Kostiakov Model Research Articles

Use of rice straw nano-biochar to slow down water infiltration and reduce nitrogen leaching in a clayey soil

Biochar exhibits numerous advantages in enhancing the soil environment despite a few limitations due to its lower surface energy. Nanomodified biochar combines the advantages of biochar and nanoscale materials. However, its effects on water infiltration and N leaching in a clayey soil remain unclear. Therefore, this study prepared rice straw nano-biochar by a ball milling method, and investigated its physicochemical properties and effects of bulk biochar and nano-biochar at various addition rates (0 %, 0.5 %, 1 %, 2 %, 3 %, and 5 %) on wetting peak migration, cumulative infiltration, water absorption and retention, and N leaching. The results showed that, compared with bulk biochar, nano-biochar presented a more abundant pore structure with an increase in specific surface area of approximately 1.5 times, accompanied by a 20 % increase in acid functional groups. Compared with those for clayey soil without biochar addition, the wetting front migration time was increased by 10.2 %–123.9 % and 17.0 %–257.9 %, and the cumulative infiltration volume at 60 min was decreased by 26.0 %–48.4 % and 14.1 %–62.4 % for bulk biochar and nano-biochar, respectively. The parameter S of Philip model and the parameter a of Kostiakov model for nano-biochar were lower than those for bulk biochar, whereas the parameter b of Kostiakov model was greater, indicating that nano-biochar decreased initial soil infiltration rate and increased attenuation degree of the infiltration rate. Nano-biochar increased water absorption by 8.03 % and subsequently enhanced water retention capacity relative to bulk biochar. In addition, bulk biochar and nano-biochar reduced NH4+-N leaching by 3.0 %–13.1 % and 5.7 %–39.2 %, respectively, and NO3−-N leaching by 2.7 %–3.6 % and 9.0 %–43.3 %, respectively, by decreasing N concentration and leachate volume relative to those with no biochar addition. This study provides new knowledge for nano-biochar application in a clayey soil.

A comparison of soil water infiltration models of moistube irrigation

As a water-saving method, moistube irrigation has been widely used. To ensure the effectiveness of moistube irrigation the development of an infiltration prediction model under moistube irrigation based on the interaction of multiple factors is required. In this paper, soil water infiltration tests with different bulk densities (1.2 g/cm³, 1.3 g/cm³, and 1.4 g/cm³) and textures (loamy sand, sandy loam, and clay loam) under different pressure heads (1 m, 1.5 m, and 2 m) were designed, and the test data were analyzed by gray correlation theory. The pressure head, bulk density, clay content, silt content, sand content, and initial water content were determined as input variables, and the model structure was composed with two parameters of Kostiakov's model as output variables. Then, the genetic algorithm was used to optimize the back propagation neural network and the particle swarm algorithm to optimize the support vector machine. The soil moisture prediction model under moistube irrigation was established, finally the model was compared and analyzed. The results showed that the consistency effect of the two models was good. However, compared with the BP neural network prediction model optimized by genetic algorithm, the particle swarm algorithm optimized the support vector machine based moistube irrigation prediction model had higher accuracy. The results of this experiment can provide theoretical support for the exploration and modelling prediction of soil water infiltration under moistube irrigation.

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.

Infiltration and Leaching Characteristics of Soils with Different Salinity under Fertilizer Irrigation

