Rainfall Interception Research Articles

Surface-groundwater interactions in hard rock, water-limited environments, simulated at very fine scale using long time-series observations and hydrotope-modeling concept

Hard rock systems are typically characterized by undulated landscapes, short flow path, dense drainage network, and low aquifer storage. If located in water-limited environments (WLE), then typically have variable rainfall characteristics, frequent floods and droughts, and savannah type of vegetation capable to uptake groundwater. In such environments, surface–groundwater interactions are of primary importance. In this study, surface–groundwater interactions are analyzed focusing on spatiotemporal net recharge dependence on hydrotopes, where a hydrotope is conceptualized as spatial unit (or object), which at a given scale of assessment can be assumed as internally homogeneous (e.g. tree canopy or rock outcrop), but hydro(geo)logically different than the adjacent area. The study was carried out in the small (7.6 ha) Trabadillo study area (TSA) in Spain, representative for hard rocks of WLE, using 3D-GSFLOW integrated hydrological model (IHM) at very fine grid (5x5m), extracted from coarser grid (100x100m) of Sardon 3D-GSFLOW model (Hassan et al., 2014, Journal of Hydrology 517, 390–410). The IHM was calibrated using: (i) 20-year head observation; (ii) 8-year soil moisture observations at 4 profiles, each at different hydrotope and each at 4 different depths; and (iii) MODIS satellite earth observation of evapotranspiration. Despite applying spatially uniform rainfall as forcing, surface–groundwater interactions were highly spatially variable, primarily, because of hydrotope-differences in rainfall interception loss and secondarily, because of differences in transpiration, in subsurface evaporation and in hydrological properties of subsurface. The high temporal variability of rainfall, ranging yearly from 310 to 925 mm, resulted in high temporal variability of all water fluxes, including groundwater fluxes; e.g. gross recharge (Rg) varied annually from 2 to 445 mm, net recharge (Rn), from −50 mm to + 89 mm, while the 20-year mean Rn was close to zero, because Rg was counterbalanced by groundwater exfiltration and less by groundwater evapotranspiration. The high temporal variability of groundwater fluxes and many dry years with largely negative Rn, in combination with low aquifer storage, emphasized TSA dependence on rainfall and its vulnerability to droughts. The hydrotope modeling concept applied at the very fine scale, emphasized also large Rn dependence on land cover type, especially on density and species composition of trees, invisible at coarser scale modeling. As such, the proposed hydrotope modelling approach can be applied as a tool to test whether in a given environment planting (or cutting) trees will result in increase or decrease of water resources.

Estimation of bark water storage capacity of broad- and needle-leaved trees planted in a semi-arid climate zone

In forest ecosystems, measurement of bark water storage capacity (BWSC) is required for determining the amount of rainfall interception and understanding throughfall and stemflow processes. We compared the bark roughness coefficient (BRC) and BWSC of even-aged, widely-planted, broad-leaved and needle-leaved species in the Chitgar Forest Park, near Tehran, Iran. Bark samples (n = 10 per species) were extracted from three needle-leaved species (Cupressus arizonica, Thuja orientalis, and Pinus eldarica) and two broad-leaved species (Acer velutinum and Robinia pseudoacacia). The highest and lowest BWSC was found to be for A. velutinum and P. eldarica trees, respectively (0.63 vs. 0.32 g cm−3). Among the studied species, R. pseudoacacia had the highest BRC (0.69), and the lowest was found to be for A. velutinum species (0.03). The whole tree bole BWSC ranged from 156.8 L for P. eldarica to 14.6 L for A. velutinum. The results suggested that A. velutinum may provide more stemflow to the forest floor due to its small size, low BRC and subsequent low whole tree bole BWSC. These findings significantly contribute to our understanding of rainfall partitioning dynamics and ecohydrological processes associated with stemflow from trees. This improved understanding will help managers in selecting tree hydrologic characteristics that align with their objectives in forestry treatments, afforestation plans and establishment of vegetation in urban park settings within drylands.

