Using geophysical techniques to characterize tillage effect on soil properties

Tillage practices influence physical, chemical, and biological soil properties, which also affect soil quality and consequently plant growth. In this study, the main objective was to evaluate the effect of different tillage systems on soil physical properties by using geophysical methods, namely, ground-penetrating radar (far-field and near-field GPR), capacitance probes (ThetaProbe and 5TE), electromagnetic induction (EMI) (Profiler and EM38), soil sampling, and by soil penetrometer. Since 2005, three contrasting tillage systems were applied on different plots of an agricultural field: i) conventional tillage (CT) with mouldboard ploughing to 27 cm depth, ii) deep loosening tillage (DL) with a heavy tine cultivator to 30 cm depth, and iii) reduced tillage (RT) with a spring tine cultivator to 10 cm depth. The geophysical and soil strength measurements were performed in April 2010. We observed that tillage influences the soil resistance (deeper tillage decreases soil resistance), which could be partly seen in the radar data. Soil water content reference measurements (capacitance probes and soil sampling) were in a relatively good agreement with the water content estimates from far-field GPR. We also observed that the tillage influences surface water content. Mean surface water content was significantly lower for CT than for DL and RT, which was partly explained by lower macropore connectivity between the topsoil and the deeper layers after conventional tillage. This study confirms the potential of GPR and EMI sensors for soil physical properties determination at the field scale and for the characterization of agricultural management practices

Assessment of the position accuracy of a single-frequency GPS receiver designed for electromagnetic induction surveys

In precision agriculture (PA), compact and lightweight electromagnetic induction (EMI) sensors have extensively been used to investigate the spatial variability of soil, to evaluate crop performance, and to identify management zones by mapping soil apparent electrical conductivity (ECa), a surrogate for primary and functional soil properties. As reported in the literature, differential global positioning systems (DGPS) with sub-metre to centimetre accuracy have been almost exclusively used to geo-reference these measurements. However, with the ongoing improvements in Global Navigation Satellite System (GNSS) technology, a single state-of-the-art DGPS receiver is likely to be more expensive than the geophysical sensor itself. In addition, survey costs quickly multiply if advanced real time kinematic correction or a base and rover configuration is used. However, the need for centimetre accuracy for surveys supporting PA is questionable as most PA applications are concerned with soil properties at scales above 1 m. The motivation for this study was to assess the position accuracy of a GNSS receiver especially designed for EMI surveys supporting PA applications. Results show that a robust, low-cost and single-frequency receiver is sufficient to geo-reference ECa measurements at the within-field scale. However, ECa data from a field characterized by a high spatial variability of subsurface properties compared to repeated ECa survey maps and remotely sensed leaf area index indicate that a lack of positioning accuracy can constrain the interpretability of such measurements. It is therefore demonstrated how relative and absolute positioning errors can be quantified and corrected. Finally, a summary of practical implications and considerations for the geo-referencing of ECa data using GNSS sensors are presented

Multi-site Calibration and Validation of a Net Ecosystem Carbon Exchange Model for Croplands

Croplands play an important role in the carbon budget of many regions. However, the estimation of their carbon balance remains difficult due to diversity and complexity of the processes involved. We report the coupling of a one-dimensional soil water, heat, and CO2 flux model (SOILCO2), a pool concept of soil carbon turnover (RothC), and a crop growth module (SUCROS) to predict the net ecosystem exchange (NEE) of carbon. The coupled model, further referred to as AgroC, was extended with routines for managed grassland as well as for root exudation and root decay. In a first step, the coupled model was applied to two winter wheat sites and one upland grassland site in Germany. The model was calibrated based on soil water content, soil temperature, biometric, and soil respiration measurements for each site, and validated in terms of hourly NEE measured with the eddy covariance technique. The overall model performance of AgroC was sufficient with a model efficiency above 0.78 and a correlation coefficient above 0.91 for NEE. In a second step, AgroC was optimized with eddy covariance NEE measurements to examine the effect of different objective functions, constraints, and data-transformations on estimated NEE. It was found that NEE showed a distinct sensitivity to the choice of objective function and the inclusion of soil respiration data in the optimization process. In particular, both positive and negative day‑ and nighttime fluxes were found to be sensitive to the selected optimization strategy. Additional consideration of soil respiration measurements improved the simulation of small positive fluxes remarkably. Even though the model performance of the selected optimization strategies did not diverge substantially, the resulting cumulative NEE over simulation time period differed substantially. Therefore, it is concluded that data-transformations, definitions of objective functions, and data sources have to be considered cautiously when a terrestrial ecosystem model is used to determine NEE by means of eddy covariance measurements

