Assessing phenological change and climatic control of alpine grasslands in the Tibetan Plateau with MODIS time series

2014 ◽  
Vol 59 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Cuizhen Wang ◽  
Huadong Guo ◽  
Li Zhang ◽  
Shuangyu Liu ◽  
Yubao Qiu ◽  
...  
Keyword(s):  
Time Series ◽  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Alpine Grasslands ◽  
Climatic Control

Declining human activity intensity on alpine grasslands of the Tibetan Plateau

2021 ◽  
Vol 296 ◽  
pp. 113198
Author(s):  
Meng Li ◽  
Xianzhou Zhang ◽  
Jianshuang Wu ◽  
Qiannan Ding ◽  
Ben Niu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Human Activity ◽  
The Tibetan Plateau ◽  
Alpine Grasslands ◽  
Activity Intensity

Extracting the cumulative distribution location of highly intermittent river from Sentinel-1 time series in an alpine catchment on the Tibetan Plateau

2021 ◽  
Author(s):  
Junyuan Fei ◽  
Jintao Liu
Keyword(s):  
Time Series ◽  
Tibetan Plateau ◽  
Time Scale ◽  
Proper Time ◽  
Cumulative Distribution ◽  
The Tibetan Plateau ◽  
Statistical Features ◽  
Catchment Scale ◽  
Intermittent Rivers ◽  
Intermittent River

<p>Highly intermittent rivers are widespread on the Tibetan Plateau and deeply impact the ecological stability and social development downstream. Due to the highly intermittent rivers are small, seasonal variated and heavy cloud covered on the Tibetan Plateau, their distribution location is still unknown at catchment scale currently. To address these challenges, a new method is proposed for extracting the cumulative distribution location of highly intermittent river from Sentinel-1 time series in an alpine catchment on the Tibetan Plateau. The proposed method first determines the proper time scale of extracting highly intermittent river, based on which the statistical features are calculated to amplify the difference between land covers. Subsequently, the synoptic cumulative distribution location is extracted through Random Forest model using the statistical features above as explanatory variables. And the precise result is generated by combining the synoptic result with critical flow accumulation area.  The highly intermittent river segments are derived and assessed in an alpine catchment of Lhasa River Basin. The results show that the the intra-annual time scale is sufficient for highly intermittent river extraction. And the proposed method can extract highly intermittent river cumulative distribution locations with total precision of 0.62, distance error median of 64.03 m, outperforming other existing river extraction method.</p>

scholarly journals Spatiotemporal patterns of High Mountain Asia's snowmelt season identified with an automated snowmelt detection algorithm, 1987–2016

2017 ◽  
Vol 11 (5) ◽  
pp. 2329-2343 ◽  
Author(s):  
Taylor Smith ◽  
Bodo Bookhagen ◽  
Aljoscha Rheinwalt
Keyword(s):  
Time Series ◽  
Tibetan Plateau ◽  
Climate Model ◽  
Single Point ◽  
Passive Microwave ◽  
Spatiotemporal Patterns ◽  
Signal Separation ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Microwave Data

Abstract. High Mountain Asia (HMA) – encompassing the Tibetan Plateau and surrounding mountain ranges – is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications – such as agriculture, drinking-water generation, and hydropower – rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season – defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3–5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade−1 over the 29-year study period (5–25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over 3 decades indicate generally earlier snowmelt seasons, data from the last 14 years (2002–2016) exhibit positive trends in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal of a long-term trend or simply interannual variability. (4) Some regions with stable or growing glaciers – such as the Karakoram and Kunlun Shan – see slightly later snowmelt seasons and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general led to earlier and shortened melt seasons, changes in HMA's cryosphere have been spatially and temporally heterogeneous.

scholarly journals Bacterial community in alpine grasslands along an altitudinal gradient on the Tibetan Plateau

2013 ◽  
Vol 87 (1) ◽  
pp. 121-132 ◽  
Author(s):  
Yanli Yuan ◽  
Guicai Si ◽  
Jian Wang ◽  
Tianxiang Luo ◽  
Gengxin Zhang
Keyword(s):  
Tibetan Plateau ◽  
Bacterial Community ◽  
Altitudinal Gradient ◽  
The Tibetan Plateau ◽  
Alpine Grasslands

Water and heat availability are drivers of the aboveground plant carbon accumulation rate in alpine grasslands on the Tibetan Plateau

2019 ◽  
Vol 29 (1) ◽  
pp. 50-64 ◽  
Author(s):  
Jian Sun ◽  
Tian‐Cai Zhou ◽  
Miao Liu ◽  
You‐Chao Chen ◽  
Guo‐Hua Liu ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Accumulation Rate ◽  
Carbon Accumulation ◽  
The Tibetan Plateau ◽  
Alpine Grasslands ◽  
Carbon Accumulation Rate

Effects of data temporal resolution on phenology extractions from the alpine grasslands of the Tibetan Plateau

2019 ◽  
Vol 104 ◽  
pp. 365-377 ◽  
Author(s):  
Yixuan Zhu ◽  
Yangjian Zhang ◽  
Jiaxing Zu ◽  
Zhipeng Wang ◽  
Ke Huang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Temporal Resolution ◽  
The Tibetan Plateau ◽  
Alpine Grasslands

Role of Tibetan Women in Carbon Balance in the Alpine Grasslands of the Tibetan Plateau. A Review

2016 ◽  
Vol 20 (1) ◽  
pp. 108-122 ◽  
Author(s):  
Zhanhuan Shang ◽  
Andrew White ◽  
A. Allan Degen ◽  
Ruijun Long
Keyword(s):  
Tibetan Plateau ◽  
Carbon Balance ◽  
The Tibetan Plateau ◽  
Alpine Grasslands

Climatic and Edaphic Controls on Soil pH in Alpine Grasslands on the Tibetan Plateau, China: A Quantitative Analysis

Pedosphere ◽  
2014 ◽  
Vol 24 (1) ◽  
pp. 39-44 ◽  
Author(s):  
Cheng-Jim JI ◽  
Yuan-He YANG ◽  
Wen-Xuan HAN ◽  
Yan-Fang HE ◽  
J. SMITH ◽  
...  
Keyword(s):  
Quantitative Analysis ◽  
Tibetan Plateau ◽  
Soil Ph ◽  
The Tibetan Plateau ◽  
Alpine Grasslands

The effects of three years of fencing enclosure on soil seed banks and the relationship with above-ground vegetation of degraded alpine grasslands of the Tibetan plateau

2012 ◽  
Vol 364 (1-2) ◽  
pp. 229-244 ◽  
Author(s):  
Zhan-Huan Shang ◽  
Bin Deng ◽  
Lu-Ming Ding ◽  
Guo-Hua Ren ◽  
Guo-Sheng Xin ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Seed Banks ◽  
Ground Vegetation ◽  
The Tibetan Plateau ◽  
Alpine Grasslands ◽  
Soil Seed Banks ◽  
The Relationship
Sign in / Sign up

Export Citation Format

Share Document