Soil Water Flow Research Articles

Transformation process of five water in epikarst zone: a case study in subtropical karst area

Five water stands for five form existence models of water. In karst area, five water means precipitation, groundwater, evapotranspiration water, soil water, and overland flow. The complicated water-bearing hydrogeological media and the inhomogeneous water storage structure lead to low efficiency of water utilization. To reveal intricate water resources transformation in karst areas, a typical epikarst zone was selected. The five water and their conversion processes were studied and the transformation models were built based on the long-term positioning observations. The results show that (1) overland flow can be generated when precipitation reaches 6 mm and lasts for 6 h. Under light and moderate rainfall (LMR) conditions, less than 6% of the precipitation is converted to overland flow. Under heavy rainfall and rainstorm (HRR) conditions, the conversion of precipitation into overland flow in about 3.5–6%. (2) Under LMR conditions, the conversion rate of precipitation to vegetation water, soil water and groundwater was 2–3.5%, 40–60% and 25–35%, and the conversion rate under HHR conditions was 1.5–2.2%, 25–30% and 32–50%. (3) The proportion of different levels precipitation was transformed to soil water is 20–70%. (4) The conversion rate of groundwater and karst fissure water for LMR conditions are 8–15% and 10–15%, and that for HRR is 15–20% and 40–50%. (5) The proportions of different degrees of precipitation transformed into vegetation transpiration and evaporation water are 1.5–3.5% and 6–9%, respectively. (6) Generally, <4% of the precipitation is converted into overland flow, 20–70% into soil water, 25–50% into karst groundwater, and 1–10% into evaporative water.

Interaction Simulation of Vadose Zone Water and Groundwater in Cele Oasis: Assessment of the Impact of Agricultural Intensification, Northwestern China

Agricultural intensification has boosted land productivity, but it has also created new sustainability issues. As one of the most important human habitations and agricultural farming areas in arid areas, the Cele Oasis has a very developed agricultural system. This paper studies the long-term effects of different types of agricultural intensification strategies on groundwater level fluctuations in the Cele Oasis. A soil water flow (HYDRUS-1D) and aquifer simulation (MODFLOW) coupling model were used to construct the geometric structures of the vadose zone and saturated zone in the Cele Oasis and to analyze the recharge and discharge mechanism of the oasis. The results showed that HYDRUS-1D accurately simulated soil moisture transport in the Cele Oasis, providing reliable data for calibration of the MODFLOW model. The groundwater level simulated by MODFLOW was in good agreement with the observed value. The results of the R2, RMSE, and NSE were ranges of 0.77–0.90, 0.45–0.74 m, and 0.76–0.87, respectively. The errors were acceptable limits. The coupling model predicted the responses of different agricultural types and cropping scenarios to groundwater. Predictions showed that the groundwater level in the Cele Oasis remained stable under the current cropping scenario (100% cropping intensity), and that the groundwater level decreased slightly under the cropping scenario (110% cropping intensity and 130% cropping intensity). When the cropping scenario was at 170% cropping intensity, the groundwater level decreased rapidly, and the maximum drawdown value was 7 m. Therefore, the maximum cropping intensity of the Cele Oasis in the future should be 130% of the current cropping intensity.

Review of Rain or Shine: An Introduction to Soil Physical Properties and Processes. Tyson Ochsner. Published by Oklahoma State University Libraries under the Creative Commons Attribution 4.0 International License. Version 6. Last updated 19 Jan. 2022. DOI: https://doi.org/10.17605/OSF.IO/Z4RBT

Review of <i>Rain or Shine: An Introduction to Soil Physical Properties and Processes</i>. Tyson Ochsner. Published by Oklahoma State University Libraries under the Creative Commons Attribution 4.0 International License. Version 6. Last updated 19 Jan. 2022. DOI: https://doi.org/10.17605/OSF.IO/Z4RBT

Soil water movement differences relating to banana (Musa nana Lour.) plantation regime