Salt and nutrient transport and transformations during water infiltration directly influence saline soil improvement and the efficient use of water and fertilizer resources. The effects of soil initial salinity (18.3 g/kg, 25.5 g/kg, 42.2 g/kg, 79.94 g/kg, and 165 g/kg, respectively, labeled S1 to S5) on the infiltration and leaching characteristics of water, salt, and nitrogen were analyzed via a one-dimensional vertical fertilizer infiltration experiment. Meanwhile, the estimation models of cumulative infiltration and wetting front, including the effect of soil initial salinity, were established. The results showed that, with the increase in soil initial salinity, the cumulative infiltration within the same time decreased, and the migration time of wet front to 45 cm was longer. The time required for S5 to reach the preset cumulative infiltration was more than six times that of S1, and, for the wet front migration to 45 cm, the time requirement for S5 was about four times that of S1. In the established Kostiakov model and wetting front model, the coefficients all decreased with the increase in soil initial salinity, and the test index R2 values both reached 0.999. In the Kostiakov model, coefficient K had a linear relationship with the natural logarithm of initial soil salt content, while index a had a direct linear relationship with initial soil salt content. The cumulative leachate volume decreased with the increase in soil initial salinity, and the corresponding data of S3 and S5 were reduced by 37% and 57.3%, respectively, compared with S1. The electrical conductivity values of S1, S3, and S5 were 15.4, 209.8, and 205.6 ms/cm, respectively, being affected by the initial content in soil, soil moisture transport rate, and exogenous potassium nitrate (KNO3) addition. The NO3−-N concentrations in the leachates of S1, S3, and S5 at the end of leaching were 55.26, 16.17, and 3.2 mg/L, respectively. Based on the results of this study, for soil with high initial salinity, the conventional irrigation amount (2250 m3/ha) of the general soil in the study area could not meet the requirements of leaching salt. These results can provide a reference for the formulation of irrigation and fertilization strategies for soils with different salinity and contribute to the sustainable development of saline soil agriculture and the ecological environment.

Comparison of infiltration model performance based on basic infiltration rate for small watersheds in Papua region, Indonesia

Research on soil water infiltration in equatorial climates like Indonesia is limited. Despite Papua accounting for 29% of Indonesia’s surface water, there’s a shortage of hydrological data. This study aimed to identify the best infiltration model tailored to the characteristics of basic infiltration rates in Papua’s small watersheds. Observations were made at 95 points across 11 small watersheds in Papua. Based on equatorial basic infiltration rate theories, analysis classified infiltration values against observation time. The performance of four infiltration models — Horton, Philip, Kostiakov, and Green Ampt — were compared. The results indicated the Philip model as superior, with average scores of 0.901 (R), 0.814 (NSE), and 0.424 (RSR), followed by the Horton and Green Ampt models. These three models showed excellent performance. However, the Kostiakov model was found lacking and needs modification. Further research on rapid and very rapid classifications is vital for enhancing infiltration rate predictions in small equatorial watersheds.

Effects of varying tillage practices and weed control methods on the efficacy of infiltration models.

Agricultural land preparation and weed control techniques are essential farm management tools that affect the dynamics of soil water infiltration and the estimation accuracy of infiltration models. To analyse the interaction effect of tillage and weed control methods on the changes in soil physical properties and the efficacy of infiltration models, an experiment was conducted on a sandy clay loam forest ochrosol at Hodzo near Ho in Ghana. Four tillage systems (No Tillage [NT], Reduced Tillage [RT], Plough + Harrow + Ridging [PHR], and Deep Tillage + Plough + Harrow + Ridging [DPHR]) and three weed control methods (Hoeing [H], Machete [MAT] and No Weeding [NW]) were employed. The study also tested the reliability of the models (Kostiakov, Philip, and Horton) using the goodness of fit statistical criteria: Root mean squared error (RMSE), Mean absolute error (MAE), Coefficient of determination (R2), and Nash-Sutcliffe efficiency (NSE). The results show that conservation tillage systems (CsT) and conventional tillage systems (CT) with MAT weeding treatments recorded the highest moisture content across the studied soil profile, especially for NT x MAT (11.189%) which was significant (p < 0.05) in the 15-30 cm layer; the lowest were observed in the CsT and CT with H weeding interactions, especially for the DPHR x H (8.086%). Comparing the interaction effect on the soil infiltration, the highest mean infiltration rate was significant (p < 0.05) under the NT X H treatment combination whilst the lowest infiltration rate was recorded in the DPHR X H and PHR X NW treatment combinations. The efficiency of the fitting models (Kostiakov > Horton > Philip) highly prioritised the soil tillage operations and weed management under the treatments DPHR x MAT > DPHR x NW > DPHR x H > RT x MAT > PHR x NW > PHR x MAT > NT x NW > RT x MAT > PHR x H > RT x H > NT x MAT > RT x NW > NT x H in that order. The trend shows that the increase in tillage intensity and the decrease in weed management intensity induce the quality of the estimation process and vice versa. The study, therefore, identified the use of machete (MAT) with DPHR under the Kostiakov model as the efficient land management for modelling the cumulative infiltration characteristics of the sandy clay loam ochrosols of the study area.

