Variability Of Soil Hydraulic Properties Research Articles

Insight into the variation of soil hydraulic properties under beech and spruce forest—A case study in the forest of Tharandt, NE Germany

AbstractBackgroundThe increasing vulnerability of forests in the temperate zone due to climate change has led to modification in the forest structure to secure woody raw materials and ecosystem benefits. Such changes will influence hydrological processes both at the stand and catchment scale. Soil hydraulic properties (SHP) play an important role in assessing the water cycle in these ecosystems. Yet, knowledge regarding the effect of forest‐ and site‐specific conditions on SHP in temperate climates is scarce.AimsThis work addresses this research gap by assessing the variation of SHP under two common European forest stands, Fagus sylvatica and Picea abies (1) with comparable site conditions, and (2) across differing site conditions.MethodsWe determined the soil water retention curve (WRC) and the hydraulic conductivity curve (HCC) in several plots with the bimodal Kosugi–Mualem's hydraulic model. These functions were determined using combined field and laboratory measurements, including hydraulic conductivity and water content from soil samples.Results(1) We observed distinct variations in SHP between beech and spruce forest stands with comparable site conditions; however, no clear pattern in the variation was discernible. (2) A noticeable effect of the site‐specific characteristics on the SHP was detected. Moreover, SHP in each analysed forest type presented individual variations.ConclusionsThis study demonstrates that SHP present a wide range of variations in terms of both forest‐ and site‐specific conditions. Hence, due to its heterogeneity, we emphasise the need for more research to better characterise SHP in temperate zone forests. Moreover, this study underlines the urgent use of a minimum set of parameters in studies when addressing SHP (e.g., tree age, soil texture).

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.

A scaling-based model to describe temporal variability in soil hydraulic properties

Accurate knowledge of temporal variability in soil hydraulic properties (SHPs) can improve the prediction capability of flow and transport models. Lab and field measurements for determining SHPs at multiple timescales are expensive and time-consuming. Further, the existing Fokker-Plank equation (FPE) based numerical and analytical models for describing temporal variation in SHPs require parameterization. In this study, a scaling model is proposed to describe temporal variation in SHPs of four different soils. As field studies related to temporal variation in SHPs are limited, first synthetic temporally varying SHPs, soil water characteristic curves and hydraulic conductivity curves are generated using the analytical solution of FPE. Functional normalization approach is then used to develop reference curves and to obtain scale factors at different time-steps. The time-varying scale factors and the initial SHPs are related by two-step regression equations. The reference curves and the regression equations together can be used to estimate SHPs at any time given the initial SHPs. The developed model is validated using a 5-fold cross validation method and with experimental data at two study sites. The average percentage error in predicted van Genuchten parameters (θs,n and Ksat) except for α are mostly less than 10 %. The performance of the proposed model is comparable to that of FPE analytical model for experimental data. The proposed method holds promise for describing temporal variation in SHPs using only the initial SHPs.

Stochastic analysis of plant available water estimates and soil water balance components simulated by a hydrological model

AbstractThe uncertainty in soil hydraulic parameters is often not taken into account in process‐based hydrological modeling. Performing runs with 104 stochastic parameter realizations, we evaluated the propagation of uncertainty in the Van Genuchten–Mualem (VGM) parameters into estimates of the threshold values of soil water content used to calculate the total and readily available water, and on the long‐term (30 years) simulations of evaporation, transpiration, bottom flux, and runoff by the SWAP hydrological model. The simulated scenarios included weather data from a location in southeast Brazil and seven soils from the same region cropped with maize, comprising a wide range of texture classes. The results showed that uncertainties in VGM parameters affect the estimates of total and readily available water. Water balance components obtained by a deterministic simulation with average VGM parameters did not always agree with the average or median of stochastic simulations, and stochastic simulations including parameter uncertainties should be preferred. Variations in yearly rainfall characteristics were more important for bottom flux and evaporation, while transpiration and runoff were more strongly influenced by the variations in soil hydraulic properties.

