Profile average soil moisture content over mesh layers 5-10 in time for uniform input and distributed input. The dashed lines indicate the minimum and maximum of the profile average soil moisture content over mesh layers 5-10. 35 Profile average soil moisture content over mesh layers 5-10 in time, for uniform input and distributed input. The dashed lines indicate the minimum and maximum of the profile average soil moisture content over mesh layers 5-10. 

Profile average soil moisture content over mesh layers 5-10 in time for uniform input and distributed input. The dashed lines indicate the minimum and maximum of the profile average soil moisture content over mesh layers 5-10. 35 Profile average soil moisture content over mesh layers 5-10 in time, for uniform input and distributed input. The dashed lines indicate the minimum and maximum of the profile average soil moisture content over mesh layers 5-10. 

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Improving the understanding of the controls on subsurface stormflow generation has been the goal of numerous experimental and modeling studies. However, the effect of the spatial variability of throughfall on soil moisture patterns and subsurface stormflow (SSF) generation has not yet been studied in detail. The objectives of this study are three-f...

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... Also, net precipitation chemical composition and precipitation intensity could possibly induce error for gypsum tablet integrated funnel measurements (Dunkerley, 2010;Filipzik et al., 2019). However, as shown in forest studies, not only the amount of mean net precipitation but also its spatial variation is important to understand hydrological processes such as drainage, subsurface storm flow and deep percolation (Guswa and Spence, 2012;Coenders-Gerrits et al., 2013;Klos et al., 2014;Metzger et al., 2017). An accurate estimation of the spatially heterogenous below canopy drip requires many samples at multiple locations (Kimmins, 1973;Kostelnik et al., 1989;Zimmermann et al., 2010;Voss et al., 2016). ...
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While net precipitation entering the soil is commonly measured in woody ecosystems, there is a lack of field measurements for herbaceous vegetation. Small canopy heights and fragile stem structures are the primary challenges for net precipitation sampling in grasslands under field conditions. We designed a new in situ device, “interception tubes”, for throughfall sampling in temperate grasslands. The instrument allows a natural development of grass canopy and sampling at multiple locations. Although it does not strictly separate throughfall and stemflow, the dominant part of the collected water is throughfall. We tested the interception tubes for splash loss with a drip experiment. Next, we evaluated the tubes’ measurements in a field installation at 25 locations both with and without vegetation cover. Also, we used measurements of gross precipitation, canopy height and soil water content to check the plausibility of the measurements. The experiment showed splash loss for the tubes is small ( < 3%) for the typical rain drop size for the growing season in the region, as well as for throughfall drops of lower falling velocity. In the uncovered period, splash loss corrected tubes’ measurements were generally smaller than classical funnel measurements. But the statistical model revealed that the slope of their relationship is close to unity (0.92) when accounting for topography and was probably related to wind effects. During the covered period, grass height systematically reduced below canopy precipitation measured by the tubes, indicating that they can capture spatial canopy drip patterns under denser grass foliage. The canopy height also altered the wind effect on the tube measurements. As in forest ecosystems, below canopy precipitation patterns were temporally stable and smaller events increased the spatial heterogeneity. The measured below canopy precipitation was between 95% and 22% that above, and grass height amplified the loss. The soil water balance showed the tubes underestimated soil water input at peak grass height, which suggests enhanced occurrence of stemflow in tall grass. Despite the underestimation of stemflow, the interception tubes are a suitable method for estimating the canopy effect on throughfall patterns in temperate grasslands, and stemflow can be quantified by additional soil moisture measurements.
... However, many other hydrological applications at the hillslope scale include tree vegetation and consider its fundamental role in capturing and "filtering" water. For instance, classical forest hydrology studies concentrate on canopy interception and spatiotemporal patterns of throughfall and stemflow at the hillslope scale in different climates and forest types (e.g., Siegert et al., 2016;Liang et al., 2011), and their impacts on hillslope hydrology (Coenders-Gerrits et al., 2013;Hopp and McDonnell, 2011). Other approaches tend to disentangle the interrelations of tree transpiration, typically measured in terms of sap flow, with hillslope topography, soil moisture patterns along the hillslope, and variable soil depths (Tian et al., 2019;Tromp-van Meerveld and McDonnell, 2006). ...