Development and analysis of the Soil Water Infiltration Global database

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type ( ∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it

Hydrologic-hydraulic modelling in the Vezza catchment (Alpi Apuane, Italy): An area prone to flash floods and debris flows

The Alpi Apuane (Italy) are located a few kilometres from the coast of the Ligurian Sea, and they are characterized by peak elevations up to two thousand meters above sea level, as well as narrow, deeply incised valleys and steep slopes. Due to these morphoclimatic conditions, heavy rains are frequent, causing floods, landslides, and debris flows, particularly within the Vezza catchment. In this work we applied two different hydrological-hydraulic models to this catchment, focusing on the catastrophic debris flow event of June 19, 1996. Firstly, recent, well-documented rainfall events were used to validate the engineering geological model of the study area, then we began to analyse the rainfall-runoff and debris flow event of 1996 in the Cardoso sub-catchment. As models, we used the FLO-2D and a novel experimental model, developed by some of the authors and based on TRENT2D, in which the dynamic of a debris flow is fully coupled with the rainfall-runoff response of a basin. Preliminary results show how the used approach allowed us to gain some insight into the hydrological behaviour and debris flows formation, erosion, transport, and deposition in the Cardoso sub-catchment

Pedotransfer functions in Earth system science: challenges and perspectives

Soil, through its various functions, plays a vital role in the Earth's ecosystems and provides multiple ecosystem services to humanity. Pedotransfer functions (PTFs) are simple to complex knowledge rules that relate available soil information to soil properties and variables that are needed to parameterize soil processes. In this paper, we review the existing PTFs and document the new generation of PTFs developed in the different disciplines of Earth system science. To meet the methodological challenges for a successful application in Earth system modeling, we emphasize that PTF development has to go hand in hand with suitable extrapolation and upscaling techniques such that the PTFs correctly represent the spatial heterogeneity of soils. PTFs should encompass the variability of the estimated soil property or process, in such a way that the estimation of parameters allows for validation and can also confidently provide for extrapolation and upscaling purposes capturing the spatial variation in soils. Most actively pursued recent developments are related to parameterizations of solute transport, heat exchange, soil respiration and organic carbon content, root density and vegetation water uptake. Further challenges are to be addressed in parameterization of soil erosivity and land use change impacts at multiple scales. We argue that a comprehensive set of PTFs can be applied throughout a wide range of disciplines of Earth system science, with emphasis on land surface models. Novel sensing techniques provide a true breakthrough for this, yet further improvements are necessary for methods to deal with uncertainty and to validate applications at global scale

Effects of input data aggregation on simulated crop yields in temperate and Mediterranean climates

The modelling exercise for this study was highly supported by partner universities and research institutes in the framework of the MACSUR project and financially supported by the German Federal Ministry of Education and Research BMBF (FKZ 2815ERA01J) in the framework of the funding measure “Soil as a Sustainable Resource for the Bioeconomy – BonaRes”, project “BonaRes (Module B): BonaRes Centre for Soil Research (FKZ BOMA03037514, 031B0026A and 031A608A) and by the Ministry of Agriculture and Food (BMEL) in the framework of the MACSUR project (FKZ 2815ERA01J). In addition, the relevant co-authors from the partner institutes are separately financed by their respective projects. AV, EC, and EL were supported by The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (220-2007-1218) and by the strategic funding ‘Soil-Water-Landscape’ from the faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences). JC thank the INRA ACCAF metaprogramm for funding. KCK, CN, XS and TS were supported by MACSUR2 (FKZ 031B0039C). MK thanks for the funding by the UK BBSRC (BB/N004922/1) and the MAXWELL HPC team of the University of Aberdeen for providing equipment and support for the DailyDayCent simulations. FE acknowledges support by the German Science Foundation (project EW 119/5-1). GRM, TG, and FE thank Andreas Enders and Gunther Krauss (INRES, University of Bonn) for support. The authors also would like to acknowledge the support provided by the BMBF and the valuable comments of the scientists of the Institut für Nutzpflanzenwissenschaften und Ressourcenschutz (INRES), University of Bonn, Germany.Peer reviewedPostprin