Analyzing the role of soil and vegetation spatial variability in modelling hydrological processes for irrigation optimization at large scale

The main purpose of this paper was to study the effect of spatial variability of soil hydraulic properties (HP) and vegetation parameters (VP) (e.g., leaf-area index, LAI, and crop coefficient, Kc) on modelling agro-hydrological processes and optimising irrigation volumes at large scale. Based on this analysis, the effect of partly overlooking the spatial variability of soil HP and/or VP inputs was verified on a 140 ha irrigation sector in “Sinistra Ofanto” irrigation system in Apulia Region, Southern Italy. Five soil profiles were excavated and the HP were measured in all the soil horizons. Additionally, measurements of soil HP were taken in the surface soil layer in ninety sites distributed over the whole irrigation sector. All the HP measurements were carried out using tension infiltrometer. Remote sensing applications were used to obtain LAI and Kc using European Space Agency’s (ESA) Sentinel-2 images with 10 m resolutions. First, distributed (on ninety polygons with an average area of about 1.5 ha) optimal irrigation volumes and related deep percolation volumes at a depth of 80 cm, were computed using an agro-hydrological model and accounting for the actual observed variability of soil HP and VP inputs. The sector scale irrigation and deep percolation volumes were obtained by aggregating the distributed irrigation volumes. This was considered as the reference scenario (hereafter DVS—Detailed Variability Scenario). Then, reduced variability scenarios (hereafter RVS—Reduced Variability Scenario) were considered, where the information on the actual spatial variability of the soil HP and VP was gradually overlooked to find the minimum data set needed to still have sector scale irrigation volumes and related deep percolation volumes comparable to those obtained under the DVS. Results showed that overlooking VP (RVS-VP) variability did not significantly change the optimal irrigation volumes and the deep percolation fluxes. By contrast, neglecting the HP variability (RVS-HP) showed significant effects on both the irrigation and percolation volumes compared to the DVS. The main practical finding was that, at least for the area investigated in this study, hydraulic characterization of one soil profile in an area of approximately 30 ha provides sector scale irrigation volumes and percolation fluxes comparable to those obtained under the DVS, thus by accounting for all the observed local variability.

Modeling Soil Hydraulic Properties Using Dynamic Variability of Soil Pore Size Distribution

The knowledge of temporal variability of soil hydraulic properties (SHPs) in agricultural fields can help in reliable assessment of crop water requirement, thus improving irrigation water usage efficiency. The Fokker–Planck equation (FPE) and its modified forms are popularly used to describe temporal variation in SHPs. These models consider statistical description of soil pore size distribution (PSD) as a probability density function to estimate SHP evolution with time. In this study, we compare four different models to describe the temporal evolution of PSD and SHPs for multiple datasets across the world with different soil types, tillage conditions and crop cover. Further, field experiments were carried out at an experimental agricultural field at IIT Kanpur for rice crops, and the performance of these models was also evaluated for Indian conditions. It is observed that existing models have low accuracy for small pore radii values, and the prediction ability of these models is more affected by soil type rather than tillage conditions. More observations can improve the performance of FPE-based numerical and analytical models. The POWER Model is the least accurate because of its inherent power law assumption of PSD, which results in incorrect values for low pore radii. The FPE analytical model can be reliably used for predicting PSD and SHP evolution at most of the field sites.

Variability of in situ soil water retention curves under different tillage systems and growing seasons

Soil pore space can change over time due to tillage, frost, wetting and drying cycles, plant roots, and compaction. However, a soil water retention curve (SWRC) is usually considered to be static and is determinedin a laboratory on a limited number of small soil samples. Field SWRCs were determined at a depth of 20 cm on Mollic Gleysol. Measurements were made in two growing seasons at different spatial locations on plots with different tillage systems: no-tillage (NT) and conventional tillage (CT). The unimodal van Genuchten retention function (VG) was fitted to each SWRC and model parameters were estimated. We evaluated the variability of the curves within growing seasons, predicted soilwater contents at field capacity, and evaluated the differences in the estimated parameters of the VG model between different growing seasons and tillage systems considering intraseasonal and spatial variability. The shape of the curves depended more on the environmental conditions during the growing season than on the tillage system. In the wetter and cooler growing season of 2020, when soybeans were grown, the soil retained water in a narrower range. In the drier growing season of 2021, when maize was grown, intraseasonal variability in SWRCs was greater than in 2020. Regardless of the growing season, estimated α values were more intraseasonally variable under the CT than under the NT. Based on the SWRCs, predicted water contents at field capacity varied intraseasonally, seasonally, and spatially. Accounting for spatial and intraseasonal variability, the estimated VG parameter θr differed between years, regardless of tillage system. In 2020, the parameter α was higher under the NT system than under the CT system. Under the CT, α differed between years, while under NT it did not. For the parameter n, there were no significant differences between tillage systems or growing seasons. Seasonal, intraseasonal, and spatial variability in soil hydraulic properties should be considered in soil water modelling studies.

