Spatio-temporal Analysis of Extreme Hydrological Events offers an extensive view of the experiences and applications of the latest developments and methodologies for analyzing and understanding extreme environmental and hydrological events. This book addresses extreme hydrological events using spatio-temporal methods such as space-time geostatistics, machine learning, statistical theory, hydrological modelling, neural network and evolutionary algorithms.
An important resource for both hydrologists and statisticians interested in the framework of spatial and temporal analysis of hydrological events, this book helps to enhance understanding of the relationship between magnitude, dynamics and the probability of extreme hydrological events.
- Presents spatio-temporal processes including multivariate dynamic modelling
- Provides variable methodological approaches giving the readers multiple hydrological modelling information to use in their work
- Includes a variety of case studies making the context of the book relatable to everyday working situations
Hydrologists, scientists working on water resource management, Aquatic Scientist, Climatologists. Statisticians interested in the framework of spatial and temporal analysis of hydrological events, water resource engineers, coastal and estuarine scientists, applied mathematicians
1. Dynamic correlation structures for interpolation of precipitation patterns
2. Local Geostatistical Models and Big Data in Hydrological Applications
3. Space-time simulation techniques for potential use in hydrological extremes
4. Space-time geostatistics for hydrological applications using sequential Gaussian simulation and Bayesian bootstrapping
5. Improved spatial prediction: A combinatorial approach
6. Using novel geostatistical techniques to identify the spatial distribution of biogeochemical hot-spots under contrasting hydrological conditions
7. Geostatistical prediction of flow-duration curves in an index-flow framework
8. Infilling and interpolation of precipitation at different temporal scales in South Africa
9. Impact of rainfall spatial variability on Flash Flood Forecasting
10. Blending satellite data and RADAR tool for rapid flood damage assessment in Agriculture: A case study in Sri Lanka
- No. of pages:
- © Elsevier 2019
- 1st September 2018
- Paperback ISBN:
Dr Gerald A. Corzo has extensive experience in modelling for different problems in Integrated water resources management, his high skills in ICT technology have been used to develop different type of scientific application. As researcher and lecturer of different academic institutions have worked and coordinated academic programs. His expertise has been mainly developed around programming mathematical models and statistical models for hydroinformatics problems. Since the last six years he has been working on the use of global hydrological models ensemble and their uncertainty for climate change analysis. This work mainly involves heavy data loads from GCM and GHM models for several scenarios and developed statistical tools for online and parallel processing of such information. This work was presented in the WATCH-EU project report No. 43. As manager of the Hydroinformatics servers during 4 years he developed and implemented data base web systems for different projects at UNESCO-IHE, as well as maintained and managed the institutional basic support collaborative working environment (BSCW). In 2012 he won the Tison award in Hydrology from the IAHS association. Recently he supervised the research projects with ministry of Nigeria to develop a Spatial Data Infraestructure for sharing and analyzing diferent regions in the country. Aside of this right now he is coordinating the activities of the development of data analsysis over large data set in the Systema Integrado de recursos Hidricos from Colombia. This work and others are being develop under the framework and cooperation with the group CUAHSI and GEOSS, following all OGC standards. He has coordinated the statistics of the Climate change inventory of adaptation and mitigation actions for Latin-America, presented at the WWF in 2012. Is Civil engineer by training with a strong background on computational science and specialized in Teleinformatics. His areas of research cover innovative methods for integrating computational intelligent algorithms and hydrological conceptual models for hydrological forecasting (Flood Early Warning System models integration, Delft-FEWS). He developed scripts for areas of computational intelligence, optimization of water resources, online modeling and in fluid dynamics simulation. One of his recent projects focuses on exploring the use of mobile phone antennas in Colombia for measuring precipitation. He have participated on research projects in different countries like China with the North China University for Water Conservancy and Electric Power in China, Colombia (CINARA), Mexico (Technologico of Monterrey), England (CEH), Norway (University of Oslo) and others. The last five years he served as chair of the session on geo-statistics at the European Geoscience Union. He leaded the LatinAqua network for water research scientist in Latin-America in 2011
Researcher and Senior Lecturer, IHE Delft Institute for Water Education
Dr. Emmanouil Varouchakis is an Instructor/Researcher at the School of Environmental Engineering, Technical University of Crete, Greece. He holds a PhD in Geo-technology and the Environment-Spatiotemporal Geostatistics from the Technical University of Crete. Since 2013 he teaches the courses ‘’Introduction to Geostatistics’’, ‘’Applied Geostatistics’’ and ‘’Environmental Risk Analysis’’ at the Schools of Environmental and Mineral Resources Engineering. He has published several research articles in international journals and he has presented his research findings in international conferences. In 2015 he has been awarded the Natural Resources Research grant award by the International Association of Mathematical Geosciences for his research work entitled ‘’A Bayesian space-time geostatistical model for groundwater level variability estimation’’.
School of Environmental Engineering, Technical University of Crete, Chania, Greece