Gerald Augusto Corzo Perez - Senior ICT and Water Resources Engineer Hydroinformatics and socio-technological innovations - IHE Delft
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Gerald Augusto Corzo Perez Senior ICT and Water Resources Engineer Hydroinformatics and socio-technological innovations Profile Dr Gerald A. Corzo is a senior researcher with extensive knowledge on ICT and its applications water resources problems. Civil engineering with studies in teleinformatics, master and PhD in hydroinformatics applications using machine learning models. Postdoctoral experience using Big Data analytics for Climate Change extremes at Wageningen University. His primary areas of expertise are in hybrid machine learning and process-based modelling. Have worked in spatiotemporal analysis of extreme events under climate change scenarios, and have contributed to the area of pattern recognition and tracking of extremes. Has more than 40 high impact journal publications, various book chapters, journal special issues and book editorials. In 2012 won the Tison award as from the International Association for Hydrological Science (IAHS). Participated in various EU and international projects. Has developed a trajectory in spatial statistics, lecturing and 9 years as convener of the geostatistics session at the European Geoscience Union. Coordinated the statistics of the Climate change inventory of adaptation and mitigation actions for Latin- America, presented at the World Water Forum in 2012. Wrote the report 43 on future extremes from the WATCH EU forcing data set and a big data analysis of the Climate model scenarios. In 2020 coordinated the analysis of climate change for the national atlas of climate change in the Dominican Republic. Currently focused on AI and spatiotemporal analysis of socio technological and water resources problems. One of his recent projects focuses on Natural processing language for understanding and finding causation of decision making from cloud data. Part of the development in the area of data collection use of citizens science and mobile teechnologies. As part of the concept of citizens involvement an “intelligent” serious games was developed to collect data and explore knowledge and behaviour in citizens. As project leader, lecturer and research supervisor had the opportunity to cooperate with institutes around the world, building a large network for science and development cooperation. Professional Experience Period: 2013-Current Associate Professor, Senior Researcher, Lecturer (IHE Delft Institute for Water Education (UNESCO- IHE), Delft, The Netherlands Achievements: Development of online modelling tools for the use of students abroad, director of the hydroinformatics lab, acquisition and leader of projects, courses in Colombia, Bolivia, Ecuador, Costa Rica, Nicaragua, Dominican Republic, Mexico and USA. Part of the scientific advisor of the committee for the PRIMA 2020 EU project, Support to the Colombian Plan for adaptation in Climate Change, Projects acquisition in Flood forecasting with the National research agency in Dominican Republic and Salvador, Spatial data-infrastructures in Colombia. UTQ from Technical University of Delft. Various MSc, PhD co-promotion and supervision. Ambassador of the IHE Delft institute for Mexico until 2018. Development of two international Master of Science programs and one NSF AI cooperation project with the University of Nebraska (USA). Two book editions, one in 2019 and one in 2021, two special editions one on geostatistics and one on spatiotemporal extremes.
Period: 2011-2013 Research professor, Tecnologico de Monterrey , Monterrey, Mexico Achievements: Team leader for the group of the statistics of inventory on adaptation to climate change in the Americas, for the World Water Forum (Marseille, 2012). This work included the design of a platform for international interactions as well as being part of the editorial team of the book of strategies for climate change actions (cooperation with CONAGUA Mexico).Coordinator and developer of the first international network for research scientists in Latinoamerica, Red Latina del Agua (Aqua Latina) Period: 2009-2011 Postdoc researcher, Wageningen University, Wageningen, The Netherlands Achievements: WATCH-EU report 43 on future drought and climate change Period: 2005-2009 PhD research fellow and Server Manager of the Hydroinformatics group, UNESCO-IHE, Delft, The Netherlands Achievements: Management of Delft Cluster project task Safety against flood, W.P. 3. Supervision and support of Master of Science on different projects. Web server manager and ICT support on hydrological workshops and exercises on database information and knowledge management Period: 2000-2003 Lecturer , Universidad Francisco de Paula Santander, Cúcuta, Colombia Achievements: Project in partnership for National Colombian Science Institute, project Waves, COLCIENCIAS (Governmental National Science Organization) 2002-2003 Education Period: 2009-2011 Postdoctoral, Wageningen University, The Netherlands Supervisor(s): Henny van Lanen Period: 2005-2009 Doctor of Philosophy, Technical University of Delft and UNESCO-IHE, The Netherlands Supervisor(s): Dimitri Solomatine, Stefan Uhlenbrook, Micha Werner and Marcel de Wit Period: 2003-2005 Master of Science in Water Resources, specialisation in Hydroinformatics, UNESCO-IHE, The Netherlands Supervisor(s): Dimitri Solomatine Period: 2001-2003
