Changes in wind erosion climatic erosivity in northern China from 1981-2016: a comparison of two climate/weather factors of wind erosion models

2021 ◽  
Vol 83 ◽  
pp. 133-146
Author(s):  
F Zhang ◽  
J Wang ◽  
X Zou ◽  
R Mao ◽  
DY Gong ◽  
...  
Keyword(s):  
Wind Erosion ◽  
Qaidam Basin ◽  
Dust Emission ◽  
Northern China ◽  
Northwest China ◽  
Gobi Desert ◽  
Weather Factors ◽  
Weather Factor ◽  
Increasing Trend ◽  
Erosion Equation

Wind erosion is largely determined by wind erosion climatic erosivity. In this study, we examined changes in wind erosion climatic erosivity during 4 seasons across northern China from 1981-2016 using 2 models: the wind erosion climatic erosivity of the Wind Erosion Equation (WEQ) model and the weather factor from the Revised Wind Erosion Equation (RWEQ) model. Results showed that wind erosion climatic erosivity derived from the 2 models was highest in spring and lowest in winter with high values over the Kumtag Desert, the Qaidam Basin, the boundary between Mongolia and China, and the Hulunbuir Sandy Land. In spring and summer, wind erosion climatic erosivity showed decreasing trends in whole of northern China from 1981-2016, whereas there was an increasing trend in wind erosion climatic erosivity over the Gobi Desert from 1992-2011. For the weather factor of the RWEQ model, the difference between northern Northwest China and the Gobi Desert and eastern-northern China was much larger than that of the wind erosion climatic erosivity of the WEQ model. In addition, in contrast to a decreasing trend in the weather factor of the RWEQ model over southern Northwest China during spring and summer from 1981-2016, the wind erosion climatic erosivity of the WEQ model showed a decreasing trend for 1981-1992 and an increasing trend for 1992-2011 over southern Northwest China. According to a comparison between dust emission and wind erosion climatic erosivity, the 2 models have the ability to project changes in future wind erosion in northern China.

scholarly journals Comparison of the Spatial Wind Erosion Patterns of Erosion Risk Mapping and Quantitative Modeling in Eastern Austria

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 974
Author(s):  
Simon Scheper ◽  
Thomas Weninger ◽  
Barbara Kitzler ◽  
Lenka Lackóová ◽  
Wim Cornelis ◽  
...  
Keyword(s):  
Soil Loss ◽  
Wind Erosion ◽  
Large Scale ◽  
Pannonian Basin ◽  
Target Area ◽  
Erosion Risk ◽  
Additional Information ◽  
Weather Factor ◽  
Not At Risk ◽  
Erosion Equation

Various large-scale risk maps show that the eastern part of Austria, in particular the Pannonian Basin, is one of the regions in Europe most vulnerable to wind erosion. However, comprehensive assessments of the severity and the extent of wind erosion risk are still lacking for this region. This study aimed to prove the results of large-scale maps by developing high-resolution maps of wind erosion risk for the target area. For this, we applied a qualitative soil erosion assessment (DIN 19706) with lower data requirements and a more data-demanding revised wind erosion equation (RWEQ) within a GIS application to evaluate the process of assessing wind erosion risk. Both models defined similar risk areas, although the assignment of severity classes differed. Most agricultural fields in the study area were classified as not at risk to wind erosion (DIN 19706), whereas the mean annual soil loss rate modeled by RWEQ was 3.7 t ha−1 yr−1. August was the month with the highest modeled soil loss (average of 0.49 t ha−1 month−1), due to a low percentage of vegetation cover and a relatively high weather factor combining wind speed and soil moisture effects. Based on the results, DIN 19706 is suitable for a general classification of wind erosion-prone areas, while RWEQ can derive additional information such as seasonal distribution and soil loss rates besides the spatial extents of wind erosion.

