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In recent decades, there has been increasing interest in studying the variability in soil water properties and, specifically, the spatiotemporal variability in the soil water content. This is motivated by the notable theoretical and applied research interests in soil moisture dynamics and their implications for many natural processes. This study aimed to study whether there are variations in the spatial pattern of the temporal stability of soil moisture over time and to analyze the possible influences of certain hydroclimatic (soil water content, precipitation, and evapotranspiration) and soil factors (texture, bulk density, and organic matter content) on these variations. This study was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS, Spain) under Mediterranean conditions, with daily surface moisture data (0-5 cm depth) obtained from 20 stations for the 2006-2023 period. The results showed differences between the average pattern obtained with the 18-year data series and that obtained with the data series for each year. In more than half of the years studied, the representative station differed from that derived from the average pattern. The mean annual precipitation and summer precipitation characteristics seem to be the main factors influencing the variability in the spatial pattern of the temporal stability of soil moisture. [ABSTRACT FROM AUTHOR]

Soil moisture is a critical factor for vegetation restoration in arid regions. Poorly planned artificial sand-fixing vegetation systems often exacerbate soil moisture depletion, leading to further degradation. In this study, soil moisture content at various depths was continuously monitored from June to October 2023 in four key community plots—Corethrodendron scoparium, Calligonum mongolicum, and Artemisia ordosica, and bare sand—in a 31-year-old revegetated area located on the northeastern edge of the Tengger Desert. We analyzed the distribution and dynamic changes of soil moisture across the different and evaluated its temporal stability. The representative soil moisture depth was determined by using the coefficient of determination (R2) and the Nash-Sutcliffe efficiency (NSE). The results showed significant differences in soil moisture among the four plots. The bare sand plot had the highest soil water storage in the 0-200 cm layer, at 46.37 mm. In contrast, the Corethrodendron scoparium, Calligonum mongolicum, and Artemisia ordosicaa plots had similar soil water storage values ranging from 33.50 to 33.67 mm, indicating that vegetation restoration has increased soil moisture absorption by an average of 27.4%. Analysis using relative difference and Spearman rank correlation methods revealed varying levels of temporal stability in soil moisture across different soil depths and plots. The Corethrodendron scoparium and bare sand plots showed higher temporal stability compared to the Calligonum mongolicum and Artemisia ordosica plots. The representative depths of temporal stability for the four plots were determined to be 100 cm, 150 cm, 20 cm, and 100 cm, respectively.

Soil moisture (SM) is a key factor that determines the stability and functioning of desert ecological systems, but has been rarely studied due to the difficulty of sampling. The characterization of the temporal stability of soil moisture (SM TS) and its statistical parameters is much needed. To identify suitable locations to estimate SM status for the study area, and obtain greater insights into the SM TS of the Horqin Sand Land, SM was measured in a fixed dune (FD) over a depth profile of 0–1 m and on 14 occasions between May and July 2021. These data were combined with soil property and precipitation measurements to assess the SM TS and determine the optimal locations that could represent the mean SM of the area. Results indicated that (1) the mean SM of FD varied from 1.98% to 6.73%, with minimal spatial variation (mean standard deviation (STD) < 3%; mean coefficient of variation (CV) ranging between 42% and 56%). (2) SM continually decreased over time until considerable precipitation occurred. Temporal dynamics decreased with increasing soil depth. Further, only larger precipitation events (> 20 mm) led to significant SM increases. In deeper soil layers (> 60 cm), the SM response exhibited a lag. (3) The relationship between STD and mean SM indicated that SM becomes more variable under wetter conditions, such that SM increases were associated with CV increases in this region. (4) The Spearman's rank correlation coefficient (RS) values between different sampling dates indicated that most of the relationships were significant (p < 0.05), especially for soils in the 60–100 cm layer. (5) The mean values of mean relative differences (MRD) were smaller for soils < 40 cm and the mean corresponding standard deviation of MRD (SDRD) values were smaller for soils < 60 cm, indicating that SM tended to be more stable in deeper soil layers. (6) Linear regression analyses between the estimated means obtained from the identified locations and the actual field means led to the identification of the best representative SM locations for the 0–20, 20–40, 40–60, 60–80, and 80–100 cm layers at locations 8, 16, 8, 11, and 6, respectively. (7) The accumulated temporal stability index (ITS) of SM for different soil layers suggested that the 12th location (with a minimum ITS value) was the most representative location to approximate the mean SM of different soil layers in the FD. However, linear regression analyses of the SM between the actual field mean and that of the 12th representative location revealed a satisfactory fit only for soil layers above 40 cm. This study contributes to our understanding of SM patterns in arid environments, which have important implications for ground sampling design and hydro-logic modeling. [ABSTRACT FROM AUTHOR]

Remote sensing technology is an essential tool for tracking human-induced alterations on the water cycle, among which irrigation prevails. The possibility of obtaining detailed and accurate information on the actual irrigation extent through remote-sensing-based approaches is of paramount importance for water resources management. In this study, an update of the TSIMAP (Temporal-Stability-derived Irrigation MAPping) method, originally developed with satellite soil moisture as an input, is proposed. To demonstrate that the flexibility of the approach does not affect its main strength point (i.e., good accuracy in the face of high simplicity for users), a dual analysis relying on 1 km NDVI (Normalised Difference Vegetation Index) instead of soil moisture is carried out over the Ebro basin (Spain); data delivered by the Copernicus Global Land Service (CGLS) are used. First, results of this work are compared with outcomes from the method's original implementation obtained over a focus area (denominated "Ebro_CATAR") through satellite soil moisture. In the proposed configuration relying on NDVI, an overall accuracy (OA) up to 93% is found. Results highlight an increase in OA ranging from +2% to +6% depending on the validation strategy with respect to the TSIMAP implementation relying on soil moisture. Then, a basin-scale application is performed, providing performances still satisfactory (OA = 75%) notwithstanding a higher degree of heterogeneity. [ABSTRACT FROM AUTHOR]

In recent decades, there has been increasing interest in studying the variability in soil water properties and, specifically, the spatiotemporal variability in the soil water content. This is motivated by the notable theoretical and applied research interests in soil moisture dynamics and their implications for many natural processes. This study aimed to study whether there are variations in the spatial pattern of the temporal stability of soil moisture over time and to analyze the possible influences of certain hydroclimatic (soil water content, precipitation, and evapotranspiration) and soil factors (texture, bulk density, and organic matter content) on these variations. This study was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS, Spain) under Mediterranean conditions, with daily surface moisture data (0–5 cm depth) obtained from 20 stations for the 2006-2023 period. The results showed differences between the average pattern obtained with the 18-year data series and that obtained with the data series for each year. In more than half of the years studied, the representative station differed from that derived from the average pattern. The mean annual precipitation and summer precipitation characteristics seem to be the main factors influencing the variability in the spatial pattern of the temporal stability of soil moisture.

