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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.

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.

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.

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.

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.

Aerodynamic shape optimization processes are often used for complex problems that meet single or multi-objective design requirements. The robust aerodynamic shape optimization techniques with a high number of design variables that consider uncertainties have a huge computational burden compared to the traditional aerodynamic shape optimization techniques without considering uncertainties. To overcome this issue, in this study, the proper orthogonal decomposition is integrated with the inductive design exploration method to use for the robust shape optimization of the ONERA M6 wing. The proper orthogonal decomposition method is utilized for reducing the number of design variables of the wing geometry. The cost due to the computational fluid dynamics analysis is mitigated by incorporating the proper orthogonal decomposition with a surrogate modeling technique called the radial basis function. The robust optimization is conducted by the proposed approach based on the inductive design exploration method by accounting for uncertainties of the Mach number in the transonic flow regime. The agreement between the performance predictions of the robust designs and the computational fluid dynamics analysis results showed the effectiveness of the proposed approach. © 2024 Gazi Universitesi Muhendislik-Mimarlik. All rights reserved.

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

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

AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 -- 2 August 2021 through 6 August 2021 -- -- 273499, A robust aerodynamic shape optimization problem is one of the most challenging processes due to the high number of design parameters. The consideration of uncertainties causes a considerable computational burden. Therefore, the reduction of the number of required design variables has a significant impact on computational efficiency. In this study, Proper Orthogonal Decomposition (POD) method is utilized to extract the essential feature of the design variables for an aircraft wing geometry. The design exploration is conducted with the reduced-order parametric model constructed with POD rather than using the more complex or high-dimensional system. The Radial Basis Function (RBF) interpolation technique is implemented to estimate the unknown field available in the design space. Model-form uncertainties originating from the turbulence model required for the CFD analyses are determined using the eigenspace perturbation methodology. Robust solutions that satisfy the design requirements are obtained while taking uncertainties into account using Inductive Design Exploration Method (IDEM). The results of the case study show that geometric filtration using POD-RBF based IDEM computation approach is an alternative multi-objective robust optimization framework. © 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2021 -- 2 August 2021 through 6 August 2021 -- -- 273499, A robust aerodynamic shape optimization problem is one of the most challenging processes due to the high number of design parameters. The consideration of uncertainties causes a considerable computational burden. Therefore, the reduction of the number of required design variables has a significant impact on computational efficiency. In this study, Proper Orthogonal Decomposition (POD) method is utilized to extract the essential feature of the design variables for an aircraft wing geometry. The design exploration is conducted with the reduced-order parametric model constructed with POD rather than using the more complex or high-dimensional system. The Radial Basis Function (RBF) interpolation technique is implemented to estimate the unknown field available in the design space. Model-form uncertainties originating from the turbulence model required for the CFD analyses are determined using the eigenspace perturbation methodology. Robust solutions that satisfy the design requirements are obtained while taking uncertainties into account using Inductive Design Exploration Method (IDEM). The results of the case study show that geometric filtration using POD-RBF based IDEM computation approach is an alternative multi-objective robust optimization framework. © 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

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.

In this study, two different well-known wind tunnel techniques; “Captive Trajectory Method “and “Grid Surveying Method “are simulated using Computational Fluid Dynamics (CFD) method. Time dependent behavior of a generic store during the release process from a delta wing under high transonic flow regime is determined. First of all, in captive trajectory simulation, simultaneous trajectory and attitude computations are accomplished by utilizing a reliable commercial flow solver called ANSYS Fluent. Secondly, aerodynamic grid database generation required for grid surveying approach is performed and the trajectory of the store is determined by using a standalone store separation module built in MATLAB Simulink. The numerical outputs are compared with available wind tunnel results conducted in Arnold Engineering Development Center. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

In this study, two different well-known wind tunnel techniques; “Captive Trajectory Method “and “Grid Surveying Method “are simulated using Computational Fluid Dynamics (CFD) method. Time dependent behavior of a generic store during the release process from a delta wing under high transonic flow regime is determined. First of all, in captive trajectory simulation, simultaneous trajectory and attitude computations are accomplished by utilizing a reliable commercial flow solver called ANSYS Fluent. Secondly, aerodynamic grid database generation required for grid surveying approach is performed and the trajectory of the store is determined by using a standalone store separation module built in MATLAB Simulink. The numerical outputs are compared with available wind tunnel results conducted in Arnold Engineering Development Center. © 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.