Initial Soil Moisture Content Research Articles

Study on the temperature field and infrared characteristics of unsaturated soils with shallow buried objects at different depths

Beneath the soil, there exist numerous concealed objects, some of which, like landmines, pose a considerable threat to human life. Infrared detection serves as a swift and secure method for detecting such hazards. However, in many current studies, the soil is often oversimplified as a single entity, overlooking the crucial internal moisture transport and phase transitions. In this paper, we propose a soil heat and moisture migration model, along with a ground infrared radiation model. Our comparisons with previous research reveal that the internal water movement, evaporation, and condensation processes in the soil have a profound influence on the soil's temperature field and infrared signature. To validate our model's reliability, we conducted three experiments with metal blocks buried 1 cm deep, having initial moisture contents of 0 %, 10 % and 20 %. A comparison of the simulation and experimental results confirms the credibility of our proposed model. Through simulations, we analyzed the daily variations in ground surface IR radiation, the effect of varying burial depths, and the influence of differing initial moisture contents. Our findings reveal that, when starting with zero initial soil moisture content, an increase in burial depth from 1 cm to 5 cm results in a substantial decrease in the peak difference between the surface center temperature and ambient temperature, dropping from 20.91 K to 5.35 K. Consequently, the optimal detection time shifts from 12:00 to 14:00 On the other hand, keeping the burial depth constant at 1 cm and increasing the initial soil moisture content from 5 % to 20 % leads to a reduction in the maximum temperature difference from 17.54 K to 12.48 K, while the optimal detection time remains unaffected. This study can provide data support for underground buried object detection and improve the accuracy of detection.

Prediction model of soil water infiltration under moistube irrigation

AbstractAs a new type of underground water‐saving irrigation method, moistube irrigation has great potential for promotion and development. However, the multi‐factor interaction influence and water infiltration prediction model of soil water infiltration under moistube irrigation need to be improved. This paper aims to obtain soil water infiltration data for different bulk densities (1.2, 1.3 and 1.4 g/cm3) and textures (loam, sandy loam and clay loam) under different pressure heads (1, 1.5 and 2 m) through an indoor moistube irrigation soil water infiltration test. By analysing multiple factors affecting soil water infiltration under moistube irrigation, the calculation method was determined with the initial soil moisture content, pressure head, bulk density and texture as the input variables and the Kostiakov model parameters as the output variables. Finally, the method of optimizing the back propagation (BP) neural network by a genetic algorithm (GA) was used to establish the Kostiakov prediction model of soil moisture in moistube irrigation, and the model was verified with analytics. The results showed that the Kostiakov prediction model based on GA‐BP had high accuracy and good consistency. The research results provide more practical proofs and perfect theoretical supplements for the study of soil water infiltration under moistube irrigation.

Prediction of Specific Fuel Consumption of a Tractor during the Tillage Process Using an Artificial Neural Network Method

In mechanized agricultural activities, fuel is particularly important for tillage operations. In this study, the impact of seven distinct parameters on fuel usage per unit of draft power was examined. The parameters are tractor power, soil texture index, plowing speed, plowing depth, width of implement, and both initial soil moisture content and soil bulk density. This study investigated the construction of an artificial neural network (ANN) model for tractor-specific fuel consumption predictions for two tillage implements: chisel and moldboard plows. The ANN model was created based on the collection of related data from previous research studies, and the validation was performed using actual field experiments in clay soil using a chisel plow. The developed ANN model (9-22-1) was confirmed by graphical assessment; additionally, the root-mean-square error (RMSE) was computed. Based on the RMSE, the results demonstrated a good agreement for specific fuel consumption per draft power between the observed and predicted values, with corresponding RMSE values of 0.08 L/kWh and 0.075 L/kWh for the training and testing datasets, respectively. The novelty of the work presented in this paper is that, for the first time, a farm machinery manager can optimize tractor fuel consumption per draft power by carefully controlling certain parameters, such as initial soil moisture content, tractor power, plowing speed, implement width, and depth of plowing. The results show that the input parameters make a significant contribution to the output over the used data with different percentages. Accordingly, the contribution analysis showed that the implement width had a high impact on tractor-specific fuel consumption for both plows at 30.13%; additionally, the chisel and moldboard plows contributed 4.19% and 4.25% in predicting tractor fuel consumption per draft power. This study concluded that practical useful advice for agricultural production can be achieved through optimizing fuel consumption rate by selecting the proper levels of affecting parameters to reduce fuel costs. Moreover, an ANN model could be used to develop future tractor fuel-planning schemes for tillage operations.