The effects of leaf traits on litter rainfall interception with consequences for runoff and soil conservation

Abstract During rainfall, plant litter interception regulates overland flow with an impact on water runoff generation and sediment displacement. Besides the rainfall characteristics, the effects of litter mass, thickness, storage and drainage properties on rainfall interception are reasonably well understood. In contrast, less is known about the influence of leaf traits, which we hypothesized to affect interception, soil hydrology and conservation via litter structure assembly. We measured the runoff and soil loss generation as determined by litter layer structural and hydraulic properties of 16 coexisting tropical woody species with wide‐range morphological leaf traits in a rainfall simulator experiment. Our results show that litter produced by coexisting species can differ in precipitation interception, thereby influencing runoff and soil loss. This is because there is important interspecific variation in litter water storage and drainage, which are negatively affected by leaf area (LA). Leaf water repellency positively affected litter water storage. Moreover, LA also negatively affected litter layer density. Litter density, in turn, increased runoff, but decreased soil loss, possibly due to protection against splash erosion. These results can be used to predict the effects of plant traits on the soil water balance and soil integrity protection through ecohydrological interception by the litter layer. The next research steps will be to extend our model to multiple‐species litter layers, and to validate and calibrate our model in different field situations in different ecosystems. Synthesis: We revealed the direct and indirect effects of species leaf size and hydraulic traits on litter rainfall interception, runoff and soil loss. We propose a new litter‐soil ecohydrological model, by using structural equation models, which can be used as a tool to predict ecosystem functioning, and guide management and restoration actions with water and soil conservation targets.

Estimating rainfall interception loss of three dominant shrub species in an oasis–desert ecotone using in situ measurements and the revised Gash analytical model

Canopy interception loss affects the local water budget by removing a non-negligible proportion of rainfall from the terrestrial surface. Thus, quantifying interception loss is essential for thoroughly understanding the role of vegetation in the local hydrological cycle, especially in dryland ecosystems. However, sparse shrubs in dryland ecosystems have not been sufficiently studied, owing to time- and labor-intensive field experiments and challenging model parameterization. In this work, 4-year growing season field experiments on rainfall partitioning were conducted for three dominant shrub species (Haloxylon ammodendron, Nitraria sphaerocarpa, and Calligonum mongolicum) in an oasis–desert ecotone in northwestern China. The revised Gash analytical model was well parameterized, which reliably simulated the cumulative interception loss for sparse shrubs, and the validated model performed better for H. ammodendron, followed by C. mongolicum and N. sphaerocarpa, with relative errors of 8.4%, 15.4%, and 23.9%, respectively. The mean individual interception loss percentage for H. ammodendron (28.4%) was significantly higher than that for C. mongolicum (11.0%) and N. sphaerocarpa (10.9%) (p < 0.05), which could be ascribed to the higher canopy storage capacity and wet-canopy evaporation rate of H. ammodendron. For all shrub species, the majority proportion of interception loss occurred during canopy saturation and drying-out periods, accounting for approximately 79–85% of the cumulative interception loss. Overall, the mean local interception loss of three dominant shrub species in the ecotone removed nearly 17% of the corresponding cumulative rainfall during the growing season. These results not only provide methodological references for estimating the interception loss of sparse vegetation in dryland ecosystems, but also provide scientific insights for water resource management and ecosystem restoration in water-limited regions similar to the experimental site.

Assessing canopy rainfall partitioning by Mediterranean dryland shrubs under extreme rainfall

