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Challenges in understanding the hydrologic controls on the mobility of slow-moving landslides
(2011)
Slow-moving landslides are a wide-spread type of active mass movement, can cause severe damages to infrastructure, and may be a precursor of sudden catastrophic slope failures. Pore-water pressure is commonly regarded as the most important among a number of possible factors controlling landslide velocity. We used high-resolution monitoring data to explore the relations of landslide mobility and hydrologic processes at the Heumoser landslide in Austria, which is characterized by continuous slow movement along a shear zone. Movement rates showed a seasonality that was associated with elevated pore-water pressures. Pore pressure monitoring revealed a system of confined and separated aquifers with differing dynamics. Analysis of a simple infinite slope mobility model showed that small variations in parameters, along with measured pore pressure dynamics, provided a perfect match to our observations. Modeling showed a stabilizing effect of snow cover due to the additional load. This finding was supported by a multiple regression model, which further suggested that effective pore pressures at the slip surface were partially differing from the borehole observations and were related to preferential infiltration and subsurface flow in adjacent areas. It appears that in a setting like the Heumoser landslide, hydrologic processes delicately influence slope mobility through their control on pore pressure dynamics and the weight of the landslide body, which challenges observation and modeling. Moreover, it appears that their simplicity, and especially their high sensitivity to parameter variations, limits the conclusions that can be drawn from infinite slope models.
Rain fall-runoff response in temperate humid headwater catchments is mainly controlled by hydrolo gical processes at the hillslope scale. Applied tracer experiments with fluore scent dye and salt tracers are well known tools in groundwater studies at the large scale and vadose zone studies at the plot scale, where they provide a means to characterise subsurface flow. We extend this approach to the hillslope scale to investigate saturated and unsaturated flow path s concertedly at a forested hill slope in the Austrian Alps. Dye staining experiments at the plot scale revealed that crack s and soil pipe s function as preferential flow path s in the fine-textured soils of the study area, and these preferenti al flow structures were active in fast subsurface transport of tracers at the hillslope scale. Breakthrough curves obtained under steady flow conditions could be fitted well to a one-dimensional convection-dispersion model. Under natural rain fall a positive correlation of tracer concentrations to the transient flows was observed. The results of this study demon strate qualitative and quantitative effects of preferential flow feature s on subsurface stormflow in a temperate humid headwater catchment. It turn s out that , at the hill slope scale, the interaction s of structures and processes are intrinsically complex, which implies that attempts to model such a hillslope satisfactorily require detailed investigation s of effective structures and parameters at the scale of interest.
Due to its high spatial and temporal variability, preferential flow is difficult to measure and quantify. Earthworms create macropores that provide common pathways for preferential flow. Therefore in this article, we link earthworm abundance to macropore numbers and hydrological effectiveness, with the future aim to use species distribution models of earthworms for the spatial parameterization of preferential flow.
Earthworms are generally categorized into three ecological types with varying burrowing behaviour, resulting in a different impact on soil hydrological processes. Therefore, we studied the relationships between the abundance of the earthworm ecological types and macropores of different size classes and in different soil depths. The abundance and biomass of earthworms were well correlated to different sizes of macropores in different soil depths. This is mainly the case for the larger, vertically oriented macropores (>6mm diameter), which are generally connected to the soil surface and hydrologically most effective. The correlation of total earthworm biomass and macropores ranges from 072 to 089 for different soil depths.
Although there is quite some variation in infiltration patterns, infiltration from macropores into the matrix is profile-specific, as it varies strongly between profiles, but not within one profile. Macropore coating seems to have a larger effect on this macropore matrix interaction than the soil physical properties of the matrix. Although the amount of macropores and their effectiveness are clearly related to the earthworm distribution, the variation in infiltration from macropores to soil matrix should be further studied.
Earthworms play a key role in regulating soil ecosystem functions and services. The small scale variability in earthworm abundance is often found to be very high, which is a problem for representative sampling of earthworm abundance at larger scales. In agricultural fields, soil tillage may influence both the average earthworm abundance as well as the spatial distribution of earthworms. Therefore we studied the abundance and spatial pattern of the different ecological earthworm types, i.e. endogeic, epigeic and anecic earthworms, in four agricultural fields differing in soil tillage (two fields with regular tillage and two fields with conservation tillage) and surrounding land use (other cropped fields or apple orchard and forest). To this aim we sampled earthworms on a total number of 430 plots (50 x 50 cm(2)) using a combination of extraction with mustard solution and hand sorting. The results exhibit large differences in average earthworm abundance between the four fields. Only one of the two fields with conservation tillage had a comparatively very high overall abundance of earthworms. Furthermore, we found a high spatial variability of earthworms within the field scale often exhibiting a patchy distribution. We detected a trend of decreasing earthworm abundances from the field border into the field for different earthworm groups on each of the fields. In three fields with low total earthworm abundance (and only very few epigeic earthworms) there was a short scale autocorrelation with ranges varying strongly for the endogeic earthworms (37.9 m, 62.6 m, and 85.2 m) compared to anecic earthworms (19.8 m, 22.8 m, and 27.4 m). In the field with high abundance, after trend removal, the variogram models for anecic and endogeic earthworms were rejected based on their negative explained variances. On this field, we found only a short scale autocorrelation for the epigeic earthworms with a range of 143 m. Based on these results it seems that ploughing alone cannot explain the differences in abundance and range of autocorrelation found on the four fields. The trend of strongly decreasing earthworm abundance from the field border into the field in the one field with high abundance does indicate that the field border or surrounding land use may also influence the recolonization of fields, but more research is required to provide further evidence for this hypothesis. Due to the very different patterns of earthworm distributions in the fields it remains difficult to recommend an optimal number and distance of samples to obtain a representative earthworm abundance for the field scale. (C) 2016 Elsevier B.V. All rights reserved.
