Soil Moisture Patterns Research Articles

Influences of temperature and precipitation on soil moisture in Anuradhapura District

Impact of climate change on soil properties has been studied by several researchers. However, the influence of soil moisture has received little attention as a key component of agricultural climate change. Using meteorological data in Anuradhapura District in Sri Lanka (one of the main paddy producers in the island nation), this study evaluated the impact of climate change on soil moisture. Monthly soil moisture values were calculated using a water balance approach. Analysis of historical data (from 1950 to 2016) indicate a strong seasonal influence on soil moisture patterns. Correlation analysis between paddy yield and physical variables indicated that soil moisture is a stronger covariate than either temperature or precipitation alone. A good relationship between soil moisture and the El Nino effect was not identified. Scenario analyses indicated that soil moisture is more sensitive to precipitation changes than temperature changes in Anuradhapura. This study highlights the value of continuous monitoring of soil moisture along with other climatic data for insights regarding mitigation of future agricultural concerns.

Soil resource availability and its effect on the ecophysiology and establishment of Stipa pulchra

The objectives of this study were to (i) determine the importance of soil moisture and soil nitrogen availability as resource requirements for the establishment of Stipa pulchra, (ii) to examine how changes in slope within a local habitat can affect the accumulation of soil moisture and soil nitrogen and (iii) to measure the physiological responses of S. pulchra among such slope locations. The field experiment occurred in the San Jose Hills of Southern California on the California State Polytechnic University, Pomona campus. Plots were established within three different slope locations (shallow, moderate and steep) within four separate canyons. Three nitrogen treatments (ambient, addition and removal) were replicated within each slope location for all four canyons, and five S. pulchra plants were planted in each plot. Soil nitrogen accumulation and soil moisture, as well as other abiotic variables, were measured across the varied slope locations and nitrogen treatments. We measured the cover, stress, and reproduction of S. pulchra plants for 2 years and used a mesocosm experiment to determine how S. pulchra responds to varying water and nitrogen availability. Stipa pulchra had a strong positive response to the wettest watering treatment and a weak response to nitrogen addition in the mesocosm experiment. In the field experiment, S. pulchra responded positively in moderate slope locations and did not respond to nitrogen treatments, possibly due to drought. Field patterns of soil moisture were driven by slope, soil compaction and solar radiation. Soil nitrogen accumulation did not vary among slope locations. For restoration of S. pulchra, priority should be placed on managing soil moisture availability and determining suitable edaphic factors.

V2Karst V1.1: a parsimonious large-scale integrated vegetation–recharge model to simulate the impact of climate and land cover change in karst regions

Abstract. Karst aquifers are an important source of drinking water in many regions of the world. Karst areas are highly permeable and produce large amounts of groundwater recharge, while surface runoff is often negligible. As a result, recharge in these systems may have a different sensitivity to climate and land cover changes than in other less permeable systems. However, little is known about the combined impact of climate and land cover changes in karst areas at large scales. In particular, the representation of land cover, and its controls on evapotranspiration, has been very limited in previous karst hydrological models. In this study, we address this gap (1) by introducing the first large-scale hydrological model including an explicit representation of both karst and land cover properties, and (2) by providing an in-depth analysis of the model's recharge production behaviour. To achieve these aims, we replace the empirical approach to evapotranspiration estimation of a previous large-scale karst recharge model (VarKarst) with an explicit, mechanistic and parsimonious approach in the new model (V2Karst V1.1). We demonstrate the plausibility of V2Karst simulations at four carbonate rock FLUXNET sites by assessing the model's ability to reproduce observed evapotranspiration and soil moisture patterns and by showing that the controlling modelled processes are in line with expectations. Additional virtual experiments with synthetic input data systematically explore the sensitivities of recharge to precipitation characteristics (overall amount and temporal distribution) and land cover properties. This approach confirms that these sensitivities agree with expectations and provides first insights into the potential impacts of future change. V2Karst is the first model that enables the study of the joint impacts of large-scale land cover and climate changes on groundwater recharge in karst regions.

