Soil Erosion Modeling and Monitoring

Soil degradation and pollution is one of the main problems threatening the sustainable development of agriculture. This study used remote sensing and geographic information system (GIS) techniques to assess the risks of soil degradation and the risks of heavy metals in some soils north of the Nile Delta. The study area suffers from salinity, alkalinity, and water logging, so a spatial degradation model was used. Relying on landsat ETM+ images and the digital elevation model (DEM), it was possible to produce a geomorphological map, and it showed that the studied area consists of two landscapes, i.e., flood plain and lacustrine plain. The results indicated that salinization, alkalization, compaction, and water logging were the main types of soil degradation in the studied area. The spatial land degradation model showed that 16.61% of soils were affected by low degrees of degradation, 74.03% were affected by moderate degrees, and 9.36% were affected by high degrees of degradation. The studied area was affected by chemical degradation risks between low and high at 90.62% and 9.37%, respectively, while the physical degradation risks varied between low, moderate, high, and very high with percentages of 9.37%, 41.53%, 40.14%, and 8.93%, respectively. The environmental risks of heavy metals were assessed in the studied area using pollution indices including, the enrichment factor (EF), the pollution load index (PLI), and the potential ecological risk index (PER). Full article

The strongest fortresses often disintegrate from the inside. Likewise, soil internal forces play a critical role in the initial breakdown process of soil aggregate, thus accelerating soil erosion and the release of soil colloid particles. To date, research on the effect of soil internal forces, especially separating the electrostatic force, and on the process of soil aggregate breakdown with particle release and transport in soil is largely inadequate. Therefore, column experiments were used to investigate the properties of transport and soil particles released from the disintegration of model soil aggregates caused by different levels of electrostatic forces. We found that the increase of electrostatic repulsive pressure was the immediate cause of soil aggregate breakdown, that the highest concentration of released soil particles could reach 808.36 mg L⁻¹, and that the mean particle sizes of the released soil ranged from 100 nm to 300 nm. The particle size distributions and clay mineral composition of the released soil particles were not dominated by the electrostatic force. In practice, the change of external conditions of agricultural soil would lead to the change of soil internal forces, then affect soil aggregate stability. This study aims to provide a micro perspective to understand the release of fine particles from soil matrix and its implication for agricultural soil. Full article

We used wind-transported particle collectors of our own inhouse design to monitor the sediment flow in a citrus orchard in Southeast Spain. These collectors, which can differentiate sediment collected by direction of origin, are very efficient, economical, and easy to manufacture from thermoplastic filaments with an industrial 3D printer. Data were acquired from six vaned masts, each with four collectors at different heights, and on one of those masts, the collectors included load cells with one end attached to the collector floor and the other end to each oriented compartment in the collectors. The load cell values were interpreted in real time by a microcontroller and amplifier. The remote monitoring system was developed with an internet of things (IoT) platform. The results showed clear predominance of winds from the Northeast after dark, and from the South during the middle of the day. After analyzing the sediment transport rates and their balance, we found that those being deposited in the citrus orchard from the Northeast had a higher carbonate content (mainly calcite), which had an aggregating and therefore stabilizing effect against wind erosion of the soil. Furthermore, significant amounts of highly adhesive phyllosilicates were captured by the upper traps, which also contributed to reducing soil wind erodibility because of their adhesiveness. However, the sediments from the South with much more total transported mass were not deposited in the study zone, but leeward of it and contained a large amount of quartz, promoting abrasion and increasing wind erodibility of the soil. Full article

Sewage sludge (SS) is widely used as a soil conditioner in agricultural soil due to its high content of organic matter and nutrients. In addition, inoculants based on soil microorganisms, such as cyanobacteria, are being applied successfully in soil restoration to improve soil stability and fertility in agriculture. However, the combination of SS and cyanobacteria inoculation is an unexplored application that may be highly beneficial to soil. In this outdoor experiment, we studied the ability of cyanobacteria inoculum to grow on degraded soil amended with different concentrations of composted SS, and examined the effects of both SS concentration and cyanobacteria application on carbon gain and soil stability. We also explored the feasibility of using cyanobacteria for immobilizing salts in SS-amended soil. Our results showed that cyanobacteria growth increased in the soil amended with the lowest SS concentration tested (5 t ha⁻¹, on soil 2 cm deep), as shown by its higher chlorophyll a content and associated deeper spectral absorption peak at 680 nm. At higher SS concentrations, inoculum growth decreased, which was attributed to competition of the inoculated cyanobacteria with the native SS bacterial community. However, SS significantly enhanced soil organic carbon gain and tightly-bound exopolysaccharide content. Cyanobacteria inoculation significantly improved soil stability and reduced soil’s wind erodibility. Moreover, it led to a decrease in the lixiviate electrical conductivity of salt-contaminated soils, indicating its potential for salt immobilization and soil bioremediation. Therefore, cyanobacteria inoculation, along with adequately dosed SS surface application, is an efficient strategy for improving carbon gain and surface stability in dryland agricultural soil. Full article

Fast and precise estimation of the available nitrogen content in vermiculite substrates promotes prescription fertilization in desert facility agriculture. This study explored near-infrared spectroscopy for rapid detection of the available nitrogen content in vermiculite substrates in desert facility agriculture. The spectra of vermiculite matrices with different available nitrogen contents were collected through a self-assembled near-infrared spectrometer. Partial least squares expression (PLSR) established the available nitrogen spectrum prediction model optimized using different pretreatments. After pretreatment, the prediction model of the available nitrogen spectrum was simplified by adopting three feature extraction methods. A comprehensive comparison of the results of each prediction model showed that the prediction model combining the first derivative with SG smoothing pretreatment was the best. The correlation coefficients of the corresponding calibration and prediction sets were 0.9972 and 0.9968, respectively. The root mean square errors of the calibration and prediction sets were 149.98 and 159.65 mg/kg, respectively, with 12.57 RPD. These results provide a feasible method for rapidly detecting the available nitrogen content of vermiculite substrates in desert facility agriculture. Full article

When growing wide-row crops on sloped lands, there is significant surface runoff. In relation to the runoff process, potatoes are classified as a risk crop. This study aimed to grow potatoes in the Bohemian-Moravian Highlands, where the protection zone of the water supply reservoir of Švihov is also located. At selected experimental areas, water samples were taken after precipitation events when surface runoff and water erosion occurred. These samples were analysed (nitrates, total P, and selected pesticides used for potato growing) in an accredited laboratory. We located three different variants of nitrogen fertilisation in each experimental area. Precipitation and the amount of water from surface runoff after each higher precipitation event were also measured in the experimental areas. By knowing the acreage of each experimental area, the volume of surface runoff water and the concentration of nitrates, phosphorus, and pesticides, it was possible to calculate the balance of these substances. We also calculated the percentage of surface runoff. The results imply that a new potato cultivator in the technology of stone windrowing should be designed for weed control as part of a weed control system with reduced herbicide application requirements. Innovative agrotechnical processes reducing pollution of water sources by phosphorus and nitrates should also be enhanced. These are based on a precise application of mineral fertiliser into the root area of plants within the period of an intensive intake of nutrients. Full article

Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha⁻¹ yr⁻¹ with an average of 1.30 t ha⁻¹ yr⁻¹ and from 0.26 to 3.09 t ha⁻¹ yr⁻¹ with a mean of 1.33 t ha⁻¹ yr⁻¹, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (<6.7 t ha⁻¹ yr⁻¹), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R² = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same conditions. Full article