Hydraulic Soil Research Articles

FLOOD RISK MAPPING IN THE IRTYSH RIVER BASIN USING SATELLITE DATA

Floods are among the most frequent and devastating natural disasters, causing significant economic damage and loss of life worldwide. Effective flood risk management relies on accurate modeling techniques that can predict vulnerable areas and assess potential impacts. In this study, flood dynamics are simulated in the Irtysh River Basin near Ust-Kamenogorsk, a city in East Kazakhstan prone to seasonal flooding using high-resolution satellite imagery and digital elevation data. The primary objective is to visually model flood risks based on terrain characteristics. The study utilizes imagery sourced from the Mapbox platform, which combines data from MODIS, Landsat 7, Maxar, and the Google Earth Engine, providing access to Sentinel-2 surface reflectance imagery at 10-meter resolution. Elevation data from the Copernicus global digital elevation model, with a 30-meter resolution, is used to simulate flood progression. The flood simulation involves calculating flood depth relative to the terrain’s elevation, allowing for a pixel-by-pixel determination of submerged areas. Each simulation incrementally increases water levels to generate a sequence of images, showcasing the progression of flooding over time. The study describes hydraulic soil characteristics usage, and focuses on visualizing flood risk based on terrain data and water level changes. The simulation results indicate that flooding initially impacts riverbanks as water flow starts from the northwest of the city with critical infrastructure becoming vulnerable once water levels exceed 2 meters from the lowest elevation point. These findings highlight the potential of high-resolution satellite imagery and terrain data for flood risk assessment and improving urban flood preparedness. The results provide valuable insights into flood progression enabling more informed decision-making for disaster mitigation.

The Dynamics of Soil Macropores and Hydraulic Conductivity as Influenced by the Fibrous and Tap Root Systems

The Dynamics of Soil Macropores and Hydraulic Conductivity as Influenced by the Fibrous and Tap Root Systems

Effects of soil heating changes on soil hydraulic properties in Central Chile

Wildfires are natural phenomena for most ecosystems on Earth. Many soil properties are impacted by fire, including soil hydraulic properties. We used a laboratory experiment to replicate the temperatures reached by a natural wildfire and documented the effects on soil hydraulic properties. This study hypothesizes that the impact of heating on soil hydrological properties can be explained by the interaction of a number of variables especially organic matter content (OM), cation exchange capacity (CEC), texture, pH, and electrical conductivity (EC). The main objective of this study is to explore the interconnections between soil hydraulic, chemical, and physical properties, focusing on understanding how these relationships change across different ecoregions and temperatures. Sixteen soils were collected across 16 sites susceptible to forest fires in the Central Zone of Chile and heated to 100 °C and 300 °C for two hours. These sites were representative of two distinct ecoregions: the Chilean Matorral (CM) and the Valdivian Temperate Forests (VTF). Chemical, physical, and hydraulic soil properties were measured before and after heating. At 100 °C, there were no significant changes in chemical, physical, or hydraulic soil properties. At 300 °C, significant changes were observed in most soil properties in soils from both ecoregions. The OM content and CEC decreased, whereas pH and electrical conductivity increased. In addition, clay content and water aggregate stability (WSA) decreased, while all hydraulic properties increased their values. The aforementioned results demonstrate that infiltration increased after the soil was heated. This can be attributed primarily to decreases in clay content. At the same time, the water repellency (R) index decreased, allowing water to more easily wet the soil particles. Correlations revealed that CEC and clay are the main factors ruling soil hydraulic properties at all temperatures. Clay mineralogy also contributes to the soil hydraulic behavior observed. Nonlinear models were developed to estimate hydraulic properties at 100 °C and 300 °C, using the main soil properties. The models illustrated that the soils of the CM ecoregion, which are characterized by lower OM and influence of clay/CEC ratio, would be less affected by fire compared to the soils of VTF. The water holding capacity would decrease in both ecoregions. However, due to the greater changes in OM and clay in VTF, the impact would be greater than in CM.11Ca2+ = Calcium cations (meq/ 100g); CEC = Cation exchange capacity (meq/ 100g); CM = Chilean Matorral; EC = Electrical conductivity (μS/cm); I = Cumulative infiltration (cm); K = Unsaturated hydraulic conductivity (mm/h); K+ = Potassium cations (meq/ 100g); Ks = Saturated hydraulic conductivity (mm/h); Mg2+ = Magnesium cations (meq/100g); Na+ = Sodium cations (meq/100g); OM = Organic matter (g/100g); R index = Water repellency index; Se = Ethanol sorptivity (cm/s05); Sw = Water sorptivity (cm/s05); VTF = Valdivian Temperate Forest; WSA = Water-stable aggregates (%).

