[1] 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). ISSN 0022-1694. https://doi.org/10.1016/j.jhydrol.2024.131809.

[2] 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.

[3] 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.

[4] 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.

[5] 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.

[6] Bhowmik, R. D., & Gupta, C., (2023). Application of a bivariate bias-correction approach to yield long-term attributes of Indian precipitation and temperature. Accepted in Frontiers in Climate.

[7] 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://ascelibrary.org/doi/full/10.1061/JHYEFF.HEENG-5768

[8] 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.

[9] 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.

[10] Bhowmik, R. D., & Sankarasubramanian, A. (2020). A Performance-based Multimodel Combination Approach to Reduce Uncertainty in Seasonal Temperature Change Projections. In production. International Journal of Climatology. https://doi.org/10.1002/joc.6870.

[11] 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.

[12] 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.

[13] 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.

[14] 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. Journal of Hydrology, 570, 304-314.

[15] 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.

[16] 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.

[17] 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.

[18] 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.