Soil Hydraulic Conductivity Research Articles

Characterization and prediction of hydraulic properties of traffic-compacted forest soils based on soil information and traffic treatments

Key messageThe hydraulic properties of compacted and rutted soils were evaluated through in-situ infiltration experiments and predicted based on soil texture class and traffic treatments. A significant decrease in saturated soil water content and soil hydraulic conductivity at saturation was observed. The resulting soil hydraulic parameters, when integrated into a soil water transfer model, effectively simulated water dynamics in these impacted forest soils, providing a crucial first step toward developing decision support tools for real-time trafficability. This approach can assist forest managers in minimizing the extent of soil compaction.ContextTo overcome trafficability issues of forest soils induced by heavy logging machinery, planning support tools are needed to determine suitable soil moisture conditions for traffic.AimsThis study aimed to identify the soil properties that differ significantly between undisturbed and compacted soils and to provide several estimation tools to predict the hydraulic properties of compacted soils beneath the skid trails.MethodsFour hundred seventeen water infiltration tests were conducted on 19 forest sites, mostly in North-eastern France, and analysed with the BEST method to estimate the hydraulic properties of the skid trails and undisturbed soils. The hydraulic properties of the skid trails were predicted thanks to linear mixed effect models using a bulk treatment effect, a site effect, or a skid trail degradation score. The predicted hydraulic properties were tested using a water flow model to assess their relevance regarding the prediction of water dynamics in skid trails.ResultsThe compaction effect was only significant for the logarithm of the hydraulic conductivity at saturation (log10(Ksat)) and the soil water content at saturation (θsat). For the skid trails, θsat was reduced by - 0.02 and − 0.11 m3m−3 in the 0 − 10 cm and 15 − 25 cm layers respectively, compared to undisturbed topsoil (0 − 10 cm). log10(Ksat) was reduced by − 0.38 and − 0.85 for skid trails in the 0 − 10 and 15 − 25 cm soil layers respectively, compared to undisturbed topsoil. The use of a pedotransfer function, in replacement of water infiltration tests, and their combination with the same correction coefficients proved to efficiently simulate the difference in water dynamics between skid trails and undisturbed forest soils.ConclusionEstimation of soil hydraulic properties based on in situ water infiltration experiments proved efficient to simulate water dynamics in compacted and rutted forest soils. Yet, further studies are needed to identify the most adapted pedotransfer function to forest soils and to test the generalisation of our findings in different conditions, especially deeply rutted soils (rut depths > 12 cm).

Monitoring groundwater vulnerability for sustainable water resource management: A DRASTIC-based comparative assessment in a newly township area of Bangladesh

Groundwater is a vital source of freshwater in our daily lives. Global and local groundwater quality are degrading due to rapid urbanization, human interference, and policy variations, which is prominent in developing nations like Bangladesh. The major purpose of this research is to analyze aquifer vulnerability in Bangladesh's north-central area (Mymensingh) using conventional and modified DRASTIC modeling. Seven influencing hydrogeological factors were employed to develop and integrate conventional DRASTIC modeling: soil media, net recharge, aquifer depth, aquifer media, topography, hydraulic conductivity, and influence of vadose zone, while land use and lineament density were used with them for modified DRASTIC modeling. The findings from four vulnerability analysis detected 29.56% (93.35 sq.km), 22.24% (83.12 sq. km), 28.52 (106.93 sq. km), and 37.6% (140.55 sq.km) of the study area as high to very high vulnerable zones for groundwater pollution. Lower groundwater depth, higher hydraulic conductivity, moderate to high groundwater recharge, dense lineaments, dense settlement, agricultural land, and inland waterbodies together might indicate a high vulnerability in the research area. The validation results based on EC and nitrate levels show that conventional (r = 0.884, p ≤ 0.01; r = 0.951, p ≤ 0.01) and modified DRASTIC models (r = 0.868, p ≤ 0.01; r = 0.840, p ≤ 0.01) have a stronger association with unconfined aquifers, than confined aquifers. Modification with both additional parameters showed more accuracy compared to the conventional one. Frequent monitoring of groundwater quality in high and moderately vulnerable zones is recommended for earlier detection and prevention of potential aquifer degradation.

Global influence of soil texture on ecosystem water limitation.

Low soil moisture and high vapour pressure deficit (VPD) cause plant water stress and lead to a variety of drought responses, including a reduction in transpiration and photosynthesis1,2. When soils dry below critical soil moisture thresholds, ecosystems transition from energy to water limitation as stomata close to alleviate water stress3,4. However, the mechanisms behind these thresholds remain poorly defined at the ecosystem scale. Here, by analysing observations of critical soil moisture thresholds globally, we show the prominent role of soil texture in modulating the onset of ecosystem water limitation through the soil hydraulic conductivity curve, whose steepness increases with sand fraction. This clarifies how ecosystem sensitivity to VPD versus soil moisture is shaped by soil texture, with ecosystems in sandy soils being relatively more sensitive to soil drying, whereas ecosystems in clayey soils are relatively more sensitive to VPD. For the same reason, plants in sandy soils have limited potential to adjust to water limitations, which has an impact on how climate change affects terrestrial ecosystems. In summary, although vegetation-atmosphere exchanges are driven by atmospheric conditions and mediated by plant adjustments, their fate is ultimately dependent on the soil.

Unveiling heavy metal(loid) contamination and migration at an abandoned smelting site: Integrated geophysical and hydrological analyse

The heavy metal contamination at abandoned smelting sites is receiving increasing attention. This study focuses on an abandoned lead–zinc smelting site and uses several methods (such as soil sampling, geophysical exploration, and groundwater monitoring) to systematically investigate the contamination characteristics, distribution patterns, and migration mechanisms of heavy metal(loid) in soil and groundwater. A geological structure model of the study area was established through drilling data and geophysical techniques (Ground penetrating radar (GPR) and Electrical resistivity tomography (ERT)), revealing the relationships among soil resistivity, electromagnetic wave reflection characteristics, and geological structure. This study revealed that heavy metal contamination in soil was concentrated mainly northwest of the site and was closely related to historical smelting activities. The presence of heavy metal(loid)s in groundwater had a complex correlation with soil physicochemical properties and environmental elements, and its distribution was influenced by both hydrogeological conditions and soil properties. This study also investigated the effects of the soil water content (SWC) and soil hydraulic conductivity (Ks) on heavy metal(loid)s migration and reported that high SWC and Ks contribute to the dissolution and migration of heavy metals. In addition, a 3D visualization model of heavy metal contamination plumes was established via Voxler software. This model intuitively demonstrated the migration and diffusion of heavy metal(loid)s in the underground environment, offering a novel perspective on their subsurface behavior. The research results provide important information for understanding the migration of heavy metal(loid)s in soil-groundwater systems.

Applying a Comprehensive Model for Single-Ring Infiltration: Assessment of Temporal Changes in Saturated Hydraulic Conductivity and Physical Soil Properties

Modeling agricultural systems, from the point of view of saving and optimizing water, is a challenging task, because it may require multiple soil physical and hydraulic measurements to investigate the entire crop cycle. The Beerkan method was proposed as a quick and easy approach to estimate the saturated soil hydraulic conductivity, Ks. In this study, a new complete three-dimensional model for Beerkan experiments recently proposed was used. It consists of thirteen different calculation approaches that differ in estimating the macroscopic capillary length, initial (θi) and saturated (θs) soil water contents, use transient or steady-state infiltration data, and different fitting methods to transient data. A steady-state version of the simplified method based on a Beerkan infiltration run (SSBI) was used as the benchmark. Measurements were carried out on five sampling dates during a single growing season (from November to June) in a long-term experiment in which two soil management systems were compared, i.e., minimum tillage (MT) and no tillage (NT). The objectives of this work were (i) to test the proposed new model and calculation approaches under real field conditions, (ii) investigate the impact of MT and NT on soil properties, and (iii) obtain information on the seasonal variability of Ks and other main soil physical properties (θi, soil bulk density, ρb, and water retention curve) under MT and NT. The results showed that the model always overestimated Ks compared to SSBI. Indeed, the estimated Ks differed by a factor of 11 when the most data demanding (A1) approach was considered by a factor of 4–8, depending on the transient or steady-state phase use, when A3 was considered and by a practically negligible factor of 1.0–1.9 with A4. A relatively higher seasonal variability was detected for θi at the MT than NT system. Under both MT and NT, ρb did not change between November and April but increased significantly until the end of the season. The selected calculation approaches provided substantially coherent information on Ks seasonal evolution. Regardless of the approach, the results showed a temporal stability of Ks at least from early April to June under NT; conversely, the MT system was, overall, more affected by temporal changes with a relative stability at the beginning and middle of the season. These findings suggest that a common sampling time for determining Ks could be set at early spring. Soil management affected the soil properties, because the NT system was significantly wetter and more compact than MT on four out of five dates. However, only NT showed a significantly increasing correlation between Ks and the modal pore diameter, suggesting the presence of a relatively smaller and better interconnected pore network in the no-tilled soil. This study confirms the need to test infiltration models under real field conditions to evaluate their pros and cons. The Beerkan method was effective for intensive soil sampling and accurate field investigations on the temporal variability of Ks.

Lithosphere infiltrometer: A low cost, automated infiltrometer (permeameter) for measurement of soil health, infiltration, and hydraulic conductivity

Accurate measurement of infiltration rate and hydraulic conductivity is important for assessing soil physical health, irrigation management and catchment modelling. Commercially available infiltrometers are often expensive, fragile, and require specialist knowledge to operate and perform complex post-measurement calculations. We developed the Lithosphere Infiltrometer (permeameter) to be usable for both experienced soil researchers, and users without prior technical or scientific expertise in soil science. The Lithosphere Infiltrometer is able measure both surface and subsoil infiltration rate and hydraulic conductivity. It is manufactured using 3D-printed parts and off-the-shelf electronic components. It has a robust, quad-leg design that allows for rapid leveling of the device and accurate setting of water depth via a novel 3D-printed bell chamber. The water level is measured using a U85 JRT laser with ±1 mm accuracy connected to an Adafruit Huzzah 32 microcontroller. Infiltration rate and hydraulic conductivity are calculated at 1 to 10 min time steps, and data is presented in real-time on an OLED display. Data is stored on the device and available for download to a mobile device by Wi-Fi.

Assessment of Groundwater Vulnerability to Pollution in the Metro Hilir Watershed Using the SINTACS Method

Abstract Assessment of groundwater vulnerability in the Metro Hilir watershed is necessary because most people use well water to meet basic needs. Identification and spatial analysis are the first steps to determine the potential for groundwater pollution in the area. The SINTACS method was used to assess the intrinsic vulnerability of groundwater using the parameters of groundwater table depth, effective infiltration, material in the unsaturated zone, soil texture type, aquifer media, hydraulic conductivity, and slope. Data processing was carried out by using Geographic Information System (GIS) techniques. Weight scenarios was used based on the hydrological conditions of the study area, namely “Normal Impact” and “Drainage/seepage”. The SINTACS index results was classified into several levels of vulnerability. The high vulnerability class is spread across the east to the south side, while the low vulnerability class is more dominant in the western area. The results of Sensitivity Analysis using the Map Removal technique showed that in both scenarios, soil texture parameters have the highest variation index value of 1.73% in the “Normal Impact” scenario and 2.13% in the “Drainage/Seepage” scenario. Parameters with high variation index values have a sensitive influence on vulnerability class values.

Segmental retention models for representing the hydraulic properties of evolving structured soils

AbstractCommon parametrizations of soil hydraulic properties rely on unimodal curves, which cannot accurately represent the properties of many macroporous, aggregated, mixed, or compacted soils. Multimodal hydraulic curves are increasingly used to represent these structured soils in eco‐hydrological models, but the dynamics of the processes that shape soil structure—and the resulting dynamics of soil hydraulic properties—are often neglected. In cases such as compaction recovery, where the structure‐shaping process can be modeled, coupling the evolving pore volumes to soil hydraulic properties in a physically based way remains challenging. Here, we show how modeled or estimated soil structure evolution, when expressed as a time series of porosities in a few pore size classes, can be assimilated into established models of soil hydraulic properties. Our method relies on the division of retention models into smooth segments, whose water contents can be independently adjusted. We apply the approach to examples of modeled soil structure evolution from the published literature: one describing soil structure recovery after compaction and one describing structure formation as a result of organic amendment. In the cases considered, the estimated soil hydraulic conductivity varies more strongly than the modeled porosity which drives it. This shows that transport‐related soil functions can be impacted longer (after compaction) or sooner (after amendment) than suggested by the evolution of structural metrics such as porosity. In general, modeling the evolution of soil hydraulic properties in cases such as these paves the way for holistic, process‐based modeling of land management practices and their impact on soil functioning.

The Dynamics of Soil Macropores and Hydraulic Conductivity as Influenced by the Fibrous and Tap Root Systems

The Dynamics of Soil Macropores and Hydraulic Conductivity as Influenced by the Fibrous and Tap Root Systems

Predicting soil hydraulic conductivity using random forest, SVM, and LSSVM models

AbstractUnderstanding the hydraulic properties of soil is essential to solve many management problems in agriculture and the environment. Water quality affects soil hydraulic conductivity. Soil hydraulic properties play an important role in nature's water cycle and are used as basic information in designing irrigation and drainage systems, hydrological issues, and soil quality assessment. In the current study, soil sampling is performed from different areas and its hydraulic conductivity was measured using the drop load method and then predicted using support vector machine (SVM) and least‐squares support vector machine (LSSVM) models. The model inputs were: soil texture (percentage of sand, silt, and clay particles), salinity (electrical conductivity), pH, sodium adsorption ratio, soil porosity, and bulk density and the output was soil hydraulic conductivity. Correlation coefficient, root mean square error (RMSE), mean bias error (MBE), and Nash–Sutcliffe efficiency (NSE) were used to evaluate the models and compare them. Based on evaluation criteria the best performance was obtained for random forest (RF) (R = 0.89, RMSE = 0.53, mean absolute error (MAE) = 0.54, and NSE = 0.72). Following RF, the SVM with (R = 0.69, RMSE = 1.32, MAE = 0.69, and NSE = 0.48) performed better than LSSVM model.

Soil response in a Mediterranean forest ecosystem of Southeast Spain following early prescribed burning

The escalation of global warming, high temperatures, and wildfire frequency in dry ecosystems, including semi-arid landscapes, has resulted in increased wildfire regimes, compromising ecosystem resistance and resilience. To mitigate these risks, prescribed burning (PB) is being employed as a preventive measure to modify fuel loads in forest ecosystems. However, fire can also impact soil structure and microbiota, which play critical roles in nutrient cycling, biodiversity conservation, and overall ecosystem functioning. Therefore, understanding post-fire processes is essential for sustainable forest management. However, while previous studies have explored the effects of prescribed fire management on semi-arid soil properties in Mediterranean forest ecosystems, gaps remain in our understanding of its specific impact on the physical structure, chemical composition, and biological activities of soils.In this study, we conducted early spring PB in SE Spain in 2021 and assessed the ecological and temporal effects of PB on semi-arid soils. Soil respiration (SR) measurements using automatic CO2 flow chambers were employed to evaluate microbiota recovery. To examine impacts on soil structure we evaluated physicochemical characteristics, soil hydraulic conductivity (SHC), and soil water repellency (SWR). No significant differences were observed in any of the variables studied after one year. However, immediate effects were detected shortly after the PB. Our research specifically targeted soil structure and microbiota in a semi-arid landscape with poor soils, characterized by slower recovery and potentially fragile ecosystems. These results provide valuable insights for forest management practices, indicating that prescribed fire management strategies in similar ecosystems are unlikely to cause adverse effects on soil health. However, further research is warranted to explore the potential effects of prescribed fire intensity and seasonality. Future studies can focus on investigating these factors to provide more targeted recommendations for effective forest management strategies and wildfire prevention efforts.