AbstractThe long‐term cultivation of banana crops (Musa nana Lour.) has caused improper utilization of soil and water resources. However, the effect of the banana plantation regime on soil water flow pattern is still poorly understood. This study focused on the dominant pattern of soil water movement in the 1‐year (B1) and 4‐year (B2) old banana plantations. The results showed that: (1) the soil physical properties showed variability with soil depths, especially obvious changes from surface to 40 cm depth, which had restriction on soil infiltration in different depths. (2) The saturated hydraulic conductivity (Ks) decreased with the increasing distance from the banana stem. Moreover, the Ks in the B2 plot increased by 65.5% compared to the B1 plot at the soil layer 0–20 cm. (3) Preferential flow was the main path of soil water transport and was significantly influenced by soil bulk density, porosity, and root systems. Redundancy analysis (RDA) showed that banana root biomass was the most prominent factor influencing the dyed area. (4) The soil infiltrability and the preferential flow degree of both B1 and B2 plots were stronger in the root zone than those in the non‐root zone. Such results were attributed to the root systems around the banana stem that were more developed than those far away from the stem (more accurately pseudostems); a large number of pore channels formed around the root systems that promoted the preferential flow. Or results suggest that banana root was the important factor affecting soil water movement. The improvement in the root network of banana plantation regime can result in better soil physical properties. This knowledge will be vital for the sustainable cultivation and irrigation of banana crops.

A Fuzzy AHP Approach to Assess Flood Hazard for Area of Bang Rakam Model 60 Project in Yom River Basin, Northern Thailand

The Thai government developed the “Bang Rakam Model 60” to solve flood issues in low-lying areas (Phitsanulok and Sukhothai Provinces). In the project, farmers will have to start planting in early April and harvest in July. This research proposes a methodology for assessing flood hazard using a fuzzy analytic hierarchy process (fuzzy AHP) relied on Chang’s extent analysis. It was employed to derive the weight for factor ranking and create a flood hazard map. Eight hazard factors are considered in the methodology: average annual rainfall, drainage density, distance from drainage network, soil water infiltration, land use, elevation, slope, and flow accumulation. The generated flood hazard maps were validated using the repeated flood area from Geo-Informatics and Space Technology Development Agency (GISTDA). Due to the difference of rated opinion on the drainage density factor, the eight experts were divided into two groups of four each. The results of both expert groups indicated that the most pivotal influencing factor to flood hazard is the average annual rainfall. From the first group, it is stated that the highest flood hazard areas are in Phrom Phiram, Mueang Phitsanulok, and Bang Rakam Districts. Whereas, the second group stated that very high flood hazards level occurring mostly in Phrom Phiram District. The flood hazard area was divided into five levels of very low, low, moderate, high, and very high which the first group found that they covered 75.59 km2, 184.44 km2, 211.94 km2, 165.78 km2, and 57.81 km2, respectively, while the second group found that they covered 38.93 km2, 100.22 km2, 175.58 km2, 218.90 km2, and 161.91 km2, respectively. The obtained flood hazard assessment provides crucial information for future flood preparation, response, prevention, mitigation, and recovery initiatives. Moreover, it will guide the government agencies in supplying water and save the compensation budget to victims’ flood-affected farms.

A monthly distributed agro-hydrological model for irrigation district in arid region with shallow groundwater table

Agro-hydrological processes in arid irrigation districts mainly include precipitation, water diversion, irrigation, drainage, evapotranspiration (ET), and soil water and groundwater flow, which interact with each other and are controlled by complex natural and anthropogenic drivers. To better understand the agro-hydrological processes in arid irrigation districts with shallow groundwater table, we developed a novel monthly distributed agro-hydrological model for irrigation districts (DAHMID) based on the concepts of canal command area (CCA) and sub-drainage command area (SDCA). The DAHMID model is driven by meteorology, irrigation, and evapotranspiration (ET) estimated by remote sensing-based ET model, and considers soil water and groundwater balances in both irrigated and non-irrigated lands and interior drainage between them. The model was applied to Hetao Irrigation District (HID), the largest irrigation district in arid region of China with a total irrigated area of 0.68 million ha. The DAHMID model was calibrated with groundwater table depth measurements in 13 CCAs of HID from 2008 to 2010, and validated from 2012 to 2013. Results depicted that the root mean square errors (RMSEs), normalized RMSEs (NRMSEs), Nash-Sutcliffe efficiency coefficients (NSEs), and coefficients of determination (r2) of groundwater table depth in both irrigated and non-irrigated lands for all CCAs were in the ranges of 0.19–0.34 m, 0.10–0.25, 0.30–0.82, and 0.68–0.91, respectively. The simulation results from 2008 to 2014 indicated that interior drainage from irrigated land to non-irrigated land is an important approach of drainage in HID, which is about 14.3% of total irrigation water diversion and 34.9% more than the drainage through ditches. The interior drainage process is basically similar to irrigation and ditch drainage processes, all reaching their peaks in May and October. ET is the major water consumption in HID, which is about 95% of total irrigation water diversion and precipitation in average. The net capillary rise of irrigated land is significantly less than that of non-irrigated land due to the impact of irrigation infiltration. The DAHMID model has less parameters and requires less inputs, and can be better applied to continuous simulation of agro-hydrological processes in irrigation districts in medium and long periods with satisfactory simulation accuracy.