AbstractIntense rain events have become more frequent in some regions due to climate change, and this trend is particularly concerning in dryland regions where the ecological and geomorphological impacts of rainfall are intimately tied to its intensity. The interception of rainfall by vegetation is a critical process in the water balance of drylands; thus, this study estimated the canopy interception capacity and interception rates as well as stemflow of three typical Mediterranean shrub species (Rosmarinus officinalis, Thymus vulgaris, and Macrochloa tenacissima) of three size classes in Spain under a simulated extreme rainfall rate (~8 mm min−1, historical return period of &gt;100 years). Given that these plants' canopy structures markedly differ from taller woody plants (i.e., trees), a novel method was developed to assess the stemflow fraction. Results showed significant differences in interception amount, rates, and storage capacity among the shrub species, with variations in plant morphology, such as shrub height and canopy diameter, being the key factors determining interception capacity. R. officinalis had the highest interception fraction per unit canopy area, or ‘specific interception,’ (18.4%). In contrast, the lowest specific interception fraction was measured for M. tenacissima (6.5%). Thymus vulgaris was characterized by the highest stemflow yields per unit canopy area (4.85 mm) and fraction (up to 29.6% of rainfall), which was the lowest for M. tenacissima (1.09 mm, ~1%–4%). Strong linear correlations were found between canopy interception and shrub canopy diameter (|r| &gt; −0.51, max = −0.90), when observations were grouped for size class. These linear correlations between shrub morphology and partitioning enabled multiple‐regression linear models to be developed that predicted canopy interception and stemflow with good accuracy (r2 &gt; 0.64, with a maximum of 0.82) from shrub height, canopy diameter, dry biomass, size class, and species. Despite these measurements being conducted under one extreme storm depth and intensity, the results provide: (i) values of rainfall partitioning for important shrub species in Mediterranean dryland environments; and (ii) a simple but reliable model that may be further developed (e.g., embedding variable rainfall values as weather input or incorporating other morphological parameters) and may be integrated into complex hydrological models.

Rainfall interception loss as a function of leaf area index and rainfall by soybean

Rainfall interception loss as a function of leaf area index and rainfall by soybean

A Review of Plastic Film Mulching on Water, Heat, Nitrogen Balance, and Crop Growth in Farmland in China

Plastic film mulching has been widely used to improve crop yield and water use efficiency, although the effects of plastic film mulching on water, heat, nitrogen dynamics, and crop growth are rarely presented comprehensively. This study investigated a large number of studies in film mulching fields from the past 10 years (mostly from 2019 to 2023) and summarized the impact of plastic film mulching, progress in modeling with film mulching, and future research directions. The effects of plastic film mulching were intricate and were influenced by film mulching methods, irrigation systems, crop types, crop growth stages, etc. Overall, plastic film mulching showed a positive effect on improving soil water, temperature, and nitrogen status, enhancing crop transpiration and photosynthetic rates, and promoting crop growth and yield, although film mulching may have negative effects, such as increasing rainfall interception, blocking water entering the soil, and reducing net radiation income. The crop yield and water use efficiency could increase by 39.9–84.7% and 45.3–106.4% under various film mulching methods. Coupled models of soil water and heat transport and crop growth under plastic film mulching conditions have been established by considering the effects of plastic film mulching on the upper boundary conditions of soil water and heat, energy budget and distribution processes, and the exchange of latent and sensible heat between soil and atmosphere. The models have good applicability in film mulched farmland of maize, rice, and potato for different regions of China. Further development is needed for soil water, heat, nitrogen migration, and crop growth models under different plastic film mulching methods, and the acquisition of soil and crop indicators under plastic film mulching conditions based on big data support. The study will provide reference for the subsequent development and innovation of plastic film mulching technology.

Canopy rainfall interception by pine (Pinus hartwegii Lindl) and oyamel [Abies religiosa ( Kunth ) Schltdl. y Cham.] at the Zoquiapan Experimental Forest Station, Mexico

Objective: To quantify and characterize the canopy rainfall interception of twodominant forest species of a coniferous forest in Mexico, in order to determine its magnitude and importance in the hydrological cycle and have a source of estimation of interception to improve the accuracy of water balance calculation.Methodology: Twenty-one rainfall events in the period May-June 2018 were analyzed in two 0.25-ha experimental plots, one with pine (Pinus hartwegii) and theother with oyamel (Abies religiosa), at the Zoquiapan Experimental Forest Station (EFEZ), located in the Sierra Nevada in the State of Mexico. Rainfall was measured with an automated weather station and interception was recorded by placing collectors under the canopy and collars on the trunks.Results: The pine tree P. hartwegii intercepted 16.37% of the precipitation, 79.86% of the throughfall, and 3.74% of the stemflow. For A. religiosa, recorded interception was 24.68%, throughfall 72.42%, and stemflow 2.90%. Precipitation had a linear relationship with both throughfall and stemflow, and an exponential one with canopy rainfall interception.Implications: The analysis should be extended to other rainy periods to strengthen the study.Conclusions: The intercepted volume depends on the forest measurement characteristics and leaf area index (LAI) of the species, and the rainfall amount. The fraction of rainfall intercepted is considerable and should be included in hydrological balances.