The impact of adaptive forest management on water fluxes and growth dynamics in a water-limited low-biomass oak coppice

Marginal semi-arid forests in areas currently affected by climate change are a challenge to forest management, which has to focus on key functional traits that can effectively contribute to resistance under extreme drought. We studied the effects of thinning in a marginal forest by quantifying functional responses relating to growth, carbon and water fluxes. Two experimental plots were established, one thinned in 2012 and the other one left as a control. The environmental conditions varied substantially during the 4-year study period, although dry years predominated. There were signs of dieback in the control with a decreasing inter-annual trend in LAI, as opposed to the treated plots, where LAI by the end of the study almost reached pre-thinning levels. Sap flow and transpiration were greatly enhanced by the treatment, with thinned trees transpiring 22.4 l tree−1 day−1 in the growing season, about twice the control figures. The seasonal patterns of transpiration and soil moisture were uncoupled, indicating a contribution of deep groundwater to the former flux. In the control, limitations to water and carbon dynamics (canopy conductance) occurred at soil moisture values below 16%, whereas in the thinned trees these limitations appeared when soil moisture dropped below 10%. Overall, oaks’ transpiration was enhanced with thinning to the point that stand-water use surpassed that of the control by the second half of the study period, averaging 24% of gross rainfall in both plots. Soil evaporation increased from 12 to 20% of gross rainfall after treatment in the overall period. The treatment had a profound watering effect in this marginal forest, led by fewer trees using the same amount of water as those in the untreated overstocked plot. This research may provide guidelines for ecohydrology-oriented silviculture in stands experiencing tree encroachment and transformation into shrublands that are more prone to global change-induced disturbances.

Effects of changes in soil moisture and precipitation patterns on plant-mediated biotic interactions in terrestrial ecosystems

Due to climate change, the amount, frequency, and intensity of precipitation worldwide are changing. There is increasing evidence that hydrological change severely affects species interactions and that these effects might overrule direct autecological responses, although this is currently understudied. Here, I synthesize published data on 405 interactions to show how changes in soil moisture affect the frequency or strength of plant-mediated biotic interactions. Despite substantial variation among published responses, general patterns have emerged. A recurrent finding in the synthesized studies is that dryness impedes beneficial interactions between plants and other organisms (decreased mycorrhization and infection with other symbiotic endophytes, less pollinator visits, less active decomposers) and increases detrimental interactions (increased performance of sucking insects, pathogen infection and competition between functionally similar plants). For increased wetness, which is far less studied, stress intensity seems to matter: Slightly increased precipitation often benefits plants and thereby associated interaction partners (increased mycorrhization and infection with symbiotic endophytes, increased herbivore performance), while extreme waterlogging or flooding impedes many interactions (decreased decomposer activity and mycorrhization). Legacy effects of changed soil moisture on plant community composition can amplify or reverse short-term effects on interactions. Although some concepts acknowledge the role of stress intensity (mild versus severe) and stress type (permanent versus pulsed) empirical research testing-related hypotheses is largely lacking, as is research on the role of soil moisture legacies for interactions.

Modeling transient soil moisture dichotomies in landscapes with intermixed land covers

Large-scale in situ soil moisture monitoring networks are becoming increasingly valuable research tools, but existing networks feature almost exclusive deployment of stations in grassland vegetation. These grassland soil moisture observations are unlikely to adequately represent the real soil moisture patterns in landscapes with intermixed land cover types. Here we demonstrate the severity of the problem for one particular landscape and introduce a flexible new method for solving the problem. The specific objectives of this study were (i) to compare root-zone soil moisture dynamics of two dominant vegetation types across Oklahoma, grassland (observed) and winter wheat cropland (simulated); (ii) to relate the soil moisture dynamics of grassland and cropland vegetation using an artificial neural network (ANN) as an observation operator; and (iii) to use the resulting ANN to estimate the soil moisture spatial patterns for a landscape of intermixed grassland and wheat cropland. Root-zone soil moisture was represented by plant available water (PAW) in the top 0.8 m of the soil profile. PAW under grassland was calculated from 18 years of soil moisture observations at 83 stations of the Oklahoma Mesonet, whereas PAW under winter wheat was simulated for the same 83 locations using a calibrated and validated soil water balance model. Then, we trained an ANN to reproduce the simulated PAW under winter wheat using only six inputs: day of the year, latitude and longitude, measured PAW under grassland, and percent sand and clay. The resulting ANN was used, along with grassland soil moisture observations, to estimate the detailed soil moisture pattern for a 9 × 9 km2 Soil Moisture Active Passive (SMAP) grid cell. The seasonal dynamics of root-zone PAW for grassland and winter wheat were strongly asynchronous, so grassland soil moisture observations rarely reflect cropland soil moisture conditions in the region. The simple ANN approach facilitated efficient and accurate prediction of the simulated PAW under winter wheat, RMSD = 21 mm and normalized RMSD = 0.17, using observed PAW under grassland as an input. This new method for estimating soil moisture under adjacent, contrasting land covers at a relatively low computational cost could be employed for any region and land cover pairing with training data available, and it may significantly enhance the applications of existing large-scale soil moisture monitoring networks.