On Infiltration and Infiltration Characteristic Times

In his seminal paper on the solution of the infiltration equation, Philip (1969), https://doi-org.proxy.library.uu.nl/10.1016/b978-1-4831-9936-8.50010-6 proposed a gravity time, tgrav, to estimate practical convergence time and the time domain validity of his infinite time series expansion, TSE, for describing the transient state. The parameter tgrav refers to a point in time where infiltration is dominated equally by capillarity and gravity as derived from the first two (dominant) terms of the TSE. Evidence suggests that applicability of the truncated two-term equation of Philip has a time limit requiring higher-order TSE terms to better describe the infiltration process for times exceeding that limit. Since the conceptual definition of tgrav is valid regardless of the infiltration model used, we opted to reformulate tgrav using the analytic implicit model proposed by Parlange et al. (1982), https://doi-org.proxy.library.uu.nl/10.1097/00010694-198206000-00001 valid for all times and related TSE. Our derived gravity times ensure a given accuracy of the approximations describing transient states, while also providing insight about the times needed to reach steady state. In addition to the roles of soil sorptivity (S) and the saturated (Ks) and initial (Ki) hydraulic conductivities, we explored the effects of a soil specific shape parameter β, involved in Parlange's model and related to the type of soil, on the behavior of tgrav. We show that the reformulated tgrav (notably urn:x-wiley:00431397:media:wrcr26009:wrcr26009-math-0001 where F(β) is a β-dependent function) is about three times larger than the classical tgrav given by urn:x-wiley:00431397:media:wrcr26009:wrcr26009-math-0002. The differences between the classical tgrav,Philip and the reformulated tgrav increase for fine-textured soils, attributed to the time needed to attain steady-state infiltration and thus i + infiltration for inferring soil hydraulic properties. Results show that the proposed tgrav is a better indicator of time domain validity than tgrav,Philip. For the attainment of steady-state infiltration, the reformulated tgrav is suitable for coarse-textured soils. Still neither the reformulated tgrav nor the classical tgrav,Philip are suitable for fine-textured soils for which tgrav is too conservative and tgrav,Philip too short. Using tgrav will improve predictions of the soil hydraulic parameters (particularly Ks) from infiltration data compared to tgrav,Philip

Impact of Spatial Soil and Climate Input Data Aggregation on Regional Yield Simulations

This work was financially supported by the German Federal Ministry of Food and Agriculture (BMEL) through the Federal Office for Agriculture and Food (BLE), (2851ERA01J). FT and RPR were supported by FACCE MACSUR (3200009600) through the Finnish Ministry of Agriculture and Forestry (MMM). EC, HE and EL were supported by The Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning (220-2007-1218) and by the strategic funding ‘Soil-Water-Landscape’ from the faculty of Natural Resources and Agricultural Sciences (Swedish University of Agricultural Sciences) and thank professor P-E Jansson (Royal Institute of Technology, Stockholm) for support. JC, HR and DW thank the INRA ACCAF metaprogramm for funding and Eric Casellas from UR MIAT INRA for support. CB was funded by the Helmholtz project “REKLIM—Regional Climate Change”. CK was funded by the HGF Alliance “Remote Sensing and Earth System Dynamics” (EDA). FH was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) under the Grant FOR1695. FE and SS acknowledge support by the German Science Foundation (project EW 119/5-1). HH, GZ, SS, TG and FE thank Andreas Enders and Gunther Krauss (INRES, University of Bonn) for support. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD