Low-water content soil moisture relations are increasingly important given current trends of climate change, desertification, and growing interest in extreme environments like those of Antarctica and Mars. Whereas most parametric models of soil water retention were developed for the intermediate and wet ranges of moisture, some alternatives published in the last three decades address water retention down to oven dryness. Such models can be strengthened and made more versatile with a deeper understanding of the physical meaning of parameters used in them.

For the shape of the dry-range retention curve, a logarithmic relation has repeatedly been shown to work well, and is consistent with accepted theories of adsorption. Fitted values of the log function’s coefficient relate closely to the specific surface area of the medium.

The lower limits of water content and matric potential require more explication. Various observers have noted problems that arise with the use of a nonzero residual water content as the lower limit. In practice, this quantity is not measured but obtained as a fitting parameter, whose value depends not on a physical property but on how far the available measurements extend into the dry range. In parametric models it can be useful for applications in which the water content never goes below the intermediate range dominated by capillary processes.

The actual lower limit of water content depends on how its zero is defined. The most common definition is based on equilibration in an oven at a particular temperature, commonly 105° C. Ambiguity arises from the dependence of the soil water on the generally uncontrolled relative humidity within the oven. Application of the Kelvin equation with reasonable assumptions about the outside air and its exchange with the inside air can indicate an equivalent matric potential of the oven-dry state, typically about -1 GPa. Logarithmic extrapolations of dry-range retention measurements intersect the water content=0 axis at values comparable to this, with variations likely related to particular conditions in the lab and oven. A way of resolving this ambiguity is to define zero water content not in terms of oven temperature but rather a specified matric potential of equilibration. An attractive possibility, convenient in SI units, is to make it exactly -1 GPa.

Neither the traditional nor this proposed definition of zero water content identifies a state where no water molecules remain in the soil. Measurements at temperatures of hundreds of degrees C show that soil water contents can be lower than these defined zero levels by as much as 2% or more. Our standard scale of water content, therefore, is a relative scale, analogous to the Celsius scale for temperature. Consequently negative values of soil water content have a valid physical meaning. To acknowledge this fact and resolve ambiguities, more rigorous definitions as proposed here are thus necessary for applications dealing with the extremely dry conditions that are becoming increasingly important.

How to cite: Nimmo, J. R.: Soil water retention parameters in the dry range—what is the physics?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9991, https://doi.org/10.5194/egusphere-egu23-9991, 2023.

The WAPPFRUIT project is related to the optimisation of irrigation techniques in the Piemonte Region, Northwest Italy. The main goal is to control irrigation to understand if it is possible to reduce the volume of water used for irrigation and also save energy. The project involves several stakeholders, among which Politecnico and the University of Torino, Piemonte Region, Agrion Foundation for research in agriculture, and three farms (two apple orchards and one Actinidia orchard). The optimisation relies on soil matric potential measurements at several soil depths. The irrigation will be triggered using a particular algorithm which is based on a system of matric potential thresholds at the depths of 20 and 40 cm. These thresholds are based on soil texture, and vegetation species (including root depth). 

Each orchard is divided into two parts: an “experimental area” where the irrigation algorithm will be tested, and an area that will be irrigated as usual by farmers. Each orchard is equipped with four to six measurement nodes, with soil water content and soil matric potential profile having measures at 20, 40, and 60 cm of depth. 

The retention curves, as well as the spatial and temporal variability of soil water content and soil matric potential, can be inferred from measures, which reveal high volumes of water used for irrigation (frequently the soil was near saturation conditions). In addition, all the soils show, in the retention curves, a hysteresis due to wetting/drying cycles. 

The farmers continued to irrigate as usual in the two parts of the fields up to October 2022. Hence, to investigate the matric potential behavior and identify good estimates of thresholds, modeling approaches are important for the simulation of soil without irrigation, to understand when water stress conditions could occur. To this purpose, two models are used to simulate the water fluxes in the atmosphere and the soil (and, particularly, the matric potential). The two models adopted are the hydrological model Hydrus 1D and the land-surface model CLM5. Forcing the models with the precipitation summed to irrigation of the fields, Hydrus, in its 1D formulation did not yield reliable results, although more studies are needed to fully understand the causes for the misrepresentation. The CLM model yields instead more reliable outcomes. The CLM model is then used to simulate the behavior of the soil matric potential under the hypothesis of no irrigation. The results illustrate that the matric potential threshold for triggering irrigation could be around -50 kPa at 20 cm, whereas the threshold at 40 cm for the deactivation of irrigation could be around -40 kPa for the sites with apple orchards. The site with Actinidia could have the aforementioned thresholds equal to -40 kPa at 20 cm and -30 kPa at 40 cm.

How to cite: Gisolo, D., N'sassila, M., Gentile, A., Pettiti, F., Barezzi, M., Garlando, U., Nari, L., Ferraris, S., Demarchi, D., and Canone, D.: Wappfruit: a project for the optimisation of water use in agriculture, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1485, https://doi.org/10.5194/egusphere-egu23-1485, 2023.

