Efficient prediction of profile mean soil water content for hillslope-scale Caragana korshinskii plantation using temporal stability analysis

CATENA ◽  
2021 ◽  
pp. 105491
Author(s):  
Guohui Wang ◽  
Zhixue Chen ◽  
Yuying Shen ◽  
Xianlong Yang
2016 ◽  
Vol 30 (3) ◽  
pp. 349-357 ◽  
Author(s):  
Aura Pedrera-Parrilla ◽  
Eric C. Brevik ◽  
Juan V. Giráldez ◽  
Karl Vanderlinden

Abstract Understanding of soil spatial variability is needed to delimit areas for precision agriculture. Electromagnetic induction sensors which measure the soil apparent electrical conductivity reflect soil spatial variability. The objectives of this work were to see if a temporally stable component could be found in electrical conductivity, and to see if temporal stability information acquired from several electrical conductivity surveys could be used to better interpret the results of concurrent surveys of electrical conductivity and soil water content. The experimental work was performed in a commercial rainfed olive grove of 6.7 ha in the ‘La Manga’ catchment in SW Spain. Several soil surveys provided gravimetric soil water content and electrical conductivity data. Soil electrical conductivity values were used to spatially delimit three areas in the grove, based on the first principal component, which represented the time-stable dominant spatial electrical conductivity pattern and explained 86% of the total electrical conductivity variance. Significant differences in clay, stone and soil water contents were detected between the three areas. Relationships between electrical conductivity and soil water content were modelled with an exponential model. Parameters from the model showed a strong effect of the first principal component on the relationship between soil water content and electrical conductivity. Overall temporal stability of electrical conductivity reflects soil properties and manifests itself in spatial patterns of soil water content.


2016 ◽  
Vol 20 (1) ◽  
pp. 571-587 ◽  
Author(s):  
W. Hu ◽  
B. C. Si

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.


2020 ◽  
Author(s):  
Yu Zhang ◽  
Xiaoyan Li ◽  
Wei Li ◽  
Weiwei Fang ◽  
Fangzhong Shi

<p>Shrub is the main vegetation type for vegetation restoration in the Loess Plateau, which plays an important role in the regional ecosystem restoration. Study on the relationships between vegetation and soil water of typical shrub ecosystems are significant for the restoration and reconstruction of ecosystems in the Loess Plateau. Three typical shrub (<em>Hippophae rhamnoides</em> Linn., <em>Spiraea pubescens</em> Turcz., and <em>Caragana korshinskii</em> Kom.) ecosystems were chosen in the Loess Plateau. Field experiments were conducted to investigate the factors that influencing the processes of rainfall interception and root uptake of typical shrubs. S-Biome-BGC model was established based on the Biome-BGC model by developing the rainfall interception and soil water movement sub-models. The model was calibrated and verified using field data. The calibrated S-Biome-BGC model was used to simulate the characteristics of leaf area index (<em>LAI</em>), net primary productivity (<em>NPP</em>), soil water content and the interactions among them for the shrub ecosystems along the precipitation gradients in the Loess Plateau, respectively. The results showed that the predictions of the S-Biome-BGC model for soil water content and<em> LAI</em> of typical shrub ecosystems in Loess Plateau were significantly more accurate than that of Biome-BGC model. The simulated <em>RMSE</em> of soil water content decreased from 0.040~0.130 cm<sup>3</sup> cm<sup>-3</sup> to 0.026~0.035 cm<sup>3</sup> cm<sup>-3</sup>, and the simulated <em>RMSE</em> of<em> LAI</em> decreased from 0.37~0.70 m<sup>2</sup> m<sup>-2</sup> to 0.35~0.37 m<sup>2</sup> m<sup>-2</sup>. Therefore, the S-Biome-BGC model can reflect the interaction between plant growth and soil water content in the shrub ecosystems of the Loess Plateau. The S-Biome-BGC model simulation for <em>LAI</em>,<em> NPP</em> and soil water content of the three typical shrubs were significantly different along the precipitation gradients, and increased with annual precipitation together. However, different <em>LAI</em>, <em>NPP</em> and soil water correlations were found under different precipitation gradients.<em> LAI</em> and<em> NPP</em> have significant positive correlations with soil water content in the areas where the annual precipitation is above 460~500 mm that could afford the shrubs growth. The results of the study provide a re-vegetation threshold to guide future re-vegetation activities in the Loess Plateau.</p>


2021 ◽  
Author(s):  
Christine Fischer ◽  
Murray Lark ◽  
Johanna C. Metzger ◽  
Thomas Wutzler ◽  
Anke Hildebrandt

<div> <p>This study investigates whether and how vegetation cover affects the spatial heterogeneity and vertical penetration of water through the Upper Critical Zone (UCZ). We assessed rainfall, throughfall and soil water contents on a 1‐ha temperate mixed beech forest plot in Germany. Throughfall and soil water content in two depths (7.5 cm and 27.5 cm) were measured on an event basis during the 2015 - 2016 growing season in independent high‐resolution stratified random designs. We calculated the increase of soil water content (Δθ) due to the rainfall by the difference between measurements at the beginning (pre-event) and the maximum soil water content after the end of rainfall event (post-event). Since throughfall and soil water content cannot be assessed at the same location, we used kriging to derive the throughfall values at the locations where soil water content was measured. We explore the spatial variation and temporal stability of throughfall and soil water content and evaluate the effects of throughfall, soil properties (field capacity and air capacity), and vegetation parameters (next tree distance) on soil water content variability.</p> <p>Throughfall patterns were related to canopy density although correlation length decreased with increasing event size. Temporal stability was high, leading to persistently high and lower input locations across rainfall events.</p> <p>A linear mixed effect model analysis confirmed that the soil water content increase due to precipitation depended on throughfall patterns, in that more water was stored in the soil where throughfall was enhanced. This was especially the case in large events and in both investigated soil depths. However, we also identified additional factors that enhanced or decreased water storage in the soil, and probably indicate fast drainage and runoff components. Locations with low topsoil water content tended to store less of the available water, indicating the role of preferential flow. In contrast in subsoil, locations with high water content, and probably poor drainage, stored less water, indicating lateral flow. Also, distance to the next tree and air capacity modified soil water storage.</p> <p>Spatial soil water content patterns shortly before a rainfall event (pre-event conditions) seem to be a key factor in soil water content increase, and also explained much of soil water content shortly after the rainfall event. Pre-event soil water content was mostly driven by random local effects, probably microtopography and root water uptake, which were not quantified in this study. The remaining spatial variation was explained by air capacity in both soil layers, indicating the role of macroporosity.</p> <p>Our findings show at the same time systematic patterns of times and locations where the soil capacity to store water is reduced and water probably conducted quickly to greater depth. Not only soil moisture patterns but also deeper percolation may depend on small scale spatial heterogeneity of canopy input patterns.</p> </div>


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