Saturated Hydraulic Conductivity Research Articles

Effects of Conversion of Rubber to Oil Palm Plantations on Soil Properties and Hydrological Dynamics in the Low Country Wet Zone of Sri Lanka

A study was conducted to investigate the impacts of converting rubber plantations into oil palm plantations on soil properties and soil hydrology. Soil organic carbon (SOC), bulk density (BD), aggregate stability (AS), saturated hydraulic conductivity (Ks), soil water retention, texture, thermal properties, and pH were determined using soil samples collected from different depths of a twelve-year-old oil palm and rubber cultivated fields located in low country wet zone of Sri Lanka. In each field, volumetric water content (VWC) of soil was continuously measured at four soil depths (0-25, 25-50, 50-75, and 75-100 cm) over a seven-month period. While the study revealed a 40% lower SOC in 0-25 cm soil layer of the oil palm field compared to the rubber field, no significant changes were observed in BD, porosity, pore size distribution, AS, and Ks for the two fields. However, the volumetric heat capacity of rubber grown soil was significantly higher than that of the oil palm grown soil. Oil palm utilized the most water from 25-75 cm soil layer; whereas, rubber extracted more water from deeper soil layers (75-100 cm). Soil water depletion in oil palm field was faster during dry periods than in rubber fields highlighting the need to examine the soil water extraction patterns of oil palm during extended dry spells in future studies. Overall, the conversion of rubber into oil palm plantations showed no significant impact on most of the soil properties and soil hydrology after twelve years of conversion.

Determining peat's vertical hydraulic diffusivity and hydraulic conductivity from naturally occurring hydraulic pressure fluctuations measured at various depths

AbstractThis study presents a method that could be used to assess the in‐situ saturated vertical hydraulic conductivity of deeper and more decomposed peat layers. Deeper peat layers may exhibit very low permeability comparable to clayey sediments, where measurements and sediment sample collection are very difficult. More traditional measurement methods, such as slug‐tests and permeameter tests, have proven difficult to carry out in these conditions, necessitating an alternative method. For surpassing these possible constraints, this paper introduces a field method to quantify vertical hydraulic diffusivity, capitalizing on naturally occurring hydraulic pressure fluctuations measured with buried pressure sensors. The determined diffusivity values are used to calculate vertical hydraulic conductivity of peat using separately measured compressibility and specific storage values. Our research demonstrates the feasibility of using this method to evaluate vertical hydraulic diffusivity in lower peat layers. Calculated diffusivity values, combined with peat compressibility measurements, yield reasonable estimates of vertical hydraulic conductivity for dense fen peat comparable with more widely used in‐situ and laboratory methods. It also shows potential for vertical hydraulic characteristics parametrization in the upper less decomposed and compacted peat layers; however, further research is needed to understand the method's limitations in such conditions. Our approach provides a potential method for measuring in‐situ vertical hydraulic properties of less accessible peat layers, often overlooked, while also providing a way to surpass the scale‐dependency constraints inherent in peatlands' heterogeneous structure. Such information is necessary when studying the hydraulic interactions between groundwater aquifers and peatlands.

Soil freeze/thaw dynamics strongly influences runoff regime in a Tibetan permafrost watershed: Insights from a process-based model

The Tibetan Plateau (TP) is a region rich in extensive frozen ground and the source of many major Asian rivers. However, how soil freeze/thaw (F/T) dynamics influence runoff production at the catchment scale in the TP is poorly understood. This study employs a process-based permafrost hydrology model with a new soil parameterization to investigate soil F/T dynamics and their impact on runoff in a TP permafrost watershed, i.e., the source region of Yangtze River (SRYR). The revised model separates soil evaporation and plant transpiration, and accounts for the influence of soil gravel and organic carbon content, as well as variation in saturated hydraulic conductivity along the soil profile. Validation results demonstrate that the revised model accurately simulates daily soil temperature (mean RMSE of 1.3 °C), soil moisture (mean ubRMSE of 0.05 cm3 cm−3), and runoff discharge (NSE = 0.82). The results reveal different altitudinal patterns of warming trend between permafrost and seasonally frozen ground (SFG). Warming rates in SFG area increase monotonously with elevation, while a turning point is observed in permafrost region around 4800 m. With active layer deepening, deep-soil water content increases but primarily replenishes soil water storage rather than directly contributing to runoff recharge, while rootzone and the middle part of the active layer become drier. Soil F/T cycles in the permafrost region exert stronger influences on runoff process compared to SFG. Delayed soil thaw onset generally results in higher spring runoff coefficient, while delayed soil freeze onset is related to slower runoff recession. The freezing zero-curtain period is likely to impact the continuity of runoff recession processes by affecting the connectivity of groundwater flow channels. These findings uncover the regulatory mechanisms of soil F/T dynamics on runoff production and river discharge characteristics, providing a fundamental basis for predicting permafrost hydrology responses to future climate change in the TP.

