Drought forecasting using the Prophet model in a semi-arid climate region of western India

ABSTRACT

Accurate drought forecasting is necessary for early warning of drought hazards, water resources and eco-environmental management. This study assessed the capability of the Prophet model to forecast meteorological drought based on the standardized precipitation index (SPI). A comparative assessment was conducted among Prophet, support vector regression (SVR) and multiple linear regression (MLR) models to test the applicability of the new model. The SPI was computed at multiple time scales ($\mathrm{S}\mathrm{P}{\mathrm{I}}_3$, $\mathrm{S}\mathrm{P}{\mathrm{I}}_6$, $\mathrm{S}\mathrm{P}{\mathrm{I}}_{12}$ and $\mathrm{S}\mathrm{P}{\mathrm{I}}_{24}$) for 38 meteorological stations located in semi-arid areas in western India. Minimum redundancy maximum relevance (mRMR) was applied to select input variables prior to the model development. The results reveal that the Prophet model yielded acceptable accuracy for drought forecasting, whereas SVR and MLR models showed greater error for short-term forecasting in terms of coefficient of determination (${\mathrm{R}}^2$) and Nash-Sutcliffe efficiency (NSE). Therefore, the Prophet model is recommended as a new robust model for drought forecasting.

KEYWORDS:

• drought forecasting
• mRMR
• standardized precipitation index
• Prophet
• SVR

Editor A. Castellarin Associate Editor H. Tyralis

Editor A. Castellarin Associate Editor H. Tyralis

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/02626667.2022.2082876