scholarly journals Model test study on the effect of dynamic compaction under low water content

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253981
Author(s):  
Xiaoshuang Zhang ◽  
Min Wang ◽  
Yunshan Han
Keyword(s):  
Energy Level ◽  
Water Content ◽  
Arid Regions ◽  
Cost Effective ◽  
Dynamic Compaction ◽  
Western China ◽  
Treatment Technology ◽  
Optimal Energy ◽  
Test Study ◽  
Η Value

Dynamic compaction is a cost-effective foundation treatment technology, that is widely used in various types and conditions of foundations. However, due to the limitation of natural conditions (water content between 3% and 8%) in north-western China, it is difficult to meet the requirements of the optimal water content during dynamic compaction. To better treat a foundation with a low water content, a series of model tests were carried out by using homemade test equipment to study the influence of the ramming energy and η value on the efficiency of dynamic compaction under a low water content. The results showed that the improvement of the energy level could compensate for the poor effect of dynamic compaction caused by a low water content in arid regions. Compared with that at the optimal water content, the efficiency of dynamic compaction was 58.1% to 66.2% at a low water content and excited the optimal energy level. Increasing the η value was also beneficial to improving the effect of dynamic compaction. Hence, the optimal energy level combined with the appropriate η value is of great merit in treating the foundation of arid regions by using the dynamic compaction method, which provides new parameter suggestions and engineering guidance for dynamic compaction construction in arid areas.

Deep Dynamic Compaction: Practical and Cost-Effective Ground Improvement at the Port of Long Beach

Ports 2013 ◽  
2013 ◽  
Author(s):  
Mariusz P. Sieradzki ◽  
Bartlett W. Patton ◽  
Douglas J. Sereno ◽  
Paul Wehrlen
Keyword(s):  
Ground Improvement ◽  
Cost Effective ◽  
Dynamic Compaction ◽  
Long Beach

scholarly journals Relating surface backscatter response from TRMM Precipitation Radar to soil moisture: results over a semi-arid region

2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using Variable Infiltration Capacity (VIC) model whereas measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.

scholarly journals Responses of runoff to historical and future climate variability over China

2017 ◽  
Author(s):  
Chuanhao Wu ◽  
Bill X. Hu ◽  
Guoru Huang ◽  
Peng Wang ◽  
Kai Xu
Keyword(s):  
Climate Variability ◽  
Arid Regions ◽  
Southern China ◽  
Aridity Index ◽  
Global Climate Models ◽  
Future Climate ◽  
Western China ◽  
Climate Projections ◽  
Positive Contribution ◽  
The Mean

Abstract. China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960–2012) water budget data and climate projections from 28 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.2 to 3.3) and potential evaporation (PET) elasticity (from −2.3 to −0.2) across China. The P elasticity is larger in northeast and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960–2012, the climate contribution to R ranges from −2.4 % a−1 to 3.3 % a−1 across China, with the negative contribution in the North China plain and the positive contribution in western China and some parts of the southwest. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071–2100, the mean annual P will likely increase in most parts of China, especially the western regions, while the mean annual PET will likely increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China will likely become wetter and drier in the period 2071–2100, respectively (relative to the baseline 1971–2000).

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