Specialisation in Teleinformatics, Universidad Distrital Francisco Jose de Caldas, Colombia Supervisor(s): Alberto Acosta Period: 1992-1998 Civil Engineer, Escuela Colombiana de Ingeniería, Colombia Supervisor(s): Ing. Manuel Delgado Vargas As a trainer in Capacity Building programmes Date 02/2021, ICT Tools for water resources and food security, Escuela Colombiana de Ingenieria and IHE Delft Institute for water education. Netherlands funded training project (OKP) Date 09/2020, Geostatistics for water and enviromental sciences, IHE Delft Institute for water Education. Netherlands funded training project. Date 06/2020, Analysis of Hydrological extremes events from global data sets, Escuela Colombiana de Ingenieria, Online – Jun, Colombia. Date 03/2020, Introduction to Machine learning for water resources at the Civil Engineering Faculty, University of Campina, Campinas, Brazil. Date 03/2019, Workshop on Introduction to Hydroinformatics applied to Machine Learning applied to extreme hydrological events at the Universidad de Cochabamba, May, Cochabamba, Bolivia. Date 08/2018, Workshop on mobile technologies for data acquisition at the Center for agriculture in Central America (CATIE), July, Turrialba, Costa Rica. Date 08/2017, Advance hydrological tools for water resources and food security, UNAN, November, Managua, Nicaragua Date 08/2017, Modelos de gestión integrada de recursos hídricos, Universidad Nacional, August, Liberia , Costa Rica Date 05/2017, Uso de redes neuronales para la predicción hidrometeorológica, Pontificia Universidad Madre y Maestra, June, Santo Domingo, Dominican Republic Date 06/2018, Training on climate change analysis of extreme hydrological events, Escuela Colombiana de ingeniería, July, Bogotá, Colombia Date 06/2017, Training on climate change analysis of extreme hydrological events, Escuela Colombiana de ingeniería, June, Bogotá, Colombia Date 06/2016, Training on climate change analysis of extreme hydrological events, Escuela Colombiana de ingeniería, June, Bogotá, Colombia Date 03/2015, Training on Advance hydrological modelling, Universidad de Veracruz, March, Xalapa, México Date 06/2015, Training on climate change analysis of extreme hydrological events, Escuela Colombiana de ingeniería, June, Bogotá, Colombia
Date 28/015, Training on Decision support systems for water resource management, module on multicriteria analysis, November, Universidad del Valle, Calí, Colombia Date 06/2014, Training on climate change analysis of extreme hydrological events, Escuela Colombiana de ingeniería, June, Bogotá, Colombia Date 07/2011, International Workshop on climate change for decision makers, National University (UNA), March, San Jose, Costa Rica Date 06/2012, Workshop on climate change and water reuse in the context of Integrated water resources management, Faculty of Engineering, April, Cooperative University of Colombia, Villavicencio, Colombia Date 03/2010, Workshop on classification and error analysis of spatial patterns, Faculty of Hydrology and quantitative water management, September, Wageningen University, Wageningen, The Netherlands Awards or fellowships Year 2012, Tison Award, best Publication in Hydrological Science Journal from IAHS. Young scientist award from the International association of Hydrological Sciences, Paper on Rainfall interception-evaporation-runoff relationships in a semi-arid catchment in Zimbawe Year 2012, Award of National System of Researchers Level 1, from the Mexican Council of Science (CONACYT) Year 2010, Scholarship. Course in Classification in atmospheric sciences, University of Augsburg, Germany Year 2008, Scholarship Boussinesq, Advanced methods in experimental hydrology, Luxemburg, Lipman Institute, Luxemburg Year 2005, Delft Cluster Scholarship, The Netherlands Year 2003, Netherlands Fellowship Programme, Nuffic, The Netherlands Research Projects 2021-2024 CLINT, Climate Intelligent Forecast, AI tools for forecasting mid-term water resources. Package on forecasting extremes. Donor: EU, H2020 2020-2022 NAIDES, Smat Water management for sustainable development goal, natural processing languague component. Donor: H2020 2016-2022 Machine learning research for analysis of extremes and forecasting, funds for 5 PhD candidates. Donor: Colciencias (Colombian Science Agency). PL 2019-2021, Sustainable Managed Mediterranean Aquifer recharg, Development of models and spatiotemporal patterns of groundwater recharge for climate change scenarios. Donor: Prince Albert II foundation. PL 2019-2021 Analysis of patterns in droughts and nature based solutions surrogate representations, funds for 2 PhD, Donor: CONACYT (Mexican Agency for Science). PL
2016-2020, HybridModels, Dominican Republic analysis of hybrid machine learning models in operational forecasting for the Yuna river basin (transfer learning from using convolutional LSTM). Donor: SENACYT. PL 2016-2020, Atlas for Climate change analysis from Meteorological variables for the Dominican Republic Donor: INDRHI (Water ministry) and Pontificia Universidad Madre y Maestra. PL 2016-2017, IGRAC-Platform Development, algorithms and python scripts for online time series forecasting of groundwater. Donor: IGRAC. PL 2016-2017, Dam uncertainty, development of machine learning models for the analysis of real-time dam structures uncertainties from monitoring stress. Donor: Polygol. PL 2015-2018, Engineering Informed Decision Making, Development of a knowledge platform to forecast and integrate real time information for the state of Nebraska in USA. Donor: US drought Doherty Foundation. PL 2014-2020, DUPC-SDI, Smultistor, Optimal Reservouir operation and analysis of enviromental and agricultural systems, Donor: Dutch Government – Colombia. PL 2020, IGRAC South African Spatial Data Infrastructure, Development of algorithms and scripts for online time series forecasting add in for Geonode. Donor:IGRAC PL 2014-2018, DUPC-SDI, Development of UNESCO-IHE Spatial Data Infrastructure system, Donor: Dutch Government. PL 2005-2009, Work package 3 