Soil moisture is important for understanding climate, water resources, water storage, and land use management. This study used Sentinel-2 (S-2) satellite optical data to retrieve surface soil moisture at a 10 m scale on grassland sites with low hydraulic conductivity soil in a climate dominated by heavy rainfall. Soil moisture was estimated after modifying the Optical Trapezoidal Model to account for mixed land cover in such conditions. The method uses data from a short-wave infra-red band, which is sensitive to soil moisture, and four vegetation indices from optical bands, which are sensitive to overlying vegetation. Scatter plots of these data from multiple, infrequent satellite passes are used to define the range of surface moisture conditions. The saturated and dry edges are clearly non-linear, regardless of the choice of vegetation index. Land cover masks are used to generate scatter plots from data only over grassland sites. The Enhanced Vegetation Index demonstrated advantages over other vegetation indices for surface moisture estimation over the entire range of grassland conditions. In poorly drained soils, the time lag between satellite surface moisture retrievals and in situ sensor soil moisture at depth must be part of the validation process. This was achieved by combining an approximate solution to the Richards' Equation, along with measurements of saturated and residual moisture from soil samples, to optimise the correlations between measurements from satellites and sensors at a 15 cm depth. Time lags of 2–4 days resulted in a reduction of the root mean square errors between volumetric soil moisture predicted from S-2 data and that measured by in situ sensors, from ~0.1 m3/m3 to <0.06 m3/m3. The surface moisture results for two grassland sites were analysed using statistical concepts based upon the temporal stability of soil water content, an ideal framework for the intermittent Sentinel-2 data in conditions of persistent cloud cover. The analysis could discriminate between different natural drainages and surface soil textures in grassland areas and could identify sub-surface artificial drainage channels. The techniques are transferable for land-use and agricultural management in diverse environmental conditions without the need for extensive and expensive in situ sensor networks. [ABSTRACT FROM AUTHOR]

In order to enhance food security and promote sustainable agricultural development, there is extensive utilization of sloping land in China. However, soil and water loss are severe in sloping lands. Understanding the spatiotemporal variability of soil water content (θ) is therefore important for determining suitable soil and water conservation strategies. Nevertheless, there exists a dearth of current research that focuses on the spatiotemporal variability of θ in microscale sloping lands. This study used statistical and temporal stability (TS) analyses to explore the characteristics of the spatiotemporal variability of θ on slopes. Furthermore, this study aimed to quantify the impacts of soil depth, slope position, air temperature, and hydrological conditions on the TS of θ. The average θ increases with depth, and it follows a logarithmic increase above 1.3 m and a linear increase below 1.3 m. The spatial variability of θ is higher in shallow soils and wet seasons compared with deep soils and dry seasons. The temporal stability of θ is higher on the upper and lower slopes compared with the middle slope. Day-MRD is more effective at capturing the temporal stability of θ than all-MRD. The diurnal variation of the TS of θ on slopes is primarily influenced by soil depth, slope position, air temperature, and hydrological conditions. We found that soil depth had a greater impact on the TS of θ than the slope position and that air temperature has a greater influence than the hydrological conditions. This study accurately describes the spatiotemporal variability of θ at the microscale slope, which helps solve the problems of soil and water conservation and water resource management on slopes. [ABSTRACT FROM AUTHOR]

Study region: Datong County, located in the loess alpine hills of north-western China. Study focus: This study investigated soil moisture and environmental factors in three catchments (10, 20 and 40 years after afforestation with sparse forests) to examine the influence and dominant factors of afforestation with sparse forests on the stability of soil moisture patterns in the catchment. New hydrological insights for the study region: The results show that long-term afforestation with sparse forests improved the soil moisture in the catchment. The spatial patterns of soil moisture (SMSP) were highly stable in all three catchments, except for surface (0–20 cm) soil moisture. Afforestation with sparse forests improved the stability of the spatial patterns and the fitting of representative locations (R2:0.818–0.878). In the early and middle afforestation periods, soil moisture was mainly influenced by plant indices such as fine root biomass, shrub grass biomass and leaf area index, whereas in the middle and late periods, the temporal stability of soil moisture gradually became more dependent on soil indices such as the clay content and soil organic carbon. This study provides a scientific basis for improving the understanding of soil hydrological processes in areas afforested with sparse forests and for optimising the selection of sample sites in the loess alpine hilly region.

Soil moisture has a great influence on vegetation growth and survival in arid and semiarid regions. Information about deep soil moisture dynamics is vital for restoring vegetation and improving land management on the water-limited Loess Plateau. The spatiotemporal dynamics and temporal stability of deep soil moisture (at a soil depth of 600 cm) were observed in situ under Caragana korshinskii shrubs that had various stand ages (named CK-10yr, CK-20yr and CK-35yr) in the Loess hilly region of China. The results showed that under C. korshinskii, soil moisture generally decreased as the stand age rose. Meanwhile, its moisture was consistent with precipitation variation, and an obvious time lag in soil moisture was found compared to that in precipitation during the entire growing season. Along the soil profile, a transition belt linking the shallow with deep soil moisture occurred at a 200 cm soil depth in different slope positions and aspects. At the slope scale, both the slope aspect and slope position significantly affected soil moisture variation in the areas with planted C. korshinskii shrubs, experiencing a decreasing trend from semi-shady slopes to sunny ones and from lower positions to upper ones. However, the variance in soil moisture between different positions and slope aspects was small. For the slope aspect, except for CK-20yr, the different-aged C. korshinskii shrubs had higher soil moisture content on sunny slopes than on semi-shady slopes at the upper 0–200 cm soil depth, while the opposite was true at the 200–600 cm soil depths. For slope positions, the soil moisture variation was small between the 0 and 200 cm soil depths and larger between the 200 and 600 cm soil depths. Within the whole profiles, the representative depth under the C. korshinskii shrubs for the soil moisture content was mainly concentrated between the 400–500 cm soil depths, on average, showing a gradual deepening trend with increasing restoration age. In summary, the findings indicate that natural recovery with low-water consumption grasslands and manual management measures, such as thinning and mowing, should be strengthened to minimize the high soil moisture consumption rates that occur in a healthy soil moisture environment and maintain sustainable vegetation restoration. [ABSTRACT FROM AUTHOR]

Temporal stability of soil moisture distribution is crucial to revealing the hydrological process of slope, but rarely accounted for during ecological restoration for engineering slopes. In this study, the effects of ecological restoration with different vegetations on soil moisture distribution were assessed by introducing temporal stability analysis. First, the ecological model slopes with grass and shrub covers were constructed to explore soil moisture distribution at the depth of 0 ∼ 100 cm. Then the spatial variability and correlation of soil moisture in ecological slope were analyzed. The similarity of the spatial distribution patterns among different periods were explored by temporal stability indices. Finally, the representative locations of soil moisture for each ecological slope were obtained and discussed. The results showed that soil moisture distribution was largely influenced by vegetation and rainfall. The similarity of spatial distribution patterns in ecological slopes with different vegetations differed from each other. Due to the difference in hydrological effects. The spatial distribution of soil moisture in slope was less similar in time under Cynodon dactylon cover, while it was better under Multiflora magnolia. Based on relative difference and time stability index, most of best representative locations were distributed at the top of the slope, followed by the middle of the slope. The study provides a theoretical basis for the rational monitoring point design of soil moisture content and a guide for the ecological restoration of engineering slopes.

Soil moisture is important for understanding climate, water resources, water storage, and land use management. This study used Sentinel-2 (S-2) satellite optical data to retrieve surface soil moisture at a 10 m scale on grassland sites with low hydraulic conductivity soil in a climate dominated by heavy rainfall. Soil moisture was estimated after modifying the Optical Trapezoidal Model to account for mixed land cover in such conditions. The method uses data from a short-wave infra-red band, which is sensitive to soil moisture, and four vegetation indices from optical bands, which are sensitive to overlying vegetation. Scatter plots of these data from multiple, infrequent satellite passes are used to define the range of surface moisture conditions. The saturated and dry edges are clearly non-linear, regardless of the choice of vegetation index. Land cover masks are used to generate scatter plots from data only over grassland sites. The Enhanced Vegetation Index demonstrated advantages over other vegetation indices for surface moisture estimation over the entire range of grassland conditions. In poorly drained soils, the time lag between satellite surface moisture retrievals and in situ sensor soil moisture at depth must be part of the validation process. This was achieved by combining an approximate solution to the Richards’ Equation, along with measurements of saturated and residual moisture from soil samples, to optimise the correlations between measurements from satellites and sensors at a 15 cm depth. Time lags of 2–4 days resulted in a reduction of the root mean square errors between volumetric soil moisture predicted from S-2 data and that measured by in situ sensors, from ~0.1 m3/m3 to 3/m3. The surface moisture results for two grassland sites were analysed using statistical concepts based upon the temporal stability of soil water content, an ideal framework for the intermittent Sentinel-2 data in conditions of persistent cloud cover. The analysis could discriminate between different natural drainages and surface soil textures in grassland areas and could identify sub-surface artificial drainage channels. The techniques are transferable for land-use and agricultural management in diverse environmental conditions without the need for extensive and expensive in situ sensor networks.