Estimating the saturated hydraulic conductivity of the vadose zone with an automatic infiltration data logger for the BEST algorithm

Estimating the saturated hydraulic conductivity of the vadose zone with an automatic infiltration data logger for the BEST algorithm

Conservation tillage: a way to improve yield and soil properties and decrease global warming potential in spring wheat agroecosystems.

Climate change is one of the main challenges, and it poses a tough challenge to the agriculture industry globally. Additionally, greenhouse gas (GHG) emissions are the main contributor to climate change; however, croplands are a prominent source of GHG emissions. Yet this complex challenge can be mitigated through climate-smart agricultural practices. Conservation tillage is commonly known to preserve soil and mitigate environmental change by reducing GHG emissions. Nonetheless, there is still a paucity of information on the influences of conservation tillage on wheat yield, soil properties, and GHG flux, particularly in the semi-arid Dingxi belt. Hence, in order to fill this gap, different tillage systems, namely conventional tillage (CT) control, straw incorporation with conventional tillage (CTS), no-tillage (NT), and stubble return with no-tillage (NTS), were laid at Dingxi, Gansu province of China, under a randomized complete block design with three replications to examine their impacts on yield, soil properties, and GHG fluxes. Results depicted that different conservative tillage systems (CTS, NTS, and NT) significantly (p < 0.05) increased the plant height, number of spikes per plant, seed number per meter square, root yield, aboveground biomass yield, thousand-grain weight, grain yield, and dry matter yield compared with CT. Moreover, these conservation tillage systems notably improved the soil properties (soil gravimetric water content, water-filled pore space, water storage, porosity, aggregates, saturated hydraulic conductivity, organic carbon, light fraction organic carbon, carbon storage, microbial biomass carbon, total nitrogen, available nitrogen storage, microbial biomass nitrogen, total phosphorous, available phosphorous, total potassium, available potassium, microbial counts, urease, alkaline phosphatase, invertase, cellulase, and catalase) while decreasing the soil temperature and bulk density over CT. However, CTS, NTS, and NT had non-significant effects on ECe, pH, and stoichiometric properties (C:N ratio, C:P ratio, and N:P ratio). Additionally, conservation-based tillage regimes NTS, NT, and CTS significantly (p < 0.05) reduced the emission and net global warming potential of greenhouse gases (carbon dioxide, methane, and nitrous oxide) by 23.44, 19.57, and 16.54%, respectively, and decreased the greenhouse gas intensity by 23.20, 29.96, and 18.72%, respectively, over CT. We conclude that NTS is the best approach to increasing yield, soil and water conservation, resilience, and mitigation of agroecosystem capacity.

A practical equation for predicting saturated hydraulic conductivity of fine-grained soils

The saturated hydraulic conductivity (ks) of soils plays a crucial role in various agricultural and environmental engineering applications, particularly in relation to pollution prevention and water migration. Firstly, the traditional Kozeny-Carman (KC) equation, which are commonly used to estimate ks, has limitations in predicting ks for different types of fine-grained soils based on the analyses of permeability test data in the literature. Secondly, to tackle this issue, a modified KC equation was proposed by introducing an expression for the shape parameter and establishing a relationship between the tortuosity equation and the plastic limit. Additionally, the validation of the proposed equation was conducted using ks values of 25 fine-grained soils obtained from other sources. Finally, a comparison was made with the four commonly used ks models to evaluate its performance. The results indicate that the proposed equation demonstrates a relatively high coefficient of determination and a low root mean square error. This suggests that the proposed equation has the potential to accurately assess ks for fine-grained soils. The predictions for ks using the modified equation showed good agreement with the experimental data mentioned in the literature.