Understanding Terrestrial Water and Carbon Cycles and Their Interactions Using Integrated SMAP Soil Moisture and OCO‐2 SIF Observations and Land Surface Models

AbstractRecently, more advanced synchronous global‐scale satellite observations, the Soil Moisture Active Passive enhanced Level 3 (SMAP L3) soil moisture product and the Orbiting Carbon Observatory 2 (OCO‐2) solar‐induced chlorophyll fluorescence (SIF) product, provide an opportunity to improve the predictive understanding of both water and carbon cycles in land surface modeling. The Simplified Simple Biosphere Model version 4 (SSiB4) was coupled with the Top‐down Representation of Interactive Foliage and Flora Including Dynamics Model (TRIFFID) and a mechanistic representation of SIF. Incorporating dynamic vegetation processes reduced global SIF root‐mean‐squared error (RMSE) by 12%. Offline experiments were conducted to understand the water and carbon cycles and their interactions using satellite data as constraints. Results indicate that soil hydraulic properties, the soil hydraulic conductivity at saturation (Ks) and the water retention curve, significantly impact soil moisture and SIF simulation, especially in the semi‐arid regions. The wilting point and maximum Rubisco carboxylation rate (Vmax) affect photosynthesis and transpiration, then soil moisture. However, without atmospheric feedback processes, their effects on soil moisture are undermined due to the compensation between soil evaporation and transpiration. With optimized parameters based on SMAP L3 and OCO‐2 data, the global RMSE of soil moisture and SIF simulations decreased by 15% and 12%, respectively. These findings highlight the importance of integrating advanced satellite data and dynamic vegetation processes to improve land surface models, enhancing understanding of terrestrial water and carbon cycles.

Effect of frequent clearcutting on some soil properties, temperatures, and herbaceous vegetation and the potential of their recovery in a short time.

Harvesting or degradation of forest ecosystems directly affects the microclimate, causing changes in air and soil temperatures and soil moisture in the forestlands. The objectives of this study were to investigate the effect of frequent clearcutting of forest cover on some selected soil properties, ambient and soil temperatures, soil moisture, and herbaceous vegetation cover and determine their recovery in a short period in the area subject to frequent clearcutting under the powerline corridors (PLCs). The study was conducted in the research forest of Istanbul University-Cerrahpaşa, Faculty of Forestry. The treatment plots were selected from the clearcut area, and control plots were selected from an untouched oak-hornbeam forestland. Soil temperature and moisture and maximum and minimum ambient temperatures were measured in the treatment and control plots between 2020 and 2021 and topsoil sampled between 2019 and 2021. Data were analyzed using analysis of variance (ANOVA) to test the effects of clearcutting on some selected soil properties in the short term after cutting. Clearcutting caused a significant increase in soil bulk density (BD) and a decrease in the soil total porosity (TP), soil hydraulic conductivity (HC), and saturation capacity (SC). Forest cover removal significantly decreased the soil organic matter (SOM) content by 3%, increased average soil temperature by 2.1°C, and the difference between maximum and minimum temperatures by 8.8°C. Additionally, clearcutting reduced the average soil moisture from 36 to 35%. The findings revealed that clearcutting negatively affected some hydro-physical soil properties and soil microclimate conditions that may not recover to their previous states within the next few years.

Effects of calcium amendments on hydraulic conductivity and sodium content of brine‐impacted soils

AbstractHigh concentrations of sodium chloride dominate oilfield produced waters (brine) of the Williston Basin. When accidental spills of produced waters occur, there is an immediate need to reduce concentrations of chloride, to protect surface and groundwater systems and to reduce concentrations of sodium (Na) in soil to prevent any unwanted swelling and dispersion in soil. Swelling and dispersion of soils will likely occur if sodium adsorption ratio values are too high and the electrical conductivity drops below a certain threshold that is required to maintain flocculation. To prevent this, a calcium (Ca) amendment can be applied to replace Na with Ca on soil exchange sites. Historically, gypsum has been the most common Ca amendment used for improving brine impacted soils. Flue gas desulfurization gypsum is available in North Dakota but is still a sparingly soluble amendment. The purpose of this research was to investigate the use of calcium acetate (Ca‐Ac) as an amendment for brine‐impacted soils as compared to gypsum. Ca‐Ac has a similar concentration of Ca compared to gypsum but is over 100 times more soluble than gypsum. This laboratory experiment will compare how varying levels of gypsum and Ca‐Ac can influence soil hydraulic conductivity, and chemical and physical properties when mixed with oilfield brine‐impacted soils.

