Spatial variation in arsenic and fluoride concentrations of shallow groundwater from the town of Shahai in the Hetao basin, Inner Mongolia

2012 ◽  
Vol 27 (11) ◽  
pp. 2187-2196 ◽  
Author(s):  
Huaming Guo ◽  
Yang Zhang ◽  
Lina Xing ◽  
Yongfeng Jia
Keyword(s):  
Spatial Variation ◽  
Inner Mongolia ◽  
Shallow Groundwater ◽  
The Town

scholarly journals Spatial variation of plant species richness in a sand dune field of northeastern Inner Mongolia, China

2016 ◽  
Vol 8 (3) ◽  
pp. 434-442
Author(s):  
Jing Wu ◽  
Jianqiang Qian ◽  
Xianzhang Hou ◽  
Carlos A. Busso ◽  
Zhimin Liu ◽  
...  
Keyword(s):  
Species Richness ◽  
Spatial Variation ◽  
Plant Species ◽  
Inner Mongolia ◽  
Sand Dune ◽  
Plant Species Richness ◽  
Dune Field

Spatial Variation of Soil Organic Matter in Gully Bed with the Seabuckthorn Flexible Dam: A Case Study of EG1 in Zhun-Ge-Er County of Inner Mongolia, China

2014 ◽  
Vol 1073-1076 ◽  
pp. 619-627
Author(s):  
Fang She Yang ◽  
Shu Zhen Su ◽  
Juan Juan Zhang ◽  
Ci Fen Bi
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Spatial Autocorrelation ◽  
Spatial Variation ◽  
Inner Mongolia ◽  
Small Scale ◽  
Obvious Effect ◽  
Small Catchment ◽  
Variation Characteristics ◽  
Random Variation

In this paper, based on geostatistics and GIS techniques, spatial variation characteristics of soil organic matter (acronym: SOM) on a small scale were analyzed and discussed in east-one-branch gully (EG1) bed with the seabuckthorn flexible dam and the contrastive gully bed (which is non-vegetated any vegetation) located in zhun-ge-er county, Erdos, inner Mongolia, which belongs to the typical Pisha Sandstone area. The results show that the seabuckthorn can significantly increase SOM in the small catchment gully bed in the Pisha sandstone area, and the mean SOM content in gully bed with the seabuckthorn flexible dam is approximate 1.75 times that in the contrastive gully. Apparent spatial variation characteristics of SOM were found in the gully with the seabuckthorn flexible dam and the contrastive gully bed, moreover, the medium spatial autocorrelation of SOM was detected in gully bed with the seabuckthorn flexible dam, and the spatial variation of SOM was together led to by the structural and random variation at 1-6.5 m range, and of which the random variation accounts for 40%. Additional, the spatial autocorrelation of SOM in the contrastive gully bed is higher, the spatial variation of SOM was dominantly brought about by the structural variation at 1-4.5 m range, and of which the random variation accounts for 37%. Furthermore, the fractal dimension values reveal that dependence of SOM of the gully bed with the seabuckthorn flexible dam on spatial is weaker than that of the contrastive gully bed. It is judged that the seabuckthorn has an obvious effect on spatial distribution patterns and heterogeneity of SOM on a small scale.

scholarly journals Microbial Community in High Arsenic Shallow Groundwater Aquifers in Hetao Basin of Inner Mongolia, China

PLoS ONE ◽  
2015 ◽  
Vol 10 (5) ◽  
pp. e0125844 ◽  
Author(s):  
Ping Li ◽  
Yanhong Wang ◽  
Xinyue Dai ◽  
Rui Zhang ◽  
Zhou Jiang ◽  
...  
Keyword(s):  
Microbial Community ◽  
Inner Mongolia ◽  
Shallow Groundwater ◽  
Groundwater Aquifers ◽  
High Arsenic

Local-scale secondary water resources modulate seasonal water limitation across Africa

2021 ◽  
Author(s):  
Çağlar Küçük ◽  
Sujan Koirala ◽  
Nuno Carvalhais ◽  
Diego G. Miralles ◽  
Markus Reichstein ◽  
...  
Keyword(s):  
Water Resources ◽  
Spatial Variation ◽  
Decay Rate ◽  
Water Availability ◽  
Land Surface ◽  
Spatial Scales ◽  
Shallow Groundwater ◽  
Local Scale ◽  
Gradient Boosting ◽  
Water Limitation

<p>Drylands contribute strongly to global biogeochemical cycles and their variability. While precipitation is the main driver of plant water availability, secondary water resources like shallow groundwater and lateral convergence of soil moisture may play important roles in supporting ecosystems against water limitation at the local scale. Despite their strong relevance, the effects of secondary water resources are often ignored or highly uncertain in studies over large spatial domains. </p><p>Here, we aimed to quantify the degree to which land properties control secondary water resources over water-limited regions in Africa. To do so, we first detected the seasonal decay periods of Fractional Vegetation Cover (FVC) time series from the changes in FVC over time at daily temporal resolution. FVC data is provided by the EUMETSAT from the image acquisitions from the geostationary satellite MSG. We then calculated the seasonal decay rate of FVC (λ) and used it with other climate, land and vegetation properties at 5 km spatial resolution. We hypothesized that any secondary water resource should slow down vegetation decays in drylands. We used gradient boosting machine learning to model λ and constrained the model according to the hypothesis. Finally, we used Shapley additive explanations in order to quantify the effects of land properties on spatial variation of the modelled λ.</p><p>Model output (NSE = 0.55) revealed that over drylands of Africa, ∼1/3 of spatial variation of λ is attributed to land properties, half of which is attributed to direct land effects while the rest is attributed to the land interactions with climate and vegetation. Though at local scales, this attribution gets much stronger over hotspots with strong secondary water resources, i.e., shallow groundwater. Spatially, land attributed variations of λ show that vegetation decays slower in regions with shallow groundwater and faster in regions where land surface is disconnected from the groundwater. Topographic complexity is another important factor, with slower vegetation decay in complex terrain, likely due to enhanced lateral moisture convergence. Moreover, these responses intensify with increasing climatological water limitation. </p><p>We found strong effects of land parameters on seasonal vegetation decay rate, spatially structured but at local scales. This highlights the importance of local scale processes affecting water availability in drylands not only at local but also continental to global scales and shows the need of bridging processes across spatial scales in regional-to-global hydrological and vegetation models.</p>

