Reetik Kumar Sahu

561 total citations
16 papers, 324 citations indexed

About

Reetik Kumar Sahu is a scholar working on Water Science and Technology, Global and Planetary Change and Environmental Engineering. According to data from OpenAlex, Reetik Kumar Sahu has authored 16 papers receiving a total of 324 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Water Science and Technology, 8 papers in Global and Planetary Change and 6 papers in Environmental Engineering. Recurrent topics in Reetik Kumar Sahu's work include Hydrology and Watershed Management Studies (8 papers), Hydrological Forecasting Using AI (6 papers) and Flood Risk Assessment and Management (5 papers). Reetik Kumar Sahu is often cited by papers focused on Hydrology and Watershed Management Studies (8 papers), Hydrological Forecasting Using AI (6 papers) and Flood Risk Assessment and Management (5 papers). Reetik Kumar Sahu collaborates with scholars based in Austria, United States and United Kingdom. Reetik Kumar Sahu's co-authors include Juliane Müller, Boris Faybishenko, Charuleka Varadharajan, Bhavna Arora, Jangho Park, D. Agarwal, Jens de Bruijn, Thomas Lees, Louise Slater and Simon Dadson and has published in prestigious journals such as The Science of The Total Environment, Water Resources Research and Journal of Environmental Management.

In The Last Decade

Reetik Kumar Sahu

14 papers receiving 310 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Reetik Kumar Sahu Austria 9 196 196 127 43 28 16 324
Marvin Höge Switzerland 8 157 0.8× 180 0.9× 122 1.0× 37 0.9× 32 1.1× 16 290
Peishi Jiang United States 11 176 0.9× 172 0.9× 164 1.3× 27 0.6× 40 1.4× 30 358
Farnaz Daneshvar Vousoughi Iran 7 241 1.2× 182 0.9× 147 1.2× 24 0.6× 16 0.6× 13 348
Hung-Wei Tseng Taiwan 7 182 0.9× 107 0.5× 173 1.4× 31 0.7× 74 2.6× 12 348
Michelle Sapitang Malaysia 6 292 1.5× 139 0.7× 154 1.2× 46 1.1× 39 1.4× 8 402
Purna Chandra Nayak India 8 324 1.7× 266 1.4× 153 1.2× 43 1.0× 13 0.5× 12 425
Dillip K. Ghose India 14 353 1.8× 253 1.3× 236 1.9× 27 0.6× 52 1.9× 32 510
T. J. Smith United States 11 211 1.1× 358 1.8× 281 2.2× 60 1.4× 40 1.4× 22 467
Ioannis Trichakis Italy 10 280 1.4× 229 1.2× 107 0.8× 54 1.3× 18 0.6× 26 395
Anneli Guthke Germany 10 230 1.2× 184 0.9× 129 1.0× 108 2.5× 15 0.5× 25 449

Countries citing papers authored by Reetik Kumar Sahu

Since Specialization
Citations

This map shows the geographic impact of Reetik Kumar Sahu'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 Reetik Kumar Sahu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Reetik Kumar Sahu more than expected).

Fields of papers citing papers by Reetik Kumar Sahu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Reetik Kumar Sahu. 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 Reetik Kumar Sahu. The network helps show where Reetik Kumar Sahu may publish in the future.

Co-authorship network of co-authors of Reetik Kumar Sahu

This figure shows the co-authorship network connecting the top 25 collaborators of Reetik Kumar Sahu. A scholar is included among the top collaborators of Reetik Kumar Sahu 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 Reetik Kumar Sahu. Reetik Kumar Sahu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Chen, Zhuo, Reetik Kumar Sahu, Taher Kahil, et al.. (2025). Impacts of water conservation, wastewater treatment, and reuse on water quantity and quality stress mitigation in China. Journal of Industrial Ecology. 29(3). 777–793. 2 indexed citations
2.
Kahil, Taher, Reetik Kumar Sahu, Peter Burek, et al.. (2025). Development of the global hydro-economic model (ECHO-Global version 1.0) for assessing the performance of water management options. Geoscientific model development. 18(20). 7987–8015.
3.
Beck, Hylke E., Jens de Bruijn, Reetik Kumar Sahu, et al.. (2024). Deep dive into hydrologic simulations at global scale: harnessing the power of deep learning and physics-informed differentiable models ( δ HBV-globe1.0-hydroDL). Geoscientific model development. 17(18). 7181–7198. 21 indexed citations
4.
Virkki, Vili, et al.. (2024). Archetypal flow regime change classes and their associations with anthropogenic drivers of global streamflow alterations. Environmental Research Communications. 6(11). 111007–111007.
5.
Baggio, Jacopo A., et al.. (2024). The role of interacting social and institutional norms in stressed groundwater systems. Journal of Environmental Management. 356. 120389–120389. 7 indexed citations
6.
Guillaumot, Luca, et al.. (2023). An assessment of water management measures for climate change adaptation of agriculture in Seewinkel. The Science of The Total Environment. 885. 163906–163906. 12 indexed citations
7.
Ortiz‐Partida, J. Pablo, Angel Santiago Fernandez‐Bou, Mahesh L. Maskey, et al.. (2023). Hydro-Economic Modeling of Water Resources Management Challenges: Current Applications and Future Directions. Water Economics and Policy. 9(1). 18 indexed citations
8.
Lees, Thomas, Steven Reece, Frederik Kratzert, et al.. (2022). Hydrological concept formation inside long short-term memory (LSTM) networks. Hydrology and earth system sciences. 26(12). 3079–3101. 95 indexed citations
9.
Sahu, Reetik Kumar, et al.. (2022). Assimilation of multi-channel radiances in mesoscale models with an ensemble technique to improve track forecasts of Tropical cyclones. Journal of Earth System Science. 131(2). 6 indexed citations
10.
Park, Jangho, Juliane Müller, Bhavna Arora, et al.. (2022). Long-term missing value imputation for time series data using deep neural networks. Neural Computing and Applications. 30 indexed citations
11.
Lees, Thomas, Steven Reece, Frederik Kratzert, et al.. (2021). Hydrological Concept Formation inside Long Short-Term Memory (LSTM) networks. 12 indexed citations
12.
Sahu, Reetik Kumar & Dennis McLaughlin. (2021). The Multi‐Scale Dynamics of Groundwater Depletion. Water Resources Research. 57(12). 3 indexed citations
13.
Müller, Juliane, Jangho Park, Reetik Kumar Sahu, et al.. (2020). Surrogate optimization of deep neural networks for groundwater predictions. Journal of Global Optimization. 81(1). 203–231. 70 indexed citations
14.
Sahu, Reetik Kumar, Juliane Müller, Jangho Park, et al.. (2020). Impact of Input Feature Selection on Groundwater Level Prediction From a Multi-Layer Perceptron Neural Network. Frontiers in Water. 2. 34 indexed citations
15.
Sahu, Reetik Kumar, et al.. (2020). Significance of Averaging the Lower Link Sensed Forces for Draft Control in Electro-Hydraulic Systems. International Journal of Current Microbiology and Applied Sciences. 9(6). 1504–1511. 1 indexed citations
16.
Sahu, Reetik Kumar & Dennis McLaughlin. (2018). An Ensemble Optimization Framework for Coupled Design of Hydropower Contracts and Real‐Time Reservoir Operating Rules. Water Resources Research. 54(10). 8401–8419. 13 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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