Impact classification of future land use and climate changes on flow regimes in the Yellow River Source Region, China

Author(s):  
Wei Wang ◽  
Yongyong Zhang ◽  
Xin Geng ◽  
Qiuhong Tang
Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2243
Author(s):  
Mingyang Tian ◽  
Xiankun Yang ◽  
Lishan Ran ◽  
Yuanrong Su ◽  
Lingyu Li ◽  
...  

Under the context of climate change, studying CO2 emissions in alpine rivers is important because of the large carbon storage in these terrestrial ecosystems. In this study, riverine partial pressure of CO2 (pCO2) and CO2 emission flux (FCO2) in the Yellow River source region (YRSR) under different landcover types, including glaciers, permafrost, peatlands, and grasslands, were systematically investigated in April, June, August, and October 2016. Relevant chemical and environmental parameters were analyzed to explore the primary controlling factors. The results showed that most of the rivers in the YRSR were net CO2 source, with the pCO2 ranging from 181 to 2441 μatm and the FCO2 ranging from −50 to 1574 mmol m−2 d−1. Both pCO2 and FCO2 showed strong spatial and temporal variations. The highest average FCO2 was observed in August, while the lowest average was observed in June. Spatially, the lowest FCO2 were observed in the permafrost regions while the highest FCO2 were observed in peatland. By integrating seasonal changes of the water surface area, total CO2 efflux was estimated to be 0.30 Tg C year−1. This indicates that the YRSR was a net carbon source for the atmosphere, which contradicts previous studies that conclude the YRSR as a carbon sink. More frequent measurements of CO2 fluxes, particularly through several diel cycles, are necessary to confirm this conclusion. Furthermore, our study suggested that the riverine dissolved organic carbon (DOC) in permafrost (5.0 ± 2.4 mg L−1) is possibly derived from old carbon released from permafrost melting, which is equivalent to that in peatland regions (5.1 ± 3.7 mg L−1). The degradation of DOC may have played an important role in supporting riverine CO2, especially in permafrost and glacier-covered regions. The percent coverage of corresponding land cover types is a good indicator for estimating riverine pCO2 in the YRSR. In view of the extensive distribution of alpine rivers in the world and their sensitivity to climate change, future studies on dynamics of stream water pCO2 and CO2 outgassing are strongly needed to better understand the global carbon cycle.


2018 ◽  
Vol 246 ◽  
pp. 01089
Author(s):  
Yongqiang Wang ◽  
Zhiming Liu ◽  
Zhe Yuan ◽  
Jijun Xu ◽  
Jin Chen

Taking the source region of the Yellow River as an example, this paper first introduces the theory of energy value and its basic steps. Then combined with the Yellow River source area, the variation characteristics of precipitation and surface water resources from 1961 to 2011 in the Yellow River source area were analyzed, and both of them showed a trend of decreasing year by year. On this basis, using the theory of energy value, combined with relevant parameters, taking 2011 year as an example, further analyses the chemical energy and solar energy of water resources in the Yellow River source area, and gives the value of surface water resources. The value of water resources per unit is 1.59 yuan/m3. For the Yellow River source area, the overall value of water resources for the whole basin in 2011 is 33.55 billion yuan. It can provide a reference for the analysis of the value of surface water resources in the Yellow River Basin.


2015 ◽  
Vol 11 (2) ◽  
pp. 249-260 ◽  
Author(s):  
Yi-ping Fang ◽  
Chen Zhao ◽  
Yong-jian Ding ◽  
Da-he Qin ◽  
Jia-li Huang

2017 ◽  
Vol 605-606 ◽  
pp. 830-841 ◽  
Author(s):  
Yue Qin ◽  
Dawen Yang ◽  
Bing Gao ◽  
Taihua Wang ◽  
Jinsong Chen ◽  
...  

2013 ◽  
Vol 17 (7) ◽  
pp. 2501-2514 ◽  
Author(s):  
Y. Hu ◽  
S. Maskey ◽  
S. Uhlenbrook

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 two future periods 2046–2065 and 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 middle and 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. By the end of the 21st century, 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 around six out of eight indices show significant increasing changes with elevation.


2012 ◽  
Vol 9 (12) ◽  
pp. 13609-13634
Author(s):  
Y. Hu ◽  
S. Maskey ◽  
S. Uhlenbrook

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.


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