A new non-stationary standardised streamflow index using the climate indices and the optimal anthropogenic indices as covariates in the Wei River Basin, China

• Published in: Journal of hydrology. Regional studies Vol. 51; p. 101649
• Main Authors: Ren, Mingming, Jiang, Shanhu, Ren, Liliang, Weng, Baisha, Wang, Menghao, Cui, Hao, Xu, Chong-Yu
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.02.2024; Elsevier
• Subjects: Climate index, Anthropogenic index; Hydrological drought; Non-stationary standardized streamflow index; Hydrological drought; Climate index, Anthropogenic index; Non-stationary standardized streamflow index
• ISSN: 2214-5818; 2214-5818
• DOI: 10.1016/j.ejrh.2023.101649

Catchment area above the Huaxian station along the Wei River Basin, China. This study attempts to construct a new Non-stationary Standardized Streamflow Index (NSSI) applicable to the variable streamflow sequence of the Wei River Basin based on the climate index and the optimal anthropogenic index, and analyse the drought characteristics of the basin. The climate index is used to quantify climate change factors and three anthropogenic indices are used to quantify the factor of human activities, including the reservoir index, the human-induced index calculated based on the Variable Infiltration Capacity (VIC) hydrological model and the Long Short-Term Memory (LSTM) model machine learning approach, respectively. The human-induced index based on the LSTM model is more suitable for quantifying anthropogenic factors in the Wei River Basin. The NSSI performs better than the SSI in drought identification. The NSSI based on the LSTM model can capture more frequent severe drought and extreme drought events. The frequency of severe drought and extreme drought is higher in summer and autumn than in the others. The NSSI can better characterize the hydrological drought processes under a non-stationary condition, thus it can provide a more effective reference for regional drought assessment and related policy-making from the perspective of a changing environment. [Display omitted] •A new Non-stationary Standardised Streamflow Index is proposed.•Climate indices and anthropogenic indices are adopted as covariates.•The method for quantifying anthropogenic factors is optimised.•The identification of drought events performs better by the proposed drought index.