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Root water uptake depends on soil moisture which is primarily fed by throughfall in forests. Several biotic and abiotic elements shape the spatial distribution of throughfall. It is well documented that throughfall patterns result in reoccurring higher and lower water inputs at certain locations. However, how the spatial distribution of throughfall affects root water uptake patterns remains unresolved. Therefore, we investigate root water uptake patterns by considering spatial patterns of throughfall and soil water in addition to soil and neighboring tree characteristics. In a beech-dominated mixed deciduous forest in a temperate climate, we conducted intensive throughfall sampling at locations paired with soil moisture sensors during the 2019 growing season. We employed a linear mixed-effects model to understand controlling factors in root water uptake patterns. Our results show that soil water patterns and interactions among neighboring trees are the most significant factors regulating root water uptake patterns. Temporally stable throughfall patterns did not influence root water uptake patterns. Similarly, soil properties were unimportant for spatial patterns of root water uptake. We found that wetter locations (rarely associated with throughfall hotspots) promoted greater root water uptake. Root water uptake in monitored soil layers also increased with neighborhood species richness. Ultimately our findings suggest that complementarity mechanisms within the forest stand, in addition to soil water variability and availability, govern root water uptake patterns. [ABSTRACT FROM AUTHOR]

Throughfall heterogeneity induced by the redistribution of precipitation in vegetation canopies has repeatedly been hypothesized to affect the variation in the soil water content and runoff behavior, especially in forests. However, observational studies relating the spatial variation in the soil water content directly to net precipitation are rare, and few confirm modeling hypotheses. Here, we investigate whether throughfall patterns affect the spatial heterogeneity in the soil water response in the main rooting zone. We assessed rainfall, throughfall and soil water content (at two depths, 7.5 and 27.5 cm) on a 1 ha temperate mixed-beech forest plot in Germany during the 2015 and 2016 growing seasons using independent, high-resolution, stratified, random designs. Because the throughfall and soil water content cannot be measured at the same location, we used kriging to derive the throughfall values at the locations where the soil water content was measured. We first explored the spatial variation and temporal stability of throughfall and soil water patterns and subsequently evaluated the effects of input (throughfall), soil properties (field capacity and macroporosity), and vegetation parameters (canopy cover and distance to the next tree) on the soil water content and dynamics. Throughfall spatial patterns were related to canopy density. Although spatial autocorrelation decreased with increasing event sizes, temporally stable throughfall patterns emerged, leading to reoccurring higher- and lower-input locations across precipitation events. Linear mixed-effects model analysis showed that soil water content patterns were poorly related to spatial patterns of throughfall and that they were more influenced by unidentified, but time constant, factors. Instead of the soil water content itself, the patterns of its increase after rainfall corresponded more closely to throughfall patterns: more water was stored in the soil in areas where throughfall was elevated. Furthermore, soil moisture patterns themselves affected the local soil water response, probably by mediating fast drainage and runoff. Locations with a low topsoil water content tended to store less of the input water, indicating preferential flow. In contrast, locations with a high water content stored less water in the subsoil. Moreover, the distance to the next tree and macroporosity modified how much water was retained in soil storage. Overall, throughfall patterns imprinted less on the soil water content and more on the soil water dynamics shortly after rainfall events; therefore, percolation rather than the soil water content may depend on the small-scale spatial heterogeneity in canopy input patterns. [ABSTRACT FROM AUTHOR]

Eddy covariance sites are ideally suited for the study of extreme events on ecosystems as they allow the exchange of trace gases and energy fluxes between ecosystems and the lower atmosphere to be directly measured on a continuous basis. However, standardized definitions of hydroclimatic extremes are needed to render studies of extreme events comparable across sites. This requires longer datasets than are available from on-site measurements in order to capture the full range of climatic variability. We present a dataset of drought indices based on precipitation (Standardized Precipitation Index, SPI), atmospheric water balance (Standardized Precipitation Evapotranspiration Index, SPEI), and soil moisture (Standardized Soil Moisture Index, SSMI) for 101 ecosystem sites from the Integrated Carbon Observation System (ICOS) with daily temporal resolution from 1950 to 2021. Additionally, we provide simulated soil moisture and evapotranspiration for each site from the Mesoscale Hydrological Model (mHM). These could be utilised for gap-filling or long-term research, among other applications. We validate our data set with measurements from ICOS and discuss potential research avenues. [ABSTRACT FROM AUTHOR]

