Hamid Mohebzadeh

436 total citations
22 papers, 330 citations indexed

About

Hamid Mohebzadeh is a scholar working on Environmental Engineering, Water Science and Technology and Global and Planetary Change. According to data from OpenAlex, Hamid Mohebzadeh has authored 22 papers receiving a total of 330 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Environmental Engineering, 12 papers in Water Science and Technology and 10 papers in Global and Planetary Change. Recurrent topics in Hamid Mohebzadeh's work include Hydrology and Watershed Management Studies (10 papers), Flood Risk Assessment and Management (7 papers) and Hydrological Forecasting Using AI (6 papers). Hamid Mohebzadeh is often cited by papers focused on Hydrology and Watershed Management Studies (10 papers), Flood Risk Assessment and Management (7 papers) and Hydrological Forecasting Using AI (6 papers). Hamid Mohebzadeh collaborates with scholars based in Canada, South Korea and United States. Hamid Mohebzadeh's co-authors include Taesam Lee, Prasad Daggupati, Asim Biswas, Ramesh Rudra, Ehsan Olyaie, Özgür Kişi, Zohrab Samani, David W. DuBois, Hossein Banejad and M. H. Ghobadi and has published in prestigious journals such as International Journal of Remote Sensing, Remote Sensing and Soil and Tillage Research.

In The Last Decade

Hamid Mohebzadeh

20 papers receiving 327 citations

Peers

Hamid Mohebzadeh

WST

GPC

OCEAN

Junxiang Cheng China

P. D. Sreekanth India

Seree Supharatid Thailand

Mani Kant Verma India

Mojtaba Noury Iran

Rana Ammar Aslam Pakistan

Faisal Baig United Arab Emirates

Recep Yurtal Türkiye

Tewodros Assefa Nigussie Ethiopia

Raphael Schneider Denmark

Junxiang Cheng China

Hamid Mohebzadeh

135 ×0.7

215 ×1.1

WST

170 ×0.9

GPC

23 ×0.7

13 ×0.4

OCEAN

Citations per year, relative to Hamid Mohebzadeh Hamid Mohebzadeh (= 1×) peers Junxiang Cheng

Countries citing papers authored by Hamid Mohebzadeh

Since Specialization

Citations

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

Fields of papers citing papers by Hamid Mohebzadeh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hamid Mohebzadeh. 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 Hamid Mohebzadeh. The network helps show where Hamid Mohebzadeh may publish in the future.

Co-authorship network of co-authors of Hamid Mohebzadeh

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

All Works

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20 of 20 papers shown

Mohebzadeh, Hamid, Asim Biswas, Ben DeVries, et al.. (2025). Integrating genetic algorithm with AnnAGNPS for optimizing BMPs placement to reduce sheet/rill and ephemeral gully erosion. Soil and Tillage Research. 252. 106598–106598.

Mohebzadeh, Hamid, Asim Biswas, Ben DeVries, et al.. (2024). Evaluation of the impact of best management practices on ephemeral gully and sheet/rill erosion using the AnnAGNPS model. CATENA. 246. 108436–108436. 4 indexed citations

Bateni, Sayed M., et al.. (2024). Filling gaps in MODIS NDVI data using hybrid multiple imputation–Machine learning and DINCAE techniques: Case study of the State of Hawaii. Advances in Engineering Software. 201. 103856–103856. 2 indexed citations

Mohebzadeh, Hamid, Asim Biswas, Ben DeVries, et al.. (2024). Efficient detection of ephemeral gully trajectories using topographic index-based approach: Calibration-free for large-scale applications. International Journal of Sediment Research. 39(4). 586–600. 1 indexed citations

Mohebzadeh, Hamid, Asim Biswas, Ramesh Rudra, & Prasad Daggupati. (2022). Machine Learning Techniques for Gully Erosion Susceptibility Mapping: A Review. Geosciences. 12(12). 429–429. 22 indexed citations

DuBois, David W., et al.. (2021). Estimation of daily reference evapotranspiration with limited climatic data using machine learning approaches across different climate zones in New Mexico. Theoretical and Applied Climatology. 147(1-2). 575–587. 19 indexed citations

Mohebzadeh, Hamid, et al.. (2021). Spatiotemporal imputation of MODIS land surface temperature using machine learning techniques (Case study: New Mexico's Lower Rio Grande Valley). Remote Sensing Applications Society and Environment. 24. 100651–100651. 6 indexed citations

Mohebzadeh, Hamid, et al.. (2021). A machine learning approach for spatiotemporal imputation of MODIS chlorophyll-a. International Journal of Remote Sensing. 42(19). 7381–7404. 11 indexed citations

Lee, Taesam, et al.. (2021). Rainfall-runoff simulation using satellite rainfall in a scarce data catchment. Journal of Applied Water Engineering and Research. 9(2). 161–174. 6 indexed citations

10.

Mohebzadeh, Hamid, et al.. (2020). Employing Machine Learning Algorithms for Streamflow Prediction: A Case Study of Four River Basins with Different Climatic Zones in the United States. Water Resources Management. 34(13). 4113–4131. 127 indexed citations

11.

Mohebzadeh, Hamid, Junho Yeom, & Taesam Lee. (2020). Spatial Downscaling of MODIS Chlorophyll-a with Genetic Programming in South Korea. Remote Sensing. 12(9). 1412–1412. 9 indexed citations

12.

Mohebzadeh, Hamid & Taesam Lee. (2020). Spatial downscaling of MODIS Chlorophyll-a with machine learning techniques over the west coast of the Yellow Sea in South Korea. Journal of Oceanography. 77(1). 103–122. 17 indexed citations

13.

Lee, Taesam, et al.. (2019). Allocating Underground Dam Sites Using Remote Sensing and GIS Case Study on the Southwestern Plain of Tehran Province, Iran. Journal of the Indian Society of Remote Sensing. 47(6). 989–1002. 6 indexed citations

14.

Mohebzadeh, Hamid, et al.. (2018). Application of GIS and statistical methods for design of dams for water supply and flood control: a case study of Virgin River basin, Utah State, USA. Indian Journal of Science and Technology. 11(26). 1–9. 1 indexed citations

15.

Mohebzadeh, Hamid, et al.. (2018). Quantitative analysis of water balance components in Lake Urmia, Iran using remote sensing technology. Remote Sensing Applications Society and Environment. 13. 389–400. 37 indexed citations

16.

Mohebzadeh, Hamid. (2018). Extracting A-L Relationship for Urmia Lake, Iran Using MODIS NDVI/NDWI Indices. 7(1). 5 indexed citations

17.

Mohebzadeh, Hamid, et al.. (2018). A GIS-Based Modelling for Identifying High Priority Areas for Groundwater Recharge. 8(3). 1 indexed citations

18.

Banejad, Hossein, et al.. (2014). Numerical Simulation of Groundwater Flow and Contamination Transport in Nahavand Plain Aquifer, West of Iran. Journal of the Geological Society of India. 83(1). 83–92. 13 indexed citations

19.

Olyaie, Ehsan, et al.. (2013). Development of a Neural Network Technique for Prediction of Water Quality Parameters in the Delaware River, Pennsylvania. Middle East journal of scientific research. 13(10). 1367–1376. 22 indexed citations

20.

Banejad, Hossein, et al.. (2012). Numerical Simulation of the Flow and Contaminant Transport in Groundwater, Case Study: Nahavand Plain Aquifer. 23(2). 43–57. 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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