Understanding the temporal behaviour of soil moisture in different environments is essential considering its importance in hydrological processes. Few studies have addressed its dynamics in a subtropical climate, in view of temperature variations throughout the year and well-distributed precipitation events which are characteristics that affect the behaviour of soil moisture over time. The temporal stability of soil moisture was investigated in two sets of data collected from a small watershed in southern Brazil. We used multiple linear regression (MLR) to evaluate whether points with greater temporal stability contributed as predictor variables of the models for estimating soil moisture. Soil moisture was monitored in the superficial (0–10 cm) and subsurface (10–20 cm) layers at 39 points with variations in soil characteristics and topography. To assess the temporal stability of soil moisture, two statistical techniques and MLR models were used to identify the topographic, climatological and soil property variables, as well as those that influenced the dynamics of the soil water content. The results showed that the factors of slope, terrain elevation, microporosity and evapotranspiration were determinants for the strong performance of the models, and that the inclusion of points with greater temporal stability helped to improve the estimate in certain datasets. Therefore, the results of this study indicate that the set of results that express topographic factors, land use and cover, along with the soil physical properties should be considered to characterise the temporal stability of soil moisture. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Soil water storage (SWS) dynamics are affected by many factors in semiarid regions such as the Loess Plateau. Spatiotemporal variation of SWS varies greatly with different landscape positions due to the rolling and fragmented terrain landscape of the Loess Plateau. However, information on the SWS and its temporal stability at different landscape positions is lacking. In this study, hillslope, dam land and gully landscape positions were selected in a typical small watershed in the Loess Plateau. A soil water observation belt with 28 sample locations was set up at each landscape position, and temporal stability analysis was conducted using SWS data of 12 sampling events. The results showed that the variation characteristics of profile SWS are influenced by landscape position. The persistence of spatial SWS patterns in different landscape positions increases with the increase of soil depth. On each landscape position, representative locations can accurately predict their SWS based on temporal stability analysis. Moreover, the stability of SWS at the representative locations was more important than its content during the prediction process. The dominant factors that lead to the difference of temporal stability characteristics in different landscape positions varied with the change in soil depths. The results provide an important basis for vegetation reconstruction and water management in small Loess Plateau watersheds. [ABSTRACT FROM AUTHOR]

The U.S. Department of Agriculture’s Agricultural Research Service (USDA-ARS) maintains seven in situ soil moisture networks throughout the continental United States, some since 2002. These networks are crucial for understanding the spatial and temporal extent of droughts in their historical context, parameterization of hydrologic models, and local agricultural decision support. However, the estimates from these networks are dependent upon their ability to provide reliable soil moisture information at a large scale. It is also not known how many network stations are sufficient to monitor watershed scale dynamics. Therefore, the objectives of this research were to: (1) determine how temporally stable these networks are, including the relationships between various sensors on a year-to-year and seasonal basis, and (2) attempt to determine how many sensors are required, within a network, to approximate the full network average. Using data from seven in situ, it is concluded that approximately 12 soil moisture sensors are sufficient in most environments, presuming their locations are distributed to capture the hydrologic heterogeneity of the watershed. It is possible to install a temporary network containing a suitable number of sensors for an appropriate length of time, glean stable relationships between locations, and retain these insights moving forward with fewer sensor resources.

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Throughfall (TF) is an important water input of rainfall redistribution into floor, and its spatial-temporal variability under some species' canopies has been documented to evaluate effect on splash erosion. However, the understanding of TF variability under large broad-leaved canopy remains insufficient. In this study, the spatial heterogeneity, temporal stability and drop size of TF were quantified using variogram fitting, normalised ranking and filter paper staining, respectively, under banana (Musa nana Lour.) canopy comprising long and wide leaves. Results indicated TF pattern showed strong spatial correlation at a range of 3-5 m. High spatial variability of TF was found, which was affected by rainfall event size and was accompanied by great canopy disturbance. TF plots revealed high time variability, which was mainly controlled by unstable banana canopy structure. TF drop size from leaf dripping points varied in 3-10 mm and showed significant differences (p,0.05) among five kinds of leaf shapes, implying that concave and broken banana leaves were involved in the variability of TF drop size. Overall, results demonstrate the spatial-temporal variability of TF is dramatically induced by banana canopy with broad leaves, which may result in non-uniform soil water content and splash erosion under the canopy. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) plays a crucial role in simulating hydrological process, guiding reforestation and controlling soil erosion in mountainous regions. Spatial-temporal variability of SWC increases the difficulty of quantifying SWC pattern in the prediction of soil moisture. Temporal stability analysis of SWC can reduce the labor consuming and simplify the costly field monitoring. This study aimed to evaluate the temporal stability of SWC at hourly, daily and monthly temporal periods and its controlling factors at a hillslope in the Three Gorges region. The SWC of five soil depths was monitored at 5 topographic locations (toe, lower, middle, upper and top slope positions) along a 170 m hillslope in the Three Gorges region (110°04′ ∼112°04′ E, 29°53′∼31°34′ N), Yichang City, Hubei Province, China from May 4th, 2018 to May 3rd, 2019. The results showed that the coefficient of variation of SWC ranged from 4% to 49%, which increased with rising soil depth within 40 cm but thereafter decreased. However, the high Spearman's rank coefficients (P<0.05) indicated strong temporal stability at three temporal periods. The representative locations (RLs) varied in the different soil depths, which were toe, upper and middle slope positions at 0∼40, 40∼60 and 60∼80 cm depths of the investigated hillslope, respectively. Saturated hydraulic conductivity served as a dominant factor controlling the temporal stability of SWC. The result advances our thorough understanding of hydrology and soil water resource in the Three Gorges region. [ABSTRACT FROM AUTHOR]

The U.S. Department of Agriculture's Agricultural Research Service (USDA-ARS) maintains seven in situ soil moisture networks throughout the continental United States, some since 2002. These networks are crucial for understanding the spatial and temporal extent of droughts in their historical context, parameterization of hydrologic models, and local agricultural decision support. However, the estimates from these networks are dependent upon their ability to provide reliable soil moisture information at a large scale. It is also not known how many network stations are sufficient to monitor watershed scale dynamics. Therefore, the objectives of this research were to: (1) determine how temporally stable these networks are, including the relationships between various sensors on a year-to-year and seasonal basis, and (2) attempt to determine how many sensors are required, within a network, to approximate the full network average. Using data from seven in situ, it is concluded that approximately 12 soil moisture sensors are sufficient in most environments, presuming their locations are distributed to capture the hydrologic heterogeneity of the watershed. It is possible to install a temporary network containing a suitable number of sensors for an appropriate length of time, glean stable relationships between locations, and retain these insights moving forward with fewer sensor resources. [ABSTRACT FROM AUTHOR]