Assessing Horton and Kostiakov models focused on estimating soil water infiltration

Water infiltration into the soil plays key role in proper soil and water conservation and management processes. The aim of the current study is to assess water behavior in soil infiltration processes by using the Horton and Kostiakov models. Double-ring infiltrometer method was used to determine water infiltration into the soil. In addition, soil samples were collected at depths of 0-10 cm, 10-20 cm and 20-30 cm, to determine soil moisture. Cumulative infiltration (IA) and instantaneous infiltration rates per time interval (TiR) were calculated. Equations describing the investigated phenomena were adjusted, according to the Horton and Kostiakov models. High water infiltration rate was observed at the beginning of the process, likely due to low moisture level at the top soil layer. Both models tend to underestimate the initial infiltration rate value. However, the Horton model tends to overestimate most of the instantaneous infiltration values up to 25 minutes. The Kostiakov model, on the other hand, tends to overestimate most of the instantaneous infiltration rate values after 80 minutes. Despite the large fluctuation observed in TiR values in the soil, the assessed models have satisfactorily described the infiltration behavior at the experimental site. Based on the heat map analysis, the Kostiakov model was the one capable of determining the infiltration values closest to actual one.

Analysis of a simplified approach for the determination of modified Kostiakov model parameters.

Accurate estimation of infiltration losses is very important in many hydrologic projects. However, the lack of available data often forces hydrologists to resort to the application of empirical and semi-empirical models for estimating the infiltration rates. Estimation of infiltration rate from these empirical and semi-empirical models is highly dependent on the method adopted to determine the parameters of models. One of the most common infiltration models known as the Kostiakov model was modified to rectify zero infiltration at the start of the infiltration process. Recently, a simplified approach for determining the parameters of the modified Kostiakov model was proposed. The present article focuses on analyzing the reliability of the simplified approach for determining the parameters of the modified Kostiakov model. In this regard, six observed datasets were analyzed from different parts of the world to arrive at some generalized results on the reliability of the simplified approach. Cumulative infiltration obtained from simplified approaches was compared with that obtained through the application of an excel spreadsheet-based nonlinear optimization solver. It was found that on average Sum of Square of Error reduced by 72% on application of nonlinear optimization as compared to the simplified approach.

Interactions between flue gas desulfurization gypsum and biochar on water infiltration characteristics and physicochemical properties of saline-alkaline soil

The application of flue gas desulfurization gypsum (FGDG) improves the soil structure, reduces soil pH, and accelerates soil salt leaching. Biochar amendment to soil can affect the soil infiltration rate, increase soil porosity, decrease soil bulk density, and enhance the water retention capacity. This study investigated the interactive effect of FGDG and biochar on water infiltration characteristics and physicochemical properties as well as determined the optimal amendment rate as a saline-alkaline soil conditioner. Seven experimental schemes were designed, and the newly reclaimed cultivated soil from Pingtan Comprehensive Experimental Zone in Fujian Province, China, was used in an indoor soil column experiment to simulate soil infiltration. Five models were employed to describe the infiltration process. The power function was used to represent the dynamic process of the wetting front. The conclusions of this study are as follows: (1) there was a reduction in the infiltration capacity of saline-alkaline soil (sandy soil) in each treatment, and the application of FGDG alone had the highest inhibition effect compared to the control (CK). The Kostiakov model provides the best fit for the experimental data of soil cumulative infiltration. (2) All treatments increased the total porosity and water content of saline-alkali soil, with the combined application of FGDG and biochar found to be more effective. (3) The application of FGDG alone or in combination with biochar decreased the pH and increased the electrical conductivity of the saline-alkali soil significantly, with the combined application having the most significant effect. In contrast, soil amended with biochar alone had minimal effect on the pH and EC of the soil. (4) The best improvement ratio was achieved with the F1B2 combination (75 g/kg FGDG + 30 g/kg biochar).