Irrigation and fertilization are essential to increasing crop yield and affect vegetable production and food security. Conventional irrigation and fertilizer application methods often exceed the crop requirements. Moreover, nitrate pollution of groundwater from agriculture is caused by the asynchrony between nutrient availability and crop demand and is an issue of major concern in many regions. As water and nutrients limitations will be more frequent in the coming decades due to climate change along with regulations aiming at protecting water resources, there is a need for innovations in agricultural production to improve water and nutrient use efficiencies. Subsurface drip fertigation (SDF) is the fertigation (irrigation combined with application of dissolved fertilizer) of crops through buried driplines which include built-in emitters to drip water to the surrounding soil. This allows placing the water and fertilizers directly into a small soil volume in the rooting zone at just the rates needed by the plants. SDF systems have a great potential to minimize the movement of water and nutrients below the root zone when effectively managed. Through the combined application of nutrients and water, drought and nutrient stresses can be diminished and yield potentials optimized. SDF systems can therefore make cropping systems not only more environmentally friendly and sustainable, but also more resilient to climatic fluctuations.

The aim of our research is to contribute to the understanding of crop growth under SDF. The work presented here is the Subsurface Drip Fertigation Estimation Tool (SubFerT) which is available for farmers who want to integrate this fertigation system in their production. The tool is based on daily water and nitrogen balances at the field scale by modeling (a) crop growth and nitrogen uptake; (b) crop water requirements though daily ET₀ estimation using the Penman–Monteith equation, separation between evaporation and transpiration (dual Kc approach); (c) dynamics of water (irrigation, precipitation, root uptake, losses) and nitrogen (mineralization, denitrification, leaching) in the soil root zone. SubFerT-tool provides information on when and how much water and fertilizer to apply to crops grown under SDF system. This tool allows farmers to manage the fertigation of the crops under SDF in an efficient way. Additionally, the tool delivers daily time series of different variables involved in the balance: soil moisture, root uptake, deep percolation, total met transpiration, etc.

How to cite: Callau-Beyer, A. C., Mburu, M., Weßler, C.-F., and Stützel, H.: Subsurface drip fertigation estimation tool (SubFerT), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9560, https://doi.org/10.5194/egusphere-egu23-9560, 2023.

A distinct greening trend is evident in Asia, especially on the Chinese Loess Plateau (CLP), which is driven by climate change and human-induced revegetation projects, such as the Grain for Green (GFG) project launched in 1999. However, revegetation may cause below-ground soil drought via excessive consumption of deep soil moisture (SM). To ascertain the contributions of revegetation projects to the greening trend on the entire CLP, and then evaluate the spatial-temporal variations of soil drought, as indicated by the dried soil layer (DSL), we collected multisource satellite datasets from 1982 to 2019 on the CLP and measured SM to a depth of 500 cm on 20 occasions at 73 locations from 2013 to 2016 at a typical watershed. We found that the revegetation project failed initially to make a positive contribution in the first few years because of the drought conditions in 1999-2005; after 2005, the increasing trend of vegetation change on the CLP indicated that the revegetation project, as a type of external disturbance, began to improve vegetation growth, meanwhile the increased precipitation played a critical role. The contribution of the revegetation projects increased quickly until 2013, after which it remained stable and reached average values of 58.8%±19.34% in the representative areas that conducted the GFG project. The DSLs occurred at > 90% of the sampling sites within the watershed, and the spatially and temporally averaged DSL thickness (DSLT) and soil water content within the DSL (DSL-SWC) were 257 cm and 10.4%, respectively, which suggests that 51.4% of the 500-cm-profile is drying out below 125 cm. The DSLT and DSL-SWC demonstrated a moderate degree of variability (20% < CV < 84%) in space, and showed a moderate and weak temporal variability, in time, respectively. The temporal series of the mean spatial DSLT significantly correlated with climatic variables. The spatial variation of the mean temporal DSL-SWC differed significantly among the land uses and between shaded and sunlit aspects. Our results highlighted that the meteorological processes, land use, and topography played an essential role in shaping DSL variation and distribution pattern. Understanding this information is helpful for vegetation construction, soil and water conservation, and soil drought meditation via the best management practices in the CLP and other water-limited regions with deep soils.

How to cite: Wang, Y. and Liu, S.: Dynamics of deep soil drought triggered by revegetation across a semiarid watershed, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15914, https://doi.org/10.5194/egusphere-egu23-15914, 2023.

Agriculture is vital for human survival and irrigation water quality plays an important role in agricultural growing and harvest. Although Taiwan has abundant rainfall, the uneven distribution of rainfall in time and space makes the irrigation water management difficult. In the past two decades, climate change has led to frequent occurrence of extreme weather events and global disasters, and the increase in the frequency and intensity of extreme events enhances the potential disaster risk in Taiwan, impacting the water resource management severely. Meanwhile, industrial wastewater is a significant pollution source, and the surface water quality would be further deteriorated if the industrial wastewater was not treated properly before its release. In Taiwan, the needs of water resources for domestic and industrial uses have the higher allocation priority than that for agricultural use, considering the political concerns and economical contribution. Oftentimes, a supplementary water resource to meet irrigation need is required due to the scarce of available water resources. The situation may become even worse under the influence of climate change.

