Identification of Hydrological Drought in Eastern China Using a Time-Dependent Drought Index
1
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
2
Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
3
Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
*
Authors to whom correspondence should be addressed.
Water 2018, 10(3), 315; https://doi.org/10.3390/w10030315
Received: 31 January 2018 / Revised: 12 March 2018 / Accepted: 12 March 2018 / Published: 13 March 2018
(This article belongs to the Special Issue Data-Driven Methods for Agricultural Water Management)
Long records (1960–2013) of monthly streamflow observations from 8 hydrological stations in the East Asian monsoon region are modeled using a nonstationarity framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarity of monthly streamflow series in different geographic regions and to select optimal distribution among five two-parameter distributions (Gamma, Lognormal, Gumbel, Weibull and Logistic). Based on the optimal nonstationarity distribution, a time-dependent Standardized Streamflow Index (denoted SSIvar) that takes account of the possible nonstationarity in streamflow series is constructed and then employed to identify drought characteristics at different time scales (at a 3-month scale and a 12-month scale) in the eight selected catchments during 1960–2013 for comparison. Results of GAMLSS models indicate that they are able to represent the magnitude and spread in the monthly streamflow series with distribution parameters that are a linear function of time. For 8 hydrological stations in different geographic regions, a noticeable difference is observed between the historical drought assessment of Standardized Streamflow Index (SSI) and SSIvar, indicating that the nonstationarity could not be ignored in the hydrological drought analyses, especially for stations with change point and significant change trends. The constructed SSIvar is, to some extent, found to be more reliable and suitable for regional drought monitoring than traditional SSI in a changing environment, thereby providing a feasible alternative for drought forecasting and water resource management at different time scales.
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MDPI and ACS Style
Zou, L.; Xia, J.; Ning, L.; She, D.; Zhan, C. Identification of Hydrological Drought in Eastern China Using a Time-Dependent Drought Index. Water 2018, 10, 315. https://doi.org/10.3390/w10030315
AMA Style
Zou L, Xia J, Ning L, She D, Zhan C. Identification of Hydrological Drought in Eastern China Using a Time-Dependent Drought Index. Water. 2018; 10(3):315. https://doi.org/10.3390/w10030315
Chicago/Turabian StyleZou, Lei; Xia, Jun; Ning, Like; She, Dunxian; Zhan, Chesheng. 2018. "Identification of Hydrological Drought in Eastern China Using a Time-Dependent Drought Index" Water 10, no. 3: 315. https://doi.org/10.3390/w10030315
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