Sap flow encodes information about how plants regulate the opening and closing of stomata in response to varying soil water supply and atmospheric water demand. This study leverages this valuable information with model–data integration and deep learning to estimate canopy conductance in a hybrid catchment-scale model for more accurate hydrological simulations. Using data from three consecutive growing seasons, we first highlight that integrating canopy conductance inferred from sap flow data in a hydrological model leads to more realistic soil moisture estimates than using the conventional Jarvis–Stewart equation, particularly during drought conditions. The applicability of this first approach is, however, limited to the period where sap flow data are available. To overcome this limitation, we subsequently train a recurrent neural network (RNN) to predict catchment-averaged sap velocities based on standard hourly meteorological data. These simulated velocities are then used to estimate canopy conductance, allowing simulations for periods without sap flow data. We show that the hybrid model, which uses the canopy conductance from the machine learning (ML) approach, matches soil moisture and transpiration equally as well as model runs using observed sap flow data and has good potential for extrapolation beyond the study site. We conclude that such hybrid approaches open promising avenues for parametrizations of complex water–plant dynamics by improving our ability to incorporate novel or untypical data sets into hydrological models. [ABSTRACT FROM AUTHOR]

Germany's 2018–2020 consecutive drought events resulted in multiple sectors – including agriculture, forestry, water management, energy production, and transport – being impacted. High-resolution information systems are key to preparedness for such extreme drought events. This study evaluates the new setup of the one-kilometer German drought monitor (GDM), which is based on daily soil moisture (SM) simulations from the mesoscale hydrological model (mHM). The simulated SM is compared against a set of diverse observations from single profile measurements, spatially distributed sensor networks, cosmic-ray neutron stations, and lysimeters at 40 sites in Germany. Our results show that the agreement of simulated and observed SM dynamics in the upper soil (0–25 cm) are especially high in the vegetative active period (0.84 median correlation R) and lower in winter (0.59 median R). The lower agreement in winter results from methodological uncertainties in both simulations and observations. Moderate but significant improvements between the coarser 4 km resolution setup and the ≈ 1.2 km resolution GDM in the agreement to observed SM dynamics is observed in autumn (+ 0.07 median R) and winter (+ 0.12 median R). Both model setups display similar correlations to observations in the dry anomaly spectrum, with higher overall agreement of simulations to observations with a larger spatial footprint. The higher resolution of the second GDM version allows for a more detailed representation of the spatial variability of SM, which is particularly beneficial for local risk assessments. Furthermore, the results underline that nationwide drought information systems depend both on appropriate simulations of the water cycle and a broad, high-quality, observational soil moisture database. [ABSTRACT FROM AUTHOR]

Canopies shape net precipitation patterns, which are spatially heterogeneous and control soil moisture response to rainfall. The vast majority of studies on canopy water fluxes were conducted in forests. In contrast, grassland canopies are often assumed to be spatially homogeneous, therefore likely not inducing patches of heterogeneity at and below the soil surface. However, some studies on short‐structured vegetation, such as grasslands, proposed the importance of canopy‐induced heterogeneity for net precipitation. Still, systematic investigations on the effects on soil wetting patterns are missing. Therefore, in this study, we investigated soil moisture response to rainfall in a managed temperate grassland by exploring the individual impacts of spatially varying throughfall, vegetation height, and antecedent soil moisture status on the soil wetting patterns. We applied linear mixed effects models to disentangle the role of grassland canopy versus abiotic drivers. The spatial average soil water response showed diminishing water amounts stored in the upper parts of the soil as the growing season progressed and the soils dried, indicating bypass flow. Spatial variation of grass height was a significant driver of soil wetting patterns along with precipitation and antecedent soil moisture status. Soil wetting was suppressed in locations with tall canopies, although surprisingly, this was not directly related to throughfall patterns. Instead, our results suggest that seasonally drier conditions and the spatial difference in grass development amplify fast flow processes. Ultimately, our results confirm that spatial variation of the canopy affects soil moisture wetting patterns not only in forests but indicate a strong influence of preferential flow on soil water patterns in managed grassland as well. [ABSTRACT FROM AUTHOR]