This study investigated the spatiotemporal variability and temporal stability of soil water at various depths in two croplands sown in corn and cotton during the 2018 growing season in the Tennessee Valley Region (TVR) of northern Alabama. Classical statistics and relative difference approaches were used to analyze soil water data in this study. In the corn field, the 30-60 cm depth showed the greatest variability, while the cotton field showed the greatest variability at 0-15 cm depth. A decreasing trend was noticed between mean soil water and coefficient of variation for all depths in the cotton field and at 30-60 cm depth in the corn field. However, convex upward, exponential decreasing, or no trends were found between mean soil water and standard deviation at different depths in both fields. The temporal stability analysis showed one representative sensor (S8 in corn and S1 in cotton) for the entire soil profile in both fields. Different statistical tests, i.e., Spearman's correlation (rs), Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), etc., were used to reduce uncertainty or increase confidence in the performance of representative sensors. Among various field attributes, topography in corn and soil properties in cotton were determined as significant factors responsible for soil water variability. Crop evapotranspiration (ETc) showed significant negative weak and moderate correlations with soil water in the corn and cotton fields, respectively. However, the mean air temperature showed a significant positive correlation with soil water in the corn field and a significant negative correlation in the cotton field. Solar radiation had a significant negative correlation with soil water in the cotton field and a non-significant correlation in the corn field. Accumulated growing degree days (accGDD) showed a significant negative correlation with soil water in the corn field and a positive correlation in the cotton field. This study gives insights into soil water variability, provides useful information about temporal stability, and identifies significant factors for precision uniform irrigation scheduling. [ABSTRACT FROM AUTHOR]

Understanding the spatio‐temporal variability of soil water content (SWC) in the Critical Zone (CZ) is essential to balance plant‐water benefits and to enhance the ability to monitor and predict drought. In current study, the spatial variability and temporal stability of multi‐layer SWC to a depth of 500 cm (35 soil layers) at 27 sampling sites were evaluated at a hillslope scale. A total of 64 SWC measurements were obtained from 28 March, 2017 to 23 December, 2018. We hypothesized the existence of a "special point" that is temporally stable both in horizontal direction (which means different layers) and in vertical direction (which means different profiles). We found a clear seasonal dynamic pattern of mean SWC for all sites in the 0–500 cm profile, with SWC varying from 4.0 to 24.8%. In the horizontal layer, both the 130‐cm and 140‐cm layers contained a maximum number of temporal stability sites (N = 4) which all located at H11, H13, H14 and H26. In the vertical profile, H19 was the most stable site, followed by H10 and H26, with 15, 10 and 6 stable layers, respectively. The decreasing order of SWC temporal stability was 200–500 cm, 0–500 cm and 0–200 cm, which means the temporal stability of SWC in 0–500 cm profile was more dependent on the 0–200 cm sub‐profile. At a three‐dimension scale, the most temporal stability layer and site was 180‐cm of H1 and H21 of 220‐cm, which confirmed our hypothesis. This study provides an accurate description of SWC spatio‐temporal variation at the hillslope scale, which is helpful for addressing eco‐hydrological models and water management issues in the Earth's CZs. [ABSTRACT FROM AUTHOR]

Knowledge of the spatial–temporal variability of soil water content is critical for water management and restoration of vegetation in semi‐arid areas. Using the temporal stability method, we investigated soil water relations and spatial–temporal variability of volumetric soil water content (VSWC) in the grassland–shrubland–forest transect at a typical semi‐arid subalpine ecosystem in the Qilian Mountains, northwestern China. The VSWC was measured on 48 occasions to a depth of 70 cm at 50 locations along a 240‐m transect during the 2016–2017 growing seasons. Results revealed that temporal variability in VSWC in the same soil layer in the three vegetation types and averaged across vegetation types tended to exhibit similar patterns of a decrease with increasing soil depth. Temporal stability in each vegetation type was stronger with an increase in soil depth. However, the results of temporal stability determined with standard deviation of relative difference (SDRD) disagreed with those based on the Spearman's rank correlation coefficient; the forest site had the highest Spearman rank correlation coefficient while the shrubland—the smallest SDRD in the 0–20 cm soil layer. Correlation analyses of VSWCs between two vegetation types indicated that soil water was related among all three vegetation types at the 0–20, and 0–70 cm soil layer, but in the 20–40 and 40–70 cm soil layers, significant correlation (p <.01) occurred only between adjacent vegetation types. In the upper soil layer (0–20 cm), soil water relations were mainly affected by surface runoff. In the lower soil layer (20–40 and 40–70 cm), soil water relations among the three vegetation types were highly complex, and probably resulting from a combination of root distribution and activity, interflow, and the impact of deep soil freeze–thaw dynamics. These results suggest that the factors affecting soil water are complex, and further research should address the relative importance of and interactions among different determining factors. [ABSTRACT FROM AUTHOR]

To increase reserve farmland resources, ensure food security, and to improve the ecological environment, large-scale gully regulation projects in Yan'an area of the Loess Plateau have been undertaken in China since 2013. Understanding the spatial and temporal distribution characteristics of slope soil moisture during the rainy season is, therefore, important for vegetation selection used in restoration measures in this area. The temporal stability of soil water content in the upper 100 cm soil depth in a gully regulation watershed was examined using six measurements taken during the rainy season (May–November 2016). Temporal stability analysis of the soil water content was undertaken using Spearman's rank correlation coefficient and the relative difference method. Results showed that soil water content in the 0–50 cm and 0–100 cm soil depths demonstrated moderate temporal and spatial variability, and soil water content variability gradually decreased with increasing soil depth. Soil water content in both depths had strong temporal stability, having a positive correlation with soil depth. Furthermore, temporal stability may decrease with increasing soil water content (p < 0.05). The number and position of representative locations were not constant, which varies with the soil depth and the estimation method. Five methods (mean relative difference, minimum relative difference standard equilibrium, temporal stability index, mean absolute deviation and root mean square error) can be used to determine the representative location of temporal stability. However, the prediction accuracy of the soil water content at representative locations obtained using the different methods for mean slope water content differed. Comparatively, the mean absolute deviation method had a higher accuracy, followed by the minimum relative difference standard equilibrium method. Results indicate that the prediction accuracy of five methods increased with soil depth. [ABSTRACT FROM AUTHOR]

• Four model slopes were constructed to study the soil water distribution. • The vegetation considerably reduced the similarity of spatial distribution pattern of soil water. • The spatial distribution pattern of the soil water under grass cover tended to be more stable. • The proposed weight-based prediction method accurately estimated the soil water status. The temporal stability of soil water is a critical state variable affecting hydrological process and structural stability of slopes. In this study, the effect of vegetation on the spatiotemporal characteristics of soil water content (SWC) was assessed via temporal stability analysis. Three types of re-vegetated slopes (grass, shrub, and grass-shrub) were constructed to explore the spatiotemporal distribution of the SWC at depths of 0–100 cm. Then, the effects of different vegetation covers on the SWC were explored. The coefficient of variation, the Spearman rank correlation coefficient, the mean relative difference, and the index of temporal stability were utilized to demonstrate the temporal stability of the SWC. Finally, a method of estimating the soil water status of re-vegetated slopes based on representative locations was developed. The results revealed that soil water dynamics were considerably governed by vegetation and rainfall. The vegetation cover considerably reduced the similarity of the spatial distribution pattern of the soil water, which tended to be more stable under grass cover. The weight-based prediction method developed in this study can more accurately estimate the overall soil water state of re-vegetated slopes. It provides a theoretical basis for the reasonable layout of SWC monitoring points and guidance for the ecological restoration of engineering slopes. [ABSTRACT FROM AUTHOR]

Mixed evergreen-deciduous broadleaved forest is the transitional type of evergreen broadleaved forest and deciduous broadleaved forest, and plays a unique eco-hydrologic role in terrestrial ecosystem. We investigated the spatio-temporal patterns of throughfall volume of the forest type in Shennongjia, central China. The results indicated that throughfall represented 84.8% of gross rainfall in the forest. The mean CV (coefficient of variation) of throughfall was 27.27%. Inter-event variability in stand-scale throughfall generation can be substantially altered due to changes in rainfall characteristics, throughfall CV decreased with increasing rainfall amount and intensity, and reached a quasi-constant level when rainfall amount reached 25 mm or rainfall intensity reached 2 mm h−1. During the leafed period, the spatial pattern of throughfall was highly temporal stable, which may result in spatial heterogeneity of soil moisture. [ABSTRACT FROM AUTHOR]