Article
Understanding the internal functioning of natural systems often requires interdisciplinary approaches and competences that allow encompassing and disentangling different and strictly intertwined physical and biological processes. Hydrology and ecophysiology are examples of complementary and highly interconnected disciplines that share water as a common analysis element when investigating the functioning of vegetated ecosystems. In this discussion paper, we call for more frequent and active dialogue and collaboration between (field) hydrologists and ecophysiologists to study natural processes at the boundary between the two disciplines. We report some examples of the specific approaches of hydrologists and ecophysiologists to analyse water movement in the soil-vegetation-atmosphere continuum at increasing spatial scales, highlighting how the same mechanisms can be seen from different, but largely complementary, points of view. We argue that these different perspectives can and should be merged in order to overcome possibly fragmented vision of complex processes and provide a more holistic comprehension of ecohydrological mechanisms in forest ecosystems.
... The spatial variability of T f potentially exercises considerable control of forest hydrology and biogeochemistry dynamics because it can lead to pronounced heterogeneity in edaphic conditions [8,9]. To optimize forest management in terms of the availability of water and nutrition in the soil, a better understanding of the spatial distribution of T f within forests and its controls is imperative [10]. ...
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This study examined the spatial variability of throughfall (Tf) and its implications for sampling throughfall during the leafless period of oak trees. To do this, we measured Tf under five single Brant’s oak trees (Quercus brantii var. Persica), in the Zagros region of Iran, spanning a six-month-long study period. Overall, the Tf amounted to 85.7% of gross rainfall. The spatial coefficient of variation (CV) for rainstorm total Tf volumes was 25%, on average, and it decreased as the magnitude of rainfall increased. During the leafless period, Tf was spatially autocorrelated over distances of 1 to 3.5 m, indicating the benefits of sampling with relatively elongated troughs. Our findings highlight the great variability of Tf under the canopies of Brant’s oaks during their leafless period. We may also conclude that the 29 Tf collectors used in the present study were sufficient to robustly estimate tree-scale Tf values within a 10% error of the mean at the 95% confidence level. Given that a ±10% uncertainty in Tf is associated with a ±100% uncertainty in interception loss, this underscores the challenges in its measurement at the individual tree level in the leafless season. These results are valuable for determining the number and placement of Tf collectors, and their expected level of confidence, when measuring tree-level Tf of scattered oak trees and those in forest stands.
... En estas regiones, la distribución espacial y temporal de la humedad del suelo es a la vez causa y consecuencia de la presencia de vegetación, la cual desempeña un papel clave porque evita la erosión y degradación del suelo, mantiene altos niveles de (David et al., 2006;Llorens y Domingo, 2007;Pereira et al., 2009;Schnabel et al., 2013b;Staelens et al., 2006;Wang et al., 2013). Sin embargo, el efecto de estos factores en el control de la humedad del suelo se ha estudiado tradicionalmente de manera separada (Doerr y Thomas, 2000;Gerrits et al., 2013;Liang et al., 2011), mientras que su influencia general sobre la humedad del suelo rara vez ha sido considerada. Por ejemplo, es común que los estudios sobre la interceptación de lluvia solo consideren la interceptación de árboles, sin tener en cuenta la de la capa de hojarasca, que puede ser tan alta o incluso mayor que aquella de los árboles (Gerrits et al., 2007). ...
... Aunque la incidencia espacio-temporal de todos los factores antes mencionados sobre la humedad del suelo no suele ser considerada, las relaciones entre la humedad del suelo y las cubiertas de vegetación han sido bien documentadas en bosques abiertos mediterráneos (Cubera y Moreno, 2007aJoffre y Rambal, 1988, 1993 Sin embargo, una desventaja es que las mediciones se han tomado comúnmente con una resolución temporal mayor que la diaria, omitiendo por lo tanto los procesos hidrológicos en escalas de tiempo más cortas y sin tener en cuenta los factores que pueden causarlos (Gerrits et al., 2013). Por lo tanto, en algunas regiones climáticas, estos procesos deben analizarse a alta resolución, ya que la naturaleza de los fenómenos es a corto plazo. ...
