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Investigation of transient soil moisture profiles yields valuable information of near- surface processes. A recently developed reconstruction algorithm based on the telegraph equation allows the inverse estimation of soil moisture profiles along coated, three rod TDR probes. Laboratory experiments were carried out to prove the results of the inversion and to understand the influence of probe rod deformation and solid objects close to the probe in heterogonous media. Differences in rod geometry can lead to serious misinterpretations in the soil moisture profile but have small influence on the average soil moisture along the probe. Solids in the integration volume have almost no effect on average soil moisture but result in locally slightly decreased moisture values. Inverted profiles obtained in a loamy soil with a clay content of about 16% were in good agreement with independent measurements.
Investigation of transient soil moisture profiles yields valuable information of near- surface processes. A recently developed reconstruction algorithm based on the telegraph equation allows the inverse estimation of soil moisture profiles along coated, three rod TDR probes. Laboratory experiments were carried out to prove the results of the inversion and to understand the influence of probe rod deformation and solid objects close to the probe in heterogeneous media. Differences in rod geometry can lead to serious misinterpretations in the soil moisture profile, but have small influence on the average soil moisture along the probe. Solids in the integration volume have almost no effect on average soil moisture, but result in locally slightly decreased moisture values. Inverted profiles obtained in a loamy soil with a clay content of about 16% were in good agreement with independent measurements.
We conducted a PUB (predictions in ungauged basins) experiment looking at hydrology and crop dynamics in the semi-arid rural Mod catchment in India. The experiment was motivated by the aims (a) to develop a coupled eco-hydrological model capable of analysing land-use strategies concerning crop water need, erosion protection, crop yield and resistivity against droughts and floods, and (b) to assess the feasibility of a strategy for collecting the necessary data in a data-scarce region. Our experiment combines parsimonious data assessment and eco-hydrological model coupling at the lower mesoscale. Linking bottom-up sampling of functionally representative soil classes and top-down regionalization based on spectral properties of the same resulted in a comprehensive distributed data basis for the model. A clear focus on the dominating processes and the catena as the organizing landscape element in the given environmental setting enabled this. We employed the WASA (Water Availability in Semi-Arid environments) model for uncalibrated process-based water balance modelling and integrated a crop simulation subroutine based on the SWAP (Soil Water Atmosphere Plant) model to account for crop dynamics, feedbacks and yield estimation. While we found the data assessment strategy and the hydrological model application largely feasible, in terms of its accounting for scale, processes and model concepts, the simulation of feedbacks with crops was problematic. Contributing to the PUB issue, more general conclusions are drawn concerning spatially-distributed structural information and uncalibrated modelling.
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Editor Z.W. Kundzewicz; Associate editor F. Hattermann
Soil respiration is the second largest flux in the global carbon cycle, yet the underlying below-ground process, carbon dioxide (CO2) production, is not well understood because it can not be measured in the field. CO2 production has frequently been calculated from the vertical CO2 diffusive flux divergence, known as "soil-CO2 profile method". This relatively simple model requires knowledge of soil CO2 concentration profiles and soil diffusive properties. Application of the method for a tropical lowland forest soil in Panama gave inconsistent results when using diffusion coefficients (D) calculated based on relationships with soil porosity and moisture ("physically modeled" D). Our objective was to investigate whether these inconsistencies were related to (1) the applied interpolation and solution methods and/or (2) uncertainties in the physically modeled profile of D. First, we show that the calculated CO2 production strongly depends on the function used to interpolate between measured CO2 concentrations. Secondly, using an inverse analysis of the soil-CO2 profile method, we deduce which D would be required to explain the observed CO2 concentrations, assuming the model perception is valid. In the top soil, this inversely modeled D closely resembled the physically modeled D. In the deep soil, however, the inversely modeled D increased sharply while the physically modeled D did not. When imposing a constraint during the fit parameter optimization, a solution could be found where this deviation between the physically and inversely modeled D disappeared. A radon (Rn) mass balance model, in which diffusion was calculated based on the physically modeled or constrained inversely modeled D, simulated observed Rn profiles reasonably well. However, the CO2 concentrations which corresponded to the constrained inversely modeled D were too small compared to the measurements. We suggest that, in well-structured soils, a missing description of steady state CO2 exchange fluxes across water-filled pores causes the soil-CO2 profile method to fail. These fluxes are driven by the different diffusivities in inter- vs. intra-aggregate pores which create permanent CO2 gradients if separated by a "diffusive water barrier". These results corroborate other studies which have shown that the theory to treat gas diffusion as homogeneous process, a precondition for use of the soil-CO2 profile method, is inaccurate for pore networks which exhibit spatial separation between CO2 production and diffusion out of the soil.