Given the information above, this study explored the irrigation water quality variation under the influence of climate change on agricultural water resource management. The Taoyuan City (including Taoyuan irrigation Shimen irrigation areas) were selected as the study area. The potential impact of climate change on irrigation water quality, considering factors of pollution discharges and economic development, was assessed. Adaptive strategies including stabilizing irrigation water demand, strengthening irrigation water supply and building an agricultural technology auxiliary system were discussed. The result showed that the increasing frequency of heavy rainfall events in Bade, Xinwu, and Guanyin Districts. The surface pollutant would be washed out easily during heavy rainfall events, impacting neighboring water bodies. On the other hand, drought events appear in Daxi and Fuhsing Districts in extreme climate events. Therefore, a new strategy for sustainable water management is needed.

How to cite: Huang, Y.-Z. and Fan, C.: Irrigation water quality management under the impact of climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3760, https://doi.org/10.5194/egusphere-egu23-3760, 2023.

The north-western part of the Padana Plain in Italy is the most important rice district in Europe. Recently, due to an increased frequency of water scarcity periods, the traditional wet seeding and continuous flooding irrigation has been replaced by dry seeding followed by a delayed flooding or by a turned irrigation. Despite the advantages that dry seeding has brought to farmers, this change is leading to unexpected problems, the main of which are: i) the lowering of groundwater levels in the first months of the agricultural season that is reducing groundwater contribution to water discharges in rivers and irrigation networks of the area, limiting the water availability for agricultural areas downstream; ii) a shift to June of the maximum rice irrigation requirement, leading to an exasperated competition between rice and other crops (e.g. maize).

In the contest of the MEDWATERICE (PRIMA Section2-2018) and RISWAGEST project (Regione Lombardia, RDP 2014-20), an experimental platform was set up in the core of the Italian rice area (Mortara, PV) to compare three rice irrigation strategies in the period 2019-2022: i) wet seeding and traditional flooding (WFL), ii) dry seeding and delayed flooding (DFL) and iii) wet seeding and alternated wetting and drying (AWD). Irrigation water use was monitored and all the other soil water balance components were quantified. At the field scale, irrigation use was found to be in the order: WFL > DFL > AWD, without penalizing rice production, while the temporal distribution of irrigation needs and percolation fluxes (i.e. groundwater recharge) changed as a function of the irrigation strategy.

Results achieved in the experimental platform were used to set-up a semi-distributed agro-hydrological model simulating water fluxes and storages of a rice irrigation district (about 1000 ha) close to the experimental platform. The modelling framework consists of three sub-models: i) one for the agricultural area, based on the physically-based SWAP (https://www.swap.alterra.nl/); ii) one for the channel network percolation; iii) one for the groundwater level dynamics. Once calibrated, the modelling system was used to explore the effects on the water resources of ‘what-if scenarios’ based on the adoption of specific irrigation strategies in the whole rice-cropped area of the district (about 90% of the agricultural surface) for the period 2013-2020. Besides the aforementioned WFL, DFL and AWD, the following strategies were additionally explored: i) dry seeding and fixed irrigation turns of 8 days (FTI) and ii) early seeding for the DFL irrigation technique (beginning of April). Three indicators were used to support the analysis: i) Water Application Efficiency - WAE, defined as the potential evapotranspiration divided by the irrigation reaching the fields plus rainfall, ii) Distribution Efficiency of the irrigation network - DE, defined as the irrigation reaching the fields divided by the irrigation discharge entering the district, iii) Relative Water Supply - RWS, defined as the irrigation discharge entering the district plus rainfall divided by the potential evapotranspiration. Water fluxes and indicators are calculated and discussed both for the entire agricultural season (April-September) and for the most critical month (June).

How to cite: Gilardi, G. L. C., Mayer, A., Rienzner, M., Ottaiano, G., Tkachenko, D., Romani, M., Cadei, E., and Facchi, A.: Modelling the impact of Alternate Wetting and Drying (AWD) rice irrigation on water resources in northern Italy, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12328, https://doi.org/10.5194/egusphere-egu23-12328, 2023.

Hydro-pedotransfer functions (hyPTF) are important methods to relate available knowledge about soil properties to soil hydraulic properties and model parameters to be applied in process models. At least more than four decades have been invested to derive such relationships. However, while models, methods, data storage capacity, and computational efficiency have advanced, there are fundamental issues related to the scope and adequacy of current hyPTFs, particularly when applied to parameterise models at the field scale and beyond. Much of the hyPTF development process has focussed on refining and advancing the methods, while fundamental questions remain largely unanswered, namely i) how should hyPTFs be built for maximum prediction confidence, ii) which processes/properties need to be predicted to move beyond the van Genuchten-Mualem based parameterisation of the Richards equation, iii) which new datasets and data coverage are needed, iv) how does the measurement process of soil hydraulic properties determine the construction of hyPTFs and at which scale, iv) how can we incorporate diverging scales (scale of derivation vs scale of application), and v) what scaling/modulation/constraining strategies are affective to make hyPTF predictions at field-to-regional scale appropriate and physically meaningful? These questions have been addressed in a joint effort by the members of the International Soil Modelling Consortium (ISMC) Pedotransfer Functions Working Group with the aim to systematise hyPTF research and provide a roadmap guiding scientists, reviewers, and make users aware of the shortcomings.