researcher and administrator. Main topic: Safety against flood. Building Hybrid Hydrological and data driven models for operational forecasting systems. Donor: Delft Cluster 2008-2009, Floodsite, Training and support on the creation of the platforms 2009-2011, WATCH-EU, Work package 4, drought analysis and floods from global hydrological models 2011-2012, CAP-NET, Cours on water reuse optimisation, Capacity building in Colombia, 2013-2014, Climacol, Climate change analysis in the Magdalena (Colombia) 2011-2012, LatinAqua, Latinoamerican network of water resources research 2011-2012, Forecast Santa Catalina, Flow forecasting prototype design for the city of Monterrey in Mexico 2013-2014, Kulturisk, Development of a knowledge platform and a database for flood risk management 2014-2015, ICE Water, Development of an online system for sharing multimedia information Academic activities Geo-statistics for space time analysis of extremes, the European Geoscience Union., Session Chair, (2012-2020)
Special Issue “Spatio-temporal and geostatistical analysis of hydrological events and related hazards”, Spatial Statistics, Elsevier, Guest Editor, 2017 Special Issue "Spatiotemporal Data Analysis, Visualization, and Modelling in Water Resources", Marine Science and Engineering, MDPI, Guest Editor, 2020 Hydrological Sciences Journal, IAHS, Taylor and Francis., Reviewer since, 2007 Journal of Hydrology, Elsevier., Reviewer since, 2007 Hydrological and Earth Science System (HESS), EGU., Reviewer since, 2008 International Joint conference 0n Neural Networks, IEEE division on Computational Intelligence, Reviewer since, 2007 Environmental software and Modeling, Elsevier., Reviewer, since 2007 Languages Spanish: Native English: Strong Dutch: Basic ICT Skills Compilers: Pascal, Java, C++, Visual Basic and C Scripting languages: Python, MATLAB, R, Javascript, Php, VBA Script Developments environments: VSCode, GoogleCollab, Delphi, Borland, Visual Studio, MATLAB, RStudio, ANACONDA, SPYDER Other technologies: HTML, XML, COM/ACTIVEX. ISAPI, AJAX, Google KML Engineering Software: SOBEK, Delft 3d WQ, Mike Software (DHI), SWMM, EPANET, HECRAS Operating Systems: Windows, Linux (Ubuntu – Centos – Server Level), iOS Office tools: GDocs, MS Office, Prezi, Visio, Microsoft Project, others
Journal publications
In 2019
1. Dahm, R., Bhardwaj, A., Sperna Weiland, F., Corzo, G., & Bouwer, L. M. (2019). A
Temperature-Scaling Approach for Projecting Changes in Short Duration Rainfall
Extremes from GCM Data. Water, 11(2), 313.
a. Doi: https://doi.org/10.3390/w11020313
2. Amaranto, A., Munoz-Arriola, F., Corzo, G., Solomatine, D. P., and Meyer, G., A
Spatially enhanced data-driven multi-model to improve semi-seasonal
groundwater forecasts in the High Plains aquifer, USA, Water Resources Research,
2019
Doi: https://doi.org/10.1029/2018WR024301
3. Alessandro Amaranto, Francesca Pianosi, Dimitri Solomatine, Gerald Corzo, Francisco
Munoz-Arriola (2019). Sensitivity Analysis of Data-driven Groundwater Forecast to
Hydroclimatic Controls in Irrigated Croplands. Hydrology and Earth System Sciences,
under review.
Doi: https://doi.org/10.2166/hydro.2018.002
4. E.A Varouchakis, D.T. Hristopulos, G.B.M., Heuvelink, G.A. Corzo Perez, "Spatio-
temporal statistical methods for the analysis of hydrological events and related hazards".
Spatial Statistics 34, 100387, 2019.
Doi: https://doi.org/10.1016/j.spasta.2019.100387
In 2020
1. Diaz, V., Corzo Perez, G. A., Van Lanen, H. A. J., Solomatine, D., & Varouchakis, E.
A. (2020). Characterisation of the dynamics of past droughts. Science of the Total
Environment, 718. https://doi.org/10.1016/j.scitotenv.2019.134588.
2. Ritter, J., Corzo, G., Solomatine, D. P., & Angarita, H. (2020). Multiobjective Direct
Policy Search Using Physically Based Operating Rules in Multireservoir Systems.
Journal of Water Resources Planning and Management.
https://doi.org/10.1061/(ASCE)WR.1943-5452.0001159
3. Valles, J., Corzo, G., & Solomatine, D. (2020). Impact of the Mean Areal Rainfall
Calculation on a Modular Rainfall-Runoff Model. Journal of Marine Science and
Engineering, 8(12), 980. https://doi.org/10.3390/jmse8120980
4. Amaranto, A., Pianosi, F., Solomatine, D., Corzo, G., & Muñoz-Arriola, F. (2020).
Sensitivity analysis of data-driven groundwater forecasts to hydroclimatic controls in
irrigated croplands. Journal of Hydrology, 587, 124957.
https://doi.org/10.1016/j.jhydrol.2020.124957
5. Laverde-Barajas, M., Corzo, G. A., Poortinga, A., Chishtie, F., Meechaiya, C.,
Jayasinghe, S., ... & Solomatine, D. P. (2020). St-corabico: A spatiotemporal object-
based bias correction method for storm prediction detected by satellite. Remote
Sensing, 12(21), 3538. https://doi.org/10.3390/rs12213538
6. Diaz, V., Perez, G. A. C., Van Lanen, H. A., Solomatine, D., & Varouchakis, E. A.
(2020). An approach to characterise spatio-temporal drought dynamics. Advances in
Water Resources, 137, 103512. https://doi.org/10.1016/j.advwatres.2020.103512
7. Uribe, N., Srinivasan, R., Corzo, G., Arango, D., & Solomatine, D. (2020). Spatio-
temporal critical source area patterns of runoff pollution from agricultural practices inthe Colombian Andes. Ecological Engineering, 149, 105810.
https://doi.org/10.1016/j.ecoleng.2020.105810
In 2021
1. Varouchakis, E. A., Hristopulos, D. T., Karatzas, G. P., Corzo Perez, G. A., & Diaz, V.
(2021). Spatiotemporal geostatistical analysis of precipitation combining ground and
satellite observations. Hydrology Research. https://doi.org/10.2166/nh.2021.160
Previous years
Corzo, G. and D. Solomatine. Knowledge-based modularization and global optimization of artificial neural
network models in hydrological forecasting. Journal of Neural Networks, 20:528–536, 2007.
