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 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.

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 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

scholarly journals Overstory–Understory Vegetation Cover and Soil Water Content Observations in Western Juniper Woodlands: A Paired Watershed Study in Central Oregon, USA

Forests ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 151 ◽  
Author(s):  
Grace Ray ◽  
Carlos G. Ochoa ◽  
Tim Deboodt ◽  
Ricardo Mata-Gonzalez
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Soil Texture ◽  
Canopy Cover ◽  
Understory Vegetation ◽  
Watershed Scale ◽  
Shrub Cover ◽  
Western Juniper ◽  
Tree Canopy Cover

The effects of western juniper (Juniperus occidentalis) control on understory vegetation and soil water content were studied at the watershed-scale. Seasonal differences in topsoil (12 cm) water content, as affected by vegetation structure and soil texture, were evaluated in a 96-ha untreated watershed and in a 116-ha watershed where 90% juniper was removed in 2005. A watershed-scale characterization of vegetation canopy cover and soil texture was completed to determine some of the potential driving factors influencing topsoil water content fluctuations throughout dry and wet seasons for approximately one year (2014–2015). We found greater perennial grass, annual grass, and shrub cover in the treated watershed. Forb cover was no different between watersheds, and as expected, tree canopy cover was greater in the untreated watershed. Results also show that on average, topsoil water content was 1% to 3% greater in the treated watershed. The exception was during one of the wettest months (March) evaluated, when soil water content in the untreated watershed exceeded that of the treated by <2%. It was noted that soil water content levels that accumulated in areas near valley bottoms and streams were greater in the treated watershed than in the untreated toward the end of the study in late spring. This is consistent with results obtained from a more recent study where we documented an increase in subsurface flow residence time in the treated watershed. Overall, even though average soil water content differences between watersheds were not starkly different, the fact that more herbaceous vegetation and shrub cover were found in the treated watershed led us to conclude that the long-term effects of juniper removal on soil water content redistribution throughout the landscape may be beneficial towards restoring important ecohydrologic connections in these semiarid ecosystems of central Oregon.

scholarly journals Soil water content evaluation considering time-invariant spatial pattern and space-variant temporal change

2013 ◽  
Vol 10 (10) ◽  
pp. 12829-12860
Author(s):  
W. Hu ◽  
B. C. Si
Keyword(s):  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Spatial Patterns ◽  
Root Zone ◽  
Temporal Changes ◽  
Near Surface ◽  
Varying Coefficients ◽  
Space And Time ◽  
Time Invariant

Abstract. Soil water content (SWC) varies in space and time. The objective of this study was to evaluate soil water content distribution using a statistical model. The model divides spatial SWC series into time-invariant spatial patterns, space-invariant temporal changes, and space- and time-dependent redistribution terms. The redistribution term is responsible for the temporal changes in spatial patterns of SWC. An empirical orthogonal function was used to separate the total variations of redistribution terms into the sum of the product of spatial structures (EOFs) and temporally-varying coefficients (ECs). Model performance was evaluated using SWC data of near-surface (0–0.2 m) and root-zone (0–1.0 m) from a Canadian Prairie landscape. Three significant EOFs were identified for redistribution term for both soil layers. EOF1 dominated the variations of redistribution terms and it resulted in more changes (recharge or discharge) in SWC at wetter locations. Depth to CaCO3 layer and organic carbon were the two most important controlling factors of EOF1, and together, they explained over 80% of the variations in EOF1. Weak correlation existed between either EOF2 or EOF3 and the observed factors. A reasonable prediction of SWC distribution was obtained with this model using cross validation. The model performed better in the root zone than in the near surface, and it outperformed conventional EOF method in case soil moisture deviated from the average conditions.

Sign in / Sign up

Export Citation Format

Share Document