How to cite: Weber, T. K. D.: Hydro-pedotransfer functions: A roadmap for future development, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17595, https://doi.org/10.5194/egusphere-egu23-17595, 2023.

Climate projections strongly suggest that the 2022 sweltering summer may be a harbinger of the future European climate. Climate extremes (e.g., droughts and heatwaves) jeopardize terrestrial ecosystem carbon sequestration. The construction of an open digital twin of the soil-plant system helps to monitor and predict the impact of extreme events on ecosystem functioning and could be used to recommend measures and policies to increase the resilience of ecosystems to climate-related challenges. A digital twin refers to a highly interconnected workflow, with a data assimilation framework at its core to combine observations and process-based models, meanwhile accompanied by an interactive and configurable platform that allows users to create and evaluate user-specific scenarios for scientific investigation and decision support. Creating an open digital twin means creating a digital twin following Open Science and FAIR principles, both for data and research software. In this contribution, the STEMMUS-SCOPE model was used as an example to develop an open digital twin of the soil-plant system. We suggest our recently developed open digital twin infrastructure could serve as the backbone for an interoperable framework to facilitate the digitalization of other Earth subsystems (e.g., by simply replacing the soil-plant model). In addition, we show how software not designed initially as open can be adopted to create an open digital twin using containers - standardized computational environments that can be shared, reused and that foster reproducibility.

How to cite: Zeng, Y., Alidoost, F., Schilperoort, B., Liu, Y., Willem Grootes, M., Wang, Y., Song, Z., Yu, D., Tang, E., Han, Q., van der Tol, C., Zurita-Milla, R., Yang, M. Y., Girgin, S., Dzigan, Y., and Su, Z.: Towards an Open Digital Twin of Soil-Plant System Following Open Science, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9786, https://doi.org/10.5194/egusphere-egu23-9786, 2023.

Evaporation is a significant part of the water cycle and the main process for water vapor exchange between Earth's surface and atmosphere. Evaporation from bare soil consists of two main stages: stage 1, with a relatively high and often steady evaporation rate that is controlled mainly by atmospheric conditions, and stage 2, with lower and exponentially decreasing evaporation rates that are limited by the diffusive nature of the vapor flow and the hydraulic properties of the drying medium. In dry or drought conditions that are characterized with long dry spells, stage 1 is short and during stage 2 water is depleted from the top near-surface soil, forming a dry soil layer (DSL), where water flows in vapor phase only. Measuring bare soil evaporation over larger areas is challenging due to the natural heterogeneity. These measurements become even more challenging under dry conditions, due to the equipment needed for capturing low fluxes under extremely high liquid water potentials and equivalent vapor pressures. Therefore, predictive tools are essential for estimation of soil evaporation. To date, modeling of this transient evaporation process is limited, mainly because it either requires sophisticated numerical models that account for its complexities or relies on analytical solutions that are too simplistic to capture its dynamics.
We present an analytical model that accounts for the main mechanisms of the evaporation process, but is relatively simple in its construction. The governing mechanisms during this dynamic process are captured by accounting for the hydraulic properties of the drying medium, the characteristic features of the medium that control water flow, the atmospheric forcing, and the partitioning between the liquid and vapor phases of the water within the drying profile. We validate this simplified approach using data from a numerical model and from evaporation experiments in different soil types, under various ambient conditions. In addition to depicting evaporation rates and the cumulative loss of water over time, we demonstrate the effect of soil hydraulic properties and their heterogeneity on the evaporation process. Additionally, we show how the model predicts the spatiotemporal partitioning between water (liquid and vapor) phases, with specific attention to the DSL that develops during longer periods of evaporation, with the corresponding downward migration of the evaporative front.

How to cite: Kamai, T. and Assouline, S.: Modelliing evaporation from soil profiles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4789, https://doi.org/10.5194/egusphere-egu23-4789, 2023.

Terrestrial gravimetry allows for integrative measurements of mass changes associated with water storage variations in all storage compartments above and below the Earth surface. Superconducting gravimeters (SGs) currently are the most precise instruments for continuous monitoring of gravity change. Their footprint typically covers a radius of about 1 km around the instrument, with most of the signal originating from within the first 100 meters. We installed a SG (iGrav033) in a mixed pine-beech-oak forest in the TERENO observatory in the lowlands of north-eastern Germany. It is housed in a small field enclosure with less than 1 m² base area, on top of a stable concrete pillar. Complementary hydro-meteorological monitoring data are available at the site, including a weather station, a groundwater monitoring well, clusters of soil moisture sensors along deep soil profiles, interception measurements and near-surface soil moisture from Cosmic Ray Neutron Sensing. For quantification and correction of the long-term instrumental SG drift, repeated measurements with an FG5 absolute gravimeter were carried out. The gravity residual time series (gravity measurements reduced to the local hydrological effect) covers a sequence of years with below average precipitation, from 2018 to 2022. We show the gravity-based water storage variations in the forested landscape throughout this period, indicating that storage depletion during summer in most years is not fully recovered by the subsequent wetter winter periods. The amplitudes of gravity-based water storage variations tend to exceed those observed by soil moisture sensors in the top meters of the soil and of groundwater. This indicates the value of terrestrial gravimetry in revealing dynamics of the deeper unsaturated zone water storage.

