Soil Hydraulic Parameters Research Articles

Liming and co‐application of water treatment residuals with biosolids for conditioning sandy soils

AbstractApplication of water treatment residuals (WTR) and biosolids (BS) might ameliorate fragile soils. However, studies integrating impacts of waste preparation methods such as liming and grinding associated with co‐application approaches for soil conditioning are lacking. The present study aimed to evaluate the feasibility of agricultural use of WTR as well as their co‐application with BS to ameliorate a sandy soil through assessing impacts on selected soil quality indicators and on nutrient and potentially toxic element concentration in plant tissue in addition to the biomass yield of annual crops. The following treatments were evaluated: non‐amended soil (control); drying plus grinding and liming WTR; WTR co‐application with BS at 3:1 ratio; and a soil amendment commercially available in Brazil. All treatments were soil incorporated in the 0.0–0.2 m layer at 30 Mg ha−1 dose (dry mass). Selected soil physical, hydraulic, and chemical parameters were determined. Furthermore, nutrients and potentially toxic elements concentration in plant tissue as well as the agronomic performance of maize and ryegrass were measured. The co‐application of WTR and BS increased the soil content of P, Zn, and Cu in the 0.0–0.1 m layer. The concentration of these nutrients also was greater in ryegrass tissue and promoted the biomass yield in 51%. WTR did not increase contaminants and did not decrease the P content in soil and in plant tissue, independently of drying plus grinding and liming. Considering the conditions investigated in our study, WTR/BS co‐application was environmentally safe and effective in ameliorating soil quality.

Examining subsurface response to an extreme precipitation event using HYDRUS‐1D

AbstractNorth‐central Colorado experienced an extreme precipitation event (EPE) in September 2013, during which the equivalent of 80% of the region's annual average precipitation fell in a few days. Widespread flooding occurred above ground, but the short‐ and long‐term subsurface response remains unclear. The objective of the study is to better understand the dynamic subsurface response, namely how the water table and soil water storage responded to a large amount of infiltration in a short period of time and how the hydrologic properties of the subsurface influence the response. Better understanding of subsurface response to EPEs is expected to increase with the advent of more intense and frequent EPEs in the coming decades. A one‐dimensional subsurface flow model using HYDRUS‐1D, was built to simulate and examine infiltration of an EPE at a site in the Boulder Creek Watershed, Colorado. Model calibration was conducted with local field data to fit site observations over a 6‐yr period. A rapid water table depth response in field observations was observed, with the modeled subsurface storing water for 18 mo acting as a hydro‐buffer during recovery. To examine influence on model results, a sensitivity study of soil hydraulic parameters was conducted. The sensitivity study found that changes in n, an empirical parameter related to pore‐size distribution, most significantly affects water table depth. The implications are that one‐dimensional models may provide useful estimates of water table fluctuations and subsurface hydro‐buffer capacities in response to EPEs, which could be of use to regions preparing for EPE effect on water resources.

Identification of varied soil hydraulic properties in a seasonal tropical rainforest

In forest areas, seasonal ecosystem changes may affect soil hydraulic properties and ultimately alter the pattern of soil moisture dynamics. A National Ecological Station in a tropical rainforest of Xishuangbanna located in southern China collected in-situ measurements of meteorological forcing, soil moisture content, litterfall, leaf area index (LAI), and water and carbon flux from 2003 to 2008, which provided an ideal dataset for a detailed investigation on how the soil hydraulic properties would vary in response to seasonal ecosystem changes. Methodologically, the Marquardt Levenberg optimization algorithm was integrated in an unsaturated flow model to inversely estimate the soil hydraulic parameters based on unvaried, seasonally varied, and monthly varied parameterization strategies, respectively. The results indicated that the simulated soil moisture using seasonally varied and monthly varied parameters were more accurate than that with unvaried parameters. Moreover, the statistical analysis of monthly varied soil hydraulic parameters suggested that the temporal variations in soil hydraulic properties were tightly related to the seasonal ecosystem changes in terms of LAI, litterfall, and heterotrophic respiration. In deciduous periods, a significant reduction of LAI was accompanied with abundant litterfall that replenished organic matter to the topsoil. In contrast, during the hot rainy periods, the high heterotrophic respiration rate indicated that the soil organic matter underwent intensive decomposition under the condition of high air temperature and wet soil moisture– leading to strong seasonal cycles in soil hydraulic properties. The seasonal ecosystem change led to a significant increase in saturated hydraulic conductivity Ks from less than 100 cm/day in hot rainy season to over 150 cm/day in cool dry season. Moreover, the inversely estimated soil hydraulic parameters of saturated water content θs and field capacity θf at the topsoil layer were also featured with clear seasonal cycles (ranging from 0.32 to 0.42 and 0.23 to 0.27 respectively). In comparison with unvaried soil hydraulic parameter, inclusion of varied soil hydraulic properties provided more accurate simulations of soil moisture dynamics, which in turn, benefited the hydro-ecological modeling in vegetated areas.

MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models

Abstract. Distributed environmental models such as land surface models (LSMs) require model parameters in each spatial modeling unit (e.g., grid cell), thereby leading to a high-dimensional parameter space. One approach to decrease the dimensionality of the parameter space in these models is to use regularization techniques. One such highly efficient technique is the multiscale parameter regionalization (MPR) framework that translates high-resolution predictor variables (e.g., soil textural properties) into model parameters (e.g., porosity) via transfer functions (TFs) and upscaling operators that are suitable for every modeled process. This framework yields seamless model parameters at multiple scales and locations in an effective manner. However, integration of MPR into existing modeling workflows has been hindered thus far by hard-coded configurations and non-modular software designs. For these reasons, we redesigned MPR as a model-agnostic, stand-alone tool. It is a useful software for creating graphs of NetCDF variables, wherein each node is a variable and the links consist of TFs and/or upscaling operators. In this study, we present and verify our tool against a previous version, which was implemented in the mesoscale hydrologic model (mHM; https://www.ufz.de/mhm, last access: 16 January 2022). By using this tool for the generation of continental-scale soil hydraulic parameters applicable to different models (Noah-MP and HTESSEL), we showcase its general functionality and flexibility. Further, using model parameters estimated by the MPR tool leads to significant changes in long-term estimates of evapotranspiration, as compared to their default parameterizations. For example, a change of up to 25 % in long-term evapotranspiration flux is observed in Noah-MP and HTESSEL in the Mississippi River basin. We postulate that use of the stand-alone MPR tool will considerably increase the transparency and reproducibility of the parameter estimation process in distributed (environmental) models. It will also allow a rigorous uncertainty estimation related to the errors of the predictors (e.g., soil texture fields), transfer function and its parameters, and remapping (or upscaling) algorithms.

Exploring the potential role of environmental and multi-source satellite data in crop yield prediction across Northeast China

Developing an accurate crop yield predicting system at a large scale is of paramount importance for agricultural resource management and global food security. Earth observation provides a unique source of information to monitor crops from a diversity of spectral ranges. However, the integrated use of these data and their values in crop yield prediction is still understudied. Here we proposed the combination of environmental data (climate, soil, geography, and topography) with multiple satellite data (optical-based vegetation indices, solar-induced fluorescence (SIF), land surface temperature (LST), and microwave vegetation optical depth (VOD)) into the framework to estimate crop yield for maize, rice, and soybean in northeast China, and their unique value and relative influence on yield prediction was assessed. Two linear regression methods, three machine learning (ML) methods, and one ML ensemble model were adopted to build yield prediction models. Results showed that the individual ML methods outperformed the linear regression methods, the ML ensemble model further improved the single ML models. Moreover, models with more inputs achieved better performance, the combination of satellite data with environmental data, which explained 72%, 69%, and 57% of maize, rice, and soybean yield variability, respectively, demonstrated higher yield prediction performance than individual inputs. While satellite data contributed to crop yield prediction mainly at the early-peak of the growing season, climate data offered extra information mainly at the peak-late season. We also found that the combined use of EVI, LST and SIF has improved the model accuracy compared to the benchmark EVI model. However, the optical-based vegetation indices shared similar information and did not provide much extra information beyond EVI. The within-season yield forecasting showed that crop yields can be satisfactorily forecasted at two to three months prior to harvest. Geography, topography, VOD, EVI, soil hydraulic and nutrient parameters are more important for crop yield prediction.