Simulations of Soil Water and Heat Processes for No Tillage and Conventional Tillage Systems in Mollisols of China

Soil water and temperature are important factors to reflect variations in soil heat and water flows especially for tillage systems. The objective of this study was to evaluate the performance of the CoupModel in predicting the effect of tillage practices on soil water and heat processes for conventional tillage (CT) and no-tillage (NT) systems with straw mulching on semi-arid and high-latitude Mollisols of northeast China. This model was calibrated and evaluated in a three-year tillage experiment from 2009 to 2011 in a field experiment station, using field measurements of daily soil temperature and water storage in profiles for CT and NT separately. The results showed that under the model, soil temperatures were well simulated at 0–90 cm soil depths for CT, as indicated by R2 ≥ 0.97, the nRMSE = 27.5–38.7% and −1.02 °C ≤ ME ≤ −0.31 °C, and soil water storage at 0–130 cm soil depth (R2 = 0.01–0.06, the nRMSE = 19.6–37.1%, 13.3 mm ≤ ME ≤ 28.2 mm) was simulated with more uncertainty. “Moderate to good agreements” were achieved for NT. In general, the temporal and spatial variations of soil temperature and water for NT were well simulated by CoupModel. Although NT decreased soil evaporation—thus improving soil water content, especially in the root zone soil—and lowered the soil frozen depths, it reduced the soil temperatures, which could influence crop growth. It was concluded that the CoupModel proved to be a functional tool to predict soil heat and water processes for CT and NT systems in high-latitude seasonal frost conditions of Mollisols in China to estimate the soil temperature, water, energy balance, and frost depth dynamics in relatively complex systems that combined plant dynamics with tillage and/or no tillage covered with straw mulching in the soil surface.

Changes of Soil Water and Heat Transport and Yield of Tomato (Solanum lycopersicum) in Greenhouses with Micro-Sprinkler Irrigation under Plastic Film

This study aimed to expound the changes in soil water flow, heat transport, and tomato production under micro-sprinkler irrigation and plastic film (MSPF) conditions. The effects of different irrigation amounts (I1:0.7 Epan; I2:1.0 Epan; and I3:1.2 Epan (Epan is the cumulative evaporation from a 20 cm diameter standard pan, mm)) on soil water, soil temperature, and tomato yield were studied. A completely randomized trial design was used; meanwhile, the drip irrigation under plastic film (CK1) and micro-sprinkler irrigation without mulch film (CK2) were used as controls. The results showed that the shape of soil moisture was banded under MSPF; the soil wetting range was larger than that of CK1 and CK2 in the profile of MSPF. The change range of 5 cm soil temperature of MSPF 1–5 days after irrigation was 4.05 °C. The change range of 5 cm soil temperature of MSPF was lower than that of CK1 from 1 to 5 days after irrigation. During the growth period of spring and autumn tomato, the average soil moisture content of 0–40 cm with CK1 was 1.97% and 3.83% (spring and autumn, respectively) higher than that of MSPF, and the average soil temperature of 5–25 cm was 2.36% and 1.66% (spring and autumn, respectively) lower than that of MSPF. Compared with CK2, the average soil moisture content of 0–40 cm under MSPF increased by 8.30% and 3.83% (spring and autumn, respectively), and the average soil temperature of 5–25 cm under MSPF increased by 5.85% and 1.68% (spring and autumn, respectively). The spring and autumn tomato yield of MSPF was significantly higher than that of CK1 by 19.39% and 4.54%, respectively. The spring and autumn tomato yield of MSPF were higher than that of CK2 by about 20.46% and 49.22%, respectively. With an increase in the irrigation amount of MSPF, the soil moisture and yield of spring and autumn tomato increase; the soil temperature and water use efficiency of spring and autumn tomato decrease. Considered comprehensively, the MSPF can be used as one of the methods of greenhouse tomato micro-irrigation, and 1.0 Epan is recommended for irrigation parameters in northwest China facility agriculture.

