Intra-storm time stability analysis of surface soil water content

Geoderma ◽  
2019 ◽  
Vol 352 ◽  
pp. 33-37 ◽  
Author(s):  
Xiaodong Gao ◽  
Xining Zhao ◽  
Daili Pan ◽  
Liuyang Yu ◽  
Pute Wu
Keyword(s):  
Stability Analysis ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Surface Soil ◽  
Time Stability

scholarly journals Estimating spatially distributed soil water content at small watershed scales based on decomposition of temporal anomaly and time stability analysis

2016 ◽  
Vol 20 (1) ◽  
pp. 571-587 ◽  
Author(s):  
W. Hu ◽  
B. C. Si
Keyword(s):  
Stability Analysis ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Spatial Patterns ◽  
Watershed Scale ◽  
Small Watershed ◽  
Time Stability ◽  
Spatially Distributed ◽  
Space Variant

Abstract. Soil water content (SWC) is crucial to rainfall-runoff response at the watershed scale. A model was used to decompose the spatiotemporal SWC into a time-stable pattern (i.e., temporal mean), a space-invariant temporal anomaly, and a space-variant temporal anomaly. The space-variant temporal anomaly was further decomposed using the empirical orthogonal function (EOF) for estimating spatially distributed SWC. This model was compared to a previous model that decomposes the spatiotemporal SWC into a spatial mean and a spatial anomaly, with the latter being further decomposed using the EOF. These two models are termed the temporal anomaly (TA) model and spatial anomaly (SA) model, respectively. We aimed to test the hypothesis that underlying (i.e., time-invariant) spatial patterns exist in the space-variant temporal anomaly at the small watershed scale, and to examine the advantages of the TA model over the SA model in terms of the estimation of spatially distributed SWC. For this purpose, a data set of near surface (0–0.2 m) and root zone (0–1.0 m) SWC, at a small watershed scale in the Canadian Prairies, was analyzed. Results showed that underlying spatial patterns exist in the space-variant temporal anomaly because of the permanent controls of static factors such as depth to the CaCO3 layer and organic carbon content. Combined with time stability analysis, the TA model improved the estimation of spatially distributed SWC over the SA model, especially for dry conditions. Further application of these two models demonstrated that the TA model outperformed the SA model at a hillslope in the Chinese Loess Plateau, but the performance of these two models in the GENCAI network (∼  250 km2) in Italy was equivalent. The TA model can be used to construct a high-resolution distribution of SWC at small watershed scales from coarse-resolution remotely sensed SWC products.

scholarly journals Estimating spatially distributed soil water content at small watershed scales based on decomposition of temporal anomaly and time stability analysis

2015 ◽  
Vol 12 (7) ◽  
pp. 6467-6503 ◽  
Author(s):  
W. Hu ◽  
B. C. Si
Keyword(s):  
Stability Analysis ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Spatial Patterns ◽  
Watershed Scale ◽  
Small Watershed ◽  
Time Stability ◽  
Spatially Distributed ◽  
Space Variant

Abstract. Soil water content (SWC) at watershed scales is crucial to rainfall–runoff response. A model was used to decompose spatiotemporal SWC into time-stable pattern (i.e., temporal mean), space-invariant temporal anomaly, and space-variant temporal anomaly. This model was compared with a previous model that decomposes spatiotemporal SWC into spatial mean and spatial anomaly. The space-variant temporal anomaly or spatial anomaly was further decomposed using the empirical orthogonal function for estimating spatially distributed SWC. These two models are termed temporal anomaly (TA) model and spatial anomaly (SA) model, respectively. We aimed to test the hypothesis that underlying (i.e., time-invariant) spatial patterns exist in the space-variant temporal anomaly at the small watershed scale, and to examine the advantages of the TA model over the SA model in terms of estimation of spatially distributed SWC. For this purpose, a SWC dataset of near surface (0–0.2 m) and root zone (0–1.0 m) from a small watershed scale in the Canadian prairies was analyzed. Results showed that underlying spatial patterns exist in the space-variant temporal anomaly because of the permanent controls of "static" factors such as depth to the CaCO3 layer and organic carbon content. Combined with time stability analysis, the TA model improved estimation of spatially distributed SWC over the SA model because the latter failed to capture the space-variant temporal anomaly which accounted for non-negligible amounts of spatial variance in SWC. The outperformance was greater when SWC deviated from intermediate conditions, especially for dry conditions. Therefore, the TA model has potential to construct a spatially distributed SWC at watershed scales from remote sensed SWC.

scholarly journals Time Stability of Soil Water Content

10.5772/52469 ◽  
2013 ◽  
Author(s):  
Wei Hu ◽  
Lindsay K. ◽  
Asim Biswas ◽  
Bing Cheng
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Time Stability

Using soil surface gray level to determine surface soil water content

2010 ◽  
Vol 53 (10) ◽  
pp. 1527-1532 ◽  
Author(s):  
YuanJun Zhu ◽  
YunQiang Wang ◽  
MingAn Shao
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Surface Soil ◽  
Soil Surface ◽  
Gray Level

Evaluating Surface-Soil Water Content by Measuring Reflectance

1975 ◽  
Vol 39 (2) ◽  
pp. 238-242 ◽  
Author(s):  
E. L. Skidmore ◽  
J. D. Dickerson ◽  
H. Schimmelpfennig
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Surface Soil
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