Spatio-temporal rainfall interception loss at the catchment scale from earth observation in a data-scarce area, Northern Ethiopia

Rainfall interception loss (EI) is an important spatio-temporal variable in hydrological studies. The EI is required as input of integrated hydrological models, which nowadays are increasingly applied in water resources management. However, the EI is typically not considered or arbitrarily simplified, which causes wrong model parameterization and typical overestimation of water resources. Such problem can be particularly consequential in water-limited environments, where EI represents a substantial percentage of rainfall. The EI is rarely quantified experimentally because field data acquisition for its direct estimation is cumbersome and costly, especially at large catchment/basin scales. Hence, Earth Observation Satellites (EOS) can be used as an alternative source of data acquisition to quantify EI, especially at large spatial scales. The main aim of this study was to estimate the daily variability of rainfall interception loss in the data-scarce Zamra catchment (1588 km2) in Ethiopia, applying the EOS solution of the revised Gash model (RGM). Next to EOS, this study utilized four automated weather station data. To test the RGM assumption permitting the use of rainfall as one storm per rainy day (instead of the event-based rainfall), high temporal resolution (15 min) automated weather-station data was used. The test confirmed the validity of that assumption in the Zamra catchment (ZC), so the daily bias-corrected by station data rainfall was used as input. The weather station data was also used to define the event-based ratio of the mean wet-canopy evaporation rate to the mean rainfall rate (Ec¯/R¯) ranging from ∼0.037 to 0.041 at the low-elevated stations to ∼0.063 at the high-elevated station. As the variability of the Ec¯/R¯ of the three low-elevated stations was pretty uniform, the mean 0.04 was assumed for areas below 2000 m a.s.l., but for the areas above, the Ec¯/R¯ was assigned as altitude-dependent applying geographical weighted regression method. Other biophysical parameters, the fractional canopy cover and the canopy storage capacity obtained from leaf area index, were derived from Sentinel 2. The final EI was highly spatially and temporally variable, ranging from zero at bare lands, to 30% of annual rainfall in forested areas and with ∼4% mean of annual rainfall for the whole ZC. While applying EOS solution of RGM, facilitated with limited amount of ground-based data, the presented study offers an efficient and realistic way of spatio-temporal quantification of EI, particularly suitable for large data-scarce areas such as the ZC.

Progression toward maximum leaf surface storage during the rainfall interception process

AbstractDuring rainfall events, leaves in the canopy absorb kinetic energy from falling raindrops causing the leaves to vibrate after each individual drop impact. Additionally, intercepted water gradually increases on foliar surfaces adding greater mass exerted on each leaf. This accumulated mass of water increases the leaf inclination angle and may enable the drainage of water from the leaf surface as the water drop retention angle is surpassed. This study explored the dynamic process of leaf vibration and changes in steady‐state leaf inclination angles after raindrop impact for three species (Acer saccharinum, Quercus gambelii, and Ulmus pumila) and with four different drop sizes. An incremental increase in steady‐state leaf inclination angle was measured from processing single frames of videos as each additional raindrop impacted leaf surfaces. In general, larger drops increased leaf inclination angles to a larger degree than the smaller drops. As maximum leaf surface storage or the water drop retention angle was approached, water drained from leaf surface causing an abrupt rebound of the leaf inclination angle. The maximum changes in steady‐state leaf inclination angle before rebound (LIAmax) and the number of drops needed for leaf inclination angle rebound were significantly correlated with the initial leaf inclination angle (LIAi) for experiments with A. saccharinum and U. pumila, but not for the experiments with Q. gambelii. No significant correlations were found between LIAmax and any leaf trait (i.e., leaf area, leaf mass, petiole length, petiole diameter, leaf hydrophobicity, and water drop retention) for A. saccharinum and U. pumila; however, a significant negative correlation was found for Q. gambelii between maximum changes in leaf inclination angle and petiole diameter. Of the leaf characteristics examined, leaf surface storage is most influenced by LIAi before drop impact.

