Dillip K. Ghose

1.1k total citations
32 papers, 510 citations indexed

About

Dillip K. Ghose is a scholar working on Environmental Engineering, Water Science and Technology and Global and Planetary Change. According to data from OpenAlex, Dillip K. Ghose has authored 32 papers receiving a total of 510 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Environmental Engineering, 24 papers in Water Science and Technology and 15 papers in Global and Planetary Change. Recurrent topics in Dillip K. Ghose's work include Hydrological Forecasting Using AI (24 papers), Hydrology and Watershed Management Studies (22 papers) and Flood Risk Assessment and Management (10 papers). Dillip K. Ghose is often cited by papers focused on Hydrological Forecasting Using AI (24 papers), Hydrology and Watershed Management Studies (22 papers) and Flood Risk Assessment and Management (10 papers). Dillip K. Ghose collaborates with scholars based in India, United States and Germany. Dillip K. Ghose's co-authors include Sandeep Samantaray, Abinash Sahoo, Siva S. Panda, Vijay Kumar Mahakur, Upendra Kumar, Ravi Kumar Guntu, Maheswaran Rathinasamy, Bibhu Prasad Mishra, Deba Prakash Satapathy and Jürgen Kurths and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Hydrology and Environmental Modelling & Software.

In The Last Decade

Dillip K. Ghose

30 papers receiving 492 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dillip K. Ghose India 14 353 253 236 52 52 32 510
Meral Büyükyıldız Türkiye 10 283 0.8× 240 0.9× 230 1.0× 72 1.4× 55 1.1× 31 480
Ngoc Duong Vo Vietnam 10 202 0.6× 256 1.0× 291 1.2× 62 1.2× 51 1.0× 24 503
Birendra Bharti India 5 276 0.8× 225 0.9× 230 1.0× 70 1.3× 59 1.1× 12 446
Mustafa Al-Mukhtar Iraq 13 264 0.7× 307 1.2× 228 1.0× 75 1.4× 39 0.8× 30 559
Marzieh Fadaee Iran 6 318 0.9× 276 1.1× 191 0.8× 51 1.0× 47 0.9× 9 540
Lingling Ni China 9 396 1.1× 345 1.4× 298 1.3× 63 1.2× 91 1.8× 13 620
Mehdi Rezaeianzadeh United States 11 334 0.9× 274 1.1× 350 1.5× 52 1.0× 90 1.7× 16 573
Ahmed H. Birima Malaysia 14 356 1.0× 297 1.2× 131 0.6× 39 0.8× 67 1.3× 21 580
Fazlı Öztürk Türkiye 12 217 0.6× 207 0.8× 187 0.8× 46 0.9× 51 1.0× 20 422
Mohammad Zeynoddin Canada 11 313 0.9× 222 0.9× 175 0.7× 41 0.8× 75 1.4× 21 530

Countries citing papers authored by Dillip K. Ghose

Since Specialization
Citations

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

Fields of papers citing papers by Dillip K. Ghose

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dillip K. Ghose. 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 Dillip K. Ghose. The network helps show where Dillip K. Ghose may publish in the future.