Temporal and spatial variations of sandstorm and the related meteorological influences over northern China in the 21st century

2021 ◽  
Author(s):  
Jie Yang ◽  
Tianliang Zhao
Keyword(s):  
Land Surface ◽  
Source Region ◽  
Northern China ◽  
Northwest China ◽  
Gobi Desert ◽  
Taklimakan Desert ◽  
Observation Data ◽  
Average Wind Speed ◽  
Modis Ndvi ◽  
Temporal And Spatial

<p>In this study, we used the sandstorm data of 233 meteorological stations in northern China, conventional meteorological observation data and MODIS-NDVI data in the 40 years from 1980 to 2019 to analyze the spatio-temporal variation of sandstorms in northern China and its related meteorological effects in this century.</p><p>The results show that: 1) The average number of sandstorm days in northern China has been fluctuating and decreasing since the beginning of this century, and increasing from 2017 to 2019. Spring is the main season of dust storm, and the springtime proportion of sandstorm days decreases year by year. 2) In the 1980s and 1990s, sandstorms covered almost covered the whole northwest region; Since the beginning of this century, the range of sandstorm days in the whole Northwest China has shown an obvious decadal downward trend. The spatial pattern of sandstorm days in northern China has been shrinking and moving westward since 2000, and the dominant position of the Gobi Desert in the Asian dust source region has been decreasing year by year. The high sandstorm days were located in the Taklimakan Desert with the increasing trend of sandstorm days year by year. 3) The temporal and spatial variation of sandstorm days in northern China is closely related to the increase of vegetation cover with the greenness and wetness of the land surface, the decreases of average wind speed and gale days, and the significant increase of annual precipitation in northern China after 2000.</p>

scholarly journals Analysis of Spatiotemporal Groundwater-Storage Variations in China from GRACE

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2378
Author(s):  
Fangfang Liu ◽  
Ping Kang ◽  
Haitao Zhu ◽  
Jiafu Han ◽  
Yaohuan Huang
Keyword(s):  
Southern China ◽  
Northern China ◽  
Northwest China ◽  
Tibet Plateau ◽  
Groundwater Depletion ◽  
Positive Trend ◽  
Groundwater Storage ◽  
Increasing Trend ◽  
Groundwater Consumption ◽  
National Perspective

In China, where some regions are over-reliant on groundwater, groundwater consumption is faster than replenishment, which results in a continuous decrease in the groundwater level. Here, we applied spatial and temporal methods to analyze the spatiotemporal variations in groundwater in China from GRACE, GRACE-FO, and GLDAS data. From a national perspective, groundwater storage showed a decreasing trend in northern China and an increasing trend in southern China. The results showed that the rates of groundwater depletion in North China, the Loess Plateau, and Northwest China were −10.09 ± 0.94, −10.05 ± 1.05, and –4.91 ± 0.28 mm y−1 equivalent height of water from 2003 to 2019, respectively. Furthermore, the groundwater in South China, the middle-lower Yangtze River, and the Ch-Yu region had a positive trend, with rates of 7.26 ± 1.51, 7.73 ± 1.35, and 3.61 ± 0.53 mm y−1 equivalent height of water, respectively. We also found that groundwater storage fluctuated slightly before 2016 on the Qinhai-Tibet Plateau and in Northeast China and decreased significantly after 2016. The Yun-Gui Plateau had a fluctuating trend. Investigating the spatiotemporal variation in groundwater storage in China can provide data for initiating regional ecological and environmental protection.

scholarly journals Vegetation Change and Its Response to Climate Extremes in the Arid Region of Northwest China

2021 ◽  
Vol 13 (7) ◽  
pp. 1230
Author(s):  
Simeng Wang ◽  
Qihang Liu ◽  
Chang Huang
Keyword(s):  
Arid Region ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Pearson Correlation ◽  
Time Lag ◽  
Climate Extremes ◽  
Northwest China ◽  
Precipitation Extremes ◽  
Temperature Extremes ◽  
Increasing Trend

Changes in climate extremes have a profound impact on vegetation growth. In this study, we employed the Moderate Resolution Imaging Spectroradiometer (MODIS) and a recently published climate extremes dataset (HadEX3) to study the temporal and spatial evolution of vegetation cover, and its responses to climate extremes in the arid region of northwest China (ARNC). Mann-Kendall test, Anomaly analysis, Pearson correlation analysis, Time lag cross-correlation method, and Least absolute shrinkage and selection operator logistic regression (Lasso) were conducted to quantitatively analyze the response characteristics between Normalized Difference Vegetation Index (NDVI) and climate extremes from 2000 to 2018. The results showed that: (1) The vegetation in the ARNC had a fluctuating upward trend, with vegetation significantly increasing in Xinjiang Tianshan, Altai Mountain, and Tarim Basin, and decreasing in the central inland desert. (2) Temperature extremes showed an increasing trend, with extremely high-temperature events increasing and extremely low-temperature events decreasing. Precipitation extremes events also exhibited a slightly increasing trend. (3) NDVI was overall positively correlated with the climate extremes indices (CEIs), although both positive and negative correlations spatially coexisted. (4) The responses of NDVI and climate extremes showed time lag effects and spatial differences in the growing period. (5) Precipitation extremes were closely related to NDVI than temperature extremes according to Lasso modeling results. This study provides a reference for understanding vegetation variations and their response to climate extremes in arid regions.