... Sin embargo, debajo de los árboles se observaron mayores retrasos en la humectación del suelo y menores incrementos de SM en comparación con los espacios abiertos. Esto puede deberse al efecto combinado de factores como la repelencia al agua por parte del suelo o la interceptación por las cubiertas, cuya influencia puede variar con el tiempo (Doerr y Thomas, 2000;Gerrits et al., 2013). En condiciones iniciales de Húmedo y MH, mayores cantidades de lluvia fueron propensas a provocar aumentos de agua del suelo en ambos tipos de vegetación, porque las cubiertas estaban previamente mojadas, lo que da lugar a la saturación de su capacidad de almacenamiento y produce un goteo más rápido del agua de lluvia. ...
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... En estas regiones, la distribución espacial y temporal de la humedad del suelo es a la vez causa y consecuencia de la presencia de vegetación, la cual desempeña un papel clave porque evita la erosión y degradación del suelo, mantiene altos niveles de (David et al., 2006;Llorens y Domingo, 2007;Pereira et al., 2009;Schnabel et al., 2013b;Staelens et al., 2006;Wang et al., 2013). Sin embargo, el efecto de estos factores en el control de la humedad del suelo se ha estudiado tradicionalmente de manera separada (Doerr y Thomas, 2000;Gerrits et al., 2013;Liang et al., 2011), mientras que su influencia general sobre la humedad del suelo rara vez ha sido considerada. Por ejemplo, es común que los estudios sobre la interceptación de lluvia solo consideren la interceptación de árboles, sin tener en cuenta la de la capa de hojarasca, que puede ser tan alta o incluso mayor que aquella de los árboles (Gerrits et al., 2007). ...
... Aunque la incidencia espacio-temporal de todos los factores antes mencionados sobre la humedad del suelo no suele ser considerada, las relaciones entre la humedad del suelo y las cubiertas de vegetación han sido bien documentadas en bosques abiertos mediterráneos (Cubera y Moreno, 2007aJoffre y Rambal, 1988, 1993 Sin embargo, una desventaja es que las mediciones se han tomado comúnmente con una resolución temporal mayor que la diaria, omitiendo por lo tanto los procesos hidrológicos en escalas de tiempo más cortas y sin tener en cuenta los factores que pueden causarlos (Gerrits et al., 2013). Por lo tanto, en algunas regiones climáticas, estos procesos deben analizarse a alta resolución, ya que la naturaleza de los fenómenos es a corto plazo. ...
... Sin embargo, debajo de los árboles se observaron mayores retrasos en la humectación del suelo y menores incrementos de SM en comparación con los espacios abiertos. Esto puede deberse al efecto combinado de factores como la repelencia al agua por parte del suelo o la interceptación por las cubiertas, cuya influencia puede variar con el tiempo (Doerr y Thomas, 2000;Gerrits et al., 2013). En condiciones iniciales de Húmedo y MH, mayores cantidades de lluvia fueron propensas a provocar aumentos de agua del suelo en ambos tipos de vegetación, porque las cubiertas estaban previamente mojadas, lo que da lugar a la saturación de su capacidad de almacenamiento y produce un goteo más rápido del agua de lluvia. ...
... Many studies have examined the effects of rainfall redistribution processes on soil water dynamics based on field observations or numerical experiments (e.g., Durocher 1990;Bouten et al. 1992a;Keim et al. 2006;Coenders-Gerrits et al. 2013). However, most of these studies minimized stemflow, dealt with interception loss as the difference between gross and net rainfall, and emphasized that the spatial distribution of throughfall mainly affects soil water dynamics. ...
