期刊论文详细信息
JOURNAL OF HYDROLOGY 卷:603
An enhanced water storage deficit index (EWSDI) for drought detection using GRACE gravity estimates
Article
Khorrami, Behnam1  Gunduz, Orhan2,3 
[1] Dokuz Eylul Univ, Grad Sch Appl & Nat Sci, Dept GIS, Dogus Cad 207-A Tinaztepe Yerleskesi, TR-35390 Izmir, Turkey
[2] Izmir Inst Technol, Fac Engn, Dept Environm Engn, Izmir, Turkey
[3] Izmir Inst Technol, Dept Environm Engn, TR-35430 Izmir, Turkey
关键词: Enhanced water storage deficit index;    Terrestrial water storage anomalies;    Drought monitoring;    Time series decomposition;    GRACE;    Turkey;   
DOI  :  10.1016/j.jhydrol.2021.126812
来源: Elsevier
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【 摘 要 】

Accurate detection and monitoring of drought events are important particularly in arid and semi-arid regions of the world. Gravity Recovery and Climate Experiment (GRACE) gravity estimates have been used widely for this purpose and a number of indices have been developed using the GRACE Terrestrial Water Storage Anomalies (TWSA) values. In the current study, a new approach is proposed to enhance the performance of the GRACE-based Water Storage Deficit Index (WSDI). The proposed Enhanced Water Storage Deficit Index (EWSDI) was developed based on the grid-based standardization of the Water Storage Deficit (WSD) values. The decomposed time series of the TWSA were computed in an attempt to evaluate the performance of the approach based on different components of the TWSA time series. Standardized Precipitation Index (SPI) and modelled Soil Moisture Storage (SMS) were also used to validate the functionality of this new GRACE-derived index. The applicability of the EWSDI index was tested in the semi-arid climatic conditions of Turkey and the results showed that the detrended EWSDI better correlated with SPI-09 and annual SPI with correlation coefficient values of 0.70 and 0.76, respectively. The findings also suggested an approximate enhancement of 13% over the existing WSDI when applied on the detrended TWSA. The findings of this study reveal that the proposed approach is effective in improving the performance of the existing WSDI to detect drought events in terms of monthly and annual correlation coefficients achieved.

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