Approximate analytical solutions for one-dimensional soil water movement equation with arbitrary initial conditions

Simple analytical solutions of one-dimensional horizontal and vertical soil water movement are of great importance for the soil hydraulic parameters estimation and precision irrigation. We present the approximate analytical solutions for the problem of horizontal absorption and vertical infiltration in soil under arbitrary initial conditions and constant boundary conditions based on the principle of least action and the variational principle. The algebraic functions of soil water content (SWC) profile, cumulative infiltration, infiltration rate and infiltration time about the wetting front distance/depth (WFD) and the parameters of Brooks-Corey model are obtained. Compared with the numerical results simulated by HYDRUS-1D, the algebraic results calculated by approximate analytical solutions have high precision to predict the horizontal and vertical soil water infiltration based on the known WFD. Contrary to the linear relationship in horizontal absorption with uniform initial conditions, the relationships between cumulative infiltration and WFD, infiltration rate and reciprocal of WFD, square of WFD and infiltration time are nonlinear for the arbitrary heterogeneous initial conditions. However, the initial conditions have little effect on the relationship between infiltration rate and WFD when the initial SWCs are lower than 0.6 θs. Based on the nonlinear relationships of infiltration rate and WFD in vertical infiltration, the WFD and time of the stable infiltration are obtained.

Soil Hydraulic and Strength Parameters as influenced by various Mechanized Rainwater Conservation Practices in Rainfed Groundnut Crop

In India, rain fed agriculture constitutes to 60% of the net cultivated area and accounts for nearly 44% of the National food basket. 54.6% of the total workforce is engaged in agricultural and allied sector activities (Census, 2011) and accounts for 17.8% of the country’s Gross Value Added (GVA) for the year 2019-20. Rain Water Harvesting (RWH) is a low-cost, easy-to-use, environmentally friendly way to recover a large part of this lost water. In India, the rainfed agriculture constitutes 60% of the total net sown area and Andhra Pradesh constitutes nearly 57% net sown area under rainfed agriculture. Groundnut (Arachis hypogea) occupies nearly 28.3% of the cultivated area under oil seed crops in India and the area under groundnut in the Country is 5.40 Mha with a total production of 6.57 Million Tonnes (MT) and with the productivity of 910 kg ha-1. The area of groundnut crop in Andhra Pradesh is 7.47 Lakh ha whereas Ananthapuramu District occupied 6.71 Lakh ha. The study was carried out under different surface and subsurface rainwater conservation practices with the objective to study the soil hydraulic and strength parameters viz., soil moisture content in frequent intervals at 10 cm, 20 cm, 30 cm depth and bulk density, particle density and porosity at 20 cm depth. From the study, it was observed that, highest soil moisture content was observed in subsoiling at 1 m distance + broad bed and furrow system treatment at three different soil sampling depths of 10 cm, 20 cm and 30 cm as 25.40%, 31.20% and 27.50%, respectively at 40 Days After Sowing (DAS) and 29.74%, 34.71% and 22.38%, respectively at 80 Days After Sowing (DAS). The lowest bulk density and highest soil porosity were observed as 1.52 g cm-3 and 32.7% in subsoiling at 1 m distance + broad bed and furrow treatment than other practices.

Using Inverse Modeling by HYDRUS-1D to Predict Some Soil Hydraulic Parameters from Soil Water Evaporation

The objective of this research was to assess the use of unsaturated water flow in terms of soil water evaporation, which was determined by evaluating some soil hydraulic parameters in different soil textures. The results show that the predicted values of these parameters, which were obtained through inverse modeling with the HYDRUS-1D software and depend on the change of the volumetric water content, exhibited a significant agreement with the measured values from laboratory or field simulation data for soil water evaporation at 5. 10. 20. and 45 days of measurement. At the same time, inverse simulation was conducted on soil hydraulic parameters obtained from a 5-day laboratory soil evaporation period to predict field infiltration values and water retention curve, which showed a significant agreement with measured values for all soil textures.

Sensitivity analysis of soil parameters in the Agricultural Production Systems sIMulator (APSIM)

Context The performance of process-based agroecosystem simulation models is highly sensitive to the numerous input parameters, many associated with high variability and uncertainty. Aims Our aims were to: (1) test the accuracy of the Agricultural Production Systems sIMulator (APSIM) model regarding the prediction of soil water storage and movement in a pasture system with a free draining pumice soil based on site-specific soil hydraulic properties; (2) identify sensitive soil hydraulic properties on model outputs; and (3) identify the influence of uncertainty in the description of soil properties on various model outputs. Methods We carried out a sensitivity analysis (SA) to identify sensitive soil hydraulic parameters. We set up APSIM to simulate a pasture system on a free-draining pumice soil in New Zealand. The model was first established with site-specific soil hydraulic properties and outputs were compared with measured soil moisture status and drainage. Next, the model’s sensitivity to the soil hydraulic parameters was assessed for various outputs linked to production and environmental outcomes. Key results Varying the various hydraulic parameters affected soil moisture status, but it had generally little effect on drainage, N leaching, and pasture production in this system. Conclusions The results suggest that for well-drained soils in a high precipitation zone with no water limitation, the model has low sensitivity to soil hydraulic parameters. Further analysis is required for different soils and for drier conditions. Implications For well-drained soils and under non-limiting water conditions the use of general data from databases, rather than site specific measurement of hydraulic properties is justified.