High-Resolution Estimation of Soil Saturated Hydraulic Conductivity via Upscaling and Karhunen–Loève Expansion within DREAM(ZS)

Quantification of the soil hydraulic conductivity is key to the study of water flow and solute transport in unsaturated soils. Rapid advances in measurement technology have provided a large number of observations at different scales, offering unprecedented opportunities and challenges for the estimation of hydraulic parameters. This paper proposes an inverse estimation method for downscaling of observations on coarse scales to estimate hydraulic parameters on high-resolution scales. Due to the significant spatial heterogeneity, the inversion faces the problems of dynamics-based integration of data at different scales, model uncertainty due to hundreds and thousands of parameters, and computational consumption due to the large number of forward simulations. To overcome these problems, this paper uses an efficient Bayesian optimization DREAM(ZS) as an inverse framework, and incorporates an analytical upscaling method and Karhunen–Loève (KL) expansion to infer finer-scale saturated hydraulic conductivity distribution conditioned on coarse-scale measurements. The efficient upscaling method is used to link measurements and hydraulic parameters at different scales, and Karhunen–Loève (KL) expansion is incorporated to greatly reduce the dimension of the parameter to be estimated. To further improve the efficiency of the inversion, a locally one-dimensional (LOD) algorithm is used to solve the multidimensional water flow model at coarse scales. The proposed inverse model is applied in a series of numerical experiments to demonstrate its applicability and effectiveness under different flow boundary conditions, different levels of ratio between coarse- and fine-scale grids, different densities of observation points, and different degrees of statistic heterogeneity of soil mediums.

Morphological and structural characteristics of preferential flow and its influencing factors on colluvial deposits of Benggang

AbstractPreferential flow plays a vital role in infiltration processes in structured soil. However, knowledge of preferential flow in colluvial deposits of Benggang remains limited. In this study, three typical colluvial deposits with different formation times were selected. The formation times of colluvial deposits A, B and C increased in sequence. Water infiltration in colluvial soil was visualized through Brilliant Blue dye experiments (a total of 90 photos from the dyed soil profiles). The dye morphological characteristics of preferential flow were analysed, and the influencing factors were explored. The dye morphological parameters confirmed the occurrence of preferential flow in the colluvial deposits. The dye coverage of colluvial deposit A was the greatest (61.12%), followed by colluvial deposits B (50.41%) and C (46.81%). The matrix flow depth, preferential flow fraction and length index of colluvial deposits A and B were greater than those of colluvial deposit C. Preferential flow was more notable in colluvial deposits A and B than in colluvial deposit C. The migration process of dyed water varied spatially. There were more preferential flow paths at a 10 cm horizontal width. In addition to the bulk density and saturated hydraulic conductivity, the soil particle composition, especially the gravel content (r = 0.740), was closely related to the observed dye coverage. According to the principal component analysis results, the soil particle composition imposed the greatest influence on the formation of preferential flow in the colluvial deposits, with a contribution of 45.24%. The results provide a theoretical reference for explaining the mechanism of soil infiltration processes and a systematic basis for the treatment of colluvial deposits.

Can hydraulic-energy-indices be effectively used to describe the saturated hydraulic conductivity?

The saturated hydraulic conductivity (Ks) and water retention curve (SWRC) parameters are important properties for simulating soil hydrological processes and characterizing soil conservation around the world. Therefore, Ks and SWRC are related with the soil physical quality (SPQ) and several SPQ indices can be derived from SWRC, such as the pore size distribution, relative field capacity, plant available water, drainable porosity, and soil hydraulic-energy indices (SHEI). It is well known that the soil structure can be assessed by using SHEI, but a possible physical relationship between Ks and SHEI was not examined yet. Therefore, the objective of this study was to investigate the behavior of Ks as function of SHEI for several soil textural classes. If this relationship be proved, then SHEI might be applied to improve the Ks prediction by PTF models. In this work, a data set of 395 measured SWRC's were fitted to the vG equation to obtain the SHEI to verify whether they are statistically correlated and physically dependent on Ks. The resulting parametric and non-parametric correlation results were split up according to six textural classes. The significant influence of Ks on at least one of the absolute SHEI (Aa or WRa) was verified on the numerical scale when all textures were grouped and on numerical and pF scales for clayey and silty textures. Ks showed significant impact on Aa and WRa indices in four textural classes. Furthermore, Ks had influence on the sum Aa + WRa denoted in pF scale for five of the six textural classes, with a significant linear correlation in the clayey texture when log (Aa + WRa) was applied. The significant and high correlation of Ks on the ratios WRa/AWC and Aa/φD was also observed in four of the six classes, and therefore the use of these indices is recommended for the development of PTFs for Ks prediction.

