Near-surface Soil Research Articles

Phosphorus Fertilizer Effects on Near-Surface Soil Aggregation in Furrow-Irrigated Rice on a Silt-Loam Soil

Phosphorus Fertilizer Effects on Near-Surface Soil Aggregation in Furrow-Irrigated Rice on a Silt-Loam Soil

Exploring Sentinel-1 backscatter time series over the Atacama Desert (Chile) for seasonal dynamics of surface soil moisture

Recent research indicates an inverse relation between Synthetic Aperture Radar (SAR) signal and near-surface soil moisture (SM) over very dry sediments, arid to hyper-arid soils resp., caused by subsurface scattering effects. This phenomenon can lead to large errors when it comes to modelling and remote sensing-based estimation of SM. While the effect of subsurface scattering and its influence on SM estimates is well described and modelled in literature, its actual presence in recorded SAR data is largely unknown. Here we investigate the relation between C-Band SAR backscatter and SM in the hyper-arid environment of the Atacama Desert (Chile). Time series (2018–2020) of Sentinel-1 VV/VH intensities are compared to in situ SM, measured at 17 stations located across the Atacama Desert. Linear and non-linear regression modelling is applied to uncover the relationship between the SAR intensities and in situ SM, while, in addition, SM variations triggered by seasonal varying humidity (i.e., not by precipitation) are investigated. Results indicate (i) a very weak linear relationship between SM variations and SAR intensities (VV/VH) for most meteorological stations in the Atacama (R2 < 0.5). In particular, noticeable and significant exceptions are found for stations located in the northern uplands of the Coastal Cordillera and on sediments, which are characterized by thick atmospheric dust deposits on top of subsurface cemented crusts; (ii) over these sites a strong inverse linear relationship is present (R2 up to 0.84) and the observable seasonal variations in SAR intensity are linked to the seasonal variations in SM; (iii) remarkably low changes in SM (ranging from approx. 1 to 3%) lead to comparable high changes in SAR intensity (up to 5.5 dB in VH and up to 4.0 dB in VV); (iv) employing a non-linear regression modelling to the SAR time series allowed identifying the occurrence and the strength of seasonal variations over the central desert. This study contributes to a better understanding of SAR scattering over arid to hyper-arid soils, indicates a moisture-regulated complex interplay of surface and subsurface scattering, and proves the presence of subsurface scattering effects in Sentinel-1C-Band data to occur over large parts of the Atacama Desert.

Multichannel Analysis of Surface Waves (MASW) to Estimate the Shear Wave Velocity for Engineering Characterization of Soils at Hawassa Town, Southern Ethiopia

Site characterization is a prerequisite for the successful and economic design of engineering structures and earthworks by providing geological information for any proposed project. Until now, no detail study has been carried out on the site characterization and classification using shear wave velocity (Vs) up to the top 30 m depth in Hawassa town. For this study, multichannel analysis of surface waves (MASW) was used to determine the variation of Vs for a proper civil engineering design in the town. In addition, vertical electrical sounding (VES) and standard penetration test (SPT) were employed to characterize the near-surface materials. The Vs30 map was prepared for Hawassa town using the estimated Vs30 values which ranges from 248.9 m/s to 371.3 m/s while the SPT-N values were ranges from 5bpf to 50bpf. The correlation of Vs and SPT-N values has been done by considering both corrected and uncorrected SPT-N values. The VES result showed that groundwater is found at a shallow depth. The correlation of Vs and SPT-N value was validated using regression model. The 1D Vs profile and 2D cross-section showed low Vs at a shallow depth. The near-surface soils of the town are classified based on the Vs30 as site class C (stiff soil and soft rock) and D class (stiff soils) according to the NEHRP (Natural Earthquake hazards Reduction Program) and as subsoil classes B and C according to the Eurocode 8. The geotechnical tests also showed that the soils in the study area are silty sand, sand and silty sand with some gravel. The low Vs values observed at a shallow depth should be given much attention during foundation design for the stability of civil engineering structures.

