Abstract
Climate change and human activity are the two major drivers that can alter hydrological cycle processes and influence the characteristics of hydrological drought in river basins. The present study selects the Wei River Basin (WRB) as a case study region in which to assess the impacts of climate change and human activity on hydrological drought based on the Standardized Runoff Index (SRI) on different time scales. The Generalized Additive Models in Location, Scale and Shape (GAMLSS) are used to construct a time-dependent SRI (SRIvar) considering the non-stationarity of runoff series under changing environmental conditions. The results indicate that the SRIvar is more robust and reliable than the traditional SRI. We also determine that different driving factors can influence the hydrological drought evolution on different time scales. On shorter time scales, the effects of human activity on hydrological drought are stronger than those of climate change; on longer time scales, climate change is considered to be the dominant factor. The results presented in this study are beneficial for providing a reference for hydrological drought analysis by considering non-stationarity as well as investigating how hydrological drought responds to climate change and human activity on various time scales, thereby providing scientific information for drought forecasting and water resources management over different time scales under non-stationary conditions.
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Acknowledgments
This study was supported by the National Natural Science Foundation of China (41501030 and 41571028) and the Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering (No. 2016490211). We are very grateful to the editors and two anonymous reviewers for their valuable comments and constructive suggestions that helped us to greatly improve the manuscript.
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Zou, L., Xia, J. & She, D. Analysis of Impacts of Climate Change and Human Activities on Hydrological Drought: a Case Study in the Wei River Basin, China. Water Resour Manage 32, 1421–1438 (2018). https://doi.org/10.1007/s11269-017-1877-1
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DOI: https://doi.org/10.1007/s11269-017-1877-1