An integrated package for drought monitoring, prediction and analysis to aid drought modeling and assessment. (May 2017)

• Record Type: Journal Article
• Authors: Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Ouyang, Wei; Cheng, Hongguang
• Is Part Of: Environmental modelling & software. Volume 91(2017)
• Page Start: 199
• Page End: 209
• Publication Date: 2017-05
• Subjects: Drought monitoring -- Drought prediction -- Drought analysis -- Drought early warning -- Extremes; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2017.02.008
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Due to severe drought events and disastrous impacts in recent decades, substantial efforts have been devoted recently to drought monitoring, prediction and risk analysis for aiding drought preparedness plans and mitigation measures. Providing an overview of these aspects of drought research, this study presents an integratedR package and illustrates a wide range of its applications for drought modeling and assessment based on univariate and multivariate drought indices for both operational and research purposes. The package also includes statistical prediction of drought in a probabilistic manner based on multiple drought indicators, which serves as a baseline for drought prediction. The univariate and multivariate drought risk analysis of drought properties and indices is also presented. Finally, potential extensions of this package are also discussed. The package is provided freely to public to aid drought early warning and management. Highlights: Derivation of univariate and multivariate drought indices based on hydroclimatic variables. Probabilistic drought prediction of multiple drought indices with statistical methods. Joint and conditional risk analysis of multiple drought properties and types. Application of an integrated R package for drought monitoring, prediction and analysis.