Modeling rainfall-infiltration-runoff processes on sloping surfaces subject to rapidly changing soil properties during seal formation

The effect of rapidly changing soil properties during surface sealing is usually neglected in hillslope infiltration-runoff modeling practices despite its substantial impact. Based on the modified seal formation model and a two-layer infiltration-runoff model, a physics-based, computationally efficient modeling framework is developed to simulate the rainfall-infiltration-runoff process on slopes during seal formation. The framework considers the rapid variations of soil properties of the surface layer over time to reflect the soil sealing process, while accounting for the steepness of the slope. On sloping surfaces, the raindrop impact can both facilitate soil sealing via the normal component to the slope (dominant role) and reverse the process because of the tangential component (secondary role). The proposed solution approach needs no numerical grid adjustment to address the progressive sealing layer compaction. The model simulations accord well with the runoff experiments of different rainfall intensities and slope gradients. During seal formation, rainfall intensity and slope gradient can significantly affect the variation of soil hydraulic properties. The new approach is compared to the case where the seal layer formation is not accounted for and to the case where a completely formed seal is assumed at the rainfall onset. It is found that accounting for the sealing process affects the hydrological processes. Neglecting seal formation or assuming a completely formed seal layer would lead to large errors in both infiltration and runoff predictions. The proposed model can improve rainfall-infiltration-runoff models applicable for hillslopes subject to fast changing soil properties during surface sealing or rapid soil compaction.

Variation in Hydraulic Properties of Forest Soils in Temperate Climate Zones

The structure of forests in temperate climates has been changing to ensure the resilience of trees. This change affects the local water balance. Knowledge of soil hydraulic properties (SHP) is essential to assess the water cycle in ecosystems. There is little knowledge about the impact of tree species on SHP and the water balance. Based on a compilation of 539 related studies we aimed at identifying the effects of tree species and age on SHP in temperate climates. However, most studies concentrated on soil biogeochemical properties, whereas only 256 studies focused on SHP. The literature presents no standard methods for assessing SHP and there is no knowledge of their variations in forests. We present a systematic overview of the current state of knowledge on variations in SHP based on forest type in temperate climates. We identify the gaps and weaknesses in the literature and the difficulties of evaluating the reviewed studies. More studies following standardised methodologies are needed to create a robust database for each forest type and soil texture. It would improve the assessment of the forest water balance through calibrated plot/site-scale process models. Such a database does not yet exist, but it would greatly improve the management and development of future forest ecosystems.

Spatio-temporal variation of surface soil hydraulic properties under different tillage and maize-based crop sequences in a Mediterranean area

AimsThe surface crust formed by the drop impact of rainfall and/or irrigation is a prevalent characteristic in many Mediterranean soils. However, the temporal variation of soil hydraulic properties induced by surface crust during the high-frequency irrigation has rarely been investigated.MethodsBeerkan infiltration tests in conjunction with the BEST method were used to investigate the effects of surface crusting on the spatio-temporal variation of saturated soil hydraulic conductivity (Ks, mm s−1), sorptivity (S, mm s−0.5), mean pore size (r, mm), number of effective pores per unit area (N, m−2) in Agramunt, NE Spain.ResultsIn response to autumn tillage, intensive tillage (IT) increased Ks and S due to higher r and N, but both declined after 60 days. Reduced tillage (RT), maintained comparable Ks and S values, despite having a lower N value. After the spring tillage, both IT and RT developed crusted layers, resulting in decreased Ks, S and N. Long-term no-tillage (NT) showed an increasing trend of Ks and S over time, except for the last sampling. Spatial variation (i.e., between the rows, B-row vs. within the row of crops, W-row) of Ks and S was found, and non-crusted soils (W-row) had consistently higher Ks and S than crusted soils (B-row).ConclusionsConservation tillage i.e., RT and NT improve the surface soil structure and reduce the risk of crust development. Surface cover by crops may help to prevent crust formation within the row of crops, improving soil hydraulic conductivity.