A Variational Framework for Coupled Estimation of Evapotranspiration and Recharge Fluxes by Assimilating Land Surface Soil Moisture and Temperature

The evapotranspiration and recharge are the key fluxes that link the land's water and energy cycles. These fluxes have major impacts on agriculture, water supply system, water resources planning, climate, etc. Accurate mapping of these fluxes is limited due to lack of in-situ observation sites and errors in estimation from numerical models. The dynamics of land surface state observations, specifically land surface soil moisture (SM) and temperature (LST), have implicit information on the partitioning of evapotranspiration and recharge fluxes, which provides an opportunity for global mapping of these fluxes across a range of spatial and temporal scales. In this study, a variational data assimilation (VDA) framework is developed for coupled estimation of evapotranspiration and recharge fluxes by assimilating LST and SM observations into a coupled water and energy balance model. We modified LIDA framework (Abdolghafoorian and Farhadi, 2019) to calculate the effective soil hydraulic parameters required for estimating the recharge flux in addition to evaporative flux parameters. Two numerical experiments are conducted using synthetic dataset generated by Hydrus 1-D model to test the accuracy and feasibility of the proposed estimation framework. Second-order information is used to estimate the uncertainty of the estimated parameters and fluxes and guide toward a well-posed optimization problem. Results demonstrate the success of the VDA framework in estimating evaporative and recharge fluxes from implicit information contained in SM and LST data and feasibility test results show promise in extending the framework to large scale using remotely sensed observations.

Rainfall-Induced Hydraulic Properties for Unsaturated Soil in Klang Valley

Klang Valley area is one of the most landslide-prone areas in Malaysia, especially at Hulu Kelang, Kuala Lumpur. The area has been frequently hit by landslide since 1990s. Soil instability is agreed by researchers occurred due to high precipitation and long duration of rainfall which cause property damage and leading to injury and fatality. Slope failure is also triggered by the antecedent rainfall leads to infiltration of rainwater into soil. Therefore, study of rainwater infiltration is vital to relates soil – water interaction and soil behaviour for varies of rainfall intensities and duration for unsaturated soil. The objective of this paper is to determine and compare soil water characteristic curve (SWCC) which is one of the soil hydraulic parameters for Klang Valley area. Samples were collected to determine the soil hydraulic properties at Hulu Kelang area, Universiti Kebangsaan Malaysia (UKM) and Universiti Pertahanan Nasional Malaysia (UPNM) campuses. SWCC was obtained by pressure plate extractor apparatus experiment and the analysis was performed using Van Genuchten equation. Result of parameters obtained shows significant differences of soil at Hulu Kelang area compared to soils at UKM and UPNM campuses. This research is relevant to supports national slope master plan 2009-2023.

ESTIMATION OF SATURATED HYDRAULIC CONDUCTIVITY FOR DIFFERENT SOIL TYPES IN JIMMA ZONE, ETHIOPIA

A saturated hydraulic conductivity (Ksat) is the utmost vital soil hydraulic parameter for flow with in the soil. The knowledge of it is vigorous for water resources applications. Numerous methods & models (field, laboratory and empirical formulae) are available for determination of it. However, all of them have their applications and limitations. But, most investigators prefer the usage of empirical formulae to direct measurements of Ksat (field / lab) as direct measurements are very challenging (sometimes impractical), necessitating testing, quantification, and decision; making it extremely difficult to use in hydrologic modeling. Thus, it is vital to effectively asses the illustrative Ksat values matching the cost and its reliability. This study therefore presents the laboratory estimation of the Ksat for different soil textures in Jimma zone (nearby Jimma, Serbo, GilgelGibe and Asendabo towns) in Ethiopia, by both constant head and falling head methods, which are the simplest and cost effective ones. In these procedures, we determined the Ksat values of the soil in the study region. The results indicated that its average values are (1) in between 0.00124 and 0.00173cm/s for sandy-loam soil, and (2) 0.000124cm/s for clay soil. The porosity of soil samples were also calculated and found out to be in the range of 41.25 % and 44.24 % (the average being 43.04%) for sandyloam soil and 43.54% for clay soil. We then compared the results with the corresponding values in the literature, and finally we concluded that the Ksat and porosity values obtained for the study region were found to be in a good agreement with the corresponding literature values.

