John Ndiritu

731 total citations
38 papers, 522 citations indexed

About

John Ndiritu is a scholar working on Water Science and Technology, Global and Planetary Change and Civil and Structural Engineering. According to data from OpenAlex, John Ndiritu has authored 38 papers receiving a total of 522 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Water Science and Technology, 17 papers in Global and Planetary Change and 13 papers in Civil and Structural Engineering. Recurrent topics in John Ndiritu's work include Hydrology and Watershed Management Studies (17 papers), Flood Risk Assessment and Management (12 papers) and Water Systems and Optimization (11 papers). John Ndiritu is often cited by papers focused on Hydrology and Watershed Management Studies (17 papers), Flood Risk Assessment and Management (12 papers) and Water Systems and Optimization (11 papers). John Ndiritu collaborates with scholars based in South Africa, Kenya and Australia. John Ndiritu's co-authors include Trevor Daniell, J. P. Maree, Vhahangwele Masindi, John O. Odiyo, Rachel Makungo, Spyros Foteinis, Memory Tekere, Efthalia Chatzisymeon, Phil Renforth and Akpofure E. Taigbenu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Hydrology and earth system sciences.

In The Last Decade

John Ndiritu

34 papers receiving 490 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Ndiritu South Africa 11 281 171 169 97 81 38 522
Y. Jeffrey Yang United States 12 300 1.1× 122 0.7× 143 0.8× 55 0.6× 194 2.4× 24 569
Mengistu Geza United States 13 350 1.2× 192 1.1× 238 1.4× 91 0.9× 47 0.6× 33 578
Masoud Taheriyoun Iran 13 277 1.0× 123 0.7× 109 0.6× 59 0.6× 63 0.8× 39 499
Tianyu Long China 13 362 1.3× 77 0.5× 149 0.9× 244 2.5× 88 1.1× 33 694
Faisal Anwar Australia 13 130 0.5× 118 0.7× 252 1.5× 32 0.3× 87 1.1× 66 498
Anatoli Vassiljev Estonia 13 169 0.6× 70 0.4× 105 0.6× 132 1.4× 185 2.3× 50 466
Haorui Chen China 15 170 0.6× 120 0.7× 238 1.4× 31 0.3× 157 1.9× 53 635
Malik Al-Wardy Oman 15 231 0.8× 127 0.7× 144 0.9× 13 0.1× 69 0.9× 58 630
P. Sundarambal Singapore 9 318 1.1× 102 0.6× 376 2.2× 55 0.6× 20 0.2× 20 688
Sayed Farhad Mousavi Iran 13 306 1.1× 180 1.1× 158 0.9× 12 0.1× 99 1.2× 22 713

Countries citing papers authored by John Ndiritu

Since Specialization
Citations

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

Fields of papers citing papers by John Ndiritu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Ndiritu

This figure shows the co-authorship network connecting the top 25 collaborators of John Ndiritu. A scholar is included among the top collaborators of John Ndiritu 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 John Ndiritu. John Ndiritu 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.
Ndiritu, John, et al.. (2025). Sorghum yield prediction based on remote sensing and machine learning in conflict affected South Sudan. Scientific Reports. 15(1). 4469–4469. 3 indexed citations
2.
3.
Ndiritu, John, et al.. (2024). Class Prediction of High-Dimensional Data with Class Imbalance: Breast Cancer Gene Expression Data. International Journal of Advances in Scientific Research and Engineering. 10(11). 28–46.
4.
5.
Ndiritu, John, et al.. (2023). Socio-hydrological modelling for incorporating human behaviour into storage–yield analysis. Hydrological Sciences Journal. 68(16). 2435–2448. 1 indexed citations
6.
Ogero, Morris, et al.. (2023). Pediatric prognostic models predicting inhospital child mortality in resource‐limited settings: An external validation study. Health Science Reports. 6(8). e1433–e1433. 3 indexed citations
7.
Ogero, Morris, et al.. (2023). Recalibrating prognostic models to improve predictions of in‐hospital child mortality in resource‐limited settings. Paediatric and Perinatal Epidemiology. 37(4). 313–321. 3 indexed citations
8.
Masindi, Vhahangwele, Spyros Foteinis, Phil Renforth, et al.. (2022). Challenges and avenues for acid mine drainage treatment, beneficiation, and valorisation in circular economy: A review. Ecological Engineering. 183. 106740–106740. 105 indexed citations
9.
Ndiritu, John, et al.. (2021). Modelling and assessing the impact of illegal water abstractions by upstream farmers on reservoir performance. DergiPark (Istanbul University). 2(2). 47–54. 1 indexed citations
10.
Makungo, Rachel, John O. Odiyo, & John Ndiritu. (2021). Hydraulic characteristics of a fractured crystalline basement aquifer in Nzhelele area, Limpopo Province, South Africa. Cogent Engineering. 8(1). 3 indexed citations
11.
Ndiritu, John, et al.. (2018). Guidelines for rainwater harvesting system design and assessment for the city of Johannesburg, South Africa. SHILAP Revista de lepidopterología. 379. 409–414. 1 indexed citations
12.
Ndiritu, John. (2013). Incorporating rainfall uncertainty into catchment modelling. Journal of the South African Institution of Civil Engineering. 55(3). 36–46. 1 indexed citations
13.
Ndiritu, John. (2013). Using data-derived perturbations to incorporate uncertainty in generating stochastic areal rainfall from point rainfall. Hydrological Sciences Journal. 58(8). 1704–1717. 4 indexed citations
14.
Onema, Jean‐Marie Kileshye, Akpofure E. Taigbenu, & John Ndiritu. (2012). Classification and flow prediction in a data-scarce watershed of the equatorial Nile region. Hydrology and earth system sciences. 16(5). 1435–1443. 10 indexed citations
15.
Ndiritu, John. (2011). A variable-length block bootstrap method for multi-site synthetic streamflow generation. Hydrological Sciences Journal. 56(3). 362–379. 8 indexed citations
16.
Ndiritu, John, et al.. (2009). The simple modelling method for storm- and grey-water quality management applied to Alexandra settlement. Water SA. 35(5). 3 indexed citations
17.
Ndiritu, John, et al.. (2009). A fuzzy inference system for modelling streamflow: Case of Letaba River, South Africa. Physics and Chemistry of the Earth Parts A/B/C. 34(10-12). 688–700. 28 indexed citations
18.
Ndiritu, John. (2005). Long-term trends of heavy rainfall in South Africa.. IAHS-AISH publication. 1(6). 178–183. 7 indexed citations
19.
Ndiritu, John & Trevor Daniell. (2001). An improved genetic algorithm for rainfall-runoff model calibration and function optimization. Mathematical and Computer Modelling. 33(6-7). 695–706. 45 indexed citations
20.
Ndiritu, John, et al.. (1999). Assessing model calibration adequacy via global optimisation. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 4 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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