Tempo-Spatial Variations in Soil Hydraulic Properties under Long-Term Organic Farming

Adequate knowledge of tempo-spatial variability on soil hydraulic properties plays an important role in irrigation scheduling and precision farming. This study was conducted to compare the impact of tempo-spatial variations in long-term conservation tillage applications in organic farming (superficial tillage using a chisel at 10 cm depth) on soil properties. Soil measurements, including infiltration capacity, saturated hydraulic conductivity (Ks), effective bulk density, and penetration resistance, were investigated in 2012 and compared to data from 2008 at the same fields in Baden-Württemberg, Germany. Long-term organic farming reflected a relative increase in Ks values with temporal variability 33% more in 2012 than in 2008, while soil texture was virtually time-invariant. The Ks increased from 27.06, 24.42, 40.46, 17.49, and 22.59 cm d−1 in 2008 to 33.17, 28.79, 47.75, 38.99, and 40.82 cm d−1 in 2012 for sample locations I, II, III, IV, and V, respectively. The effective bulk density values decreased from 1.72, 1.72, 1.68, 1.64, and 1.81 Mg m−3 in 2008 to 1.63, 1.56, 1.67, 1.32, and 1.48 Mg m−3 in 2012 for sample locations I, II, III, IV, and V, respectively. For spatial variations within the same season, variances in computed Ks values were attributed to differences in the soil textures and effective bulk density between different parcels. As the soil was managed by organic farming for a long time, the soil depth compactness was more pronounced in 2012 than in 2008. Nevertheless, the Ks values showed a temporal increase from 2008 to 2012 due to the preferential water flow pathways approach used in organic farming. Estimated Ks values by the Hydrus-1D model in 2012 were five times higher than in 2008. With soil depth, Ks values revealed a decreasing trend over time. Using the numerical model, Hydrus-1D was representative for comparing hydraulic parameters and simulating water transfer in the soil matrix.

Structure Degradation Induced by Wetting and Drying Cycles for the Hilly Granitic Soils in Collapsing Gully Erosion Areas

The hydrological and mechanical properties of granitic residual soils can be significantly altered by periodical wetting and drying (W-D) cycles. The soil structure degradation induced by W-D cycles can lead to soil mass failure and collapsing gully erosion in granitic hilly slopes in south China. However, limited attempts have been made at a comprehensive investigation of the effects of W-D cycles on the structure degradation of granitic residual soils, especially at the pedon scale. The purpose of this paper is to investigate the structural degradation of granite soils induced by W-D cycles and explore its potential influence on the development of collapsing gully erosion. The granitic soil properties, including hydraulic properties, shear strength, and disintegration characteristics, were performed after W-D cycles. The results indicated that the W-D cycles altered the soil pore structure, leading to variations in soil hydraulic properties. Specifically, with increasing alternate W-D cycles, the initial saturated water content and residual water content decreased, while the saturated hydraulic conductivity increased. Meanwhile, increasing W-D cycles contributed significantly to variations in cohesion and internal friction strength by decreasing the shear strength variables, especially the soil cohesion strength. Correspondingly, soil disintegration was increased during W-D cycles. Furthermore, most degradation of soil structure was recorded within the first two cycles of W-D. The obtained results indicate that the W-D cycles weaken soil structure, increase rainwater infiltration, decrease soil shear strength and disintegration resistance, and accelerate soil erosion. A vicious cycle of granitic slope failure induced by W-D cycles is eventually formed. This study provides useful information about the mechanism of soil mass failure and collapsing gully erosion in granitic hilly slopes.

Investigation of spatial variability of soil hydraulic properties for application in intensive green roofs

Investigation of spatial variability of soil hydraulic properties for application in intensive green roofs

Temporal variation of saturated and near‐saturated soil hydraulic conductivity and water‐conducting macroporosity in a maize‐wheat rotation under conventional and conservation tillage practices