The temporal dynamics of hydrological model performance gives insights into errors that cannot be obtained from global performance measures assigning a single number to the fit of a simulated time series to an observed reference series. These errors can include errors in data, model parameters, or model structure. Dealing with a set of performance measures evaluated at a high temporal resolution implies analyzing and interpreting a high dimensional data set. This paper presents a method for such a hydrological model performance assessment with a high temporal resolution and illustrates its application for two very different rainfall-runoff modeling case studies. The first is the Wilde Weisseritz case study, a headwater catchment in the eastern Ore Mountains, simulated with the conceptual model WaSiM-ETH. The second is the Malalcahuello case study, a headwater catchment in the Chilean Andes, simulated with the physicsbased model Catflow. The proposed time-resolved performance assessment starts with the computation of a large set of classically used performance measures for a moving window. The key of the developed approach is a data-reduction method based on self-organizing maps (SOMs) and cluster analysis to classify the high-dimensional performance matrix. Synthetic peak errors are used to interpret the resulting error classes. The final outcome of the proposed method is a time series of the occurrence of dominant error types. For the two case studies analyzed here, 6 such error types have been identified. They show clear temporal patterns, which can lead to the identification of model structural errors.
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.
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.
Tile drains strongly influence the water cycle in agricultural catchment in terms of water quantity and quality. The connectivity of preferential flow to tile drains can create shortcuts for rapid transport of solutes into surface waters. The leaching of pesticides can be linked to a set of main factors including, rainfall characteristics, soil moisture, chemical properties of the pesticides, soil properties, and preferential flow paths. The connectivity of the macropore system to the tile drain is crucial for pesticide leaching. Concurring influences of the main factors, threshold responses and the role of flow paths are still poorly understood. The objective of this study is to investigate these influences by a replica series of three irrigation experiments on a tile drain field site using natural and artificial tracers together with applied pesticides. We found a clear threshold behavior in the initialization of pesticide transport that was different between the replica experiments. Pre-event soil water contributed significantly to the tile drain flow, and creates a flow path for stored pesticides from the soil matrix to the tile drain. This threshold is controlled by antecedent soil moisture and precipitation characteristics, and the interaction between the soil matrix and preferential flow system. Fast transport of pesticides without retardation and the remobilization could be attributed to this threshold and the interaction between the soil matrix and the preferential flow system. Thus, understanding of the detailed preferential flow processes clearly enhances the understanding of pesticide leaching on event and long term scale, and can further improve risk assessment and modeling approaches. (C) 2014 Elsevier B.V. All rights reserved.
