A comparison of three canopy interception models for a leafless mixed deciduous forest stand in the eastern United States

Canopy interception of incident precipitation is a critical component of the forest water balance during each of the four seasons. Models have been developed to predict precipitation interception from standard meteorological variables because of acknowledged difficulty in extrapolating direct measurements of interception loss from forest to forest. No known study has compared and validated canopy interception models for a leafless deciduous forest stand in the eastern United States. Interception measurements from an experimental plot in a leafless deciduous forest in northeastern Maryland (39°42'N, 75°5'W) for 11 rainstorms in winter and early spring 2004/05 were compared to predictions from three models. The Mulder model maintains a moist canopy between storms. The Gash model requires few input variables and is formulated for a sparse canopy. The WiMo model optimizes the canopy storage capacity for the maximum wind speed during each storm. All models showed marked underestimates and overestimates for individual storms when the measured ratio of interception to gross precipitation was far more or less, respectively, than the specified fraction of canopy cover. The models predicted the percentage of total gross precipitation (PG) intercepted to within the probable standard error (8.1%) of the measured value: the Mulder model overestimated the measured value by 0.1% of PG; the WiMo model underestimated by 0.6% of PG; and the Gash model underestimated by 1.1% of PG. The WiMo model’s advantage over the Gash model indicates that the canopy storage capacity increases logarithmically with the maximum wind speed. This study has demonstrated that dormant-season precipitation interception in a leafless deciduous forest may be satisfactorily predicted by existing canopy interception models

Spatio-temporal variability of stable isotopes (18 O and 2H) in soil and xylem waters under Mediterranean conditions.

Soil profiles and trees twigs were sampled in the Can Vila Mediterranean catchment (0.56 km2; Vallcebre Research catchments, NE Spain) to evaluate the spatial variability of the isotopic signature (18O and 2H) of xylem and bulk soil waters at the plot scale and between different locations within the catchment. During two one day sampling campaigns with different antecedent soil moisture conditions, soil samples (0-10, 10-20, 20-30, 40-50 and 90-100 cm) and xylem samples (3 trees per plot) were collected in six Scots pine stands distributed throughout the catchment. Moreover, the water stable isotopes analysed were collected in rainfall, groundwater and streamwater at the catchment outlet during and between the sampling campaigns. Water from soil and xylem samples was extracted by cryogenic vacuum distillation and isotope analyses were obtained by infrared spectroscopy. Stable isotopes ratios of bulk soil water and xylem water fell below the local meteoric water line (LMWL) in both sampling campaigns. In contrast, groundwater ratios fell along the LMWL, being well mixed with stream water. A marked vertical variation in soil water isotopes was observed for the dry campaign in all profiles, with enriched shallow horizons indicating evaporation. This variation was not observed for the wet campaign. Moreover, the spatial variation across the catchment was much greater for the dry campaign compared to the wet campaign. A marked variability in the xylem isotopic signature among trees of the same plot was observed for both sampling campaigns. Finally, in some plots and for both campaigns, the isotopic signature of xylem water was more evaporated than that of bulk soil water. There was no clear pattern relating the topographic index, as an indicator of saturation conditions of the sampling location within the catchment, with soil water isotopic signature. Nor was there a clear relationship found between the isotopic signature of pines¿ xylem and tree characteristics, such as DBH, height, or tree competition index