Subtropical regions have clay-rich, weathered soils, and long dry periods followed by intense rainfall that produces large fluctuations in soil water content (SWC) and hydrological behavior. This complicates predictions of spatio-temporal dynamics, as datasets are typically collected at too coarse resolution and observations often represent a duration that is too short to capture temporal stability. The aim of the present study was to gain further insights into the role of temporal sampling scale on the observed temporal stability features of SWC order to aid the design of optimal SWC sampling strategies. This focused on both sampling frequency and total monitoring duration, as previous analyses have not considered both of these sampling aspects simultaneously. We collected relatively high resolution data of SWC (fortnightly over 3.5 years) for various soil depths and under contrasting crops (peanuts and citrus) at the red soil region of southeast China. The dataset was split into a three-year training period and a six-month evaluation period. Altogether 13 sampling frequencies (intervals ranging from 15 to 240 days) and eight monitoring duration periods (between three and 36 months) were derived from the training period to identify temporal stability features and the most time stable location (MTSL). The prediction accuracies of these MTSLs were tested using the independent evaluation data. Results showed that vegetation type did affect the spatio-temporal patterns of SWC, whereby the citrus site exhibited a stronger temporal variation and weaker temporal stability than the peanut site. However, the effects of both sampling frequency and observation duration were more pronounced, irrespective of the role of vegetation type or soil depth. With increasing sampling interval or decreasing monitoring duration, temporal stability of SWC was generally overestimated; by less than 10% when sampling interval increased from every 15 to 240 days and by up to 40% with duration decreasing from 36 to 3 months. Our results suggest that sampling strategies and trade-offs between sampling interval and duration should focus on capturing the main variability in hydro-climatological conditions. For subtropical conditions, we found that sampling once every 45 days over 24 months to be the minimum sampling strategy to ensure errors in SWC temporal stability of less than 10%. [ABSTRACT FROM AUTHOR]

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Highlights • Soil moisture is characterized by high spatial and temporal variability. • A sampling scheme to optimize its monitoring over large areas is investigated. • During humid periods just one optimal measurement point can represent the catchment. • During dry periods the number of optimal measurement points become at least two. Abstract Soil moisture plays a fundamental role in the mass and energy balance between the land surface and the atmosphere, making its knowledge essential for several hydrological and climatic applications. The aim of this study is to extend the current knowledge of soil moisture spatial-temporal variability at the catchment scale (up to 500 km2). The main implication is to provide guidelines to obtain soil moisture values representative of the mean behaviour at the medium-sized river basin scale, which is useful for remote sensing validation analysis and rainfall-runoff modeling. To this end, 23 measurements campaigns were carried out during a time span of 14 months at 20 sites located within the Upper Chiascio River Basin, a catchment with a drainage area of about 460 km2 in the Umbria Region (central Italy). The data set allowed the analysis of both soil moisture temporal stability and its dynamics. On the basis of statistical and temporal stability approaches, it was investigated how factors such as climatic regime and geomorphology influence soil moisture behaviour. For the investigated area, the spatial variability of soil moisture was higher in dry periods with respect to wet periods, mainly due to the rainfall pattern characteristics during different periods of the year. Soil moisture values recorded during wet periods showed a better correlation than those recorded during dry periods. The maximum number of required samples, to obtain the mean areal soil moisture with an absolute error of 3% vol/vol, was found equal to 12. The temporal stability analysis showed that during wet periods just one "optimal" measurement point can provide values of soil moisture representative of the catchment-mean behaviour, while during dry periods the number of "optimal" measurement points became equal to two. Therefore, at the adopted spatial scale the use of a single measurement point can lead to significant errors. From the perspective of soil moisture dynamics, the decomposition of the spatial variance showed that the contribution of the time-invariant component (temporal mean of each site) was predominant on respect to the total spatial variance of absolute soil moisture data, for almost the whole observation period. Results provided guidance to optimize soil moisture sampling by performing targeted measurements at a few selected points representative of the catchment-mean behaviour. [ABSTRACT FROM AUTHOR]

Purpose: Information on root-zone soil water content (SWC) is essential for vegetation restoration, irrigation scheduling, and hydrological modeling. However, measurements of SWC within a variety of land uses may be time-consuming and labor-costing. This study tested whether SWC at a depth of a land use can be used to predict profile SWC of other land uses in terms of temporal stability analysis at a karst depression area in southwest China.Materials and methods: A total of 30 datasets of root-zone SWC from 0.1- to 0.5-m depths were collected by time domain reflectometry probes for three typical land uses from March 12 to November 8, 2015.Results and discussion: Results showed that the profile mean SWC and its associated standard deviation (SDP) and coefficient of variation (CVP) differed significantly (P < 0.05) among the grassland, farmland, and forestland. The profile SWC was more temporally stable according to the apparently lower CVT in comparison with CVP. The similarities of the vertical patterns of SWC were strong for the same land uses, while were relatively weak between the different land uses. The SWC measurements of the most temporally stable depth can be used to accurately predict profile SWC for both the same land use and other land uses.Conclusions: This study further expands the application of the temporal stability analysis and can aid water resource management in areas with diverse land uses. [ABSTRACT FROM AUTHOR]

Highlights • Temporal stability of soil water storage (SWS) in high-elevation forests are analyzed. • Temporal changes and spatial variation of SWS decreased with increasing soil depth. • One time-stable location (TSL) can be representative of the mean SWS. • These TSLs be with average LAI or relatively low canopy interception loss locations. • Temporal stability of SWS was mainly affected by soil and vegetation properties. Abstract Understanding soil water storage (SWS) dynamics in soil profiles is important for hydrological modeling and restoration of vegetation in semi-arid areas. Using the temporal stability method, we aimed to investigate the temporal stability of SWS at 0–40, 40–80, and 80–120 cm depth, and to identify representative sites for reliable estimates of the mean SWS in the permanent forest plot in the Qilian Mountains of China. Further, we wanted to identify correlations between temporal stability of SWS and soil, topography, and properties of the vegetation. Soil water content at soil depths 0–120 (for locations 1–40) and 0–70 cm (for locations 41–60) were measured using time-domain reflectometry (TDR) on 52 dates from 2016 to 2017. Results revealed that time-averaged mean SWS for the three layers differed significantly (P < 0.05), and the temporal changes and spatial variations of the mean SWS all decreased with increasing soil depth. Based on either the Spearman correlation coefficient or the standard deviation of relative difference (SDRD) index, the temporal stability of SWSs within the soil profiles under different soil layers were strong, and the number of time-stable locations increased with increasing soil depth, indicating that the SWS intended to be more temporally stable in deeper soil. One time-stable site can be representative of the mean SWS for multiple soil layers for the whole plot, and can accurately estimate the mean SWS for the three soil layers (R2 > 0.86, P < 0.001). Moreover, these time-stable locations should be those having average LAI, SBD or relatively low canopy interception loss compared to the corresponding field means. Soil bulk density, canopy interception rate, and aboveground biomass of mosses can significantly (P < 0.05) affect the stability of SWSs in this high-elevation forests. Such effects, however, differed among the different soil layers due to different conditions of soil characteristics, distribution of root biomass, and freeze–thawing processes. These results suggest that the influence of vegetation properties of the temporal stability of SWS should attract more attention and that both the relative importance of and interactions among different determining factors is helpful for better understanding the mechanistic determinants of SWS temporal stability in these areas. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) is a key factor for successful vegetation restoration in arid and semiarid regions, and vegetation has significant influences on the spatial patterns and temporal dynamics of SWC. The aim of this study was to investigate the temporal stability of SWC under different restored grasslands in an arid hilly area of Central China. SWC was measured in the 0‐ to 300‐cm soil profile in the natural grassland (Stipa capillata) and three typical planted grasslands (Medicago sativa, Agropyron cristatum, and Caragana korshinskii) over two growing seasons (from June to October 2015 and 2016) under natural rainfall conditions. The results showed that the mean SWC in the natural grassland was approximately 30% higher than those in the planted grasslands. The SWC consumption of the planted legume grasslands in the deepest soil layers (below 200 cm) was higher than that of the natural grassland, owing to the deep root system of the legumes. Both natural and planted grasslands had low SWC temporal stability in the top soil layers (0–50 cm), whereas more stable conditions were gradually observed with increasing the soil depth. The mean value of the mean relative differences of SWC in natural grassland (ca. 15%) was lower than that in the planted grasslands (A. cristatum grasslands) and much lower than that in the scrubland, highlighting the stronger temporal stability of SWC in the natural grassland. In conclusion, natural grassland could maintain higher and stable SWC and is recommended to be used for achieving sustainable vegetation restoration in arid and semiarid regions. [ABSTRACT FROM AUTHOR]

