Pravendra Kumar
Impact in
- Environmental Engineering top 5%
- Hydrological Forecasting Using AI
- Water Science and Technology top 5%
- Hydrology and Watershed Management Studies
- Water Quality Monitoring Technologies
Papers in
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- Hydrology and Watershed Management Studies 21
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- Hydrological Forecasting Using AI 17
- Groundwater and Watershed Analysis 2
- Co-authors
- Alban Kuriqi (7 shared papers)Manish Kumar (6 shared papers)Ahmed Elbeltagi (3 shared papers)Rawshan Ali (2 shared papers)Anurag Malik (2 shared papers)Dinesh Kumar Vishwakarma (3 shared papers)Nadhir Al‐Ansari (2 shared papers)Anil Kumar (1 shared paper)
In The Last Decade
Pravendra Kumar
21 papers receiving 344 citations
Peers
Comparison fields: 5 of 47
- Environmental Engineering 239
- Water Science and Technology 233
- Global and Planetary Change 175
- Soil Science 48
- Ecology 57
Countries citing papers authored by Pravendra Kumar
This map shows the geographic impact of Pravendra Kumar'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 Pravendra Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pravendra Kumar more than expected).
Fields of papers citing papers by Pravendra Kumar
This network shows the impact of papers produced by Pravendra Kumar. 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 Pravendra Kumar. The network helps show where Pravendra Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Pravendra Kumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 65 | |
| 2 | 2022 | 38 | |
| 3 | 2021 | 37 | |
| 4 | 2021 | 35 | |
| 5 | 2020 | 33 | |
| 6 | 2021 | 31 | |
| 7 | 2023 | 28 | |
| 8 | 2022 | 25 | |
| 9 | 2024 | 17 | |
| 10 | 2021 | 13 | |
| 11 | Modelling river suspended sediment load using artificial neural network and multiple linear regression: Vamsadhara River Basin, India | 2017 | 5 |
| 12 | 2018 | 5 | |
| 13 | 2021 | 4 | |
| 14 | 2023 | 3 | |
| 15 | 2018 | 3 | |
| 16 | 2021 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2024 | 2 | |
| 19 | 2017 | 1 | |
| 20 | 2022 | 1 |
About Pravendra Kumar
Pravendra Kumar is a scholar working on Water Science and Technology, Environmental Engineering, Global and Planetary Change, Soil Science and Ecology, having authored 25 papers that have together received 353 indexed citations. Recurring topics across this work include Hydrology and Watershed Management Studies (21 papers), Hydrological Forecasting Using AI (17 papers), Flood Risk Assessment and Management (9 papers), Hydrology and Drought Analysis (6 papers), Soil erosion and sediment transport (4 papers), Neural Networks and Applications (2 papers), Groundwater and Watershed Analysis (2 papers) and Plant Water Relations and Carbon Dynamics (2 papers). The work is most often cited by research in Environmental Engineering (239 citations), Water Science and Technology (233 citations), Global and Planetary Change (175 citations), Soil Science (48 citations) and Ecology (57 citations). Pravendra Kumar has collaborated with scholars based in India, Portugal and Iraq. Frequent co-authors include Alban Kuriqi, Manish Kumar, Ahmed Elbeltagi, Rawshan Ali, Anurag Malik, Dinesh Kumar Vishwakarma, Nadhir Al‐Ansari, Anil Kumar, Rohitashw Kumar and Anuradha Kumari. Their work appears in journals such as Sustainability, Environmental Science and Pollution Research, Applied Water Science, Water Resources Management and Heliyon.
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.