Developing novel ensemble models for predicting soil hydraulic properties in China’s arid region

Accurately quantifying the mass (water, nutrients, and carbon) and energy exchange processes between the Earth’s atmosphere, biosphere, and lithosphere requires the accurate parameterization of soil hydraulic properties (SHPs) and their spatial heterogeneity. Because direct measurements of SHPs are difficult, time-consuming, and impossible at larger spatial scales, various pedotransfer functions (PTFs) have been developed in the last few decades, providing divergent estimates of SHPs from readily measurable variables. However, existing PTFs are mostly developed for specific regions and may not be suitable for other pedoclimatic conditions. Here, PTFs were developed using multiple machine-learning algorithms to estimate SHPs and examined the weaknesses and strengths of each method in estimating the average and variability of SHPs across China’s arid region. The optimal PTFs were applied to a 1 × 1 km2 regional map of texture and bulk density, thus producing maps of the saturated hydraulic conductivity (Ks), the parameters of the van Genuchten (VG) formulation, field capacity (θfc), wilting point (θwp), plant available water (θpa), and soil macroporosity (ϕm) in the 0–2 m soil profile throughout the region. The results indicate that the ensemble model with the averaging method (EMA) is the most robust for estimating all SHPs. The EMA-PTFs for Ks yielded the best performance for sand textures, followed by sandy loam, loam, silty loam, silty clay loam, loamy sand, and clay loam textures. There were no significant differences in estimating soil water retention curve parameters among the different soil texture classes. Using the same observed data set, we demonstrated that the new EMA-PTFs outperformed those of existing PTFs, such as Rosetta and HYPRES, with RMSE values decreasing by 25–83 % depending on the SHPs. Furthermore, our SHP datasets exhibited significantly deeper soil profiles and higher accuracy than other available regional and global SHP products. The VG retention parameter α shows the greatest variation vertically throughout the 0–2 m soil profile, followed by ln(Ks), θr, θpa, θfc, θwp, ϕm, θs and n. All SHPs exhibit much lower variability in the desert than in other areas, likely due to the homogeneous particle size distribution of desert areas. This study provides more accurate SHP estimates in China’s arid region than the existing SHP products by developing advanced PTFs and highlights the inconsistency in SHPs among different global or regional products; the uncertainties induced by PTFs should thus be considered in future terrestrial biosphere modeling.

Study on the Effect and Enhancement of Near-Natural Integrated Plant Positioning Configuration in the Hilly Gully Region, China

The establishment of protective forests plays a crucial role in mitigating soil erosion on slopes within hilly and gully regions. However, in practical applications, the configuration of protective forests on slopes is intricate and diverse, and the suitability and rationality of different configuration patterns for various slope sections have not been thoroughly investigated. This study focuses on a 40-year-old artificial protective forest, examining 16 different configuration patterns on the top, middle, and lower slopes. It compares the growth conditions, community structure stability, and characteristics of the saturated soil’s hydraulic conductivity. The findings indicate that the top slope should be identified as a critical area for slope protection. The optimal configuration for this area is the “tree + grass” pattern with a spacing of 5 m × 5 m, which promotes the optimal growth of tree species and effectively reduces the surface runoff of gravel particles ranging from 1 cm to 3 cm in diameter. On the middle slope, the “tree + shrub + grass” structure proves effective in slowing down the erosive force of slope runoff. The recommended spacing for trees is 5 m × 6 m, and for understory shrubs, it is 1 m × 6 m. This configuration pattern results in the most stable structure for the plant community and maximizes the water conservation potential of forest litter. By analyzing the characteristics of the saturated soil’s hydraulic conductivity, we find that the complexity of the plant configuration on the lower slopes is correlated with a greater coefficient of variation in the saturated soil’s hydraulic conductivity. Nevertheless, there is no significant difference in the average soil saturated hydraulic conductivity per unit area between the different configuration patterns. Consequently, the lower slope can rely on the natural recovery of herbaceous plants. The results of this research contribute valuable scientific and technical insights to the management of soil erosion in hilly and gully areas, both in China and around the world.