Corzo, G. A. and D. P. Solomatine. Baseflow separation techniques for modular artificial neural networks
modelling in flow forecasting. Hydrological Sciences Journal, 52(3):491–507, 2007.
M. K. Akhtar, Corzo, G. A., S. J. van Andel, and A. Jonoski. River flow forecasting with artificial neural networks
using satellite observed precipitation pre-processed with flow length and travel time information: case study of the
ganges river basin. Hydrology and Earth System Sciences, 13(9):1607–1618, 2009.
Corzo G. A., Solomatine D. P., Hidayat, de Wit M., Werner M., Uhlenbrook S., and Price R. K. Combining semi-
distributed process-based and data-driven models in flow simulation: a case study of the meuse river basin.
Hydrology and Earth System Sciences, 13(9):1619–1634, 2009.
A. Elshorbagy, Corzo, G., S. Srinivasulu, and D. P. Solomatine. Experimental investigation of the predictive
capabilities of data driven modeling techniques in hydrology - part 1: Concepts and methodology. Hydrology and
Earth System Sciences, 14(10):1931–1941, 2010.
A. Elshorbagy, Corzo, G., S. Srinivasulu, and D. P. Solomatine. Experimental investigation of the predictive
capabilities of data driven modeling techniques in hydrology - part 2: Application. Hydrology and Earth System
Sciences, 14(10):1943–1961, 2010.
D. Love, S. Uhlenbrook, G. Corzo-Perez, and S. Twomlow. Rainfall-interception-evaporation-runoff relationships
in a semi-arid catchment, northern limpopo basin, zimbabwe. Hydrological Sciences Journal, 55(5), 2010.
K. Kuntiyawichai, B. Schultz, S. Uhlenbrook, F.X. Suriyadi, and Corzo Perez, G. A. Comprehensive flood
mitigation and management in the chi river basin, thailand. Lowland Technology International, 13(1):10–18,
2011.
Corzo Perez, G. A., M. H. J. van Huijgevoort, F. Voß, and H. A. J. van Lanen. On the spatio-temporal analysis of
hydrological droughts from global hydrological models. Hydrology and Earth System Sciences Discussions,
8(1):619–652, 2011
Hong Li, Gerald A. Corzo Perez, Carlos A. Martinez, Arthur E. Mynett. (2013) Self-Learning Cellular Automata
for Forecasting Precipitation from Radar Images. Journal of Hydrologic Engineering 18, 206-211. Online
publication date: 1-Feb-2013.
Minaya V., Corzo G., Romero, H., van der Kwast J., Latinga, E., Mynett A. (2014) Altitudinal analysis of carbon
stocks in the Antisana páramo, Ecuadorian Andes.Journal of Plant Ecology 9 (2016)5. - ISSN 1752-9921 - p. 553
- 563.
Minaya V., Corzo G., van der Kwast J., Galarraga-Sanchez, R., Mynett A. (2014) Classification and multivariateerror analysis of gross primary production simulation with BIOME-BGC in the páramos; Ecuadorian Andean Region. Revista de Matemática Teoría y Aplicaciones, Print version ISSN 1409-2433 Minaya V., Corzo G., van der Kwast J., Galarraga-Sanchez, R., Mynett A, Simulating gross primary production and stand hydrological processes of páramo grasslands in the Ecuadorian Andean Region using the BIOME-BGC model, Soil Science: July 2016 - Volume 181 - Issue 7 - p 335–346, doi: 10.1097/SS.0000000000000154 Varouchakis, Emmanouil A.; Spanoudaki, Katerina; Hristopulos, Dionissios T.; Karatzas, George P.; Corzo Perez, Gerald A, Stochastic Modeling of Aquifer Level Temporal Fluctuations Based on the Conceptual Basis of the Soil-Water Balance Equation, June 2016 - Volume 181 - Issue 6 - p 224–231, doi: 10.1097/SS.0000000000000157 Veronica Minaya and Gerald A. Corzo and Dimitri P. Solomatine and Arthur E. Mynett, Data-driven techniques for modelling the gross primary production of the páramo vegetation using climate data: Application in the Ecuadorian Andean region, 2016, pg 1574-9541, Ecological Informatics Moura Mikhaeil, Gerald Corzo, Islam Abou El-Magd, Model-based evaluation of structural measures impact on the inundation area of Wadi driven flash floods, Volume 03 Issue 08 (August 2016) Joanne Craven, Hector Angarita, G.A. Corzo Perez, Daniel Vasquez, Development and testing of a river basin management simulation game for integrated management of the Magdalena-Cauca river basin, Environmental Modelling & Software, Volume 90, April 2017, Pages 78-88, ISSN 1364-8152, http://dx.doi.org/10.1016/j.envsoft.2017.01.002. Reem F. Digna, Y. A. Mohamed, P. van der Zaag, S. Uhlenbrook, and G. A. Corzo, (2017) Nile River Basin modelling for water resources management - a literature review, International Journal Of River Basin Management Vol. 15, Iss. 