A Comparison of two Parallelization Strategies for TRACE

In this report we compare two different methods of parallelization of a finite element code describing water flow in soils. The first method uses Domain Decomposition based on a parallel Schwarz algorithm. The second method uses a Data Partitioning approach pursued in High Performance Fortran (HPF). Experiments with the parallel versions were performed on the Paragon XP/S 10 at KFA

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

3-D characterization of high-permeability zones in a gravel aquifer using 2-D crosshole GPR full-waveform inversion and waveguide detection

Reliable high-resolution 3-D characterization of aquifers helps to improve our understanding of flow and transport processes when small-scale structures have a strong influence. Crosshole ground penetrating radar (GPR) is a powerful tool for characterizing aquifers due to the method's high-resolution and sensitivity to porosity and soil water content. Recently, a novel GPR full-waveform inversion algorithm was introduced, which is here applied and used for 3-D characterization by inverting six crosshole GPR cross-sections collected between four wells arranged in a square configuration close to the Thur River in Switzerland. The inversion results in the saturated part of this gravel aquifer reveals a significant improvement in resolution for the dielectric permittivity and electrical conductivity images compared to ray-based methods. Consistent structures where acquisition planes intersect indicate the robustness of the inversion process. A decimetre-scale layer with high dielectric permittivity was revealed at a depth of 5-6 m in all six cross-sections analysed here, and a less prominent zone with high dielectric permittivity was found at a depth of 7.5-9 m. These high-permittivity layers act as low-velocity waveguides and they are interpreted as high-porosity layers and possible zones of preferential flow. Porosity estimates from the permittivity models agree well with estimates from Neutron-Neutron logging data at the intersecting diagonal planes. Moreover, estimates of hydraulic permeability based on flowmeter logs confirm the presence of zones of preferential flow in these depth intervals. A detailed analysis of the measured data for transmitters located within the waveguides, revealed increased trace energy due to late-arrival elongated wave trains, which were observed for receiver positions straddling this zone. For the same receiver positions within the waveguide, a distinct minimum in the trace energy was visible when the transmitter was located outside the waveguide. A novel amplitude analysis was proposed to explore these maxima and minima of the trace energy. Laterally continuous low-velocity waveguides and their boundaries were identified in the measured data alone. In contrast to the full-waveform inversion, this method follows a simple workflow and needs no detailed and time consuming processing or inversion of the data. Comparison with the full-waveform inversion results confirmed the presence of the waveguides illustrating that full-waveform inversion return reliable results at the highest resolution currently possible at these scales. We envision that full-waveform inversion of GPR data will play an important role in a wide range of geological, hydrological, glacial and periglacial studies in the critical zon

Solute transport in aquifers with evolving scale heterogeneity

Transport processes in groundwater systems with spatially heterogeneous properties often exhibit anomalous behavior. Using first-order approximations in velocity fluctuations we show that anomalous superdiffusive behavior may result if velocity fields are modeled as superpositions of random space functions with correlation structures consisting of linear combinations of short-range correlations. In particular, this corresponds to the superposition of independent random velocity fields with increasing integral scales proposed as model for evolving scale heterogeneity of natural porous media [Gelhar, L. W. Water Resour. Res. 22 (1986), 135S-145S]. Monte Carlo simulations of transport in such multi-scale fields support the theoretical results and demonstrate the approach to superdiffusive behavior as the number of superposed scales increases.publishedVersio

Validation of spaceborne and modelled surface soil moisture products with cosmic-ray neutron probes

The scale difference between point in situ soil moisture measurements and low resolution satellite products limits the quality of any validation efforts in heterogeneous regions. Cosmic Ray Neutron Probes (CRNP) could be an option to fill the scale gap between both systems, as they provide area-average soil moisture within a 150–250 m radius footprint. In this study, we evaluate differences and similarities between CRNP observations, and surface soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2), the METOP-A/B Advanced Scatterometer (ASCAT), the Soil Moisture Active and Passive (SMAP), the Soil Moisture and Ocean Salinity (SMOS), as well as simulations from the Global Land Data Assimilation System Version 2 (GLDAS2). Six CRNPs located on five continents have been selected as test sites: the Rur catchment in Germany, the COSMOS sites in Arizona and California (USA), and Kenya, one CosmOz site in New South Wales (Australia), and a site in Karnataka (India). Standard validation scores as well as the Triple Collocation (TC) method identified SMAP to provide a high accuracy soil moisture product with low noise or uncertainties as compared to CRNPs. The potential of CRNPs for satellite soil moisture validation has been proven; however, biomass correction methods should be implemented to improve its application in regions with large vegetation dynamics

Seasonal soil moisture and crop yield prediction with fifth-generation seasonal forecasting system (SEAS5) long-range meteorological forecasts in a land surface modelling approach