A Study on Infiltration Characteristics and One-Dimensional Algebraic Model Simulation in Reclaimed Soil with Biochar

The cultivated land area in China is approaching the red line of farmland protection. The newly reclaimed land will become a vital reserved land resource, and it possesses a large exploratory potential. Newly reclaimed soil usually has low productivity with poor physical and chemical properties as well as weak fertility, and it is prone to serious soil erosion. The effects of corn straw biochar and rice husk biochar (at the mass ratio of 2%, 4%, and 8%) on the soil infiltration process and soil moisture distribution in the soil profile were studied. The results showed that the infiltration duration was prolonged, and the wetting front migration distance and infiltration rate were decreased under biochar addition treatments, except under the low addition rate for rice husk biochar. The Philip model and Kostiakov model accurately described the water infiltration process of the newly reclaimed soil with both kinds of biochar. The two kinds of biochar used in this study affected both the initial infiltration rates and stable infiltration rates, and water infiltration was more sensitive to rice husk biochar and its addition rate. The moisture in the soil profile after infiltration was simulated using a one-dimensional algebraic model. The surface soil moisture was improved with both kinds of biochar addition, and the water retention ability was enhanced with an increased biochar addition rate. In conclusion, corn straw biochar with a high addition rate is beneficial for inhibiting soil water infiltration and improving weak water retention ability in the newly reclaimed area, which is a recommended choice for efficient soil construction in newly reclaimed land.

Effects of Bio-Organic Fertilizer on Soil Infiltration, Water Distribution, and Leaching Loss under Muddy Water Irrigation Conditions

This study analyzes the soil water infiltration characteristics under muddy water irrigation and bio-organic fertilizer conditions in the current context of muddy water irrigation rarely being used in agricultural production and in combination with the problems of water resource shortages and low soil fertility in arid and semi-arid regions. An indoor one-dimensional soil column infiltration device was used for studying the effects of four muddy water sediment concentration levels (ρ0: 0; ρ1: 4%; ρ2: 8%; ρ3: 12%) and four bio-organic fertilizer levels (FO0: 0; FO1: 2250 kg·hm−2; FO2: 4500 kg·hm−2; sFO3: 6750 kg·hm−2) on soil water infiltration, evaporation characteristics, and leaching loss. The results demonstrated that a higher muddy water sediment concentration and fertilization level resulted in a smaller wetting front distance and cumulative infiltration amount within the same time, but the infiltration reduction rate (η) gradually increased. The three infiltration models (Kostiakov, Philip, and Horton) were fitted, and it was discovered that all three had good fitting results (R2 &gt; 0.8), with the Kostiakov model displaying the best fit and the Horton model exhibiting the worst fit. The cumulative evaporation amount and evaporation time in muddy water irrigation and fertilization conditions was consistent with the Black and Rose evaporation models (R2 &gt; 0.9), the Black model was proved to be higher than the Rose model. In comparison to ρ0, muddy water irrigation increased conductivity and total dissolved solids (TDS) in the leaching solution, but it reduced cumulative evaporation, soil moisture content, the uniformity coefficient of soil water distribution, and leaching solution volume. Compared with FO0, the application of bio-organic fertilizer increased soil water content and reduced soil water evaporation while also reducing the leaching solution volume, conductivity, and TDS in the leaching solution. The results of this research can provide scientific reference for the efficient utilization of muddy water irrigation and the rational application of bio-organic fertilizer.