1,2017 A Jeuken, L Bouaziz, G Corzo, L Alfonso (2016). Analyzing Needs for Climate Change Adaptation in the Magdalena River Basin in Colombia. Journal of Climate Change Adaptation, Resilience and Hazards, 329-344 Impact of Water Resources Development on Water Availability for Hydropower Production and Irrigated Agriculture of the Eastern Nile Basin Reem F. Digna; Yasir A. Mohamed; Pieter van der Zaag; Stefan Uhlenbrook; Wil van der Krogt; and Gerald Corzo (2018). Volume 144 Issue 5 - May 2018 Spatio-temporal analysis of annual rainfall in Crete, Greece, Varouchakis, E.A., Corzo, G.A., Karatzas, G.P. et al. Acta Geophys. (2018). https://doi.org/10.1007/s11600-018-0128-z Spatiotemporal Hydrological Analysis, Corzo PGA, Diaz V, Laverde M (2018) Spatiotemporal Hydrological Analysis. Int J Hydro 2(1): 00045. DOI: 10.15406/ijh.2018.02.00045 Digna, R.F.; Castro-Gama, M.E.; van der Zaag, P.; Mohamed, Y.A.; Corzo, G.; Uhlenbrook, S. Optimal Operation of the Eastern Nile System Using Genetic Algorithm, and Benefits Distribution of Water Resources Development. Water 2018, 10, 921. Yalina Montecelos-Zamora, Tereza Cavazos, Thomas Kretzschmar, Enrique R. Vivoni, Eugenio Molina-Navarro, Gerald Corzo (2018). Hydrological Modelling of Climate Change Impacts in a Tropical River, Basin: A Case Study of the Cauto River, Cuba. Water 2018, In press. Uribe, N., Corzo, G., Quintero, M., van Griensven, A., & Solomatine, D. (2018). Impact of conservation tillage on nitrogen and phosphorus runoff losses in a potato crop system in Fuquene watershed, Colombia. Agricultural Water Management, 209, 62-72. Amaranto, A., Munoz-Arriola, F., Corzo, G., Solomatine, D. P., and Meyer, G. (2018). Semi-seasonal groundwater forecast,using multiple data-driven models in an irrigated cropland. Journal of
Hydroinformatics, jh2018002.
1.
Conference publications
D. P. Solomatine and Corzo, G. A. Learning hydrologic flow separation algorithm and local ann committee
modelling. In IJCNN 06. International Joint Conference on Neural Networks, pages 5104 – 5109, Vancouver,
2006.
Corzo, G. A. and D. P. Solomatine. Optimization of base flow separation algorithm for modular data-driven
hydrologic models. In 7th International Conference on Hydroinformatics, Nice, FRANCE, 2006. Research
Publishing Services.
Corzo, G. A. and Hong Li. Ensemble of model trees and neural network for forecasting models. In IJCNN 07.
International Joint Conference on Neural Networks, pages Poster presentation - International competence on
forecasting, Orlando, USA, 2007.
Corzo, G. A., A. Jonoski, G. Yimer, Y. Xuan, and D. Solomatine. Downscaling global climate models using
modular models and fuzzy committees. In SheiYui Liong, editor, 8th international conference on
hydroinformatics, Concepcion Chile, 2009. World Scientific Publishing Company.
D. Love, S. Uhlenbrook, G. Corzo-Perez, and S. Twomlow b. Semidistributed modelling of rainfallrunoff
relationships in a small semi-arid catchment, northern limpopo basin, zimbabwe. In UNESCO/WMO Small Basin
Workshop, Goslar Hahnenklee, Germany, March 2009.
K. Kuntiyawichai, B. Schultz, S. Uhlenbrook, F.X. Suriyadi, and G. Corzo. Comprehensive flood mitigation and
management in the chi river basin, thailand. In International Symposium on Lowland Technology (ISLT 2010),
Theme: Water/Environmental Engineering, Sept, 2010.
H Li, C Martinez, Corzo G.A., and A. Mynnet. Selflearning cellular automata for forecasting precipitation from
radar images. In SheiYui Liong, editor, 9th international conference on hydroinformatics, Tianjin China, Sept,
2010. World Scientific Publishing Company.
Corzo, G. A., W Barreto, D. Love, and S Uhlenbrook. Hbvx: A semidistributed hydrological modelling tool with
multicriteria calibration. In SheiYui Liong, editor, 9th international conference in hydroinformatics, Tianjin
China, Sept, 2010. World Scientific Publishing Company.
M Laverde-Barajas, A Pedrozo Acuña, A Breña-Naranjo & G Corzo-Perez, The rolde of hydrological
uncertainties in flood risk analysis: Tonala river, Mexico, ICFM6, 2014, DOI: 10.13140/2.1.4844.1600 ·
S. S. Putra, G. A. Corzo Perez, S. van der Pijl, H. Kernkamp, A. van Dam and D. P. Solomatine, Measuring
domain decomposition effect in estuary model parallelization using high performance computer, 2014 6th
International Conference on Information Technology and Electrical Engineering (ICITEE), Yogyakarta, 2014, pp.