The objective is to compare the time scale of microbial degradation of the herbicide Isoproturon at the end of earthworm burrows with the time scale of microbial degradation in the surrounding soil matrix. To this end, we developed a method which allows the observation of microbial degradation on Isoproturon in macropores under field conditions. Study area was the well-investigated Weiherbach catchment (Kraichgau, SW Germany). The topsoil of a 12 m(2) large plot parcel was removed, the parcel was covered with a tent and instrumented with TDR and temperature sensors at two depths. After preliminary investigations to optimize application and sampling techniques, the bottom of 55 earthworm burrows, located at a depth of 80-100cm, was inoculated with Isoproturon. Within an interval of 8 d, soil material from the bottom of 5-6 earthworm burrows was taken into the laboratory and analyzed for the Isoproturon concentration for investigation of the degradation kinetics. Furthermore, the degradation of Isoproturon in the soil matrix, that surrounded the macropores at the field plot, was observed in the laboratory. Microbial degradation of Isoproturon at the bottom of the earthworm burrows was with a DT-50-value of 15.6 d almost as fast as in the topsoil. In the soil matrix that closely surrounded the center of the earthworm burrows, no measurable degradation was observed within 30 d. The clearly slower degradation in the soil matrix may be likely explained by a lower microbial activity that was observed in the surrounding soil matrix. The results give evidence that deterministic modeling of the fate of pesticides once transported into heterogeneous subsoils by preferential flow requires an accuracy of a few centimeters in terms of predicting spatial locations: time scales of microbial degradation in the subsoil drop almost one order of magnitude, in case the herbicides dislocates from the bottom of an earthworm burrow a few centimeter into the surrounding soil matrix. If at all, predictions of such an accuracy can only be achieved at locations at sites where the soil hydraulic properties and the macropore system are known at a very high spatial resolution
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.
The phrase form and function was established in architecture and biology and refers to the idea that form and functionality are closely correlated, influence each other, and co-evolve. We suggest transferring this idea to hydrological systems to separate and analyze their two main characteristics: their form, which is equivalent to the spatial structure and static properties, and their function, equivalent to internal responses and hydrological behavior. While this approach is not particularly new to hydrological field research, we want to employ this concept to explicitly pursue the question of what information is most advantageous to understand a hydrological system. We applied this concept to subsurface flow within a hillslope, with a methodological focus on function: we conducted observations during a natural storm event and followed this with a hillslope-scale irrigation experiment. The results are used to infer hydrological processes of the monitored system. Based on these findings, the explanatory power and conclusiveness of the data are discussed. The measurements included basic hydrological monitoring methods, like piezometers, soil moisture, and discharge measurements. These were accompanied by isotope sampling and a novel application of 2-D time-lapse GPR (ground-penetrating radar). The main finding regarding the processes in the hillslope was that preferential flow paths were established quickly, despite unsaturated conditions. These flow paths also caused a detectable signal in the catchment response following a natural rainfall event, showing that these processes are relevant also at the catchment scale. Thus, we conclude that response observations (dynamics and patterns, i.e., indicators of function) were well suited to describing processes at the observational scale. Especially the use of 2-D time-lapse GPR measurements, providing detailed subsurface response patterns, as well as the combination of stream-centered and hillslope-centered approaches, allowed us to link processes and put them in a larger context. Transfer to other scales beyond observational scale and generalizations, however, rely on the knowledge of structures (form) and remain speculative. The complementary approach with a methodological focus on form (i.e., structure exploration) is presented and discussed in the companion paper by Jackisch et al. (2017).
The study deals with the identification and characterization of rapid subsurface flow structures through pedo- and geo-physical measurements and irrigation experiments at the point, plot and hillslope scale. Our investigation of flow-relevant structures and hydrological responses refers to the general interplay of form and function, respectively. To obtain a holistic picture of the subsurface, a large set of different laboratory, exploratory and experimental methods was used at the different scales. For exploration these methods included drilled soil core profiles, in situ measurements of infiltration capacity and saturated hydraulic conductivity, and laboratory analyses of soil water retention and saturated hydraulic conductivity. The irrigation experiments at the plot scale were monitored through a combination of dye tracer, salt tracer, soil moisture dynamics, and 3-D time-lapse ground penetrating radar (GPR) methods. At the hillslope scale the subsurface was explored by a 3-D GPR survey. A natural storm event and an irrigation experiment were monitored by a dense network of soil moisture observations and a cascade of 2-D time-lapse GPR "trenches". We show that the shift between activated and non-activated state of the flow paths is needed to distinguish structures from overall heterogeneity. Pedo-physical analyses of point-scale samples are the basis for sub-scale structure inference. At the plot and hillslope scale 3-D and 2-D time-lapse GPR applications are successfully employed as non-invasive means to image subsurface response patterns and to identify flow-relevant paths. Tracer recovery and soil water responses from irrigation experiments deliver a consistent estimate of response velocities. The combined observation of form and function under active conditions provides the means to localize and characterize the structures (this study) and the hydrological processes (companion study Angermann et al., 2017, this issue).
