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Soils in various places of the Panama Canal Watershed feature a low saturated hydraulic conductivity (K-s) at shallow depth, which promotes overland-flow generation and associated flashy catchment responses. In undisturbed forests of these areas, overland flow is concentrated in flow lines that extend the channel network and provide hydrological connectivity between hillslopes and streams. To understand the dynamics of overland-flow connectivity, as well as the impact of connectivity on catchment response, we studied an undisturbed headwater catchment by monitoring overland-flow occurrence in all flow lines and discharge, suspended sediment, and total phosphorus at the catchment outlet. We find that connectivity is strongly influenced by seasonal variation in antecedent wetness and can develop even under light rainfall conditions. Connectivity increased rapidly as rainfall frequency increased, eventually leading to full connectivity and surficial drainage of entire hillslopes. Connectivity was nonlinearly related to catchment response. However, additional information on factors such as overland-flow volume would be required to constrain relationships between connectivity, stormflow, and the export of suspended sediment and phosphorus. The effort to monitor those factors would be substantial, so we advocate applying the established links between rain event characteristics, drainage network expansion by flow lines, and catchment response for predictive modeling and catchment classification in forests of the Panama Canal Watershed and in similar regions elsewhere.
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.
In the humid tropics, continuing high deforestation rates are seen alongside an increasing expansion of secondary forests. In order to understand and model the consequences of these dynamic land-use changes for regional water cycles, the response of soil hydraulic properties to forest disturbance and recovery has to be quantified.At a site in the Brazilian Amazonia, we annually monitored soil infiltrability and saturated hydraulic conductivity (K-s) at 12.5, 20 cm, and 50 cm soil depth after manual forest conversion to pasture (year zero to four after pasture establishment), and during secondary succession after pasture abandonment (year zero to seven after pasture abandonment). We evaluated the hydrological consequences of the detected changes by comparing the soil hydraulic properties with site-specific rainfall intensities and hydrometric observations. Within one year after grazing started, infiltrability and K-s at 12.5 and 20 cm depth decreased by up to one order of magnitude to levels which are typical for 20-year-old pasture. In the three subsequent monitoring years, infiltrability and K-s remained stable. Land use did not impact on subsoil permeability. Whereas infiltrability values are large enough to allow all rainwater to infiltrate even after the conversion, the sudden decline of near-surface K-s is of hydrological relevance as perched water tables and overland flow occur more often on pastures than in forests at our study site. After pasture abandonment and during secondary succession, seven years of recovery did not suffice to significantly increase infiltrability and K-s at 12.5 depth although a slight recovery is obvious. At 20 cm soil depth, we detected a positive linear increase within the seven-year time frame but annual means did not differ significantly. Although more than a doubling of infiltrability and K-s is still required to achieve pre-disturbance levels, which will presumably take more than a decade, the observed slight increases of K-s might already decrease the probability of perched water table generation and overland flow development well before complete recovery.
The influence of land-use changes on soil hydraulic properties : implications for runoff generation
(2006)
Changes in soil hydraulic properties following ecosystem disturbances can become relevant for regional water cycles depending on the prevailing rainfall regime. In a tropical montane rainforest ecosystem in southern Ecuador, plot- scale investigations revealed that man-made disturbances were accompanied by a decrease in mean saturated hydraulic conductivity (Ks), whereas mean Ks of two different aged landslides was undistinguishable from the reference forest. Ks spatial structure weakened after disturbances in the topsoil. We used this spatial-temporal information combined with local rain intensities to assess the probability of impermeable soil layers under undisturbed, disturbed, and regenerating land-cover types. We furthermore compared the Ecuadorian man-made disturbance cycle with a similar land-use sequence in a tropical lowland rainforest region in Brazil. The studied montane rainforest is characterized by prevailing vertical flowpaths in the topsoil, whereas larger rainstorms in the study area potentially result in impermeable layers below 20 cm depth. In spite of the low frequency of such higher-intensity events, they transport a high portion of the annual runoff and may therefore significant for the regional water cycle. Hydrological flowpaths under two studied landslides are similar to the natural forest except for a somewhat higher probability of impermeable layer formation in the topsoil of the 2-year-old landslide. In contrast, human disturbances likely affect near-surface hydrology. Under a pasture and a young fallow, impermeable layers potentially develop already in the topsoil for larger rain events. A 10-year-old fallow indicates regeneration towards the original vertical flowpaths, though the land-use signal was still detectable. The consequences of land-cover change on near-surface hydrological behaviour are of similar magnitude in the tropical montane and the lowland rainforest region. This similarity can be explained by a more pronounced drop of soil permeability after pasture establishment in the montane rainforest region in spite of the prevailing much lower rain intensities.
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.
A wide range of basic and applied problems in water resources research requires high-quality estimates of the spatial mean of throughfall. Many throughfall sampling schemes, however, are not optimally adapted to the system under study. The application of inappropriate sampling schemes may partly reflect the lack of generally applicable guidelines on throughfall sampling strategies. In this study we conducted virtual sampling experiments using simulated fields which are based on empirical throughfall data from three structurally distinct forests (a 12-year old teak plantation, a 5-year old young secondary forest, and a 130-year old secondary forest). In the virtual sampling experiments we assessed the relative error of mean throughfall estimates for 38 different throughfall sampling schemes comprising a variety of funnel- and trough-type collectors and a large range of sample sizes. Moreover, we tested the performance of each scheme for both event-based and accumulated throughfall data. The key findings of our study are threefold. First, as errors of mean throughfall estimates vary as a function of throughfall depth, the decision on which temporal scale (i.e. event-based versus accumulated data) to sample strongly influences the required sampling effort. Second, given a chosen temporal scale throughfall estimates can vary considerably as a function of canopy complexity. Accordingly, throughfall sampling in simply structured forests requires a comparatively modest effort, whereas heterogeneous forests can be extreme in terms of sampling requirements, particularly if the focus is on reliable data of small events. Third, the efficiency of trough-type collectors depends on the spatial structure of throughfall. Strong, long-ranging throughfall patterns decrease the efficiency of troughs substantially. Based on the results of our virtual sampling experiments, which we evaluated by applying two contrasting sampling approaches simultaneously, we derive readily applicable guidelines for throughfall monitoring. (C) 2014 Elsevier B.V. All rights reserved.
estimating mean throughfall
(2016)
The selection of an appropriate spatial extent of a sampling plot is one among several important decisions involved in planning a throughfall sampling scheme. In fact, the choice of the extent may determine whether or not a study can adequately characterize the hydrological fluxes of the studied ecosystem. Previous attempts to optimize throughfall sampling schemes focused on the selection of an appropriate sample size, support, and sampling design, while comparatively little attention has been given to the role of the extent. In this contribution, we investigated the influence of the extent on the representativeness of mean throughfall estimates for three forest ecosystems of varying stand structure. Our study is based on virtual sampling of simulated throughfall fields. We derived these fields from throughfall data sampled in a simply structured forest (young tropical forest) and two heterogeneous forests (old tropical forest, unmanaged mixed European beech forest). We then sampled the simulated throughfall fields with three common extents and various sample sizes for a range of events and for accumulated data. Our findings suggest that the size of the study area should be carefully adapted to the complexity of the system under study and to the required temporal resolution of the throughfall data (i.e. event-based versus accumulated). Generally, event-based sampling in complex structured forests (conditions that favor comparatively long autocorrelations in throughfall) requires the largest extents. For event-based sampling, the choice of an appropriate extent can be as important as using an adequate sample size. (C) 2016 Elsevier B.V. All rights reserved.