SSS6.3

Abstract – A new approach for water content determination in an in situ soil at depths ranging from the soil surface down to a few meters in soil profile is under development. The concept of this method is based on a core drill that will be equipped with a multi-probe sensor working at  radio and  microwave frequencies. The objective of the presented research focuses on the study of the multi-probe sensor that was carried out on sandy soils and clay.

This solution is based on reflection and transmission measurements using several probes arranged on the circumference of a metal tube. The use of various probes allows us on one hand to detect thresholds of the water in soil and on the other hand to diagnose the homogeneity of the material under test. This sensor is incorporated in a test bench composed of a VNA and a Switch Matrix that allows the VNA to connect with the 6 probes of the sensor. The measurements are the reflection of each probe and the transmission between two identified probes in a band of frequencies between 100MHz and 12GHz.

The first series of measurements with the multiprobe sensor was carried out on sand containing 0 to 20% water with increments of 5%. From the reflection coefficient values of each probe and the transmissions between two respective probes, we were able to verify the variation related to the increase of the water content in the sand. This determination of the water content is made from the modulus of the reflection coefficient and the different cases of transmissions between two probes.

In conclusion, a new concept of a multi-probe sensor, for the determination of a soil moisture profile in the relatively loose and homogeneous sandy and clayey soil has been developed and tested. Thus, we were able to evaluate thresholds of water content in the sand of around 5% with this sensor. In order to continue the study of the sensor, we now plan to test more complex soils, but especially to extrapolate this multi-probe sensor to a system using a core drill to increase the depth of testing. This is a solution to characterize soils without sampling them. Especially, it is hoped that with the developed sensor a soil profile can be measured down to several meters in depth.

Acknowledgment : This work has been supported by the Polish National Agency for Academic Exchange under Grant No. PPI/APM/2018/1/00048/U/001.

How to cite: Sabouroux, P., Sparma, F., and Szypłowska, A.: New approach to water content measurements in soil core using microwave probing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1350, https://doi.org/10.5194/egusphere-egu22-1350, 2022.

Soil water retention curves (SWRCs) provide information on the energy status of soil water and its availability to plants and are therefore important for irrigation management. SWRCs have traditionally been determined in the laboratory. With the development of new equipment that allows continuous measurement of soil water content and matric potential, it is possible to generate SWRCs in the field. The objective of our study was to determine SWRCs from continuous measurements in the field using dielectric methods and to see how SWRCs change over time. We compared them to SWRCs determined in the laboratory on undisturbed soil samples using the evaporation method (HYPROP®, METERgroup, Munich, Germany). Both the SWRCs determined in the field and in the laboratory were based on drying data only. Our results show significant differences between the SWRCs determined in the laboratory and in the field. For a given value of the matric potential, SWRCs in the laboratory often reach higher water contents, which can be attributed to the difference in soil wetting in the laboratory and in the field. The SWRCs constructed in the field also exhibit temporal variations. Therefore, we can conclude that the use of a single laboratory-constructed SWRC is not sufficient to describe the relationship between soil water content and matric potential.

How to cite: Pečan, U., Pintar, M., and Kastelec, D.: Soil water retention curves determined in the laboratory and in the field, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1450, https://doi.org/10.5194/egusphere-egu22-1450, 2022.

Water potential directly controls the function of leaves, roots and microbes, and water potential gradients drive water flows throughout the soil-plant-atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in-situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely-sensed proxies. Together, these considerations offer a roadmap for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modeling uncertainties.

How to cite: Novick, K., Ficklin, D., Baldocchi, D., Davis, K., Ghezzehei, T., Konings, A., MacBean, N., Raoult, N., Scott, R., Shi, Y., Sulman, B., and Wood, J.: Confronting the water potential information gap, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2086, https://doi.org/10.5194/egusphere-egu22-2086, 2022.