How effective is information on soil-landscape units for determining spatio-temporal variability of near-surface soil moisture?

In the last decades, a growing interest in fostering advanced interdisciplinary studies is leading to the establishment of observatories in pilot catchments for long-term monitoring of hydrological variables and fluxes. Nevertheless prior to sensor network installation, this investment necessitates preliminary surveys on key-variables such as near-surface soil moisture in order to prevent risks of erronously distributing sensors by missing sufficient spatial information for understanding hydrological processes within the landatmosphere interactions. The availability of maps describing areas with similar morphological, topographical, soil, and vegetation characteristics enable preliminary surveys to be organized for capturing spatio-temporal variability of soil moisture as best as possible. The soil-landscape classification can be considered as an interesting approach for grouping mapping units with similar hydrological behavior. Therefore, we assume the soil-landscape units as hydrotopes or hydrological similar units. Six transects were established along two hillsides of the Upper Alento River catchment (southern Italy) which is a proper candidate to become a Critical Zone Observatory. In this paper we use a soil-landscape map to infer spatial and temporal dynamics of soil moisture measured along these transects, whereas quantitative analyses were obtained by using multivariate techniques. The effectiveness of available information on soil-landscape mapping units is evaluated with respect to different observed patterns of soil moisture: wetter- and drier-than average observation points belong to agricultural and forested hillslopes, respectively. Soil texture and topographical controlling factors, especially clay content and slope gradient, are found to explain approximately 70% of the observed spatial variations in soil moisture along the forested hillslopes. The spatial structure explained by the environmental controlling factors decreases to 45% in the cases of the agricultural hillslopes mainly due to perturbations induced by grazing and tillage practices.

Hydrologic Downscaling of Soil Moisture Using Global Data Sets without Site-Specific Calibration

AbstractNumerous applications require fine-resolution (10–30 m) soil moisture patterns, but most satellite remote sensing and land-surface models provide coarse-resolution (9–60 km) soil moisture e...

Spatiotemporal impact of soil moisture on air temperature across the Tibet Plateau

The Himalayan Tibet Plateau (HTP) is regarded as the third pole of the globe and is highly sensitive to global climate change. The hydrothermal properties of HTP greatly impacts the water cycle of the HTP and climate change in its surrounding regions. Using the NCEP-CFSR dataset, this study investigated the spatiotemporal pattern of soil moisture (SM) during different seasons considering vegetation types. The response of the evaporation fraction (EF) to SM and the impact of SM on air temperature through evapotranspiration were analyzed. Results showed that the spatial distribution of SM across the HTP was persistent during different seasons. A decreasing SM trend was observed from southeastern to northwestern HTP. Further, results of this study indicated a wetting tendency in past thirty years, espcially in desert region. In addition, the majority of the HTP regions were dominated by persistent transitional SM conditions which could be identified in the Himalayas and the southeastern HTP, whereas a persistent SM deficit in the Qaidam basin. The sensitivity of temperature response to EF was the strongest during spring and summer. Moreover, the spatial distribution of sensitivity was highly consistent with the vegetation regionalization, indicating the remarkable impact of vegetation type on the sensitivity of temperature to EF changes in summer.

Inter-dripper variation of soil water and salt in a mulched drip irrigated cotton field: Advantages of 3-D modelling