Estimating rainfall interception of xerophytic deciduous shrubs by static- and variable-parameter Gash models with stem- and leaf-dominated canopy water storage

The precise modeling of rainfall interception is important to understand the water balance of forest ecosystems, particularly in water-stressed restoration regions. However, xerophytic deciduous shrubs are currently underrepresented in rainfall interception models due to the significant variations in their canopy structures. Therefore, we estimated the rainfall interceptions of four representative deciduous shrubs (Spiraea pubescens, Potentilla fruticose, Hippophae rhamnoides, and Caragana korshinskii) in the semiarid region of northern China using the revised Gash model (RG model) with static parameters and a modified Gash model (MG model) with variable parameters. The results indicate that the MG model outperformed the RG model in studies of S. pubescens and P. fruticose, with regard to the modeling error (6.6%–7.9%), Nash–Sutcliffe model efficiency (0.68–0.86), and the root-mean-square error (0.17–0.71). However, the RG model was better than the MG model for H. rhamnoides and C. korshinskii, with regard to the modeling error (3.6%–6.3%), Nash–Sutcliffe model efficiency (0.82–0.94), and the root-mean-square error (0.17–0.66). The MG model was highly sensitive to changes in the leaf area index, canopy cover, mean evaporation rate, canopy storage capacity, and leaf storage capacity for S. pubescens and P. fruticose. Nevertheless, the RG model demonstrated high sensitivity to changes in the canopy storage capacity and stem storage capacity for H. rhamnoides and C. korshinskii. These indicated that canopy storage capacity has a significant effect on the rainfall interception capabilities of different shrub species, as indicated by both the RG and MG models. This critical indicator was determined by the water storage of stems for H. rhamnoides and C. korshinskii (ranged contribution of 59.5%–81.6%), whereas the water storage of leaves for S. pubescens and P. fruticose (with contributions of 51.3%–80.7%). Therefore, the optimized RG and MG models are recommended for estimating the rainfall interception of xerophytic shrubs with stem-dominated water storage and leaf-dominated water storage, respectively. This study categorizes the applicability of rainfall interception models in terms of important plant traits to precisely assess the water balance of xerophytic deciduous shrub ecosystems. In future studies, leaf configuration and hydrophobicity are highly recommended to be quantified for further improving rainfall interception models.

Water quality improvement project for initial rainwater pollution and its performance evaluation

Efficiently addressing initial rainwater pollution is crucial for mitigating urban water pollution. However, the performance evaluation of initial rainwater pollution control project is rarely introduced. In this study, the architecture of effective comprehensive engineering measures for improving the water quality of initial rainwater in Anhui Province, China, was described. Three water quality indicators, ammonia nitrogen (NH3–N), chemical oxygen demand (COD), and total phosphorus (TP), were selected to explore the severity of urban pollution caused by initial rainwater under various rainfall scenarios. A single-factor evaluation method was used to contrast and assess the benefits of the initial rainfall interception project in terms of water quality enhancement. Results showed that initial rainfall pollution was gentler under light rainfall conditions but more prominent under moderate and heavy conditions. The percentages of NH3–N, COD, and TP in Lotus Pond that met the tertiary drinking water standard were 100%, 74.91%, and 100% with great improvement, and the average concentrations of NH3–N, COD, and TP in Fushan Road Drainage have decreased by 91.43%, 10.49%, and 57.33% respectively, after the construction of the interception project. These indicated that the nitrogen and phosphorus pollution were successfully controlled by the control techniques in both locations, but COD concentration has to be addressed with more specialized strategies. Overall, the water quality improvement project for initial rainwater pollution plays a great role in effectively governing initial rainwater pollution and improving river water quality, and provides an effective technical reference for urban water ecological environment management.