Water status in almond and walnut orchards is critical in optimizing irrigation management practices since it affects productivity, nut quality, and composition. Water status is frequently determined by the midday stem water potential (SWP) of almond and walnut orchards. Using SWP, allows for determination of the water status of almond and walnut trees, as well as to compare stress between days. SWP measurements are collected on a tree-by-tree basis and do not provide information on spatial variability or the comparison of different time periods because the recorded value is affected by both soil water content and the weather conditions on the day of the measurement, which makes comparisons between different time periods impracticable unless SWP readings are normalized by a baseline (non -water stressed tree under similar environmental conditions). The utilization of a very high-resolution manned and unmanned aerial vehicles equipped with multispectral cameras is being used to record the variability of different spectral features from the plant to the field-scale.

With this research, we aimed to construct a data-driven model based on the Random Forest (RF) ensemble technique to predict SWP spatial variability in drip and sprinkler irrigated almond and walnut orchards in the Central Valley of California, USA. For the training of the RF model, SWP data from three crop seasons from 2019 to 2021 were used along with Landsat-derived evaporation fraction, normalized vegetation index, soil water content from neutron probe, meteorological parameters, and soil properties as covariates. The results demonstrate that the trained model was capable of predicting the SWP at higher spatial resolutions when aerial imagery data were used in conjunction with the trained model. The R² values for training and validation for almond and walnut orchards were 0.92 and 0.84, respectively. Using the results of the comparison between the pressure chamber measurements and the RF model predictions, we were able to estimate SWP with root mean square errors (RMSE) of 2 and 1.2 bars, mean absolute errors (MAE) of 1.2 and 0.96 bars, and mean bias of 0.62 and 0.48 bars in almond and walnut orchards, respectively. These results demonstrate the capabilities of a machine learning-based RF algorithm for predicting the SWP at higher spatial resolutions by using satellite, aerial imagery, and other meteorological variables as covariates. Spatial maps of SWP can be used by growers to optimize precision irrigation management in orchards characterized by water induced spatial variability.

How to cite: Kisekka, I. and Peddinti, S.: Water status monitoring in almond and walnut orchards using random forest and remote sensing, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6128, https://doi.org/10.5194/egusphere-egu22-6128, 2022.

In precision irrigation, a wise approach for decision making would consider not only a response to the current observations by sensors or other means. It should also consider forecasting the near future and prospecting hypothetical scenarios for water requirements and potential yield. These would require simulations which, in turn, demand for site specific characterization of the Soil-Plant-Atmosphere scenario. While crop parameters can be retrieved relatively easy from remote sensing, the availability of precise soil data would be limiting the accuracy of the simulations. Such limitations could be alleviated by in-situ calibration of the soil-crop models where the simulated soil water budget is contrasted with observed series of crop’s vigor and water state. This contribution describes an example where the soil waterholding capacity was estimated from inverse modelling during the seasons of 2020 and 2021 in a vineyard near Lleida, Spain.

How to cite: Casadesus, J. and Bellvert, J.: In situ calibration of soil-plant-atmosphere simulations, for precision irrigation practice, using timeseries of crop’s vigor and water state, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8928, https://doi.org/10.5194/egusphere-egu22-8928, 2022.

The increased water demand from the irrigated agriculture sector calls for the introduction of more efficient water saving strategies in order to maintain sustainable crop production. This need is particularly urgent in Mediterranean climate areas, already deeply affected by water scarcity and soil depletion issues. In this context, the use of advanced near surface geophysics monitoring techniques can help to characterize the temporal and spatial soil physics dynamics and the related soil moisture processes active at the root-zone level aiming at optimizing the irrigation management.

In this study, the electrical resistivity imaging (ERI) technique was applied for characterizing the mass exchange mechanisms acting within the soil-plant system of heterogeneous micro-irrigated orchards. In particular, repeated ERI surveys were carried out in a citrus orchard (Citrus sinensis (L.) Osbeck), located in Eastern Sicily, southern Italy, characterized by the presence of crop heterogeneity features within the same plant framework, both in terms of variety and age (i.e. 3-year old Tarocco Ippolito and 8 year-old Tarocco Nucellare Scirè, respectively).

The time-lapse ERI monitoring has permitted to identify specific wetting fronts and root water uptake (RWU) patterns effective in the soil / root system during dynamic condition (i.e. an irrigation cycle), mostly affected by the complex nonlinear interactions (i.e., soil evaporation, RWU and soil water redistribution) operating under crop heterogeneous conditions. Moreover, the use of soil moisture sensors installed in situ has permitted to identify a clear relationship between the changes in the soil water content observed in the field and the soil electrical resistivity (ER) characteristics with reference to the different types of analysed tree crops (with overall R² value of 0.63). Specifically, it has been observed that the soil evaporative process, represented by an increasing of ER values, was greater in the younger citrus trees due to their lower vegetation groundcover and roots development. While, the greater soil moisture changes (resulting in greater ER decreasing patterns) occurred for the mature tree crops, characterized by higher root biomass, because its initial soil water condition was lower in comparison to the young tree crops.

How to cite: Vanella, D., Longo-Minnolo, G., Ramírez-Cuesta, J. M., Longo, D., D'Emilio, A., and Consoli, S.: Characterizing soil-plant interactions under heterogeneous micro-irrigated citrus orchards, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9931, https://doi.org/10.5194/egusphere-egu22-9931, 2022.

Mitigating plant water stress while reducing irrigation is one of the biggest challenges that sustainable agricultural practices aim to tackle. The rhizosphere is the main unknown component controlling the water distribution in the soil, but non-destructive observations of root physiology are often lacking due to methodological limitations.  

Numerous studies relate the use of electrical resistivity tomography (ERT) or stem-based methods to measure soil water content changes associated with root water uptake (RWU) in the rhizosphere area. Nevertheless, geoelectrical data are correlated with many rhizosphere parameters and their interpretation needs to be supported by physics-based models of root hydrology.

Here, we use a Data Assimilation (DA) framework to combine geoelectrical data with a hydrological model (Mary et al. 2021). DA offers the possibility to estimate model parameters governing RWU, such as in the well-known Feddes approach while introducing data observations to update them. 

In a synthetic experiment mimicking a top-down infiltration in a rhizotron containing a wine plant (Vitis Vinifera), we simulated different scenarios of ERT data assimilation with the CATHY surface-subsurface hydrological model. The rooting depth associated with the Feddes parameters are perturbed to generate the ensemble states. At each observation time, model states and root depth parameters are updated using the Ensemble Kalman Filter (ENKF). 

Expected results aim to demonstrate (i) what is the best ENKF scheme to integrate ERT measurements with the hydrological model and (ii) how much the uncertainties on the Feddes parameters can be reduced with the assimilation of ERT data. In a future work, the best approach identified will be applied to real soil and plant observation datasets.

Mary, B., Peruzzo, L., Iván, V., Facca, E., Manoli, G., Putti, M., et al. (2021). Combining Models of Root-Zone Hydrology and Geoelectrical Measurements: Recent Advances and Future Prospects. Front. Water 3, 767910. doi:10.3389/frwa.2021.767910.

How to cite: Mary, B., Botto, A., Iván, V., Peruzzo, L., Chou, C., Wu, Y., Cassiani, G., and Camporese, M.: Assimilation of ERT data to improve Feddes parameters in a hydrological model during a root water uptake experiment, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6648, https://doi.org/10.5194/egusphere-egu22-6648, 2022.

Due to the spatial heterogeneity, root presence and other specific properties, measurement of forest soil hydraulic properties is difficult. Forests are generally hydrologically important systems that can mitigate negative climate change impact, and specifically, forest soil represents crucial water reservoir. A common forest management strategy is to plant monocultural stands of trees. Due to the differences in trees characteristics, e.g., root system, litter and leaf area, the development of soil undergoes specific changes according to the planted species. The main aim of this study is to investigate the connection between the tree species and hydro-physical properties of forest soil with focus on long term soil moisture and temperature regime monitoring. This research brings an early-stage view to data obtained from May 2021 up to nowadays.

A set of 55 TDT (time domain transmission) soil moisture and temperature sensors were installed into three nearby locations. In each of those a monoculture stand of beech (Fagus sylvatica), spruce (Picea Abies), and larch (Larix Decidua) are planted. Half of the sensors are used for measuring the mineral soil moisture in depth of -15 to -29 cm below soil surface and point temperature of -23, -15, +5 cm relative to the surface, the rest is used for measuring the topsoil moisture from the surface to the depth of -14 cm and point temperatures in levels of -8, 0 and +15 cm.

Results shows distinct differences in soil moisture among tested tree species. After longer period without precipitation (period of soil-water loss), the highest differences in volumetric water content (VWC) were observed. After one-month period without rain in early summer, mean values of VWC for topsoil were 35% for beach, 28% for larch, and 21% for spruce. Overall, the beech stands showed the highest ability to maintain soil water after periods of soil water loss and therefore, potentially exhibited the strongest resistance towards soil drought. By contrast, spruce tends to lose water relatively fast which can be problematic especially in events of long-term drought. For the surface temperature during vegetation season, the highest values were observed in larch stands followed by spruce and the lowest in beach. These findings probably corresponding to different solar radiation permeability of tree canopies. The observed effects of tree species on soil moisture and temperature should be considered for hydrological modelling, future forest planning, and water management improvement of forest soil.

How to cite: Kuželková, M., Jačka, L., Kovář, M., and Hradilek, V.: Effect of different tree species on soil moisture and temperature. Early-stage view of continuous forest soil regime monitoring., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-7678, https://doi.org/10.5194/egusphere-egu22-7678, 2022.

In the Galapagos archipelago, about 96% of the land area has been declared a Protected National Park in 1959. Of the four inhabited islands, Santa Cruz is the most populated, with 15,393 inhabitants in 2010. The non-protected area in Santa Cruz corresponds to the south-central part of the island and the bay area around Puerto Ayora. Over the period 1961-2018, the agricultural land expanded from 6% to 67% of the non-protected land area. In a field-based study around the settlement of Santa Rosa, we monitored hydrometeorological and soil physical and hydrological properties over the period July 2019-December 2021. Six sites were monitored including two replicates per land cover type: (i) native Miconia forest, (ii) agricultural land, and (iii) abandoned farmland with invasive species. The spatiotemporal distribution of rainfall and air temperature over the sites is recorded via one weather station, four rain gauges, air temperature and relative humidity sensors; and the atmospheric input and rainfall were sampled at biweekly basis. After pedological characterization of the six profiles, soil and rock samples were taken per horizon for analysis of elemental chemistry, mineralogy, texture, C/N ratio, and organic matter content. Upslope of the soil profiles, TDR probes measured volumetric soil moisture content, soil electrical conductivity and temperature; and soil water samples were taken using suction lysimeters. 

Over the monitoring period, the highest rainfall amounts were measured in January (226 to 265 mm), and the lowest in May (20 to 25 mm). Most of the year, the relative air humidity is close to 100% with values dropping to 60% in March. The lowest air temperatures (15 °C) are measured in August, and the highest (29 °C) in March and April. Solar radiation strongly fluctuates from 80 W/m² during the rainiest month to 220 W/m² in March. Deeply weathered soils are developed on basaltic parent material and have a depth up to 50 cm. Soils are loose and lack macro-structure. The dry bulk density varies as a function of land cover, with the highest bulk densities of 0.9 g.cm^-³ in abandoned farmlands, intermediate values of 0.7 g.cm^-³ in agricultural land and lowest values of 0.5 g.cm^-³ in forests. Although the air temperature is similar amongst all six sites, there are clear differences in the soil temperature between agricultural and abandoned farmland, and forest sites. Our data show that soil moisture is systematically higher in the two forest sites compared to the agricultural and abandoned sites.  

As such, the field data provide evidence of the impact of forest clearing on soil physical properties and soil-water balance.

Keywords

Soil weathering, soil water balance, Galapagos, basaltic soils, Agricultural expansion

How to cite: Alomia, I., Paque, R., Molina, A., Montes, Y., Dixon, J., and Vanacker, V.: Land-use change impacts on soil water balance in Santa Cruz Island, Galapagos, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8297, https://doi.org/10.5194/egusphere-egu22-8297, 2022.

