Soil Water Infiltration Research Articles

Impact of Earthworms (Metaphire sp., Amynthas zenkevichi, and Amynthas robustus) on Soil Porosity and Water Infiltration

Abstract: Epigeic Metaphire sp., anecic Amynthas zenkevichi, and endogeic Amynthas robustus are three earthworm species commonly found in Northern Vietnam and are expected to have contrasting impacts on soil structure and water infiltration. Through computed tomography and image analysis, our study confirmed contrasting burrowing behaviors among these species and their differential effects on water flow under saturated conditions. Metaphire sp. was a surface-dwelling species, exhibiting a food consumption and surface cast production of 4.57 and 11.05 times their weight, respectively. They made few burrows near the soil surface (0.02% of the soil column), resulting in negligible influence on water infiltration. A. zenkevichi was less active on the soil surface, with lower food consumption and surface cast production (2.48 and 7.52 times their weight, respectively). Their drilosphere (zone of soil directly influenced by earthworms) accounted for 3.92% of the soil column, characterized by vertical burrows (55.4º), fewer branches, distributed throughout the soil column, and high connectivity, leading to a 1.68-fold increase in water infiltration compared to the control. Meanwhile, A. robustus was only active within the first 10 cm of the soil column. Their drilosphere occupied 3.25% of the soil column, consisting of horizontal burrows (14º), disconnected by deposition within the burrows, resulting in no significant difference in water flows in comparison with the control column without earthworms. Additionally, the ratio between compaction zone around burrows and burrows made by A. zenkevichi has a larger than that of A. robustus (2.4 and 1.3, respectively), despite their similar diameter.
 
 
 

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.

The Most Likely Flooded Soil in Terengganu State During Historically Greatest Rainfall Intensity

Water infiltration in the soil is an essential topic for investigation because soil fully saturated with water forms standing water that leads to flooding on top of the soil. Soil investigation is vital for agricultural study due to the necessity to know soil carrying capacity in holding water, field capacity, and also the soil temperature for biological activities and chemical reactions. However, human urbanization and expansion into previously unexplored soil areas could lead to unnecessary environmental stress, such as floods. Floodwater forms when the rainfall intensity exceeds soil water infiltration. The flood event is crucial since it affects the human livelihood and facility damages. Therefore, a good understanding of soil hydraulic water infiltration helps better understanding the cause of flood occurrence. The current study examines the soil series in Terengganu state with its soil properties concerning the soil water characteristics curve, which indicates the soil's ability to absorb and allow water movement in the ground. The equation used was the improved Richards’ equation that can be applied to examine the standing water or floodwater impacts on water infiltration. Also, the unsaturated soil moisture movement conditions can be investigated. The simulation equation verifies with benchmark datasets that was solved on Richards’ equation using a different numerical method. The twelve-soil series of Terengganu state subjected to water infiltration study subjected to flooded conditions, by exposing the soil to the highest rainfall identified in the history of Kuala Terengganu from 1985 to early 2023. The results reveal Jambu, Rhu Tapai and Rudua soil series' water infiltration rate was greater than the rainfall intensity, whereas other soil series could not accommodate the rainfall intensity. Thus, other soil series areas will likely encounter flooded conditions when exposed to heavy rainfall, as has occurred in history.

The impacts of irrigation methods and regimes on the water and nitrogen utilization efficiency in subsoiling wheat fields

Long-term rotary tillage limit water infiltration and crop productivity in North China Plain (NCP). The practice of subsoiling to fracture plow pans has made beneficial impacts on soil surface structure and water infiltration. Further, appropriate irrigation method coupled with irrigation regime can improve crop productivity in subsoiling condition. A three-year field trial (2020–2023) was carried out to assess the effects of the irrigation regime and the method on winter wheat evapotranspiration (ET), grain yield (GY), water productivity (WP), partial factor productivity from applied nitrogen (PPFN), and economic analysis. The three irrigation regimes were irrigated when soil moisture levels decreased to 70%, 60% and 50% of the field capacity (referred as H, M and L) and two irrigation methods were the surface drip irrigation (SDI) and the micro-sprinkler irrigation (MSI). The traditional flood irrigation with 70% of the field capacity in subsoiling filed was CK. The results showed optimizing irrigation method and irrigation regime significantly influenced ET, GY, WP, PPFN, and net incomes. As the irrigation amount increased, the ET first increased while GY, WP, PPFN, and net incomes increased and then slightly decreased. Based on the three-year average, the maximum GY of 9454 kg ha−1 and the net income of 11089 yuan ha−1 was achieved in SDI-M, which had WP of 2.3 kg m−3 and PPFN of 39.4 kg kg−1. At the same time, SDI-M did not result in much increase of ET (average of 405.1 mm in three seasons). Considering comprehensively ET, GY, WP, PPFN, and net incomes, to irrigate when soil moisture decreases to 60% of the field capacity by surface drip irrigation was the optimal strategy in all aspects. These results will provide a scientific reference for irrigation management in subsoiling wheat field in NCP, as well as in similar production areas worldwide.

