کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10144274 | 1646298 | 2019 | 10 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
sc_PDSI is more sensitive to precipitation than to reference evapotranspiration in China during the time period 1951-2015
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم کشاورزی و بیولوژیک
بوم شناسی، تکامل، رفتار و سامانه شناسی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: sc_PDSI is more sensitive to precipitation than to reference evapotranspiration in China during the time period 1951-2015 sc_PDSI is more sensitive to precipitation than to reference evapotranspiration in China during the time period 1951-2015](/preview/png/10144274.png)
چکیده انگلیسی
The self-calibrating Palmer Drought Severity Index (sc_PDSI) is developed within the frame of the PDSI model, but is considered to be more appropriate for global drought monitoring. The sc_PDSI can automatically calibrate itself at any location using dynamically computed values and can calculate evapotranspiration using the FAO-56 Penman-Monteith (P-M) equation. However, the correlation of the sc_PDSI(P-M) with some factors that drive drought, such as precipitation (P) and the reference evapotranspiration (ET0), is still unclear in China. With the aim of solving this issue, we analyzed the correlation of the detrended sc_PDSI(P-M) with the detrended P and ET0 on different timescales (one, three, six and 12â¯months) in China for the period 1951-2015. The results show that both the P and ET0 are highly correlated with the sc_PDSI(P-M) on a 12-month timescale. On this timescale, the sc_PDSI(P-M) is more sensitive to P than to ET0 on the national scale, except for northeastern China. Thus the sc_PDSI(P-M) may effectively fit the long-term variations in these drivers of drought, especially P. These results provide guidance on the use of the sc_PDSI(P-M) to detect the impacts of climate change on drought severity under the climatic conditions found in China.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Ecological Indicators - Volume 96, Part 1, January 2019, Pages 448-457
Journal: Ecological Indicators - Volume 96, Part 1, January 2019, Pages 448-457
نویسندگان
Yajie Zhang, Gaopeng Li, Jing Ge, Yao Li, Zhisheng Yu, Haishan Niu,