Drought forecasting using the Standardized Precipitation Index

By A. Cancelliere, G. D. Mauro, B. Bonaccorso, G. Rossi. 2007

337 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/3774b6198ed11a8f7152216d8491b598563c28d9

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In Ecology, Evolution, Behavior and Systematics

In Global and Planetary Change

Citations in the corpus

Critical drought intensity-duration-frequency curves based on total probability theorem-coupled frequency analysis (2021, background): “When the characterization of the drought process is concerned, determination of the return period becomes an important issue (Fernandez and Salas 1999, Chung and Salas 2000, Shiau and Shen 2001, Bonaccorso et al. 2003, Serinaldi et al. 2009, Cancelliere and Salas 2010).”
Application of linear stochastic models for drought forecasting in the Büyük Menderes river basin, western Turkey (2010, methodology): “Among the most commonly used meteorological drought indices for drought monitoring, the SPI has found widespread application (McKee et al. 1993; Heim 2000; Wilhite et al. 2000; Cancelliere et al. 2007; Labedzki 2007).”
A copula-based joint deficit index for droughts. (2010, methodology): “Cancelliere et al., 2007 ), it can lead to confusion because inconsistent results may emerge under different window sizes (unfortunately, there is no representative window).”
Characterisation of Drought Properties with Bivariate Copula Analysis (2013, background): “…and monitoring the drought episode, it was reported that SPI has the universal applicability (Angelidis et al. 2012) and diversified application in describing and comparing the drought episodes during different time periods and regions with different climatic conditions (Cancelliere et al. 2007).”
SPI-based drought category prediction using loglinear models (2008, methodology): “This approach has to be later combined with other predictions of stochastic nature (e.g. Paulo and Pereira, 2007; Cancelliere et al., 2007) and weather regime modeling.”
Meteorological Drought Analysis in the Lower Mekong Basin Using Satellite-Based Long-Term CHIRPS Product (2017, methodology): “The SPI has been widely applied to study the characteristics of drought, such as drought forecasting [12], drought frequency analysis [13,14], spatiotemporal drought analysis [15,16], drought period and severity [17], and climate change impact studies [18].”
Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models (2014, methodology): “Due to a slow evolution in time, drought is often a phenomenon whose consequences take a significant amount of time with respect to its inception to be perceived by the socio-economic sector (Cancelliere et al., 2007b).”