Effect of data availability and pedotransfer estimates on water flow modelling in wildfire-affected soils

Understanding the impact of wildfires on soils exposed to fire is critical, especially in the current climate scenario, where an increase in the occurrence of wildfires is expected. Near-surface soil physical properties are affected by temperature increases caused by wildfires; therefore, changes in the soil water retention curve (SWRC) are expected. Parameters describing the SWRC can be obtained either by measuring or deriving using pedotransfer functions (PTF). However, PTFs have been developed using data from agricultural soils without major heating events; therefore, it is uncertain whether the estimation of parameters in fire-affected soils is reliable. This study evaluated changes in the hydraulic properties of near-surface soil due to fire during three wildfire events of different magnitudes. The objectives were: a) to identify changes in soil properties and SWRC due to wildfires, b) to assess the PTF performance (Rosetta versions 1, 2, and 3) of non-affected and fire-affected soils and (c) to evaluate changes in SWRC due to wildfires and water flow behavior changes through modelling using the HYDRUS-1D model. Decreases in organic matter (OM) and Ksat and increases in pH and bulk density (BD) were observed in fire-affected soils compared to non-affected soils. Based on sand, silt, clay, bulk density, and field capacity, Rosetta version 1 had the lowest values of root-mean-square error for the entire range of suctions, although it did not accurately estimate θs or Ksat. Among Rosetta’s estimations, Ksat showed the highest variations, which were more marked in fire-affected soils, when measured values were 15.85 cm d−1 while those estimated were 79.14 cm d−1 on average. The implications for hydrologic modelling were translated into lower annual water content and higher infiltration when using Rosetta inputs compared to inputs based on the measured SWRC.

Thermal tolerance and growth responses to in situ soil water reductions among alpine plants

ABSTRACT Background Changes to precipitation patterns and warming temperatures are predicted to reduce the water available to Australian alpine plants during the growing season. Soil water deficits are likely to co-occur with frost extremes that are common throughout the year and heatwaves which are increasing in severity with ongoing climate change. Aims We aimed to determine whether co-occurring reductions in soil moisture would affect the capacity of alpine plants to tolerate temperature extremes. Methods We used small rainout shelters to impose a drought treatment in situ in the alpine zone, which chronically reduced soil moisture in plots of alpine plant species including evergreen shrubs, graminoids and perennial forbs. We determined photosynthetic freezing tolerance and heat tolerance during the growing season across 2 years, and measured plant growth, in response to the drought treatment. Results Thermal tolerance was insensitive to chronically reduced soil moisture, and graminoids exhibited overall greater freezing and heat tolerance thresholds than other life forms. The drought treatment improved shrub growth, likely due to the amelioration of wind and the slightly warmer temperatures provided by the rainout shelters. Conclusion We conclude that Australian alpine plants maintain high tolerances to both high- and low-temperature extremes during the growing season and are relatively robust to combined temperature extremes and reductions in near-surface soil moisture that are likely to occur with ongoing climate warming.

Modeling a severe wintertime Asian dust event observed in the East Asia region: Sensitivity of the WRF-Chem dust emission schemes

This study investigates the capability of the Weather Research and Forecasting-Chemistry (WRF-Chem) model in modeling a severe wintertime Asian dust event, which originated from the East Asia dust source region during 20–22 February 2015. The WRF-Chem simulations were conducted changing with the five embedded dust emission schemes of the UC01, UC04, UC11, GO01, and GA19 schemes. The model reasonably simulated meteorological fields, capturing the characteristic meteorological features over the dust source regions during the severe wintertime Asian dust event. A good meteorological comparison led to the reasonable simulation of the occurrence and transport of the Asian dust plumes, comparing well with the surface dust occurrence reports and the satellite-detected dust signals of aerosol optical depth (AOD) and extinction coefficient. However, considerable (approximately fivefold) differences existed in the dust emission amounts simulated by the different dust emission schemes. From the model-measurement comparison of surface PM10 concentration, it was found that the UC01 and UC04 schemes could simulate the severe wintertime Asian dust plumes in the dust source regions, capturing the dust occurrence timing and the concentration level reasonably. However, the performance of the schemes significantly depended on near-surface wind speed and soil moisture amount. On the contrary, the UC11, GO01, and GA19 schemes failed to simulate the dust plumes, revealing intrinsic limitations for severe wintertime dust plume simulation. Furthermore, this study suggests the realistic representation of the Asian dust source region and the inclusion of frozen soil parameterization in the WRF-Chem model to predict severe wintertime Asian dust events realistically.