Consideration of vegetation interception of rainfall within the SCS-CN model: Application to the west bank of Dianchi Lake

Study regionThe west bank of Dianchi Lake, China. Study focusThe Soil Conservation Service Curve Number (SCS-CN) model is widely used to simulate rainfall runoff of mountain floods. The determination of the CN parameter within the SCS-CN model is key to accurately simulating runoff. CN is closely related to regional land use, soil type, antecedent moisture conditions and slope. Therefore, this study established an optimized SCS-CN model by comprehensively considering the above factors, particularly the interception of rainfall by vegetation. New hydrological insights for the region(1) The original CN value resulted in underestimation of surface runoff in the study area [Nash-Sutcliffe Efficiency Coefficient (NSE) = 0.2260], indicating that regional differences reduce the applicability of the original CN value; (2) the optimized model considering the slope, antecedent rainfall, and other single or combined factors generated simulations of runoff that were closer to observations (NSE = 0.6811); the accuracy of the CN value can be effectively improved by combining various factors; however, since the CN had not yet reached the optimal value, simulations remained inaccurate; (3) consideration of interception of rainfall by vegetation in the model greatly improved the accuracy of simulated runoff [NSE = 0.8620]; indicating that the impact of vegetation interception of rainfall on surface runoff cannot be ignored. The results demonstrated that the SCS-CN model can provide more accurate simulations of mountain flood runoff in the study area after considering multiple factors, such as vegetation interception of rainfall.

Spatiotemporal dynamics of rainfall interception and effective precipitation in the Loess Plateau after large‐scale afforestation

AbstractThe Grain for Green Program (GFGP) has promoted vegetation restoration and environmental improvement in the Loess Plateau (LP) and has sparked considerable interest in its effects on local hydrological cycle processes. However, few studies have examined the spatiotemporal evolution characteristics of rainfall interception (RI) and its influencing factors in the LP after GFGP implementation, even though RI directly controls the potential available water resources entering the ecosystem (Peffective) and largely influences the changes in hydrological fluxes in water‐limited regions. This study employed the remote sensing (RS)‐Gash model to investigate RI and Peffective in the LP. Results showed that RI and Peffective increased at a rate of 0.7 (p &lt; 0.01) and 2.5 mm/year (p = 0.12), respectively, during the complete implementation of the GFGP (2001–2018). Spatially, the two were dominated by significantly increasing (area share, 50.3%) and nonsignificantly increasing (74.2%) trends, respectively. The dominant drivers of the changes in RI and Peffective are vegetation factors and precipitation, respectively. The results imply that after the implementation of the GFGP, water scarcity in most areas of the LP seems to show signs of improvement, rather than worsening at source. However, people should remain alert about issues that can occur in semihumid areas, including vegetation's degradation due to excessive afforestation or single‐species plantations, particularly at the Ziwuling Mountains. The successful greening experience of the GFGP in the LP is worth promoting, but lessons should also be learned regarding its unsustainability in areas with relatively abundant water.

Assessment of rainfall interception, soil moisture dynamics and seasonal headwaters in a micro-catchment of Western ghats

ABSTRACT The aim of this study is to assess the canopy rainfall interception, surface detention storage, and soil moisture fluctuation in a micro-catchment of a coffee plantation. Field measurements were carried out using 15 funnel-type ordinary rain gauges in an experimental area of 30 m × 30 m to measure the rainfall passing through the upper and lower canopy to estimate interception and throughfall. Rain gauges were placed at different locations to account for variability in net rainfall falling over the catchment. Throughfall measurements were compared with Gross rainfall measurements taken in an open space near to the plot. The overall ratio of the average of net ground precipitation to gross rainfall measured at the open space for the season was 0.82. Analysis for different rainfall intensities showed that lower-intensity rainfall contributes a higher fraction of the rainfall to interception loss. Site-specific field-based equations have been developed to convert the rainfall into throughfall for the agrarian basins of coffee plantations. Soil moisture depletion data revealed that the upper layer of the soil responds to rainfall and atmospheric demand quickly, compared to the deeper soil layers. Thick soil layers require a longer duration to reach field capacities and contribute significant amounts of the flow in seasonal/low-order streams. The discharge measurements after two months of continuous rainfall revealed that soils in plantation fields reach saturation during the monsoon season and release water to maintain flow in non-perennial streams after the monsoon season ends.