The temporal and spatial dynamics of soil water are closely interlinked with terrestrial ecosystems functioning. The interaction between plant community properties such as species composition and richness and soil water mirrors fundamental ecological processes determining above‐ground–below‐ground feedbacks. Plant–water relations and water stress have attracted considerable attention in biodiversity experiments. Yet, although soil scientific research suggests an influence of ecosystem productivity on soil hydraulic properties, temporal changes of the soil water content and soil hydraulic properties remain largely understudied in biodiversity experiments. Thus, insights on how plant diversity—productivity relationships affect soil water are lacking.Here, we determine which factors related to plant community composition (species and functional group richness, presence of plant functional groups) and soil (organic carbon concentration) affect soil water in a long‐term grassland biodiversity experiment (The Jena Experiment).Both plant species richness and the presence of particular functional groups affected soil water content, while functional group richness played no role. The effect of species richness changed from positive to negative and expanded to deeper soil with time. Shortly after establishment, increased topsoil water content was related to higher leaf area index in species‐rich plots, which enhanced shading. In later years, higher species richness increased topsoil organic carbon, likely improving soil aggregation. Improved aggregation, in turn, dried topsoils in species‐rich plots due to faster drainage of rainwater. Functional groups affected soil water distribution, likely due to plant traits affecting root water uptake depths, shading, or water‐use efficiency. For instance, topsoils in plots containing grasses were generally drier, while plots with legumes were moister.Synthesis. Our decade‐long experiment reveals that the maturation of grasslands changes the effects of plant richness from influencing soil water content through shading effects to altering soil physical characteristics in addition to modification of water uptake depth. Functional groups affected the soil water distribution by characteristic shifts of root water uptake depth, but did not enhance exploitation of the overall soil water storage. Our results reconcile previous seemingly contradictory results on the relation between grassland species diversity and soil moisture and highlight the role of vegetation composition for soil processes. The effect of plant species richness on soil water content in the Jena Experiment changed with time after establishment, and was related at the beginning to aboveground (canopy) and later to belowground (soil organic carbon, roots) processes. In contrast, each plant functional group affected soil water distribution in a characteristic fashion that did not change with time, but varied in strength between years. Overall, the analysis suggests that recovery of soil functions after abandonment of arable farming may benefit from higher grassland diversity as a follow up land use, which likely feeds back on other ecosystem functions. [ABSTRACT FROM AUTHOR]

Abstract: Efficient extraction of soil water is essential for the productivity of plant communities. However, research on the complementary use of resources in mixed plant communities, and especially the impact of plant species richness on root water uptake, is limited. So far, these investigations have been hindered by a lack of methods allowing for the estimation of root water uptake profiles. The overarching aim of our study was to determine whether diverse grassland plant communities in general exploit soil water more deeply and whether this shift occurs all the time or only during times of enhanced water demand. Root water uptake was derived by analysing the diurnal decrease in soil water content separately at each measurement depth, thus yielding root water uptake profiles for 12 experimental grasslands communities with two different levels of species richness (4 and 16 sown species). Additional measurements of leaf water potential, stomatal conductance, and root traits were used to identify differences in water relations between plant functional groups. Although the vertical root distribution did not differ between diversity levels, root water uptake shifted towards deeper layers (30 and 60 cm) in more diverse plots during periods of high vapour pressure deficit. Our results indicate that the more diverse communities were able to adjust their root water uptake, resulting in increased water uptake per root area compared to less diverse communities (52% at 20 cm, 118% at 30 cm, and 570% at 60 cm depth) and a more even distribution of water uptake over depth. Tall herbs, which had lower leaf water potential and higher stomatal conductance in more diverse mixtures, contributed disproportionately to dynamic niche partitioning in root water uptake. This study underpins the role of diversity in stabilizing ecosystem function and mitigating drought stress effects during future climate change scenarios. Furthermore, the results provide evidence that root water uptake is not solely controlled by root length density distribution in communities with high plant diversity but also by spatial shifts in water acquisition. A plain language summary is available for this article. [ABSTRACT FROM AUTHOR]