Effects of Freeze–Thaw Cycles on Soil Nitrogen Transformation in Improved Saline Soils from an Irrigated Area in Northeast China

Freeze–thaw cycles (FTCs) occur during the nongrowing season, and residual nitrogen (N) increases the risk of N loss with melting water. To study the effect of FTCs on soil N, rice fields in improved irrigated saline soil in northeast China were selected as the research subjects. Water content (10%, 20%, and 30%), different N fertilizer levels (180 and 220 kg/ha), and multiple FTCs of soil samples were used to clarify the effects of N fertilizer application and water content on N efficiency. The results indicate that, after the third FTC, the soil ammonium nitrogen (NH4+-N) level increased significantly. NH4+-N increased with an increase in the initial soil moisture content and decreased with fertilizer levels. Nitrate nitrogen (NO3−-N) decreases with increasing initial soil moisture. The inorganic N increased significantly compared with that in the unfrozen stage, indicating that FTCs promote soil N mineralization. However, high fertilization rates inhibit mineralization. Analysis of variance showed that NO3−-N is sensitive to the N application rate, water content, and salinity (p < 0.05). FTCs and artificial fertilization are the factors that affect N mineralization (p < 0.05). The research results are significant for preventing nitrate leaching and soil acidification during spring plowing and providing a scientific basis for fertilization systems and water environment pollution in improved saline soils.

Effects of slopes, rainfall intensity and grass cover on runoff loss of mercury from floodplain soil in Oak Ridge TN: A laboratory pilot study

Mercury is recognized as a global pollutant. A large amount of elemental mercury was used in the Manhattan Project in Oak Ridge, TN and Hg is still present in the water-shed surrounding the Y-12 facility and East Fork Poplar Creek. Soil erosion during rainfall-runoff events result in nonpoint source Hg transport from floodplain soils to aquatic ecosystems. This study investigated transport mechanisms of Hg through surface runoff processes from floodplain soils in Oak Ridge, TN into water with a simulated rainfall laboratory pilot scale experiment. The experiments simulated rainfall intensity (50–140 mm/h), the ground grass coverage (5 %-85 %), the soil moisture conditions and the slopes (7.5–16.32 degrees) producing soil runoff erosion processes. Results show that high grass coverage, decreased landscape slope and low rainfall resulted in the decreased Hg concentrations in sediments transported through runoff from the floodplain soil. Hg loss was strongly correlated with and controlled by soil loss. The order of environmental factors on Hg loss was the slope > rainfall intensity > grass cover. As grass cover increased from 5 % to 85 %, Hg in sediment decreased from 124 to 72.3 µg/kg and Hg in penetrating water decreased from 4.7 to 2.8 µg/kg on wet soil condition at the slope 12.560. Hg loss and soil loss significantly increased with the increase of the soil slope. As the slope increased from 7.550 to 12.560, Hg loss increased from 364 to 2905 mg/m2 in the dry soil condition with 5 % grass cover. Meanwhile Hg loss and soil loss significantly decreased with the increase of grass cover. The Hg concentration in sediment increased with increasing initial soil moisture from Dry Soil, to Wet Soil and Very Wet Soil. The roots of grasses stabilized soil Hg and the Hg content in soil rhizosphere were significantly higher than that in non-rhizosphere. This study indicates that rainfall intensity, ground grass coverages, landscape slopes and initial soil moisture content strongly controlled Hg transport from the floodplain ecosystem and its flux into stream water. Mercury associated with sediment was the major Hg input into stream waters from floodplain soils in Oak Ridge, TN. Proper onsite management, such as increasing ground coverages with local low lying grasses and decreasing landscape slopes may significantly reduce potential Hg transport into local stream water in Oak Ridge TN.