AbstractKnowledge of temporal variation of soil hydraulic properties (SHPs) is crucial to understand soil physical behaviour under different tillage practices. The objective of this study was to assess the variation of saturated and near‐saturated soil hydraulic conductivity (NSHC) and water‐conducting macroporosity (Ɛ) under long‐term (09 years) tillage regimes viz. zero tillage (ZT), conventional tillage (CT), and minimum tillage (MT) in a rain‐fed maize‐wheat crop rotation (RMWC) in the North‐West Himalayas, India (NWHI). A hood infiltrometer (HI) was used to measure the steady‐state water flux (q) at 0, −10, and −30 mm pressure head (PH) after harvesting of maize and over two wheat cropping seasons for each treatment. The infiltration data were analyzed in terms of unsaturated hydraulic conductivity k(h), field saturated hydraulic conductivity (ks), water‐conducting macroporosity (Ɛ). The results showed that the seasonal effects on ks, k(h), and Ɛ values were significantly different (p ≤0.05) for tilled treatments (CT and MT). In contrast, no significant difference (p ≤0.05) was found for untilled treatment (ZT). Significantly higher (p ≤0.05) ks, k(h), and Ɛ values were observed in ZT than CT and MT, associated with higher SOC and lower ρb values. A multivariate analysis of variance of the ks showed a highly significant difference (p ≤0.01) with both time and tillage treatments. Overall, a significant improvement of hydraulic conductivity characteristics was observed during the wheat‐growing seasons compared with the maize harvest season. The temporal dynamics of SHPs under different tillage regimes indicate that ZT can be a suitable tillage practice for reducing runoff and soil loss in monsoon maize and winter wheat cropping system.

A Computational Method for Modeling Spatiotemporal Variability of Hydrodynamic Properties in Sandy Soil Under Drainage and Recharge

This article proposes an analytical strategy that combines X-ray Computed Tomography (CT) and Continuous Wavelet Transform (CWT) analysis as an alternative solution to long-term experiments that seek to investigate spatiotemporal variations in soil hydraulic properties induced by drainage and recharge cycles. We conducted CT scanning on 100-cm-high column filled with two types of sandy soil in a laboratory environment to simulate, over the period of a month, the equivalent of nearly 40 years of drainage/recharge cycles akin to agricultural fields adopting subirrigation as water management practices. We also monitored soil matric potential, water inflow and outflow, as well as movement of tracers. This later consists in zirconium oxide (ZrO2) that we added to the top 20 cm of each soil column. The results revealed that drainage and recharge cycles greatly affect the evolution of soil hydraulic properties at different locations along the soil profile by reducing drainage and capillary capacities. The approach also allowed us to identify each periodic component of drainage and recharge cycles, and thereby calculate the periodic drift over time. The proposed method can be applied to predict soil evolution according to soil texture, drainage system design and water management, thereby offering a potential basis for proposing mitigation measures related to soil hydrodynamics. It may find its application in agricultural farms adopting subirrigation and surface (e.g., drip) irrigation approaches and, in mining and civil engineering.

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.

Identification of Infiltration Features and Hydraulic Properties of Soils Based on Crop Water Stress Derived from Remotely Sensed Data

Knowledge of the spatial variability of soil hydraulic properties is important for many reasons, e.g., for soil erosion protection, or the assessment of surface and subsurface runoff. Nowadays, precision agriculture is gaining importance for which knowledge of soil hydraulic properties is essential, especially when it comes to the optimization of nitrogen fertilization. The present work aimed to exploit the ability of vegetation cover to identify the spatial variability of soil hydraulic properties through the expression of water stress. The assessment of the spatial distribution of saturated soil hydraulic conductivity (Ks) and field water capacity (FWC) was based on a combination of ground-based measurements and thermal and hyperspectral airborne imaging data. The crop water stress index (CWSI) was used as an indicator of crop water stress to assess the hydraulic properties of the soil. Supplementary vegetation indices were used. The support vector regression (SVR) method was used to estimate soil hydraulic properties from aerial data. Data analysis showed that the approach estimated Ks with good results (R2 = 0.77) for stands with developed crop water stress. The regression coefficient values for estimation of FWC for topsoil (0–0.3 m) ranged from R2 = 0.38 to R2 = 0.99. The differences within the study sites of the FWC estimations were higher for the subsoil layer (0.3–0.6 m). R2 values ranged from 0.12 to 0.99. Several factors affect the quality of the soil hydraulic features estimation, such as crop water stress development, condition of the crops, period and time of imaging, etc. The above approach is useful for practical applications for its relative simplicity, especially in precision agriculture.