Knowledge about soil water balance and ecosystem water partitioning is crucial for managing soils in semi-arid areas like the Sahel, but hydraulic parameters are hardly available to run either parsimonious or detailed process models. This study aims at bridging this parameterization gap in a typical deep (> 2m) loamy sand soil from the groundnut basin in Senegal[1]. Five approaches of soil hydraulic parameterization with a range of different complexity were compared: (1) the lookup table of Carsel and Parrish (1988) that use only the soil texture class known as “Class PTFs”, (2) Rosetta PTFs from only topsoil characterization, (3) Rosetta PTFs with a detailed multilayer soil characterization, and inverse estimation from soil moisture using Hydrus-1D, considering the soil column either as (4) a single soil material and (5) with three-layered soil material. We compared the predicted (i) soil water content (SWC) with high-frequency measurements from 15 cm down to 200 cm deep and (ii) actual evapotranspiration (ET) with Eddy Covariance (EC) data during four consecutive growing seasons under a rotation of pearl millet and peanut crops. The simplest methods (1 & 2) resulted in a significant bias of the predicted SWC, with, however, some predictive ability of Method 2 to simulate the general trends of Swc, especially under peanut crops. Method 3 behaved reasonably with average RMSE for SWC, varying between 0.029 and 0.023 cm^-3 cm^-3. Method 4 further improved the predictions with RMSE ranging from 0.013 to 0.020 cm^-3 cm^-3. The best agreement was found under peanut using Method 5 (RMSE ≤ 0.013 cm³ cm^-3). Methods 3, 4 or 5 behaved satisfactorily for predicting ET whatever the crop, e.g. Method 4 (RMSE= 0.05 cm day-1, NSE= 0.9 and R²= 0.93) for pearl millet.

We showed that inverse modelling should be preferred over using PTFs when studying water fluxes and evapotranspiration in cultivated Sahelian soils.

How to cite: Diongue, D. M. L., Do, F. C., Stumpp, C., Orange, D., Jourdan, C., Sow, S., Faye, S., and Roupsard, O.: Comparing the performances of Pedotransfer Functions with Hydrus 1D Inverse Parameters Estimation in a deep cultivated sahelian soil, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9499, https://doi.org/10.5194/egusphere-egu22-9499, 2022.

Proper parameterisation and conceptualisation of the commonplace process of infiltration into the soil is still a topic of debate. Measuring soil water distribution in a spatio-temporally continuous manner can advance our understanding of infiltration in non-uniform flow networks and the soil matrix. At the same time, we find different measurement techniques bound to different concepts and scales, which make a general interpretation and quantification of the data still a challenging task.

We present results from several irrigation experiments at the plot and hillslope scale, in which we combined hydrological, geophysical and remote sensing techniques. On this basis, we will point out how different techniques have advantages and pitfalls for their interpretation. E.g. despite the different scales, we found hydraulic conductivity measured in soil cores in good coherence with plot scale experiments, while in-situ measurements with a constant head permeameter deviated substantially. Another example are multispectral data of the changing surface conditions during irrigation which cannot discern different subsurface infiltration patterns, once the surface becomes sufficiently wet.

Since any parameterisation links back to the conceptual and numerical models, we have developed an alternative concept to simulate soil water infiltration and redistribution based on a Langangian approach using film flow in representative macropores and a 2D random walk for the soil matrix. Simulations highlight the inherently combined effect of antecedent state and connected preferential flow networks on the respective generation of non-uniform infiltration patterns.

How to cite: Jackisch, C. and Allroggen, N.: Initial non-uniform soil water redistribution as inherent hydrological process – from field experiments to model insights, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-12777, https://doi.org/10.5194/egusphere-egu22-12777, 2022.

