Comment on ‘Examining the variation of soil moisture from cosmic‑ray neutron probes footprint: experimental results from a COSMOS‑UK site’ by Howells, O.D., Petropoulos, G.P., et al., Environ Earth Sci 82, 41 (2023)

The published article by Howells et al. (2023) attempts to empirically derive the lateral footprint for a single cosmic-ray neutron sensor (CRNS), which is part of the COSMOS-UK network (Evans et al. 2016). The main result is the “true” footprint to be 50 m in radius, substantially smaller than previously published estimates. Their conclusion contradicts more than 15 peer-reviewed studies and more than a decade of research on the subject conducted by various international research groups, and thus, it would be considered as a ground-breaking finding if the methods were scientifically sound. However, the methods and arguments presented by the authors have major errors and the presented conclusions are consequently wrong

Expansion of Agriculture in Northern Cold-Climate Regions: A Cross-Sectoral Perspective on Opportunities and Challenges

Agriculture in the boreal and Arctic regions is perceived as marginal, low intensity and inadequate to satisfy the needs of local communities, but another perspective is that northern agriculture has untapped potential to increase the local supply of food and even contribute to the global food system. Policies across northern jurisdictions target the expansion and intensification of agriculture, contextualized for the diverse social settings and market foci in the north. However, the rapid pace of climate change means that traditional methods of adapting cropping systems and developing infrastructure and regulations for this region cannot keep up with climate change impacts. Moreover, the anticipated conversion of northern cold-climate natural lands to agriculture risks a loss of up to 76% of the carbon stored in vegetation and soils, leading to further environmental impacts. The sustainable development of northern agriculture requires local solutions supported by locally relevant policies. There is an obvious need for the rapid development of a transdisciplinary, cross-jurisdictional, long-term knowledge development, and dissemination program to best serve food needs and an agricultural economy in the boreal and Arctic regions while minimizing the risks to global climate, northern ecosystems and communities

Northward shift of the agricultural climate zone under 21st-century global climate change

As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21st-century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions

Geoelectrical Monitoring of Shallow Vadose Zone Moisture Dynamics over Three Annual Cycles:Electromagnetic Induction Results

Since late summer 2010, high-resolution electromagnetic induction (EMI) surveys have been performed as a part of a larger hydrogeophysical investigation to monitor changes in shallow moisture conditions at a clayey vineyard located in Vineland, Ontario, Canada. Our data set consists of 66 acquisition days during a 36-month period ending in August 2013. A wide range of soil conditions are witnessed at the site including wet spring and fall, dry summer, and frozen winter periods. Also, we were able to observe variation in hydrological processes between contrasting annual cycles (e.g., wet versus dry summer conditions). During the initial two-years of the study, EMI surveys were performed approximately bi-weekly along 25- metre lines at three monitoring sites within the vineyard. Data was collected using Geonics EM38 and EM31 ground conductivity metres in both vertical and horizontal dipole orientations. The final year of the study focused on EM38 surveys at only one of these sites, with data acquisition occurring weekly during a significantly wet summer period. Analysis of the data shows significant temporal variation in the EMI response due to seasonal moisture and provides insight towards the distribution of soil moisture in the subsurface. Geophysical observations are supported by nearby weather station data and gravimetric water content measurements. EM38 observations have been compared to predicted EM38 results calculated from data obtained by electrical resistivity tomography surveys at the site. This analysis shows reasonable agreement between observed and predicted values during conductive periods, with results displaying increasing deviation during progressively more resistive periods. Furthermore, this deviation is strongest in the horizontal dipole, suggesting that this discrepancy is caused by very shallow near surface conditions. Additional EMI studies at the site included seasonal field-scale EM38 surveys during the first year of data acquisition, two years of data acquired by EM38 vertical profiling, observing the seasonal functioning of tile drains, and investigating the response to storm events as observed by the EMI technique. The complete geophysical data set collected at this site is unique in the scientific community, and will provide the groundwork for significant future research in the field of hydrogeophysics

Comparison of Electromagnetic Induction Data with the Wireless Sensor Network at Wüstebach: An approach for non-invasively Characterisation of Soil Moisture Pattern in Conifer Forests

Knowledge about spatial and temporal soil moisture distribution is one of the key elements in land and water management and supports the prediction of climate relevant events. Although information of soil moisture conditions is of utmost importance, it is still difficult to obtain reliable information over the field-scale. A possibility of filling that information gap is the indirect mapping of soil moisture by easily recordable physical variables, e.g. from the electric conductivity measured by electromagnetic induction (EMI) due to the (dependent) relationship between moisture and electric soil conditions. EMI has been an established tool for subsurface characterization for several decades and has the capacity to non-invasively map over larger spatial areas with low operation costs. However, the recorded electrical conductivity (EC) is an integrated value and includes the effects of clay and mineral properties, porosity and water content; hence, making an allocation to one of these qualities, in this case oil moisture, can be difficult. The Wireless Sensor Network SoilNet at Wüstebach catchment (approx. 27 ha) provides a reliable near-real-time monitoring of soil moisture at three different exploration depths (Bogena et al. 2010). However the SoilNet network is spatial limited, not portable and installation, monitoring and service are time and effort costly. A combination of the advantages of EMI measurement with these reliable moisture data could improve the allocation of the ECa signal to soil moisture values. This offers the deriving of moisture information from EMI maps recorded at areas outside of the network time and cost efficient. In this study we analysed EMI data from Wüstebach of two different exploration depths obtained during different weather condition / seasons. To separate the dynamic moisture signal from the geological background signal, we subtracted the temporal ECa values from the mean values and delineated so the relative changes at each depth as proxy for moisture changes. We also used the standard deviations estimated from the temporal ECa changes and identified therewith areas of higher and lower dynamic soil moisture changes. A comparison with the corresponding SoilNet data confirms similar areas of higher and lower soil moisture fluctuation and general trends, both spatial and temporal. The study demonstrates the ability of non-invasively hydrogeophysical measurement to reveal soil moisture pattern with relatively low effort. Thus the applied approach provides an adequate alternative to time and cost consuming invasive methods. The study also shows that the practice of EMI monitoring is not limited by areas with heterogeneous topography and / or complex accessibility appropriated for application within conifer forests