Experimental and Modeling Evaluation of Impacts of Different Tillage Practices on Fitting Parameters of Kostiakov’s Cumulative Infiltration Empirical Equation

The evaluation and modeling of the water infiltration rate into the soil are important to all aspects of water resources management and the design of irrigation systems for agricultural purposes. However, research focused on experimental studies of infiltration rates in clay soils under different tillage practices remains minimal. Therefore, an empirical prediction model for cumulative water infiltration needs to be created to estimate water depth under different tillage practices. Thus, the present research investigated the impacts of different tillage practices, including plow type (three tillage systems: moldboard, disk, and rotary plows), tillage depth (100 and 200 mm) and four soil compactions levels (0, 1, 3, and 5 tractor wheel passes), on cumulative infiltration behavior in a clay soil under a randomized complete design with three replications. Double-ring infiltration experiments were conducted to collect infiltration data. The research was conducted in three different stages. The first stage was performed through a field test to obtain infiltration data, the second stage involved using a Kostiakov empirical equation (Z = q × tb) for cumulative infiltration to acquire the fitting parameters of “q” and “b”, and in the last stage, we predicted the fitting parameters of “q” and “b” based on soil mean weight diameter, tillage depth, and four soil compaction levels by applying regression data mining approaches in Weka 3.8 software. The results show that the effects of relevant factors on the cumulative water infiltration depth of the soil could be statistically significant (p &lt; 0.05). The Kostiakov model, with an average coefficient of determination of 0.939, had a good fitting effect on the cumulative water infiltration depth process of the investigated soil. The average, lowest, and maximum values of the “q” parameter were 2.7073, 2.2724, and 3.1277 mm/minb, respectively, while for the “b” parameter, they were 0.5523, 0.5424, and 0.5647, respectively. Furthermore, the evaluation of several regression data mining approaches determined that the KStar (K*) data mining approach, with a root mean square error of 0.0228 mm/minb, a mean absolute error of 0.0179 mm/minb, and a correlation coefficient of 0.997, was the most accurate method for fitting parameter “q” using the testing dataset. The most accurate method for fitting the parameter “b” estimation was determined to be the Multilayer Perceptron method, with a root mean square error of 0.0026, a mean absolute error of 0.0013, and a correlation coefficient of 0.962, using the testing dataset. Therefore, this research, which consisted of in situ field observation experiments and infiltration modeling of the infiltration process in a clay soil, provides an essential theoretical basis for improving models of the rate of cumulative infiltration. Moreover, the proposed methodology could be employed for simulation of the fitting parameters “q” and “b” for soil water cumulative infiltration processes, not only for irrigation management purposes under regular crop production conditions, but also for the selection of the most suitable tillage practices to modify the soil during the agriculture season to conserve water and prevent yield declines. The results support the understanding of the infiltration processes in a clay soil and demonstrate that tillage practices could reduce the water infiltration rate into the soil.

Influence of Interlayer Soil on the Water Infiltration Characteristics of Heavy Saline–Alkali Soil in Southern Xinjiang

Interlayer soil is common in southern Xinjiang, because interlayer can reduce the infiltration rate of soil water. To simulate the interlayer soil in heavy saline–alkali cotton fields, this paper adopted a vertical one-dimensional infiltration test. T1 (315 mm), T2 (270 mm), and T3 (225 mm) and different interlayer positions (T5, 315 mm) and thicknesses of the interlayer (T6, 315 mm) with the same irrigation volume, as well as one perforation and sand filling treatment (T4, 315 mm), were set. The influence of different irrigation amounts, locations, and thicknesses of the interlayer and sand injection on water infiltration was analyzed. The analysis results showed that with the increase in irrigation amount, the water infiltration rate and the migration distance of the wet front increased, but did not penetrate to the bottom soil (90 cm). Under the same irrigation volume, the increase in interlayer thickness (T6) compared with the increase in interlayer position (T5), the change in soil moisture content in the upper and lower layers of the interlayer was greater, and the advance time of wetting front migration and cumulative infiltration were slightly higher. After tunneling and sand filling (T4), the infiltration rate of water was increased, the migration time of the wet front was reduced, and the profile water content of each soil layer was improved. The Kostiakov model could better simulate the water infiltration characteristics of interlayer soil with different profile configurations in heavily saline–alkali land. The results showed that in all of the treatments, only the wet front of the soil moisture reached 100 cm in the T4 treatment, and the maximum was only 87.8 cm in the other treatments, indicating that too little irrigation water or the upward movement and thickening of the interlayer were not conducive to water infiltration. For the interlayer soil area in the heavy saline–alkali land in southern Xinjiang, the appropriate irrigation water should be more than 315 mm. The treatment of drilling first and then filling sand can be used as a simple but effective measure to increase the water infiltration rate of the interlayer soil, and can thus be applied to the layered soil structure in the interlayer position of 60–80 cm.

Effects of urea solution concentration on soil hydraulic properties and water infiltration capacity

Elucidating the effect of fertigation on soil hydraulic parameters and water-solute transportation is fundamental to the design of farmland irrigation systems and their sustainable utilization. Few studies have focused on soil hydraulic parameters or water infiltration characteristics or how they are influenced by urea solution concentration. In this study, the clay loam and sandy loam in Yangling District of Shaanxi Province, China, were used as test soil, and experiments involving seven urea solution concentrations (0.2, 0.4, 0.6, 0.8, 1, 3, and 5 g/L) and a control treatment (0 g/L) were conducted to explore the influence of the various urea solution concentrations on soil hydraulic parameters and water infiltration characteristics. The results indicated that the cumulative infiltration and wetting front migration depth increased with urea solution concentration, as accurately estimated using the Kostiakov model and a power function, respectively. In addition, the coefficients of the Kostiakov model and the power function increased with urea solution concentration. Treatment with multiple concentrations of urea solution resulted in an increase in the volume of macro pores in the soil but a reduction in the volume of mesopores and micro pores in the soil, leading to increases in the saturated water content, saturated hydraulic conductivity, soil water diffusivity, and infiltration capacity and a reduction in the water-holding capacity of the soil. The effect of urea solute potential on the inhibition of soil water movement is small, and this inhibitory effect is far weaker than the improvement effect of the urea solution on soil structure, and hence enhance the soil water infiltration capacity. Our results increase the understanding of soil hydrological mechanisms and may be usefully applied for improving the management of fertigation.

Analysis of Water Infiltration Characteristics and Hydraulic Parameters of Sierozem Soil under Humic Acid Addition

The farmland in Yinchuan is composed of sierozem soil, which is characterized by high sand content and low organic matter content, resulting in poor water-holding capacity and weak soil structure. Humic acid is a natural organic polymer soil amendment. It is critical to study how humic acid affects soil water infiltration in sierozem soil at the microlevel. A one-dimensional vertical infiltration experiment was conducted to explore how adding different amounts of humic acid (0, 1%, 2%, 3% and 4%) affected the infiltration characteristics and hydraulic parameters of the sierozem soil. The results revealed that the wetting front and cumulative infiltration decreased with the increase in humic acid addition. When the infiltration time was 90 min, the wetting front of the 1%, 2%, 3% and 4% treatments was 6.50%, 10.00%, 15.00% and 21.00% lower than CK (0 for CK), and the cumulative infiltration volume was 4.50%, 11.14%, 18.42% and 23.60% lower than CK, respectively. Among the three infiltration models created by Philip, Horton and Kostiakov, the Kostiakov model (R2 &gt; 0.95) could more accurately describe the soil water infiltration process in the study area. After infiltration, the moisture content of each soil layer increased with the increase in humic acid, which improved the water-holding capacity of the sierozem soil. Using Hydrus-1D to calculate soil hydraulic parameters, we found that the humic acid addition affected the hydraulic parameters. With the increase in the amount of humic acid addition, the retention water content θr and saturated water θs were positively correlated with the humic acid addition amount and negatively correlated with the saturated water conductivity Ks and the reciprocal of air-entry α. The results showed that humic acid could increase the water-holding capacity of soil and improve the rapid water loss and poor water-holding capacity of sierozem soil.

