Abstract:Despite the vast extent of desert soils on the earth's surface, our understanding of the moisture dynamics of near-surface desert soils (i.e., the top centimeters to few meters of the soil profile) remain limited. The goal of this study was to explore the use of the Peters-Durner-Iden (or PDI) instead of bimodal van Genuchten (or BVG) hydraulic functions to improve water redistribution simulations using HYDRUS-1D for drier soils in desert environments. The PDI hydraulic functions take capillary and film flow i… Show more
“…As can be seen, the FL model with the fitting parameters presented in Table 3 matches well with the measurements, despite that the fitting parameters are slightly different in three tests. This indicates that the FL model can accurately fit the WRC and RHC data measured by Luo et al (2020). In the numerical model, the average value of each fitting parameter was taken for the FL model.…”
Section: An Application Of the Fl Model To A Numerical Modelsupporting
confidence: 58%
“…The initial soil water content profile is presented in (c). Source : Data compiled from Luo et al (2020)…”
Section: An Application Of the Fl Model To A Numerical Modelmentioning
confidence: 99%
“…The desert soil filled in the lysimeter had a saturated hydraulic conductivity of 10.32 cm/d and a saturated soil water content of 0.355. The WRC and RHC of the desert soil were determined experimentally by Luo et al (2020) by means of the desorption method (using WP4C dew‐point potentiometer from METER Environment) and evaporation method (using HYPROP from METER Environment), respectively. To minimize the uncertainty, three repeated tests were conducted.…”
Section: An Application Of the Fl Model To A Numerical Modelmentioning
confidence: 99%
“…The same as Luo et al (2020) and Dijkema et al (2018), HYDRUS‐1D, a process‐based soil physics model developed by Šimůnek et al (2005), was employed to simulate the water distribution in the lysimeter. The only difference between the present numerical model and the previous ones by Luo et al (2020) and Dijkema et al (2018), is that the FL was implemented into HYDRUS‐1D as an external table in order to describe WRC and RHC of the lysimeter soil. The boundary conditions were consistent with the experimental setup (Figure 7a).…”
Section: An Application Of the Fl Model To A Numerical Modelmentioning
Motivated by a versatile three‐parameter water retention curve (WRC) formula of Fredlund and Xing, we proposed an alternative expression to describe the relative hydraulic conductivity (RHC) for soils that can capture oven‐dry to water‐saturated conditions (full moisture range) with a single, closed‐form equation (without having to explicitly partitioning the capillary and film flow components). This RHC expression was tested using an existing data set that includes a wide range of soil textures, and shown to be more accurate than the other two RHC expressions. Subsequently, the new RHC expression was combined with the WRC formula of Fredlund and Xing, generating an alternative model (hereafter called the FL model) applicable to describe soil hydraulic properties over the full moisture range. The FL model requires both the known WRC and RHC data since three additional fitting parameters are involved in the present RHC expression. Furthermore, the FL model was employed in a HYDRUS‐1D numerical model for simulating the soil moisture redistribution within a lysimeter. The numerical simulation with using the FL model can accurately predict the moisture redistribution, in turn confirming the validity of the FL model despite without partitioning the capillary and film flow components.
“…As can be seen, the FL model with the fitting parameters presented in Table 3 matches well with the measurements, despite that the fitting parameters are slightly different in three tests. This indicates that the FL model can accurately fit the WRC and RHC data measured by Luo et al (2020). In the numerical model, the average value of each fitting parameter was taken for the FL model.…”
Section: An Application Of the Fl Model To A Numerical Modelsupporting
confidence: 58%
“…The initial soil water content profile is presented in (c). Source : Data compiled from Luo et al (2020)…”
Section: An Application Of the Fl Model To A Numerical Modelmentioning
confidence: 99%
“…The desert soil filled in the lysimeter had a saturated hydraulic conductivity of 10.32 cm/d and a saturated soil water content of 0.355. The WRC and RHC of the desert soil were determined experimentally by Luo et al (2020) by means of the desorption method (using WP4C dew‐point potentiometer from METER Environment) and evaporation method (using HYPROP from METER Environment), respectively. To minimize the uncertainty, three repeated tests were conducted.…”
Section: An Application Of the Fl Model To A Numerical Modelmentioning
confidence: 99%
“…The same as Luo et al (2020) and Dijkema et al (2018), HYDRUS‐1D, a process‐based soil physics model developed by Šimůnek et al (2005), was employed to simulate the water distribution in the lysimeter. The only difference between the present numerical model and the previous ones by Luo et al (2020) and Dijkema et al (2018), is that the FL was implemented into HYDRUS‐1D as an external table in order to describe WRC and RHC of the lysimeter soil. The boundary conditions were consistent with the experimental setup (Figure 7a).…”
Section: An Application Of the Fl Model To A Numerical Modelmentioning
Motivated by a versatile three‐parameter water retention curve (WRC) formula of Fredlund and Xing, we proposed an alternative expression to describe the relative hydraulic conductivity (RHC) for soils that can capture oven‐dry to water‐saturated conditions (full moisture range) with a single, closed‐form equation (without having to explicitly partitioning the capillary and film flow components). This RHC expression was tested using an existing data set that includes a wide range of soil textures, and shown to be more accurate than the other two RHC expressions. Subsequently, the new RHC expression was combined with the WRC formula of Fredlund and Xing, generating an alternative model (hereafter called the FL model) applicable to describe soil hydraulic properties over the full moisture range. The FL model requires both the known WRC and RHC data since three additional fitting parameters are involved in the present RHC expression. Furthermore, the FL model was employed in a HYDRUS‐1D numerical model for simulating the soil moisture redistribution within a lysimeter. The numerical simulation with using the FL model can accurately predict the moisture redistribution, in turn confirming the validity of the FL model despite without partitioning the capillary and film flow components.