From field soil sampling to watershed model: Upscaling by integrating information entropy and interpolation method

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation.

Inverse modeling of frequency domain-based one-dimensional soil water flow in layered soils

Soils are heterogeneous at multiple scales. Estimates of spatially varying saturated hydraulic conductivity (Ks) of soils dictate the resolution of modeling water flux based on the Richardson-Richards equation (RRE), but direct measurements of Ks everywhere in a field are practically impossible. As a result, this study develops an inverse approach to estimate spatially varying Ks utilizing soil moisture observations driven by periodic weather variability at different frequencies. Using a numerical solution to vertical, one-dimensional RRE based on Gardner-Kozeny (GK) model in a heterogeneous soil with periodic flux, we investigate the spatial cross-correlation between Ks and observations (the amplitude or phase shift) of soil moisture fluctuation at different frequencies without high computational cost in the conventional time-domain model. These correlation patterns vary with the spatial location and frequency, suggesting that soil moisture fluctuations at different frequencies at one monitoring location carry non-redundant information about the heterogeneous distribution of Ks. Guided by cross-correlation maps, several inverse experiments reveal the effectiveness of multi-frequency data of soil moisture fluctuation for mapping the heterogeneous distribution of Ks. Monte Carlo simulations suggest that multi-frequency data can provide non-redundant and useful information about the estimation of heterogeneous Ks. Synthetic data based on a commonly-applied nonlinear van Genuchten-Mualem (VG) model is then tested in our inversion algorithm. The results indicate that the spatial pattern of the inverted GK Ks is very similar to that of the VG Ks, although these two parameters are inherently not identical since they are used in two different models. In addition, the inverted GK Ks can successfully predict the soil moisture fluctuation of frequencies that were not used in the inversion. Despite having no field experiments to validate this model, we believe this is the first attempt to conduct frequency-domain inverse modeling in vadose zone hydrology using soil moisture fluctuation.

Effect of Humic Amendment on Selected Hydrophysical Properties of Sandy and Clayey Soils

In recent years, products containing humic acids have been increasingly used in agriculture to improve soil parameters. Quantifying their impact on soil quality is, therefore, of key importance. This study seeks to evaluate the impact of the commercial humic acid product (HA) on the hydrophysical parameters of sandy and clayey soils sampled from different sites in Slovakia. Specifically, the study hypothesizes that humic amendment will enhance particle density (ρs), dry bulk density (ρd), porosity (Φ), saturated hydraulic conductivity (Ks), soil water repellency (SWR), and water retention capacity in sandy and clayey soils. The results of the laboratory measurements were analyzed using NCSS statistical software at a statistical significance of p &lt; 0.05. In sandy soil, there was a statistically significant decrease in ρd and Ks and an increase in Φ and a contact angle (CA) after the application of 1 g/100 cm3 HA. At a dose of 6 g/100 cm3 HA, the values of ρs, ρd, and Ks decreased, and the Φ and CA values increased. In clayey soil, the Ks value significantly decreased by −35.5% only after the application of 6 g/100 cm3 HA. The addition of HA increased the full water capacity (FWC) and available water capacity (AWC) of clayey and sandy soils. The positive influence of HA on the studied soil parameters was experimentally confirmed, which can be beneficial, especially for their use in agricultural production.

Tritium behavior in soil and mineral rock components used for plant cultivation

Immersion, percolation and tritium release experiments in peat and vermiculite soil samples were performed to analyze their behavior in this widely used medium for plant cultivation. Samples were immersed in tritiated water for 696 h and the isotope exchange capacity evaluated. A vertical flow regime was also considered with analysis for hydraulic conductivity to understand tritium mobility and therefore its availability. Peat soil showed a high tritium retention after percolation, but vermiculite seem to suppress its retention ability. The high moisture and organic content of peat enhanced its isotope exchange capacity. The falling head method was used to numerically evaluate the saturated hydraulic conductivity and outflow flux. Calculated isotope exchange capacity was 4.95×10-2 mol-T2O/g for peat and 3.38×10-2 mol-T2O/g for vermiculite. The tritium release experiment showed significant release of tritiated carbons in peat.