Effects of Straw Mulching on Near-Surface Hydrological Process and Soil Loss in Slope Farmland of Red Soil

Slope farmland is prone to soil erosion, especially in sub/tropical regions. However, our understanding of near-surface hydrology characteristics and their controlled factors in red soil sloping farmland remains limited. Here, we conducted simulated rainfall experiments to assess the impact of rainfall pattern, straw mulching, and soil structure on near-surface hydrological processes of red soil sloping farmland of southern China. Results showed that: (1) short duration-high intensity rain caused greater surface runoff and sediment production than did long duration-low intensity rain, whereas the variation pattern of subsurface flow exhibited the opposite trend; (2) tillage behavior could weaken the surface runoff intensity and promote the development of subsurface flow; (3) straw mulching increased the water infiltration rate and associated subsurface flow production (increased by 1.33~12.71 times), and thus reduced the surface runoff production (reduced by 99.68~100%). These findings highlight the crucial roles of rainfall pattern and straw mulching in regulating the spatial distribution pattern of rainwater and suggest that straw mulching can effectively reduce soil erosion via accelerating water infiltration and subsurface flow form in slope farmland of soil erosion in southern China.

Use of an L-band radiometer for proximal moisture measurement in road construction

The moisture content level during compaction plays a crucial role in the performance of road pavements. Current state-of-the-art methods involve manually taking small samples from a few isolated locations, making it difficult to monitor the spatial variation in moisture content along the entire construction corridor during compaction in an economically feasible manner. Therefore, finding an easy and effective method to measure soil moisture is a matter of importance. In agricultural applications, L-band passive microwave has proven to be the most accurate method for measuring soil moisture, with current satellites having a spatial resolution of approximately 40 km, which however is too coarse for road construction. Nevertheless, this technology can be deployed closer to the ground, to the point that a spatial resolution of less than 10 m is possible to achieve. Consequently, this study demonstrates the effectiveness of an L-band passive microwave radiometer for measuring soil moisture in the context of optimum compaction for road construction materials. An L-band radiometer called ELBARA-III was used to measure near-surface soil moisture in a 4.5 m × 7.5 m × 0.3 m test-bed having a sand subgrade and then an unbound granular material (UGM) sub base/base. The moisture content of the material was measured using traditional techniques such as taking thermogravimetric physical samples at targeted locations at 50 mm depth to validate the results. The results demonstrated that the L-band microwave radiometer can provide an accuracy of 5 % volumetric moisture content (VMC) or 3 % gravimetric moisture content (GMC) for sand subgrade and 2 % VMC or 1 % GMC for UGM sub base/base. An incidence angle of 0° using dual or single (horizontal or vertical) polarization was found to be the most effective configuration since it is less affected by surface roughness and is recommended for use in further field testing.

Circum-Arctic release of terrestrial carbon varies between regions and sources

Arctic change is expected to destabilize terrestrial carbon (terrOC) in soils and permafrost, leading to fluvial release, greenhouse gas emission and climate feedback. However, landscape heterogeneity and location-specific observations complicate large-scale assessments of terrOC mobilization. Here we reveal differences in terrOC release, deduced from the Circum-Arctic Sediment Carbon Database (CASCADE) using source-diagnostic (δ13C-Δ14C) and carbon accumulation data. The results show five-times larger terrOC release from the Eurasian than from the American Arctic. Most of the circum-Arctic terrOC originates from near-surface soils (61%); 30% stems from Pleistocene-age permafrost. TerrOC translocation, relative to land-based terrOC stocks, varies by a factor of five between circum-Arctic regions. Shelf seas with higher relative terrOC translocation follow the spatial pattern of recent Arctic warming, while such with lower translocation reflect long-distance lateral transport with efficient remineralization of terrOC. This study provides a receptor-based perspective for how terrOC release varies across the circum-Arctic.