Long-range weather forecasts provide predictions of atmospheric, ocean and land surface conditions that can potentially be used in land surface and hydrological models to predict the water and energy status of the land surface or in crop growth models to predict yield for water resources or agricultural planning. However, the coarse spatial and temporal resolutions of available forecast products have hindered their widespread use in such modelling applications, which usually require high-resolution input data. In this study, we applied sub-seasonal (up to 4 months) and seasonal (7 months) weather forecasts from the latest European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal forecasting system (SEAS5) in a land surface modelling approach using the Community Land Model version 5.0 (CLM5). Simulations were conducted for 2017–2020 forced with sub-seasonal and seasonal weather forecasts over two different domains with contrasting climate and cropping conditions: the German state of North Rhine-Westphalia (DE-NRW) and the Australian state of Victoria (AUS-VIC). We found that, after pre-processing of the forecast products (i.e. temporal downscaling of precipitation and incoming short-wave radiation), the simulations forced with seasonal and sub-seasonal forecasts were able to provide a model output that was very close to the reference simulation results forced by reanalysis data (the mean annual crop yield showed maximum differences of 0.28 and 0.36 t ha−1 for AUS-VIC and DE-NRW respectively). Differences between seasonal and sub-seasonal experiments were insignificant. The forecast experiments were able to satisfactorily capture recorded inter-annual variations of crop yield. In addition, they also reproduced the generally higher inter-annual differences in crop yield across the AUS-VIC domain (approximately 50 % inter-annual differences in recorded yields and up to 17 % inter-annual differences in simulated yields) compared to the DE-NRW domain (approximately 15 % inter-annual differences in recorded yields and up to 5 % in simulated yields). The high- and low-yield seasons (2020 and 2018) among the 4 simulated years were clearly reproduced in the forecast simulation results. Furthermore, sub-seasonal and seasonal simulations reflected the early harvest in the drought year of 2018 in the DE-NRW domain. However, simulated inter-annual yield variability was lower in all simulations compared to the official statistics. While general soil moisture trends, such as the European drought in 2018, were captured by the seasonal experiments, we found systematic overestimations and underestimations in both the forecast and reference simulations compared to the Soil Moisture Active Passive Level-3 soil moisture product (SMAP L3) and the Soil Moisture Climate Change Initiative Combined dataset from the European Space Agency (ESA CCI). These observed biases of soil moisture and the low inter-annual differences in simulated crop yield indicate the need to improve the representation of these variables in CLM5 to increase the model sensitivity to drought stress and other crop stressors.</p

Intercomparison of Flow and Transport Models Applied to Vertical Drainage in Cropped Lysimeters

International audienceThe vertical water flow, heat flow and transport of the herbicide methabenzthiazuron were monitored for 627 days in lysimeters sampled at a field site close to the research centre Jülich, Germany. During this period the lysimeters were cropped with winter wheat, winter barley and oat. The models TRACE, MARTHE, ANSWERS and MACRO were applied to the lysimeter data with the scope of upscaling local scale process understanding for regional scale. MARTHE and TRACE solve the 3-d Richards' equation for variably saturated water flow. MACRO is a 1-d model based on the Richards' Equation and accounting for preferential flow in the unsaturated zone, while ANSWERS is a regional scale capacity based watershed model. Measurements of soil moisture, evapotranspiration, drainage, soil temperature, pesticide residues and leaching are used for comparison with model results. Although the adopted models differ in terms of model concepts, the use of model performance indices proved a proper simulation of water flow for all models. The heat flow is also well described with ANSWERS, MARTHE and MACRO. Larger deviations were found between model results and measured pesticide transport. An inadequate reproduction of the measured MBT degradation was found for the available model input parameters. A very small amount of MBT leaching, observed in the measurements, was only reproduced with MACRO after strong calibration. In other respects only plant parameters were calibrated. Calibration of the crop conversion factor used for scaling of the potential evapotranspiration was found to be a crucial parameter for the adequate description of the water balance by the models

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

Relationship between vegetation microwave optical depth and cross-polarized backscatter from multiyear Aquarius observations

Soil moisture retrieval algorithms based on passive microwave remote sensing observations need to account for vegetation attenuation and emission, which is generally parameterized as vegetation optical depth (VOD). This multisensor study tests a new method to retrieve VOD from cross-polarized radar backscattering coefficients. Three years of Aquarius/SAC-D data were used to establish a relationship between the cross-polarized backscattering coefficient σHV and VOD derived from a multitemporal passive dual-channel algorithm (VODMT). The dependence of the correspondence is analyzed for different land use classes. There are no systematic differences in the slope for woody versus nonwoody vegetation, resulting in a strong correlation (80% explained-variance) and a global linear relationship when all classes are combined. The relationship is stable over the years of observations. The comparison of the Aquarius-derived VODMT to Soil Moisture and Ocean Salinity's multi-angular VOD estimates shows similar spatial patterns and temporal behavior, evident in high correlations. However, VODMT has considerably higher mean values, but lower dynamic range globally. Most of the differences can be attributed to differences in instrument sampling. The main result of this study, a relationship between backscatter and VOD, will permit high-resolution mapping of VOD with synthetic aperture radar measurements. These maps allow future studies of scaling and heterogeneity effects of vegetation on soil moisture retrieval at the coarser scales of land microwave radiometry. The study shows that VOD based on passive measurements and predicted by active measurements are comparable globally and that the breakdown by land cover classification does not affect the relationship appreciably