Exploring Weather Data to Predict Activity Attendance in Event-based Social Network

2021 ◽  
Vol 15 (2) ◽  
pp. 1-25
Author(s):  
Jifeng Zhang ◽  
Wenjun Jiang ◽  
Jinrui Zhang ◽  
Jie Wu ◽  
Guojun Wang
Keyword(s):  
Real Life ◽  
Prediction Performance ◽  
Weather Data ◽  
Gradient Boosting ◽  
User Interest ◽  
Weather Factors ◽  
Event Duration ◽  
Outdoor Activities ◽  
Weather Factor ◽  
Event Based

Event-based social networks (EBSNs) connect online and offline lives. They allow online users with similar interests to get together in real life. Attendance prediction for activities in EBSNs has attracted a lot of attention and several factors have been studied. However, the prediction accuracy is not very good for some special activities, such as outdoor activities. Moreover, a very important factor, the weather, has not been well exploited. In this work, we strive to understand how the weather factor impacts activity attendance, and we explore it to improve attendance prediction from the organizer’s view. First, we classify activities into two categories: the outdoor and the indoor activities. We study the different ways that weather factors may impact these two kinds of activities. We also introduce a new factor of event duration. By integrating the above factors with user interest and user-event distance, we build a model of attendance prediction with the weather named GBT-W , based on the Gradient Boosting Tree. Furthermore, we develop a platform to help event organizers estimate the possible number of activity attendance with different settings (e.g., different weather, location) to effectively plan their events. We conduct extensive experiments, and the results show that our method has a better prediction performance on both the outdoor and the indoor activities, which validates the reasonability of considering weather and duration.

scholarly journals Wind speed in spring dominated the decrease in wind erosion across the Horqin Sandy Land in northern China

2021 ◽  
Vol 127 ◽  
pp. 107599
Author(s):  
Hanbing Zhang ◽  
Jian Peng ◽  
Chaonan Zhao ◽  
Zihan Xu ◽  
Jianquan Dong ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Erosion ◽  
Northern China ◽  
Horqin Sandy Land ◽  
Sandy Land

Trace and rare earth element geochemistry of Jurassic mudstones in the northern Qaidam Basin, northwest China

Geochemistry ◽  
2012 ◽  
Vol 72 (3) ◽  
pp. 245-252 ◽  
Author(s):  
Jian Cao ◽  
Ming Wu ◽  
Yan Chen ◽  
Kai Hu ◽  
Lizeng Bian ◽  
...  
Keyword(s):  
Rare Earth ◽  
Rare Earth Element ◽  
Earth Element ◽  
Qaidam Basin ◽  
Northwest China ◽  
Element Geochemistry

Geophysical Variables and Behavior: II. Weather Factors as Predictors of Local Social Indicators of Maladaptation in Two Non-Urban Areas

1978 ◽  
Vol 43 (2) ◽  
pp. 427-434 ◽  
Author(s):  
George Banziger ◽  
Karen Owens
Keyword(s):  
Urban Areas ◽  
Social Indicator ◽  
Social Indicators ◽  
Geographical Area ◽  
Drunk Driving ◽  
Medical Patient ◽  
Stepwise Multiple Regression ◽  
Weather Factors ◽  
Weather Factor ◽  
Telephone Hotline

The relative predictive strengths of eight weather factors were examined using as separate dependent variables monthly figures for community mental health intake, welfare caseload, calls to a telephone hotline, medical patient caseload, felony arrests, juvenile complaints, drunk-driving arrests, and mortality rates in two non-urban areas of Ohio. Z-score transformations of subjective discomfort of the weather factors as indicated by three independent samples were analyzed with a stepwise multiple regression. With the exception of hotline calls, each of the social indicators in the two localities was significantly predicted by a different weather factor, and the weather factors, taken together, accounted for about 10% of the variance of each social indicator. For each geographical area, combined weather factors accounted for no more than 30% of the variance of any local social indicator. Problems of overgeneralization and exaggeration of the effects of weather factors on social indicators in previous studies were discussed. A balanced approach to behavioral effects of geophysical variables must be achieved (Ammons, 1978).

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