A Novel Freeze-Thaw State Detection Algorithm Based on L-Band Passive Microwave Remote Sensing

Knowing the freeze-thaw (FT) state of the land surface is essential for many aspects of weather forecasting, climate, hydrology, and agriculture. Microwave L-band emission contains rather direct information about the FT-state because of its impact on the soil dielectric constant, which determines microwave emissivity and the optical depth profile. However, current L-band-based FT algorithms need reference values to distinguish between frozen and thawed soil, which are often not well known. We present a new FT-state-detection algorithm based on the daily variation of the H-polarized brightness temperature of the SMAP L3c FT global product for the northern hemisphere, which is available from 2015 to 2021. Exploiting the daily variation signal allows for a more reliable state detection, particularly during the transition periods, when the near-surface soil layer may freeze and thaw on sub-daily time scales. The new algorithm requires no reference values; its results agree with the SMAP FT state product by up to 98% in summer and up to 75% in winter. Compared to the FT state inferred indirectly from the 2-m air temperature and collocated soil temperature at 0–7 cm of the ERA5-land reanalysis, the new FT algorithm has a similar performance to the SMAP FT product. The most significant differences occur over the midlatitudes, including the Tibetan plateau and its downstream area. Here, daytime surface heating may lead to daily FT transitions, which are not considered by the SMAP FT state product but are correctly identified by the new algorithm. The new FT algorithm suggests a 15 days earlier start of the frozen-soil period than the ERA5-land’s estimate. This study is expected to extend the L-band microwave remote sensing data for improved FT detection.

GNSS-IR multisatellite combination for soil moisture retrieval based on wavelet analysis considering detection and repair of abnormal phases

Signal-to-noise ratio (SNR) data received with standard geodetic instrumentation can be used to retrieve near-surface soil moisture (SM). However, low-quality SNR data usually cause abnormal phases in the fitting of nonlinear least squares (LLS) algorithms. This is not conducive to the effective use of multisatellite phases. In this paper, an SM retrieval method based on multisatellite combinations considering the detection and repair of abnormal phases is proposed. This method is aimed at using wavelet transform to separate the trend and modulation terms in SNR data, followed by detecting and repairing the abnormal phase for all satellites, finally constructing the multisatellite linear regression (MSLR) model for SM retrieval, and analysing the variation of accuracy with the increase of model testing days. The results indicate that with the coif5 wavelet, the trend and modulation terms of the SNR (compared to the traditional low-order polynomial) can be better separated. The abnormal phases can effectively be detected and repaired by combining the interquartile range and moving average filter, and further, the quality of the phases for each satellite can be improved. Furthermore, MSLR can fully combine the multisatellite phases to improve the accuracy of SM retrieval, and it is suitable for SM retrieval over different time periods.

The Patitapu Soil Moisture Network (PTSMN) dataset and its deployment in New Zealand’s hill country

A significant portion of New Zealand’s beef and sheep pastoral farming systems are located in the East Coast hill country of the North Island. In these landscapes, one of the main drivers of pasture growth is the highly variable soil water content. Decision making about fertiliser applications, stock and feed budgeting are guided by pasture growth models which rely on soil water information. However, due to the difficulties related to conventional soil moisture data collection, soil water dynamics are still poorly understood in hill country. To capture spatial and temporal soil moisture variability on diverse terrain positions, a soil moisture monitoring network was established at the field scale. The Patitapu Soil Moisture Network (PTSMN) is composed of twenty multi-sensor probes, collecting data from four consecutive depths at 0.1 m intervals. The paper describes the PTSMN deployment and the strategic selection of sensor locations through an extensive spatial analysis and discusses the challenges associated with the network deployment in an operating hill country farm. Additionally, we demonstrate the non-normal nature of soil moisture distribution and that Year 1 and Year 2 showed similarly shaped density curves in the 0.2 − 0.4 m soil depths indicating temporal stability. Similar magnitudes of temporal stability suggested the PTMSN is a temporally stable network although stability changed with depth. Results indicated that soil moisture variability decreased with depth and that higher mean soil moisture content was associated with low variability. Descending and ascending transition stages, i.e., drying, and rewetting periods resulted in the highest spatial variability. As PTSMN is a member of the International Soil Moisture Network, the calibrated, quality checked 2-year dataset has been made accessible online. The presented soil moisture dataset is expected to contribute to the research of near-surface and root-zone soil water dynamics and to assist with the establishment of future networks.