Effects of freeze-thaw on soil detachment capacity in the black soil region of Northeastern China

Soil detachment capacity (Dc) is an important parameter used to determine erosion intensity in physical-process-based erosion models. Freeze-thaw affects soil detachment processes by altering the mechanical properties of soil; however, due to the compound action of freeze-thaw and runoff on Dc, quantifying the impact of seasonal freeze-thaw on Dc remains challenging. A series of experiments with six freeze-thaw cycles (FTC), six initial soil moisture contents (SMC), three slope gradients, and five flow discharges were conducted to investigate the effect of freeze-thaw and hydrodynamic characteristics on Dc. The results showed that soil shear strength (τm), cohesion (Coh), and internal friction angle (φ) gradually tended to become stable with increasing FTC, indicating that repeated FTC had a cumulative impact on soil mechanical properties, and there was a critical FTC between 5 and 7. When FTC rose from 1 to 15, the reduction in τm, Coh, and φ was 0.03∼23.96%, 2.63∼75.21%, and − 5.70∼19.24%, respectively, which increased with an increasing SMC, suggesting that the deterioration effect of FTC on soil mechanical properties was promoted by increasing SMC. During alternating FTC, the relative range and variation coefficient of Dc were 2.21–2.43 and 67.87–75.72%, respectively, indicating that Dc was highly sensitive to FTC. Furthermore, Dc increased by 2.37–71.22% after 15 FTC. Alternating freeze-thaw weakened the soil resistance to detachment. Moreover, the promoting effect of FTC on Dc intensified with an increasing SMC, indicating that the variation in Dc was strongly affected by SMC during FTC. A prediction model (R2=0.955, RRMSE=14.99%) was established to quantify the influence of freeze-thaw and hydrodynamic characteristics on Dc. The explanation rate of variables in the Dc prediction equation was quantitated: the explanation rate of stream power (64.3%) was higher than that of FTC (10.02%) and SMC (3.92%), suggesting that the impact of freeze-thaw on Dc was covered by hydrodynamic characteristics. Further validation is required for the prediction equations when applied beyond the range of construction conditions.

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.

Evaluating The Effect of Initial Soil Moisture Content on Infiltration Characteristics Using Empirical and Hydrus 1D Models

Evaluating The Effect of Initial Soil Moisture Content on Infiltration Characteristics Using Empirical and Hydrus 1D Models

PENGARUH DURASI IRIGASI TETES TERHADAP REDUKSI LENGAS TANAH PADA LAHAN POLYBAG

Soil moisture is an important factor needed by plants for growth, and therefore the amount of soil moisture that can be stored depends on the type of soil or the composition of the soil-forming materials. Compost is one of the nutrients that is often used in the manufacture of planting media on land in the form of polybags, and the amount of compost composition on the soil is thought to greatly affect the ability to store water in the media, both the size and duration of storage. This study aims to examine the effect of using compost on storage of irrigation water in the form of soil moisture and how long it can be stored. in three-storey drip irrigation. The main data analyzed is soil moisture data (w) and the results of the analysis and discussion and conclusions are drawn descriptively. The results of the analysis show that the initial soil moisture content in the range of 19% -25%, can be given additional soil moisture by irrigation of about 12%. The average daily decrease in soil moisture that occurs in soil variation 1 (70%: 30% ) is 3% -4.4% and in soil variation 2 (50%: 50%), the average moisture reduction is around 3% -6%, soil moisture reduction in variation 2 is greater than soil variation 1 for all floors.

Land Surface Influence on Convective Available Potential Energy (CAPE) Change during Interstorms

Abstract Changes in surface water and energy balance can influence weather through interactions between the land and lower atmosphere. In convecting atmospheres, increases in convective available potential energy (CAPE) at the base of the column are driven by surface turbulent fluxes and can lead to precipitation. Using two global satellite datasets, we analyze the impact of surface energy balance partitioning on convective development by tracking CAPE over soil moisture drydowns (interstorms) during the summer, when land–atmosphere coupling is strongest. Our results show that the sign and magnitude of CAPE development during summertime drydowns depends on regional hydroclimate and initial soil moisture content. On average, CAPE increases between precipitation events over humid regions (e.g., the eastern United States) and decreases slightly over arid regions (e.g., the western United States). The soil moisture content at the start of a drydown was found to only impact CAPE evolution over arid regions, leading to greater decreases in CAPE when initial soil moisture content was high. The effect of these factors on CAPE can be explained by their influence principally on surface evaporation, demonstrating the importance of evaporative controls on CAPE and providing a basis for understanding the soil moisture–precipitation relationship, as well as land–atmosphere interaction as a whole. Significance Statement Land–atmosphere coupling is a long-standing topic with growing interest within the climate and modeling communities. Understanding and characterizing the feedbacks between the land surface and lower atmosphere has important implications for weather and climate prediction. One component of land–atmosphere coupling not yet fully understood is the soil moisture–precipitation relationship. Our work quantifies the land influence on one pathway for precipitation, convection, by tracking the evolution of atmospheric convective energy as soils dry between storms. Using global satellite observations, we find clear spatial and temporal trends that link summertime convective development to soil moisture content and evaporation. Our observational results provide a benchmark for evaluating how well weather and climate models capture the complex coupling between land and atmosphere.