1-6. doi: 10.1109/ICITEED.2014.7007908
Diaz-Mercado V., Corzo G., Solomatine D. (2015). A framework for regional and global long-term and middle-
term assessment of floods and droughts under an approach of computational intelligence linking Earth
observation, global climate and hydrological models. Proc. of the 36th IAHR World Congress, The Hague, The
Netherlands. ISBN 978-90-824846-0-1. http://89.31.100.18/~iahrpapers/97467.pdfSpatio-temporal Analysis of Hydrological Drought at Catchment Scale Using a Spatially-distributed Hydrological
Model, Vitali Diaz Mercado, Gerald Corzo Perez, Dimitri Solomatine, Henny A.J. van Lanen, Procedia
Engineering, Volume 154, 2016, Pages 738-744, ISSN 1877-7058,
http://dx.doi.org/10.1016/j.proeng.2016.07.577
Meteorological Drought Forecasting Based on Climate Signals Using Artificial Neural Network – A Case Study
in Khanhhoa Province Vietnam, Manh Hung Le, Gerald Corzo Perez, Dimitri Solomatine, Luong Bang Nguyen,
Procedia Engineering, Volume 154, 2016, Pages 1169-1175, ISSN 1877-7058,
http://dx.doi.org/10.1016/j.proeng.2016.07.528
Diaz-Mercado V., Corzo G., van Lanen H.A.J., Solomatine D. (2016). Spatio-temporal analysis of large-scale
meteorological drought: Helping to achieve the SDGs 6.A and 11.5. 12th Kovacs Colloquium, Paris, France.
Manh Hung Le, Gerald Corzo Perez, Vicente Medina and Dimitri Solomatine,(2017), Studying the Impact of
Infilling Techniques on Drought Estimation – a Case Study in the South Central Region of Vietnam, ICIST 2017
paper 51
Books
Hybrid models for Hydrological Forecasting: integration of data-driven and conceptual modelling technique,
2009, ISBN: 9780415565974
Hydrology and Best Practices for Managing Water Resources in Arid and Semi-Arid Lands, Chapter, Infrastructures for data
in the context of flow forecasting using Artificial Neural Network model for Okavango River in Namibia, 2017, SBN13:
9781522527190|ISBN10: 1522527192|EISBN13: 9781522527206|DOI: 10.4018/978-1-5225-2719-0
Spatio-temporal Analysis of Extreme Hydrological Events, Elsevier, 2018, Paperback ISBN: 9780128116890
Book chapters
1. Vitali Diaz, Gerald A. Corzo Perez, Henny A.J. Van Lanen, Dimitri Solomatine, 2018,
Spatio-temporal drought analysis at country scale through the application of the STAND
toolbox, In: Spatiotemporal analysis of extreme rainfall events (Corzo and Varouchakis,
eds.), ISBN 9780128116890, Chapter 4.
2. M. Laverde-Barajas, G.A. Corzo Perez, B. Bhattacharya, R. Uijlenhoet, and D.P Solomatine,
2018, In: Spatiotemporal analysis of extreme rainfall events (Corzo and Varouchakis, eds.),
ISBN 9780128116890, Chapter 5.
3. Diaz, V., Corzo, G., & Pérez, J. R. (2018). Large-Scale Exploratory Analysis of the
Spatiotemporal Distribution of Climate Projections: Applying the STRIVIng Toolbox.
In Spatiotemporal Analysis of Extreme Hydrological Events (pp. 59-76). Elsevier.
4. Le, H. M., Corzo, G., Medina, V., Mercado, V. D., Nguyen, B. L., & Solomatine, D. P.
(2018). A Comparison of Spatial–Temporal Scale Between Multiscalar Drought Indices in
the South Central Region of Vietnam. In Spatiotemporal Analysis of Extreme Hydrological
Events (pp. 143-169). Elsevier.
5. Alvarez-Mieles, G., Corzo, G., & Mynett, A. E. (2018). Spatial and Temporal Variations′ of
Habitat Suitability for Fish: A Case Study in Abras de Mantequilla Wetland, Ecuador.
In Spatiotemporal Analysis of Extreme Hydrological Events (pp. 113-141). Elsevier.6. M. Laverde-Barajas, G.A. Corzo Perez, B. Bhattacharya, R. Uijlenhoet, and D.P
Solomatine (2018). Spatiotemporal object-based method for extreme rainfall events:
characteristics and applications for satellite products. (Book chapter).
7. Amutenya, J. T., & Perez, G. A. C. (2018). Infrastructures for Data in the Context of
Flow Forecasting Using Artificial Neural Network Model for Okavango River in
Namibia. In Hydrology and Best Practices for Managing Water Resources in Arid
and Semi-Arid Lands (pp. 106-120). IGI Global.
MSc Supervision
Anietie Okon, Development of a AI chatbot tool to guide Nigerian citizens in flood emergency situation. (2020-
2021) IHE Delft Institute for Water education
Camilo Andres Gonzales, Natural Processing language tool python code for a new semantic word algorithm in
water resources (2020-2021). Case study of Bolivia. In Cooperation with the Stokholm Environmental Institute and
IHE Delft Institute for Water Education.
Hudson Ebadoni, A convolution LSTM forcasting algorithm for flash flood guidance in the Mekon river (2020-
2021). In cooperation with the NASA-Servir program at the Asian Disaster preparedness center and the IHE Delft
Institute for Water Education
Victor Arcia, Deep learning for analysis spatiotermporal objects of rain and its relation to landslides (2020-2021).