Measurement of Physical Parameters for Transient Seepage Assessment of Levees

Abstract An embankment was instrumented and monitored as part of a multiyear project to assess appropriate pore-water pressure distributions and soil water retention curves for use as initial conditions in transient seepage analyses. The increased use of unsaturated soil mechanics and transient seepage has led to the need for practical methods of assigning accurate properties and initial conditions in these types of analyses. Monitoring results were validated against published pore-water pressure measurements collected from multiple embankment studies. The collected distributions showed nonlinear behavior in near-surface embankment soils due to infiltration and evapotranspiration processes. Seasonal variations in pore-water pressure and the soil moisture deficit were shown to correlate at the monitoring site. The seasonal response of the embankments exhibited a large variation in pressures between summer and winter. Assessment of flood occurrence showed the distribution of pore pressures during flood loading was typically near −10 kPa at a depth of 2 m at the onset of the flood. Laboratory soil water retention testing of undisturbed samples collected from the embankment showed that when compared with field measurements, they overestimated the field response for the considered initial water content and dry density values. Also, comparisons between hydrostatic pore pressures above the phreatic surface showed that at soil moisture deficits greater than 20 mm, the difference between the measured and hydrostatic pore pressures greatly increased. The laboratory and monitoring results were used to provide practical methods of assigning representative pore-water pressure distributions and material properties necessary for performing transient seepage analyses. These results will aid in more accurate transient seepage analyses of flood control embankments.

Determination of Long-Term Soil Apparent Thermal Diffusivity Using Near-Surface Soil Temperature on the Tibetan Plateau

The knowledge of soil apparent thermal diffusivity (k) is important for investigating soil surface heat transfer and temperature. Long-term k determined using the near-surface soil temperature is limited on the Tibetan Plateau (TP). The main objective of this study is to determine k with a conduction–convection method using the near-surface soil temperature measured at three sites during 2014–2016 on the TP. The hourly, daily, and monthly k values of the 0.0 m to 0.20 m layer were obtained. The hourly and daily k values ranged from 0.3 × 10−6 m2 s−1 to 1.9 × 10−6 m2 s−1 at the wet site, and from 1.0 × 10−7 m2 s−1 to 4.0 × 10−7 m2 s−1 at the two dry sites. For the monthly timescale, k ranged from 0.4 (±0.0) × 10−6 m2 s−1 to 1.1 (±0.2) × 10−6 m2 s−1 at the wet site, and varied between 1.7 (±0.0) × 10−7 m2 s−1 and 3.3 (±0.2) × 10−7 m2 s−1 at the two dry sites. The k was not constant over a day, and it varied seasonally to different degrees at different sites and years. The variation of k with soil moisture (θ) appeared to be roughly similar for unfrozen soil at these sites and years, namely, k increased sharply before reaching the peak as θ increased, and then it tended to be stable or varied slightly with further increases in θ. This variation trend was consistent with previous studies. However, the relationship between k and θ changed when soil temperature was below 0 °C, because ice had higher k than water. The correlation coefficients (r) between k and θ ranged from 0.37 to 0.80, and 0.80 to 0.92 on hourly and monthly timescales, respectively. The monthly and annual k values were significantly correlated (r: 0.73~0.93) to the Normalized Difference Vegetation Index (NDVI). The results broaden our understanding of the relationship between in situ k and θ. The presented values of k at various timescales can be used as soil parameters when modeling land–atmosphere interactions at these TP regions.