Transformation of tall-tussock grasslands and soil water dynamics in the Flooding Pampa

Cow-calf production is the main practice within marginal agricultural lands of the world, like the Flooding Pampa of Argentina, where it promotes the transformation of native tall-tussock grasslands Paspalum quadrifarium into native short-grass grasslands or sown pastures. The effect of these land use changes on water dynamics are not well understood, especially in regions subjected to marked interannual drought and flooding cycles. Here we measured soil properties (infiltration rate, bulk density and soil organic matter), rainfall interception by the canopy, and soil moisture during two years with different annual rainfall. Then, we parameterized a hydrological model (HYDRUS) for inferring consequences of soil water fluxes on water regulation. Infiltration rate was significantly higher in native tall-tussock grasslands than native short-grass grasslands and sown pastures, bulk density was significantly lower in native tall-tussock grasslands than native short-grass grasslands and sown pastures, and soil organic matter was significantly higher in native tall-tussock grasslands than sown pastures. Simulated water dynamics during years of low annual precipitation (summer rainfall deficit), show that transpiration and evaporation from native short-grass grasslands represented 59 % and 23 % of total water balance, whereas transpiration and evaporation from native tall-tussock grasslands represented 70 % and 12 %, respectively. This result reflects the high productive capacity of native tall-tussock grasslands under dry conditions. In contrast, under high annual precipitation (excess during fall and winter), transpiration and evaporation from native short-grass grasslands represented 48 % and 26 % of total water balance, whereas in native tall-tussock grasslands represented 35 % and 9 %, respectively. These results suggest a low capacity of native tall-tussock grasslands to evacuate water excess, especially during fall and winter. The observed differences in water fluxes between native tall-tussock grasslands and native short-grass grasslands are important to understand water dynamics under different climatic conditions and could be useful for adaptation to climate change through ecosystem-based management.

Exploring the potential of machine learning for leaf angle distribution type identification from leveled digital photography: A case study for broadleaf tree and shrub species

Leaf angle distribution (LAD) is an important plant structural trait that determines radiation interception, biomass production, rainfall interception, and evapotranspiration. LAD has remained one of the most poorly constrained parameters and a major source of uncertainty in ecological models due to difficulty in quantification. In this study, we look for a simple, affordable way to estimate leaf angle distribution type by anyone, anywhere. For the first time, we test the possibility of determining LAD type from photographs (816 in total) of single plants from various broadleaf tree and shrub species taken from field works. We used Google's TensorFlow and built models using a convolutional neural network to classify these images by LAD type. The best results, training accuracy of 95% and validation accuracy of 91%, were acquired using the two most distinct LAD types – planophile and erectophile. The accuracy decreased with the addition of categories, as expected. However, our results indicate that the involvement of machine learning may indeed hold the potential to remove the current bottleneck in retrieving the information on LAD.

Drought decreases water storage capacity of two arboreal epiphytes with differing ecohydrological traits