Comparing mini-disk infiltrometer, BEST method and soil core estimates of hydraulic conductivity of a sandy-loam soil

Saturated, Ks, and near-saturated, K, soil hydraulic conductivity control many hydrological processes but they are difficult to measure. Comparing methods to determine Ks and K is a means to establish how and why these soil hydrodynamic properties vary with the applied method. A comparison was established between the Ks and K values of a sandy-loam soil obtained, in the field, with the BEST (Beerkan Estimation of Soil Transfer parameters) method of soil hydraulic characterization and an unconfined MDI (mini-disk infiltrometer) experiment and, in the laboratory, with a confined MDI experiment and the CHP (constant-head permeameter) method. Using for the BEST calculations the soil porosity instead of the saturated soil water content yielded 1.4–1.1 times higher estimates of Ks and K, depending on the pressure head, and differences decreased in more unsaturated soil conditions. The confined MDI experiment yielded 22 % - 77 % higher K values than the unconfined MDI experiment, depending on the established pressure head, h0, and differences were not significant for h0 = −1 cm. In the close to saturation region, the soil hydraulic conductivity function predicted with BEST did not generally agree well with the Ks and K values obtained in the laboratory by a direct application of the Darcy’s law. In particular, BEST yielded a 5.6 times smaller Ks value than the CHP method and up to an 8.1 times higher K value than the MDI. Overall, i) the two application methods of the MDI yielded relatively similar results, especially close to saturation, and ii) there was not a satisfactory agreement between the field (BEST) and the laboratory (MDI plus CHP) determination of soil hydraulic conductivity close to saturation, unless a comparison was made with the same soil water content. The detected differences were probably attributable to soil spatial variability, overestimation of Ks in the laboratory due to preferential flow phenomena, underestimation of Ks in the field due to air entrapment in the soil and infiltration surface disturbance, inability of BEST to describe the actual soil hydraulic conductivity function at the sampled field site. Testing BEST predictions of Ks and K in other soils appears advisable and combining the MDI and CHP methods appears a rather simple means to make these checks. These additional investigations could improve interpretation of the differences between methods, which is an important step for properly selecting a method yielding Ks and K data appropriate for an intended use.

Ecohydrological and hydrogeological dynamics of groundwater springs in Eastern Himalaya, India

Groundwater springs are critical to achieving Sustainable Development Goals (SDG 6, access to clean water) in the Himalaya and remain highly vulnerable to climate change and land-use and land cover change. In a first from Eastern Himalaya, we analysed the relative controls of land-use, precipitation, soil properties, and hydrogeology on the diel and seasonal variability in three representative springs using high-frequency discharge monitoring. Kamrang spring is a high-discharge depression spring fed by a homogenous aquifer, whereas Mamley and Gaddi show dual-flow characteristics attributed to primary matrix-based flows and secondary conduit (karst) or unconsolidated storage-based flows, respectively. The first reports of strong diel fluctuations in springflows show significantly higher amplitude in the depression spring (22 ± 41 l min−1) than the fracture (15 ± 26 l min−1) and karst springs (12 ± 24 l min−1), attributed to evapotranspiration and hydrogeology, respectively. The forest spring (Gaddi, low soil hydraulic conductivity, Ksat) showed a faster response at intense precipitation (>30 mm h−1), whereas the agriculture springs (Kamrang and Mamley, high Ksat) showed the lowest lags at low-moderate intensities (<20 mm h−1). The depression spring showed high recharge potential, whereas the karst and fracture springs were constrained by their relatively smaller recharge area and low Ksat, respectively. The per capita daily water availability was barely sufficient to support the minimum (20 l) and mandated (55 l) requirements for 30–70% and 2–47% of days a year, respectively. Thus, future precipitation intensification and land-use change will disproportionately impact the >5th-order karst and fracture springs. The study provides an integrated analytical framework for understanding Himalayan springs, which are critical for achieving SDG 6 (access to clean water) and a baseline for developing appropriate springshed models for effective management of freshwater ecosystems (SDG 15) against future climate change impacts (SDG 13), as well as informing the water security assessment in the Himalaya.

