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Stormflow generation in headwater catchments dominated by subsurface flow has been studied extensively, yet catchments dominated by surface flow have received less attention. We addressed this by testing whether stormflow chemistry is controlled by either (a) the event-water signature of overland flow, or (b) the pre-event water signature of return flow. We used a high-resolution hydrochemical data set of stormflow and end-members of multiple storms in an end-member mixing analysis to determine the number of end-members needed to explain stormflow, characterize and identify potential end-members, calculate their contributions to stormflow, and develop a conceptual model of stormflow. The arrangement and relative positioning of end-members in stormflow mixing space suggest that saturation excess overland flow (26-48%) and return flow from two different subsurface storage pools (17-53%) are both similarly important for stormflow. These results suggest that pipes and fractures are important flow paths to rapidly release stored water and highlight the value of within-event resolution hydrochemical data to assess the full range and dynamics of flow paths.

In Lutzito catchment on Barro Colorado Island, Panama, extraordinarily high suspended-sediment yields of 1-2Mgha-1year-1 were generated despite the dense forest cover coinciding with erosion-resistant soils. We hypothesized that ant mounding activity is an important zoogeomorphological mechanism in this area, providing relevant quantities of easily transportable material at the soil surface. To test this hypothesis, all ant mound material was collected collected for dry mass determination from thirty 4m2 plots installed in the study area every 1-3days during the 39-day sampling period. Additionally, three ground-nesting ant species responsible for mounds in the study area, Ectatomma ruidum, Trachymyrmex cornetzi and Strumigenys marginiventris, were identified. On the basis of the total of 1.38kg of material collected in the wet season of 2011, the estimate for the whole 8months wet season amounts to 725kgha-1. As this value is in the same order of magnitude as sediment output, it shows that ants may act as important ecosystem engineers and contribute to sediment production here by providing large quantities of fine-grained, readily erodible material at the soil surface for subsequent transport to the streambed. Copyright (c) 2014 John Wiley & Sons, Ltd.

In undisturbed tropical montane rainforests massive organic layers accommodate the majority of roots and only a small fraction of roots penetrate the mineral soil. We investigated the contribution of vegetation to slope stability in such environments by modifying a standard model for slope stability to include an organic layer with distinct mechanical properties. The importance of individual model parameters was evaluated using detailed measurements of soil and vegetation properties to reproduce the observed depth of 11 shallow landslides in the Andes of southern Ecuador. By distinguishing mineral soil, organic layer and above-ground biomass, it is shown that in this environment vegetation provides a destabilizing effect mainly due to its contribution to the mass of the organic layer (up to 973 t ha-1 under wet conditions). Sensitivity analysis shows that the destabilizing effect of the mass of soil and vegetation can only be effective on slopes steeper than 37.9 degrees. This situation applies to 36% of the study area. Thus, on the steep slopes of this megadiverse ecosystem, the mass of the growing forest promotes landsliding, which in turn promotes a new cycle of succession. This feedback mechanism is worth consideration in further investigations of the impact of landslides on plant diversity in similar environments.

Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region's predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.

The investigation of throughfall patterns has received considerable interest over the last decades. And yet, the geographical bias of pertinent previous studies and their methodologies and approaches to data analysis cast a doubt on the general validity of claims regarding spatial and temporal patterns of throughfall. We employed 220 collectors in a 1-ha plot of semideciduous tropical rain forest in Panama and sampled throughfall during a period of 14 months. Our analysis of spatial patterns is based on 60 data sets, whereas the temporal analysis comprises 91 events. Both data sets show skewed frequency distributions. When skewness arises from large outliers, the classical, nonrobust variogram estimator overestimates the sill variance and, in some cases, even induces spurious autocorrelation structures. In these situations, robust variogram estimation techniques offer a solution. Throughfall in our plot typically displayed no or only weak spatial autocorrelations. In contrast, temporal correlations were strong, that is, wet and dry locations persisted over consecutive wet seasons. Interestingly, seasonality and hence deciduousness had no influence on spatial and temporal patterns. We argue that if throughfall patterns are to have any explanatory power with respect to patterns of near-surface processes, data analytical artifacts must be ruled out lest spurious correlation be confounded with causality; furthermore, temporal stability over the domain of interest is essential.