Tree species explain only half of explained spatial variability in plant water sensitivity.

Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.

Segmentation and deep learning to digitalize the kinematics of flow-type landslides

Flow-type landslides, including subaerial and submarine debris flows, have poor spatiotemporal predictability. Therefore, researchers rely heavily on experimental evidence in revealing complex flow mechanisms and evaluating theoretical models. To measure the velocity field of experimental flows, conventional image analysis tools for measuring soil deformation and hydraulics have been borrowed. However, these tools were not developed for capturing the kinematics of fast-moving soil–water mixtures over complex terrain under non-uniform lighting conditions. In this study, a new framework based on deep learning was used to automatically digitalize the kinematics of experimental flow-type landslides. Captured images were broken into sequences and binarized using a fully convolutional neural network (FCNN). The proposed framework was demonstrated to outperform classic image processing algorithms (e.g., particle image velocimetry, trainable Weka segmentation, and thresholding algorithms) over a wide range of experimental conditions. The FCNN model was even able to process images from consumer-grade cameras under complex shadow, light, and boundary conditions. This feature is most useful for field-scale experimentation. With fewer than 15 annotated training images, the FCNN digitalized experimental flows with an accuracy of 97% in semantic segmentation.

Https://vestnik.mrsu.ru/index.php/en/articles2-en/123-24-1/1114-10-15507-0236-2910-034-202401-5

Introduction. The article describes the process of considering the geometric parameters of water jet depending on a water jet operation mode and nozzle type. Within the framework of the study of hydraulic soil treatment in the under-tree zones, it became necessary to study the water jet parameters when using different types of nozzles. There was need to determine the geometric parameters of water flow for calculating the cross-sectional area and determining the structural features of the water jet formation. These characteristics are important for a complete description, subsequent study and calculation of water jet action during hydraulic soil treatment; they also allow studying the real shape and structure of the water jet when using different types of nozzles. Aim of the study. The study is aimed at determining the geometric parameters of the water jet for different nozzles including turbo cutters located at different heights. Materials and Methods. To solve this problem, there was developed a test bench, on four pillars, to which the adapter of the supply line of the high-pressure apparatus with replaceable nozzles is fixed. To fix the position and shape of the water jet with a certain frequency, a Basler ace acA1920 camera was used. There was also used a high-pressure apparatus with a maximum pressure of P = 140 MPa, a maximum flow rate of Q = 360 l/h. A standard nozzle with a flat jet, a standard turbo nozzle, and a turbo nozzle of the developed design were used. The geometric parameters of the water jet section were measured from the photographs obtained. Results. From the photos obtained, it can be seen that the rotating water stream entering the turbo nozzle of its own design and the standard turbo nozzle disintegrates from rapid rotation, forming a cone, the cross-sectional area of which is a circle, and affects the soil surface. A flat jet is characterized by a rectangular cross-section. Discussion and Conclusion. According to the results of the study we can draw the following conclusions, the nozzle of the proposed design allows creating water jets of the largest area, which should provide an increase in the working width and, as a consequence, an increase in productivity and quality of soil surface treatment in mainline plantations. This study will also make it possible to analyze the structure of the jet during its operation.

The prevalent life cycle of agricultural flash droughts

This work examines the characteristics and prevalent life cycle of agricultural flash droughts globally. Using ERA5 data, the study introduces a flash drought indicator based on soil water availability. This approach integrates root-zone soil moisture and hydraulic soil properties, such as field capacity and wilting point, to couple the rapid soil moisture depletion and plant water stress. Our findings reveal that agricultural flash droughts present their higher frequency predominantly during the critical growth periods of crops. Notably, these droughts exhibit a similar life cycle regardless of the location or climatic regime. The primary cause of the rapid soil moisture depletion is the precipitation deficit, but evapotranspiration also plays a significant role. In an energy-limited environment, evapotranspiration rapidly increases before the onset and decreases rapidly during the intensification period as the system becomes water-limited. Upon concluding the intensification period, most crops experience water stress, diminishing their yields.

