Reepal Shah

1.0k total citations
17 papers, 770 citations indexed

About

Reepal Shah is a scholar working on Global and Planetary Change, Water Science and Technology and Environmental Engineering. According to data from OpenAlex, Reepal Shah has authored 17 papers receiving a total of 770 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Global and Planetary Change, 10 papers in Water Science and Technology and 5 papers in Environmental Engineering. Recurrent topics in Reepal Shah's work include Hydrology and Watershed Management Studies (10 papers), Hydrology and Drought Analysis (9 papers) and Climate variability and models (8 papers). Reepal Shah is often cited by papers focused on Hydrology and Watershed Management Studies (10 papers), Hydrology and Drought Analysis (9 papers) and Climate variability and models (8 papers). Reepal Shah collaborates with scholars based in India, United States and Russia. Reepal Shah's co-authors include Vimal Mishra, Bridget Thrasher, Milind Mujumdar, R. Krishnan, Auroop R. Ganguly, J. Sanjay, Devashish Kumar, Dennis P. Lettenmaier, Amar Deep Tiwari and Saran Aadhar and has published in prestigious journals such as Geophysical Research Letters, Environmental Research Letters and Hydrology and earth system sciences.

In The Last Decade

Reepal Shah

16 papers receiving 761 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Reepal Shah India	9	637	268	236	122	103	17	770
Si Hong China	13	450 0.7×	261 1.0×	169 0.7×	62 0.5×	129 1.3×	20	620
K. Koteswara Rao India	15	538 0.8×	108 0.4×	330 1.4×	115 0.9×	84 0.8×	39	691
Sonja Folwell United Kingdom	11	672 1.1×	343 1.3×	382 1.6×	79 0.6×	105 1.0×	23	861
Joel Main United States	4	543 0.9×	175 0.7×	389 1.6×	67 0.5×	75 0.7×	9	671
J. Liebert Germany	3	637 1.0×	315 1.2×	354 1.5×	107 0.9×	44 0.4×	7	735
Mohammad Amin Asadi Zarch Iran	10	833 1.3×	264 1.0×	164 0.7×	208 1.7×	87 0.8×	12	973
Ali Ümran Kömüşçü Türkiye	11	597 0.9×	147 0.5×	142 0.6×	180 1.5×	80 0.8×	26	688
A. Mirin United States	8	660 1.0×	375 1.4×	411 1.7×	55 0.5×	87 0.8×	17	878
Binhui Liu China	9	875 1.4×	201 0.8×	532 2.3×	115 0.9×	100 1.0×	10	1.0k
Andreas Hänsler Germany	7	732 1.1×	121 0.5×	510 2.2×	167 1.4×	46 0.4×	10	855

Countries citing papers authored by Reepal Shah

Since Specialization

Citations

This map shows the geographic impact of Reepal Shah's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Reepal Shah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reepal Shah more than expected).

Fields of papers citing papers by Reepal Shah

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Reepal Shah. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Reepal Shah. The network helps show where Reepal Shah may publish in the future.

Co-authorship network of co-authors of Reepal Shah

This figure shows the co-authorship network connecting the top 25 collaborators of Reepal Shah. A scholar is included among the top collaborators of Reepal Shah based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Reepal Shah. Reepal Shah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Shah, Reepal, et al.. (2024). Spatio-temporal Causal Learning for Streamflow Forecasting. 6161–6170.

Ding, Kaize, et al.. (2023). STREAMS: Towards Spatio-Temporal Causal Discovery with Reinforcement Learning for Streamflow Rate Prediction. 4815–4821. 4 indexed citations

Shah, Reepal, et al.. (2023). Design principles for engineering wetlands to improve resilience of coupled built and natural water infrastructure. Environmental Research Letters. 18(11). 114045–114045. 2 indexed citations

Shah, Reepal, et al.. (2022). STCD: A Spatio-Temporal Causal Discovery Framework for Hydrological Systems. 2022 IEEE International Conference on Big Data (Big Data). 5578–5583. 5 indexed citations

Stampoulis, Dimitrios, John L. Sabo, Reepal Shah, et al.. (2020). A Bayesian Neural Network for an Accurate Representation and Transformation of Runoff Dynamics: A Case Study of the Brazos River Basin in Texas. 8. 41–51. 1 indexed citations

Shah, Reepal, et al.. (2019). Accurate Prediction of Streamflow Using Long Short-Term Memory Network: A Case Study in the Brazos River Basin in Texas. International Journal of Environmental Science and Development. 10(10). 294–300. 37 indexed citations

Stampoulis, Dimitrios, et al.. (2019). Machine Learning: An Efficient Alternative to the Variable Infiltration Capacity Model for an Accurate Simulation of Runoff Rates. International Journal of Environmental Science and Development. 10(9). 288–293. 2 indexed citations

Mishra, Vimal, Amar Deep Tiwari, Saran Aadhar, et al.. (2019). Drought and Famine in India, 1870–2016. Geophysical Research Letters. 46(4). 2075–2083. 148 indexed citations

Mishra, Vimal, Reepal Shah, Syed Azhar Syed Sulaiman, et al.. (2018). Reconstruction of droughts in India using multiple land-surface models (1951–2015). Hydrology and earth system sciences. 22(4). 2269–2284. 85 indexed citations

10.

Shah, Reepal, A. K. Sahai, & Vimal Mishra. (2017). Short to sub-seasonal hydrologic forecast to manage water and agricultural resources in India. Hydrology and earth system sciences. 21(2). 707–720. 36 indexed citations

11.

Shah, Reepal, A. K. Sahai, & Vimal Mishra. (2016). Short-to-medium range hydrologic forecast to manage water and agricultural resources in India. 1 indexed citations

12.

Shah, Reepal & Vimal Mishra. (2016). Utility of Global Ensemble Forecast System (GEFS) Reforecast for Medium-Range Drought Prediction in India. Journal of Hydrometeorology. 17(6). 1781–1800. 21 indexed citations

13.

Shah, Reepal & Vimal Mishra. (2014). Development of an Experimental Near-Real-Time Drought Monitor for India*. Journal of Hydrometeorology. 16(1). 327–345. 85 indexed citations

14.

Shah, Reepal & Vimal Mishra. (2014). Short-term Drought Prediction in India. AGU Fall Meeting Abstracts. 2014. 1 indexed citations

15.

Mishra, Vimal, Devashish Kumar, Auroop R. Ganguly, et al.. (2014). Reliability of regional and global climate models to simulate precipitation extremes over India. Journal of Geophysical Research Atmospheres. 119(15). 9301–9323. 152 indexed citations

16.

Shah, Reepal & Vimal Mishra. (2014). Evaluation of the Reanalysis Products for the Monsoon Season Droughts in India. Journal of Hydrometeorology. 15(4). 1575–1591. 84 indexed citations

17.

Mishra, Vimal, Reepal Shah, & Bridget Thrasher. (2014). Soil Moisture Droughts under the Retrospective and Projected Climate in India*. Journal of Hydrometeorology. 15(6). 2267–2292. 106 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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