Paúl Muñoz

555 total citations
18 papers, 348 citations indexed

About

Paúl Muñoz is a scholar working on Global and Planetary Change, Atmospheric Science and Water Science and Technology. According to data from OpenAlex, Paúl Muñoz has authored 18 papers receiving a total of 348 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Global and Planetary Change, 9 papers in Atmospheric Science and 9 papers in Water Science and Technology. Recurrent topics in Paúl Muñoz's work include Flood Risk Assessment and Management (12 papers), Hydrology and Watershed Management Studies (9 papers) and Precipitation Measurement and Analysis (8 papers). Paúl Muñoz is often cited by papers focused on Flood Risk Assessment and Management (12 papers), Hydrology and Watershed Management Studies (9 papers) and Precipitation Measurement and Analysis (8 papers). Paúl Muñoz collaborates with scholars based in Ecuador, United States and Germany. Paúl Muñoz's co-authors include Rolando Célleri, Johanna Orellana‐Alvear, David F. Muñoz, Hamid Moradkhani, Hamed Moftakhari, Patrick Willems, Jörg Bendix, Jan Feyen, Gerald Corzo and Dimitri Solomatine and has published in prestigious journals such as The Science of The Total Environment, Water Resources Research and Remote Sensing.

In The Last Decade

Paúl Muñoz

15 papers receiving 338 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paúl Muñoz Ecuador 9 248 150 135 129 31 18 348
V. Bhanumurthy India 11 319 1.3× 137 0.9× 93 0.7× 115 0.9× 28 0.9× 20 422
Roberto Bentivoglio Netherlands 7 240 1.0× 138 0.9× 135 1.0× 106 0.8× 15 0.5× 9 305
Fabio Cian United States 8 302 1.2× 99 0.7× 88 0.7× 130 1.0× 39 1.3× 9 383
Amanda Markert United States 9 232 0.9× 124 0.8× 108 0.8× 114 0.9× 48 1.5× 15 351
Vinit Sehgal United States 12 350 1.4× 228 1.5× 260 1.9× 137 1.1× 20 0.6× 19 543
Sun‐Kwon Yoon South Korea 10 215 0.9× 105 0.7× 91 0.7× 108 0.8× 26 0.8× 46 292
Linda Speight United Kingdom 8 320 1.3× 198 1.3× 110 0.8× 142 1.1× 21 0.7× 24 421
Huabing Huang China 13 362 1.5× 150 1.0× 136 1.0× 236 1.8× 29 0.9× 27 478
Seree Supharatid Thailand 11 229 0.9× 123 0.8× 130 1.0× 107 0.8× 24 0.8× 23 363
Filsa Bioresita Indonesia 6 210 0.8× 92 0.6× 85 0.6× 83 0.6× 55 1.8× 36 300

Countries citing papers authored by Paúl Muñoz

Since Specialization
Citations

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

Fields of papers citing papers by Paúl Muñoz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paúl Muñoz

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

All Works

18 of 18 papers shown
1.
2.
Muñoz, Paúl, et al.. (2025). Advancing timely satellite precipitation for IMERG-ER using GOES-16 data and a U-net convolutional neural network modelling approach. Environmental Modelling & Software. 189. 106457–106457.
3.
Muñoz, Paúl, et al.. (2024). Enhancing Peak Runoff Forecasting through Feature Engineering Applied to X-Band Radar Data. Water. 16(7). 968–968. 3 indexed citations
4.
Célleri, Rolando, et al.. (2024). Precipitation forecasting using random forest over an ecuadorian andes basin. Meteorology and Atmospheric Physics. 137(1).
5.
Muñoz, Paúl, David F. Muñoz, Johanna Orellana‐Alvear, & Rolando Célleri. (2024). Enhancing runoff forecasting through the integration of satellite precipitation data and hydrological knowledge into machine learning models. Natural Hazards. 121(4). 3915–3937. 2 indexed citations
6.
7.
Muñoz, Paúl, Gerald Corzo, Dimitri Solomatine, Jan Feyen, & Rolando Célleri. (2022). Near-real-time satellite precipitation data ingestion into peak runoff forecasting models. Environmental Modelling & Software. 160. 105582–105582. 12 indexed citations
8.
Muñoz, Paúl, Gerald Corzo, Dimitri Solomatine, Jan Feyen, & Rolando Célleri. (2022). Near-Real-Time Satellite Precipitation Data Ingestion into Peak Runoff Forecasting Models. SSRN Electronic Journal. 1 indexed citations
9.
Muñoz, Paúl, David F. Muñoz, Johanna Orellana‐Alvear, et al.. (2021). Long Short-Term Memory Networks for Real-Time Runoff Forecasting using Remotely Sensed Data. 2 indexed citations
10.
Muñoz, David F., Paúl Muñoz, Atieh Alipour, et al.. (2021). Fusing Multisource Data to Estimate the Effects of Urbanization, Sea Level Rise, and Hurricane Impacts on Long-Term Wetland Change Dynamics. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 14. 1768–1782. 19 indexed citations
11.
Muñoz, Paúl, Johanna Orellana‐Alvear, Jörg Bendix, Jan Feyen, & Rolando Célleri. (2021). Flood Early Warning Systems Using Machine Learning Techniques: The Case of the Tomebamba Catchment at the Southern Andes of Ecuador. Hydrology. 8(4). 183–183. 16 indexed citations
12.
Orellana‐Alvear, Johanna, et al.. (2021). Influence of Random Forest Hyperparameterization on Short-Term Runoff Forecasting in an Andean Mountain Catchment. Atmosphere. 12(2). 238–238. 49 indexed citations
13.
Muñoz, David F., Paúl Muñoz, Hamed Moftakhari, & Hamid Moradkhani. (2021). From local to regional compound flood mapping with deep learning and data fusion techniques. The Science of The Total Environment. 782. 146927–146927. 92 indexed citations
14.
Orellana‐Alvear, Johanna, et al.. (2020). Assessment of Native Radar Reflectivity and Radar Rainfall Estimates for Discharge Forecasting in Mountain Catchments with a Random Forest Model. Remote Sensing. 12(12). 1986–1986. 17 indexed citations
15.
16.
Muñoz, Paúl, Johanna Orellana‐Alvear, Jörg Bendix, & Rolando Célleri. (2020). Comparison of Machine Learning Techniques Powering Flood Early Warning Systems. Application to a catchment located in the Tropical Andes of Ecuador.. 1 indexed citations
17.
Muñoz, Paúl, Johanna Orellana‐Alvear, Patrick Willems, & Rolando Célleri. (2018). Flash-Flood Forecasting in an Andean Mountain Catchment—Development of a Step-Wise Methodology Based on the Random Forest Algorithm. Water. 10(11). 1519–1519. 87 indexed citations
18.
Muñoz, Paúl, Rolando Célleri, & Jan Feyen. (2016). Effect of the Resolution of Tipping-Bucket Rain Gauge and Calculation Method on Rainfall Intensities in an Andean Mountain Gradient. Water. 8(11). 534–534. 32 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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2026