Soumya S. Singha

782 total citations · 1 hit paper
13 papers, 495 citations indexed

About

Soumya S. Singha is a scholar working on Environmental Engineering, Water Science and Technology and Geochemistry and Petrology. According to data from OpenAlex, Soumya S. Singha has authored 13 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Environmental Engineering, 6 papers in Water Science and Technology and 4 papers in Geochemistry and Petrology. Recurrent topics in Soumya S. Singha's work include Groundwater and Watershed Analysis (9 papers), Groundwater and Isotope Geochemistry (4 papers) and Water Quality and Pollution Assessment (4 papers). Soumya S. Singha is often cited by papers focused on Groundwater and Watershed Analysis (9 papers), Groundwater and Isotope Geochemistry (4 papers) and Water Quality and Pollution Assessment (4 papers). Soumya S. Singha collaborates with scholars based in India and Russia. Soumya S. Singha's co-authors include Sudhakar Singha, Srinivas Pasupuleti, Suresh Kumar, Rambabu Singh, A. S. Venkatesh, Mithila Verma, Sunil Saha and R. Singh and has published in prestigious journals such as Chemosphere, Journal of Environmental Management and Environmental Earth Sciences.

In The Last Decade

Soumya S. Singha

12 papers receiving 483 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Prediction of groundwater quality using efficient machine learning technique

2021 255 citations Sudhakar Singha, Srinivas Pasupuleti et al. Chemosphere profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Soumya S. Singha India	9	347	287	156	73	65	13	495
Sudhakar Singha India	11	369 1.1×	299 1.0×	161 1.0×	86 1.2×	68 1.0×	18	546
Ammar Tiri Algeria	12	238 0.7×	313 1.1×	204 1.3×	37 0.5×	77 1.2×	17	542
Gagandeep Singh India	12	292 0.8×	319 1.1×	345 2.2×	81 1.1×	66 1.0×	20	594
Suyash Kumar India	9	269 0.8×	231 0.8×	197 1.3×	92 1.3×	70 1.1×	11	496
Nura Umar Kura Malaysia	11	245 0.7×	203 0.7×	231 1.5×	44 0.6×	36 0.6×	16	454
Abel Ojo Talabi Nigeria	9	294 0.8×	161 0.6×	125 0.8×	151 2.1×	58 0.9×	34	516
Wenwen Feng China	8	303 0.9×	324 1.1×	394 2.5×	41 0.6×	39 0.6×	15	602
Hekmat Ibrahim Egypt	7	268 0.8×	284 1.0×	212 1.4×	21 0.3×	71 1.1×	9	454
Obialo S. Onwuka Nigeria	13	211 0.6×	216 0.8×	204 1.3×	30 0.4×	58 0.9×	25	437
Gyoo-Bum Kim South Korea	13	368 1.1×	334 1.2×	180 1.2×	117 1.6×	57 0.9×	83	641

Countries citing papers authored by Soumya S. Singha

Since Specialization

Citations

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

Fields of papers citing papers by Soumya S. Singha

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soumya S. Singha. 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 Soumya S. Singha. The network helps show where Soumya S. Singha may publish in the future.

Co-authorship network of co-authors of Soumya S. Singha

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

All Works

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13 of 13 papers shown

Singha, Soumya S., et al.. (2025). Comparative assessment of groundwater quality using subjective and objective weighting methods in a multi-criteria decision analysis framework. Groundwater for Sustainable Development. 31. 101553–101553. 1 indexed citations

Singh, R., et al.. (2023). Geospatial delineation of flood susceptible zones using analytical hierarchy process. IOP Conference Series Earth and Environmental Science. 1280(1). 12052–12052.

Pasupuleti, Srinivas, Soumya S. Singha, Soumya S. Singha, et al.. (2022). Groundwater characterization and non-carcinogenic and carcinogenic health risk assessment of nitrate exposure in the Mahanadi River Basin of India. Journal of Environmental Management. 319. 115746–115746. 42 indexed citations

Singha, Soumya S., Sudhakar Singha, Srinivas Pasupuleti, & A. S. Venkatesh. (2022). Knowledge-driven and machine learning decision tree-based approach for assessment of geospatial variation of groundwater quality around coal mining regions, Korba district, Central India. Environmental Earth Sciences. 81(2). 16 indexed citations

Singha, Sudhakar, Srinivas Pasupuleti, Soumya S. Singha, Rambabu Singh, & Suresh Kumar. (2021). Prediction of groundwater quality using efficient machine learning technique. Chemosphere. 276. 130265–130265. 255 indexed citations breakdown →

Singha, Sudhakar, et al.. (2020). A fuzzy geospatial approach for delineation of groundwater potential zones in Raipur district, India. Groundwater for Sustainable Development. 12. 100529–100529. 18 indexed citations

Singha, Sudhakar, Srinivas Pasupuleti, Soumya S. Singha, & Suresh Kumar. (2020). Effectiveness of groundwater heavy metal pollution indices studies by deep-learning. Journal of Contaminant Hydrology. 235. 103718–103718. 62 indexed citations

Singha, Soumya S. & Srinivas Pasupuleti. (2020). Hydrogeochemical modeling based approach for evaluation of groundwater suitability for irrigational use in Korba district, Chhattisgarh, Central India. SN Applied Sciences. 2(9). 13 indexed citations

Singha, Soumya S., Srinivas Pasupuleti, Sudhakar Singha, Rambabu Singh, & A. S. Venkatesh. (2019). Analytic network process based approach for delineation of groundwater potential zones in Korba district, Central India using remote sensing and GIS. Geocarto International. 36(13). 1489–1511. 29 indexed citations

10.

Singha, Soumya S., Srinivas Pasupuleti, Sudhakar Singha, Rambabu Singh, & A. S. Venkatesh. (2019). A GIS-based modified DRASTIC approach for geospatial modeling of groundwater vulnerability and pollution risk mapping in Korba district, Central India. Environmental Earth Sciences. 78(21). 34 indexed citations

11.

Singha, Sudhakar, et al.. (2019). An analytical hierarchy process-based geospatial modeling for delineation of potential anthropogenic contamination zones of groundwater from Arang block of Raipur district, Chhattisgarh, Central India. Environmental Earth Sciences. 78(24). 16 indexed citations

12.

Pasupuleti, Srinivas, et al.. (2018). Delineation of groundwater potential zones utilising geospatial techniques in Kadiri watershed of Anantapur district, Andhra Pradesh, India. Journal of Environmental Biology. 40(1). 61–68. 4 indexed citations

13.

Singha, Soumya S., et al.. (2015). Assessing Ground Water Quality using GIS. International Journal of Engineering Research and. V4(11). 5 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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