Soil Compaction Effects on Root-Zone Hydrology and Vegetation in Boreal Forest Clearcuts

Soil compaction is a common consequence of forestry traffic traversing unprotected, moist soils; it decreases porosity and affects hydraulic conductivity even in coarse-textured soils. The aim here was to study root-zone hydrology and vegetation in three microsites (in, between, and beside wheel tracks) 4 to 5 yr after forwarder traffic, on stony and sandy till soils in two clearcuts in northern Sweden. Measurements of soil volumetric water content (VWC), vegetation indicators and one-dimensional hydrological modeling (Hydrus-1D) of wheel tracks and undisturbed soil were conducted. Soil VWC was monitored hourly during 2017 and 2018 in three or four plots along a slope on each site. Soil VWC was also measured once with a portable sensor in 117 plots along two slopes at each site, where the vegetation was recorded and analyzed using Ellenberg indicator indexes. Soil VWC was highest in wheel tracks and lowest between tracks; this was corroborated by the species composition in the wheel tracks (Ellenberg indicator for soil moisture). Bare soil was more frequent in wheel tracks and between tracks than in undisturbed soil. The model simulations indicated that the changed soil hydraulic properties influenced the VWC results in the wheel tracks. However, the differences in average pressure heads in the root zone were small between the microsites and only apparent during dry periods. In the wheel tracks, air-filled porosity was <0.10 m3 m-3, indicating insufficient soil aeration during 82% (Site T) and 23% (Site R) of the 2017 growing season. Insufficient aeration could be one explanation for the presence of some still unvegetated areas

Form and function in hillslope hydrology : in situ imaging and characterization of flow-relevant structures

Thanks to Elly Karle and the Engler-BunteInstitute, KIT, for the IC measurements of bromide. We are grateful to Selina Baldauf, Marcel Delock, Razije Fiden, Barbara Herbstritt, Lisei Köhn, Jonas Lanz, Francois Nyobeu, Marvin Reich and Begona Lorente Sistiaga for their support in the lab and during fieldwork, as well as Markus Morgner and Jean Francois Iffly for technical support and Britta Kattenstroth for hydrometeorological data acquisition. Laurent Pfister and Jean-Francois Iffly from the Luxembourg Institute of Science and Technology (LIST) are acknowledged for organizing the permissions for the experiments. Moreover, we thank Markus Weiler (University of Freiburg) for his strong support during the planning of the hillslope experiment and the preparation of the manuscript. This study is part of the DFG-funded CAOS project “From Catchments as Organised Systems to Models based on Dynamic Functional Units” (FOR 1598). The manuscript was substantially improved based on the critical and constructive comments of the anonymous reviewers, Christian Stamm and Alexander Zimmermann, and the editor Ross Woods during the open review process, which is highly appreciated.Peer reviewedPublisher PD

Data assimilation of in situ soil moisture measurements in hydrological models: third annual doctoral progress report, work plan and achievements

