[24] Kona, K.S. & Bhowmik, R. D. (2025). Understanding the interannual variation in river stage-discharge relationship and its impact on flood discharge estimation. Accepted in ASCE Journal of Hydrologic Engineering.
[23] Alexander, A. A., Rasool, T., Kumar, C., Sahoo, S., Bhowmik, R. D., & Nagesh Kumar, D. (2025). Unprecedented rainfall events increase the magnitude of design storms. Environmental Research Letters. DOI 10.1088/1748-9326/add175.
[22] Posa, P. C. L., & Bhowmik, R. D. (2025). Estimating the spatial and model uncertainties in yielding extreme rainfall return levels across India. Journal of Hydrology: Regional Studies, 59, 102442. https://doi.org/10.1016/j.ejrh.2025.102442.
[21] Tabbussum, R., Bhowmik, R. D., & Mujumdar, P. (2025). Association of climate variability modes with concurrent droughts and heatwaves in India. Journal of Hydrology X, 26, 100196.
[20] Kumar, K. B., Das Bhowmik, R., & Mujumdar, P. P. (2025). Revising flood return periods by accounting for the co‐occurrence between floods and their potential drivers. International Journal of Climatology, e8783.
[19] Budamala, V., Roy, T., & Bhowmik, R. D. (2025). A robust skill verification of hindcast decadal experiments on streamflow regimes using CMIP6 data. Journal of Hydrology, 650, 132525.
[18] Rasool, T., Sahoo, S., Bhowmik, R. D., & Nagesh Kumar, D. (2024). Development of a stochastic rainfall generator to yield unprecedented rainfall events. Journal of Hydrology, 131809. https://doi.org/10.1016/j.jhydrol.2024.131809
[17] Posa, P. C. L., Rasool, T., Budamala, V., & Bhowmik, R. D. (2024). Influence of global teleconnections on long-term variability in flood seasonality across peninsular India. Environmental Research Letters, 19(6), 064069.
[16] Bhowmik, R. D., Budamala, V., & Sankarasubramanian, A. (2024). Influence of long-term observed trends on the performance of seasonal hydroclimate forecasts. Advances in Water Resources, 188, 104707.
[15] Dhanurkar, T., Budamala, V., & Bhowmik, R. D. (2024). Understanding the association between global forest fire products and hydrometeorological variables. Science of The Total Environment, 945, 173911.
[14] Budamala, V., Wadhwa, A., Bhowmik, R. D., Mahindrakar, A., Yellamelli, R. S. R., & Kasiviswanathan, K. S. (2023). Multi-temporal downscaling of daily to sub-daily streamflow for flash flood watersheds at ungauged stations using a hybrid framework. Journal of Hydrology, 625, 130110.
[13] Bhowmik, R. D., & Gupta, C. (2023). Application of a bivariate bias-correction approach to yield long-term attributes of Indian precipitation and temperature. Frontiers in Climate (Accepted).
[12] Basu, B., Bhowmik, R. D., & Sankarasubramanian, A. (2022). Changing seasonality of annual maximum floods over the conterminous US: Potential drivers and regional synthesis. Journal of Hydrologic Engineering, 28(4), 04023007. https://doi.org/10.1061/JHYEFF.HEENG-5768
[11] Joseph, R., Mujumdar, P. P., & Das Bhowmik, R. (2022). Reconstruction of urban rainfall measurements to estimate the spatiotemporal variability of extreme rainfall. Water, 14(23), 3900.
[10] Bhowmik, R. D., NG, T. L., & Wang, J. P. (2020). Understanding the impact of observation data uncertainty on probabilistic streamflow forecasts using a dynamic hierarchical model. Water Resources Research, 56(4), e2019WR025463.
[9] Bhowmik, R. D., & Sankarasubramanian, A. (2020). A performance-based multimodel combination approach to reduce uncertainty in seasonal temperature change projections. International Journal of Climatology. https://doi.org/10.1002/joc.6870
[8] Bhowmik, R. D., Seo, S., Das, P., & Sankarasubramanian, A. (2020). Synthesis of irrigation water supply use in the United States: Spatiotemporal patterns. Journal of Water Resources Planning and Management, DOI:10.1061/(ASCE)WR.1943-5452.0001249
[7] Bhowmik, R. D., Suchetana, B., & Li, M. (2019). Shower effect of a rainfall onset on the heat accumulated during a preceding dry spell. Scientific Reports, 9, 7011. https://doi.org/10.1038/s41598-019-43437-7
[6] Bhowmik, R. D., & Sankarasubramanian, A. (2019). Limitations of univariate statistical downscaling to preserve cross-correlation between monthly precipitation and temperature. International Journal of Climatology, 1–18. https://doi.org/10.1002/joc.6086
[5] Seo, S., Bhowmik, R. D., Sankarasubramanian, A., Mahinthakumar, G., & Kumar, M. (2019). The role of cross-correlation between precipitation and temperature on basin-scale simulation of hydrologic variables. Journal of Hydrology, 570, 304–314.
[4] Bhowmik, R. D., Seo, S., & Sahoo, S. (2018). Streamflow simulation using Bayesian regression with multivariate linear spline to estimate future changes. Water, 10(7), 875.
[3] Bhowmik, R. D., Sharma, A., & Sankarasubramanian, A. (2017). Reducing model structural uncertainty in climate model projections—a rank-based model combination approach. Journal of Climate, 30(24), 10139–10154.
[2] Sankarasubramanian, A., Sabo, J. L., Larson, K. L., Seo, S. B., Sinha, T., Bhowmik, R. D., … & Kominoski, J. (2017). Synthesis of public water supply use in the United States: Spatio‐temporal patterns and socio‐economic controls. Earth’s Future, 5(7), 771–788.
[1] Bhowmik, R. D., Sankarasubramanian, A., Sinha, T., Patskoski, J., Mahinthakumar, G., & Kunkel, K. E. (2017). Multivariate downscaling approach preserving cross-correlations across climate variables for projecting hydrologic fluxes. Journal of Hydrometeorology, 18(8), 2187–2205.
[1] Sengupta, S., & Bhowmik, R. D. (2022). Understanding the Influence of Snow Cover in Issuing Streamflow Forecasts for High-Mountainous Basins in the Himalayan Region. Proceedings of the 39th IAHR World Congress (Granada). doi:10.3850/IAHR-39WC252171192022930.
[1] Bhowmik, R. D., & Roy, T. (2022). Challenges and Solution Pathways in Water Use Through the Lens of COVID-19. Global Pandemic and Human Security: Technology and Development Perspective, 211.
[1] Mohammad, A. H., Budamala, V., & Bhowmik, R. D. (2025). Application of machine learning-based postprocessing to improve crowd-sourced rainfall estimates. Under-review in Applied Computing and geosciences.