Co-authorship network of co-authors of Dillip K. Ghose

This figure shows the co-authorship network connecting the top 25 collaborators of Dillip K. Ghose. A scholar is included among the top collaborators of Dillip K. Ghose 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 Dillip K. Ghose. Dillip K. Ghose 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.
2.
Ghose, Dillip K., et al.. (2024). Identifying hidden groundwater reserves: GIS advances and multi-criteria decision analysis for enhanced potential assessment. Advances in Space Research. 75(1). 432–450. 3 indexed citations
3.
Mahakur, Vijay Kumar, et al.. (2024). Prediction of runoff at ungauged areas employing interpolation techniques and deep learning algorithm. SHILAP Revista de lepidopterología. 8. 265–275. 23 indexed citations
4.
Ghose, Dillip K., et al.. (2024). Assessment of Groundwater Potential Using Geospatial Techniques Employing FUCOM, BWM, and AHP. Journal of Hydrologic Engineering. 29(6). 4 indexed citations
5.
Ghose, Dillip K., et al.. (2023). Geospatial Modeling of Groundwater Potential Using Multi-criteria Decision Analysis in Humid Subtropical Region, India. Journal of the Geological Society of India. 99(11). 1532–1538. 3 indexed citations
6.
Samantaray, Sandeep, et al.. (2022). Prediction of Bed-Load Sediment Using Newly Developed Support-Vector Machine Techniques. Journal of Irrigation and Drainage Engineering. 148(10). 23 indexed citations
7.
Sahoo, Abinash, et al.. (2022). Prediction of Rainfall Using Hybrid SVM-HHO Model. IOP Conference Series Earth and Environmental Science. 1084(1). 12054–12054. 6 indexed citations
8.
Mishra, Bibhu Prasad, Dillip K. Ghose, & Deba Prakash Satapathy. (2022). Geospatial modeling using hybrid machine learning approach for flood susceptibility. Earth Science Informatics. 15(4). 2619–2636. 10 indexed citations
9.
Samantaray, Sandeep & Dillip K. Ghose. (2021). Prediction of S12-MKII rainfall simulator experimental runoff data sets using hybrid PSR-SVM-FFA approaches. Journal of Water and Climate Change. 13(2). 707–734. 24 indexed citations
10.
Ghose, Dillip K., et al.. (2021). Multiscale Spatiotemporal Analysis of Extreme Events in the Gomati River Basin, India. Atmosphere. 12(4). 480–480. 19 indexed citations
11.
Sahoo, Abinash, Sandeep Samantaray, & Dillip K. Ghose. (2021). Prediction of Flood in Barak River using Hybrid Machine Learning Approaches: A Case Study. Journal of the Geological Society of India. 97(2). 186–198. 34 indexed citations
12.
Samantaray, Sandeep & Dillip K. Ghose. (2020). Modelling runoff in an arid watershed through integrated support vector machine. H2Open Journal. 3(1). 256–275. 6 indexed citations
13.
Samantaray, Sandeep & Dillip K. Ghose. (2020). Assessment of Suspended Sediment Load with Neural Networks in Arid Watershed. Journal of The Institution of Engineers (India) Series A. 101(2). 371–380. 6 indexed citations
14.
Samantaray, Sandeep, Abinash Sahoo, & Dillip K. Ghose. (2020). Assessment of Sediment Load Concentration Using SVM, SVM-FFA and PSR-SVM-FFA in Arid Watershed, India: A Case Study. KSCE Journal of Civil Engineering. 24(6). 1944–1957. 20 indexed citations
15.
Ghose, Dillip K. & Sandeep Samantaray. (2020). Modelling runoff in a river basin, India: an integration for developing un-gauged catchment. International Journal of Hydrology Science and Technology. 10(3). 248–248. 3 indexed citations
16.
Samantaray, Sandeep & Dillip K. Ghose. (2020). Modelling runoff in a river basin, India: an integration for developing un-gauged catchment. International Journal of Hydrology Science and Technology. 10(3). 248–248. 5 indexed citations
17.
Ghose, Dillip K., et al.. (2018). Modeling response of runoff and evapotranspiration for predicting water table depth in arid region using dynamic recurrent neural network. Groundwater for Sustainable Development. 6. 263–269. 43 indexed citations
18.
Samantaray, Sandeep, et al.. (2018). Removal of Turbidity Using Dual Media Filter. 4. 302–311. 1 indexed citations
19.
Ghose, Dillip K., et al.. (2011). EROSION AND SEDIMENT CHARACTERISTICS OF PENINSULAR RIVER INDIA, A CASE STUDY. 3 indexed citations
20.
Ghose, Dillip K., et al.. (2009). Oscillation of a higher order neutral differential equation with a sub-linear delay term and positive and negative coefficients. Mathematica Bohemica. 134(4). 411–425. 1 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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