179-184). American Meteorological Society.
20. Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I: A discussion of principles. Journal of Hydrology, 10(3), 282-290. https://doi.org/10.1016/0022-1694(70)90255-6
21. Nearing, G. S., Kratzert, F., Sampson, A. K., Pelissier, C. S., Klotz, D., Frame, J. M., Prieto, C., & Gupta, H. V. (2021). What role does hydrological science play in the age of machine learning? Water Resources Research, 57(3), e2020WR028091. https://doi.org/10.1029/2020WR028091
22. Pettitt, A. N. (1979). A non-parametric approach to the change-point problem. Journal of the Royal Statistical Society: Series C (Applied Statistics), 28(2), 126-135.
23. Rasel, H. M., Al Mamun, M. A., Hasnat, A., Alam, S., Hossain, I., Mondal, R. K., Good, R. Z., Alsukaibi, A. K. D., & Awual, M. R. (2023). Sustainable futures in agricultural heritage: Geospatial exploration and predicting groundwater-level variations in Barind tract of Bangladesh. Science of the Total Environment, 865, 161297. https://doi.org/10.1016/j.scitotenv.2022.161297
24. Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall’s tau. Journal of the American Statistical Association, 63(324), 1379-1389.
25. Shahid, S., & Behrawan, H. (2008). Drought risk assessment in the western part of Bangladesh. Natural Hazards, 46(3), 391-413. https://doi.org/10.1007/s11069-007-9191-5
26. Shamsudduha, M., Taylor, R. G., Haq, M. I., Nowreen, S., Zahid, A., & Ahmed, K. M. U. (2022). The Bengal Water Machine: Quantified freshwater capture in Bangladesh. Science, 377(6612), 1315-1319. https://doi.org/10.1126/science.abm4730
27. Stagge, J. H., Tallaksen, L. M., Gudmundsson, L., Van Loon, A. F., & Stahl, K. (2015). Candidate distributions for climatological drought indices (SPI and SPEI). International Journal of Climatology, 35(13), 4027-4040. https://doi.org/10.1002/joc.4267
28. Sutanto, S. J., Syaehuddin, W. A., & de Graaf, I. (2024). Hydrological drought forecasts using precipitation data depend on catchment properties and human activities. Communications Earth & Environment, 5, 118. https://doi.org/10.1038/s43247-024-01295-w
29. Tijdeman, E., Hannaford, J., & Stahl, K. (2018). Human influences on streamflow drought characteristics in England and Wales. Hydrology and Earth System Sciences, 22(2), 1051-1064. https://doi.org/10.5194/hess-22-1051-2018
30. Van Loon, A. F. (2015). Hydrological drought explained. WIREs Water, 2(4), 359-392. https://doi.org/10.1002/wat2.1085
31. Van Loon, A. F., & Van Lanen, H. A. J. (2013). Making the distinction between water scarcity and drought using an observation-modeling framework. Water Resources Research, 49(3), 1483-1502. https://doi.org/10.1002/wrcr.20147
32. Van Loon, A. F., Rangecroft, S., Coxon, G., Werner, M., Wanders, N., Di Baldassarre, G., Tijdeman, E., Bosman, M., et al. (2022). Streamflow droughts aggravated by human activities despite management. Environmental Research Letters, 17(4), 044059. https://doi.org/10.1088/1748-9326/ac5def
33. Wang, J., Wang, W., Cheng, H., Wang, H., & Zhu, Y. (2021). Propagation from meteorological to hydrological drought and its influencing factors in the Huaihe River Basin. Water, 13(14), 1985. https://doi.org/10.3390/w13141985
34. Wilcoxon, F. (1945). Individual comparisons by ranking methods. Biometrics Bulletin, 1(6), 80-83.
35. Zhang, Q., Miao, C., Guo, X., Gou, J., & Su, T. (2023). Human activities impact the propagation from meteorological to hydrological drought in the Yellow River Basin, China. Journal of Hydrology, 623, 129752. https://doi.org/10.1016/j.jhydrol.2023.129752