Chapter
Stemflow contributes to an uneven water input and preferential infiltration and percolation that increases the heterogeneity of soil water dynamics in forested stands. These aboveground and underground effects are referred to as the double-funneling effect of a tree. Stemflow serves as a principal source of the rainwater input around a tree, and tends to enter the soil over a small infiltration area and then preferentially flow along the network of root channels. This kind of concentrated infiltration and channelization of stemflow could generate perched water in soil layers or at the soil–bedrock interface. The double-funneling effect also influences the soil water redistribution process and the spatial pattern of soil water during the drying process. The double-funneling effect has been qualitatively demonstrated for various species with links to soil erosion, subsurface flow, slope stability, groundwater recharge, and runoff generation at various scales. A comprehensive and integrated understanding of the double-funneling effect is needed. This chapter reviews the current understanding of how stemflow affects soil water dynamics in both wetting and drying processes. After discussing field evidence of the effects of stemflow on soil water responses, their modeling and issues requiring future study are highlighted.
... Throughfall, on the other hand, must percolate through any litter layer between it and the mineral soil layer-which can substantially reduce and chemically alter throughfall (Michalzik et al. 2001;Van Stan et al. 2017). The litter cover and composition of the surface that receives throughfall is also spatiotemporally variable, depending on season (Coenders-Gerrits et al. 2013) and an area's effectiveness at accumulating litter (Kappes et al. 2009). Aboveground observations of surface exposure to atmospheric conditions (i.e., evaporative drivers) also indicate differences between areas receiving throughfall versus stemflow. ...
... Hopp and McDonnell (Hopp and McDonnell 2011) modeled the influence of throughfall on subsurface stormflow generation at the Panola hillslope site including outcrops and soils up to about 1.8 m depth using spatial throughfall patterns from Keim et al. (2005). Coenders-Gerrits et al. (2013) combined the previous modeling study with interpolated throughfall from the Huewelerbach site in Luxembourg to assess the effect of spatially distributed throughfall on soil moisture patterns. Liang et al. (2009) modeled a stemflow-sprinkling experiment. ...
... With respect to modeling, the double funneling concept is largely applied in experimental studies (e.g., Schwärzel et al. 2012), whereas modeling studies still focus on water transport modeling through the soil matrix. Modeled flow through the soil matrix may then include different spatial input fields for throughfall (e.g., Coenders-Gerrits et al. 2013) or higher fluxes at stems through stemflow infiltration areas but with respect to the subsurface revert to matrix flow Liang et al. 2009). No studies could be found that explicitly include macropore or preferential flow along roots in soil water modeling. ...
Chapter
Net precipitation recharges soil- and groundwater beneath vegetation canopies and litter layers. Interactions between subsurface water and net precipitation fluxes differ, however, as there are multiple types of net precipitation: free throughfall (rain that passes through canopy gaps), throughfall, and stemflow (rain that drains down plant stems). Rates and infiltration areas for these different hydrologic fluxes interact with soil properties to result in complex wetting fronts, preferential flow paths along roots and through macropores, and localized soil water recharge. How far net precipitation travels through the subsurface and whether it contributes to streamflow or groundwater recharge is reviewed in this chapter. Past and current methods for monitoring throughfall and stemflow infiltration patterns are reviewed, and a critical synthesis is provided for our understanding of subsurface–precipitation interactions to date.
... Hopp and McDonnell (2009) explored the role of bedrock topography in the runoff generation using HYDRUS 3-D (Simunek et al., 2006) at the Panola hillslope. Coenders-Gerrits et al. (2013) used the same model structure to examine the role of interception and slope in the subsurface runoff generation. Bishop et al. (2015), Wienhöfer and Zehe (2014) and Klaus and Zehe (2011) used physically based models to investigate the influence of vertical and lateral preferential flow networks on subsurface water flow and solute transport, including the issue of equifinality and its reduction. ...
... The different pathways of precipitation through the forest canopy create a strongly heterogeneous pattern of water input to the soil, with consequences for soil hydrobiochemistry (Levia and Frost, 2003;Zimmermann et al., 2007). These pathways compartmentalize the forest floor into cold and hot spots of infiltration, with a strong subsequent impact on subsurface flow and biogeochemical processes (Liang et al., 2007;Guswa and Spence, 2012;Coenders-Gerrits et al., 2013). Thus, an understanding of forest canopy precipitation partitioning processes is highly important for our conceptual understanding of forest ecohydrology systems. ...