Soil contamination in a cemetery area: a case study in Nova Hartz City—RS, Brazil

We conducted a study in a cemetery area covering 2608.53 m2 in the municipality of Nova Hartz, Metropolitan Region of the State of Rio Grande do Sul. Soil samples were collected to determine the physicochemical parameters of the local soil at nine points within the study area and at three different depths (0 cm, 50 cm, and 120 cm). Granulometry and saturated hydraulic conductivity of the soil were assessed, and chemical analyses for Cadmium, Cobalt, Copper, and Chromium were performed using the Atomic Absorption Spectrometry technique.The results revealed that the soil exhibited average values of 78.34% sand, 8.25% silt, and 13.41% clay, classifying it as sandy loam. The saturated hydraulic conductivity was measured at 5.7 × 10–4 cm s−1 across the profile (from 0 to 120 cm). Chemical analyses identified concentrations exceeding the allowed limits for Cadmium (points 1, 4, 5, 6, 7, 8, and 9), Cobalt (points 2, 3, 4, 5, 7, and 8), and Copper (points 4, 5, 6, 7, and 8), with only two values for Chromium (both at point 7). Some points exhibited concentrations above the maximum allowed values at multiple depths. Evaluating vertical distribution, Cadmium did not show depth variations, suggesting a possible natural origin unrelated to cemetery activities. Conversely, Copper, Cobalt, and Chromium displayed increased concentrations with depth. In conclusion, significant changes in concentrations of Cadmium, Cobalt, and Copper were observed, especially between depths of 0 and 120 cm.

Soil surface greenhouse gas emissions and hydro-physical properties as impacted by prairie cordgrass intercropped with kura clover

Prairie cordgrass (PCG) is a perennial crop which has the potential for biofuel production under marginal lands. The intercropping of a perennial legume, kura clover (KC) with PCG can reduce the use of chemical fertilizer while maintaining the soil hydro-physical conditions. The objective of this study was to compare the soil hydro-physical properties and greenhouse gas (GHG) fluxes under PCG intercropped with KC (PCG–KC), and PCG fertilized with graded levels of N (0, 75, 150, and 225 N kg ha−1). During the summer of 2021, soil samples (0–10 cm) were collected. Additionally, gas samples were collected weekly from April through September of the same year. Soil water retention, saturated hydraulic conductivity ( Ksat), thermal conductivity (λ), soil organic carbon (SOC), and total N (TN) concentrations were measured. Soil pore characteristics were measured using X-ray computed tomography. The PCG–KC had 1.42 g kg−1 TN and 24 g kg−1 SOC at 0–10 cm, non-significant to PCG-75, 150, and 225 N. Nonetheless, TN significantly increased in both PCG–KC and other fertilized treatments compared to the control. Intercropping boosted macroporosity (0.024 cm3 cm−3), Ksat (+50%), and lowered λ (−1%), compared to the N fertilized treatments. Soil cumulative CO2 under PCG–KC (1012.67 kg C ha−1) was similar to PCG-75, 150 N, but lower than PCG-225 N (1418.66 kg C ha−1). Overall, this study showed that PCG–KC can be a sustainable option over the use of N fertilizers since they had similar levels of hydro-physical characteristics and had a comparable ability to mitigate GHG emissions.

A simple, accurate, and explicit form of the Green–Ampt model to estimate infiltration, sorptivity, and hydraulic conductivity

AbstractFinding an explicit solution to the widely used Green–Ampt (G–A) one‐dimensional infiltration model has been subject of efforts for more than half a century. We derived an explicit semiempirical approach that combines accuracy with simplicity, a concept that has been generally neglected in previous studies. The equation is , with F (L), Ks (L/T), S (L/T0.5) and t (T) being cumulative infiltration, saturated hydraulic conductivity, sorptivity, and time, respectively. Relative errors (ɛ) by the application of this equation generally do not exceed ±0.3% in most applied infiltration problems faced by water resources engineering today. We show both numerically and mathematically that │ɛ│&gt; 0.3% could only occur if Kst/F &gt; 0.904, a criterion that could apply to sand and loamy sand soils (i.e., coarse texture) and if they experience infiltration rates for over 6 h and 19 h, respectively. Hence, we also derived a simple linear adjustment in the model as Fadj ≅ 0.9796 F + 0.335 S2/Ks to address these longer infiltration rates, and to assure that ɛ remains within the expected ±0.3% range of uncertainty. A linearized regression technique was also developed to accurately estimate S and Ks when the G–A model is used. We numerically demonstrated that our fitting method could be used even when the G–A approach is less valid (diffusive soils), provided that the actual value of the capillary length (λ) is initially known. An added benefit of our approach is that by setting λ equal to 1/3 and 2/3, it can significantly limit the range of initializing, unknown, a priori values of S and Ks, as these two parameters are estimated through the inverse solution of implicit infiltration models. Due to the model's simplicity and accuracy, our solution should find application among hydrologists, natural resource scientists, and engineers who wish to easily derive accurate estimations from the G–A infiltration approach and/or estimate sorptivity and hydraulic conductivity without encountering divergence problems.