Determinants of Field‐Saturated Soil Hydraulic Conductivity Across Sub‐Saharan Africa: Texture and Beyond

AbstractSoil infiltration is critical for water security and related ecosystem services. This infiltration, the ability of soils to absorb water at their surface, is controlled by the soil hydraulic conductivity. Despite recent efforts in assembling measurements of soil hydraulic conductivity, global databases and derived pedotransfer functions lack coverage in the tropics. Here, we present soil infiltration measurements and other indicators of soil and land health collected systematically in 3,573 plots from 83 100 km2 sites across 19 countries in sub‐Saharan Africa. We use these data to (a) determine field‐saturated hydraulic conductivity (K fs) and (b) explore which variables best predict variation in K fs. Our results show that sand content, soil organic carbon (SOC), and woody cover had a positive relationship with K fs, whereas grazing intensity and soil pH had a negative relationship. Our findings highlight that, despite soil texture being important, structure also plays a critical role. These results indicate considerable potential to improve soil hydrological functioning through management and restoration practices that target soil structure. Enhancing SOC content, limiting animal stocking, promoting trees, shrubs, and other vegetation cover, and preventing soil erosion can increase K fs and improve water security. This data set can contribute to improving Earth system and land surface models for applications in Africa.

An artificial neural network emulator of the rangeland hydrology and erosion model

Machine learning (ML) is becoming an ever more important tool in hydrologic modeling. Previous studies have shown the higher prediction accuracy of those ML models over traditional process-based ones. However, there is another advantage of ML which is its lower computational demand. This is important for the applications such as hydraulic soil erosion estimation over a large area and at a finer spatial scale. Using traditional models like Rangeland Hydrology and Erosion Model (RHEM) requires too much computation time and resources. In this study, we designed an Artificial Neural Network that is able to recreate the RHEM outputs (annual average runoff, soil loss, and sediment yield and not the daily storm event-based values) with high accuracy (Nash-Sutcliffe Efficiency ≈ 1.0) and a very low computational time (13 billion times faster on average using a GPU). We ran the RHEM for more than a million synthetic scenarios and train the Emulator with them. We also, fine-tuned the trained Emulator with the RHEM runs of the real-world scenarios (more than 32,000) so the Emulator remains comprehensive while it works specifically accurately for the real-world cases. We also showed that the sensitivity of the Emulator to the input variables is similar to the RHEM and it can effectively capture the changes in the RHEM outputs when an input variable varies. Finally, the dynamic prediction behavior of the Emulator is statistically similar to the RHEM.

Study of the effect of the compaction level on the hydrodynamic properties of loamy sand soil in an agricultural context

Agricultural soil compaction adversely affects crop water use and yield performance and should be avoided or remediated through appropriate soil management strategies. The investigation of the impact of different levels of soil compaction on its hydrodynamic properties remains a crucial step in improving water use and crop yields. We examined five compaction levels of silty sand soil sampled from a potato field in the agricultural regions of northern Quebec (Canada). Soil hydraulic characteristics (saturated and unsaturated hydraulic conductivity, soil water retention capacity) were measured using the constant head method, the HYPROP device, and a WP4C dew point potentiometer. The sixteen hydraulic models integrated into the HYPROP software were fitted to the soil water retention curve (SWRC) data for the studied compaction levels. Statistical parameters such as the mean bias error, mean absolute error, correlation coefficient, and root mean square error were used to measure the performance of the models. The results show that saturated and unsaturated conductivity decreases with increasing soil compaction. The lowest saturated hydraulic conductivity (Ks) value is observed for the highest level of soil compaction, reflecting a solid medium with less pore space and connectivity. Among the hydraulic models, the Peters-Durner-Iden (PDI) variant of van Genuchten's unconstrained bimodal model (VGm-b-PDI) outperformed all other models for SWRC simulation of different soil compaction levels and was, accordingly, selected as the optimal model. This model was implemented in HYDRUS-1D to estimate the amount of irrigation for different compaction levels. We simulated irrigation scenarios with the dual-porosity model. The results indicated that soil compaction can strongly influence soil hydraulic properties and water differently. However, the amount of irrigation for the potato crop was optimal at a moderate level of soil compaction. Overall, combined HYPROP and HYDRUS 1D can provide helpful information on the soil hydraulics properties dynamics and a rigorous simulation for irrigation planning and management in potato fields.