Experimental evaluation of salinity geosynthetics capillary barriers

This paper explores the transient upward flow of saline water in one-dimensional soil and soil–geosynthetics columns to evaluate preventive measures to mitigate salinity rise. Unsaturated soil concepts are utilised to elucidate the salinity movement through geotextile and geocomposite drain interfaces. The presence of a geotextile layer slowed down the capillary rise of the saline water. However, it did not prevent the breakthrough of the saline water due to the hydrophilicity of the geotextile and the suction at the geotextile base being close to the geotextile's water entry suction value. In contrast, using a geocomposite drain mitigated the upward saline wetting front. It acted as a salinity capillary barrier due to the initial hydrophobicity of its geotextile component and the air gap present in the geonet core.

Soil macroporosity and water flow in the root zone of oases in hyper‐arid regions

AbstractThe characteristics of soil macropores and water infiltration are closely connected to the growth of plant roots and their root zone environment. However, it is unclear how the root zone environment of oasis farmlands regulates the development of soil macropores and water flow in hyper‐arid regions. The objective of this study was to investigate soil macropores and their effect on water flow under irrigated oasis farmlands using a combination of X‐ray computed tomography (CT) and dye tracer. It was hypothesized that the integration of CT and dye tracer could clearly reveal preferential flow through biopores and large pores of oasis soils. A helical medical CT scanner was used to quantify more information about soil macropores in the root zone, along with an in situ single‐ring dye infiltration experiment to reveal water flow in three different oasis farmlands (piedmont oasis farmland, marginal oasis farmland, and old oasis farmland). Soil macroporosity was 0.44% under crop rows, while soil macroporosity in the interrows was only 0.30% across the oasis farmlands. Biopores contributed 73% of the volume of the total macropores under crop rows. The stable infiltration rate in the interrows was 0.3 mm min−1, which was significantly (p &lt; 0.05) less than that under crop rows (0.7 mm min−1). Water flow under crop rows were mainly transported in biopores and large pores. The contribution of macropores to preferential flow under crop rows was 4.8 times larger than interrows. The integration of CT and dye tracer was a more holistic technique, which adequately revealed that oases had preferential flow affected by biopores and large pores, resulting in higher solute and contaminant transport.Key Points Soil macropores and preferential flow affected by crop roots were investigated in hyper‐arid regions. The integration of CT and dye tracer adequately identified preferential flowpaths of oasis soils. Biopores were larger under crop rows than interrows. Preferential flow transported in biopores and large soil pores under crop rows.

Prediction of saturated hydraulic conductivity of sandy soil using Sauter mean diameter of soil particles

