[1] 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.

[2] 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 Engineering28(4), 04023007.

[3] 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.

[4] 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.

[5] 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.

[6] 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).

[7] 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.

[8] 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.

[9] 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.

[10] 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.

[11] 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.

[12] 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] Bhowmik, R. D., & Sankarasubramanian, A. (2023). Understanding the influence of long-term trends in forecasting seasonal precipitation. Submitted in Water Resources Research. 2023WR035622.

[2] Rasool T, Bhowmik, R. D., D Nagesh Kumar & Sahoo. S (2023). A novel stochastic rainfall generator to account for unprecedented extreme events. Submitted in Journal of Hydrology. HYDROL51229.

[3] Mohammad, A. H., Budamala, V., & Bhowmik, R. D. (2023)Application of machine learning-based postprocessing to improve crowd-sourced rainfall estimates. Submitted in Urban Climate. UCLIM-D-23-00289.

[1] Tabbussum, R., Bhowmik, R. D., Mujumdar PP., (2023). Understanding the connection between large-scale climate drivers and the occurrence of concurrent droughts and heatwaves in India.

[2] Budamala, V., & Bhowmik, R. D., (2023). A robust skill verification on hindcast decadal experiments for streamflow regimes using CMIP6 outputs.