Efficient water utilization and optimal water supply/distribution to increase food and fodder productivity are of utmost importance in confronting worldwide water scarcity, climate change, growing populations and increasing water demands. In this respect, irrigation efficiency, which is influenced by the type of irrigation and irrigation scheduling, is an essential issue for achieving higher productivity. To improve irrigation strategies in precision agriculture, soil water status can be more accurately described using a combination of advanced monitoring and modeling. Our study focuses on the combination of high resolution hydrological data with hydrological models that predict water flow and solute (pollutants and salts) transport and water redistribution in agricultural soils under irrigation. Field plots of a potato farmer in a sandy region in Belgium were instrumented to continuously monitor soil moisture and water potential before, during and after irrigation in dry summer periods. The aim is to optimize the irrigation process by assimilating online sensor field data into process based models. This research is part of Activity 305 ‘Precision agriculture and remote sensing’ of the VITO GWO and is also part of the strategic cooperation with UGent within the platform ‘Managing Natural Resources’. Over the past 2 years, we applied a combination of in-situ monitoring and numerical modeling -Hydrus 1D- to estimate water content fluctuations in a heterogeneous sandy grassland soil under irrigation with water table fluctuating between 80 and 155 cm. Over the last year, more sampling and analyses were carried out to further characterize the hydraulic properties over the entire field. Modeling results for the field demonstrated clearly the profound effect of the position of the GWL, and to a lesser extent, the effect of spatially variable soil hydraulic properties (Ks, n and α) on the estimated water content in the sandy two-layered soil under grass. Our results show that currently applied uniform water distribution using sprinkler irrigation seems not to be efficient since at locations with shallow groundwater, the amount of water applied will be excessive as compared to the plant requirements while in locations with a deeper GWL, requirements will not be met. To derive the optimal parameter set best describing the measured soil moisture content, 37 optimization scenarios were conducted with two to six parameters using various parameter combinations for the two soil layers. The best performing parameter optimization scenario was a 2-parameter scenario with Ks optimized for each layer. The results showed a better identifiability of the parameters (less correlations among parameters) with equal performance as compared to three, four or six parameter optimization. Model predictions using the calibrated model (with data from 2012) for an independent data set of soil moisture data in the validation period (2013) showed satisfactory performance of the model in view of irrigation management purposes. Comparing the degree of water stress for different optimization scenarios of groundwater depth, showed that grass was exposed to water stress in summer in 2013 but not for such a long period as compared to the 2012 growing season. The degree of water stress simulated with Hydrus 1D suggested to increase the irrigation amount in 2012 and 2013 and at least one or two times in the summer (June and July) and further distributing the amount of irrigation during the growing season, instead of using a huge amount of irrigation later in the season, as is common practice by the farmer. A second part of the study focused on finding a relation between measured soil hydraulic properties and apparent electrical conductivity ECa. Our measurements of hydraulic properties of the field clearly confirm that there is considerable spatial variability in the field and that this has an impact on the simulation of soil moisture content. Therefore this should be taken into account when upscaling soil hydraulic properties to the field scale in order to in understand and model flow, solute and energy fluxes in the field and develop strategies for efficient irrigation. Upscaling soil hydraulic properties to the field scale can be done by linking them to apparent electrical conductivity (ECa), which can be measured efficiently and inexpensively so a spatially dense dataset for describing within-field spatial soil variability can be generated. In this study relations between the spatial variation of soil hydraulic properties and apparent soil electrical conductivity ECa measured with EM38 and DUALEM-21S sensors at two depths of explorations (DOE) 0-50 and 0-100 cm were investigated. Two predictive modelling approaches, i.e. i) a simple regression and ii) applying Archie’s laws for saturated and unsaturated conditions in combination with MVG equations, were developed and it was compared how they were able to explain the observed values of hydraulic parameters. Results demonstrated the spatial variability and heterogeneity of ECa and soil hydraulic properties Ks, α and n. We derived a regression relationship between log Ks and ECa measured with DUALEM (r2≥0.70) and with EM38 (r2>0.46) sensors. The predicted results were tested vs measured data and confirmed that the performance of DUALEMp,100-Ks model is relatively better than that of the same sensor with lower DOE and of the EM38 sensor (RMSE = 1.31 cmh-1, R2 = 0.55). The relationships between MVG shape parameters and ECa datasets were generally poor (0.05<R2<0.26). In the second approach, we showed that the water retention curve can be translated to ECa-(h) and ECa-Se relations by combining the MVG equations and Archie’s law. Results also show that reformulating the MVG equations based on ECa-Se relationships can help to estimate unsaturated hydraulic conductivity at the field scale. In the third year, a second study site has been set up in a nearby field where potatoes are grown and has been instrumented with soil moisture sensors, tensiometers, groundwater level loggers and a weather station. Field hydraulic properties for the field will be derived using the equations developed for the first study site and the modeling approach developed for the first field will be tested here. Also quasi 3D-modelling of water flow at the field scale will be conducted. In this modeling set-up, the field will be modeled as a collection of 1D-columns representing the different field conditions (combination of soil properties, GWL, root zone depth). Combining this model with crop based models such as LINGRA-N or Aquacrop gives a direct simulation of the impact of irrigation strategies on crop yield at the field scale

PRENOLIN project. Results of the validation phase at sendai site

One of the objectives of the PRENOLIN project is the assessment of uncertainties associated with non-linear simulation of 1D site effects. An international benchmark is underway to test several numerical codes, including various non-linear soil constitutive models, to compute the non-linear seismic site response. The preliminary verification phase (i.e. comparison between numerical codes on simple, idealistic cases) is now followed by the validation phase, which compares predictions of such numerical estimations with actual strong motion data recorded from well-known sites. The benchmark presently involves 21 teams and 21 different non-linear computations. Extensive site characterization was performed at three sites of the Japanese KiK-net and PARI networks. This paper focuses on SENDAI site. The first results indicate that a careful analysis of the data for the lab measurement is required. The linear site response is overestimated while the non-linear effects are underestimated in the first iteration. According to these observations, a first set of recommendations for defining the non-linear soil parameters from lab measurements is proposed. PRENOLIN is part of two larger projects: SINAPS@, funded by the ANR (French National Research Agency) and SIGMA, funded by a consortium of nuclear operators (EDF, CEA, AREVA, ENL)