Coupled heat and water transfer in heterogeneous and deformable soils: Numerical model using mixed finite element method

We present a generic model framework for coupled heat and water transfer (CHWT) in deformable (non-rigid) soils with spatial variations of soil properties. The model backbone is a mixed finite element method (FEM), which solves the Philip and de Vries (1957) CHWT model and achieves conservation of mass and energy on both local and global scales. Spatial variations occur in soil hydraulic and thermal properties due to transient water content and temperature distributions. Based on the mixed FEM scheme, a gradient measure and a clustering model (“k-means”) are proposed to trace the regions with large spatial variations of soil properties, and an adaptive mesh refinement technique is developed to improve the spatial resolution and simulation accuracy. Deformation perturbates local soil topography and alters transient soil water and temperature regimes in the deformed regions. A quasi-static deformation model is presented, and the deformation effects are incorporated into the mixed FEM scheme. When external load exists, soil deformation is simulated with an updated Lagrangian formulation, and the local water content and temperature variations due to soil volume changes are also updated in the CHWT model. Numerical examples, including thermally induced soil water transfer and water infiltration, illustrate the model ability to provide plausible CHWT results, especially the refined solutions near the wetting fronts and the water content and temperature distributions when the soil is deformable. In conclusion, the proposed model framework provides an effective pipeline to incorporate and process the spatial variations of soil properties and soil deformation in CHWT simulations.

Newly established, multifunctional woody polycultures preserve agroforestry soil health benefits of a widespread U.S. land retirement program

Soil health degradation within intensively managed annual crop systems threatens the long-term economic sustainability of maize- and soybean-dominated production regions like the U.S. Corn Belt. While Conservation Reserve Program (CRP) efforts to perennialize portions of farmland to improve soil health have been largely successful, many landowners intend to return CRP land to high revenue maize and soybean cultivation. The CRP could be a pathway for a regionally tailored and profitable form of agroforestry focused on fruit and nut production potential, known as multifunctional woody polycultures (MWPs). In theory, MWPs should provide similar soil health benefits as CRP agroforestry, as soil health benefits are generally robust across agroforestry practices. We conducted a study in the heart of the U.S. Corn Belt to compare soil health responses between newly established (<10 years) CRP and MWP agroforestry systems and adjacent annual crop production fields. Because organic inputs from plant litter and roots are more consistent under untilled perennial vegetation systems compared to intensively managed annual crop systems, we hypothesized that CRP and MWP would entail similar enhancements to physical, soil organic matter (SOM), and biological soil health. Our results indicate establishing untilled, perennial CRP and MWP systems can quickly improve physical and biological soil health relative to annual crop production, based on decreased soil bulk density, greater soil water infiltration, and increased soil enzyme activity. Unexpectedly, CRP and MWP elicited divergent SOM responses. Notably, only MWP increased surface soil organic carbon stocks relative to annual crop fields, likely reflecting species-variant plant biomass growth rates. Our study demonstrates MWPs can manifest similar improvements to physical and biological soil health as CRP agroforestry on a relatively short timescale. The sensitivity of transition-state SOM responses between CRP and MWP demonstrates the importance of woody perennial selection to maximize specific soil health outcomes.

