Reprint
The Drought Risk Analysis, Forecasting, and Assessment under Climate Change
Edited by
January 2021
168 pages
- ISBN978-3-03936-806-8 (Hardback)
- ISBN978-3-03936-807-5 (PDF)
This book is a reprint of the Special Issue The Drought Risk Analysis, Forecasting, and Assessment under Climate Change that was published in
Biology & Life Sciences
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Public Health & Healthcare
Summary
This Special Issue is a platform to fill the gaps in drought risk analysis with field experience and expertise. It covers (1) robust index development for effective drought monitoring; (2) risk analysis framework development and early warning systems; (3) impact investigations on hydrological and agricultural sectors; (4) environmental change impact analyses. The articles in the Special Issue cover a wide geographic range, across China, Taiwan, Korea, and the Indo-China peninsula, which covers many contrasting climate conditions. Hence, the results have global implications: the data, analysis/modeling, methodologies, and conclusions lay a solid foundation for enhancing our scientific knowledge of drought mechanisms and relationships to various environmental conditions.
Format
- Hardback
License and Copyright
© 2021 by the authors; CC BY-NC-ND license
Keywords
extreme spring drought; atmospheric teleconnection patterns; drought prediction; China; SPI; reference precipitation; reference period; climate change; climate change; drought; GAMLSS; nonstationarity; meteorological drought; standardized precipitation evapotranspiration index; climate variability; seasonal drought; drought return period; extreme drought; Indochina Peninsula; Indian Ocean Dipole; intentionally biased bootstrap method; drought risk; climate change; human activities; quantitative attribution; artificial neural network; stochastic model; ARIMA model; drought forecasting; southern Taiwan; bivariate frequency analysis; climate change; drought; hydrologic risk; drought; global warming; maize yield; Songliao Plain maize belt; comprehensive drought monitoring; Hubei Province; multivariate; multisource data; climate change; drought risk; assessment; forecasting