Muthoni Masinde

1.1k total citations
69 papers, 642 citations indexed

About

Muthoni Masinde is a scholar working on Global and Planetary Change, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Muthoni Masinde has authored 69 papers receiving a total of 642 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Global and Planetary Change, 14 papers in Information Systems and 12 papers in Computer Networks and Communications. Recurrent topics in Muthoni Masinde's work include Hydrology and Drought Analysis (12 papers), Climate variability and models (10 papers) and ICT in Developing Communities (8 papers). Muthoni Masinde is often cited by papers focused on Hydrology and Drought Analysis (12 papers), Climate variability and models (10 papers) and ICT in Developing Communities (8 papers). Muthoni Masinde collaborates with scholars based in South Africa, Kenya and Ethiopia. Muthoni Masinde's co-authors include Antoine Bagula, Ntsoaki Joyce Malebo, Mokgaotsa Jonas Mochane, Joel O. Botai, Christina M. Botai, Tafadzwanashe Mabhaudhi, Omolola M. Adisa, Abiodun M. Adeola, Israel Edem Agbehadji and Nzioka John Muthama and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sensors and International Journal of Environmental Research and Public Health.

In The Last Decade

Muthoni Masinde

62 papers receiving 611 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muthoni Masinde South Africa 14 157 103 74 73 64 69 642
Agnes F. Vandome 8 166 1.1× 31 0.3× 33 0.4× 54 0.7× 114 1.8× 40 696
Frederic P. Miller 8 166 1.1× 31 0.3× 33 0.4× 54 0.7× 114 1.8× 39 696
John McBrewster 8 166 1.1× 31 0.3× 33 0.4× 54 0.7× 114 1.8× 39 696
Yutaka Matsuno Japan 14 76 0.5× 159 1.5× 27 0.4× 25 0.3× 53 0.8× 93 645
Asaf Tzachor United Kingdom 18 98 0.6× 46 0.4× 24 0.3× 26 0.4× 86 1.3× 47 951
Rob Knapen Netherlands 11 214 1.4× 101 1.0× 238 3.2× 38 0.5× 81 1.3× 33 932
Jiyang Zhang China 14 136 0.9× 62 0.6× 33 0.4× 93 1.3× 67 1.0× 45 848
Xiaofeng Zhao China 18 183 1.2× 23 0.2× 35 0.5× 45 0.6× 50 0.8× 63 997
Thomas Clemen Germany 10 302 1.9× 84 0.8× 30 0.4× 36 0.5× 37 0.6× 38 831
Yu Hua China 15 65 0.4× 103 1.0× 15 0.2× 25 0.3× 85 1.3× 54 994

Countries citing papers authored by Muthoni Masinde

Since Specialization
Citations

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

Fields of papers citing papers by Muthoni Masinde

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muthoni Masinde

This figure shows the co-authorship network connecting the top 25 collaborators of Muthoni Masinde. A scholar is included among the top collaborators of Muthoni Masinde 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 Muthoni Masinde. Muthoni Masinde 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.
Kebede, Asfaw, et al.. (2025). Hybrid data-driven and process-based modeling for streamflow forecasting: comparative uncertainty analysis in the upper Baro watershed. Stochastic Environmental Research and Risk Assessment. 39(12). 6299–6328.
2.
Masinde, Muthoni, et al.. (2025). Integrating machine learning and physical models for rainfall-runoff prediction in the Upper Baro Akobo River Basin, Ethiopia. Hydrological Sciences Journal. 70(12). 2129–2146. 2 indexed citations
3.
Kebede, Asfaw, et al.. (2024). Comparative analysis of HEC-HMS and machine learning models for rainfall-runoff prediction in the upper Baro watershed, Ethiopia. Hydrology research. 55(9). 873–889. 8 indexed citations
4.
Masinde, Muthoni, et al.. (2023). Investigating the adoption of indigenous knowledge in mitigating climate-linked challenges. International Journal of Research in Business and Social Science (2147-4478). 12(7). 394–404. 1 indexed citations
5.
Masinde, Muthoni, et al.. (2023). A Scalable Semantic Framework for an Integrated Multi-Hazard Early Warning System. 2. 1–6. 1 indexed citations
6.
Agbehadji, Israel Edem, Stefanie Schütte, Muthoni Masinde, Joel O. Botai, & Tafadzwanashe Mabhaudhi. (2023). Climate Risks Resilience Development: A Bibliometric Analysis of Climate-Related Early Warning Systems in Southern Africa. Climate. 12(1). 3–3. 16 indexed citations
7.
Agbehadji, Israel Edem, Tafadzwanashe Mabhaudhi, Joel O. Botai, & Muthoni Masinde. (2023). A Systematic Review of Existing Early Warning Systems’ Challenges and Opportunities in Cloud Computing Early Warning Systems. Climate. 11(9). 188–188. 16 indexed citations
8.
9.
Masinde, Muthoni, et al.. (2021). An Analysis of Precipitation Extreme Events Based on the SPI and EDI Values in the Free State Province, South Africa. Water. 13(21). 3058–3058. 10 indexed citations
10.
Botai, Joel O., Christina M. Botai, Katlego P. Ncongwane, et al.. (2021). A Review of the Water–Energy–Food Nexus Research in Africa. Sustainability. 13(4). 1762–1762. 55 indexed citations
11.
Adisa, Omolola M., Muthoni Masinde, Joel O. Botai, & Christina M. Botai. (2020). Bibliometric Analysis of Methods and Tools for Drought Monitoring and Prediction in Africa. Sustainability. 12(16). 6516–6516. 30 indexed citations
12.
Botai, Christina M., et al.. (2019). Analysis of Drought Progression Physiognomies in South Africa. Water. 11(2). 299–299. 13 indexed citations
13.
14.
Masinde, Muthoni. (2017). Proceedings of the South African Institute of Computer Scientists and Information Technologists. 3 indexed citations
15.
Masinde, Muthoni, et al.. (2016). Adaptive Environmental Management System for Lejweleputswa District: A Participatory Approach Through Fuzzy Cognitive Maps. 1 indexed citations
16.
Masinde, Muthoni. (2015). MAS-DEWS: A multi-agent system for predicting Africa's drought. 4. 1–7. 1 indexed citations
17.
Masinde, Muthoni, et al.. (2014). Intelligent System For Predicting Agricultural Drought For Maize Crop. International Journal of Technology Enhancements and Emerging Engineering Research. 2(4). 51–54.
18.
Bagula, Antoine, et al.. (2010). A Middleware for Integrating Mobile Phone and Grid Computing; in the proceedings of the 6th International Conference on Network and Service Management (CNSM 2010), Niagra Falls Canada, Oc. 1 indexed citations
19.
Masinde, Muthoni & Antoine Bagula. (2010). A framework for predicting droughts in developing countries using sensor networks and mobile phones. 390–393. 13 indexed citations
20.
Masinde, Muthoni. (2006). Using JAD to Bridge the Design-Reality Gaps; a Major Cause of ISProjects’ Failures in the Developing Countries; in the proceedings of The 2 nd AnnualInternational Conference on Sustainable ICT Capacity in Developing Countries, MakerereUniversity, Kampala, Uganda 6 - 9 August 2006.. 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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