Case study in the Island of Ometepe in Nicaragua. In Cooperation with the National University of Nicaragua and
IHE Delft Institute for Water Education
Karel Sanchez, A platform for tracking drought patterns using Deep learning (2020-2021). Case study in Central
America. IHE Delft Institute for Water Education
Mubarak Mohammed, Spatiotemporal drought forecasting in the Amazon river basin using an ANN-MLP (2020-
2021) IHE Delft Institute for Water Education
Thaine Herman Assumpcao, Improvement of the Monte Carlo sampling technique integrated to Global Sensitivity
Analysis, (2014), UNESCO-IHE, The Netherlands.
Daniel Vazquez Vado, Data driven and hybrid techniques to predict the reservoir inflows; case study Itaipu., (2014),
UNESCO-IHE, The Netherlands.
Dibesh Shrestha, Refining ensemble Kalman Filtering for hydrological prediction using modular approach., (2014),
UNESCO-IHE, The Netherlands.
Jacobine Amunteya, Big data infrastructure for Namibia, linking data with models online ., (2014), UNESCO-IHE,
The Netherlands.Badruz Saman, Best management practice for the drainage system in Jakarta , (2013), UNESCO-IHE, The Netherlands. Hadush Kidane, Data driven models for flood forecasting in the Lezarde river basin (Martinique) ., (2013), UNESCO-IHE, The Netherlands. H. Hidayat, Application of Data-Driven Techniques in Semi-Distributed Hydrological Modelling., (2008), UNESCO-IHE, The Netherlands. Wen Jie, Multi-objective optimisation of reservoir operation,, (2011), North West University for Water Resources and Electrical Power, China. Roxana Fonseca, Innovative radar forecasting techniques using local and global information., (2013), Tecnologico de Monterrey, Mexico. Joanne Craven SimBasin: serious gaming for integrated water resource management in the Magdalena-Cauca basin, (2015), University of Dresden , Germany. Tom Ouden Flood risk assessment and modelling uncertainty relations using data-driven models , (2015), Universidad de Barcelona, Spain. Anahit Hobyan Prediction of Runoff in Ungauged Basins in Australia with Existing Online Analytical Tools: Evaluation of Pentaho BI-BA with MySQL, (2015), UNESCO-IHE, The Netherlands. Mora Yousef Investigation of Data Mining techniques in a context of Reservoir Operation, (2016), UNESCO-IHE, The Netherlands. Yousra Omer Elfaroug Mohammed Khair Exploring the Use of Earth Observation and Ground Station Precipitation Data for Improving Meteorological Drought Monitoring in Mexico, Case Study: Guerrero State, (2016), UNESCO- IHE, The Netherlands. Meiline Harliana Siahaan Development of a Web-based Water Allocation Model: Case Study of Coello Basin, Colombia, (2016), UNESCO-IHE, The Netherlands. Marta Hidayat Web-based 1D Hydrodynamic Modelling: Case Study Papaloapan River, Mexico, (2016), UNESCO-IHE, The Netherlands. Francesca Caggiao Serious gaming as a tool for training and learning in the Momposina Depression, Colombia, (2016), UNESCO-IHE, The Netherlands. Josias Ritter Optimisation of hydropower dam cascade operations with respect to energy generation, flood hazard and flow regime alteration using operational modelling, (2016), Universidad de Barcelona, Spain Le Manh Hung Analysis of drought forecasting based on ENSO and PDO indices for a case study in Vietnam South Central Region, (2016), Universidad de Barcelona, Spain. Yogi Suardiwerianto An study of flash flood guidance models for Dominican Republic, (2017), UNESCO-IHE, The Netherlands.
Jose Valles Leon Analysis of the spatial precipitation distribution impacts in the flow forecasting accuracy: case study in Rio Lempa y Jiboa in Salvador, (2017), UNESCO-IHE, The Netherlands. Cecilia Emanueli Gandara Exploring the abilities of deep learning for training hydrological flow forecasting models, (2017), UNESCO-IHE, The Netherlands. Yuan Zhuang Flow cytometer data analysis for identifying water quality variables: case study of Lake Taihu, China, (2017), UNESCO-IHE, The Netherlands. Rodrick Kunkwenzu Prediction of arch dam deformations using computational intelligence techniques: Case study of Tsankov Kamak dam in Bulgaria, (2017), UNESCO-IHE, The Netherlands Jason Ernest Evaluation of an online Flood Risk Management System for the Yuna River Basin Dominican Republic, (2018), IHE Delft, The Netherlands. Mengwei Chu Understanding Virtual Water Trade in the Middle East and North Africa Countries and Addressing Implications for Water Resources Management, (2018), IHE Delft, The Netherlands. Joel Cantu Guerrero Big data analysis to understand the interaction of irrigation and groundwater levels on a real time online system in Nebraska, USA., (2018), IHE Delft, The Netherlands. Mostafa Farrag Developing ensemble forecasting capabilities in Jiboa Catchment Case study: Jiboa Catchment in El Salvador, (2018), IHE Delft, The Netherlands. Ahmed Abdelmoneim Ahmed Osman Data-driven model to predict crop yield loss as consequence of meteorological drought using ENSO and historical data Case Study of India, (2018), IHE Delft, The Netherlands. Freddy Santiago Duarte Prieto Chaos theory applied to downscaling weather information into hydrological models, (2017), Escuela Colombiana de Ingenieria J.G., Colombia. Ximena Lemaitre Development of a software for water distrubution and management, (2018), Escuela Colombiana de Ingenieria J.G., Colombia. Nicolas Antonio Lopez Rozo Metodología para la separación espacial de zonas en una cuenca hidrológica según su respuesta ante eventos extremos, (2018), Escuela Colombiana de Ingenieria JG, Colombia. Yessica Alejandea Rodriguez Belasquez Metodología para la separación espacial de zonas en una cuenca hidrológica según su respuesta ante eventos extremos, (2018), Escuela Colombiana de Ingenieria JG, Colombia. Dianah Nassaira, Modeling Flood Nature based solutions using Hydrological models (2019), , IHE Delft, The Netherlands. Shamdipa Rai, Serious gaming for Water Resources in Bagmati river basin, (2019), IHE Delft, The Netherlands. Carlos Tami, Indirect analysis of operational rules in reservours using ANN (Yuna River in Dom. Rep.), (2019), Escuela Colombiana de Ingenieria JG, Colombia.
