Dynamic soil moisture monitoring in shendong mining area using Temperature Vegetation Dryness Index

Author(s):  
Ying Liu ◽  
Weiyu Ma ◽  
Hui Yue ◽  
Hu Zhao
2020 ◽  
Vol 13 (1) ◽  
pp. 122
Author(s):  
Liangliang Tao ◽  
Dongryeol Ryu ◽  
Andrew Western ◽  
Dale Boyd

The temperature vegetation dryness index (TVDI) has been commonly implemented to estimate regional soil moisture in arid and semi-arid regions. However, the parameterization of the dry edge in the TVDI model is performed with a constraint to define the maximum water stress conditions. Mismatch of the spatial scale between visible and thermal bands retrieved from remotely sensed data and terrain variations also affect the effectiveness of the TVDI. Therefore, this study proposed a new drought index named the condition vegetation drought index (CVDI) to monitor the temporal and spatial variations of soil moisture status by substituting the land surface temperature (LST) with the modified perpendicular drought index (MPDI). In situ soil moisture observations at crop and pasture sites in Victoria were used to validate the effectiveness of the CVDI. The results indicate that the dry and wet edges in the parameterization scheme of the CVDI formed a better-defined trapezoid shape than that of the TVDI. Compared with the MPDI and TVDI for soil moisture monitoring at crop sites, the CVDI exhibited a performance superior to the MPDI and TVDI in most days where the coefficients of determination (R2) achieved can reach to 0.67 on DOY023, 137, 274 and 0.71 on DOY 322 and reproduced more accurate spatial and seasonal variation of soil moisture. Moreover, the CVDI showed higher correlation with the Australian Water Resource Assessment Landscape (AWRA-L) soil moisture product on temporal scales. The R2 can reach to 0.69 and the root mean square error (RMSE) is also much better than that of the MPDI and TVDI. Overall, it can be concluded that the CVDI appears to be a feasible method and can be successfully used in regional soil moisture monitoring.


2013 ◽  
Vol 77 (6) ◽  
pp. 1888-1919 ◽  
Author(s):  
Tyson E. Ochsner ◽  
Michael H. Cosh ◽  
Richard H. Cuenca ◽  
Wouter A. Dorigo ◽  
Clara S. Draper ◽  
...  

2012 ◽  
Vol 48 (7) ◽  
Author(s):  
A. B. Smith ◽  
J. P. Walker ◽  
A. W. Western ◽  
R. I. Young ◽  
K. M. Ellett ◽  
...  

2021 ◽  
pp. 113227
Author(s):  
Yee Jher Chan ◽  
Adam R. Carr ◽  
Subhanwit Roy ◽  
Caden M. Washburn ◽  
Nathan Neihart ◽  
...  

2012 ◽  
Vol 29 (7) ◽  
pp. 933-943 ◽  
Author(s):  
Weinan Pan ◽  
R. P. Boyles ◽  
J. G. White ◽  
J. L. Heitman

Abstract Soil moisture has important implications for meteorology, climatology, hydrology, and agriculture. This has led to growing interest in development of in situ soil moisture monitoring networks. Measurement interpretation is severely limited without soil property data. In North Carolina, soil moisture has been monitored since 1999 as a routine parameter in the statewide Environment and Climate Observing Network (ECONet), but with little soils information available for ECONet sites. The objective of this paper is to provide soils data for ECONet development. The authors studied soil physical properties at 27 ECONet sites and generated a database with 13 soil physical parameters, including sand, silt, and clay contents; bulk density; total porosity; saturated hydraulic conductivity; air-dried water content; and water retention at six pressures. Soil properties were highly variable among individual ECONet sites [coefficients of variation (CVs) ranging from 12% to 80%]. This wide range of properties suggests very different behavior among sites with respect to soil moisture. A principal component analysis indicated parameter groupings associated primarily with soil texture, bulk density, and air-dried water content accounted for 80% of the total variance in the dataset. These results suggested that a few specific soil properties could be measured to provide an understanding of differences in sites with respect to major soil properties. The authors also illustrate how the measured soil properties have been used to develop new soil moisture products and data screening for the North Carolina ECONet. The methods, analysis, and results presented here have applications to North Carolina and for other regions with heterogeneous soils where soil moisture monitoring is valuable.


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