AbstractSaturated hydraulic conductivity of soil, Ksat, is a critical parameter for mathematical modelling of groundwater and soil water flow. Current empirical Ksat models, such as Kozeny–Carman model, Hazen models, or empirical approaches based on soil pedotranfer functions (PTFs) rely on the specific surface area, certain characteristic particle size(s), for example, d5, d10, d15, d50, etc., or the fractionation of sand, silt and clay. In this study, we proposed an alternative modelling framework to estimate Ksat from void ratio and arithmetic mean diameter of soil particles. We suggested to describe the particle size distribution (PSD) using a continuous mathematical distribution function, for example, the lognormal distribution function, and to obtain the Sauter mean diameter (dS) by calculating the moments of the PSD function. The proposed empirical equations were tested against the measured Ksat values for 54 sand samples with available measured PSD and void ratio as reported in Toumpanou et al. and validated using 49 sandy soil samples obtained from the Unsaturated Soil Database (UNSODA). We found that the dS was more relevant to Ksat than the number mean diameter (dN) and mass mean diameter (dM) (the RMSE was 0.486 for Ksat ‐ dN; 0.187 for Ksat ‐ dS; and 0.212 for Ksat ‐ dM, respectively). We also found that the proposed equation with dS had superior performance over the Hazen equation and PTF‐based models. Our results indicated that the Ksat calculated using dS, which was either estimated from discrete experimental data or calculated from a continuous lognormal PSD function, best matched with the measured values for coarse‐textured soils. Future studies should focus on developing empirical relationships for soil water retention curves and other soil properties based on continuous PSD functions.Highlights A modelling framework to estimate Ksat from the void ratio and arithmetic mean diameter is proposed. Sauter mean diameter, dS, can be obtained by calculating the moments of the PSD function. Ksat model using dS performs better than that using dN, dM, d5, d10, or d50 or PTF‐based models.

Combining FDR and ERT for monitoring soil moisture and temperature patterns in undulating terrain in south-eastern Norway

The occurrence of freeze–thaw cycles modifies water infiltration processes and surface runoff generation. Related processes are complex and are not yet fully investigated at field scale. While local weather conditions and soil management practices are the most important factors in both runoff generation and surface erosion processes, local terrain heterogeneities may significantly influence soil erosion processes in catchments with undulating terrain.This paper presents a field-based investigation of spatial and temporal heterogeneities in subsurface soil moisture and soil temperature associated with freezing, thawing, and snowmelt infiltration. The field setup consists of a combination of traditional point measurements performed with frequency domain reflectometry (FDR) and electrical resistivity tomography (ERT). The transect was approximately 70 m long and spanned an entire depression with a north-facing slope (average slope of 11.5%) and a south-facing slope (average slope of 9.7%). The whole depression was entirely covered with stubble.Observed resistivity patterns correspond well to the measured soil moisture patterns. During the observation period, the north facing slope froze earlier and deeper compared with the south facing slope. Freeze–thaw cycles were less pronounced in the north-facing slope than in the south-facing slope. There were also differences in soil temperature and soil moisture patterns between lower and upper parts of the monitored depression. These indicate that initiation and development of runoff related processes, and consequently soil erosion, in regions with freeze–thaw cycles may differ significantly depending on local terrain characteristics. Consequently, it indicates that spatial terrain heterogeneities, especially slope aspects, may be important when studying soil erosion processes, water flow and nutrient leaching in lowlands where patchy snowpacks and dynamic freeze–thaw cycles are predominating.

A coupled surface-subsurface flow model for simulating soil-water dynamics in lowland rice field under alternate wetting and drying conditions

The lack of coupled surface-subsurface flow models applied in lowland rice irrigation systems is the prime mover for this research. This study aimed to develop a coupled model that can capture the soil-water dynamics in paddy rice fields and to calibrate and validate the model using actual field data to serve as basis for irrigation water management using alternate wetting and drying (AWD) for lowland rice production systems. The zero-inertia surface flow model was internally coupled with the Richards-based subsurface flow model through Python scripts. Boundary conditions were set accordingly based on lowland rice field scenarios. Irrigation advance times were observed manually, while field water recession data were collected using wireless sensors. Model calibration showed acceptable results for the surface flow (R2≥0.99; SE≥0.97; RMSE≤3.14min), and subsurface flow (R2≥0.71; NSE≥0.60; MSE≤8.78mm; SD≤5.51mm; AE≤7.51mm) domains. Likewise, model validation yielded acceptable results for surface flow (R2≥0.98; NSE≥0.88; RMSE≤6.12min) and subsurface flow (R2≥0.76; NSE≥0.60; RMSE≤10.87mm; SD≤7.91mm; AE≤8.28mm), respectively. Results also showed the model’s capability to simulate water level fluctuations in AWD-irrigated rice fields during the wet and dry seasons under various rainfall scenarios. Model projections showed the need for AWD irrigation practice when the normal rainfall had been reduced by 75% during the wet season. Dry season simulations indicated the need for AWD under all rainfall scenarios. Simulation results have further unveiled the importance of the plow pan characteristics in influencing the soil-water flow behavior. This study was also able to address the limitations of the existing coupled models that could not meet the boundary conditions of paddy rice field settings. Ultimately, the model developed in this study could serve as basis for the development of optimum irrigation operation schemes in AWD -irrigated rice fields.