“…Comparisons with data covering a large variety of soils showed that the PDI model system can describe the water retention and hydraulic conductivity over the full moisture range well, despite its simplification of the underlying processes (Iden et al., 2021; Peters, 2013; Rudiyanto et al., 2015; Weber et al., 2017). Due to its simple formulation, it can easily be used in parameter estimation and numerical simulation studies for variably‐saturated water flow (Luo et al., 2020). A distinct disadvantage of the PDI model system is that the film conductivity is only expressed as a relative conductivity function, which must be scaled by a factor to contribute to the total liquid conductivity function.…”
In order to adequately model water, solute and energy transport in the vadose zone, an accurate mathematical representation of the soil hydraulic properties, that is, the soil water retention and hydraulic conductivity curves, is required. Common representations of both functions, as given, for example, by van Genuchten (1980), Durner (1994), or Kosugi (1996, describe capillary water retention and conductivity, but neglect water adsorption, film and corner flow. Therefore, they are well suited to model transport processes in the medium to wet moisture range. They fail, however, to describe water transport when the soil becomes dry (Peters et al., 2015).Most traditional water retention functions assume a distinct residual water content, which is asymptotically reached at high suctions. This residual water content is either interpreted as water that is held by adsorptive forces (Corey & Brooks, 1999) or it is used as a mere fitting parameter. Thirty years ago, Nimmo (1991) discussed the problem and the fundamental misconception of this approach. From a physical point of view, the water film thickness will continually decrease as suction increases (Tuller & Or, 2005) and finally the water content becomes by definition zero at oven dryness (Schneider & Goss, 2012). To our knowledge, Campbell and Shiozawa (1992) were the first to show that in the hygroscopic moisture range, the water content often decreases linearly toward zero if it is plotted versus the log of suction. This was accounted for in the retention models of Rossi and Nimmo (1994), Fayer andSimmons (1995) and Khlosi et al. (2006). The frequently used functions of Fayer and Simmons (1995) and Khlosi et al. (2006) (e.g., Lebeau & Konrad, 2010 do not predict a water content of zero at oven dryness for soils with wide pore-size distributions (Peters, 2013). Moreover, these models sometimes predict even an increase in water content with increasing suction near saturation, which is physically wrong (Peters et al., 2011). Therefore, Peters ( 2013) suggested an alternative model formulation, which describes water retention by a linear superposition of the capillary and non-capillary components. This model was improved by Iden and Durner (2014).
Climate change will lead to prolonged droughts in various regions of the world, which may significantly affect agricultural production. This is particularly problematic for soils with low water retention capacity, which cannot store sufficient water for crops. In this paper, we investigate how a change in the water‐holding capacity of the soil material, as could be achieved by increasing the soil organic carbon (SOC) amount, affects the components of the soil water balance (evaporation, transpiration, and groundwater recharge). Specifically, we state the hypothesis that an increased water‐holding capacity in a shallow soil layer, as it is achieved through SOC enrichment at the soil surface, will result in more water being stored near the soil surface and lost to unproductive evaporation, thereby reducing the amount of water available to plants and groundwater recharge. The hypothesis was tested by numerical simulations, employing the Hydrus‐1D program package to model the water balance in a soil–plant–atmosphere system for an arable crop in hydrologically contrasting years. The study considered soils with varying textures and different depths of a soil layer with increased SOC content. The soil hydraulic properties (SHP) of the soil material, including the effect of SOC on the SHP, were determined using a recently developed pedotransfer model based on data from over 500 samples. We showed that both the improved water retention by SOC and its vertical distribution affect the soil water balance in a complex manner. In sandy soils, increasing the water‐holding capacity in shallow layers up to 0.1 m led to enhanced evaporation and thus a decrease in water availability for crops. However, deeper incorporated SOC could ameliorate these negative effects. Our findings suggest that not only the amount but also the vertical SOC distribution should be considered if enrichment of SOC shall be applied to mitigate the effect of droughts.
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