Abstract

Global Drought and Flood: Monitoring, Prediction, and Adaptation is an American Geophysical Union monograph (published by Wiley) that introduces the latest advancements in physical and remote sensing models developed for drought and flood issues. The book consists of 18 chapters in 3 parts, which introduce global remote sensing monitoring of droughts and floods, modeling and prediction of global drought and flood, as well as risk assessment, management, and socioeconomic responses to global drought and flood. Current remote sensing observation research suggests that merging climate data can generate longer records suitable for drought assessment and monitoring, while some variables such as snow and relative humidity can be integrated into drought monitoring models to improve the monitoring and estimation of drought initiation, respectively. However, changes in satellite sensors also introduce considerable unquantifiable uncertainty to drought modeling. An ideal approach to this issue is to provide uncertainty boundaries based on top of the original observations. This uncertainty and the structural and parameter uncertainties generated by model-based simulations can be combined to assist decision-making in operational applications. The monograph not only elaborates on the dominant models, methods, techniques, and products used in practical applications internationally but also provides planning and deployment for flood disaster prediction. The drought and flood modeling and remote sensing methods presented in this book can be used for reference and use by global emergency organizations and decision-makers.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.