Spatial–temporal modeling of root zone soil moisture dynamics in a vineyard using machine learning and remote sensing

High-resolution spatial–temporal root zone soil moisture (RZSM) information collected at different scales is useful for a variety of agricultural, hydrologic, and climate applications. RZSM can be estimated using remote sensing, empirical equations, or process-based simulation models. Machine learning (ML) approaches for evaluating RZSM across numerous spatial–temporal scales are less generalizable than process-based models. However, data-driven ML approaches offer a unique opportunity to develop complex models of soil moisture without making assumptions about the processes governing soil water dynamics in a given study region. In this study, comparisons were made between two models, pySEBAL and EFSOIL, which were based on evaporation fraction (EF) and soil properties, and a data-driven model based on the Random Forest (RF) ensemble algorithm. These approaches were evaluated to demonstrate their capabilities for RZSM estimation. The EF obtained from Landsat images was used after validation with eddy covariance measurements as the major input to all three models, along with other meteorological and soil physical properties. The RF model was trained using in situ soil moisture data from Time Domain Reflectometry (TDR) sensors installed in a vineyard from 2018 to 2020. The predictor variables comprised of meteorological, soil properties, EF, and a vegetation index. The results reveal that there was a strong correlation between the in situ measured soil moisture and the RF predicted soil moisture at all sensor locations. Due to the complexity of the physical processes involved in soil water flow, the empirical models pySEBAL and EFSOIL were unable to reliably predict RZSM values at all monitored locations. The high RZSM predicted by pySEBAL demonstrated the presence of possible bias in the model’s algorithm used to estimate soil moisture. We also demonstrated that ML based on the RF algorithm may be used to predict spatially distributed RZSM when a few soil moisture ground measurements are combined with remote sensing to produce soil moisture maps.

Assessment of Soil Physical Quality and Water Flow Regulation under Straw Removal Management in Sugarcane Production Fields

Removing sugarcane straw to increase bioenergy production can generate significant income to the industry. However, straw contributes to the regulation of soil functions and consequently supports the provision of ecosystem services, such as water flow regulation. Thus, straw removal may hinder the provision of these services, especially in mechanized sugarcane production systems, which have soil compaction problems due to machinery traffic. In this study, we assess a six-year experiment in Brazil with four rates of straw removal: 0 Mg ha−1 (TR), 5 Mg ha−1 (HR), 10 Mg ha−1 (LR), and 15 Mg ha−1 (NR) remaining straw. Using attributes, such as soil bulk density, porosity, water infiltration, runoff, saturated hydraulic conductivity and available water-holding capacity, as indicators of key soil functions, we calculated a soil-related ecosystem service (ES) index for water flow regulation provision. The ES index revealed that water flow regulation was low regardless of the straw management (0.56, 0.63, 0.64 and 0.60 for TR, HR, LR and NR, respectively). It can be a consequence of soil compaction caused by machinery traffic throughout the successive cycle, whose straw was unable to mitigate this issue. Thus, by the end of the sugarcane cycle (sixth ratoon), straw removal had little effect on soil physical and hydraulic indicators, and consequently had little impact on the provision of the soil-related ES associated with water flow regulation. Nevertheless, straw management should be planned to consider other functions and soil-related ES benefited by straw retention.

Changes in Soil Infiltration and Water Flow Paths: Insights from Subtropical Forest Succession Sequence

Changes in Soil Infiltration and Water Flow Paths: Insights from Subtropical Forest Succession Sequence

Numerical Solution of Water Flow in Unsaturated Soil with Evapotraspiration

Flow movement in unsaturated soil can be expressed by Richards equation. This equation can be obtained by applying the mass conversation law and the Darcy law. In this work, we solve one-dimensional Kirchhoff transformed Richards equation with loss of water due to the evaporation of unsaturated porous media (soils) and transpiration of plants numerically using Crank-Nicolson method. The result has compared with evapotranspiration function and without it in the governing equation. It has found that an additional work in time and flow movement is needs to reach the given boundary condition for the model without evapotranspiration.