Water Infiltration in Different Soil Covers and Management in the Cerrado–Amazon Ecotone, Brazil

Soil water infiltration is an important component of the hydrological cycle, and it is best evaluated when the raindrop impacts the ground surface. For this reason, it is affected by changes in land use and land cover and by the characteristics and physical–hydric properties of the soil. This study aimed to evaluate soil water infiltration in areas occupied by annual crops (soybean and corn) and pastures in two watersheds of the Teles Pires River-MT, using simulated rainfall, physical models, and principal component analysis. Infiltration rates were evaluated based on simulated rainfall with an average intensity of 75 mm h−1, with four repetitions per region (upper, middle, and lower) of the hydrographic sub-basins of the Caiabi and Renato rivers, and soil use with cover, without cover, and disturbed. Soil tillage provided higher water infiltration rates into the soil, especially in pasture areas in the two hydrographic sub-basins. There were significant adjustments to the mathematical models based on the infiltration rate data for all land use and land cover conditions. The soil attributes that most interfered with the infiltration rate were microporosity, bulk density, and total porosity in the crop areas of the middle Caiabi and microporosity, clay content, total porosity, and silt content in the areas farming at the source of the Renato River. The Horton and Philip models presented the best adjustments in the hydrographic sub-basins of the Caiabi and Renato Rivers, which are recommended for estimating the water infiltration rate into the soil in different uses, coverages, and regions.

Influence of Conservation Agriculture on Certain Soil Qualities Both Physical and Chemical in Relation to Sustainable Agriculture Practices a Review

Conventional tillage raises the possibility of soil erosion and degrades crucial physical characteristics of the soil, such as soil organic carbon (SOC) reduction. Additionally, ineffective management techniques result in a decrease in soil organic matter, a breakdown of the soil&amp;apos;s structure, and more erosion. As a result, crop yields have decreased. Conservation agriculture (CA) is being considered as a potential system having the capability of improving soil quality and providing stable yields. This review&amp;apos;s primary goal is to demonstrate how conservation agricultural practices affect certain physical and chemical characteristics of soil in order to support sustainable agriculture. So as to produce production system that are sustainable, conservation agriculture refers to cropping system management approaches that support permanent soil cover, low soil disturbance, and appropriate crop rotation. With the use of conservation agriculture techniques, it is possible to enhance the physical and structural health of the soil (by reducing bulk density and improving soil aggregation), in addition to increase soil water infiltration, decrease water runoff and soil loss, decrease evaporation loss, decrease soil organic carbon, and lower greenhouse gas emissions from agriculture. These factors are crucial for maintaining soil health and sustainable crop production. In general, applying the conservation agriculture concepts of limited tillage, soil cover, and legume integration would promote the development of soil microorganisms and organic matter by decreasing erosion. Conservation agriculture is therefore regarded as one of the agricultural systems that have the ability to favorably contribute to soil physical and chemical improvement as well as techniques for mitigating and adapting to climate change.

A new interpretable streamflow prediction approach based on SWAT-BiLSTM and SHAP.

Streamflow is a crucial variable for assessing the available water resources for both human and environmental use. Accurate streamflow prediction plays a significant role in water resource management and assessing the impacts of climate change. This study explores the potential of coupling conceptual hydrological models based on physical processes with machine learning algorithms to enhance the performance of streamflow simulations. Four coupled models, namely SWAT-Transformer, SWAT-LSTM, SWAT-GRU, and SWAT-BiLSTM, were constructed in this research. SWAT served as a transfer function to convert four meteorological features, including precipitation, temperature, relative humidity, and wind speed, into six hydrological features: soil water content, lateral flow, percolation, groundwater discharge, surface runoff, and evapotranspiration. Machine learning algorithms were employed to capture the underlying relationships between these ten feature variables and the target variable (streamflow) to predict daily streamflow in the Sandu-River Basin (SRB). Among the four coupled models and the calibrated SWAT model, SWAT-BiLSTM exhibited the best streamflow simulation performance. During the calibration period (training period), it achieved R2 and NSE values of 0.92 and 0.91, respectively, and maintained them at 0.90 during the validation period (testing period). Additionally, the performance of all four coupled models surpassed that of the calibrated SWAT model. Compared to the tendency of the SWAT model to underestimate streamflow, the absolute values of PBIAS for all coupled models are below 10%, which indicates that there is no significant systematic bias evident. SHapley Additive exPlanations (SHAP) were used to analyze the impact of different feature variables on streamflow prediction. The results indicated that precipitation contributed the most to streamflow prediction, with a global importance of 29.7%. Hydrological feature variable output by the SWAT model played a dominant role in the Bi-LSTM's prediction process. Coupling conceptual hydrological models with machine learning algorithms can significantly enhance the predictive performance of streamflow. The application of SHAP improves the interpretability of the coupled models and enhances researchers' confidence in the prediction results.

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.

Effect of seasonal freeze–thaw process on spatial and temporal distribution of soil water and its infiltration to recharge groundwater

AbstractClarifying the distribution and dynamics of soil moisture during the freeze–thaw process is crucial for surface ecology and is an objective requirement to investigate the mechanism of changes during the groundwater recharge process in a freeze–thaw zone. Based on the monitoring data of soil moisture and temperature in the Changbai Mountain area, the freeze–thaw process is classified into four periods. This study investigates the hydrothermal migration processes during different periods. The simultaneous heat and water model is used to simulate and analyse the infiltration of soil moisture into groundwater under five precipitation insurance rates. The results are as follows: (1) The smaller the soil depth, the stronger is the correlation between soil temperature and air temperature during the freeze–thaw process. (2) The redistribution of soil moisture before and after freeze–thaw is significantly affected by the soil texture, and soil permeability affects the recharge of soil moisture from the upper region to the lower region during the thawing period. (3) Groundwater receives vertical infiltration recharge mainly during non‐freezing and is supplied by freezing and snowmelt recharge during the stable thawing period. The percentage of soil water infiltration during the stable thawing period in the total annual infiltration increases gradually with the precipitation insurance rate.

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.

The effect of soil texture, layering and water head on the infiltration rate and infiltration model accuracy

AbstractInfiltration is one of the most important physical characteristics of soil and depends on various factors. This study investigated the influence of soil texture, layering and water head on the soil water infiltration rate. It also selected the most accurate infiltration models to determine the water infiltration rate in homogeneous and heterogeneous soil profiles. Experiments were carried out in four soil containers with a length, width and height of 20 × 20 × 70 cm. Treatments consisted of two soil textures (sandy loam, SL; clay loam, CL), four soil profiles (homogeneous texture, SL and CL; and heterogeneous texture, lighter texture on the top, SL/CL, and heavier texture on the top CL/SL) and three water head sizes (4, 7 and 10 cm). Several models were used to determine the water infiltration rate under homogeneous (Kostiakov, modified Kostiakov, Philip, Horton, traditional Green–Ampt, modified Green–Ampt and HYDRUS‐1D) and heterogeneous soils (traditional Green–Ampt, modified Green–Ampt and HYDRUS‐1D). According to the results, the infiltration rate decreased over time and along the soil profile. Nevertheless, it jumped at the interface of two‐layered soils when the heavier soil was in the bottom layer (SC treatments) due to the high potential of the second layer, and then it decreased. In the reverse layering, the infiltration rate in the interface was lowest (CS treatments) because of the higher hydraulic conductivity of the second layer. Additionally, the infiltration rate increased with increasing water head, but the rate of this increase was higher by changing the water head from 7 to 10 cm. The results of infiltration models showed that the accuracy of these models was higher in clay loam texture than in sandy loam texture. The modified Green–Ampt was the most accurate model in homogeneous and layered soils, with average RMSE of 0.0204 and 0.019, respectively. The Horton model had the weakest simulation in homogeneous soils, with an average RMSE of 0.1299. Additionally, the accuracy of HYDRUS‐1D in layered soils was less than that in homogeneous soils (NS of 0.95 and 0.85, respectively), and its accuracy decreased with increasing water head in most treatments.

Long term response and adaptation of farmland water, carbon and nitrogen balances to climate change in arid to semi-arid regions