Abstract Gully is a typical geographical unit and a key component of the slope–gully system on the northern Loess Plateau. Understanding the distribution of soil moisture in gullies aids water resource regulation and ecological restoration. To investigate temporal–spatial variability of soil moisture, we measured values of soil water content (SWC) within 0–500 cm by using a neutron probe on 19 occasions from October 2014 to July 2017 in the gully and bank of a developed gully in Liudaogou catchment of Shenmu County. Results showed that the values of space–averaged soil water storage (SWS) in the gully were significantly (P < 0.01) higher than those in the bank. Soil clay content (SCC) and topography (including site elevation and distance from the gully head) were the most important factors affecting SWS of 0–500 cm in the gully. Topography can indirectly control SWS by redistribution of rainfall and soil properties. SWS and SCC rose with increasing distance from the gully head to the outlet. SWS in the gully exhibited strong temporal stability, and two time–stable sites around the middle section can be used to represent mean SWS within 500 cm depth in the gully. The gully sidewall significantly (P < 0.05) aggravated drought of soils in the bank between 150 and 250 cm from the gully edge. Gullies make the temporal–spatial patterns of soil moisture complex in slope–gully system. These results were expected to improve understanding of soil moisture distribution in the gully region and aid vegetative restoration of the northern Loess Plateau. Highlights • Soil texture and topography predominantly influence the soil moisture from o to 500 cm in the gully. • Intense rainfall may contribute to the unique spatial pattern of SWS in the gully. • Plots around the middle can represent the mean SWS within 0–500 cm in the gully. • Gully sidewall aggravated the soil drought in the bank between 150 and 250 cm from the gully edge. [ABSTRACT FROM AUTHOR]

Highlights • Soil moisture sensing networks are typically deployed under grassland vegetation. • Conditions under grassland can differ greatly from those under adjacent cropland. • A neural network translated grassland soil moisture into cropland soil moisture. • This efficient new approach does not rely on temporal stability or complex models. • The approach revealed the dichotomous soil moisture pattern within a SMAP grid cell. Abstract 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. [ABSTRACT FROM AUTHOR]

The spatial and temporal variability in soil moisture modulates runoff generation and the degree of land‐atmosphere coupling. Numerous statistical and modeling approaches have been implemented to characterize soil moisture spatial heterogeneity at fine spatial resolution using data from sparse observational networks or distributed model simulations. This characterization has been subsequently employed to translate coarse model simulations (of the order of a few hundred meters or kilometers) to finer spatial scales for a range of ensuing applications that rely on high‐resolution characterization of soil moisture. One common feature of these disaggregation methods is that the impact of soil moisture memory is ignored. This results in both spatial and temporal persistence being poorly simulated, leading to poorer specifications of cropping and irrigation plans. To overcome this shortcoming, we developed a hybrid disaggregation method that uses the first‐order autoregressive model (AR1) constructed from fine‐resolution (60 m) soil moisture simulations to disaggregate catchment mean soil moisture obtained from remote sensing or semidistributed model simulations. Soil moisture simulations from an integrated land surface‐groundwater model, ParFlow‐Common Land Model in Baldry subcatchment, Australia, are used as virtual observations. We examined the AR1 method performance against topographic wetness index‐based methods and those developed from temporal stability method. Results illustrate that the disaggregation schemes calibrated to a 10‐day fine‐scale model simulation perform better than the topographic‐based methods in approximating soil moisture distribution at a 60‐m resolution in the catchment. Furthermore, the AR1 model is the best model (Nash‐Sutcliffe efficiency [NSE] > 0.45) among various alternatives explored here. Applying the hybrid univariate AR1 model is promising for disaggregating semidistributed models' soil moisture simulations while significantly reducing the computational time. Key Points: Application of four disaggregation alternatives to disaggregate catchment mean soil moisture to fine resolution is examinedA univariate first‐order autoregressive model is the best performing model to represent spatial heterogeneity and temporal persistenceOnly 10 days of fine‐resolution hydrologic model simulations is required for parameterizing the disaggregation model [ABSTRACT FROM AUTHOR]

Regional soil moisture distributions and changes are critical for agricultural production and environmental modeling. Currently, hundreds of satellite sensors exist with different soil moisture observation capabilities. However, multi-sensor collaborative observation mechanisms for improving regional soil moisture monitoring capabilities are lacking. In this study, a Spatial pattern and Temporal variation law-based Multi-sensor Collaboration (STMC) method is proposed to solve this problem. The first component of the STMC method deduces the regional soil moisture distribution and variation patterns based on time stability theory and long-term statistical analyses. The second component of the STMC method detects potential anomalous soil moisture events and immediately triggers the high spatial resolution sensor with the soonest pass-over time. In the detection phase, an anomalous soil moisture judgment (ASMJ) algorithm and high temporal resolution sensors (the Advanced Microwave Scanning Radiometer 2 (AMSR2)) were utilized. Experiments conducted in Hubei province, China, demonstrated that the proposed STMC method was capable of accurately identifying of anomalous soil moisture conditions caused by waterlogging and drought events. Additionally, we observed that the STMC method combined the advantages of different long-term observation, high temporal, and high spatial resolution sensors synergistically for monitoring purposes.

Accurate estimates of soil moisture and soil hydraulic parameters via data assimilation largely depend on the quality of the model structure, input data and observations. Often, however, all of this information is subject to uncertainty under real circumstances. This real-case study seeks to understand the effects of different uncertainty sources and observation scales on data assimilation performance. Ensemble Kalman filter method based on the soil water-flow model, a sub-module of soil-water-atmosphere-plant model, is established to simultaneously estimate the model states and parameters. The soil hydraulic parameters are extensively measured or calibrated to examine the parameter estimation accuracy. Furthermore, considering the high spatial and temporal variability of soil moisture observation in the field-scale problem, an analysis of spatiotemporal characteristics is combined with data assimilation. Results indicated that simultaneously considering parameter and initial conditions uncertainty leads to a better soil moisture and parameter estimation than that ignoring initial uncertainty in realistic practice. Unlike the other error sources, an inadequate description to the meteorological forcing has a negative influence on surface soil moisture estimation, which might be attributed to the persistent disturbances of evaporation uncertainty and the lack of observations at shallow soil depth. Moreover, a prior knowledge of spatiotemporal features of soil moisture observation is beneficial to efficiently improve data assimilation performance. It is possible to implement field-scale data assimilation with a few representative points, instead of using the spatial average of all observations at a high cost. The assimilation results highlight the possibly positive outcomes of accounting for the multi-source of uncertainties and emphasize the significant importance of characterizing the spatial-temporal feature of soil moisture for a field-scale application. [ABSTRACT FROM AUTHOR]