Soil water content is a key variable for biogeochemical and atmospheric coupled processes. Its small-scale heterogeneity impacts the partitioning of precipitation (e.g., deep percolation or transpiration) by triggering threshold processes and connecting flow paths. Forest hydrologists frequently hypothesized that throughfall and stemflow patterns induce soil water content heterogeneity, yet experimental validation is limited. Here, we pursued a pattern-oriented approach to explore the relationship between net precipitation and soil water content. Both were measured in independent high-resolution stratified random designs on a 1-ha temperate mixed beech forest plot in Germany. We recorded throughfall (350 locations) and stemflow (65 trees) for 16 precipitation events in 2015. Soil water content was measured continuously in topsoil and subsoil (210 profiles). Soil wetting was only weakly related to net precipitation patterns. The precipitation-induced pattern quickly dissipates and returns to a basic pattern, which is temporally stable. Instead, soil hydraulic properties (by the proxy of field capacity) were significantly correlated with this stable soil water content pattern, indicating that soil structure more than net precipitation drives soil water content heterogeneity. Also, both field capacity and soil water content were lower in the immediate vicinity of tree stems compared to further away at all times, including winter, despite stemflow occurrence. Thus, soil structure varies systematically according to vegetation in our site. We conclude that enhanced macroporosity increases gravity-driven flow in stem proximal areas. Therefore, although soil water content patterns are little affected by net precipitation, the resulting soil water fluxes may strongly be affected. Specifically, this may further enhance the channelling of stemflow to greater depth and beyond the rooting zone. [ABSTRACT FROM AUTHOR]

We combine ecohydrological observations of sap flow and soil moisture with thermodynamically constrained estimates of atmospheric evaporative demand to infer the dominant controls of forest transpiration in complex terrain. We hypothesize that daily variations in transpiration are dominated by variations in atmospheric demand, while site-specific controls, including limiting soil moisture, act on longer timescales. We test these hypotheses with data of a measurement setup consisting of five sites along a valley cross section in Luxembourg. Both hillslopes are covered by forest dominated by European beech (Fagus sylvatica L.). Two independent measurements are used to estimate stand transpiration: (i) sap flow and (ii) diurnal variations in soil moisture, which were used to estimate the daily root water uptake. Atmospheric evaporative demand is estimated through thermodynamically constrained evaporation, which only requires absorbed solar radiation and temperature as input data without any empirical parameters. Both transpiration estimates are strongly correlated to atmospheric demand at the daily timescale. We find that neither vapor pressure deficit nor wind speed add to the explained variance, supporting the idea that they are dependent variables on land-atmosphere exchange and the surface energy budget. Estimated stand transpiration was in a similar range at the north-facing and the south-facing hillslopes despite the different aspect and the largely different stand composition. We identified an inverse relationship between sap flux density and the site-average sapwood area per tree as estimated by the site forest inventories. This suggests that tree hydraulic adaptation can compensate for heterogeneous conditions. However, during dry summer periods differences in topographic factors and stand structure can cause spatially variable transpiration rates. We conclude that absorption of solar radiation at the surface forms a dominant control for turbulent heat and mass exchange and that vegetation across the hillslope adjusts to this constraint at the tree and stand level. These findings should help to improve the description of land-surface-atmosphere exchange at regional scales. [ABSTRACT FROM AUTHOR]

Background and aims: Soil hydraulic properties drive water distribution and availability in soil. There exists limited knowledge of how plant species diversity might influence soil hydraulic properties. Methods: We quantified the change in infiltration capacity affected by soil structural variables (soil bulk density, porosity and organic carbon content) along a gradient of soil texture, plant species richness (1, 2, 4, 8, 16 and 60) and functional group composition (grasses, legumes, small herbs, tall herbs). We conducted two infiltration measurement campaigns (May and October 2012) using a hood infiltrometer. Results: Plant species richness significantly increased infiltration capacity in the studied grasslands. Both soil porosity (or inversely bulk density) and organic carbon played an important role in mediating the plant species richness effect. Soil texture did not correlate with infiltration capacity. In spring 2012, earthworm biomass increased infiltration capacity, but this effect could not be attributed to changes in soil structural variables. Conclusions: We experimentally identified important ecological drivers of infiltration capacity, suggesting complex interactions between plant species richness, earthworms, and soil structural variables, while showing little impact of soil texture. Changes in plant species richness may thus have significant effects on soil hydraulic properties with potential consequences for surface run-off and soil erosion. [ABSTRACT FROM AUTHOR]