Dry lands are exposed to a highly variable environment and face a high risk of degradation. The effects of climate change are likely to increase this risk; thus a profound knowledge of the system dynamics is crucial for evaluating management options. This applies particularly for the interactions between water and vegetation, which exhibit strong feedbacks. To evaluate these feedbacks and the effects of climate change on soil moisture dynamics, we developed a generic, process-based, spatially explicit soil moisture model of two soil layers, which can be coupled with vegetation models. A time scale relevant for ecological processes can be simulated without difficulty, and the model avoids complex parameterization with data that are unavailable for most regions of the world. We applied the model to four sites in Israel along a precipitation and soil type gradient and assessed the effects of climate change by comparing possible climatic changes with present climate conditions. The results show that in addition to temperature, the total amount of precipitation and its intra-annual variability are an important driver of soil moisture patterns. This indicates that particularly with regard to climate change, the approach of many ecological models that simulate water dynamics on an annual base is far too simple to make reliable predictions. Thus, the introduced model can serve as a valuable tool to improve present ecological models of dry lands because of its focus on the applicability and transferability.
Drylands worldwide are exposed to a highly variable environment and face a high risk of degradation. The effects of global climate change such as altered precipitation patterns and increased temperature leading to reduced water availability will likely increase this risk. At the same time, an elevated atmospheric CO2 level could mitigate the effects of reduced water availability by increasing the water use efficiency of plants. To prevent degradation of drylands, it is essential to understand the underlying processes that affect water availability and vegetation cover. Since water and vegetation are strongly interdependent in water-limited ecosystems, changes can lead to highly non- linear effects. We assess these effects by developing an ecohydrological model of soil moisture and vegetation cover. The water component of the model simulates the daily dynamics of surface water and water contents in two soil layers. Vegetation is represented by two functional types: shrubs and grasses. These compete for soil water and strongly influence hydrological processes. We apply the model to a Namibian thornbush savanna and evaluate the separate and combined effects of decreased annual precipitation, increased temperature, more variable precipitation and elevated atmospheric CO2 on soil moisture and on vegetation cover. The results show that two main factors control the response of plant types towards climate change, namely a change in water availability and a change in water allocation to a specific plant type. Especially, reduced competitiveness of grasses can lead to a higher risk of shrub encroachment in these systems.
[1] Spatial patterns of land surface and subsurface characteristics often exert significant control over hydrological processes at many scales. Recognition of the dominant controls at the watershed scale, which is a prerequisite to successful prediction of system responses, will require significant progress in many different research areas. The development and improvement of techniques for mapping structures and spatiotemporal patterns using geophysical and remote sensing techniques would greatly benefit watershed science but still requires a significant synthesis effort. Effective descriptions of hydrological systems will also significantly benefit from new scaling and averaging techniques, from new mathematical description for spatial pattern/structures and their dynamics, and also from an understanding and quantification of structure and pattern-building processes in different compartments ( soils, rocks, and land surface) and at different scales. The advances that are needed to tackle these complex challenges could be greatly facilitated through the development of an interdisciplinary research framework that explores instrumentation, theory, and simulation components and that is implemented in a coordinated manner
Low-cost monitoring of snow height and thermal properties with inexpensive temperature sensors
(2011)
Small, self-recording temperature sensors were installed at several heights along a metal rod at five locations in a case study catchment. For each sensor, the presence or absence of snow cover was determined on the basis of its insulating effect and the resulting reduction of the diurnal temperature oscillations. Sensor coverage was then converted into a time series of snow height for each location. Additionally, cold content was calculated. Snow height and cold content provide valuable information for spring flood prediction.
Good agreement of estimated snow heights with reference measurements was achieved and increased discharge in the study catchment coincided with low cold content of the snow cover. The results of the proposed distributed assessment of snow cover and snow state show great potential for (i) flood warning, (ii) assimilation of snow state data and (iii) modelling snowmelt process.
In this paper we investigate the use of hydrological models as learning tools to help improve our understanding of the hydrological functioning of a catchment. With the model as a hypothetical conceptualization of how dominant hydrological processes contribute to catchment-scale response, we investigate three questions: (1) During which periods does the model (not) reproduce observed quantities and dynamics? (2) What is the nature of the error during times of bad model performance? (3) Which model components are responsible for this error? To investigate these questions, we combine a method for detecting repeating patterns of typical differences between model and observations (time series of grouped errors, TIGER) with a method for identifying the active model components during each simulation time step based on parameter sensitivity (temporal dynamics of parameter sensitivities, TEDPAS). The approach generates a time series of occurrence of dominant error types and time series of parameter sensitivities. A synoptic discussion of these time series highlights deficiencies in the assumptions about the functioning of the catchment. The approach is demonstrated for the Weisseritz headwater catchment in the eastern Ore Mountains. Our results indicate that the WaSiM-ETH complex grid-based model is not a sufficient working hypothesis for the functioning of the Weisseritz catchment and point toward future steps that can help improve our understanding of the catchment.