D. Nagesh Kumar

7.9k total citations
164 papers, 6.1k citations indexed

About

D. Nagesh Kumar is a scholar working on Global and Planetary Change, Environmental Engineering and Water Science and Technology. According to data from OpenAlex, D. Nagesh Kumar has authored 164 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Global and Planetary Change, 65 papers in Environmental Engineering and 43 papers in Water Science and Technology. Recurrent topics in D. Nagesh Kumar's work include Hydrology and Watershed Management Studies (37 papers), Water resources management and optimization (35 papers) and Climate variability and models (34 papers). D. Nagesh Kumar is often cited by papers focused on Hydrology and Watershed Management Studies (37 papers), Water resources management and optimization (35 papers) and Climate variability and models (34 papers). D. Nagesh Kumar collaborates with scholars based in India, United States and France. D. Nagesh Kumar's co-authors include M. Janga Reddy, K. Srinivasa Raju, P. Sonali, Rajib Maity, L. Karthikeyan, C. T. Dhanya, Ravi S. Nanjundiah, Basudev Biswal, Komaragiri Srinivasa Raju and P. Anand Raj and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Geophysical Research Atmospheres and Remote Sensing of Environment.

In The Last Decade

D. Nagesh Kumar

157 papers receiving 5.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Nagesh Kumar India 44 2.6k 2.3k 1.8k 1.7k 1.2k 164 6.1k
Hugo A. Loáiciga United States 40 1.7k 0.7× 2.9k 1.3× 2.4k 1.3× 1.6k 1.0× 461 0.4× 283 6.2k
Dimitri Solomatine Netherlands 48 3.6k 1.4× 4.1k 1.8× 881 0.5× 3.9k 2.3× 997 0.8× 199 8.3k
Fi‐John Chang Taiwan 54 3.0k 1.2× 4.1k 1.8× 1.9k 1.1× 4.3k 2.6× 925 0.8× 200 9.0k
Andrea Castelletti Italy 50 2.3k 0.9× 3.6k 1.6× 3.5k 2.0× 1.0k 0.6× 308 0.3× 225 7.3k
Guangtao Fu United Kingdom 49 3.1k 1.2× 3.4k 1.5× 1.7k 1.0× 3.2k 1.9× 533 0.4× 196 8.7k
Francesca Pianosi United Kingdom 34 1.7k 0.7× 2.0k 0.9× 1.2k 0.7× 1.2k 0.7× 451 0.4× 97 5.0k
Yuefei Huang China 41 2.3k 0.9× 1.9k 0.8× 703 0.4× 957 0.6× 558 0.5× 147 5.1k
K. P. Sudheer India 41 3.3k 1.3× 3.9k 1.7× 645 0.4× 4.4k 2.6× 725 0.6× 119 7.0k
David R. Maidment United States 44 4.0k 1.5× 4.7k 2.0× 951 0.5× 1.9k 1.1× 1.2k 1.0× 201 7.7k
Bryan A. Tolson Canada 29 1.5k 0.6× 2.2k 1.0× 950 0.5× 1.5k 0.9× 581 0.5× 94 4.0k

Countries citing papers authored by D. Nagesh Kumar

Since Specialization
Citations

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

Fields of papers citing papers by D. Nagesh Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Nagesh Kumar