New Method for Modelling Seasonal Variation in Resistance and Performance of Earthing Systems

The current techniques utilized for estimating seasonal fluctuations in earthing system resistance, including artificial neural networks (ANNs) and correlation/correction factors, rely on resistance records, soil resistivity measurements, and meteorological data collected across broad areas. However, they frequently fail to consider the impact of soil conditions and properties at the actual earthing location. As a solution, this research introduces a new method that models atmospheric conditions as soil suction and incorporates hydraulic soil properties (soil water retention characteristics and hydraulic conductivity) to estimate the seasonal changes in earthing resistance and performance. To illustrate this approach, this study constructs geometric models of vertical earthing rods for three homogeneous soil textures (clayey, silty, and sandy) utilizing COMSOL Multiphysics software. By coupling the differential equations governing electric current and water flow using Archie’s formula and solving numerically with the finite element method (FEM) for various soil suctions, this research reveals that soil water retention and resistivity variations are notably influenced by soil texture. Sandy soil displays higher variability, silt soil demonstrates moderate changes, while clayey soil exhibits lower fluctuation. By linking soil resistivity changes to soil suction and hydraulic properties, this innovative method predicts seasonal trends in earthing resistance and performance.

A Novel Analytical Solution for Ponded Infiltration With Consideration of a Developing Saturated Zone

AbstractPonding at the soil surface exerts profound impacts on infiltration. However, the effects of ponding depth on infiltration, especially the development of a saturated zone below the soil surface, have yet to be considered in present infiltration models. A new general Green‐Ampt model solution (GAMS) was derived for a one‐dimensional vertical infiltration problem under a uniform initial moisture distribution with ponding on its surface. An expression was included in the new solution for simulating the saturated layer developed below the soil surface as long as the pressure head at the surface is sufficiently high to saturate the soil. The GAMS simulates the infiltration processes closer to the numerical solution by HYDRUS‐1D than the traditional and the recently improved Green‐Ampt model. Moreover, an inversion method to improve the estimates of soil hydraulic parameters from one‐dimensional vertical infiltration experiments that is based on the GAMS was suggested. The effect of ponding depth (hp), initial soil moisture content, soil texture, and hydraulic soil properties (saturated hydraulic conductivity Ks, water‐entry suction hd and shape coefficient n of soil water retention curve) in the saturated zone was also evaluated. The results indicate that the saturated zone length increased at a comparable rate with the unsaturated wetted zone length during infiltration. Generally, a larger saturated zone was found for soils with higher initial soil moisture contents, coarser texture, higher Ks values, greater n, and lower −hd. Our findings reveal that including the saturated zone in the infiltration model yields a better estimate of the soil hydraulic parameters. The proposed GAMS model can improve irrigation design and rainfall‐runoff simulations.

CLSoilMaps: A national soil gridded database of physical and hydraulic soil properties for Chile

Spatially explicit soil information is crucial for comprehending and managing many of Earth´s processes related to carbon, water, and other biogeochemical cycles. We introduced a gridded database of soil physical properties and hydraulic parameters at 100 meters spatial resolution. It covers the continental area of Chile and binational basins shared with Argentina for six standardized depths following the specifications of the GlobalSoilMap project. We generated soil maps based on digital soil mapping techniques based on more than 4000 observations, including unpublished data from remote areas. These maps were used as input for the pedotransfer function Rosetta V3 to obtain predictions of soil hydraulic properties, such as field capacity, permanent wilting point, total available water capacity, and other parameters of the water retention curve. The trained models outperformed several other DSM studies applied at the national and regional scale for soil physical properties (nRMSE ranging from 6.93% to 15.7%) and delivered acceptable predictions (nRMSE ranging from 10.4% to 15.6%) for soil hydraulic properties, making them suitable for countless environmental studies.