Evaluation of pedotransfer functions for predicting soil hydraulic properties: A voyage from regional to field scales across Europe

Study regionEurope. A total of 660, 522, and 4940 soil samples belonging to GRIZZLY, HYPRES, and EU-HYDI databases, respectively, were used for parametric evaluation. Study focusThe soil water retention and hydraulic conductivity functions are crucial input information for land surface models. Determining these functions by using direct methods is hampered by excessive time and unaffordable costs required for field activities and laboratory analyses. Pedotransfer functions (PTFs) are widely-used indirect techniques enabling soil hydraulic properties to be predicted by using easily-retrievable soil information. In a parametric evaluation, the predictive capability of PTFs is examined by comparing measured and estimated soil water retention parameters and saturated hydraulic conductivity. Yet information about the performance of PTFs for specific modeling applications is mandatory to evaluate PTF effectiveness in greater depth. This approach is commonly defined as functional evaluation. New hydrological insights for the regionThe best performing four PTFs selected in the parametric evaluations are tested under two functional evaluations. The first encompasses a spatial interpolation with a geostatistical technique, whereas the second employs Hydrus-1D to simulate the water balance components along an experimental transect. Our results reinforce and integrate the insights of previous studies about the use of a PTF, and highlight the ability, or inability, of this technique to adequately reproduce the observed spatial variability of soil hydraulic properties and simulated water fluxes.

Spatial and fractal characterization of soil hydraulic properties along a catena

AbstractSoil hydraulic properties influence water and nutrient availability as well as environmental sustainability, and these properties vary across several landscape positions. This study investigated the spatial variability and fractal characterization of soil hydraulic properties across five slope positions: summit, shoulder, back, foot, and toe slopes. Triplicate soil samples (0–18 cm) were collected from each slope position from a pasture field planted to tall fescue [Festuca arundinacea Schreb., syn. schendonorus arundinaceus (Schreb.) Dumort., nom. cons.]. Soil bulk density (ρb); saturated hydraulic conductivity (Ksat); water retention at 0, −33, and −1,500 kPa soil water matric potentials; soil organic carbon (SOC); and various pore sizes (macropores [>1,000 μm], mesopores [10–1,000 μm], and micropores [<10 μm]) were analyzed. Results show that SOC was 26% higher, while ρb was 10% lower at the toe slope compared with the summit. Similarly, Ksat values were 3, 9, 16, and 2% greater at the toe slope compared with the summit, shoulder, back, and foot slopes, respectively. Semivariogram analysis showed that the gaussian isotropic model provided the best fit (R2 > .99) for hydraulic properties across all slope positions. The range of spatial variability of soil hydraulic properties was between 5.60 and 123.00 m at all slope positions. The fractal dimensions of soil hydraulic properties across all slope positions ranged from 0.784 to 1.966. Soil hydraulic properties were similar at the foot and toe slopes, which might favor improved crop productivity at these slope positions.

Experimental evaluation of different subsurface water movement models in an agricultural field with soil heterogeneity

Spatial heterogeneity in soil hydraulic properties poses severe challenges to the modeling of soil moisture dynamics in agricultural fields. For simplicity, 1-D water flow models that ignore soil heterogeneity are commonly used to simulate water movement in agricultural fields. As soil hydraulic properties are one of the most crucial input data, it is particularly desirable to investigate how the simulations of these water flow models compare with experimental observations. This study aims to examine the performances of streamtube, 1-D, and 3-D Richards equation based water flow models with experimental observations. Experiments were conducted at an agricultural plot of 20 m × 30 m located in IIT Kanpur, India, for 1 year under wheat (Triticum aestivum L.) and rice (Oryza sativa L.) crop covers. The site was heavily instrumented to monitor soil moisture variation, weather conditions, root depth, and LAI. Further, 54 undisturbed soil samples were analyzed to determine the heterogeneity in soil hydraulic parameters. The results indicate that the performance of the models varies with land cover, atmospheric boundary condition, and crop growth stages. Besides, the difference between model estimates varies with soil moisture wetness and a maximum relative error of 13% was observed under wetting conditions. The streamtube model showed the best performance under wheat crop cover for all boundary conditions and growth stages, as it considers spatial variability in soil hydraulic properties and irrigation application at each subplot. The numerical-1D model was the best predictor under rice crop cover. Further, the results suggest that an increase in model complexity does not lead to an improvement in water simulation, and accurate representation of soil hydraulic properties plays a more important role.