Climate change poses a challenge for resource utilization and environmental pollution issues caused by agricultural production, especially in arid to semi-arid regions. Farmland water, carbon and nitrogen balances are closely related to these resource and environmental issues. Thus, the Agro-Hydrological & chemical and Crop systems simulator was used to assess the response of water, carbon and nitrogen balances to climate change in a spring wheat farmland of arid to semi-arid Northwest China and to propose adaptation strategies. Five Global Climate Models from the Coupled Model Intercomparison Project 6 and two Shared Socioeconomic Pathways (SSP1–2.6 and SSP5–8.5) were used to establish scenarios with the Agro-Hydrological & chemical and Crop systems simulator to simulate farmland water, carbon and nitrogen balances for the 2025–2100 period. Various irrigation amounts and nitrogen fertilization rates were tested as compensation strategies. Results indicated that climate change could negatively affect farmland water, carbon and nitrogen balances, especially under the SSP5–8.5 scenario. Precipitation showed an increasing trend, thus percolation increased and soil water consumption decreased from 2025 to 2100. However, for the carbon budget, although the soil carbon dioxide emissions tend to decrease, the net primary production was also significantly reduced, which resulted in declining the net ecosystem carbon budget under future climatic conditions. In addition, higher temperature and increased precipitation enhanced soil inorganic nitrogen leaching and nitrous oxide emissions but reduced ammonia volatilization from 2025 to 2100. Overall, the soil total nitrogen loss was increased over time, whereas crop nitrogen uptake was significantly reduced. In relation to the SSP1–2.6 scenario, the SSP5–8.5 scenario accelerated the increase rates of soil water percolation and total nitrogen loss over time, as well as the decrease rates of crop nitrogen uptake and net primary production over time. The negative effects caused by climate change can be mitigated by reducing irrigation and increasing nitrogen fertilization. For the SSP1–2.6 scenario, 30% irrigation reduction and 30% nitrogen fertilization increase can effectively decrease soil water percolation and the related nitrogen losses while crop nitrogen uptake, net primary production and net ecosystem carbon budget increase in relation to the current management (irrigation = 240 mm and nitrogen fertilization = 200 kg ha–1). For SSP5–8.5 the strategy with 45% irrigation reduction and 45% nitrogen fertilization increase can also decrease nitrogen losses and increase crop nitrogen uptake, net primary production and net ecosystem carbon budget.

Dynamics of soil water and nitrate within the vadose zone simulated by the WHCNS model calibrated based on deep learning

Excessive application of water and nitrogen fertilizer during farmland management practices leads to serious groundwater nitrate pollution. A field experiment was conducted during the spring maize growth period in Alxa, Inner Mongolia, China. The soil Water Heat Carbon Nitrogen Simulator (WHCNS) model was calibrated by the ensemble smoother method (ES(DL)) based on the field experiment. Then dynamics of soil water content, soil water percolation flux, soil nitrate concentration and soil nitrate leaching flux were simulated with the calibrated WHCNS model under different water and nitrogen fertilization treatments within the vadose zone. The main conclusions are as follows: ES(DL) is feasible for the calibration of the WHCNS model. RMSE_Maximum a posteriori (RMSE_MAP) of soil water content are 0.0301 cm3 cm−3 and 0.0302 cm3 cm−3 for model calibration and model validation, respectively. RMSE_MAP of soil nitrate concentration are 5.49 mg N kg−1 and 3.86 mg N kg−1 for model calibration and model validation, respectively. Both average soil nitrate concentration and average nitrate leaching flux increase with increasing irrigation amount under the same nitrogen fertilization level for the depths of 1.2 m and 1.8 m. However, average soil nitrate concentration decreased and leaching flux increased with increasing irrigation amount under the same nitrogen fertilization level for the depths of 10 m and 20 m. The study of nitrate dynamics in the deep vadose zone contributes to better understand the procedure of nitrate pollution in groundwater caused by excessive water and nitrogen application.

Woody species alongside earth contour bunds enhance the soil water‐infiltration capacity in the Sahel, West Africa

AbstractLand degradation, including the loss of tree, forest and vegetation cover, and its related loss of water availability are the main constraints affecting the rainfed agricultural systems in West African Sahel and dry savanna. Therefore, farmers are implementing various soil and water conservation techniques such as zaï pits, half‐moons, contour stone and earth bunds to improve crop production through reduced erosion and enhanced water retention. This study explores the effect of woody and herbaceous vegetation established along earth contour bunds on soil infiltration capacity in southern Mali. The soil infiltration measurements were carried out from September to December 2019 using single ring infiltrometers up‐slope and down‐slope of the bunds built on contour lines in 2015 and 2016 with four types of vegetation: (1) natural annual herbaceous vegetation; (2) planted Andropogon gayanus (perennial grass); (3) planted Gliricidia sepium (woody species) and (4) planted Acacia colei (woody species). The field‐saturated hydraulic conductivity (Kfs) was estimated from the infiltration data and subjected to statistical analysis to compare the effect of the four types of vegetation on soil infiltration capacity. The results revealed significant differences in infiltration rate and Kfs between the four vegetation types. The highest infiltration rate and Kfs were observed for earth contour bunds reinforced with woody species G. sepium (299.5 ± 0.6; 45.3 ± 1.4 mm h−1), followed by A. colei (232.2 ± 2; 38.2 ± 1.6 mm h−1). These were followed by the grass A. gayanus (189.4 ± 2.5; 33.0 ± 1.7 mm h−1) and natural annual herbaceous vegetation (132 ± 2.3; 20.7 ± 1.9 mm h−1). In addition, soil water‐infiltration rate and Kfs were higher for down‐slope compared to up‐slope areas for the two woody species. In practice, it is appropriate for farmers to reinforce contour bunds with woody species and perennial herbs given the beneficial effect on soil water infiltration and retention capacity and the expected socio‐economic benefit they can get from them.

