scholarly journals Use of Google Earth Engine to generate a 20-year 1 km 1 km monthly air temperature product over Yellow River Basin

2021 ◽  
pp. 1-1
Author(s):  
Meiling Gao ◽  
Zhenhong Li ◽  
Zhenyu Tan ◽  
Huifang Li ◽  
Jianbing Peng
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Yellow River ◽  
Yellow River Basin ◽  
Google Earth ◽  
Google Earth Engine

scholarly journals Dynamic Changes of Soil Erosion in the Taohe River Basin Using the RUSLE Model and Google Earth Engine

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1293 ◽  
Author(s):  
Hao Wang ◽  
Hu Zhao
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Water Conservation ◽  
Yellow River ◽  
Google Earth ◽  
Large Area ◽  
Conservation Area ◽  
Conservation Practice ◽  
Rusle Model ◽  
Google Earth Engine

The Taohe River Basin is the largest tributary and an important water conservation area in the upper reaches of the Yellow River. In order to investigate the status of soil erosion in this region, we conducted a research of soil erosion. In our study, several parameters of the revised universal soil loss equation (RUSLE) model are extracted by using Google Earth Engine. The soil erosion modulus of the Taohe River Basin was calculated based on multi-source data, and the spatio-temporal variation characteristics of the soil erosion intensity were analyzed. The results showed the following: (1) the average soil erosion modulus of the Taohe River Basin in 2000, 2005, 2010, 2015 and 2018 were 1424, 1195, 1129, 1099 and 1124 t·ha−1·year−1, respectively, and the overall downward trend was obvious. (2) The ranges of soil erosion in the Taohe River Basin in 2000, 2005, 2010, 2015 and 2018 are basically the same—mainly with slight erosion—and the soil erosion in the middle and lower reaches was more serious. (3) When dealing with the vegetation cover factor and conservation practice factor in the RUSLE model, Google Earth Engine provided a new approach for soil erosion investigation and monitoring over a large area.

scholarly journals Estimation of Heating-Up Effecting in the Yellow River Basin Based on MODIS Data

2021 ◽  
Author(s):  
Ziwu Pan ◽  
Jun Zhu ◽  
Fen Qin
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Land Surface ◽  
Yellow River ◽  
Yellow River Basin ◽  
Temperature Data ◽  
Tibet Plateau ◽  
The Yellow River ◽  
The Yellow River Basin ◽  
Heating Up

Abstract Using MODIS land surface temperature data, air temperature data and elevation data from 2000 to 2015 in the Yellow River Basin. The GWR analysis method with high accuracy was chosen to establish the regression model of plateau air temperature, land surface temperature and altitude. In the 12-month GWR regression model, the determination coefficient (Adjusted R2) was above 0.95 or more (0.959-0.980) and the root-mean-square error (RMSE)was between 0.740 and 1.029°C. Depending on the model, the air temperature of the Yellow River Basin is estimated and the accuracy is verified. On this basis, the average monthly air temperature in the basin is converted to altitudes of 4500m and 5000m, and the heating-up effects of various shapes in the basin are compared and discussed. The results show that: (1) Using the GWR method, combined with the observation data of the ground station, the accuracy of the air temperature estimation in the Yellow River Basin can be increased to 0.740°C; (2) According to the estimated annual variation of the spatial distribution of the 12-month average temperature, in the upper of the Tibet Plateau, the Huangshui Valley and the Gannan Plateau have lower annual air temperatures and less spatial distribution. While the air temperature in the northeast of the upstream Inner Mongolia plateau was higher, which was related to the rapid drying temperature rise near the desert. The change of mean monthly temperature in the middle and lower reaches is relatively high and the change is small, which is closely linked to the fact that it is located in the low-elevation area of the basin plain and has perennial light and heat.(3) The heating-up effect in the Yellow River Basin is outstanding. It is preliminaries estimated that at the same altitude, the Tibet Plateau is about 1.5~8°C higher than the Loess Plateau, and about 6~13°C higher than the North China Plain.