Modeling seasonal soil moisture dynamics in gley soils in relation to groundwater table oscillations in eastern Croatia

This study aims to explain complex vadose zone hydrology of fine-textured (gley) agricultural soils influenced by a shallow and dynamic groundwater (GW) levels. The field site was located in the Biđ field (Eastern Croatia), where a detailed soil survey was performed. The simulations included a three-year period (2016–2018) at four locations. Soil hydraulic parameters (SHP) were estimated based on variables determined in the laboratory, while soil water flow was monitored using in-field zero-tension lysimeters. Piezometers were installed and used to monitor daily oscillations of groundwater levels (average depth to GW 2.2 m), while data from nearby Sava River was monitored. Unsaturated flow and water regime assessment was performed using HYDRUS-1D numerical modeling. Additional SHP optimization of van Genuchten-Mualem parameters (α and n) was performed using Shuffled Complex Evolution algorithm (SCE). The autocorrelation analysis was used to detect patterns in the precipitation, GW, and river level time series, while the Mutual Information (MI) was used to estimate the codependence of the processes in unsaturated zone and the main hydrological events. The model successfully (R2 0.72 – 0.94) reproduced measured lysimeters outflows. The outflows from lysimeters were connected to precipitation patterns, transpiration intensity, and soil moisture content influenced by the shallow water table. Comparable MI values obtained for precipitation, GW, and river level suggest a concurrent role of these parameters in the unsaturated flow dynamics. The relationship between upward flux/water storage change into the domain, and transpiration/growth stages, suggests a strong connection between the water fluxes and the root water uptake. Results confirm the importance of GW for the agricultural production due to the major influence on upper soil layer moisture.

Laboratory Study on the Effect of Water-Cement Ratio on Strength Characteristics of Jet Grouting Columns

Jet grouting is one of the most widely applied soil improvement techniques. It is suitable for most geotechnical problems, including improving bearing capacity, decreasing settlement, forming seals, and stabilizing slopes. One of the difficulties faced by designers is determining the strength and geometry of elements created using this method. Jet grouted soil-cement columns in soil are a complicated issue because they are dependent on a number of parameters such as soil type, grout and water flow rate, rotation and lifting speed of monitor, nozzle jetting force, and water to cement ratio of slurry. This paper discusses the effect of the water-cement ratio on the physical and mechanical characteristics of soilcrete. In the laboratory, sandy soil mixed with cement grout with water-cement ratio varies from (0.7:1 to 1.4:1). To evaluate the characteristics of soilcrete, 96 specimens were prepared in the laboratory and tested at different curing times. The results indicate that the Uniaxial Compressive Strength (UCS) of soilcrete decreases with increasing the (W/C) ratio of the grout, where the soilcrete strength of W/C ratio of 0.7 is higher about 237% of W/C ratio of 1.4 at 28-day; the evolution of the (UCS) is proportional to the logarithm of the curing time; the ratio between the modulus of elasticity (Etg50) to the maximum UCS varies from 113 to 175; when the water-cement ratio increases, the dry density of soilcrete decreases, as a result, the (USC) of soilcrete decreases.

Estimating soil water suction from texture, bulk density and electrical resistivity

Information on soil water suction (h) is essential to study water flow and solute transport in soils, and to understand engineering behaviors of unsaturated soils. Due to limited availability of field methods that can accurately measure h, numerous studies have been performed to estimate h from more readily available soil properties. In this study, a new relationship between h and soil electrical resistivity (ρ), developed from the Gardner water retention model and Archie’s second law, was used to estimate h values lower than the air entry value and a formation factor (expressed on log-scale) less than 1. The two model parameters (A and B), which are functions of soil texture and bulk density, were obtained by fitting the model to ρ and h data measured on soil columns of eight textures and various bulk densities. Laboratory and field evaluations with independent h and ρ data showed that the model estimated h values agreed well with the measured values, with root mean square errors less than 0.85 kPa. The model provides a new opportunity to evaluate in situ h dynamics and study coupled transport of water and solutes in the field.