Spatio-temporal Variation of Soil Respiration and Its Driving Factors in Semi-arid Regions of North China

2018 ◽  
Vol 28 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Xinhua Zeng ◽  
Yigang Song ◽  
Wanjun Zhang ◽  
Shengbing He
Keyword(s):  
Soil Respiration ◽  
Temporal Variation ◽  
Arid Regions ◽  
North China ◽  
Driving Factors ◽  
Spatio Temporal ◽  
Semi Arid

Partitioning soil respiration in two typical forests in semi-arid regions, North China

CATENA ◽  
2016 ◽  
Vol 147 ◽  
pp. 536-544 ◽  
Author(s):  
Xinhua Zeng ◽  
Yigang Song ◽  
Chunmin Zeng ◽  
Wanjun Zhang ◽  
Shengbing He
Keyword(s):  
Soil Respiration ◽  
Arid Regions ◽  
North China ◽  
Semi Arid

scholarly journals Spatio-temporal variation and driving factors analysis of PM2.5 health risks in Chinese cities

2021 ◽  
Vol 129 ◽  
pp. 107937
Author(s):  
Qian Liu ◽  
Zheyu Zhang ◽  
Chaofeng Shao ◽  
Run Zhao ◽  
Yang Guan ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Health Risks ◽  
Driving Factors ◽  
Chinese Cities ◽  
Factors Analysis ◽  
Spatio Temporal

Spatial distribution and temporal variation of reference evapotranspiration in arid and semi-arid regions of Iran

2011 ◽  
Vol 26 (4) ◽  
pp. 500-512 ◽  
Author(s):  
Hossein Tabari ◽  
Ali Aeini ◽  
P. Hosseinzadeh Talaee ◽  
B. Shifteh Some'e
Keyword(s):  
Spatial Distribution ◽  
Temporal Variation ◽  
Arid Regions ◽  
Reference Evapotranspiration ◽  
Semi Arid

scholarly journals Spatial and temporal variation of precipitation characteristics in the semiarid region of Xi'an, northwest China

2021 ◽  
Author(s):  
Hao Han ◽  
Jingming Hou ◽  
Rengui Jiang ◽  
Jiahui Gong ◽  
Ganggang Bai ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Arid Regions ◽  
Resource Planning ◽  
Northwest China ◽  
Annual Precipitation ◽  
Spatial And Temporal Variation ◽  
Semiarid Region ◽  
Monthly Precipitation ◽  
Xi’An City ◽  
Semi Arid

Abstract Precipitation variations mostly affect the water resource planning in semi-arid regions of northwest China. The objective of this study is to quantitatively explore the spatial and temporal variations of precipitation in different time scales in Xi'an city area. The Mann–Kendall test and wavelet analysis methods were applied to analyze the precipitation variability. In terms of temporal variation of precipitation, the results indicated that the annual precipitation exhibited a significant decreasing trend during 1951–2018. Except for summer precipitation representing a slightly increasing trend, the other seasonal precipitations had a similar decreasing trend to annual precipitation throughout 1951–2018. The monthly precipitation had different change trends, showing the precipitation from June to September could account for 58.4% of the total annual precipitation. In addition, it was clear that annual precipitation had a significant periodic change, with the periods of 6, 13, 19, and 27 years. For the spatial variation of precipitation during 1961–2018, the results showed that annual and seasonal precipitation exhibited obvious spatial differences, indicating an increasing spatial trend from north to south. Thus, understanding the precipitation variation in Xi'an city can provide a theoretical foundation of future water resources management for other cities in semi-arid regions of northwest China.

scholarly journals Spatio-Temporal Variation and Controlling Factors of Water Quality in Yongding River Replenished by Reclaimed Water in Beijing, North China

Water ◽  
2017 ◽  
Vol 9 (7) ◽  
pp. 453 ◽  
Author(s):  
Yilei Yu ◽  
Muyuan Ma ◽  
Fandong Zheng ◽  
Licai Liu ◽  
Nana Zhao ◽  
...  
Keyword(s):  
Water Quality ◽  
Temporal Variation ◽  
North China ◽  
Reclaimed Water ◽  
Controlling Factors ◽  
Spatio Temporal ◽  
Yongding River

scholarly journals Extending the Spatio-Temporal Applicability of DISPATCH Soil Moisture Downscaling Algorithm: A Study Case Using SMAP, MODIS and Sentinel-3 Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Nitu Ojha ◽  
Olivier Merlin ◽  
Christophe Suere ◽  
Maria José Escorihuela
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Arid Regions ◽  
Data Sets ◽  
Sparse Vegetation ◽  
Thermal Data ◽  
Spatio Temporal ◽  
Temporal Coverage ◽  
Semi Arid

DISPATCH is a disaggregation algorithm of the low-resolution soil moisture (SM) estimates derived from passive microwave observations. It provides disaggregated SM data at typically 1 km resolution by using the soil evaporative efficiency (SEE) estimated from optical/thermal data collected around solar noon. DISPATCH is based on the relationship between the evapo-transpiration rate and the surface SM under non-energy-limited conditions and hence is well adapted for semi-arid regions with generally low cloud cover and sparse vegetation. The objective of this paper is to extend the spatio-temporal coverage of DISPATCH data by 1) including more densely vegetated areas and 2) assessing the usefulness of thermal data collected earlier in the morning. Especially, we evaluate the performance of the Temperature Vegetation Dryness Index (TVDI) instead of SEE in the DISPATCH algorithm over vegetated areas (called vegetation-extended DISPATCH) and we quantify the increase in coverage using Sentinel-3 (overpass at around 09:30 am) instead of MODIS (overpass at around 10:30 am and 1:30 pm for Terra and Aqua, respectively) data. In this study, DISPATCH is applied to 36 km resolution Soil Moisture Active and Passive SM data over three 50 km by 50 km areas in Spain and France to assess the effectiveness of the approach over temperate and semi-arid regions. The use of TVDI within DISPATCH increases the coverage of disaggregated images by 9 and 14% over the temperate and semi-arid sites, respectively. Moreover, including the vegetated pixels in the validation areas increases the overall correlation between satellite and in situ SM from 0.36 to 0.43 and from 0.41 to 0.79 for the temperate and semi-arid regions, respectively. The use of Sentinel-3 can increase the spatio-temporal coverage by up to 44% over the considered MODIS tile, while the overlapping disaggregated data sets derived from Sentinel-3 and MODIS land surface temperature data are strongly correlated (around 0.7). Additionally, the correlation between satellite and in situ SM is significantly better for DISPATCH (0.39–0.80) than for the Copernicus Sentinel-1-based (−0.03 to 0.69) and SMAP/S1 (0.37–0.74) product over the three studies (temperate and semi-arid) areas, with an increase in yearly valid retrievals for the vegetation-extended DISPATCH algorithm.

Spatio-temporal variation of potential evapotranspiration and climatic drivers in the Jing-Jin-Ji region, North China

2018 ◽  
Vol 256-257 ◽  
pp. 75-83 ◽  
Author(s):  
Jingyan Han ◽  
Jianhua Wang ◽  
Yong Zhao ◽  
Qingming Wang ◽  
Bing Zhang ◽  
...  
Keyword(s):  
Temporal Variation ◽  
North China ◽  
Potential Evapotranspiration ◽  
Climatic Drivers ◽  
Spatio Temporal
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