Measurements of Soil Water Potential and Conductivity based on a Simple Evaporation Experiment using a Hydraulic Property Analyzer.

The measurement of soil hydraulic properties is critical in understanding the physical components of soil health as well as integrated knowledge of soil systems under various management practices. Collecting reliable data is imperative for informing decisions that affect agriculture and the environment. The simple evaporation experiment described here uses instrumentation in a laboratory setting to analyze soil samples collected in the field. The soil water tension of the sample is measured by the instrument, and tension data is modeled by software to return soil hydraulic properties. This method can be utilized to measure soil water retention and hydraulic conductivity and give insight into differences in treatments or environmental dynamics over time. Initial establishment requires a user, but data acquisition is automated with the instrument. Soil hydraulic properties are not easily measured with traditional experiments, and this protocol offers a simple and optimal alternative. Interpretation of results and options for extending the data range are discussed.

Improving Subsurface Soil Moisture Estimation Using a 2‐Dimensional Data Assimilation Framework Incorporated With a Dual State‐Parameter Scheme

AbstractAccurate subsurface soil moisture (SM) estimation is critical for vegetation growth, drought monitoring, and climate change mitigation, yet remains a significant challenge. Previous data assimilation (DA) approaches are limited to only surface SM assimilation. In this study, we utilized the proxy subsurface SM estimated via the exponential filter method (ExpF) as another assimilation variable in our 2‐dimensional DA. Meanwhile, the dual updating DA scheme was implemented to simultaneously update model parameters and states. The two DA pathways were incorporated into the proposed framework (DA_1E_D), which enhanced the subsurface SM accuracy, with the effects of 2‐dimensional assimilation being more significant. Under 2‐dimensional DA, the information transfer between layers was more accurately characterized, leading to overall improvements with unbiased root‐mean‐square error (ubRMSE) reductions of 0.015 and 0.005 m3 · m−3, and Kling–Gupta efficiency (KGE) increases of 0.248 and 0.067 for surface and subsurface SM, respectively, across five SM networks. The soil thickness (d2) and hydraulic conductivity exponent (expt2) are the most influential parameters affecting subsurface SM dynamics through model propagation. DA_1E_D also outperformed ExpF in subsurface SM accuracy, particularly in SM networks with weak surface‐subsurface correlation, achieving an average ubRMSE reduction of 0.003 m3 · m−3 and an average KGE increase of 0.202. It was also applied to Soil Moisture Active Passive data at regional scale, demonstrating significant improvements. The model surface‐subsurface SM coupling was adjusted toward the actual coupling after subsurface assimilation and dual updating. This study may provide new insights into the diagnosis and refinements of the model representation of surface‐subsurface processes.

A generalized van Genuchten model for unsaturated soil hydraulic conductivity

AbstractThe hydrodynamics of variably saturated soils or porous media in general are described via nonlinear functions of water retention and hydraulic conductivity, which facilitate the simulation of various mass and energy transport processes (e.g., water, heat, contaminants, colloids) within the porous medium. We set out to derive improved functions for more accurate estimations of soil hydraulic functions to advance the simulation of porous medium hydrodynamics. A new model is proposed for estimating the unsaturated hydraulic conductivity (UHC) from a soil water retention (SWR) function that is parameterized via nonlinear regression of measured data. The function can be viewed as a generalized van Genuchten (1980) model (GVG). We tested the new SWR and UHC expressions for numerous data sets from literature that cover a wide range of soil textures. Our comparisons reveal more accurate estimations using the GVG model by comparison with the original van Genuchten model.

Sequential Gaussian simulation for mapping the spatial variability of saturated soil hydraulic conductivity at watershed scale

Sequential Gaussian simulation for mapping the spatial variability of saturated soil hydraulic conductivity at watershed scale