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.

Prediction of the van Genuchten model soil hydraulic parameters for the 5-m soil profile in China’s Loess Plateau

Soil hydraulic parameters (SHPs) represent a crucial input for modelling of water flow, biogeochemical processes, and plant growth. This modelling depends on an accurate description of the water balance in a critical soil zone. To this end, pedotransfer functions (PTFs) are required to translate basic soil data into SHPs as it is challenging to measure them. This challenge is peculiarly acute for deep soil layers in thick loess deposits, such as in the China’s Loess Plateau Region (CLPR). In this study, we analysed which factors are strongly correlated with SHPs, and developed PTFs for the SHPs. To this end, undisturbed and disturbed soil samples were collected up to 8 m depth at seven sampling sites in the CLPR to measure the soil water retention curve, saturated hydraulic conductivity (Ks), and associated soil and environmental factors. Furthermore, soil core samples in the 5 m soil profile were collected at 243 sites, and the corresponding environmental factors were calculated to estimate the spatial distribution of SHPs across the CLPR using the established PTFs. Redundancy analysis of the collected data in the 0–8-m soil profile revealed that soil texture, soil depth, mean annual precipitation, slope gradient, slope aspect, and elevation were strongly correlated with SHPs. The most correlated variables were used to develop PTFs for SHPs by using stepwise multiple linear regression. The accuracy of the established regional PTFs was significantly higher compared to state-of-the-art in this domain. The spatial distribution of SHPs in the CLPR study area exhibited significant spatial clustering. Generally, SHPs transitioned from the southeast to the northwest, with significant differences between the south and north. Our results provide empirical basis for further quantification of the response of soil hydrological processes to vegetation restoration and land-use change not only in the CLPR, but also in other similar regions.

Estimating Soil Hydraulic Parameters of Different Textured Soils in Semiarid Duhok Conditions - Iraqi-Kurdistan Region by using RETC Program

Estimating Soil Hydraulic Parameters of Different Textured Soils in Semiarid Duhok Conditions - Iraqi-Kurdistan Region by using RETC Program

Estimating Soil Hydraulic Parameters of Different Textured Soils in Semiarid Duhok Conditions - Iraqi-Kurdistan Region by using RETC Program

RETC is a computer program that can be used to estimate soil hydraulic functions by easily determining soil properties. Using van Genuchten model in the RETC program gave high accuracy for estimating the hydraulic functions e.g., θ (h), k (θ) and D (h), also the mentioned program is considered a good tool for potential optimization of water management especially though calculating irrigation water after consuming 60% of the available water in root zone restoring technique.
 In the current study surface, soil samples (0 – 30 cm) from eight locations with a wide range in texture were collected RETC code is used to refine the water retention curve through minimizing the residual error according to van Genuchten – Mualem approach (1980). the obtained results indicated that the sum square SSQ (residual error) values becomes smaller after refining for eight studied soils which were (Avkendal, Berderash, Chemrash, Kanisark, Keperto, Khanik, Qerwola and Terbsbia), which their SSQ values before RETC refining were ( 0.0470264, 0.0680298, 0.0240080, 0.0190478, 0.0396200, 0.0166960, 0.094400 and 0.0199100) whereas these values decrease as fallowing (0.000333400, 0.000942618, 0.0000997008, 0.000167315, 0.002448800, 0.000243300, 0.00080000, and 0.000099917 ) with ha high coefficient of determination (R2) greater than (0.964) and the maximum refining was (0.000099917) at Chemrash silty clay loam soil with 0.9986 (R2), whereas the minimum value was(0.002448800) at Keperto loamy soil with 0.9720(R2) and this means higher precision in fitting using the retention model.
 RETC code was used to analyze soil water retention curve and hydraulic conductivity functions which are the key parameters in any quantitative description of water flow into the unsaturated zone of soils, van Genuchten et. al. (1991)

Biocrust effects on soil infiltrability in the Mu Us Desert: Soil hydraulic properties analysis and modeling