Modification of Values for the Horizontal Force of Tillage Implements Estimated from the ASABE Form Using an Artificial Neural Network

The famous empirical model for the horizontal force estimation of farm implements was issued by the American Society of Agricultural Biological Engineers (ASABE). It relies on information on soil texture through its soil texture adjustment parameter, which is called the Fi -parameter. The Fi-parameter is not measurable, and the geometry of the plow through the machine parameter values are not measurable; however, the tillage speed, implement width, and tillage depth are measurable. In this study, the Fi-parameter was calibrated using a regression technique based on a soil texture norm that combines the sand, silt, and clay contents of a soil with R2 of 0.703. A feed-forward artificial neural network (ANN) with a backpropagation algorithm for training purposes was established to estimate the modified values of the horizontal force based on four inputs: working field criterion, soil texture norm, initial soil moisture content, and the horizontal force (which was estimated by the ASABE standard using the new—Fi-parameter). Our developed ANN model had high values for the coefficient of determination (R2) and their values in the training, testing, and validation stages were 0.8286, 0.8175, and 0.8515, respectively that demonstrated the applicability for the prediction of the modified horizontal forces. An Excel spreadsheet was created using the weights of the established ANN model to estimate the values of the horizontal force of specific tillage implements, such as a disk, chisel, or moldboard plows. The Excel spreadsheet was tested using data for a moldboard plow; in addition, a good prediction of the required horizontal force with a percentage error of 10% was achieved. The developed Excel spreadsheet contributed toward a numerical method that can be used by agricultural engineers in the future. Furthermore, we also concluded that the equations presented in this study can be formulated by any of computer language to create a simulation program to predict the horizontal force requirements of a tillage implement.

Soil Moisture Content from Spectral Reflectance Using Visible, Near-Infrared, and Short-Wave Infrared Light

Quantification of soil moisture content is important for understanding physical processes that occur on and within the earth. The methods that are currently used for the determination of soil moisture content are point-based (gravimetry, time-domain reflectometry, neutron scattering, or gamma ray scanning). Remote sensing methods exist but have several disadvantages (poor resolution and dependence on local meteorological conditions). The objective of the study described herein was to determine soil moisture content by means of remote sensing from hyperspectral imagery. Reflectance values obtained from optical remote sensing (wavelengths from 350 nm to 2,500 nm) were acquired from materials with different moisture content levels. Reflectance values, obtained from a spectroradiometer, were obtained for three soils and two commercial sands and then correlated with the initial soil moisture content obtained from gravimetric methods. The correlations were based on the collected reflectance values at prescribed wavelengths and a continuum analysis across all wavelengths. For all investigated materials, the reflectance values decreased with increasing moisture content. The best results were obtained when 1,900 nm was considered (coefficients of determination greater than 0.94, indices of agreement greater than 0.97, coefficients of efficiency greater than 0.41, mean absolute error less than 1.2 percent, and root mean square error less than 1.6 percent). With the continuum analysis, 1,450 nm was the best wavelength. Based on these results, a correlation was observed to exist between soil moisture content and the spectral reflectance values. Using this technique, the determination of soil moisture content can be rapidly obtained (within seconds).

Asystasia intrusa: Cover crop and water balance dynamics in oil palm plantation

Cultivation of A. intrusa as cover crops in oil palm plantation plays a role in reducing water deficit as much as 90% on condition of higher water deficit occurred. The present study aimed to examine the roles of A. intrusa as land cover crop on water balance in oil palm plantation in Bireuen Regency, Aceh Province, Indonesia during the year of 2020. The initial soil moisture content during the experiment were measured at various depths and conducted using a sensor connected to multimeter. The hydrological variables observed were included rainfall, interception of oil palm plants, water interception of A. intrusa, A. intrusa evapotranspiration, initial soil water content, soil water content during the experiment at each predetermined soil depth and percolation. This study showed that with A. intrusa as cover crop, positively affected soil water content especially during dry season and on months when rainfall are moderate. A. intrusa as cover crops in oil palm plantation played an important role in affecting water balance by reducing ground water deficit during dry season or months with lower rainfall.

