Soil moisture variability and land use in a seasonally arid environment

Williams, Andy; Ternan, J. L.; Fitzjohn, C.; Alba, S. de; Pérez‐González, Alfredo

doi:10.1002/hyp.1120

Cited by 40 publications

(25 citation statements)

References 15 publications

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“…The different land use types were expected to induce different MTSDs because the processes affecting soil water depended greatly on the type, coverage, and root distribution of the vegetation comprising a given land use type (Williams et al, 2003;Yang et al, 2012;Zucco et al, 2014). Hydrological (e.g., interception of rain by vegetation, surface runoff, infiltration, and redistribution) and ecological (e.g., sap flow, root water uptake, and hydraulic redistribution) processes under different land use types could lead to different soil-water regimes ( (Table 2).…”

Section: Temporal Stability Of Aws 1mmentioning

confidence: 99%

Vertical distribution and temporal stability of soil water in 21-m profiles under different land uses on the Loess Plateau in China

Wang

Zhu

et al. 2015

Journal of Hydrology

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Keywords:Deep soil Land use MABE Temporal stability Most temporally stable depth The Chinese Loess Plateau s u m m a r y Deep soil-water content (SWC) plays a crucial role in water-limited terrestrial ecosystems, because plant roots can extract soil water from depths of 20 m or more. The distribution of soil water and its temporal variation in deep (>5 m) soil profiles are not completely understood, partly due to the time and labor needed for their determination. We examined the vertical distribution patterns and temporal stabilities of soil water in 21-m soil profiles for two years under four typical land use types in the Liudaogou watershed of the Chinese Loess Plateau (CLP). The SWCs exhibited considerable variability over both depth and time under farmland, natural grassland, planted grassland, and shrubland. The soil profile could be partitioned into an active layer (0-2 m) and a relatively stable layer (2-21 m) based on the amount of temporal change in SWC. The mean available soil water contents (AWCs) among the land use types in the depth-time domain differed significantly (P < 0.05), and followed the order: farmland (7.1%) > natural grassland (6.5%) > planted grassland (5.7%) > shrubland (4.9%). The mean available soil water storage for each 1-m-depth (AWS 1m ) in the 0-21 m profile, in the time domain, ranged from 50.3 to 71.4 mm among the four land use types. Within the 21-m profile, as the depths of sub-profiles increased from 3 m to 21 m, the most temporally stable depths (MTSDs) of AWS 1m tended to become deeper in a step-like manner, producing ranges of MTSDs of 3-18 m, 2-15 m, 2-9 m, and 3-20 m under farmland, natural grassland, planted grassland, and shrubland, respectively. The ability of the MTSDs to estimate the mean AWS 1m in a soil profile was generally acceptable for each sub-profile, as indicated by the RMSD and RBIAS values obtained from a validation dataset, which ranged from 3.6 to 7.7 mm and from 0.07 to 0.13, respectively, among the four land use types. The mean AWS 1m within the 21-m profile could, in general, be accurately estimated by measuring AWC to a depth of only 18 m based on the temporal stability analysis. Land use greatly affected the vertical distributions and temporal stabilities of the AWC in the deep soils. The knowledge obtained from this information is vital for the sustainable use of water resources, rational management of various land uses, and scientific determinations of soil water in deep soils on the CLP and possibly in other fragile ecosystems covered by deep soils around the world.

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Section: Temporal Stability Of Aws 1mmentioning

confidence: 99%

Vertical distribution and temporal stability of soil water in 21-m profiles under different land uses on the Loess Plateau in China