Fast analysis of different species of molecules in soils is investigated by capillary electrophoresis (CE). Several CE techniques for the analysis of inorganic ions and carbohydrates have been tested. With regard to the intents of pedologists and the usually large number of soil analyses a bundle of CE systems is proposed, capable of effecting time-saving soil analyses. Adapted electrolyte systems recently published and new separation systems are described. Examples of the application of these methods to two different soil samples are presented.

Throughfall measurements were made under primary terra firme rainforest in the Rio Pichis valley, in the Upper Amazon Basin of Peru. Based on 214 precipitation events over nearly 18 months, throughfall was estimated to be 83.1±8.8% of gross precipitation. Regression analysis of all events revealed that gross precipitation is the only significant explanatory variable; the use of one-burst events does not significantly improve the regression relationship. Gross precipitation is, however, a poor predictor of throughfall for small rainfall events. The two forest structure parameters, canopy capacity, S, and free throughfall coefficient, p, were determined to be 1.3±0.2 mm and 0.32±0.18 mm. Rainfall intensity was found to influence these parameters. New methods which attempt to minimize the influence of meteorologic variables are used to estimate the potential values of these canopy parameters.

[1] Observations of hydrological response often exhibit considerable scatter that is difficult to interpret. In this paper, we examine runoff production of 53 sprinkling experiments on the water-repellent soils in the southern Alps of Switzerland; simulated plot scale tracer transport in the macroporous soils at the Weiherbach site, Germany; and runoff generation data from the 2.3-km(2) Tannhausen catchment, Germany, that has cracking soils. The response at the three sites is highly dependent on the initial soil moisture state as a result of the threshold dynamics of the systems. A simple statistical model of threshold behavior is proposed to help interpret the scatter in the observations. Specifically, the model portrays how the inherent macrostate uncertainty of initial soil moisture translates into the scatter of the observed system response. The statistical model is then used to explore the asymptotic pattern of predictability when increasing the number of observations, which is normally not possible in a field study. Although the physical and chemical mechanisms of the processes at the three sites are different, the predictability patterns are remarkably similar. Predictability is smallest when the system state is close to the threshold and increases as the system state moves away from it. There is inherent uncertainty in the response data that is not measurement error but is related to the observability of the initial conditions.

This study investigates spatial patterns of Ks and tests the hypothesis of whether structural variance emerges from noise with increasing sampling precision. We analyzed point measurements of Ks along independent transects at sampling intervals of 25, 10, 1 and 0.25 m. The field area is a tropical rainforest catena (i.e. toposequence) characterized by systematic downslope changes in soil properties including color (red to yellow), mineralogy (kaolinite- illite to kaolinite) and texture (sandy clay to sand). Independent tramsects spanning the entire catena at lag intervals of 25 and 10 in reveal little to no spatial patterns in Ks; i.e. scatter plots are noisy and lack apparent spatial trends, and semivariograms suggest little to no autocorrelation in Ks. As sampling precision is increased (h = 1 and 0.25 m), spatial patterns emerge in Ks for the downslope areas, in which distinctive hydraulic boundaries in Ks correlate with relatively small-scale, topography-controlled soils with coarse textures (greater than or equal to 80% sand). For these areas, semivariograms of Ks and those of %sand and %clay exhibit similar spatial structure characterized by small nugget variances and large ranges, and nugget variance is reduced as sampling precision increases from 1 to 0.25 m. In the upslope, clay-rich locations along this toposequence, Ks exhibits few spatial patterns, irrespective of sampling scale. For these locations, scatter plots are noisy without apparent spatial trends, and semivariograms show almost complete nugget variance, suggesting little to no correlation in this hydraulic parameter at any scale. This study suggests that in the absence of coarse textures (greater than or equal to 80% sand), there is little predictability in Ks, even at sampling intervals of 0.25 m. We believe this lack of spatial structure is due to a predominance of small-scale processes such as biological activity that largely control Ks in this forested setting. (C) 2003 Elsevier B.V. All rights reserved

What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.