Abstract The presence of biocrusts changes water infiltration in the Mu Us Desert. Knowledge of the hydraulic properties of biocrusts and parameterization of soil hydraulic properties are important to improve simulation of infiltration and soil water dynamics in vegetation-soil-water models. In this study, four treatments, including bare land with sporadic cyanobacterial biocrusts (BL), lichen-dominated biocrusts (LB), early-successional moss biocrusts (EMB), and late-successional moss biocrusts (LMB), were established to evaluate the effects of biocrust development on soil water infiltration in the Mu Us Desert, northwest of China. Moreover, a combined Wooding inverse approach was used for the estimation of soil hydraulic parameters. The results showed that infiltration rate followed the pattern BL > LB > EMB > LMB. Moreover, the LB, EMB, and LMB treatments had significantly lower infiltration rates than the BL treatment. The saturated soil moisture (θs ) and shape parameter (α VG) for the EMB and LMB treatments were higher than that for the BL and LB treatments, although the difference among four treatments was insignificant. Water retention increased with biocrust development at high-pressure heads, whereas the opposite was observed at low-pressure heads. The development of biocrusts influences van Genuchten parameters, subsequently affects the water retention curve, and thereby alters available water in the biocrust layer. The findings regarding the parameterization of soil hydraulic properties have important implications for the simulation of eco-hydrological processes in dryland ecosystems.

Hierarchical prediction of soil water content time series

Quantifying the spatial and temporal dynamics of soil moisture is an important subject in vadose zone hydrology. A 1282-day field study was conducted to provide a hierarchy of data to assess neural network simulations of field soil water content time series θ(t). Volumetric water content was determined, typically once a week, by neutron thermalization at 20-, 40-, 60-, 80- and 100-cm depths. Soil samples were taken at 60 locations between 14- and 114-cm depths to determine soil properties, water retention, and saturated hydraulic conductivity. Prediction of hydraulic parameters from basic and extended soil properties yielded low correlation coefficients. Water content could be predicted reasonably with neural networks from soil properties or hydraulic parameters (0.880 < R < 0.942). Prediction of θ(t) based solely on rainfall data was not accurate. Independent networks could accurately simulate water content from one observed θ(t) based on the Nash-Sutcliffe Model Efficiency and Percent Bias. Once a network is trained for a particular depth, accurate predictions can be made beyond the training period using observations at just one location.

Development of the Green-Ampt Infiltration Rate Model and Relationship of the GA Model Parameters with Soil Hydraulic Parameters

In the Green-Ampt model, the infiltration rate is indirectly related to time via the intermediate term of cumulative infiltration depth. In the present study, the direct theoretical relationship between the infiltration rate of the GA infiltration model with time is derived and elaborated. A new laboratory method for separate measurement of the GA model parameters is developed and tested via the constant-head infiltration tests on two sandy soil columns considering different values of initial soil water content. Hysteretic soil water characteristic (SWC) curves of studied soils are also measured. Results indicate that the GA model parameters are constant values and independent from the initial soil water content. Hydraulic conductivity K, wetting front matric head Ψf, and water content of wetted zone θwz of GA model are separately estimated from proposed method and are found to be respectively equal to saturated hydraulic conductivity Ks, water-entry value hw−e, and saturated water content of the wetting SWC curve θsw. By setting K=Ks, Ψf=hw−e, and θwz=θsw, the results of the GA model matched reasonably well with the numerical solution of Richards’ equation using HYDRUS-1D and measured data.

Water treatment residuals for ameliorating sandy soils: Implications in environmental, soil and plant growth parameters

Water treatment residuals (WTR) application may improve the quality of sandy soils; however, nutrient deficiency to plants and potentially toxic elements (PTEs) may be limiting. In contrast, adjusting the WTR pH, soil pH and WTR application rate might prevent adverse effects. This study aimed to evaluate the environmental safety and agronomic effectiveness of limed WTR for application in sandy soils. The tested treatments were increasing rates (0, 15, 30 and 60 Mg ha−1 of dry mass) of ground, dried and limed WTR in sandy soil under field conditions. Soil samples with disturbed and undisturbed structure were collected to determine selected soil physical, hydraulic and chemical parameters related to fertility, as well as the soil concentration of PTEs. Nutrients and PTEs content in plant tissue and the agronomic performance of maize and ryegrass were also evaluated. WTR were beneficial as they increased the content of fine and reactive particles (clay and silt). In general, WTR rates did not spoil soil chemical parameters related to soil fertility; did not increase aluminium saturation; and did not change soil PTE contents which were below the limits indicated by environmental legislations. The tested WTR rates did not cause negative effects on the agronomic variables of maize and ryegrass plants. Thus, waste application rates up to 30 Mg ha−1 are recommended. Liming WTR and soil makes this material safe and suitable for application in sandy and acidic agricultural soils.