scholarly journals Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0258549
Author(s):  
Ziwu Pan ◽  
Jun Zhu ◽  
Junjie Liu ◽  
Jiangyan Gu ◽  
Zhenzhen Liu ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
River Basin ◽  
Air Temperature ◽  
Yellow River ◽  
Mass Effect ◽  
Yellow River Basin ◽  
The Yellow River ◽  
Air Temperatures ◽  
Source Data ◽  
The Yellow River Basin

Quantitative studies of the multiple factors influencing the mountain-mass effect, which causes higher temperatures in mountainous than non-mountainous regions, remain insufficient. This study estimated the air temperature in the Yellow River Basin, which spans three different elevation ranges, using multi-source data to address the uneven distribution of regional meteorological stations. The differences in mountain-mass effect for different geomorphic regions at the same altitude were then compared. The Manner–Kendall nonparametric test was used to analyse time series changes in temperature. Moreover, we employed the geographically weighted regression (GWR) model, with MODIS land-surface and air-temperature data, station-based meteorological data, vertical temperature gradients corresponding to the 2000–2015 period, and elevation data, to estimate the correlation between monthly mean surface temperature and air temperature in the Yellow River Basin. The following major results were obtained. (1) The GWR method and ground station-based observations enhanced the accuracy of air-temperature estimates with an error of only ± 0.74°C. (2) The estimated annual variations in the spatial distributions of 12-month average temperatures showed that the upper Tibetan Plateau is characterised by low annual air temperatures with a narrow spatial distribution, whereas north-eastern areas upstream of the Inner Mongolia Plateau are characterised by higher air temperatures. Changes in the average monthly air temperature were also high in the middle and lower reaches, with a narrow spatial distribution. (3) Considering the seasonal variation in the temperature lapse rate, the mountain-mass effect in the Yellow River Basin was very high. In the middle of each season, the variation of air temperature at a given altitude over the Tibetan Plateau was higher than that over the Loess Plateau and Jinji Mountain. The results of this study reveal the unique temperature characteristics of the Yellow River Basin according to its geomorphology. Furthermore, this research contributes to quantifying mountain-mass effects.

scholarly journals Carbon Storage Change Analysis and Emission Reduction Suggestions under Land Use Transition: A Case Study of Henan Province, China

2021 ◽  
Vol 18 (4) ◽  
pp. 1844
Author(s):  
Dongyang Xiao ◽  
Haipeng Niu ◽  
Jin Guo ◽  
Suxia Zhao ◽  
Liangxin Fan
Keyword(s):  
Land Use ◽  
River Basin ◽  
Yangtze River ◽  
Carbon Emission ◽  
Yellow River ◽  
Yangtze River Basin ◽  
Yellow River Basin ◽  
River Basins ◽  
Henan Province ◽  
Huai River

The significant spatial heterogeneity among river basin ecosystems makes it difficult for local governments to carry out comprehensive governance for different river basins in a special administrative region spanning multi-river basins. However, there are few studies on the construction of a comprehensive governance mechanism for multi-river basins at the provincial level. To fill this gap, this paper took Henan Province of China, which straddles four river basins, as the study region. The chord diagram, overlay analysis, and carbon emission models were applied to the remote sensing data of land use to analyze the temporal and spatial patterns of carbon storage caused by land-use changes in Henan Province from 1990 to 2018 to reflect the heterogeneity of the contribution of the four basins to human activities and economic development. The results revealed that food security land in the four basins decreased, while production and living land increased. Ecological conservation land was increased over time in the Yangtze River Basin. In addition, the conversion from food security land to production and living land was the common characteristic for the four basins. Carbon emission in Henan increased from 134.46 million tons in 1990 to 553.58 million tons in 2018, while its carbon absorption was relatively stable (1.67–1.69 million tons between 1990 and 2018). The carbon emitted in the Huai River Basin was the main contributor to Henan Province’s total carbon emission. The carbon absorption in Yellow River Basin and Yangtze River Basin had an obvious spatial agglomeration effect. Finally, considering the current need of land spatial planning in China and the goal of carbon neutrality by 2060 set by the Chinese government, we suggested that carbon sequestration capacity should be further strengthened in Yellow River Basin and Yangtze River Basin based on their respective ecological resource advantages. For future development in Hai River Basin and Huai River Basin, coordinating the spatial allocation of urban scale and urban green space to build an ecological city is a key direction to embark upon.

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