Faster velocity changes in the near-surface soil freeze state in croplands than in forests across northeast China from 1979 to 2020

Climate warming has significantly changed the near-surface soil freeze state, significantly impacting terrestrial ecosystems and regional agroforestry production. As Northeast China (NEC) is highly sensitive to climate change, this study introduces the concept of velocity to analyze the spatial pattern of frozen days (FDAY), onset date of soil freeze (FON), offset date of soil freeze (FOFF), and number of soil freeze/thaw cycles in spring (FTC) in NEC from 1979 to 2020. We observed that the velocity changes of FDAY, FON, and FTC in croplands were significantly higher than those in forests (difference >1 km yr−1), with the fastest velocity changes found in the cropland of the Songnen Plain. The highest velocity of FOFF was found in the forests of the Greater Khingan Range. In most study areas (>60%), the isoline of FDAY/FON/FOFF/FTC showed a northward movement. The isoline of FDAY/FON/FOFF/FTC moved in the cold direction in each cropland region (Sanjiang, Songnen, and Liaohe River Plains) and forest regions (Greater Khingan and Lesser Khingan Ranges, and the Changbai Mountains). The results of the quantitative analysis indicate that air temperature (TA) had a more significant effect on the velocity change of FDAY and FON in cropland, whereas snowpack is the dominant factor in forests. In both forests and croplands, the main factor affecting the velocity of FOFF was snowpack, and TA mainly affected the FTC. This study is significant for formulating regional climate change countermeasures and maintaining ecological security in cold regions.

Drone applications in hydrogeophysics: Recent examples and a vision for the future

The recent boom of commercially available drone technology capable of supporting geophysical imaging systems has led to several practitioners adopting the platforms to collect geophysical data. This has led to significant opportunities for studying hydrologic systems, as these platforms enable more efficient data collection and data collection in difficult-to-access locations. Recent examples from snow and stream studies show the viability of these platforms for studying complex systems in difficult locations and the added value of data provided by the technology. Small unoccupied aerial system (sUAS) ground-penetrating radar (GPR) surveys conducted over water bodies and snow have proven beneficial for determining bathymetry in dangerous swift water and depth of snowpack in mountainous regions. Challenges arise due to decoupling of the GPR antenna and the ground surface, which limits signal penetration. Additionally, multifrequency or multichannel GPR imaging remains a challenge due to the payload limitations of an sUAS. Drone-mounted thermal infrared data collection enables the generation of thermal orthomosaic images with unprecedented detail and spatial range for quantifying groundwater fluxes to surface water bodies and reduces issues with infrared reflection common in ground-based studies. Several drone-mounted electromagnetic studies also show utility in efficient, high-resolution mapping of near-surface soil conductivity. Overall, the use of drone platforms for studying hydrologic systems remains a frontier in science applications that needs further refinement before wide-scale adoption. The preliminary studies presented here hint that the development of robust geophysical data acquisition tools based on UAS will lead to an explosion of applications to near-surface hydrologic problems.

Environment-Monitoring IoT Devices Powered by a TEG Which Converts Thermal Flux between Air and Near-Surface Soil into Electrical Energy

Environment-Monitoring IoT Devices Powered by a TEG Which Converts Thermal Flux between Air and Near-Surface Soil into Electrical Energy

Carbon and nitrogen cycling dynamics following permafrost thaw in the Northwest Territories, Canada

Rapid climate warming across northern high latitudes is leading to permafrost thaw and ecosystem carbon release while simultaneously impacting other biogeochemical cycles including nitrogen. We used a two-year laboratory incubation study to quantify concomitant changes in carbon and nitrogen pool quantity and quality as drivers of potential CO2 production in thawed permafrost soils from eight soil cores collected across the southern Northwest Territories (NWT), Canada. These data were contextualized via in situ annual thaw depth measurements from 2015 to 2019 at 40 study sites that varied in burn history. We found with increasing time since experimental thaw the dissolved carbon and nitrogen pool quality significantly declined, indicating sustained microbial processing and selective immobilization across both pools. Piecewise structural equation modeling revealed CO2 trends were predominantly predicted by initial soil carbon content with minimal influence of dissolved phase carbon. Using these results, we provide a first-order estimate of potential near-surface permafrost soil losses of up to 80 g C m−2 over one year in southern NWT, exceeding regional historic mean primary productivity rates in some areas. Taken together, this research provides mechanistic knowledge needed to further constrain the permafrost‑carbon feedback and parameterize Earth system models, while building on empirical evidence that permafrost soils are at high risk of becoming weaker carbon sinks or even significant carbon sources under a changing climate.