How to cite: Güntner, A., Reich, M., Rasche, D., Blume, T., Schröder, S., Brachmann, E., Gebauer, A., and Wziontek, H.: Water storage variations in a forest during a sequence of dry years: integrative monitoring with a superconducting gravimeter, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12860, https://doi.org/10.5194/egusphere-egu23-12860, 2023.

Root-zone soil moisture (RZSM) information is valuable in a wide range of applications, including weather forecasting, hydrological and land surface modeling, and agricultural production. However, there is still a lack of sensing information that adequately represents RZSM, especially with regard to longer periods and larger spatial scales. For example, active and passive microwave remote sensing observations for soil moisture are limited to the topsoil and can be influenced by land cover type. One option for RZSM observation is terrestrial gamma radiation as it is inversely related with soil moisture. Hence, the near-real-time data of more than 4600 gamma radiation monitoring stations archived by the EUropean Radiological Data Exchange Platform (EURDEP) may be a potential source to develop a RZSM product for Europe without extra investments in sensors. The aim of this study was to investigate to what extent the EURDEP data can be used for RZSM estimation. For this, two gamma radiation monitoring stations were equipped with in-situ soil water content sensors to measure reference RZSM. The terrestrial component of gamma radiation was extracted after eliminating the contribution of secondary cosmic radiation. For this, it was assumed that the long-term contribution of secondary cosmic radiation is constant and that the variations are caused by changes in atmospheric pressure and incoming neutrons. In addition, precipitation effects creating a sudden increase in gamma radiation due to atmospheric washout of radon progenies to the ground were eliminated by excluding time periods with precipitation. Finally, multi-year terrestrial gamma radiation measurements were used to estimate weekly RZSM and the results were compared with the reference measurements. It was found that the seasonal variation of RZSM can be reasonably well predicted with an RMSE of 7 – 9 vol.% from gamma radiation measurements. However, the radiation-based RZSM estimates fluctuated with a much greater amplitude compared to the reference data, especially during the winter and spring season. This may be related to unknown or neglected additional sources that affect the gamma radiation signal and this needs to be further investigated. Although the accuracy of radiation-based RZSM estimates is not as good as many other in-situ sensors, this technique is still competitive with satellite-based remote sensing technique to estimate RZSM on the continental scale.

How to cite: Akter, S., Huisman, J. A., and Bogena, H. R.: Estimating root-zone soil moisture from gamma radiation monitoring data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4390, https://doi.org/10.5194/egusphere-egu23-4390, 2023.

Vegetation plays a fundamental role in modulating the exchange of water, energy, and carbon fluxes between the land and the atmosphere. These exchanges are modelled with Land Surface Models (LSMs) which are part of numerical weather prediction systems to support the performance of weather forecasts. However, most current LSMs only utilise observed vegetation information in the form of mean seasonal cycles. The potential benefits of additionally including information about shorter-term vegetation anomalies and inter-annual variability are understudied.

In this study, we update vegetation information in the HTESSEL (Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land) model and investigate the resulting effects on the performance of simulated shallow and deep soil moisture as well as latent heat flux. The updated information includes an interactive observation-based leaf area index from Sentinel-3 and THEA GEOV2, and a land use/land cover map from ESA-CCI. The resulting simulations of soil moisture and latent heat flux are validated against global gridded observation-based datasets.

Results show that the updated land surface information deteriorates the overall model performance for both latent heat flux and soil moisture in most regions across the globe. In a second step, we re-calibrate soil and vegetation-related parameters at each grid cell in order to adjust them to the new vegetation information. This leads to improved model performance and illustrates the benefits of updated vegetation information. Morover, we attribute the spatial variations of parameter perturbations resulting from the re-calibration to multiple land surface and climate characteristics. This highlights potential venues in model development to take static ecological and hydroclimatological information into greater consideration.

Furthermore we compare the performances of local model calibration - performed for each grid cell individually - and global model calibration considering a single parameter set for all grid cells globally. We analyse the agreement of parameter calibrations obtained for shallow and deep soil moisture as well as latent heat flux.

In summary, our results highlight that Earth-observation products of vegetation dynamics and land cover changes can improve land surface model performances, which in turn can contribute to more accurate weather forecasts.

How to cite: Ruiz-Vásquez, M., Oh, S., Brenning, A., Balsamo, G., Boussetta, S., Arduini, G., Reichstein, M., and Orth, R.: Updating vegetation information in a land surface model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12430, https://doi.org/10.5194/egusphere-egu23-12430, 2023.

The most important parameterizations of the soil water retention curve do not perform very well in either the wet or the dry end. Rossi and Nimmo (WRR 1994) therefore gave the Brooks-Corey (1966) power-law model of the soil water retention curve a non-asymptotic dry range. Ippisch et al. (Adv. Water Resour., 2006) added an air-entry value to the sigmoidal retention model of van Genuchten (SSSAJ 1980). The models of Rossi and Nimmo and Ippisch et al. were Adapted by de Rooij (HESS 2021) to arrive at a sigmoidal, non-asymptotic soil water retention curve with an air-entry value, dubbed RIA. In RIA, the matric potential at oven-dryness, h_d, appeared as a derived parameter.

