scholarly journals Evaluation and Hydrological Simulation of CMADS and CFSR Reanalysis Datasets in the Qinghai-Tibet Plateau

Water ◽  
2018 ◽  
Vol 10 (4) ◽  
pp. 513 ◽  
Author(s):  
Jun Liu ◽  
Donghui Shanguan ◽  
Shiyin Liu ◽  
Yongjian Ding
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Yellow River ◽  
Hydrological Processes ◽  
Tibet Plateau ◽  
Maximum Temperature ◽  
The Yellow River ◽  
Observation Data ◽  
Yellow River Source ◽  
Qinghai Tibet Plateau

Multisource reanalysis datasets provide an effective way to help us understand hydrological processes in inland alpine regions with sparsely distributed weather stations. The accuracy and quality of two widely used datasets, the China Meteorological Assimilation Driving Datasets to force the SWAT model (CMADS), and the Climate Forecast System Reanalysis (CFSR) in the Qinghai-Tibet Plateau (TP), were evaluated in this paper. The accuracy of daily precipitation, max/min temperature, relative humidity and wind speed from CMADS and CFSR are firstly evaluated by comparing them with results obtained from 131 meteorological stations in the TP. Statistical results show that most elements of CMADS are superior to those of CFSR. The average correlation coefficient (R) between the maximum temperature and the minimum temperature of CMADS and CFSR ranged from 0.93 to 0.97. The root mean square error (RMSE) for CMADS and CFSR ranged from 3.16 to 3.18 °C, and ranged from 5.19 °C to 8.14 °C respectively. The average R of precipitation, relative humidity, and wind speed for CMADS are 0.46; 0.88 and 0.64 respectively, while they are 0.43, 0.52, and 0.37 for CFSR. Gridded observation data is obtained using the professional interpolation software, ANUSPLIN. Meteorological elements from three gridded data have a similar overall distribution but have a different partial distribution. The Soil and Water Assessment Tool (SWAT) is used to simulate hydrological processes in the Yellow River Source Basin of the TP. The Nash Sutcliffe coefficients (NSE) of CMADS+SWAT in calibration and validation period are 0.78 and 0.68 for the monthly scale respectively, which are better than those of CFSR+SWAT and OBS+SWAT in the Yellow River Source Basin. The relationship between snowmelt and other variables is measured by GeoDetector. Air temperature, soil moisture, and soil temperature at 1.038 m has a greater influence on snowmelt than others.

scholarly journals Abundant and rare bacterial taxa structuring differently in sediment and water in thermokarst lakes in the Yellow River Source area, Qinghai-Tibet Plateau

2021 ◽  
Author(s):  
Ze Ren ◽  
Cheng Zhang ◽  
Xia Li ◽  
Kang Ma ◽  
Kexin Feng ◽  
...  
Keyword(s):  
Bacterial Communities ◽  
Yellow River ◽  
Source Area ◽  
Tibet Plateau ◽  
The Yellow River ◽  
Thermokarst Lakes ◽  
Β Diversity ◽  
Α Diversity ◽  
Yellow River Source ◽  
Qinghai Tibet Plateau

Thermokarst lakes are forming from permafrost thaw and severely affected by accelerating climate change. Sediment and water in these lakes are distinct habitats but closely connected. However, our understanding of the differences and linkages between sediment and water in thermokarst lakes remain largely unknow, especially from the perspective of bacterial community patterns and underlying mechanisms. In this study, we examined bacterial communities in sediment and water in thermokarst lakes in the Yellow River Source area, Qinghai-Tibet Plateau. Bacterial taxa were divided to abundant and rare according to their relative abundance, and the Sorensen dissimilarity (βsor) was partitioned into turnover (βturn) and nestedness (βnest). The results showed that the whole bacterial communities as well as the abundant and rare subcommunities differed substantially between sediment and water, in terms of taxonomical composition, α-diversity, and β-diversity. Sediment had significantly lower α-diversity indexes but higher β-diversity than water. Abundant taxa had significantly higher relative abundances but lower α-diversity and β-diversity than rare taxa. Moreover, bacterial communities are predominantly governed by strong turnover processes (βturn/βsor ratio of 0.925). Abundant subcommunities were significantly lower in βturn/βsor ratio compared to rare subcommunities. Bacterial communities in sediment had a significantly higher βturn/βsor ratio than in water. The results suggest that the bacterial communities of thermokarst lakes, especially rare subcommunities or particularly in sediment, might be strongly structured by environmental filtering and geographical isolation, leading to compositional distinct. By revealing bacterial communities in sediment and water, this integral study increased our current knowledge of thermokarst lakes, enhancing our understanding of the community assembly rules and ecosystem structures and processes of these rapid changing and vulnerable ecosystems.

Tracing of soil erosion and sediment transport by 10Be isotope in watershed of the Yellow River Source Area (YRSA)-Tibet Plateau

2017 ◽  
Author(s):  
Peng Chen ◽  
Peng Yi ◽  
Ala Aldahan ◽  
Ahmed Murad ◽  
Göran Possnert
Keyword(s):  
Sediment Transport ◽  
Soil Erosion ◽  
Yellow River ◽  
Source Area ◽  
Tibet Plateau ◽  
The Yellow River ◽  
Yellow River Source

Application of Rn-222 isotope for the interaction between surface water and groundwater in the Source Area of the Yellow River