Impact of Groundwater Flow on Permafrost Degradation and Transportation Infrastructure Stability

INE/AUTC 13.0

Soil moisture and matric potential-an open field comparison of sensor systems

Soil water content and matric potential are central hydrological state variables. A large variety of automated probes and sensor systems for state monitoring exist and are frequently applied. Most applications solely rely on the calibration by the manufacturers. Until now, there has been no commonly agreed-upon calibration procedure. Moreover, several opinions about the capabilities and reliabilities of specific sensing methods or sensor systems exist and compete. A consortium of several institutions conducted a comparison study of currently available sensor systems for soil water content and matric potential under field conditions. All probes were installed at 0.2mb.s. (metres below surface), following best-practice procedures. We present the set-up and the recorded data of 58 probes of 15 different systems measuring soil moisture and 50 further probes of 14 different systems for matric potential. We briefly discuss the limited coherence of the measurements in a cross-correlation analysis. The measuring campaign was conducted during the growing period of 2016. The monitoring data, results from pedophysical analyses of the soil and laboratory reference measurements for calibration are published in Jackisch et al. (2018, https://doi.org/10.1594/PANGAEA.892319)

Calibration of a granular matrix sensor for suction measurements in partially saturated pyroclastic soil

Field monitoring of soil moisture and matrix suction is a useful tool for the implementation of a reliable early warning system against rainfall-induced landslide occurrence. Several test fields have been set up in Campania region (southern Italy), frequently affected by flow-like landslides involving pyroclastic soil cover. In particular, at the Mount Faito test site (Lattari Mountains, southeast of Naples), field matric suctions were measured over two years by conventional jet-fill tensiometers and granular matrix sensors (Watermark, Irrometer®) at different depths. Granular matrix sensor is a resistive device that is more and more spread in agriculture applications and that may also be used for geotechnical purposes thanks to a suitable calibration. In order to gain the calibration curve of the Watermark sensor, two small tip tensiometers (STT) and one High Capacity Tensiometer (HCT) were installed at the same depth of the Watermark sensor in the partially saturated pyroclastic soil sampled at the topsoil of the Mount Faito test site. Tests were carried out in the laboratory by performing drying and wetting phases on undisturbed soil sample. By coupling resistance measurements by Watermark and matrix suction provided by the reference tensiometers, it was possible to derive the non-linear relationship between these two quantities. The soil retention curve was also determined thanks to the installation in the soil sample of a decagon probe previously calibrated in the same pyroclastic soil

Development and Validation of a New Calibration Model for Diviner 2000® Probe Based on Soil Physical Attributes

This study aimed to develop a new model, valid for soil with and without expandable characters, to estimate volumetric soil water content (θ) from readings of scaled frequency (SF) acquired with the Diviner 2000® sensor. The analysis was carried out on six soils collected in western Sicily, sieved at 5 mm, and repacked to obtain the maximum and minimum bulk density (ρb). During an air-drying process SF values, the corresponding gravimetric soil water content (U) and ρb were monitored. In shrinking/swelling clay soils, due to the contraction process, the variation of dielectric permittivity was affected by the combination of the mutual proportions between the water volumes and the air present in the soil. Thus, to account for the changes of ρb with U, the proposed model assumed θ as the dependent variable being SF and ρb the independent variables; then the model’s parameters were estimated based on the sand and clay fractions. The model validation was finally carried out based on data acquired in undisturbed monoliths sampled in the same areas. The estimated θ, θestim, was generally close to the corresponding measured, θmeas, with Root Mean Square Errors (RMSE) generally lower than 0.049 cm3 cm−3, quite low Mean Bias Errors (MBE), ranging between −0.028 and 0.045 cm3 cm−3, and always positive Nash-Sutcliffe Efficiency index (NSE), confirming the good performance of the model

Monitoring and Analysis of Frozen Debris Lobes, Phase I

INE/AUTC 12.2