Time and Space Evolution of Shallow Saline Groudwater Dynamic in Inland Area of Jiyang County，Shandong Province, China

2015 ◽  
Vol 1092-1093 ◽  
pp. 1197-1201
Author(s):  
Feng Juan Zhang ◽  
Li Ting Xing ◽  
Tong Qiang Peng ◽  
Juan Zhou ◽  
Yi Yang
Keyword(s):  
Saline Water ◽  
Shallow Groundwater ◽  
Pumping Test ◽  
Water Area ◽  
Creeping Flow ◽  
Water Testing ◽  
Dynamic Type ◽  
Groundwater Circulation ◽  
The Town

Inland plain shallow saline water has great exploitation potentiality. Based on field water testing, water level monitoring, pumping test, as well as indoor leaching experiment, applying mathematical statistics, Pipers trilinear nomograph and PHREEQC chemistry simulation methods, saline water area of the town of Sungeng Jiyang was studied. The results showed as follows: (1) Inland shallow groundwater presents “weather-evaporative” dynamic type; (2)The shallow saline water and middle-deep groundwater belonging to different flow system; (3) Because of the creeping flow and aqueous medium riched in clay, inland shallow groundwater mineralized significantly. In saline water area inland plain, the unique features of groundwater circulation result in brackish water dynamic relative stability.

Near surface lithology and spatial variation of arsenic in the shallow groundwater: southeastern Bangladesh

2008 ◽  
Vol 56 (8) ◽  
pp. 1687-1695 ◽  
Author(s):  
Mohammad A. Hoque ◽  
Aftab A. Khan ◽  
M. Shamsudduha ◽  
Muhammad S. Hossain ◽  
Tariqul Islam ◽  
...  
Keyword(s):  
Spatial Variation ◽  
Shallow Groundwater ◽  
Near Surface

scholarly journals Study on Spatial-temporal Variation of Atmospheric Pollution in China between 2014 and 2019

2019 ◽  
Author(s):  
Guo Peng ◽  
Umarova Aminat Batalbievna ◽  
Luan Yunqi
Keyword(s):  
Spatial Variation ◽  
Temporal Variation ◽  
Atmospheric Pollution ◽  
Inner Mongolia ◽  
Mass Concentration ◽  
Environmental Governance ◽  
Mainland China ◽  
Temporal Distribution ◽  
Temporal Variations ◽  
Atmospheric Environment

AbstractThe study in this paper reveals that the atmospheric contaminants in mainland China is of concentricity in spatial distribution, persistence in temporal distribution and correlation between different parameters. This spatial-temporal variation law plays an important role in improving and addressing the problem with atmospheric environment of given cities and regions by employing focused and pointed measures. In this paper, seven kinds of atmospheric pollution parameters including PM2.5, PM10, AQI, CO, NO2, O3 and SO2 in 370 Chinese cities from 2014 to 2019 are analyzed based on their hourly mass concentration. The spatial-temporal variations of each parameter in each separated year are obtained by using interpolation calculation towards the annual atmospheric pollution parameters. The results show that higher mass concentration (including the highest mass concentration) of PM2.5, AQI, PM10, CO, NO2, SO2 mainly concentrated in Beijing-Tianjin-Hebei region in the northeast of mainland China and its neighboring regions and Xinjiang region in the northwest of mainland China. The spatial variation of PM2.5, AQI, PM10, CO, NO2, SO2 experienced similar trend. Higher mass concentration (including the highest mass concentration) of O3 mainly concentrated in Qinghai and Inner Mongolia in the central north of mainland China and Shandong on the right side of Beijing-Tianjin-Hebei region. The spatial variation of O3 experienced different trend from that of other parameters. PM2.5, AQI, PM10 indicated increase and decrease, followed by increase and decrease again with time, which was a S-shaped change. Almost the same temporal variation happened to PM2.5, AQI, PM10 and to CO, NO2, SO2, which was opposite to O3. The analysis from the perspective of the annual highest mass concentration of PM2.5, AQI, PM10, NO2 and O3 indicates the atmospheric environment of mainland China had not been authentically improved by 2019. The analysis from the perspective of the annual highest mass concentration of CO and SO2 indicates the atmospheric environment of mainland China had been authentically improved by 2019. What should we do immediately is to strengthen environmental governance and address the source of contamination in Beijing-Tianjin-Hebei region in the northeast of China, Xinjiang region in the northwest of China, Qinghai and Inner Mongolia regions in the central north of China.

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