Commentary: What We Know About Stemflow's Infiltration Area

[No abstract available

Peak grain forecasts for the US High Plains amid withering waters

Irrigated agriculture contributes 40% of total global food production. In the US High Plains, which produces more than 50 million tons per year of grain, as much as 90% of irrigation originates from groundwater resources, including the Ogallala aquifer. In parts of the High Plains, groundwater resources are being depleted so rapidly that they are considered nonrenewable, compromising food security. When groundwater becomes scarce, groundwater withdrawals peak, causing a subsequent peak in crop production. Previous descriptions of finite natural resource depletion have utilized the Hubbert curve. By coupling the dynamics of groundwater pumping, recharge, and crop production, Hubbert-like curves emerge, responding to the linked variations in groundwater pumping and grain production. On a state level, this approach predicted when groundwater withdrawal and grain production peaked and the lag between them. The lags increased with the adoption of efficient irrigation practices and higher recharge rates. Results indicate that, in Texas, withdrawals peaked in 1966, followed by a peak in grain production 9 y later. After better irrigation technologies were adopted, the lag increased to 15 y from 1997 to 2012. In Kansas, where these technologies were employed concurrently with the rise of irrigated grain production, this lag was predicted to be 24 y starting in 1994. In Nebraska, grain production is projected to continue rising through 2050 because of high recharge rates. While Texas and Nebraska had equal irrigated output in 1975, by 2050, it is projected that Nebraska will have almost 10 times the groundwater-based production of Texas

A review of stemflow generation dynamics and stemflow-environment interactions in forests and shrublands

Many geoscientists now recognize stemflow as an important phenomenon which can exert considerable effects on the hydrology, biogeochemistry, and ecology of wooded ecosystems and shrublands. Despite the explosive growth of stemflow research, until this review there has been no comprehensive attempt to summarize and synthesize this literature since 2003. Topical areas of substantive new knowledge in stemflow research include the following: (1) the interrelationships among stemflow and meteorological conditions, especially within individual rain events; (2) the dynamic interplay between stemflow and canopy structure; (3) stemflow and the cycling of solutes and transport of particulate matter; (4) stemflow and its interactions with canopy fungi and corticolous lichens; and (5) stemflow-soil interactions. Each of these five topical areas of substantive new stemflow research is summarized and synthesized, with areas of future research opportunities discussed. In addition, we have reviewed the parameters which can be used to describe stemflow and critically evaluate their utility for different purposes. This review makes a call for scientists studying stemflow to utilize common metrics in an effort to increase the cross-site comparability of stemflow studies. Capitalizing on the insights of prior research, exciting research opportunities await hydrologists, biogeoscientists, and forest ecologists who will conduct studies to deepen our knowledge of stemflow which will enable a better and more accurate framing of stemflow in the larger context of watershed hydrology and biogeochemistry

Advancing ecohydrology in the 21st century: A convergence of opportunities

Nature‐based solutions for water‐resource challenges require advances in the science of ecohydrology. Current understanding is limited by a shortage of observations and theories that can further our capability to synthesize complex processes across scales ranging from submillimetres to tens of kilometres. Recent developments in environmental sensing, data, and modelling have the potential to drive rapid improvements in ecohydrological understanding. After briefly reviewing advances in sensor technologies, this paper highlights how improved measurements and modelling can be applied to enhance understanding of the following ecohydrological examples: interception and canopy processes, root uptake and critical zone processes, and up‐scaled effects of land use on streamflow. Novel and improved sensors will enable new questions and experiments, while machine learning and empirical methods provide additional opportunities to advance science. The synergy resulting from the convergence of these parallel developments will provide new insight into ecohydrological processes and thereby help identify nature‐based solutions to address water‐resource challenges in the 21st century.This paper stems from discussions at the Ettersburg Ecohydrology Workshop, which was held in Ettersburg, Germany, in October 2018. Funding for the Ettersburg Ecohydrology Workshop was graciously provided by the UNIDEL Foundation, Inc. and the University of Delaware. The authors kindly recognize the administrative support of Sandy Raymond before, during, and after the workshop. Her attention to detail and high degree of professionalism helped make the workshop a success. B. Michalzik is recognized for finding the Schloss Ettersburg (the venue of the workshop) and serving as the local point of contact for the workshop. Finally, the authors thank the staff of the Schloss Ettersburg, especially Frau S. Wagner, for a memorable workshop experience. The authors kindly thank David Aldred for drafting Figure 1b. The authors declare no conflict of interest.Peer reviewe

