Spatio-temporal variability behavior of land surface soil water content in shrub- and grass-land

Hu, Wei; Shao, Mingan; Han, Fengpeng; Reichardt, Klaus

doi:10.1016/j.geoderma.2011.02.008

Cited by 80 publications

(38 citation statements)

References 47 publications

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“…While the highest soil moisture value of C. korshinskii was found in the surface layers, greater coefficients of variation were also observed in these layers (Table 3), similar to several other studies [34,35]. Large variations in SMC occurred on the surface as it was exposed to greater changes in the precipitation, temperature, and aeration [36].…”

Section: Spatial Variation Of Smc and Relationships Between Precipitasupporting

confidence: 85%

Spatial Variations of Soil Moisture under Caragana korshinskii Kom. from Different Precipitation Zones: Field Based Analysis in the Loess Plateau, China

Liu¹,

Zhao²,

Wang³

et al. 2016

Forests

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Soil moisture scarcity has become the major limiting factor of vegetation restoration in the Loess Plateau of China. The aim of this study is: (i) to compare the spatial distribution of deep (up to 5 m) soil moisture content (SMC) beneath the introduced shrub Caragana korshinskii Kom. under different precipitation zones in the Loess Plateau and (ii) to investigate the impacts of environmental factors on soil moisture variability. Soil samples were taken under C. korshinskii from three precipitation zones . We found that the highest soil moisture value was in the 0-0.1 m layer with a large coefficient of variation. The soil water storage under different precipitation zones increased following the increase of precipitation (i.e., Semiarid-350 < Semiarid-410 < Semiarid-470), although the degree of SMC variation was different for different precipitation zones. The SMC in the Semiarid-350 zone initially increased with soil depth, and then decreased until it reached the depth of 2.8-m. The SMC in the Semiarid-410 zone showed a decreasing trend from the top soil to 4.2-m depth. The SMC in the Semiarid-470 zone firstly decreased with soil depth, increased, and then decreased until it reached 4.6-m depth. All SMC values then became relatively constant after reaching the 2.8-m, 4.2-m, and 4.6-m depths for Semiarid-350, Semiarid-410, and Semiarid-470, respectively. The low but similar SMC values at the stable layers across the precipitation gradient indicate widespread soil desiccation in this region. Our results suggested that water deficit occurred in all of the three precipitation zones with precipitation, latitude, field capacity, and bulk density as the main environmental variables affecting soil moisture. Considering the correlations between precipitation, SMC and vegetation, appropriate planting density and species selection should be taken into account for introduced vegetation management.

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Section: Spatial Variation Of Smc and Relationships Between Precipitasupporting

confidence: 85%

Spatial Variations of Soil Moisture under Caragana korshinskii Kom. from Different Precipitation Zones: Field Based Analysis in the Loess Plateau, China

Liu¹,

Zhao²,

Wang³

et al. 2016

Forests

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“…Often, wetter conditions corresponded to greater σ 2 n (S tn ), as further indicated by moderate correlation between σ 2 n (S tn ) and S tn (R 2 of 0.51 and 0.38 for the near surface and the root zone, respectively). This was in agreement with others (Gómez-Plaza et al, 2001;Martínez-Fernández and Ceballos, 2003;Hu et al, 2011). Furthermore, there were greater σ 2 n (S tn ) values at the near surface than in the root zone, indicating greater variability of SWC in the near surface.…”

Section: Time-stable Pattern (Mt N ) Space-invariantsupporting

confidence: 92%

“…Along a hillslope of 100 m in length in the Chinese Loess Plateau, SWC of 0-0.06 m was measured 136 times from 25 June 2007 to 30 August 2008 by a Delta-T Devices Theta probe (ML2x) at 51 locations (Hu et al, 2011 (Brocca et al, 2012(Brocca et al, , 2013. The GENCAI area was dominated by grassland with a flat topography, in silty clay soils.…”

Section: Study Area and Data Collectionmentioning

confidence: 99%

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

Cheng

2016

Hydrol. Earth Syst. Sci.

