Drought is an important climate event and is linked to water availability, temperature, sunshine, and wind speed (
Journal of Resources and Ecology, Volume. 11, Issue 3, 304(2020)
Variations in the Drought Severity Index in Response to Climate Change on the Tibetan Plateau
Drought is an important climate event and is linked to water availability, temperature, sunshine, and wind speed (
1 Introduction
Drought is an important climate event and is linked to water availability, temperature, sunshine, and wind speed (
The Tibetan Plateau is one of the landscapes considered to be sensitive to climate change (
The impact of climate change varies across different vegetation types on the Tibetan Plateau (
2 Materials and methods
2.1 Study area
Known as the Third Pole by some, the Tibetan Plateau has distinctive features including high elevation (elevation 【-逻*辑*与-】gt;4000 m), strong solar radiation, thin air and low temperatures. The predominant vegetation types include alpine meadows, alpine steppes, temperate steppes, forests, shrublands, and croplands.
2.2 Drought severity index (DSI) data
The vegetation response-incorporated DSI products used in this study were obtained from MODIS16 onboard the NASA Earth Observing System (EOS) Terra and Aqua satellites. The MODIS 16 evapotranspiration (ET) and potential evapotranspiration (PET) data were used as primary inputs to calculate the DSI; the spatial resolution was 0.05°×0.05° and the temporal resolution was one year. The specific calculation follows Mu et al
The temporal standard deviation of ratio (${{\sigma }_{Ratio}}$) and ratio average ($\overline{Ratio}$) were then computed on a grid cell-wise basis over the available satellite record (from 2000 to present). The standardized ratio (
We derived the standardized
The
The remotely sensed
Compared to traditional drought monitoring methods, DSI enhances the capability of near real-time drought monitoring (Mu et al
2.3 Climate data
We obtained climate data from the China Meteorological Data Sharing Service System (http://cdc.cma.gov.cn/). The study used data from a total of 69 meteorological stations. Of these stations, 22 stations were in alpine meadows, 8 in alpine steppes, 4 in temperate steppes, 7 in forests, 12 in shrublands and 16 in croplands. Climate data included five temperature factors (average annual air temperature (Ta), maximum air temperature (MAT), minimum air temperature (MIT), extreme maximum air temperature (EMAT), and extreme minimum air temperature (EMIT)), two precipitation factors (total annual precipitation (TP), and maximum precipitation (MAP)), four humidity factors (average annual vapor pressure (Ea), relative humidity (RH), minimum relative humidity (MIRH), and vapor pressure deficit (VPD)), two sunshine factors (annual percentage of sunshine (SP) and total sunshine hours (SH)), and average annual wind speed (WS).
2.4 Data analysis
The map for vegetation type (1:1000000 scale) was converted into a raster file (0.05°×0.05° spatial resolution) prior to other analyses. We used the slope and intercept of the regression straight line to analyze changes in DSI and the five temperature factors, two precipitation factors, four humidity factors, two sunshine factors, and annual average wind speed. We used a correlation analysis to analyze the relationship between DSI and the climate factors. All spatial analyses were performed using ArcGIS (version 9.3).
3 Results and discussion
3.1 Climate factor changes
The climate became warmer and drier from 2000 to 2011, based on meteorological records for the Tibetan Plateau (
Figure 1.
3.2 DSI changes
Spatially averaged DSI change varied among vegetation types (
Figure 2.
Inter-annual DSI change during recent years varied among the 69 meteorological stations (
The change rate of DSI decreased with increasing temperatures (i.e., Ta, MAT, MIT, EMAT, and EMIT), and environmental humidity (TP, MAP, and Ea), but increased with increasing SP, SH, and WS (
Figure 3.
DSI change showed a positive relationship with TP change, but negative correlations with temperature (MAT, EMAT, EMIT), SP and SH changes (
Thus, the findings in our study suggest that the correlations between DSI change and climate factors are dependent on local climate conditions.
Figure 4.
Figure 5.
Figure 6.
3.3 Relationships between DSI and climate factors
Spatially averaged DSI was related positively to spatially averaged TP and MIRH, but correlated negatively to SP and SH at all of the 69 meteorological stations (
Correlation coefficients for spatially averaged annual drought severity index (DSI) with spatially averaged climate factors from 2000 to 2011 at 69 meteorological stations on the Tibetan Plateau
Correlation coefficients for spatially averaged annual drought severity index (DSI) with spatially averaged climate factors from 2000 to 2011 at 69 meteorological stations on the Tibetan Plateau
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Figure 7.
Figure 8.
Spatially averaged DSI increased as TP increased in alpine meadows, alpine steppes and shrublands (
Generally, correlations between DSI and climate factors varied among the 69 meteorological stations. At three stations, wind speed was the dominant factor influencing DSI, at 26 stations temperature factors were dominant, at 11 stations precipitation factors were dominant, at 15 stations air humidity factors were dominant, and at 14 stations sunshine factors were dominant. Most stations showed positive correlations between DSI and water availability, and these stations were distributed mainly in the center and east of Tibet, the east and south of Qinghai and the northwest of Sichuan (
Figure 9.
Most meteorological stations showed negative correlations between DSI and sunshine conditions, and these stations were distributed mainly in the east of Tibet, the south of Qinghai and the northwest of Sichuan. Among this group of stations, ten stations were found to have significant correlations (
More than 50% of the meteorological stations showed negative correlations of DSI with Ta, MIT and EMIT, and these stations were distributed mainly in central and eastern Tibet and the northwest of Sichuan. Five stations showed significant correlations of DSI with Ta and MIT (
Spatially averaged DSI decreased as Ta, MAT, and EMAT increased in forests and shrublands (
Figure 10.
Figure 11.
4 Conclusions
In this study, we investigated the correlation of DSI with 14 climate factors (including factors for temperature, precipitation, humidity, wind speed, and sunshine) from 2000 to 2011 on the Tibetan Plateau. Our main conclusions are as follows: 1) spatial DSI averages increased as precipitation and minimum relative humidity increased, but decreased as sunshine increased; 2) The correlation between DSI and climate factors differed due to the changes of the climate factors and the difference of background values among different vegetation types; and 3) The degree of correlation between DSI and climate change was stronger in environments that were colder and drier, and had higher wind speeds and more sunshine. These findings indicate that DSI can mirror the dynamics of water availability regardless of location or ecosystem scale. This study provides a scientific basis for local meteorological departments to implement effective, long-term drought monitoring programs. This is important and has practical significance for agriculture, animal husbandry and human life in alpine regions.
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Xiangtao WANG, Xianzhou ZHANG, Junhao WANG, Ben NIU. Variations in the Drought Severity Index in Response to Climate Change on the Tibetan Plateau[J]. Journal of Resources and Ecology, 2020, 11(3): 304
Received: Jan. 9, 2020
Accepted: Mar. 17, 2020
Published Online: Apr. 23, 2021
The Author Email: NIU Ben (niub@igsnrr.ac.cn)