The phrase form and function was established in architecture and biology and refers to the idea that form and functionality are closely correlated, influence each other, and co-evolve. We suggest transferring this idea to hydrological systems to separate and analyze their two main characteristics: their form, which is equivalent to the spatial structure and static properties, and their function, equivalent to internal responses and hydrological behavior. While this approach is not particularly new to hydrological field research, we want to employ this concept to explicitly pursue the question of what information is most advantageous to understand a hydrological system. We applied this concept to subsurface flow within a hillslope, with a methodological focus on function: we conducted observations during a natural storm event and followed this with a hillslope-scale irrigation experiment. The results are used to infer hydrological processes of the monitored system. Based on these findings, the explanatory power and conclusiveness of the data are discussed. The measurements included basic hydrological monitoring methods, like piezometers, soil moisture, and discharge measurements. These were accompanied by isotope sampling and a novel application of 2-D time-lapse GPR (ground-penetrating radar). The main finding regarding the processes in the hillslope was that preferential flow paths were established quickly, despite unsaturated conditions. These flow paths also caused a detectable signal in the catchment response following a natural rainfall event, showing that these processes are relevant also at the catchment scale. Thus, we conclude that response observations (dynamics and patterns, i.e., indicators of function) were well suited to describing processes at the observational scale. Especially the use of 2-D time-lapse GPR measurements, providing detailed subsurface response patterns, as well as the combination of stream-centered and hillslope-centered approaches, allowed us to link processes and put them in a larger context. Transfer to other scales beyond observational scale and generalizations, however, rely on the knowledge of structures (form) and remain speculative. The complementary approach with a methodological focus on form (i.e., structure exploration) is presented and discussed in the companion paper by Jackisch et al. (2017).
The study deals with the identification and characterization of rapid subsurface flow structures through pedo- and geo-physical measurements and irrigation experiments at the point, plot and hillslope scale. Our investigation of flow-relevant structures and hydrological responses refers to the general interplay of form and function, respectively. To obtain a holistic picture of the subsurface, a large set of different laboratory, exploratory and experimental methods was used at the different scales. For exploration these methods included drilled soil core profiles, in situ measurements of infiltration capacity and saturated hydraulic conductivity, and laboratory analyses of soil water retention and saturated hydraulic conductivity. The irrigation experiments at the plot scale were monitored through a combination of dye tracer, salt tracer, soil moisture dynamics, and 3-D time-lapse ground penetrating radar (GPR) methods. At the hillslope scale the subsurface was explored by a 3-D GPR survey. A natural storm event and an irrigation experiment were monitored by a dense network of soil moisture observations and a cascade of 2-D time-lapse GPR "trenches". We show that the shift between activated and non-activated state of the flow paths is needed to distinguish structures from overall heterogeneity. Pedo-physical analyses of point-scale samples are the basis for sub-scale structure inference. At the plot and hillslope scale 3-D and 2-D time-lapse GPR applications are successfully employed as non-invasive means to image subsurface response patterns and to identify flow-relevant paths. Tracer recovery and soil water responses from irrigation experiments deliver a consistent estimate of response velocities. The combined observation of form and function under active conditions provides the means to localize and characterize the structures (this study) and the hydrological processes (companion study Angermann et al., 2017, this issue).
[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
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.