In Situ Detection of Tree Root Systems under Heterogeneous Anthropogenic Soil Conditions Using Ground Penetrating Radar

Tree roots can cause damage to surface and subsurface infrastructure. Hence, timely detection of root system architecture (RSA) is needed to reduce conflict between trees and man-made facilities. Because excavation is expensive and often restricted, noninvasive detection of RSA by ground penetrating radar (GPR) is a promising technique. Although several studies have proven the ability of GPR for RSA detection, the problem of distinguishing roots from unwanted reflections at urban test sites with heterogeneous, silty, clayey, or stony soil has not yet been fully solved. This study assessed the performance of GPR for in situ detection of RSA from a plane tree (Platanus acerifolia) and a buckeye (Aesculus hippocastanum) in urban heterogeneous multilayered soil using shielded 250-MHz antennas. Repeated manual hyperbola selections were performed, extracting the three-dimensional (3D) coordinates, which were visualized in top view to reveal connected structures. Unwanted selections were manually filtered by internal confirmation using depth slices from 3D radargram interpolations. Root indications were retraced in the field and validated by vacuum excavation. At our test site, the suggested approach was suitable for detecting the lateral positions of roots with diameters between 1 and 4 cm at depths of 17 to 70 cm, despite unfavorable substrate. Moreover, the assumed depth ranges were correct for both trees, and the main depth characteristics were fairly precisely projected. The rapid and cost-effective protocol allows minimal interventions and opens the door for similar applications in urban and nonurban land uses

Soil Moisture Assessment over an Alpine Hillslope with Significant Soil Heterogeneity

We strive to assess soil water content on a well-studied slow-moving hillslope in Austria. In doing so, we employ time lapse mapping of bulk electrical conductivity using a geophysical electromagnetic induction system operated at low induction numbers. This information is complemented by the acquisition of soil samples for gravimetric water content analysis during one survey campaign. Simple visual soil sample analysis reveals that the upper material in the survey area is a spatially highly variable mixture of predominately sandy, silty, clayey and organic materials. Due to this heterogeneity, classical approaches of mapping soil moisture on the basis of stationary mapping of electrical conductivity variations are not successful. Also the time-lapse approach does not allow ruling out some of the ambiguity inherent to the linkage of bulk electrical conductivity to soil water content. However, indication is found that time-lapse measurements may have supportive capabilities to identify regions of low precipitation infiltration due to high soil saturation. Furthermore, the relationship between the mean electrical conductivity averaged over a full vegetation period and an already available ecological moisture map produced by vegetation analysis is found to resemble closely the relationship observed between gravimetric soil water content and electrical conductivity during the time of sample collection except for highly organic soils. This leads us to the assumption that the relative soil moisture distribution is temporarily stable except for those areas characterized by highly organic soil

Mapping peat layer properties with multi-coil offset electromagnetic induction and laser scanning elevation data

Peatlands store large amounts of soil organic carbon (SOC). Depending on their present condition, they act as a source or sink of carbon dioxide. Therefore, peatlands are highly relevant for climate change investigations and there is considerable interest to assess spatial heterogeneity of peat soil properties in order to assess the total amount of stored carbon. However, reliable information about peat properties remains difficult to obtain at the field scale. A potential way to acquire this information is the indirect mapping of easily recordable physical variables that correlate with peat properties, such as the apparent electrical conductivity (ECa). In this study, we aim to explore the potential of multi-coil offset electromagnetic induction (EMI) measurements to provide spatial estimates of SOC content, bulk density, and SOC stock for a highly variable and disturbed peatland relict (~ 35 ha) with a remaining peat layer thickness of less than 1 m. EMI measurements comprised six integral depths that varied from 0–0.25 to 0–1.80 m. In combination with ancillary laser-scanning elevation data, a multiple linear regression model was calibrated to reference data from 34 soil cores that were used to calculate integral properties of the upper 0.25, 0.5, and 1 m layer, as well as for the total peat layer. Leave-one-out cross-validation for the different depth ranges resulted in a root mean square error of prediction (RMSEP) between 1.36 and 5.16% for SOC content, between 0.108 and 0.183 g cm− 3 for bulk density, and between 3.56 and 9.73 kg m− 2 for SOC stocks, which corresponds to roughly 15%, 10%, and 20% of the total field variability, respectively. The selection of explanatory variables in the regression models showed that the EMI data were important for accurate model predictions, while the topography-based variables mainly acted as noise suppressors. The accuracy of the SOC content estimates roughly equalled the quality of SOC content predictions obtained in previous field applications of the visible-near infrared technique (vis-NIR). The spatial variation of the predicted peat layer properties showed similarities to the former land use distribution. Overall, it was concluded that EMI measurements offer a useful alternative to the established vis-NIR method for SOC content mapping in carbon-rich soils