Detection of the main stream of the Yellow River based on spectral feature and the dynamic transmission model

2008 ◽  
Author(s):  
Hong-Wei She ◽  
Yan-Ning Zhang ◽  
Xue-Gong Liu ◽  
Na Zhao
Keyword(s):  
Yellow River ◽  
Spectral Feature ◽  
Transmission Model ◽  
The Yellow River ◽  
Main Stream ◽  
Dynamic Transmission Model

scholarly journals Analysis of precipitation cycles based on MEM in the Yellow River basin

2015 ◽  
Vol 368 ◽  
pp. 114-119
Author(s):  
Z. Li ◽  
T. Cheng ◽  
H. Song ◽  
Z. Li ◽  
J. Yu
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
Entropy Method ◽  
The Yellow River ◽  
Main Stream ◽  
Monthly Precipitation ◽  
Annual Cycles ◽  
The Yellow River Basin ◽  
Precipitation Cycles

Abstract. Using the monthly precipitation series of 32 meteorological stations in the Yellow River basin from 1951 to 2003, the precipitation cycles were discussed using the Maximum Entropy Method (MEM), the spatial distribution of the precipitation cycles were analysed, and the possible driving factors of the cycles investigated. The results show that the precipitation in the Yellow River has decadal (60a), inter-decadal (25a and 14a) and inter-annual cycles (9a and 3a). The main oscillations over the whole basin are 3a and 9a. There are clearer inter-decadal variations in the riverhead area with much greater water resources, and north of the region of LanHe main stream. The decadal signals are detected in the inner area with less precipitation and Wei River basin. These differences are possibly related to some physical processes, such as the mutual action of sea and atmosphere, and solar activities.

scholarly journals Spatial-Temporal Characteristics of Agricultural Greenhouse Gases Emissions of the Main Stream Area of the Yellow River Basin in Gansu, China

Atmosphere ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1296
Author(s):  
Lili Pu ◽  
Xingpeng Chen ◽  
Chengpeng Lu ◽  
Li Jiang ◽  
Binbin Ma ◽  
...  
Keyword(s):  
River Basin ◽  
Yellow River ◽  
Ghg Emissions ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Main Stream ◽  
Rate Of Increase ◽  
Three Stages ◽  
Emissions Intensity ◽  
The Yellow River Basin

In 2021, The People’s Republic of China proposed goals for peaking carbon dioxide emissions before 2030 and carbon neutrality before 2060, in the 15 counties (districts) of the Main Stream Area of the Yellow River Basin in Gansu that plays an important role in ecological protection and green development. Next the CO2 equivalents were converted according to the IPCC2 standard, the total agricultural GHG emissions was calculated, the relationship with the agricultural output value was analyzed, and the discretization of the space was analyzed by the coefficient of variation and standard deviation. Firstly, the total agricultural GHG emissions in 15 counties (districts) of the Main Stream Area of the Yellow River Basin increased 55.54% in 2000–2019, and 2.35% annually, roughly divided into three stages: the rapid growth period (2000–2008), the slow decline period (2009–2014) and the rapid decline period (2015–2019). The economic efficiency is significantly improved, with an average annual decline of 6.49%, roughly divided into three stages: the slow-descent stage (2000–2004), the period of slow-growth stage (2005–2008) and the period of fast-decline (2009–2019). Secondly, based on the characteristics of the total GHG emissions, Maqu County has the largest GHG emissions increase, from 26.8842 kt in 2000 to 38.9603 kt, in 2019, an increase of 44.92%, while the smallest GHG emissions, in Anning District, decreased 87.33% from 111 t in 2000 to 14.1 t in 2019; In the rate of increase in the total GHG emissions, Dongxiang County had the largest rate of increase from 2000 to 2019, an increase of 160.28% and an average annual increase of 4.90%. The smallest rate of decrease in GHG emissions was seen in Chengguan District, where they decreased 92.11% from 2000 to 2019, an average annual decrease of 11.93%. The characteristics of agricultural GHG emissions intensity is a significant declining trending and agricultural production efficiency has been significantly improved. Finally, to provide a basis for the formulation of differentiated agricultural energy conservation and emissions reduction policies, reduce agricultural GHG emissions intensity and reduce the use efficiency of resources by formulating differentiated emission targets, tasks and incentive measures.

scholarly journals Identification Sources and High-Risk Areas of Sediment Heavy Metals in the Yellow River by Geographical Detector Method

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1103
Author(s):  
Jianxiu Hao ◽  
Jun Ren ◽  
Hongbing Fang ◽  
Ling Tao
Keyword(s):  
Heavy Metals ◽  
Influencing Factors ◽  
Inner Mongolia ◽  
Yellow River ◽  
Anthropogenic Factors ◽  
The Yellow River ◽  
Main Stream ◽  
Risk Area ◽  
Geographical Detector ◽  
Risk Areas

In order to determine the key influencing factors, risk areas, and source pathways of heavy metals in the sediment of the Yellow River, 37 samples were collected in the surface sediment (0–5 cm) of the Inner Mongolia section of the Yellow River main stream for the determination of heavy metals copper (Cu), nickel (Ni), zinc (Zn), chromium (Cr), lead (Pb), and cadmium (Cd). Based on the geographical detector model (GDM) and ArcGIS 10.2 software, this paper selected 6 heavy metals and 15 influencing factors, including 8 natural factors and 7 anthropogenic factors, to detect key influencing factors, risk areas, and sources of heavy metals. The results showed that: (1) The average contents of heavy metals Cr and Cd in the sediments exceeded the average value in soil, the world average concentration in the shales, and the first-level standard of soil environmental quality in China, and they were the main risk metals; (2) Vegetation coverage (VC) was the largest influencing factor for the spatial distribution of heavy metals in the sediment, followed by per capita income (PI), and land use type (LUT) and road network density (RD) were smaller influencing factors. The interactions of the factors were enhanced; (3) The Wuhai section for a risk area was mainly polluted by Cd and Pb, which were caused by atmospheric deposition and industrial emission. The Baotou section for a risk area was mainly polluted by Cr, which mainly originated from river transportation and industrial discharge. The conclusions can provide a scientific basis for the environmental protection and management of the different areas in the Inner Mongolia section of the Yellow River.

GEOMORPHOLOGICAL CHARACTERISTICS OF A TRANSECT FROM THE YELLOW RIVER TO THE IRON PAGODA IN KAIFENG CITY, CHINA

2018 ◽  
Vol 14 (1) ◽  
pp. 245-254 ◽  
Author(s):  
Yang LI ◽  
◽  
Zhixiang XIE ◽  
Fen QIN ◽  
Yaochen QIN ◽  
...  
Keyword(s):  
Yellow River ◽  
The Yellow River ◽  
Kaifeng City

Incentives in Water Management Reform: Case Study in the Yellow River Basin

Water Nepal ◽  
2004 ◽  
Vol 11 (2) ◽  
Author(s):  
Jinxia Wang ◽  
Zhigang Xu ◽  
Jikun Huang ◽  
Scott Rozelle
Keyword(s):  
Water Management ◽  
River Basin ◽  
Yellow River ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Management Reform ◽  
The Yellow River Basin

Characteristic of Land Cover Changes in the Yellow River Headwaters Region over the Past 30 Years

2011 ◽  
Vol 13 (3) ◽  
pp. 289-296 ◽  
Author(s):  
Longfei BING ◽  
Quanqin SHAO ◽  
Jiyuan LIU
Keyword(s):  
Land Cover ◽  
Yellow River ◽  
The Yellow River ◽  
Land Cover Changes ◽  
The Past
Sign in / Sign up

Export Citation Format

Share Document