Abstract: Dynamic relationships among rainfall patterns, soil water distribution, and plant growth are crucial for sustainable conservation of soil and water resources in water‐limited ecosystems. Spatial and temporal variation in deep soil water content at a watershed scale have not yet been characterized adequately due to the lack of deep soil water data. Deep soil–water storage (SWS) up to a depth of 5 m (n = 73) was measured at 19 sampling occasions at the LaoYeManQu watershed on the Chinese Loess Plateau (CLP). At a depth of 0–1.5 m, the annual mean SWS was highly correlated with rain intensity, and the correlation decreased with depth, but within the layers at 1.5–5.0 m, the changes in SWS indicated a lag between precipitation and the replenishment of soil water. Geostatistical parameters of SWS were also highly dependent on depth, and the mean SWS presented similar spatial structures in two adjacent layers. Temporal stability of SWS as indicated by mean relative difference, standard deviation of the relative difference (SDRD), and mean absolute bias error (MABE) was significantly weaker at the shallow than at deeper layers. Soil separates and organic carbon content controlled the spatial pattern of SWS at the watershed scale. One representative location (Site 57) was identified to estimate the mean SWS in the 1‐ to 5‐m layer of the watershed. Semivariograms of the SDRD and MABE were best fitted by an isotropic spherical model, and their spatial distributions were depth‐dependent. Both temporal stability and spatial variability of SWS increased over depth. This study is helpful for deep SWS estimation and sustainable management of soil and water on the CLP, and for other similar regions around the world. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Topsoil water content (TSWC) varies at spatial and temporal scales owing to the influence of several factors. In woody crops, few studies have analysed these dynamics under rainfed conditions. The temporal stability of the spatial patterns of TSWC in a Mediterranean rainfed sub-catchment (27 ha; Spain) was analysed during 12 months. Cropland includes four vineyards with cover crops, five cereal fields (fallow/crop rotation), one olive grove under conventional tillage, and one abandoned olive grove. In total, nine land use compartments were distinguished in twelve fields and nine non-cultivated soils. During the test period (May 2016–April 2017) the monthly TSWC values (mean 13.1% vol. ±8.0) showed a significant correlation with evapotranspiration. The spatial variability of TSWC increased under dry conditions and more homogeneous patterns appeared in the wet surveys. The vineyards’ inter-rows had the wettest (62% > in the rows) conditions owing to the cover crops and their high soil-water holding capacity, and average temporal stability. The vineyards’ rows were dry and very stable due to the tillage practices (higher elevation) and the low infiltration rates; and the corridors had wet and stable conditions. The forest presented the driest and stable temporal conditions associated to the water demand by the trees. Soil in the fallow cereal fields was drier and more stable than in the cereal fields. The abandoned olive grove showed wetter though less stable conditions than the olive grove. The trails had wet but not stable conditions. The different land uses and tillage practices influenced more the TSWC dynamics than the spatial variability of the analysed soil physical properties. However, silty loam and loamy soils presented wetter and more stable conditions than the average values, and the sandy loam and loamy sand soils had drier and less stable conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) plays a significant role in land surface hydrological processes (e.g., evapotranspiration, infiltration and runoff) and the spatial and temporal distribution of vegetation in arid and semi-arid regions. The aim of this study was to analyze the temporal stability of the SWC distribution pattern and to examine the primary factors that influence SWC temporal stability over a year and during the rainy season at different soil depths in terraces. The SWCs in eight soil depths at intervals of 0.2 m down to a depth of 1.6 m were measured at 21 locations in terraces containing jujube trees ( Ziziphus jujuba Mill. ) over two periods (over a year and during the rainy season). The results showed that the mean SWC over a year was larger than that for the rainy season in the corresponding layers. The mean SWC was highest in the lower slope. Soil depth significantly affected the SWC distribution over time and space. Water uptake mainly occurred between 1.0 and 1.2 m soil depth in both the rainy season and over the whole season. Moreover, the SWC demonstrated moderate spatial variability and was normally distributed at each depth. The temporal stabilities of SWC spatial patterns were strong for both the year period and the rainy season. The number of SWC representative locations varied depending on the soil depth. The SWCs measured at the best representative locations correctly represented the mean SWCs. Soil particles were the primary influencing factor affecting the mean relative difference, and root density was the primary influencing factor affecting the standard deviation of the relative differences. In conclusion, the SWC in the terraces showed stronger temporal stability during the rainy season compared to the year period. [ABSTRACT FROM AUTHOR]

This study was conducted to evaluate the performance of a preliminary soil moisture product estimated from the cosmic-ray neutron probe (CRNP) installed at a densely vegetated and monsoon climate area, namely the Soil Moisture - FDR and Cosmic-ray (SM-FC) site in South Korea. In this study, different calibration approaches, considering soil wetness conditions, were evaluated to select the most appropriate calibration method for deriving the best cosmic-ray soil moisture at the SM-FC site. We tested the potential application of two horizontal-vertical weighting methods, including the linear and non-linear approaches, with regard to the specific characteristics of the SM-FC site. The comparison of the two weighting approaches for in-situ soil moisture measurement suggested that the linear approach provided better performance compared to the non-linear in term of representing field-average soil moisture within the CRNP footprint. Our calibration results revealed that dry condition-based calibration outperformed wet condition-based calibration. The comparison of the cosmic-ray soil moisture utilizing dry condition-based calibration showed reasonable agreement with the linear weighted average soil moisture estimated from the FDR sensor network, with RMSE = 0.035 m 3  m −3 , and bias = −0.003 m 3  m −3 ; while the worst calibration solution with the wettest conditions had RMSE and bias values of 0.077 m 3  m −3 and 0.063 m 3  m −3 , respectively. The application of a biomass correction significantly improved the cosmic-ray soil moisture product at the SM-FC site, resulting in the reduction of RMSE from 0.035 to 0.013 m 3  m −3 . A temporal stability analysis was conducted to demonstrate the feasibility of cosmic-ray soil moisture in representing soil moisture for a large heterogeneous SM-FC site. Our temporal stability analysis results indicated the representativeness of cosmic-ray soil moisture over an area with a high degree of heterogeneity, compared to single measurements from FDR stations. [ABSTRACT FROM AUTHOR]

It has been proposed that changes to grazing systems, from continuous to rotational grazing, alter the pasture mass and composition, which are reflected in changes to stored soil water. Additionally, in highly variable landscapes, determining whether the variation in soil water is due to the inherent landscape properties rather than the imposed grazing management has long been a contentious argument. To address this question, soil moisture was measured across a highly variable landscape under three differing grazing treatments (1-, 4- and 20-paddock systems). From the soil-water measurements, plant-available water and plant-available water capacity were determined. Different production zones (high, medium and low) were identified in the landscape by visually estimating green herbage mass in late spring. There were no observed differences in the measured plant-available water capacity across the grazing treatments; however, significant differences occurred in plant-available water capacity across the three production zones (high-production zone, 114 mm; medium-production zone, 102 mm; low-production zone, 88 mm) within the study period. There appears to be a trend between the plant-available water capacity and near-surface gravel content as measured in production zones. The high production zones held more plant-available water than did the low production zones, enabling more biomass and longer pasture growth during spring and autumn. The plant-available water in the low production zones significantly decreased with time. In all, 22 of the 50 soil-moisture monitoring locations displayed high temporal stability and were identified as being catchment-average soil water-content monitoring locations. A majority of these locations occurred in the medium production zone, demonstrating that representative soil moisture can be measured in these landscapes. [ABSTRACT FROM AUTHOR]