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Abstract. Soil water content (SWC) is crucial to rainfallrunoff 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 spacevariant 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 CaCO 3 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 km 2 ) in Italy was equivalent. The TA model can be used to construct a high-resolution distribution of SWC at small watershed scales from coarseresolution remotely sensed SWC products.

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“…The relationship between CVs and mean VSM varied in different studies: both decreases [21,43,44] and increases of CVs [45,46] with rising mean VSM were reported. In our study, we observed a VSM threshold below which the CVs correlated with the mean VSM positively but above which they correlated negatively.…”

Section: Spatial and Temporal Variability Of Vsmmentioning

confidence: 99%

Spatial Pattern and Temporal Stability of Root-Zone Soil Moisture during Growing Season on a Larch Plantation Hillslope in Northwest China

Liu

Wang

et al. 2018

Forests

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Soil moisture plays a decisive role for tree growth and forest ecosystems services supply in dryland regions. Hence, it is necessary to clarify the spatio-temporal variation of soil moisture under field conditions. This study selected a hillslope in the Liupan Mountains covered by the plantation of Larix principis-rupprechtii Mayr (larch), a main afforestation tree species in north and northwest China. The volumetric soil moisture (VSM) in root zone layers was monitored with a time interval of about 15 days during the growing season (from May to October) in 2016 at 48 points on this hillslope. The aim was to evaluate the spatial pattern and temporal stability of soil moisture at slope scale. The results showed a moderate spatial variability of VSM in each soil layer, with the variation coefficients range of 17.12-22.63%. The spatial variability of VSM showed a dependence on the soil wetness and a threshold effect, it increased with rising VSM until the VSM reached a threshold of about 15%, but thereafter decreased. The mean relative difference (MRD) among the 48 points ranged from −30.56% to 27.20%, −29.89% to 39.58%, and −28.13% to 33.71% for the soil layers of 0-20, 20-40, and 40-60 cm, respectively. The associated standard deviation (SDRD) (and range) was 11.38% (5.20-26.06%), 8.28% (4.64-15.63%), and 6.51% (2.00-14.16%) for the soil layers of 0-20, 20-40, and 40-60 cm, respectively. The high Spearman's rank coefficients (p < 0.05) among the measuring dates at each soil layer indicated that the spatial distribution of VSM in the root zone had strong temporal stability. The decrease of Spearman' rank correlation coefficient and mean SDRD with rising soil depth indicated an increasing temporal stability of VSM with rising soil depth. The mean VSM of the three soil layers on the entire hillslope can be estimated by the direct method (using representative points determined by the index of temporal stability (ITS)) successfully, and these representative points determined by ITS were mainly located at the points with a ratio of field capacity to leaf area index (LAI) close to the slope mean. Moreover, the mean VSM of the three soil layers on the entire hillslope can also be estimated by indirect method (using the time-stable points determined by mean absolute bias error (MABE) and considering the offset between slope mean VSM and observed VSM at time-stable points), and the prediction accuracy of the indirect method was better than the direct method. Significant correlation between MRD and soil bulk density, field capacity, capillary porosity, and LAI were observed for all soil layers, indicating that both the water-retention ability in root zone soil (expressed mainly by field capacity) and water-consumption ability of trees (expressed mainly by canopy LAI) are the main factors controlling the spatial pattern of root-zone VSM on the larch plantation hillslope studied.

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Spatio-temporal variability behavior of land surface soil water content in shrub- and grass-land

Cited by 80 publications

References 47 publications

Spatial Variations of Soil Moisture under Caragana korshinskii Kom. from Different Precipitation Zones: Field Based Analysis in the Loess Plateau, China

Spatial Variations of Soil Moisture under Caragana korshinskii Kom. from Different Precipitation Zones: Field Based Analysis in the Loess Plateau, China

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

Spatial Pattern and Temporal Stability of Root-Zone Soil Moisture during Growing Season on a Larch Plantation Hillslope in Northwest China

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