Towards Improved Flash Flood Forecasting over Dire Dawa, Ethiopia Using WRF-Hydro

Flash floods are increasingly frequent worldwide. Recent flooding in eastern Ethiopia resulted in casualties, destruction of property and interruptions of service. National flash flood forecasts made today primarily consider precipitation, putting less emphasis on surface processes. Enhancing accurate flash flood forecasts by accounting for surface processes and hydrological models together with a deeper understanding of heavy precipitation mechanisms is of paramount importance. To this end, an uncoupled WRF-Hydro model was calibrated for eastern Ethiopia to simulate extreme floods. Sensitivity analysis for August 2006 showed that infiltration runoff, hydraulic soil conductivity and saturated volumetric soil moisture with parameter values of 0.1, 1.5 and 1.0 produced realistic streamflow distribution. Extreme floods in March 2005 and April 2007 were further studied. The results showed that WRF-Hydro replicates temporal and spatial patterns well. Analysis using observational/reanalysis data revealed associated physical processes. Precipitation during these events exceeded long-term climatology and spanned wider areas in eastern Ethiopia. These heavy precipitation events are associated with strong upper-level westerly jet streams and rainfall-conducive circulation anomalies at lower levels. Positive outcomes from WRF-Hydro suggest operational implementation for flood monitoring and early warning systems in forecasting centers.

Soil Macropore and Hydraulic Conductivity Dynamics of Different Land Uses in the Dry–Hot Valley Region of China

Soil macropores and hydraulic conductivity are important indexes used to describe soil hydrology. In the dry-hot valley region of Southwest China, with its dramatic seasonal dry–wet rhythm, soil properties and hydraulic conductivity can reflect unique dynamics as determined by the interaction between land use and the seasonal dry–wet cycle. In this study, the soil macropore characteristics and hydraulic conductivity of five land uses (traditional corn, plum orchard, pine forest, grassland, and abandoned cropland) in a dry–hot valley region were quantified using X-ray computed tomography (CT) and a mini disk infiltrometer in the rainy season (July) and dry season (November), respectively. The results showed that the soil macropore indexes (soil macroporosity, mean diameter of macropores, connectivity, hydraulic radius and compactness) in the rainy season were, on average, 1.26 times higher than those in the dry season. Correspondingly, the hydraulic conductivity of different land uses in the rainy season was significantly higher than those in the dry season (2.10 times higher, on average). Correlation analysis and principal component analysis (PCA) indicated that the hydraulic conductivity was mainly determined by soil macropore parameters rather than by general soil properties, such as organic matter (OM) and bulk density (BD). The hydraulic conductivity for the five land uses followed the order of PF > GL > TC > PO > AC in both the rainy and the dry seasons. This ranking order reflects the protective effect of vegetation in reducing raindrop splash and soil crust formation processes. The above results can help guide soil water conservation and vegetation restoration in the dry-hot valley region of Southwest China.

Extension of the Gardner exponential equation to represent the hydraulic conductivity curve: Inclusion of macropore flow effects

In soil hydraulics, it is crucial to establish an accurate representation of the relative hydraulic conductive curve (rHCC), K_r(h). This paper proposes a simple way to determine K_r(h), called the Modified Gardner Dual model (MGD), using a logarithmic extension of the classical Gardner exponential representation and including macropore flow effects. MGD has five parameters which are hydraulic constants clearly identified in the bilogarithmic representation of K_r(h). Two of them are related to the main inflection point coordinates of rHCC; from them, it is possible to determine the macroscopic capillary length of the infiltration theory. The model was tested in the suction interval 0 < h < 15,000 cm with a total of 249 soil samples from two databases, and employing a flexible representation of the Mualem-van Genuchten (MVG) equation as a reference. Using the RMSE statistics (with log base) to measure the fitting errors, we obtained a 31% reduction in errors (RMSE_MGD = 0.27, RMSE_MVG = 0.39). In 74% of the soils, including samples from the two databases, the reduction was 53% (RMSE_MGD = 0.19, RMSE_MVG = 0.40); the rHCC data fitting of this group was accurate over all the suction h intervals, with RMSE_MGD < 0.32 in each soil sample. In the remaining 26% of the samples, the quality of the MGD fitting degraded due mainly to the presence of multiple rHCC data inflection points. Therefore, in soils without this structural peculiarity, the proposed model revealed to be quite accurate in addition to being analytically simple. Another advantage of MGD is that its parameters depend mainly on the data with h around and lower than the main inflection suction value, which, in turn, never exceeded the 300-cm limit in this study. Hence, in soils that do not have multiple inflections, the extrapolations of the model in drier intervals (1000 cm < h < 15,000 cm) are reliable. The MGD parameter optimization software has been called KUNSAT. It is available in the Supplementary Material or from the corresponding author on request.