Bittelli and Flury (SSSAJ 2009) showed that dry-range soil water retention data points often are unreliable. In order to make RIA robust when this is the case, this presentation explains how h_d was made a fitting parameter that can be fixed if needed. This modification was complicated by the peculiar behavior of shape parameter α that made adequate parameter fitting impossible. The presentation elucidates this behavior and explains how this problem was solved by a reformulated model (de Rooij, HESS 2022). It then shows how earlier fits (when the problem had not yet been discovered) corroborate the reformulated model.

The work also offers support for a theoretical value for h_d proposed by Schneider and Goss (Geoderma 2012), which is very helpful if dry-range data are lacking or of poor quality. The mathematical structure of RIA is such that, for α → ∞, Rossi and Nimmo’s model arises as a special case of RIA, and, by implication, Brooks-Corey as a special case of Ippisch et al.

A public-domain code to fit the parameters using shuffled complex evolution (SCE) is available on Zenodo (de Rooij, 2022). It has features that help the user identify issues with local minima and overparameterization, and provides more information than most codes to offer better insight into the fitting process for those familiar with the SCE algorithm. These features may be useful for other parameter identification problems, so they will be discussed as well.

How to cite: de Rooij, G. H.: A new sigmoidal but non-asymptotic soil water retention curve for the entire soil water content range brings together the van Genuchten and Brooks-Corey models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3368, https://doi.org/10.5194/egusphere-egu23-3368, 2023.

Plant roots exhibit plasticity in their branching patterns to forage efficiently for heterogeneously distributed resources, such as soil water. The xerobranching response represses lateral root formation when roots lose contact with water (e.g. in “air gaps”), and provides an experimental model to study root adaptive responses to transient water stress.

To discover the mechanistic basis of xerobranching, soil- and agar-based xerobranching bioassays were developed. As levels of the abiotic stress signal abscisic acid (ABA) increase in root tips during transient water stress, we observed that tomato, maize and Arabidopsis mutants deficient in ABA are disrupted in xerobranching response. Using novel ABA biosensors and mutants, we showed that when reaching an air gap, it takes about half a day for ABA originating from phloem tissues to radially travel through the unloading zone and accumulate in epidermal tissues.

When root tips lose contact with water, could the direction of water flow across root tissues change, and trigger the outwards accumulation of ABA, acting as a “hydrosignal” ? Our 3-dimensional root micro-hydrological model of solute advection-diffusion “MECHA” supports the following hypotheses :

• Such a reversal of radial water flow direction may happen in the root elongation zone, as cell elongation may not be fed by water absorbed at the root surface anymore, and therefore water for cell elongation (e.g. in the epidermis) entirely relies on phloem as a water source.
• If water soluble hormones such as ABA “ride” on water fluxes through plasmodesmata and along cell walls, it would take them about 8 hours to accumulate to levels comparable to concentrations observed in phloem cells. This timing is compatible with our experimental observations.

From there on, our Arabidopsis mutants reveal that ABA uses plasmodesmatal closure to lock up the symplastic radial pathway that is necessary for auxin to initiate lateral root branching.

In conclusion, our study reveals how roots might adapt their branching pattern to heterogeneous soil water conditions by linking changes in hydraulic flux with dynamic hormone redistribution.

This work includes material recently published in Science, under the following link: https://doi.org/10.1126/science.add3771

How to cite: Couvreur, V., Mehra, P., Pandey, B. K., Draye, X., and Bennett, M. J. and the co-authors: Hydrosignalling : How air gaps in soils alter the distribution of root water and hormones fluxes, thereby blocking root lateral branching, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9384, https://doi.org/10.5194/egusphere-egu23-9384, 2023.

Infiltration is an important hydrological process impacting ecology, forestry, agronomy, civil- and environmental engineering. Most infiltration models assume soils to be “wettable”, i.e., water in the soil forming an effective contact angle with the soil matrix that is close to zero. For a range of applications, e.g., infiltration into organic-rich soils or soils that turned water repellent due to fire, the “wettability assumption” no longer holds. Hence, the need for an infiltration model that can take soil water repellency into account. This study proposes a process-based approach for modeling infiltration into water repellent soil using the concepts of effective contact angle and sorptivity. The approach was developed using the Green-Ampt infiltration model but can be easily adapted for other process-based infiltration models such as Philip or Smith-Parlange. The infiltration model demonstrates the considerable impact of soil water repellency on infiltration, also for subcritically-water repellent soils, i.e., soils with effective contact angles <90°. It illustrates the non-linear relationship between infiltration rate and effective contact angle with effective contact angles >70° having a much larger impact on infiltration rate than effective contact angles <70°. The model also indicates that due to gravity, infiltration could occur into super-critically water repellent soil (i.e., soil with effective contact angles ≥90°), even with zero hydraulic head at the soil surface. Infiltration at zero hydraulic head, however, likely ceases at effective contact angles between 91° and 101°, depending on the amount of cumulative infiltration. All infiltration simulations showed decreasing infiltration rates with increasing soil water repellency expressed as effective contact angle or sorptivity at any level of cumulative infiltration. Finally, the water repellency effects on infiltration rates for short-duration, high intensity storms—a critical situation commonly associated with wildfire and flooding—were illustrated.