Solid-state 13C NMR characterization of surface fire effects on the composition of organic matter in both soil and soil solution from a coniferous forest

Wildfires change the chemical composition of soil organic matter (SOM). Since the effects of fires on organic matter (OM) in soil solution are largely unknown, we sought to compare the quality of dissolved organic matter (DOM) and total organic matter (TOM =DOM +particulate OM) between burned and control sites. The sites were subjected to a low-intensity surface fire in a coniferous forest in Germany dominated by spodic Cambisols derived from Triassic sandstone. Soil solutions from three different soil horizons (O, Ah, Bw), and throughfall (TF) were analyzed using solid state 13C NMR spectroscopy, allowing us to track the initial fire impact on OM vertically through the soil profile and 70 days after the fire. In addition, organic layer samples were analyzed by 13C NMR spectroscopy to compare the OM quality. Under control conditions, properties of SOM influence the chemical composition of DOM and TOM in soil solutions. However, with fire, there is an initial increase in aromatic C in SOM, but not in DOM and TOM. Seventy days after the fire treatment, the aromatic C fraction in soil solutions of O and Ah layers increased, possibly due to accelerated oxidation processes, which would make the aromatic C more water-soluble. Our findings highlight the importance of short-term low-intensity fire-induced changes on forest soils that are useful to those seeking to better understand and model the temporal variability in the response of soil chemistry to fire to improve our knowledge of TOM and DOM dynamics in soils

Rainfall partitioning by vegetation in China: A quantitative synthesis

Rainfall partitioning into stemflow, throughfall, and interception loss by vegetation alters hydrological and biogeochemical fluxes between vegetation and soil. Here, we compiled a comprehensive dataset of rainfall partitioning by forests, shrublands, croplands, and grasslands in China from 287 peer reviewed papers (71 in English and 216 in Chinese). Based on this dataset, we summarized the best-fit functions reported for rainfall partitioning (in both mm and %) as a function of rainfall amount, as well as the rainfall thresholds for throughfall and stemflow initiation. We explored the pattern of the proportions of stemflow, throughfall, and interception loss of vegetation in China, and performed boosted regression trees (BRT) analysis to model the relative effects of cross-site biotic and abiotic predictors on each of the rainfall partitioning fluxes (%). Our results identified the scarcity of rainfall partitioning data, particularly for grasslands. A substantial variability of each rainfall partitioning flux (mm) could be explained solely by rainfall amount, with median R2 values of 0.91, 0.99, and 0.82 for stemflow, throughfall, and interception loss, respectively, and with linear functions most often reported as the best-fit functions. Significant differences (p < 0.0001) were detected in rainfall thresholds for initiating stemflow (median: 3.3 mm; interquartile range, IQR: 1.8–5.4 mm) and throughfall (median: 1.2 mm; IQR: 0.8–2.2 mm). Stemflow (%) had a median (IQR) of 2.7 % (1.2–6.0 %), and that value was 74.3 % (66.7–80.3 %) for throughfall (%) and 21.6 % (16.3–28.5 %) for interception loss (%), respectively. Significant differences were detected in the proportion of stemflow (p < 0.001) and throughfall (p < 0.01) between forests and shrublands, respectively; whereas no significant differences in the proportion of interception loss were found among vegetation types. BRT analysis indicated that of the eleven biotic and abiotic predictors examined, six were classified as significant predictors in determining stemflow (%) and interception loss (%), respectively, whereas throughfall (%) had four significant predictors. Non-linear partial effects of predictors on rainfall partitioning fluxes were prevalent. This study avails a global readership to the findings of a large cache of Chinese studies that have been inaccessible hitherto, providing a mechanistic understanding of the effects of cross-site biotic and abiotic predictors on rainfall partitioning fluxes.This research was funded by the Youth Innovation Promotion Association of Chinese Academy of Sciences (grant 2019415), and the National Natural Science Foundation of China (grants 41901038 and 31971452)