Two-dimensional (2-D) numerical models have been widely used to predict soil water-salt transport under mulched drip irrigation. However, conventional 2-D models often neglect the spatial variation of soil water-salt transport along drip lines and over-simplifies it by averaging values. This calls for a more robust model to better reflect the actual spatial and temporal variation of soil water-salt distribution in the field, especially in arid regions using brackish water with additional salt. In this study, mulched drip irrigation with brackish water was applied to a cotton field with loam soil in an arid region of southern Xinjiang, northwest China. The changes of soil water potential and total dissolved solid (TDS) of soil water over two irrigation events were intensively measured on hourly base to establish and calibrate a 3-D model, and another five irrigation cycles were monitored on daily base to validate the 3-D model. The mean absolute relative errors between measured and calculated soil water potential and TDS of soil water were 13.7% and 10.7% during hourly-based model calibration, even though there might be bias inevitably introduced by pre-determined sampling intervals and volumes. The calculated values during model validation were reasonably in line with the temporal patterns of soil moisture and TDS before and after irrigation at different irrigation cycles. This 3-D model was then applied to predict the spatial and temporal variations of soil water-salt transport during and after irrigation. Our results show that (1) the 3-D model with additional consideration on point-source discharge from individual drippers effectively reflected the wet front interferences along the drip lines. (2) A semi-elliptic cylindrical wet bulb together with relatively low salinity was formed along the drip lines, which matched well with the cotton layout (one mulch, two drip lines and four rows). However, the uneven overlapping of wet front interferences among individual drippers required to optimize the design of dripper intervals and irrigation regime to provide desirable soil water-salt conditions for cotton growth in this loam soil. (3) During the 96 h after irrigation, the TDS of soil water was always greatest in the dense root zone, increasing from approximately 3.8 g L−1 to 7.0 g L−1 as a result of root water uptake. Such localized re-salinization patterns demand repeated leaching in continued irrigation cycles to ensure cotton growth. Our study suggests that a smaller interspace between drippers with short but more frequent irrigation cycles would be much more helpful to timely and spatial-precisely meet plant water demanding.

Investigation of SMAP Active–Passive Downscaling Algorithms Using Combined Sentinel-1 SAR and SMAP Radiometer Data

The aim of this paper was to test the capabilities of the Sentinel-1 radar data in downscaling Soil Moisture Active Passive (SMAP) radiometer data for high-resolution soil moisture estimation. Three different active–passive downscaling algorithms, including the brightness temperature-based downscaling algorithm (BTBDA), the soil moisture-based downscaling algorithm (SMBDA), and a change detection method (CDM), were analyzed using pairs of Sentinel-1 active and SMAP passive observations collected over a semiarid landscape in southeastern Australia from May 2015 to May 2016. While these algorithms have been tested previously, this is the first study to evaluate the three algorithms using real Sentinel-1 radar and SMAP radiometer data. The SMAP passive observations were disaggregated to 9-, 3-, and 1-km scales and then compared with ground soil moisture measurements. The results suggest that the root-mean-square error (RMSE) in downscaled soil moisture at 9-km resolution was 0.057, 0.056, and 0.067 cm3/cm3 for the BTBDA, SMBDA, and CDM, respectively. The accuracy of downscaling methods was generally decreased when applied at the finer spatial resolution. The SMBDA had overall better performance in terms of correctly detecting the soil moisture pattern and relatively lower RMSE values, and is, therefore, recommended for the combined Sentinel-1 radar and SMAP radiometer setup for soil moisture monitoring. The influence of incidence angle normalization of Sentinel-1 SAR data on downscaled soil moisture was also investigated and found to be minimal.

Greenhouse gas emissions and soil organic matter dynamics in woody crop orchards with different irrigation regimes

Water scarcity in arid, semiarid and dry regions is a limiting factor for the development of sustainable agriculture. As a consequence, the adoption of new strategies such as regulated deficit irrigation (RDI) to reduce water and energy consumption will be essential. Decreases in irrigation water content may also have positive effects on soil C cycle. Thus, an experiment was setup in three woody crop orchards during two years, with the objective of assessing if RDI can reduce soil CO2 and N2O emissions, modify soil inorganic C and organic C quality and stability and affect soil aggregation. Soil CO2 and N2O emissions were measured every two weeks while soil samplings were carried out every three months. Results indicated that decreases in soil moisture by RDI implementation were related to significant decreases in CO2 emissions in all crops. RDI contributed to an average decrease, compared with full irrigation, of 1088–1664 g CO2 m−2 in the experimental period. Furthermore, CO2 emission was negatively correlated with inorganic C, suggesting the protective effect of soil carbonates towards organic matter. RDI also contributed to significantly decrease soil N2O emissions. However, N2O emission patterns did not directly follow soil moisture patterns and were constant in the experimental period. RDI contributed to an average decrease, compared with full irrigation, of 90–409 mg N2O m−2. No physicochemical property was significantly affected by irrigation regime. Although microbial biomass was not significantly affected by RDI, β-glucosidase activity was significantly higher under full irrigation during the warm seasons, with significant positive correlation with CO2 emissions. This seems to suggest that a significant fraction of CO2 emitted from soil derives from organic matter degradation, which is limited with low water content. So, RDI could contribute to promote soil C sequestration by reduced greenhouse gas emissions, with no negative effects on soil structure at short-term.