How to cite: Berli, M. and Shillito, R.: Modeling infiltration into water repellent soil, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10495, https://doi.org/10.5194/egusphere-egu23-10495, 2023.

A new pedotransfer function (PTF) was developed based on the Arya and Paris (AP) approach to obtain Water Retention (WRC) and Hydraulic Conductivity (HCC) curves. The AP approach obtains the unimodal WRC from the Particle-Size Distribution (PSD). The proposed PTF is an extension of AP approach by incorporating the Aggregate-Size Distribution (ASD) to include the inter-aggregate pores (macropores) retention, and thus obtain the bimodal WRC. A bimodal porosity model was developed to specify the ratios of the matrix and the macropores in the overall soil porosity. Kozeny-Carmen equation was utilized to obtain the saturated hydraulic conductivity, K₀, from the bimodal WRC behaviour near saturation. Then, Mualem model was applied to obtain the full HCC. To calibrate the proposed PTF, soil physical and hydraulic properties were measured from a 140-ha irrigation sector in “Sinistra Ofanto” irrigation system in Apulia Region, South Italy. Hydraulic properties came from infiltration experiments. Infiltration data were fitted using bimodal and unimodal hydraulic properties by an inverse solution of Richards Equation. The scaling parameter of the proposed PTF, α_AP, was calibrated using the measured bimodal hydraulic properties. A similar calibration was carried out for the sake of comparison, in which the α_AP of the classical unimodal AP was calibrated using the unimodal hydraulic properties. The proposed bimodal AP (bimAP) PTF significantly improves the predictions of the mean WRC parameters, K₀ and the entire HCC, compared to the classical unimodal AP (unimAP) PTF. In addition, compared to unimAP, bimAP allows to reproduce the statistics of the hydraulic parameters (e.g., the variance) similar to those obtained from field measurements. Finally, Multiple Linear Regression (MLR) was applied to study the sensitivity of bimodal α_AP to the soil textural and structural properties and the results confirmed the significant predictive effects of soil structure.

How to cite: Hassan, S. B. M., Dragonetti, G., Comegna, A., Sengouga, A., Lamaddalena, N., and Coppola, A.: A bimodal extension of the ARYA&PARIS approach for predicting hydraulic properties of structured soils, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12011, https://doi.org/10.5194/egusphere-egu23-12011, 2023.

Ag-IoT systems enable a data pipeline for modern agricultural production. Using Ag-IoT technologies, growers can make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Here, we designed a flexible microprocessor-based platform, called TreeTalker, to monitor in real-time plant sap flow rate via thermal approaches. TreeTalker has an onboard spectrometer to collect data in near infrared and visible areas using 12 bands from 450 to 860 nm. Moreover, TreeTalker collects microclimate data (air temperature and air relative humidity) as well as soil moisture and temperature measurement. Sap flow and soil moisture measurements are the main tools to understand the plant water demand for precision irrigation and water-energy efficiency. In this study, 9 TreeTalker units are mounted on Soreli Kiwifruit trees in the Lazio region, Italy. The site is divided into three clusters with different irrigation regimes, 100, 80 and 60 %, respectively. The first objective of this study was to apply new algorithms for sap flow measurement considering the heating and cooling phases of the heat flow curve at the same time and secondly, a compare of phenological and ecohydrological trends of trees under full and deficit irrigation systems. Data captured was used to analyze the correlation between fruit quality, productivity, health, and fertility of trees with ecophysiological parameters under different irrigation systems. The result of continuous monitoring for one growing season in 2022 revealed that sap flow function based on cooling phase data has higher accuracy than heating phase due to independency to the zero-flux condition as well as semi-theoretical flow index. Given sap flow results, plants with the full irrigation system have ∼ 1.3 to 3 times greater sap flow rate than plants with deficit irrigation regimes. Kiwi peak water demand occurred in July coinciding with max VPD confirming maximum sap flow rates between each irrigation regime. A variation between the 80% and 60% irrigation regimes, ∼ 4 to 15 %, is linked to slight differences in sap flow rates and is most prominent in the early part of the growing season. Considering fruit quality data, kiwifruit trees with full irrigation showed lower acidity, and higher Vitamin C concentration while sugar concentrations were noticeably lower. Our results suggest that the 80% irrigation schedule achieves the optimum water energy efficiency as well as reaching optimum fruit quality conditions. This finding requires validation via continued monitoring over successive seasons and irrigation regimes. The revolution in the Internet of trees offers a promising new big data solution for assessing optimal conditions for fruit tree agricultural production considering future and potential water scarcity scenarios.

How to cite: Asgharinia, S., Lembo, M., Eramo, V., Forniti, R., Renzi, F., Valentini, R., and Botondi, R.: Ag-IoT application for Vital Monitoring of Plant Ecophysiological Data and Soil Parameters, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17401, https://doi.org/10.5194/egusphere-egu23-17401, 2023.