Spatiotemporal variability of minimum runoff generating areas: a field investigation

ABSTRACT Past studies described several dominant factors responsible for minimum runoff-generating areas (MRGAs) which are seldom backed by field observations. Here, soil moisture and runoff data for 45 rainfall events were collected from a small (21.62 ha) agricultural watershed in Ontario, Canada, using a remotely operated wireless sensor network system. The relationship developed between MRGA and basin moisture index (M) indicated that MRGAs are insensitive up to the threshold M value of 25 cm. A higher M leads to an exponential increase in the MRGA. Various factors (e.g. rainfall amount) affecting the spatiotemporal variability of MRGA were then identified. Statistical analyses (e.g. F-test) indicated a strong seasonal influence and showed that MRGA during spring, summer, and fall seasons was 34.3%, 8.0%, and 13.6%, respectively. The relationship of MRGA with rainfall amount, initial soil moisture content and rainfall intensity was the strongest for the summer season followed by fall and then spring.

Characteristics and influencing factors of soil preferential flow in typical stands of Karst area in southwest China.

The study of preferential flow phenomena in Karst areas and the identification of the main factors influencing preferential flow are of great importance for the recovery of local vegetation. The distribution of the dyeing solution in the vertical and horizontal directions was examined by field staining tracer test and image processing technique. We analyzed the total dyeing area ratio, matrix flow depth, preferential flow ratio, and length index as pre-ferential flow characteristic parameters, and 14 factors affecting preferential flow using grey correlation analysis. The results showed that there were two main types of preferential flow, funnel-shaped and dendritic, with lateral water movement occurring in the soil of typical Karst stands. The mean value of the dyeing area ratio of the understory in Karst areas was 19.4%, and that of the matrix flow depth, preferential flow ratio, and length index was 4.96 cm, 62.9%, and 385.5%, respectively. Among the 14 environmental factors influencing preferential flow, the initial soil moisture content had the strongest influence on the dyeing area ratio, the available potassium content had the most significant influence on the matrix flow depth, and available phosphorous content had the most significant influence on both the preferential flow ratio and the length index. The high degree of development and spatial variability of preferential flow under typical forest stands in Karst areas was strongly influenced by physical properties such as initial soil water content, while soil nutrient also exerts important influence on preferential flow.

Long-term immobilization of cadmium and lead with biochar in frozen-thawed soils of farmland in China

The problem of potentially toxic elements (PTEs) in farmland is a key issue in global pollution prevention and control and has an important impact on environmental safety, human health, and sustainable agricultural development. Based on the climate background of high–latitude cold regions, this study simulated freeze–thaw cycles through indoor tests. Different initial conditions, such as biochar application rates (0%, 1%, 2%) and different initial soil moisture contents (15%, 20%, 25%), were set to explore the morphological changes in cadmium (Cd) and lead (Pb) in soil and the response relationship to the changes in soil physicochemical properties. The results indicate that soil pH decreases during freeze–thaw cycles, and soil alkalinity increases with increasing biochar content. Freeze–thaw cycles caused the total amount of PTEs to have a U–shaped distribution, and the amount of PTEs in the soluble (SOL) and reducible (RED) fraction increased by 0.28–56.19%. Biochar reduced the amount of Cd and Pb migration in the soil, and an increase in soil moisture content reduced the availability of Cd and Pb in the soil. Freezing and thawing damaged the soil structure, and biochar reduced the fractionation of small particle aggregates by enhancing the stability of soil aggregates, thereby reducing the soil's ability to adsorb Cd and Pb. In summary, for farmland soil remediation and pollution control, the application of biochar has a certain ability to optimize soil properties. Considering the distribution of PTEs in the soil and the physicochemical properties of the soil, the application of 1% biochar to soil with a 20% moisture content is optimal for regulating seasonally frozen soil remediation.