Investigation of the Sensitivity of Microwave Land Surface Emissivity to Soil Texture in MLEM

This study analyzes the spectral characteristics of desert surface emissivity according to soil classification and the influence of mineral materials and soil texture information using simulation results from the microwave land emissivity model (MLEM). It also aims at exploring the feasibility of reducing the simulation error in MLEM by refining the soil classification characteristic parameters (such as soil composition content, distribution of particle size, etc.). The surface emissivity of the Taklimakan Desert is derived, to our knowledge for the first time, from FY-3B/MWRI (FengYun-3B Microwave Radiation Imager), and then the spectral characteristics of the study area for different soil types are further analyzed according to soil classification. In addition, emissivity spectra of the four most widely mineral materials in the desert area are reproduced using an MLEM under different conditions. Results showed that microwave land emissivity is highly correlated with the soil type and changes are markedly affected by the soil water content, soil texture, mineral composition, and soil particle size. For the desert soil, the emissivity of horizontal/vertical polarization is affected by the frequency in those soils dominated by large-size particles. However, for those dominated by smaller particles, the surface emissivity is almost constant or appears to be somehow dependent on the frequency. Moreover, the season effect on emissivity characteristics is clear, especially for soils composed of small-size particles. The emissivity of horizontal polarization shows stronger seasonal variation than that of vertical polarization. The study findings also showed that refining soil texture information (soil component content, distribution of particle size) improves the simulation accuracy in desert areas. For example, for the soil dominated by clay and clay loam, the simulation error is reduced from 6–9% to less than 6%. The latter is evident, especially for soil types containing a large number of small particles, such as clay and clay loam, for which the simulation error is reduced. All in all, our study contributes to a better understanding of the influencing factors of soil texture and stratification of the near-surface soil, helping to improve microwave land surface emissivity prediction by the studied here model. As MLEM consists of an important part of the global meteorological data assimilation and weather forecast system, results can also help towards increasing the use of satellite data in desert areas and in improving the accuracy of numerical weather forecast models.

Water inputs across the Namib Desert: implications for dryland edaphic microbiology

Microbes have a dominant role in nutrient cycling processes in the world’s deserts, where growth and activity are limited by the availability of water. In order to understand the dynamics of water availability in a desert system and how it may affect the soil microbiome, we analysed soil temperature and relative humidity fluctuations recorded between April 2018 and April 2020 across a precipitation gradient in the Namib Desert and compared them with recorded data from satellites and nearby weather stations. This allowed us to assess the possible impact of fog and rain events in terms of biologically-available water. Using published literature on the water activity limits for various physiological processes in microorganisms, we were able to infer the annual ‘metabolic windows’ for desert microbial communities across the longitudinal precipitation gradient. Specifically, soil surface microbial communities were estimated to have the capacity for active growth for an average of 184- 363 hours per year with the duration heavily dependent on intermittent rainfall events. During the relatively wet period of April 2018 - March 2019, the maximum growth window was found in the hyper-arid central region of the transect (approximately 100 km from the coast). During the dryer 2019- 2020 period, there was almost no predicted growth capacity in the hyper-arid region but substantial metabolic windows both near the coast and for the eastern inland areas, where water input comes in the form of fog and moist coastal air, and higher rainfall, respectively. As the first detailed study of the temperature and relative humidity characteristics of Namib Desert near-surface soils, this study provides valuable insights into the biogeography of microbial communities. In addition, the estimates for organismal functionality calculated in this study offer a baseline for future quantitation of the impacts of climate change on the functional capacity of desert soil microbiomes.