The Simulated Experimental Design and Study of the Synergistic Treatment of Chicken Manure and Traditional Chinese Medicine Residues on Earthworm Growth and Soil Quality

Annelids conspicuously exert influence upon soil physicochemical attributes through their alimen-tary, burrowing, and excretion endeavors, thereby imparting ramifications upon soil erosion phenomena. Nev-ertheless, comprehension of the particular repercussions stemming from annelid activities vis-à-is soil erosion remains circumscribed. The primary objective of this investigation was to scrutinize the synergistic ramifica-tions of gallinaceous fecal matter and remnants of traditional Chinese medicinal substances on annelid prolif-eration and soil characteristics within a simulated experiment. In order to gauge the impact of annelid activities upon soil hydric distribution, runoff velocity, and soil erosion, a laboratory-simulated precipitation experiment was executed across three incline gradients (5 degrees, 10 degrees, and 15 degrees), featuring a uniform pre-cipitation intensity of 80 mm/h and a 60-minute precipitation duration post-runoff initiation. Findings evinced that annelids significantly heightened soil hydric infiltration and retention. In tanks inhabited by annelids, the increments in soil hydric retention were 93%, 51%, and 70% more elevated than those in control plots at incline gradients of 5 degrees, 10 degrees, and 15 degrees, respectively. Comparatively, earthworm activities led to a 70% reduction in runoff rate at a 5-degree slope, a 13% reduction at 10 degrees, and a 39% reduction at 15 degrees. However, soil erosion rates increased by 42% and 46% at slope gradients of 10 degrees and 15 degrees, respectively. Earthworms, through their feeding and burrowing activities, not only enhanced soil water infil-tration but also mitigated surface runoff while contributing to increased soil erosion. This research proffers invaluable perspicacity regarding the influence of subterranean fauna on the vicissitudes of soil erosion pro-cesses, furnishing empirical evidence amenable for assimilation into extant soil erosion simulation paradigms or as a substratum for the construction of nascent models.

Método sobol para análise de sensibilidade do modelo hydrus na simulação de infiltração de água em depósito aluvionar no semiárido brasileiro

ABSTRACT Simulation of water flow in the soil in semiarid regions is fundamental for managing scarce water resources. Aiming for more accurate results, the sensitivity analysis (SA) of the hydrodynamic parameters involved in the simulations is very relevant. This study aims to evaluate the influence of hydrodynamic parameters on the hydrological response of an alluvial deposit in the dry bed of the Capibaribe River using the Hydrus-1D. A global sensitivity analysis method proposed by Sobol was chosen to evaluate the sensitivity of the soil water infiltration curve. A convergence analysis was carried out to investigate the evolution of the indices with increasing sample size. Values of the sensitivity indices showed gross variations at the beginning of the simulations for the different parameters, but they converged within the set of 10,000 samples. For parameters whose sensitivity indices are closer to 0, it is noted that 1,000 samples (14,000 simulations) were sufficient for the index to converge to their final value. The total and first-order sensitivity index calculated with 10,000 samples present the parameters n and Ks as the most important, being expressly more influential than the others.

Effects of land use and land cover on Soil-Water Infiltration: A Literature Review and Bibliometric Analysis

The impact of land use and land cover (LULC) on hydrology is gaining increased attention due to global concerns about water sustainability. Although various studies have been conducted related to the topic, there were only a few publications that specifically focused on the effects of LULC on soil water infiltration. This study gathered and synthesized relevant research publications and performed co-occurrence and co-citation analyses to identify the existing themes and the research development trend on LULC-soil infiltration relation. Analysis of 103 Scopus-indexed articles from as early as 2000 revealed four major themes: soil characteristics, hydrology and watershed, hydrology and management, and groundwater and LULC. These findings highlight key areas of focus and can assist in identifying research gaps and topics requiring further exploration. The paper offers a concise overview of the current research trajectory in the realm of LULC and soul water infiltration.

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.