Effect of Soil Compaction due to Organic Matter and 4-Wheel Tractor Traffic on Sugarcane Growth

Background: Soil compaction can occur due to the intensity of tractor traffic in the tillage process. The objective of this study was to determine the changes in physical, mechanical properties of the soil and plant growth that occurred due to tractor traffic and how it would affect if the addition of organic matter (compost) was added to the soil. Methods: The experimental work was conducted at the Sugarcane Plantation of PTPN II Klumpang at an initial soil moisture content of 24.69% and a bulk density of 1.08 gr/cm3 with compost and no compost then the land is traversed by the tractor with 2,4 and 6 passes. Result: The results of indicate that the tractor trajectory and the addition of compost have a significant effect on soil compaction. The highest values for water content, bulk density, particle density and penetration resistance were obtained at 6 times tractor traffic with soil without compost sowing respectively 35.36%, 1.31 gr/cm3, 1.87 gr/cm3, 9.61 kgf/cm2, while in soil with compost, the values obtained were 33.62%, 1.23 gr/cm3, 1.82 gr/cm3, 9.04 kgf/cm2, respectively. These findings indicated that the application of compost can reduce the level of soil density so that plant growth becomes better and more even rate of plant growth is obtained than without compost.

Influence of Hydraulic Response Time of Tensiometer in Hydraulic Characteristics Estimation for Riverbank Sand

The knowledge of the continuous evolution of soil hydraulic characteristics is required for several environmental geotechnical applications such as capillary barrier systems and river bank slope stability analysis. Such data are obtained in the field by embedding suction sensors in slopes for stability analysis. The hydraulic equilibrium time and other limitations of sensors in establishing the hydraulic characteristics are not available for the compacted soils. Thus the influence of initial soil moisture content, initial wetting condition of the suction sensor, and soil compaction density on the hydraulic equilibrium time of the tensiometer was studied on riverbank sand. A laboratory method considering the equilibrium data at each saturation/drying state was proposed for establishing the equilibrium-SWCC data. The hydraulic equilibrium time of the tensiometer for the studied soil was found to vary from a few hours to several days depending upon the magnitude of suction and state of the sensor. The conventional method for estimating the instantaneous SWCC severely overestimated the suction values at a given water content. The sensor response time was found to be the single most influencing factor in the estimation of soil hydraulic characteristics. The in-situ tensiometer application should be replaced with the moisture sensor readings combined with the lab-based proposed equilibrium SWCC approach.

How much raindrop energy is used for transportation of the two-phase splashed material?

The ejection of a mixture of solid (soil) and liquid (water) phases is one of the aspects of the energy dissipation of the impacting drop during the soil splash phenomenon. All calculations to date have only been taking into account the ejection of solid phase material and were based on significant simplifications of the measured quantities. Therefore, the aim of the study was an improved calculation of the falling drop energy transferred to the ejected material, while considering that such material was a mixture of solid soil particles and water droplets and therefore, “two-phase”. Experimental variants included combinations of soils with different textures and initial moisture contents as well as various falling water-drop energies. Two complementary methods of i)splash cup measurements and ii) image analysis based on high-speed cameras were used for the calculation of quantities i.e. the number of ejected particles, their mass, and their ejection velocity. Based on the obtained results, it was stated that the kinetic energy of ejected particles, expressed as a percentage of falling drop energy, ranged from 1 % to 14 %. This percentage depended strongly on soil texture as well as initial moisture content. The highest values were obtained for soil with the largest amount of sand fraction and the lowest for the soil with the largest amount of finer fractions. All tested soils showed a trend of a higher drop energy transferred to the splashed particles with increasing initial soil moisture content. Taking into account the varied energy of the falling drop variants, the amount of energy transferred to ejected particles was constant.

Experimental Investigation of Relationship between Infiltration Rate and Soil Moisture under Rainfall Conditions

In this study, a mathematical expression describing the relationship between infiltration rate and soil moisture content was deduced based on the Horton equation in order to study the relationship between infiltration rate and soil moisture content during the rainfall infiltration process. Specific experimental data on infiltration processes were used to verify the validity of the equations and to analyze the main factors affecting the infiltration rate. The results indicate the following: (1) The experimental data demonstrated a high degree of accuracy. The volumetric error of soil moisture increase and cumulative infiltration was 3.5% and the coefficient of determination (R2) was 0.87 in the 42 tests. (2) The equation obtained in this paper can well describe the relationship between infiltration rate and soil moisture content; the R2 of the fitted results was greater than 0.80 in more than 80% of the experiments. (3) The relationship between infiltration rate and soil moisture content is mainly influenced by initial soil moisture content; the higher the initial soil moisture content, the lower the initial infiltration rate, the faster the infiltration rate decreases with soil moisture content, and the lower the “relative stable infiltration rate” in the process of infiltration.