ABSTRACT In the literature, contrasting effects of plant species richness on the soil water balance are reported. Our objective was to assess the effects of plant species and functional richness and functional identity on soil water contents and water fluxes in the experimental grassland of the Jena Experiment. The Jena Experiment comprises 86 plots on which plant species richness (0, 1, 2, 4, 8, 16, and 60) and functional group composition (zero to four functional groups: legumes, grasses, tall herbs, and small herbs) were manipulated in a factorial design. We recorded meteorological data and soil water contents of the 0·0-0·3 and 0·3-0·7 m soil layers and calculated actual evapotranspiration ( ETa), downward flux ( DF), and capillary rise with a soil water balance model for the period 2003-2007. Missing water contents were estimated with a Bayesian hierarchical model. Species richness decreased water contents in subsoil during wet soil conditions. Presence of tall herbs increased soil water contents in topsoil during dry conditions and decreased soil water contents in subsoil during wet conditions. Presence of grasses generally decreased water contents in topsoil, particularly during dry phases; increased ETa and decreased DF from topsoil; and decreased ETa from subsoil. Presence of legumes, in contrast, decreased ETa and increased DF from topsoil and increased ETa from subsoil. Species richness probably resulted in complementary water use. Specific functional groups likely affected the water balance via specific root traits (e.g. shallow dense roots of grasses and deep taproots of tall herbs) or specific shading intensity caused by functional group effects on vegetation cover. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Critical to the reliable application of gridded soil moisture products is a thorough assessment of their quality at spatially compatible scales. While previous studies have attempted to evaluate different soil moisture products, comprehensive assessments at the appropriate scale remain challenging and rare. This study explores the potential of the Cosmic-Ray Soil Moisture Observation System (COSMOS) in Germany for effectively mitigating the scale mismatch between soil moisture products and reference measurements. A newly released extensive COSMOS data set provides time series of hectare-scale soil moisture of the main root zone at different locations in Germany and offers a unique opportunity for a comprehensive quality assessment of 15 commonly-used coarse-scale soil moisture products. Those are either satellite-based (AMSR2 LPRM, ASCAT H115/H116, Sentinel-1 SSM, SMAP L3E, SMOS L3, ASCAT/Sentinel-1 SWI, SMAP/Sentinel-1 L2, CCI Combined, and NOAA SMOPS) or model-based (ERA5-Land, GLDAS-Noah, ASCAT H141/H142, GLEAM, SMAP L4, and SMOS L4). We compared the temporal dynamics of the soil moisture products against that of the COSMOS soil moisture estimates at 21 sites of different land cover types over six years (2015–2020), including the drought of 2018. We found that the model-based products generally yield a higher correlation (0.74) and lower unbiased root-mean-square differences (0.05 m 3 m − 3) than the satellite-based products (0.60 and 0.07 m 3 m − 3 , respectively) against the COSMOS data in Germany. Notably, the application of the exponential filter significantly improves the performance of the products. Conversely, deseasonalized time series of all selected products demonstrate lower performances across all COSMOS sites. Most products show a considerable positive bias, which limits their usability for the assessment of absolute soil water storage. We also found that the land cover type, mean annual soil moisture, and vertical support have notable influences on the performance of the soil moisture products. Additionally, the performances of the soil moisture products show seasonal variations, such that both correlation and bias are highest during the summer season. This study highlights the strengths of COSMOS data as a robust reference for evaluating soil moisture products. Additionally, it provides insights on how to assess, interpret, and improve large-scale soil moisture products. • Quality assessment of 15 soil moisture products from satellites/process-based models. • Data from Cosmic-Ray Soil Moisture Observation Systems (COSMOS) solved as reference. • Model-based products generally agree well with COSMOS soil moisture. • Performance influenced by exponential filter, land cover type, average soil moisture. • Best performance on seasonal variation and long-term trends found during summer. [ABSTRACT FROM AUTHOR]