Rainfall threshold determination for flash flood warning in mountainous catchments with consideration of antecedent soil moisture and rainfall pattern

Flash flood disaster is a prominent issue threatening public safety and social development throughout the world, especially in mountainous regions. Rainfall threshold is a widely accepted alternative to hydrological forecasting for flash flood warning due to the short response time and limited observations of flash flood events. However, determination of rainfall threshold is still very complicated due to multiple impact factors, particular for antecedent soil moisture and rainfall patterns. In this study, hydrological simulation approach (i.e., China Flash Flood-Hydrological Modeling System: CNFF-HMS) was adopted to capture the flash flood processes. Multiple scenarios were further designed with consideration of antecedent soil moisture and rainfall temporal patterns to determine the possible assemble of rainfall thresholds by driving the CNFF-HMS. Moreover, their effects on rainfall thresholds were investigated. Three mountainous catchments (Zhong, Balisi and Yu villages) in southern China were selected for case study. Results showed that the model performance of CNFF-HMS was very satisfactory for flash flood simulations in all these catchments, especially for multimodal flood events. Specifically, the relative errors of runoff and peak flow were within ± 20%, the error of time to peak flow was within ± 2 h and the Nash–Sutcliffe efficiency was greater than 0.90 for over 90% of the flash flood events. The rainfall thresholds varied between 93 and 334 mm at Zhong village, between 77 and 246 mm at Balisi village and between 111 and 420 mm at Yu village. Both antecedent soil moistures and rainfall temporal pattern significantly affected the variations of rainfall threshold. Rainfall threshold decreased by 8–38 and 0–42% as soil saturation increased from 0.20 to 0.50 and from 0.20 to 0.80, respectively. The effect of rainfall threshold was the minimum for the decreasing hyetograph (advanced pattern) and the maximum for the increasing hyetograph (delayed pattern), while it was similar for the design hyetograph and triangular hyetograph (intermediate patterns). Moreover, rainfall thresholds with short time spans were more suitable for early flood warning, especially in small rural catchments with humid climatic characteristics. This study was expected to provide insights into flash flood disaster forecasting and early warning in mountainous regions, and scientific references for the implementation of flash flood disaster prevention in China.

Plant Harvesting Impacts on Soil Water Patterns and Phenology for Shrub-encroached Grassland

Harvesting is a common method in grassland management. With shrub encroachment into grassland, special hydrological and physiological dynamics probably occur in the shrub-grass coexisted ecosystem after harvesting, which remains largely unclear. Therefore, this study aims to identify potential effects of harvesting on soil moisture pattern, phenology dynamics, and water utilization in a shrub encroached grassland. We monitored soil water for a year beneath the Caragana microphylla canopy and interspace grassland after harvesting. The results showed that the soil water content increased under shrubs and grass patches after harvesting, especially under later ones. The water storage in soil of 0–100 cm depth increased by 18.9 mm under grass but only 5.5 mm under shrubs. Harvesting also decreased the difference of water storage between shrubs and grass from 19.1 to 5.7 mm. More snowmelt compensation, less evapotranspiration, shorter growing season, and higher water use efficiency may jointly contribute to the water recovery of harvesting soil. This study contributes novel evidence to the ecohydrological impacts of harvesting on shrub-grass co-existed ecosystems, shows application value in controlling shrub encroachment process and provides fundamental insights for the further study on soil water dynamics of similar ecosystems worldwide.

Simulation of Soil Wetting Pattern of Vertical Moistube-Irrigation

Knowledge of the soil wetting pattern characteristics of vertical moistube-irrigation is essential for the design of cost-effective and efficient irrigation systems. We conducted laboratory experiments to determine the specific discharge calculation formula and compare the accuracy of HYDRUS-2D simulation. The cumulative infiltrations, wetting pattern distances, and water content distributions predicted with HYDRUS-2D were found to align well with experimental data. The results provide support for using HYDRUS-2D as a tool for investigating and designing moistube-irrigation management practices. Numerical simulations were carried out with HYDRUS-2D to investigate the influence of soil texture, initial water content, pressure head, moistube length, and buried depth on wetting pattern characteristics. There are small differences in the shape of the soil wetting pattern, as well as significant differences in size. The wetting pattern and water content contour are approximately “ellipsoid” around the moistube. Soil texture has a significant effect on the wetting pattern characteristics, the vertical and horizontal wetting front distance, and the wetted soil volume decrease along with the increase of soil clay content. The initial water content, pressure head, and moistube length have great influence on the wetting front distance and the wetted soil volume. Both are positively correlated with the initial water content, pressure head, and length. Moistube buried depth affects the wetting pattern position. The soil wetting pattern decreases synchronously as the buried depth drops.