Characterizing the spatiotemporal variability of soil-water content (SWC) is of paramount importance in many scientific fields and operational applications. We present a case study of the temporal stability and variability of SWC in a gravel-mulched field, a form of mulching that has been widely used by farmers on the loessial area of China for over 300 years, using Spearman correlation coefficients, frequency distributions and an index of temporal stability. SWC was measured weekly from May to August 2013 in the 0–10, 10–20, 20–30 and 30–50 cm layers. SWC was more variable in the surface soil, due to several environmental factors, and the variability gradually decreased with depth. A large sample size was needed for estimating the mean SWC of the field under dry conditions. High Spearman correlation coefficients between the SWCs measured on different sampling campaigns indicated a high temporal stability. The stability of the SWC spatial patterns over time and along the soil profile allowed us to identify a location representative of the field-mean SWC, with high coefficients of determination ranging between 0.8564 and 0.9325. The large-scale monitoring of SWC from few observations is thus feasible, which will aid the management of soil moisture in gravel-mulched fields in arid regions. [ABSTRACT FROM AUTHOR]

Soil water content (SWC) in the root zone is controlled by a suite of environmental variables. Complication arises from the cross-correlation between these environmental variables. Therefore, there is still a poor understanding on the controls of root zone SWC dynamics due, in part, to a lack of an appropriate method to untangle the controls. The objective of this study was to reveal the dominant controls of root zone soil water dynamics in a small watershed using an appropriate method based on empirical orthogonal function (EOF). For this purpose, SWC of 0–0.8 m layer in a small watershed on the Chinese Loess Plateau was used. The space-variant temporal anomaly ( R tn ) of SWC, which is responsible for the spatial variability of soil water dynamics, was decomposed using the EOF. Results indicated that 86% of the total variations of R tn were explained by three significant spatial structures (EOFs). Sand content and grass yield dominated the EOF1 of R tn and elevation and aspect dominated EOF2 and EOF3 of R tn , respectively. Moreover, their effects on soil water dynamics were time-dependent. The EOF analysis showed that three independent groups of factors (i.e., soil and vegetation dominated earth surface condition, elevation related near surface air humidity, and aspect regulated energy input) may drive the variability in soil water dynamics. Traditional correlation analysis, however, indicated that SWC was greater at higher elevation and sun-facing slopes, which distorted the soil water dynamics controls. Although original SWC-based partial correlation basically supported our findings, the results highly depended on the controlling factors selected. This study implied that R tn rather than original SWC should be preferred for understanding soil water dynamics controls. [ABSTRACT FROM AUTHOR]

Temporal stability of soil moisture has been widely used in hydrological monitoring since it emerged. However, the spatial analysis of temporal stability at the landscape scale is often limited because of insufficient sampling numbers. This work made an effort to investigate the spatial variations of temporal stability of soil moisture in an oasis landscape. The specific objectives of the study were to explore the spatial patterns of temporal stability and to determine the controlling factors of temporal stability in the desert oasis. A time series of soil moisture measurements were gathered on 23 occasions at 118 locations over 3 years in a rectangular transect of approximately 100 km2. The nonparametric Spearman's rank correlation coefficient, standard deviation of relative difference (SDRD), and mean absolute bias error (MABE) were used to quantify the temporal stability of soil moisture. Results showed that the temporal stability of soil moisture was depth dependent and season dependent. The spatial pattern of soil moisture in a deep soil layer and between two same seasons generally had a high temporal stability. SDRD and MABE were spatially autocorrelated and exhibited strong spatial structures in the geographic space. The concept of temporal stability can be extended to describe the time-stable areas of soil moisture with geostatistics. There were great differences between SDRD and MABE in describing the temporal stability of soil moisture and in identifying the controlling factors of temporal stability. In this case, MABE was a better alternative to estimate the areal mean soil moisture using representative locations than SDRD. Land use type, soil moisture condition, and soil particle composition were the dominant controls of temporal stability in the oasis. These insights could help to better understand the essence of temporal stability of soil moisture in arid regions. [ABSTRACT FROM AUTHOR]

Knowledge on the water content of a certain soil profile and its temporal changes due to rainfall and plant water uptake is a key issue for irrigation management. In this regard, sensors can be utilized to monitor soil water content (SWC). Due to the characteristic spatial variability of SWC, a key question is whether the measurements are representative and reliable. This study focused on the assessment of SWC and its variability in a vineyard with subsurface drip irrigation. SWC was measured in profiles down to a 50 cm depth by means of multi-sensor capacitance probes. The probes were installed at six locations along vine rows. A temporal stability analysis was performed to evaluate the representativeness and reliability of each monitoring profile with regard to irrigation control. Mean SWC was within a plausible range compared to unsaturated hydraulic parameters determined in a laboratory. The measurements revealed a considerable variability, but standard deviations were comparable to values from literature. The main finding was that some monitoring profiles (probes) proved to be more suitable to monitor SWC with respect to irrigation control than the others. Considering temporal stability provided helpful insights into the spatio-temporal variability of SWC measurements. However, not all questions that are related to the concept of temporal stability could be answered based on the given dataset. [ABSTRACT FROM AUTHOR]

With the increasing attention to site-specific or variable rate irrigation management, it is helpful to reconsider the quantity and placement of soil water monitoring locations in this context. Volumetric soil water content (θ v ) was monitored using a neutron probe (NP) at 72 locations in a center pivot irrigated field in eastern Nebraska. Variance reduction and temporal stability analyses were performed on θ v from shallow (∼top 46 cm) and full profile (∼122 cm) readings for four monitoring cycles in the 2015 growing season and 2016 preseason. Eleven additional cycles were included for a subset of the data for the temporal stability analysis. The spatial correlation scale for θ v was found to be less than the closest spacing of monitoring locations in the study (i.e. <37 m). For this field site, approximately three neutron probe monitoring locations were required to determine mean soil water depletion (±2 cm) for the field or for a management zone. Little economy would be gained in variance reduction for areal mean θ v from using a stratified network for management areas of reasonable size in a center pivot irrigated field. Temporally stable monitoring locations were identified. However, relatively low-cost spatial predictor variables, including elevation, deviation from mean elevation, apparent electrical conductivity, and mean relative difference of interpolated cosmic ray neutron probe surveys, were not consistent predictors of NP mean relative difference. The small range of variability of θ v within the study field is thought to be a contributing factor. It is possible that for fields with similar variability, or for site-specific irrigation where zones have been selected to reduce within-zone variance, that sensor quantity is more important than sensor placement in quantifying the areal mean θ v for irrigation management. [ABSTRACT FROM AUTHOR]

The general objectives of this study were to evaluate (i) the specificity of the spatial and temporal dynamics of apparent soil electrical conductivity (EC) measured by a electromagnetic induction (EMI) sensor, over 7 years, in variable conditions (of soil moisture content (SMC), soil vegetation cover and grazing management) and, consequently, (ii) the potential for implementing site-specific management (SSM). The DUALEM 1S sensor was used to measure the EC in a 6 ha pasture experimental field four times between June 2007 and February of 2013. Soil spatial variability was characterized by 76 samples, geo-referenced with the global positioning system (GPS). The soil was characterized in terms of texture, moisture content, pH, organic matter content, nitrogen, phosphorus and potassium. This study shows a significant temporal stability of the EC patterns under several conditions, behavior that is an excellent indicator of reliability of this tool to survey spatial soil variability and to delineate potential site-specific management zones (SSMZ). Significant correlations were obtained in this work between the EC and relative field elevation, pH, silt and soil moisture content. These results open perspectives for using the EMI sensor as an indicator of SMC in irrigation management and of needs of limestone correction in Mediterranean pastures. However, it is interesting to extend the findings to other types of soil to verify the origin of the lack of correlation between the EC data measured by DUALEM sensor and properties such as the clay, organic matter or phosphorus soil content, fundamental parameters for establishment of pasture SSM projects. [ABSTRACT FROM AUTHOR]