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

All Works

20 of 20 papers shown
1.
Kumar, D. Nagesh, et al.. (2025). Unprecedented rainfall events increase the magnitude of design storms. Environmental Research Letters. 20(6). 64011–64011.
2.
Bala, Ruchi, et al.. (2024). Examining the relationship of major air pollutants with land surface parameters and its monthly variation in Indian cities using satellite data. Remote Sensing Applications Society and Environment. 35. 101232–101232. 2 indexed citations
3.
Raju, K. Srinivasa, et al.. (2024). Boosting algorithms for projecting streamflow in the Lower Godavari Basin for different climate change scenarios. Water Science & Technology. 89(3). 613–634. 8 indexed citations
4.
Kumar, D. Nagesh, et al.. (2024). A framework for multivariate analysis of compound extremes based on correlated hydrologic time series. Journal of Hydrology. 637. 131294–131294. 2 indexed citations
5.
Kumar, D. Nagesh, et al.. (2024). Optimizing parameter estimation in hydrological models with convolutional neural network guided dynamically dimensioned search approach. Advances in Water Resources. 194. 104842–104842. 1 indexed citations
6.
7.
Gomez, Cécile, et al.. (2024). Visible and infrared lab spectroscopy for soil texture classification: Analysis of entire spectra v/s reduced spectra. Remote Sensing Applications Society and Environment. 35. 101242–101242. 1 indexed citations
8.
Kumar, D. Nagesh, et al.. (2023). Endmember variability based abundance estimation of red and black soil over sparsely vegetated area using AVIRIS-NG hyperspectral image. Advances in Space Research. 73(2). 1349–1359. 5 indexed citations
9.
Sushama, Laxmi, Lijun Sun, M. N. Khaliq, et al.. (2023). Physics-informed deep learning framework to model intense precipitation events at super resolution. Geoscience Letters. 10(1). 19–19. 6 indexed citations
10.
Kumar, D. Nagesh, et al.. (2023). Evaluating the parameter sensitivity and impact of hydrologic modeling decisions on flood simulations. Advances in Water Resources. 181. 104560–104560. 4 indexed citations
11.
Murthy, C. S., et al.. (2022). Generating pre-harvest crop maps by applying convolutional neural network on multi-temporal Sentinel-1 data. International Journal of Remote Sensing. 43(15-16). 6078–6101. 15 indexed citations
12.
Reddy, M. Janga & D. Nagesh Kumar. (2020). Evolutionary algorithms, swarm intelligence methods, and their applications in water resources engineering: a state-of-the-art review. H2Open Journal. 3(1). 135–188. 82 indexed citations
13.
Vinayaraj, Poliyapram, et al.. (2020). Canopy Averaged Chlorophyll Content Prediction of Pear Trees Using Convolutional Autoencoder on Hyperspectral Data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13. 1426–1437. 16 indexed citations
14.
Adarsh, S., et al.. (2019). Multifractal characterization of meteorological drought in India using detrended fluctuation analysis. International Journal of Climatology. 39(11). 4234–4255. 44 indexed citations
15.
Raju, K. Srinivasa, et al.. (2018). Prioritization of sub-catchments of a river basin using DEM and Fuzzy VIKOR. H2Open Journal. 1(1). 1–11. 6 indexed citations
16.
Kumar, D. Nagesh, et al.. (2015). Seasonal Change Detection and Attribution of Surface Temperature changes over Interior Peninsular Region of India. EGUGA. 292. 1 indexed citations
17.
Dhanya, C. T. & D. Nagesh Kumar. (2009). Fuzzy Association Rules for Prediction of Monsoon Rainfall.. Indian International Conference on Artificial Intelligence. 1299–1309. 1 indexed citations
18.
Kumar, D. Nagesh, M. Janga Reddy, & Rajib Maity. (2005). Regional Rainfall Forecasting using Large Scale Climate Teleconnections and Evolutionary Algorithms. Indian International Conference on Artificial Intelligence. 1169–1182. 2 indexed citations
19.
Reddy, M. Janga & D. Nagesh Kumar. (2005). Multi-Objective Particle Swarm Optimization for Optimal Reservoir Operation.. Indian International Conference on Artificial Intelligence. 1183–1192. 6 indexed citations
20.
Raju, K. Srinivasa & D. Nagesh Kumar. (2000). IRRIGATION PLANNING OF SRI RAM SAGAR PROJECT USING MULTI OBJECTIVE FUZZY LINEAR PROGRAMMING. ISH Journal of Hydraulic Engineering. 6(1). 55–63. 25 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Hugo A. Loáiciga Breakdown of academic impact, for papers by Dimitri Solomatine Breakdown of academic impact, for papers by Fi‐John Chang Breakdown of academic impact, for papers by Andrea Castelletti Breakdown of academic impact, for papers by Guangtao Fu Breakdown of academic impact, for papers by Francesca Pianosi Breakdown of academic impact, for papers by Yuefei Huang Breakdown of academic impact, for papers by K. P. Sudheer Breakdown of academic impact, for papers by David R. Maidment Breakdown of academic impact, for papers by Bryan A. Tolson
Rankless by CCL
2026