Wang

Zhu

et al. 2015

Journal of Hydrology

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“…As reviewed in Brocca et al (2007), soil moisture statistical properties can be impacted by lateral redistribution (Moore et al, 1988;Williams et al, 2003), radiation (Moore et al, 1993;Western et al, 1999), soil characteristics (Hu et al, 1997;Famiglietti et al, 1998;Seyfried, 1998), vegetation characteristics (Qiu et al, 2001;Hupet and Vanclooster, 2002), elevation above the drainage channel (Crave and GascuelOdoux, 1997), downslope gradient (Merot et al, 1995), bedrock topography (Chaplot and Walter, 2003), specific upslope area (Brocca et al, 2007), and landscape unit (Park and van de Giesen, 2004;Wilson et al, 2004). Famiglietti et al (1998) argued that under wet conditions, the best correlation of soil moisture variability was with soil porosity and hydraulic conductivity, and under dry conditions, with relative elevation, aspect, and clay content.…”

Section: Introductionmentioning

confidence: 99%

Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations

Riley

2014

Hydrol. Earth Syst. Sci.

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Abstract. Watershed-scale hydrological and biogeochemical models are usually discretized at resolutions coarser than where significant heterogeneities in topography, abiotic factors (e.g., soil properties), and biotic (e.g., vegetation) factors exist. Here we report on a method to use fine-scale (220 m grid cells) hydrological model predictions to build reduced-order models of the statistical properties of nearsurface soil moisture at coarse resolution (2 5 times coarser, ∼ 7 km). We applied a watershed-scale hydrological model (PAWS-CLM4) that has been previously tested in several watersheds. Using these simulations, we developed simple, relatively accurate (R 2 ∼ 0.7-0.8), reduced-order models for the relationship between mean and higher-order moments of near-surface soil moisture during the nonfrozen periods over five years. When applied to transient predictions, soil moisture variance and skewness were relatively accurately predicted (R 2 ∼ 0.7-0.8), while the kurtosis was less accurately predicted (R 2 ∼ 0.5). We also tested 16 system attributes hypothesized to explain the negative relationship between soil moisture mean and variance toward the wetter end of the distribution and found that, in the model, 59 % of the variance of this relationship can be explained by the elevation gradient convolved with mean evapotranspiration. We did not find significant relationships between the time rate of change of soil moisture variance and covariances between mean moisture and evapotranspiration, drainage, or soil properties, as has been reported in other modeling studies. As seen in previous observational studies, the predicted soil moisture skewness was predominantly positive and negative in drier and wetter regions, respectively. In individual coarse-resolution grid cells, the transition between positive and negative skewness occurred at a mean soil moisture of ∼ 0.25-0.3. The type of numerical modeling experiments presented here can improve understanding of the causes of soil moisture heterogeneity across scales, and inform the types of observations required to more accurately represent what is often unresolved spatial heterogeneity in regional and global hydrological models.

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“…Identification and prediction of soil moisture controls at different scales thus remain important in a wide range of agronomic, hydrological, and environmental studies [4][5][6]. Understanding and characterizing spatio-temporal variability of soil water content presents one of the major challenges in modern soil physics [4,[7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Agro-ecosystem Model AGROTOOL Coupled with GIS for Simulation of the Spatial Variability of the Soil Hydrophysical Properties

Vladimir¹,

Vitaly²,

Nikolay³

et al. 2015

Proceedings of the AASRI International Conference on Industrial Electronics and Applications (2015)

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Abstract-The approach to taking into account the spatial variability of soil properties during decision making in agroecosystem management has presented. The approach is based on the quantitative indicators of plants production process (wheat crop) obtained by using a dynamic model of the agricultural plants production process AGROTOOL. The studies were conducted in the environment of a special software package that is based on the integration of the dynamic model AGROTOOL and GIS. Computer simulations data allowed identifying the conditions under which the influence of the soil hydrophysical characteristics variability on the crop production exists or disappears.

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Soil moisture variability and land use in a seasonally arid environment

Cited by 40 publications

References 15 publications

Vertical distribution and temporal stability of soil water in 21-m profiles under different land uses on the Loess Plateau in China

Vertical distribution and temporal stability of soil water in 21-m profiles under different land uses on the Loess Plateau in China

Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations

Agro-ecosystem Model AGROTOOL Coupled with GIS for Simulation of the Spatial Variability of the Soil Hydrophysical Properties

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