Saturated and near-saturated hydraulic conductivities K (mm/h) are important soil properties that determine the partitioning of precipitation into surface runoff and infiltration and indicate soil susceptibility to preferential flow as well as soil aeration properties. Measurements of saturated and near-saturated soil hydraulic conductivities are time consuming and not practical for larger scales where they are mostly needed. The research community has therefore put effort in deriving pedotransfer functions to predict K using proxy variables. The precision of such pedotransfer functions has been very modest, however. As a result, recent studies have focused on assembling and analyzing bigger databases, aiming to find better predictors for the saturated and near-saturated soil hydraulic conductivities. A prominent example is the meta-database on tension-disk infiltrometer data compiled by Jarvis et al. (2013. Influence of soil, land use and climatic factors on the hydraulic conductivity of soil. Hydrology and Earth System Sciences 17(12), 5185-5195), who found that climate variables were better correlated with K than soil properties. OTIM (Open Tension-disk Infiltrometer Meta-database) builds on this database, adding 577 new data entries collated from 48 additional peer-reviewed scientific publications. OTIM contains more detailed information on local climate as well as land use and management than its predecessor. In this study, we present OTIM together with a meta-analysis on topsoil K from supply tensions ranging between 0 and 10 cm. Evaluating Spearman coefficients, we found that near-saturated K correlated best with the mean diurnal temperature range (0.54), the aridity index (-0.47) and the precipitation in the driest quarter of the year (-0.44). It may be speculated that larger diurnal temperature ranges stimulate the vertical movement of soil fauna while dry climates may lead to well-developed networks of shrinkage cracks. Notably, the correlations vanished for all considered climate variables at and close to saturation. At saturation, bulk density exhibited the highest correlation (-0.36). Furthermore, we found that arable land uses were related to strong decreases in saturated, but only moderate reductions in near-saturated K. This is well explained by effects of tillage and trafficking. Tillage disconnects macropores, diminishes the presence of macrofauna and thus leads to smaller saturated K; but for some weeks after seedbed preparation, it also improves near-saturated K by creating a well-connected inter-aggregate pore-network in the topsoil. Trafficking, in contrast, leads to soil compaction and higher bulk-densities. We found that soil compaction strongly reduced K for all investigated tensions. In line with the above explanations, we observed that no-till agriculture was associated with decreased K compared to conventional and reduced tillage for all considered tensions. Moreover, infiltration measurements conducted soon after seedbed preparation led to larger K, also for all investigated tensions. Our study demonstrates the importance of land use, soil management and time of measurement relative to tillage for predicting saturated and near-saturated K. Besides, we found confirmation that climate variables have a large impact on near-saturated K. The underlying mechanisms are however not clear and should be investigated in future studies.   

How to cite: Koestel, J., Blanchy, G., Albrecht, L., Bragato, G., and Jarvis, N.: A meta-analysis of near-saturate hydraulic conductivities using the newly compiled Open Tension-disk Infiltrometer Meta-database OTIM, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-5290, https://doi.org/10.5194/egusphere-egu22-5290, 2022.

Over the past two centuries, studying the infiltration process has received significant efforts resulting in numerous infiltration models being developed. These models depended on specific soil properties, and were influenced by initial and boundary conditions. They were also classified into two major categories: empirical and conceptual models, although the boundaries between those two categories can be debated for several models. The empirical models solved the infiltration problem by curve-fitting measured data into algebraic equations. In contrast, the conceptual approaches built on earlier concepts, mainly derived from the fundamental flow models, and then formulated analytical solutions applied to the infiltration problem. In this review, we create an inclusive survey covering the diverse spectrum of published infiltration modeling to understand the philosophy and evolution of those empirical and conceptual models across the years. After providing a full historical retrospective of infiltration models, we explored the model parameters and their evolution with time. We also reviewed the different methods applied to estimate the basic and common infiltration parameters, as well as the challenges that arise by such methods.

How to cite: Abou Najm, M., Basset, C., Angulo-Jaramillo, R., Bagarello, V., Di Prima, S., Iovino, M., Lassabatere, L., and Stewart, R.: A critical review of conceptual and empirical approaches to characterize infiltration, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10912, https://doi.org/10.5194/egusphere-egu22-10912, 2022.