Infiltration Model of Mediterranean Soil with Clay Texture

Infiltration plays an essential role in increasing the soil water content as a part of the hydrological cycle. Infiltration affects surface runoff and soil conservation. It also determines the sustainability of the groundwater system. Heavy rain intensity exceeding the infiltration capacity will result in surface runoff, and excessive surface runoff will cause soil erosion. This study aims to investigate the suitable infiltration rate model in the Mediterranean soil of clay textured with various soil conditions. Infiltration rate measurement employed a double-ring infiltrometer in soil without and with tillage. The applied infiltration rate model was an empirical model and the function of time, which includes the Kostiakov, Horton, and Philip Models. The results demonstrated that the Mediterranean soil infiltration rate with a clay texture was 0.91 cm/min and was relatively higher in the soil without tillage. The suitable infiltration rate model to be applied in soil conditions without and with tillage is the Kostiakov Model f = 0.700 t-0.25 and f = 0.682 t-0.22, respectively. The Kostiakov model is the most suitable infiltration rate model in Mediterranean textured clay, without tillage conditions, with a determination value of 0.988 and a deviation value of 0.005. Keywords: Horton model, Philip model, Infiltrometer; Kostiakov model, Tillage

Estimation of Infiltration Rate using a Nonlinear Regression Model

The primary abstraction of precipitation is infiltration. Accurate estimation of the infiltration rate is helpful in determining the direct runoff, groundwater recharge, water availability, and degree of saturation of soil. In this study, infiltration rate was estimated for the soils in Vishakhapatnam, Andhra Pradesh, India. The agriculture sector in the study region contributes to about 12% of the total GDP of the state. The study region faces an acute shortage of water and hence, accurate estimation of infiltration rates is vital. In this regard, the application of an Excel Solver was explored in estimating the infiltration rates. The results of the infiltration rates obtained through the Excel Solver were compared with the conventional Graphical method. In the present study, the best infiltration model was selected using the sum of square error (SSE), Maximum Absolute Error (MAE), Wilmot Index (WI), Mean Absolute Relative Error (MARE), and Nash-Sutcliffe Efficiency (NSE). Horton’s model was found to be the best-fit model for the Samantha Hostel, NCC Building, Assembly Hall, and CSE building. For the dispensary, the Kostiakov model was found to be the best-fit model of the study area. Upon application of the Excel Solver, the SSE was reduced by 70.48%, 39.55%, and 87.39% for the Kostiakov, Horton, and SCS models, respectively, as compared to the Graphical method. The WI improved by 5.68%, 36.39%, and 17.85% for the Kostiakov, Horton and SCS models, respectively, for the Excel Solver model as compared to the Graphical method. Based on this analysis, the Excel Solver was found to be a reliable tool for determining the parameters of nonlinear equations, and therefore its application should be explored in different fields of engineering.

Soil Reclamation Models by Soil Water Infiltration for Refuse Dumps in Opencast Mining Area of Northern China

The water infiltration rules of five different homogeneously or heterogeneously-constructed soil samples were determined to select the best soil construction module for refuse dump reclamation in the opencast mines of the Shanxi-Shaanxi-Inner Mongolia energy circle. Five treatments, including three homogeneous soil samples consisting of sandy soil, Montmorillonite-enriched sandstone, and sand-Montmorillonite-enriched sandstone mixture, together with two heterogeneous soil samples composed of sandy soil + Montmorillonite-enriched sandstone + sandy soil and sandy soil + sandy − Montmorillonite-enriched sandstone mixture (7:3) + sandy soil. Three replicates of each treatment were prepared in the indoor pillars to measure the infiltration process by auto-recording geometry, to investigate the infiltration features of various soil configurations by testing their infiltration rate, cumulative infiltration capacity, wetting front migration, and profile soil content, and to evaluate the infiltration of newly constructed soil in the natural conditions of the research area. The experiment demonstrated that the addition of Montmorillonite-enriched sandstone into sandy soil significantly slowed down soil water infiltration, especially in the heterogeneous soils. Traditional models perfectly simulated the soil water infiltration in the three homogeneous soils in which soil infiltration capacity could be segmentally fitted by Kostiakov model and linear model, and wetting front could be fitted by a power function. Compared with the homogeneous soil samples, heterogeneous soil could reduce the direct surface runoff and deep percolation, and is an idealized structure for soil reconstruction in opencast coal mine dump.