Combining root and soil hydraulics in macroscopic representations of root water uptake

AbstractPlant water uptake and plant and soil water status are important for the soil water balance and plant growth. They depend on atmospheric water demand and the accessibility of soil water to plant roots, which is in turn related to the hydraulic properties of the root system and the soil around root segments. We present a simulation model that describes water flow in the soil–plant system mechanistically considering both root and soil hydraulic properties. We developed an approach to upscale three‐dimensional (3D) flow in the soil toward root segments of a 3D root architecture to a model that considers one‐dimensional flow between horizontal soil layers and radial flow to root segments in that layer. The upscaled model couples upscaled linear flow equations in the root system with an analytical solution of the nonlinear radial flow equation between the soil and roots. The upscaled model avoids simplifying assumptions about root hydraulic properties and water potential drops near roots made in, respectively, soil‐ and root‐centered models. Xylem water potentials and soil–root interface potentials are explicitly simulated and show, respectively, large variations with depth and large deviations from bulk soil water potentials under dry soil conditions. Accounting for hydraulic gradients in the soil around root segments led to an earlier but slower reduction of transpiration during a drought period and a better plant water status with higher nighttime plant water potentials.

Soil pore structure dynamics under steady-state wetting-drying cycle

The soil pore space is an arena for processes responsible for numerous critical soil functions. We sampled 15 soil samples from 3 horizons (A, E, Bt) and performed a detailed X-ray microtomography (XCT) imaging study of the full wetting-drying (W-D) curve. This way, we revealed the dynamics of soil pore structure under slow water changes for Albic Retisols. In total, our analysis is based on 135 3D tomography scans (9 soil moisture points for each sample). Using the obtained structural information in the form of binary pore-solid segmentations, we were able not only to visualize structural dynamics (which showed significant changes within the soil at ∼10 µm – 3 mm pore sizes range) but also computed major classical morphological metrics. The analysis of these parameters and conceptual model of structural behavior revealed that after the W-D cycle the studied soil degraded in general. This is contrary to the prevailing previous findings for mainly compacted soils where W-D cycles led to structural improvements. We discussed the major implications of these findings and outlined a possibility to deepen our understanding of soil structure-function relationships, including dynamic hydraulic soil properties and 3D soil structure digital model.

THE ASSOSIATION OF CHEMICAL SOIL PROPERTIES ON EVAPOTRANSPIRATION RATE EVALUATION

We examine the evapotranspiration (ET) process and some chemical and physical properties of soil, such as soil salinity, soil hydraulic (SH), soil texture, soil electrical (SE), and soil mineral, to explain the relationship between the atmosphere and the soil degradation processes. The result reveals that, in the two stations observed, the difference between ET and precipitation value, even though they are very close, does not have a significant correlation. The remarkable complexity of the soil resulted in a higher value on the SE, CEC and SH in station A, whereas it had a low ET value, and the opposite result occurred at station B. The mineral content of the soil in station A was dominated by Kaolinite while in station B it was dominated by Montmorilonite; however, their salinity level was low. This study provided varying content of chemical elements in the two stations observable, such as Si, Al, Ca, Fe, Ti, Na, S, Mn, Co, P, Mg, K, Cr, Re, Cu, Ni, V, Yb, and Sc, even though they have an irregular pattern. The unique find that the abundance of the rear earth element elements like Eu, Yb and Sc in station A may be due to its low ET value. This information directly related the impact of the soil properties to the ET value and reveals that radiation, air temperature, humidity, wind speed, and plant characteristics were not the only parameters to be taken into account in determining the ET rate.

Parameter optimization and test of hydraulic soil insertion device of orchard gas explosion subsoiling and fertilizing machine

Parameter optimization and test of hydraulic soil insertion device of orchard gas explosion subsoiling and fertilizing machine