کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6411035 1629923 2015 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Development of a new composite drought index for multivariate drought assessment
ترجمه فارسی عنوان
توسعه یک شاخص جدید خشکسالی کامپوزیت برای ارزیابی چند متغیری خشکسالی
کلمات کلیدی
خشکی، شاخص خشکسالی، فاصله اقلیدسی وزنی، شاخص کامپوزیت چند متغیره،
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- Composite drought index (CDI) - a multivariate index for drought assessment was proposed.
- CDI considers the causative variables of multi drought forms and aggregate the effect of them.
- With a simple computation procedure, CDI is statistically robust, comprehensive and more flexible.

SummaryComprehensibly considering all physical forms of agricultural, hydrological, and meteorological drought is essential to develop reliable monitoring and prediction indices for the proper assessment of drought. This consideration encouraged to develop and evaluate a multivariate composite drought index (CDI) that considers all possible variables related to individual types of drought. The proposed CDI was primarily based on the weighted similarity measure (entropy weighted Euclidian distance) and the anomaly from the possible wettest and driest conditions of the selected study region (sub basin of Han River, South Korea). The CDI time series identified 2008-2009 as the driest year, while May 2008 was the driest month within the selected period (2003-2011). The comparative analysis revealed that the CDI monthly time series had a significant correlation with the aggregate drought index (ADI). In addition, in comparison with the single variable-based indices i.e., the standardized precipitation index (SPI) and the streamflow drought index (SDI), the CDI comprehensively responded to variability embedded in the individual drought attributes. Moreover, it was concluded that the developed CDI provided a physically sound, temporally flexible and unbiased index that can be directly associated with all possible variants and linked to the climate conditions of the study region without considering any feature extraction technique.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 527, August 2015, Pages 30-37
نویسندگان
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