Performance evaluation of infiltration models under different tillage operations in a tropical climate

Land management practices have the propensity to influence soil infiltration characteristics and predictability of infiltration models. This study was conducted to evaluate the performances of the Kostiakov model, the Philip model and the Horton model in predicting cumulative infiltration depth under four tillage systems in a sandy clay loam: (i) No Tillage (NT), (ii) Reduced Tillage (RT), (iii) Ploughing followed by Harrowing and Ridging (PHR), and (iv) Deep tillage followed by Ploughing, Harrowing and Ridging (DPHR). Using the double ring infiltrometer to measure the infiltration rate, the observed data was fitted to the infiltration models and their goodness of fit was verified by Root Mean Square Error (RMSE), Mean Absolute Error (MAE), coefficient of determination (R2), Nash Sutcliffe efficiency (NSE) and paired sample t-test. The results show that the Kostiakov model exhibited the highest accuracy with the highest R2 and NSE values (R2≥0.9967 and NSE ≥ 0.9965) and lowest errors (RMSE≤ 1.16 mm and MAE ≤ 0.98 mm). The comparison of the performances of the models in predicting the cumulative infiltration depth revealed that the Kostiakov model is superior to the Philip and the Horton models under all the Tillage systems, as the Philip and the Horton models underestimated and overestimated the observed data at the initial and latter parts of the experiment, respectively. The observed and predicted cumulative infiltration depth compared using the paired sample t-test showed that the Kostiakov model was better than the Horton and the Philip models under NT, RT and PHR, while the Horton model predicted better on the DPHR than the Kostiakov and the Philip models. The infiltration capacities of the conservation tillage practices (NT and RT) were higher than the conventional tillage conditions (PHR and DPHR). However, the performance of the evaluated models in predicting cumulative infiltration shows that the measured infiltration was best simulated for the DPHR followed by the PHR, RT and NT tillage practices. From our study the Kostiakov model precisely predicted the cumulative infiltration depth relative to the Horton and Philip models. It is, therefore, the preferred choice for modelling cumulative infiltration depth in the ochrosols of the study area and under verified field conditions, these models can be applied to determine the suitable infiltration characteristics to minimise deep percolation and run off losses in irrigation scheduling.

Analysing the Infiltration Rate of Different Types of Infiltration Model: A Review

The term "infiltration" refers to the process of water moving in all directions into the soil. The maximum rate at which water is absorbed into the soil at any given time is known as the infiltration rate. The rate of infiltration is measured in centimetres per hour (cm/hr) or millimetres per hour (mm/hr). Before the building can be built, the soil must be stabilized if it has a low infiltration capacity. The lifespan of a building is reduced if water remains stagnant at ground level. As a result, determining the rate of infiltration is critical. This paper makes an attempt to look into infiltrometers and models that are best for determining infiltration rate. The Kostiakov model, Horton model, Philips model, Green-Ampt model, Regression model, M5P model, Modified Kostiakov model, and Branched Modified Kostiakov model were all used by the significant proportion of the authors. The results show that the Kostiakov and Horton models were both effective in estimating the infiltration rate. Keyword : infiltration, infiltrometers, Kostiakov model, Horton model, Philips model, Green-Ampt model, Regression model, M5P model, Modified Kostiakov model, Branched Modified Kostiakov model.