2016 ◽  
Vol 47 (6) ◽  
pp. 1253-1262 ◽  
Author(s):  
M. J. Zheng ◽  
C. W. Wan ◽  
M. D. Du ◽  
X. D. Zhou ◽  
P. Yi ◽  
...  
Keyword(s):  
Surface Water ◽  
Yellow River ◽  
Reference Value ◽  
Source Area ◽  
Tibet Plateau ◽  
The Yellow River ◽  
The North ◽  
Surface Water And Groundwater ◽  
Average Fraction ◽  
Qinghai Tibet Plateau

A pioneering rapid and direct measurement of dissolved 222Rn in the field has been used here to explore interaction between surface and groundwater in the source area of the Yellow River (SAYR). The results indicate average 222Rn activity of 2,371 Bq/m3 in surface water and 27,835 Bq/m3 in groundwater. The high 222Rn activity (up to 9,133 Bq/m3) found in the southeast part of the SAYR suggests possible influence of permafrost on the exchange between surface water and groundwater. The remarkable contrast among the different samples of a stream in the Shuangchagou basin, a typical basin in the SAYR, clearly indicates groundwater infiltration along the north tributary and occurrence of groundwater end-member in the south tributary. Considering no 222Rn decay and atmospheric evasion, the daily average fraction of groundwater input to the surface water through the end-member in a location (S1) is estimated at 19%. Despite the up to 40% uncertainty, this is the first estimate of a reference value for groundwater input in this basin and which can be improved in the future with more samples and measurements. 222Rn can be a rapid and easily measured tracer of surface water–groundwater interaction for future investigation in the Qinghai-Tibet Plateau.

Landform-related permafrost characteristics in the source area of the Yellow River, eastern Qinghai-Tibet Plateau

Geomorphology ◽  
2016 ◽  
Vol 269 ◽  
pp. 104-111 ◽  
Author(s):  
Jing Li ◽  
Yu Sheng ◽  
Jichun Wu ◽  
Ziliang Feng ◽  
Zuojun Ning ◽  
...  
Keyword(s):  
Yellow River ◽  
Source Area ◽  
Tibet Plateau ◽  
The Yellow River ◽  
Qinghai Tibet Plateau

scholarly journals Expected changes in future temperature extremes and their elevation dependency over the Yellow River source region

2012 ◽  
Vol 9 (12) ◽  
pp. 13609-13634
Author(s):  
Y. Hu ◽  
S. Maskey ◽  
S. Uhlenbrook
Keyword(s):  
Interannual Variability ◽  
Yellow River ◽  
Source Region ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
The Yellow River ◽  
Hot Days ◽  
Yellow River Source ◽  
Temperature Indices ◽  
Ipcc Sres

Abstract. Using the Statistical DownScaling Model (SDSM) and the outputs from two global climate models we investigate possible changes in mean and extreme temperature indices and their elevation dependency over the Yellow River source region for the period 2081–2100 under the IPCC SRES A2, A1B and B1 emission scenarios. Changes in interannual variability of mean and extreme temperature indices are also analyzed. The validation results show that SDSM performs better in reproducing the maximum temperature-related indices than the minimum temperature-related indices. The projections show that by the end of the 21st century all parts of the study region may experience increases in both mean and extreme temperature in all seasons, along with an increase in the frequency of hot days and warm nights and with a decrease in frost days. Interannual variability increases in all seasons for the frequency of hot days and warm nights and in spring for frost days while it decreases for frost days in summer. Autumn demonstrates pronounced elevation-dependent changes in which six out of eight indices show significant increasing changes with elevation.

Evaluation of groundwater discharge into surface water by using Radon-222 in the Source Area of the Yellow River, Qinghai-Tibet Plateau

2018 ◽  
Vol 192 ◽  
pp. 257-266 ◽  
Author(s):  
Peng Yi ◽  
Huan Luo ◽  
Li Chen ◽  
Zhongbo Yu ◽  
Huijun Jin ◽  
...  
Keyword(s):  
Surface Water ◽  
Yellow River ◽  
Groundwater Discharge ◽  
Source Area ◽  
Tibet Plateau ◽  
The Yellow River ◽  
Qinghai Tibet Plateau

scholarly journals Impacts of the Two Biggest Lakes on Local Temperature and Precipitation in the Yellow River Source Region of the Tibetan Plateau

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Lijuan Wen ◽  
Shihua Lv ◽  
Zhaoguo Li ◽  
Lin Zhao ◽  
Nidhi Nagabhatla
Keyword(s):  
Tibetan Plateau ◽  
Yellow River ◽  
Source Region ◽  
Maximum Temperature ◽  
The Yellow River ◽  
The Tibetan Plateau ◽  
Lake Area ◽  
Local Climate ◽  
Community Land Model ◽  
Yellow River Source

The Tibetan Plateau harbors thousands of lakes; however few studies focus on impacts of lakes on local climate in the region. To investigate and quantify impacts of the two biggest lakes (Ngoring Lake and Gyaring Lake) of the Yellow River source region in the Tibetan Plateau on local climate, two simulations (with and without the two large lakes) from May 2010 to July 2011 are performed and analyzed using the WRF-CLM model (the weather research and forecasting model coupled with the community land model). Differences between simulated results show that the WRF-CLM model could provide realistic reproduction of surface observations and has better simulation after considering lakes. Lakes mostly reduce the maximum temperature all year round and increase the minimum temperature except in March due to the large heat capacity that makes lakes absorb (release) more energy for the same temperature change compared to land. Lakes increase precipitation over the lake area and in the nearby region, mostly during 02–14 BT (Beijing Time) of July to October when the warm lake surface induces the low level horizontal convergence and updraft over lake and provides energy and vapor to benefit the development of the convection for precipitation.

Sign in / Sign up

Export Citation Format

Share Document