Danilo Rodriguez Correa, Learning from hydrodynamic models about morphological changes in Zapayan, Colombia, (2020), IHE Delft, The Netherlands. Fabio Aguilar Carrillo, Analysis of drought indexes in the context of spatiotemporal analysis, (2020), Escuela Colombiana de Ingenieria JG, Colombia Juan Manuel Palma Cotrino, Sensitivity analysis of hydrological variables in the measuremten and characterisation of spatiotemporal drought, (2020), Escuela Colombiana de Ingenieria JG, Colombia Alban Doko, Integration of global rainfall data for hydrological forecasting in albanian river catchments, (2020) , IHE Delft, The Netherlands. Jordi Palacios, 2D HD model comparison of Particle transport patterns in the río la Miel in Colombia, (2020), Escuela Colombiana de Ingenieria JG, Colombia PhD Supervision and Co-promotion Freddy Santiago Duarte Prieto, Machine learning and AI in spatiotemporal tracking of anomalies in Nexus Water- Food and Energy systems, (2020-2024), Tec. Univ. of Delft and IHE-Delft Institute for Water Education, The Netherlands Enya Enriquez, An intelligent combined AI and citizens science approach to determine river health (2021-2025). Tec. Univ. of Delft and IHE-Delft Institute for Water Education, The Netherlands Alessandro Amaranto, Data-driven models to improve spatiotemporal monitoring and forecasting of water levels for Nebraska, (2016-2019), UNESCO-IHE and University of Nebraska Lincoln, US Miguel Angel Laverde, Spatiotemporal uncertainty analysis in a cascade of hydrological and hydrodynamic models for flood risk analysis, (2015-2020), Tec. Univ. of Delft and IHE-Delft Institute for Water Education, The Netherlands Vitali Diaz Mercado, Global hydrological analysis of extreme hydrological events, (2015-2020), Tec. Univ. of Delft and IHE-Delft Institute for Water Education, The Netherlands Chen Wang, Smart Serious gaming for Tacit knowledge acquisition and sharing in Sponge Cities, (2020-2024), Tec. Univ. of Delft and IHE-Delft Institute for Water Education, The Netherlands Natalia Uribe, Spatiotemporal optimisation of best management practices for assessing multiobjective impacts of climate change scenarios, (2016-2020), Tec. Univ. of Delft and UNESCO-IHE, The Netherlands Ana Maria Paez, Drought patterns dynamics from global observations, (2018-2022), Tec. Univ. of Delft and IHE- Delft Institute for Water Education, The Netherlands Nguyen Huy, Spatiotemporal urban flood risk and health modelling in Can Tho city, Ninh Kieu District. (2021- 2022) Veronica Minaya, Multi-scale analysis of hydrological models for assessing water stress due to climate change in the Ecuatorian Paramos., (2013-2017), Tec. Univ. of Delft and UNESCO-IHE, The Netherlands
Ornella Sosa, Multi-objective optimisation and computational modelling of microbial desalination cells., (2011- 2015), Tecnologico de Monterrey, Mexico Reem F.M.O. Digna, On optimising the operation of the multi-reservoir system in the Eastern Nile basin considering water and sediment fluxes, (2015-2019), Tec. Univ. of Delft and UNESCO-IHE, The Netherlands Ricardo da Silva Manca, Multi-objective and multicriteria analysis for urban water systems for the city of Sao Paulo, (2011-2015), UNICAMP, Brasil Jose del Castillo, Downscaling precipitation methods to assess engineering uncertainties, (2017-2020), Tecnologico de Monterrey, Mexico Yalina Montemorelos, Hydrological analysis of climate change impacts in Mexico and Cuba, (2017-2019), CISESE, Mexico Juan Carlos Ramirez Muñoz, Analysis of fast floods from small regions in agricultural fields, (2017-2020), Universidad de Veracruz, Mexico Teaching track record From 2000-2003 Lecturer in Maths, mainly on topics of Calculus I and II, Numerical Methods and Partial Differential Equations, Universidad Francisco de Paula Santander, Cucuta, Colombia From 2005 Sept -2009 Sept Lecturer o IT, and in the topics of databases, and support to the Hydrology workshops. IHE Delft Institute for Water Esucations, Delft, The Netherlands From 2011 june to Dece 2012, Lecturing on Remote sensing and Programing From 2013 april to now, Lecturer on ICT in the topics of Programing, Computer Architecture and Web development. Lecturer in Uncertainty analysis and Mathematical modelling.
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