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Although stemflow oftentimes only represents a small portion of net precipitation in forests, it creates hot spots of water input that can affect subsurface storm-flow dynamics. The distribution of stemflow over different trees is assumed to be temporally stable, yet often unknown. Therefore, it is essential to know the systematic factors driving stemflow patterns. Several drivers have been identified in the past, mainly related to tree traits. However, less attention has been paid to tree neighbourhood interactions impacting stemflow generation and creating stand patches with enhanced or reduced stemflow. We recorded stemflow during 26 precipitation events on 65 trees, growing in 11 subplots (100 m2 each), in a temperate mixed beech forest in the Hainich National Park, Germany. We used linear mixed effects models to investigate how traits of individual trees (tree size, tree species, number of neighbouring trees, their basal area and their relative height) affect stemflow and how stemflow is affected by stand properties (stand, biomass and diversity metrics). As expected, stemflow increased with event and tree size. Stemflow was highly variable at both the tree and subplot scale. Especially in large rainfall events (>10 mm), the tree/subplot ranking was almost identical between events, probably due to fully developed flow paths bringing out the full stemflow potential of each tree. Neighbourhood and stand structure were increasingly important with event size (15 % of fixed effects on the tree scale and ca. 65 % on the subplot scale for large events). Subplot-scale stemflow was especially enhanced by a higher proportion of woody surface, expressed by a high number of trees, low leaf area and a large maximum tree size. The Simpson diversity index contributed positively to stemflow yield for large events, probably by allowing more efficient space occupation. Furthermore, our models suggest that the neighbourhood impacts individual tree morphology, which may additionally increase stemflow in dense, species diverse neighbourhoods. Unexpectedly, rain shading within the canopy had little impact on the stemflow spatial variation. Overall, we find a strong cross-scale temporal stability. Tree size and tree density were the main drivers, independently increasing stemflow, creating forest patches with strongly enhanced or reduced stemflow. Our results show that, besides tree metrics, forest structure and tree diversity also affect stemflow patterns and the potentially associated biogeochemical hot spots.
... The relationship between soil moisture content and runoff is usually non-linear (cf. Coenders-Gerritsen et al., 2013;Zabaleta and Antigüedad, 2013;Penna et al., 2015) and often threshold like (Western and Grayson, 1998;Noguchi et al., 2005;Detty and McGuire, 2010;Penna et al., 2011;Saffarpour et al., 2016). Similar findings have been reported for plots and micro-catchments under contrasting vegetation types in the humid tropics (Chandler and Walter, 1998;Godsey et al., 2004;Fu et al., 2013). ...
Article
Years of slash-and-burn activities across the tropics have led to very patchy land-cover with vegetation in various stages of regrowth but the associated effects on runoff generation remain under-studied. We analysed soil moisture-, perched water level- and overland flow (OF) dynamics during two periods (15 February-2 November 2015 and 20 December 2015-2 March 2016) for plots in a small catchment in Eastern Madagascar where slash-and-burn agriculture has been practiced for more than 50 years: a 1.58 ha tree fallow (TF2), a 1.93 ha terraced shrub fallow (TSF), and a 0.08 ha degraded grassland plot with regularly coppiced and burned eucalypt trees (EUC). Near-surface saturated soil hydraulic conductivity (Ksat) was distinctly lower beneath TF2 compared to TSF and EUC, leading to distinctly different perched water level responses and OF occurrence. OF was highest for TF2 and lowest for TSF. Soil moisture content was lowest for EUC, producing the lowest antecedent moisture plus precipitation threshold for OF occurrence (82 mm compared to 129 mm for TSF and 137 mm for TF2). OF was generally in the form of saturation overland flow (SOF) and reflected perched water level dynamics, except at EUC where the occurrence of a perched water level was rare during the first measurement period. Soil moisture responses to rainfall at EUC were highly variable and became larger after harvesting and burning the plot prior to the second measurement period. These results show that soil physical properties and runoff-generation processes in areas with a long history of slash-and-burn agriculture can vary markedly over small spatial scales and need to be taken into account if catchment scale runoff responses are to be simulated or predicted.