Soil moisture index from ERS-SAR and its application to the analysis of spatial patterns in agricultural areas

Soil moisture is an important factor influencing hydrological and meteorological exchange processes at the land surface. Synthetic aperture radar (SAR) backscatter is strongly affected by the volumetric soil moisture content, thus providing the potential to derive spatially distributed soil moisture information. Archives of historic SAR data exist, in which the use is limited by the lack of corresponding ground truth measurements. This study analyzes the potential of using a soil moisture index (SMI) with high spatial resolution to assess the soil moisture status in the absence of ground truth data. The index method is applied to agricultural areas in the catchment of the river Rur in Germany. The SMI was evaluated using antecedent precipitation and the wetting and drying behavior. The spatial patterns of the SMI were analyzed using semivariograms. This study confirms the applicability of a high resolution soil moisture index for monitoring near-surface soil moisture changes, to analyze soil moisture patterns, and indicates the possibility to complement antecedent precipitation as an input to hydrological models.

IMPACT OF LAND USE ON SOIL WATER CONTENT IN A HILLY RAINFED AGROSYSTEM: A CASE STUDY IN THE CAP BON PENINSULA IN TUNISIA

Understanding the temporal and spatial variability of soil moisture is fundamentalfor improving the management of water and soil resources on rainfed agrosystems.The present study focused on the soil moisture (SM) patterns observed in a hillyrainfed agrosystem. We analyzed five datasets from measurement at 15 sites duringvarious crop growth cycles under the common cereals/legumes/pasture croppingsystems within the Kamech catchment in Tunisia. Results indicated a strongseasonality in the precipitation and evapotranspiration dynamics that stronglyinfluences soil moisture patterns, with a strong reduction in the water availabilityduring summer (average SM = 0.20 m3/m3) as compared to winter (average SM =0.40 m3/m3). The data of two consecutive years showed that the spatial variability,expressed through the coefficient of variation of soil moisture, was at its highestpoint during spring. The averaged soil moisture of the two years yielded areasonable significant linear relation (R²=0.67**), indicating temporal stability ofthe spatial pattern. Actual evapotranspiration was found to be the predominantfactor influencing the dynamics of soil moisture.

Soil Texture Often Exerts a Stronger Influence Than Precipitation on Mesoscale Soil Moisture Patterns

AbstractSoil moisture patterns are commonly thought to be dominated by land surface characteristics, such as soil texture, at small scales and by atmospheric processes, such as precipitation, at larger scales. However, a growing body of evidence challenges this conceptual model. We investigated the structural similarity and spatial correlations between mesoscale (∼1–100 km) soil moisture patterns and land surface and atmospheric factors along a 150 km transect using 4 km multisensor precipitation data and a cosmic‐ray neutron rover, with a 400 m diameter footprint. The rover was used to measure soil moisture along the transect 18 times over 13 months. Spatial structures of soil moisture, soil texture (sand content), and antecedent precipitation index (API) were characterized using autocorrelation functions and fitted with exponential models. Relative importance of land surface characteristics and atmospheric processes were compared using correlation coefficients (r) between soil moisture and sand content or API. The correlation lengths of soil moisture, sand content, and API ranged from 12–32 km, 13–20 km, and 14–45 km, respectively. Soil moisture was more strongly correlated with sand content (r = −0.536 to −0.704) than with API for all but one date. Thus, land surface characteristics exhibit coherent spatial patterns at scales up to 20 km, and those patterns often exert a stronger influence than do precipitation patterns on mesoscale spatial patterns of soil moisture.

Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie’s law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater growing season temporal variability, and reduced levels of soil moisture, whilst projected decreasing summer precipitation may alter the feedbacks between soil moisture and vegetation water use and increase growing season soil moisture deficits.

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

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.