Evaluation of infiltration testing methods for design of stormwater drywell systems

The current infiltration testing and drywell design methods do not always provide accurate estimates of the capacity of production-scale dry wells. In numerous cases, the predicted capacities appear to be considerably lower than the actual drywell capacity, resulting in more drywells than required and significantly higher construction and long-term maintenance costs. In other cases, the uncertainty in the measurements results in the predicted capacities being higher than the actual drywell capacity, resulting in fewer drywells being required. In this study, we discuss the reasons for these inaccurate predictions of drywell performance using current methods, as well as the results of recent studies to develop improved methods for predicting the capacity of stormwater infiltration drywells. These studies, funded by the United States Environmental Protection Agency (EPA) and the Los Angeles County Safe Clean Water Program (SCW), include numerical simulations and field studies in California. These test methods rely on steady-state infiltration tests in small-diameter boreholes and produce an estimate of the saturated hydraulic conductivity, which can be used to reliably predict the performance of large-diameter drywells. The methods were validated by testing small- and large-diameter test wells in close proximity using three different drilling methods. The results of this study describe the design and conduct of a borehole infiltration test that accurately represents drywell performance. Furthermore, based on a combination of numerical simulations and field studies, reduction factors were developed to account for test uncertainty, test duration, analytical error, field variability, potential for groundwater mounding, and clogging.

Summer cover crop and temporary legume-cereal intercrop effects on soil microbial indicators, soil water and cash crop yields in a semi-arid environment

ContextFew studies have investigated summer cover crops as a replacement for bare fallow in semi-arid temperate regions, and summer cover crop impacts on soil biological function, water balances and subsequent winter crop yields in these regions remain largely unknown. ObjectiveThe 4-year field study aimed to determine the consequences of replacing a summer fallow with a summer growing cover crop on soil function, water balances and subsequent winter cash crop yields in a semi-arid region (486 mm mean annual rainfall) of the Australian southern cropping zone. MethodsA canola (Brassica napus)-wheat (Triticum aestivum L.) rotation with summer fallow was compared to the same rotation with either i) a single species (buckwheat, Fagopyrum esculentum L.) summer cover crop; ii) a four-species mixed brassica + cereal summer cover crop or iii) a cropping sequence with a temporary legume intercrop in the wheat phase of the rotation. Cover crop biomass production, soil water to a depth of 90 cm at cash crop sowing, crop yields and soil functional indices were quantified. ResultsCover crops produced 500–700 kg biomass ha−1 in the 2020 and 2021 seasons and 1000–2400 kg biomass ha−1 in 2022. The four-species mixed cover crop significantly lowered soil water (around 30 mm; P < 0.05) at the time of sowing the cash crop compared to the control and resulted in 15% reduction (P = 0.12) in canola seed yield in 2020, but no significant effect of cover crops of soil water and mineral N at sowing, or cash crop yields, were observed in subsequent seasons. In 2021 the temporary vetch intercrop produced > 1000 kg ha−1 biomass over 9 weeks, and led to a (non-significant) 10% wheat yield reduction. There was no significant effect of cover crop or temporary intercrop treatments on soil functions in the 2020 or 2021 seasons, but activities of several soil enzymes (leucine aminopeptidase, arylsulfatase and B-glucosidase; P < 0.05) and water-soluble carbon (P = 0.059) were significantly higher in the summer cover crop plots compared to control and intercrop plots in March 2022 following termination of the cover crops. These changes coincided with a significant increase in saturated hydraulic conductivity in the four-species cover crop plots in March 2022 compared to control plots. ImplicationsThe study did not provide any compelling evidence for benefits of summer cover crops over fallow in the short term (3–4 years). The relatively low cover crop biomass production over the 4-year study suggests summer cover crops are unlikely to substantially improve soil carbon levels in temperate, semi-arid cropping systems.