Petr Máca

1.2k total citations
37 papers, 878 citations indexed

About

Petr Máca is a scholar working on Global and Planetary Change, Water Science and Technology and Atmospheric Science. According to data from OpenAlex, Petr Máca has authored 37 papers receiving a total of 878 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Global and Planetary Change, 18 papers in Water Science and Technology and 13 papers in Atmospheric Science. Recurrent topics in Petr Máca's work include Hydrology and Watershed Management Studies (18 papers), Hydrology and Drought Analysis (18 papers) and Climate variability and models (16 papers). Petr Máca is often cited by papers focused on Hydrology and Watershed Management Studies (18 papers), Hydrology and Drought Analysis (18 papers) and Climate variability and models (16 papers). Petr Máca collaborates with scholars based in Czechia, United States and Germany. Petr Máca's co-authors include Martin Hanel, Yannis Markonis, Pavel Pech, Jan Kyselý, Rohini Kumar, Oldřich Rakovec, Luis Samaniego, Amir AghaKouchak, Adam Vizina and E. R. Cook and has published in prestigious journals such as Nature Communications, Scientific Reports and Science Advances.

In The Last Decade

Petr Máca

32 papers receiving 854 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Petr Máca Czechia	16	616	332	240	158	74	37	878
Chaolei Zheng China	17	650 1.1×	283 0.9×	222 0.9×	186 1.2×	190 2.6×	53	880
Changjie Lin China	8	556 0.9×	236 0.7×	155 0.6×	118 0.7×	78 1.1×	8	707
Ansoumana Bodian Senegal	18	777 1.3×	499 1.5×	157 0.7×	250 1.6×	77 1.0×	55	1.0k
Jianduo Li China	19	707 1.1×	332 1.0×	559 2.3×	317 2.0×	75 1.0×	42	1.1k
Xinguang He China	16	406 0.7×	168 0.5×	250 1.0×	238 1.5×	61 0.8×	53	736
Nikul Kumari Australia	14	446 0.7×	290 0.9×	132 0.6×	241 1.5×	182 2.5×	31	724
Munir Ahmad Nayak India	12	685 1.1×	198 0.6×	292 1.2×	95 0.6×	24 0.3×	24	824
Débora Regina Roberti Brazil	15	441 0.7×	138 0.4×	211 0.9×	238 1.5×	97 1.3×	93	686
Jiqun Zhang China	14	344 0.6×	258 0.8×	72 0.3×	123 0.8×	132 1.8×	42	736

Countries citing papers authored by Petr Máca

Since Specialization

Citations

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

Fields of papers citing papers by Petr Máca

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Petr Máca

This figure shows the co-authorship network connecting the top 25 collaborators of Petr Máca. A scholar is included among the top collaborators of Petr Máca 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 Petr Máca. Petr Máca 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

Pradhan, Rajani Kumar, K. C. Gouda, Laxmi Kant Sharma, et al.. (2025). Disaggregating IMERG satellite precipitation over Czech Republic: an innovative approach using hybrid Extreme Gradient Boosting based on Fuzzy Spatial-Temporal Multivariate Clustering. Journal Of Big Data. 12(1).

Máca, Petr, et al.. (2025). Combination of Hybrid Artificial Neural Networks with Particle Swarm Optimization Algorithm for SPEI Forecasting. Journal of Hydrometeorology. 26(11). 1775–1793.

Máca, Petr, et al.. (2025). Can causal discovery lead to a more robust prediction model for runoff signatures?. Hydrology and earth system sciences. 29(19). 4761–4790.

Langhammer, Jakub, et al.. (2024). Testing sensitivity of BILAN and GR2M models to climate conditions in the Gambia River Basin. Journal of Hydrology and Hydromechanics. 72(1). 131–147.

Máca, Petr, et al.. (2023). Hybrid multi-model ensemble learning for reconstructing gridded runoff of Europe for 500 years. Information Fusion. 97. 101807–101807. 12 indexed citations

Papacharalampous, Georgia, Hristos Tyralis, Yannis Markonis, Petr Máca, & Martin Hanel. (2023). Features of the Earth’s seasonal hydroclimate: characterizations and comparisons across the Köppen–Geiger climates and across continents. Progress in Earth and Planetary Science. 10(1). 2 indexed citations

Markonis, Yannis, et al.. (2023). Systematic analysis of the flash drought research: contribution, collaboration, and challenges. Theoretical and Applied Climatology. 154(3-4). 1203–1216. 2 indexed citations

Pech, Pavel, et al.. (2019). Evaluation of a pumping test with skin effect and wellbore storage on a confined aquifer in the Bela Crkva, Serbia. International Journal of Water. 13(1). 1–1. 1 indexed citations

Hanel, Martin, Oldřich Rakovec, Yannis Markonis, et al.. (2018). Revisiting the recent European droughts from a long-term perspective. Scientific Reports. 8(1). 9499–9499. 258 indexed citations

10.

Markonis, Yannis, Martin Hanel, Petr Máca, Jan Kyselý, & E. R. Cook. (2018). Persistent multi-scale fluctuations shift European hydroclimate to its millennial boundaries. Nature Communications. 9(1). 1767–1767. 49 indexed citations

11.

Hanel, Martin, et al.. (2017). Characteristics of rainfall events in regional climate model simulations for the Czech Republic. Hydrology and earth system sciences. 21(2). 963–980. 12 indexed citations

12.

Hanel, Martin, et al.. (2016). Characteristics of rainfall events in RCM simulations for the Czech Republic. 3 indexed citations

13.

Hanel, Martin, et al.. (2016). Projected changes of rainfall event characteristics for the Czech Republic. Journal of Hydrology and Hydromechanics. 64(4). 415–425. 22 indexed citations

14.

Máca, Petr, et al.. (2015). Parameter Estimation in Rainfall-Runoff Modelling Using Distributed Versions of Particle Swarm Optimization Algorithm. Mathematical Problems in Engineering. 2015. 1–13. 12 indexed citations

15.

Máca, Petr & Pavel Pech. (2015). The Inertia Weight Updating Strategies in Particle Swarm Optimisation Based on the Beta Distribution. Mathematical Problems in Engineering. 2015. 1–9. 8 indexed citations

16.

Máca, Petr, et al.. (2014). A Comparison of Selected Modifications of the Particle Swarm Optimization Algorithm. Journal of Applied Mathematics. 2014. 1–10. 26 indexed citations

17.

Hanel, Martin & Petr Máca. (2013). Spatial variability and interdependence of rain event characteristics in the Czech Republic. Hydrological Processes. n/a–n/a. 19 indexed citations

18.

Máca, Petr, et al.. (2012). A portable simulator for investigating rain-on-snow events. Zeitschrift für Geomorphologie. 57(1). 73–89. 7 indexed citations

19.

Hanel, Martin, et al.. (2012). A Multi-Model Assessment of Climate Change Impact on Hydrological Regime in the Czech Republic. Journal of Hydrology and Hydromechanics. 60(3). 152–161. 40 indexed citations

20.

Máca, Petr. (2003). 8. Movement of Rainfall Events in Prague Area. Tunnelling and Underground Space Technology. 14(1). 8–8. 2 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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