The beerkan infiltration experiment is carried out by inserting the ring a short depth into the soil and establishing a positive head of water on the infiltration surface for at least a part of the run. Nevertheless, the data are analyzed by assuming a fully unconfined infiltration process (ring insertion depth, d = 0) and a null ponded depth of water (H = 0). The influence of ring insertion and ponded water on an infiltration process of 2 hours sampled every minute was tested in this numerical investigation. Five soils varying from sand to silt loam, three ring radii (5 - 15 cm) and the beerkan specific range of values for both d and H, that is between 0 and 1 cm were considered. The differences between the theoretical (d = H = 0) and the practical (d = H = 1 cm) setups varied from -10.4% and +8.6% for the mean infiltration rate and from -10.2% to +8.3% for the final cumulative infiltration. These differences were small and they decreased by considering a soil dependent ring radius. In particular, nearly negligible differences were detected using a small ring in coarse-textured soils and a large ring in fine-textured soils. In the coarser soils, inserting the ring and establishing a ponded depth of water did not alter appreciably the estimated coefficients of the two-parameter infiltration model with the Cumulative Linearization method since these coefficients differed between the theoretical and practical setups by no more than 9.2%; while in fine soils, linearization could not be possible regardless of the considered setup or it was the use of d = H = 1 cm instead of d = H = 0 that impeded a convincing linearization of the data. In conclusion, the satisfactory correspondence, in many circumstances, between the theoretical and the practical beerkan infiltration experiment reinforced the interest for this simple experiment as a practical means to collect infiltration data in the field. Other numerical tests should be carried out to reach more general conclusions, also considering heterogeneous soil conditions. The numerical results should represent the first step of a wider investigation that also includes laboratory and field experiments.

How to cite: Iovino, M., Bagarello, V., Dohnal, M., and Lai, J.: Testing effects of deviations from theory for beerkan infiltration experiments, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8703, https://doi.org/10.5194/egusphere-egu22-8703, 2022.

Water-repellent soils usually experience water flow impedance during the early stage of a wetting process followed by progressive increase of infiltration rate. Current infiltration models are not formulated to describe this peculiar process. Similarly, simplified methods of soil hydraulic characterization (e.g., BEST) are not equipped to handle water-repellent soils. Here, we present an adaptation of the BEST method, named BEST-WR, for the hydraulic characterization of soils at any stage of water-repellency. We modified the Haverkamp explicit transient infiltration model, included in BEST for modeling infiltration data, by embedding a scaling factor describing the rate of attenuation of infiltration rate due to water repellency. The new model was validated using analytically generated data, involving soils with different texture and a dataset that included data from 60 single-ring infiltration tests. The scaling factor was used as a new index to assess soil water repellency in a Mediterranean wooded grassland, where the scattered evergreen oak trees induced more noticeable water repellency under the canopies as compared to the open spaces. The new index produced results in line with those obtained using the water drop penetration time test, which is one of the most widely test applied for quantifying soil water repellency persistence. Finally, we used BEST-WR to determine the hydraulic characteristic curves under both hydrophilic and hydrophobic conditions.

How to cite: Di Prima, S., Stewart, R. D., Abou Najm, M. R., Ribeiro Roder, L., Giadrossich, F., Angulo-Jaramillo, R., Yilmaz, D., Roggero, P. P., Pirastru, M., and Lassabatere, L.: BEST-WR for the hydraulic characterization of hydrophilic and water-repellent soils, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1385, https://doi.org/10.5194/egusphere-egu22-1385, 2022.

Infiltration trenches are compensatory techniques that have been settled up for decades. These aim to store the stormwater previously collected and infiltrate water into its banks. The objectives of the proposed study consist of modeling the water dynamics in an infiltration trench in order to evaluate its hydraulic performance. The studied trench is installed in the city of Recife (Pernambuco-Brazil, Brazil). We analyzed the response time of the infiltration system, the percentage of the infiltrated volume, and the dynamics of water storage processes for an extensive series of several rainfall events. We used the PULS method to model the events and quantify the contributions of each compartment to the water budget (infiltration, evaporation, etc.). Both observations and modeling demonstrated that the infiltration trench had a positive effect, with high performance, allowing the infiltrating of a large part of the drained volume. The infiltration trench achieved its objective of decreasing the volume drained on the surface. In this research, we also question the changes in the soil characteristics with time (in particular clogging of the banks) and the potential occurrence of preferential flow.

How to cite: Coutinho, A. P., Lopes Bezerra, P. H., Lassabatere, L., Neto, S. M. D. S., Melo, T. D. A. T., Antonino, A. C. D., Angulo-Jaramillo, R., and Montenegro, S. M. G. L.: Water dynamics in an infiltration trench in an urban centre in Brazil, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9216, https://doi.org/10.5194/egusphere-egu22-9216, 2022.