At a critical soil water content (θ_crit), terrestrial ecosystem fluxes at the soil-vegetation-atmosphere interface transition from energy into water limitation. Understanding and predicting soil, plant and atmospheric mechanisms that control θ_crit are central to interpreting and predicting impacts of drought on ecosystems, including the associated feedbacks to carbon and hydrological cycle. Thanks to the existing monitoring networks, θ_crit can now be estimated globally across soils, biomes and climates. However, the mechanisms and key parameters that explain θ_crit as a result of soil-, plant-, and climate-interaction remain elusive. Here, we show that the soil hydraulic conductivity function determines mean and variability of θ_crit. The underlying concept to calculate θ_crit assumes that soil moisture limitation of transpiration is triggered by a loss in soil hydraulic conductivity around the roots. Taking soil-specific hydraulic properties into account, our soil-plant hydraulic model predicts the observed mean and variance of θ_crit as a function of soil textural classes. In coarse textured soils, θ_crit is small due to the lower absolute soil hydraulic conductivity and its steeper decline with soil drying compared to fine textured soils. The increasing variability of θ_crit in fine-textured soils is explained by (i) the wide range of hydraulic conductivity values for similar soil textures as a result of soil structure formation and (ii) by the higher sensitivity to plant traits and climate for soils with less steep hydraulic conductivity curves (i.e., loamy soils). The corresponding critical soil matric potential (h_crit) is also soil texture specific, and it covers a broad range of values, from values close to field capacity in sandy soils (h_crit ca. -100 hPa) to values close to the wilting point in clay soils (h_crit ca. – 1 MPa). The model implies that climate change has a smaller effect on θ_crit in sandy soils, suggesting that soil texture modulates climate effects on water use and photosynthesis globally. Overall, our results prove the prominent role of soil hydraulic conductivity for water limitation of ecosystem fluxes and for plants’ potential to adjust to water limitations subject to alterations due to climate change.

How to cite: Wankmüller, F., Delval, L., Cecere, A., Lehmann, P., Javaux, M., and Carminati, A.: Soil Hydraulic Conductivity Controls Soil Moisture Limitation of Transpiration Globally, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12613, https://doi.org/10.5194/egusphere-egu23-12613, 2023.

The partitioning between soil evaporation and transpiration from plants is an important process of water and carbon cycles and surface energy balance. Its quantification is prone to errors because of the complexity of flow geometry, which is affected by the variation of root length density over depth and time and the dynamics of soil hydraulic properties in the rhizosphere. Root water uptake and concurrent evaporation depend on the forces (capillarity, gravity, and viscous losses) controlling water flow and propagation of the drying front. We simulate the water flow from the soil to the atmosphere using invasion percolation models, draining elements as a function of the retaining forces depending on the lengths of the potential flow paths. The partitioning between evaporation and transpiration is simulated for different pore size distributions, root length densities, and vegetation covers controlling the transpiring area. Starting with a three dimensional percolation model (to reproduce the connectivity of the liquid phase) at the column scale consisting of elements in the submillimeter range, we deduce one-dimensional partitioning rules for wet and dry soils. As an outlook, we discuss how these rules can be (i) implemented in large scale models and (ii) tested by measuring vapor fluxes above and below canopy.

How to cite: Lehmann, P. and Carminati, A.: Modeling the partitioning of evapotranspiration using invasion percolation theory, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15294, https://doi.org/10.5194/egusphere-egu23-15294, 2023.

Preferential flow induced by desiccation cracks (PF-DC) has been proven to be an important hydrological effect that could cause various geotechnical engineering and ecological environment problems. Investigation on the PF-DC remains a great challenge due to the soil shrinking-swelling behavior. This work presents an experimental and numerical study of the PF-DC considering the dynamic changes of DC. A soil column test was conducted under wetting-drying cycles to investigate the dynamic changes of DC and their hydrological response. The ratio between the crack area and soil matrix area (crack ratio), crack aperture and depth were measured. The soil water content, matrix suction and water drainage were monitored. A new dynamic dual-permeability preferential flow model (DPMDy) was developed, which includes physically-consistent functions in describing the variation of both porosity and hydraulic conductivity in crack and matrix domains. Its performance was compared to the single-domain model (SDM) and rigid dual-permeability model (DPM) with fixed crack ratio and hydraulic conductivity. The experimental results showed that the maximum crack ratio and aperture decreased when the evaporation intensity was excessively raised. The self-closure phenomenon of cracks and increased surficial water content were observed during low evaporation periods. The simulation results showed that the matrix evaporation modeled by the DPMDy is lower than that of the SDM and DPM, but its crack evaporation is the highest. Compared to the DPM, the DPMDy simulated a faster pressure head building-up process in the crack domain and higher water exchange rates from the crack to the matrix domain during rainfall. Using a fixed crack ratio in the DPM, whether it is the maximum or the average value from the experiment data, will overestimate the infiltration fluxes of PF-DC but underestimate its contribution to the matrix domain. In conclusion, the DPMDy better described the underlying physics involving crack evolution and hydrological response with respect to the SDM and DPM. Further improvement of the DPMDy should focus on the hysteresis effect of the SWRC curve and soil deformation during wetting-drying cycles.

How to cite: Luo, Y., Zhang, J., Zhou, Z., Pablo Aguilar López, J., Greco, R., and Bogaard, T.: Effects of dynamic changes of desiccation cracks on preferential flow: Experimental investigation and numerical modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4336, https://doi.org/10.5194/egusphere-egu23-4336, 2023.