Arboreal epiphytes, plants that grow on trees, can significantly increase rainwater storage and evaporation (i.e., “interception”) within canopies. Drought conditions may affect this hydrological role, as epiphytes' physiological responses change leaf properties that affect water retention. Drought-induced changes in epiphyte water storage capacity could substantially alter canopy hydrology, but have not been studied. We tested the effects of drought on the water storage capacity (Smax) of leaves and leaf properties of two epiphytes with distinct ecohydrological traits: resurrection fern (Pleopeltis polypodioides), and Spanish moss (Tillandsia usneoides). Both species are common in maritime forests of the Southeastern USA, where climate change is expected to decrease precipitation in spring and summer. To simulate drought, we dried leaves to 75 %, 50 %, and ~25 % of fresh weight, and quantified their Smax in fog chambers. We measured relevant leaf properties: hydrophobicity, minimum leaf conductance (gmin; a measure of water loss under drought), and Normalized Difference Vegetative Index (NDVI). We found that drought significantly reduced Smax and increased leaf hydrophobicity for both species, indicating that lower Smax may be due to shedding of droplets. While the overall reduction in Smax did not differ between the two species, they exhibited distinct drought responses. Dehydrated T. usneoides leaves had lower gmin, demonstrating the ability to limit water loss under drought. P. polypodioides increased gmin when dehydrated, consistent with its extraordinary ability to withstand water loss. NDVI decreased with dehydration in T. usneoides but not P. polypodioides. Our results suggest that increased drought may have a dramatic effect on canopy water cycling by reducing the Smax of epiphytes. Reduced rainfall interception and storage in forest canopies could have widespread effects on hydrological cycling, thus understanding the potential feedbacks of plant drought response on hydrology is crucial. This study highlights the importance of connecting foliar-scale plant response with broader hydrological processes.

A Case Study of Leaf Wettability Variability and the Relations with Leaf Traits and Surface Water Storage for Urban Landscape Plants

Leaf wettability, the affinity of a leaf surface to water droplets, affects the interactions between leaves and external environments. This study aimed to determine the interspecific and seasonal variabilities of leaf wettability across 30 common landscape plants, and their relationships with leaf functional traits, surface micromorphology and rainfall interception in Hefei city, China. Results indicated that leaf wettability was species-specific, and the adaxial and abaxial contact angles ranged from 63° to 134° and 66° to 134°, respectively, with the adaxial surface proving more wettable. Leaf wettability gradually increased from spring to winter. Classification of life forms revealed that there were no significant wettability differences among trees, shrubs and herbs, and between evergreen and deciduous plants, but deciduous plants’ wettability increased more significantly in winter. Leaf wettability was not significantly correlated with any leaf functional traits. Single surface microscopic parameters also had low correlations with leaf wettability. Instead, the low-wettability species were found to possess more prominent epidermis cells, dense waxy layers or trichomes on leaf surfaces. Leaf wettability was the best predictor of surface rainwater storage within all functional traits. Our results highlighted that leaf wettability was variable between different species and growth periods due to micromorphological differences, and significantly affected rainfall interception at the leaf scale, which may have great significance for evaluating plant hydrological function in urban areas.

Variability analysis and the conservation capacity of soil water storage under different vegetation types in arid regions

Time-series analysis of soil water storage (SWS) can provide important information on critical hydrological variability related to soil water recharge, retention, and vegetation water consumption, all of which are highly non-linear and non-stationary, making mining and analysis extremely challenging. In this study, Multivariate Empirical Mode Decomposition (MEMD) was used to separate and analyze time-series data on soil moisture, soil temperature, and meteorological factors in three different land types (bare land [BL], grassland [GL], and shrubland [SL]) in the Mu Us Desert, Shaanxi Province, China. Path analysis was then used to reveal the driving force of periodic variability in SWS after decomposition. Using daily SWS data, two new indicators, evapotranspiration capacity (Ke) and rainfall interception capacity (Kp), were also proposed in order to improve the accuracy of soil water conservation capacity calculation. The results revealed strong time-persistent memory of SWS in all land types, with hydrological periodic variability mainly reflected on a monthly scale (34–45 d). The greatest memory period was observed in SL followed by BL and GL. Subsequent path analysis suggested that dry-wet alternation (R2=0.32–0.48) driven by interactions between precipitation, solar radiation, and saturated vapor pressure were the main causes of SWS variability in the summer. While, freeze–thaw cycles (R2=0.73–0.86) driven by the soil temperature and meteorological factors were the main causes of SWS variability in winter. In the root zone (0–150 cm), the water conservation capacity of BL, GL, and SL was 139.24, 38.24, and 24.76 mm/y, respectively. In addition, the Ke/Kp values and MEMD residual component revealed that SL has greater potential for water conservation than GL. Overall, these findings suggest that in order to conserve local groundwater aquifers, areas of BL require appropriate protection in arid regions. The results of this study provide a basis for future analyses of soil moisture variability and water conservation in arid regions.