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Article

Impact of Duration of Land Abandonment on Infiltration and Surface Runoff in Acidic Sandy Soil

by
Lucia Toková
1,
Slavomír Hološ
1,2,
Peter Šurda
1,
Jozef Kollár
3 and
Ľubomír Lichner
1,*
1
Institute of Hydrology, Slovak Academy of Sciences, Dúbravská cesta 9, 841 04 Bratislava, Slovakia
2
Faculty of Horticulture and Landscape Engineering, Institute of Landscape Engineering, Slovak University of Agriculture, Hospodárska 7, 949 76 Nitra, Slovakia
3
Institute of Landscape Ecology, Slovak Academy of Sciences, Štefánikova 3, 814 99 Bratislava, Slovakia
*
Author to whom correspondence should be addressed.
Agriculture 2022, 12(2), 168; https://doi.org/10.3390/agriculture12020168
Submission received: 9 December 2021 / Revised: 21 January 2022 / Accepted: 21 January 2022 / Published: 25 January 2022
(This article belongs to the Section Agricultural Water Management)
Browse Figures
Versions Notes

Abstract

:
Sandy soils are less fertile and, therefore, often abandoned in the Central European region. Land abandonment can cause the recovery of ecosystems by the replacement of crop species by vegetation that disperses from surrounding habitats and will be subsequently established (secondary succession). The objective of this study was to find the impact of secondary succession during more than 30 years of lasting abandonment of agricultural fields with acidic sandy soil on infiltration and surface runoff. The method of space-for-time substitution was used so that the fields abandoned at different times were treated as a homogeneous chronosequence. The impact of abandonment on infiltration and surface runoff was characterized by the changes in soil organic carbon content, pH, water and ethanol sorptivity, hydraulic conductivity, water drop penetration time, repellency index, time to runoff, and surface runoff coefficient. It was found that the abandoned soils previously subjected to agriculture showed a decrease in pH, a significant increase in soil water repellency, and a decrease in infiltration, which can lead to serious problems in terms of surface runoff and soil erosion. The pH(H2O) and pH(KCl) decreased monotonously and ethanol sorptivity did not change significantly during abandonment. The time to runoff did not change significantly between 10 and 30 years of abandonment, and it was not measured after 1 year of abandonment because no runoff occurred. The dependence of the other characteristics on the duration of field abandonment was not unambiguous. Water sorptivity and hydraulic conductivity showed a decrease between 1 and 10 years followed by a slight increase between 10 and 30 years of abandonment. On the other hand, soil organic carbon content, water drop penetration time, repellency index, and surface runoff coefficient showed an increase between 1 and 10 years followed by a slight decrease between 10 and 30 years of abandonment. To prevent soil water repellency and its consequences in sandy soils, an adequately high soil water content should be maintained, and mixed forest afforestation should be preferred to pine afforestation. This is extremely important in the context of climate change and the increasing frequency of prolonged dry periods.

1. Introduction

Agricultural land abandonment often referred to as the cessation of farming and giving away land for natural succession, is a type of land use transformation that potentially causes the recovery of ecosystems [1]. Passive revegetation in permanently abandoned arable land (secondary succession) is characterized by the replacement of arable plant species by vegetation that disperses from surrounding habitats and will be subsequently established [2]. Under usual Central European conditions, secondary succession after abandonment initially starts with annual or biannual plants, followed by perennial forbs, grasses and shrubs, and ends with forest (climax stage).
The agricultural land abandonment followed by natural revegetation showed increased soil organic carbon (SOC) content and greater accumulation of SOC and soil total nitrogen contents in the upper soil layers [3]. Apostolakis et al. [4] found that in the 50-year set-aside/abandoned field, the SOC content was 62% higher compared to the 0- and 6-year set-aside fields. The authors of [5] found when comparing arable land with fallow and permanent grassland that SOC increased up to 46.5% in fallow grassland and by max. 71.2% in permanent grassland. The average pH(KCl) increased from 4.6 in arable land to 5.1 and 5.3 in fallow and permanent grasslands, respectively.
Vegetation and its changes during succession can induce soil water repellency (SWR), which characteristics are influenced by agricultural practices [6], soil temperature [7], soil water content [8,9], soil water retention [10], soil texture [11], soil pH [12], SOC content and structure of humic substances [13], and clay (mainly kaolinite) content [14]. SWR is temporally and spatially variable [15] and varies with depth [16,17]. Sándor et al. [18] concluded that climate and soil texture are two of the main factors influencing SWR.
Hydrophobic layers on or near the surface of the soil can result in reduced infiltration occurring in irregular patterns, enhanced runoff, and increased erosion rates [19]. Infiltration can be parameterized by the hydraulic conductivity and sorptivity. Long et al. [20] showed that hydraulic conductivity decreased, and repellency index increased in silty loam soil following the land use and cover change from wheat field to woodland in a semiarid area in the Loess Plateau of China. However, they did not find significant correlations between these characteristics. Zema et al. [21] also did not find significant correlations between hydraulic conductivity and slight SWR in sandy clay loam soil in Spanish black pine forest. The lack of correlation between these two hydrological parameters was attributed to the fact that some soil properties and covers influence only SWR but not hydraulic conductivity and vice versa. Lucas-Borja et al. [22] assessed the effect of different land use on SWR and hydraulic conductivity, k, on three plots representing intensive agricultural use, abandoned agricultural land, and forest ecosystem. They found that forest soils showed high SWR and low k, while soils exposed to intensive agriculture showed low SWR and high k, and that SWR and k values were affected by SOC and bulk density. Sorptivity can be interpreted as the capillary-driven component of water infiltration into unsaturated soil. Shillito et al. [23] found that sorptivity of water-repellent sand decreased with an increase in water-repellency characterized by water drop penetration time (WDPT) and contact angle.
An increase in surface runoff with an increase in SWR has been observed in many studies [24,25]. Lemmnitz et al. [24] studied the temporal dynamics of surface runoff in wettable and hydrophobic sand and reported that seasonal variations in the actual water repellency caused an increase in the runoff coefficient in the summer and autumn. Miyata et al. [26] found that the surface runoff coefficient for a storm event was negatively correlated with initial soil water content. However, during a period of successive storm events separated by short intervals, the coefficient decreased gradually indicating a weakening of water repellency by repeated wetting. Müller et al. [27] evidenced that SWR governed runoff generation from Andosol and SWR was not lost through the washing off of hydrophobic materials during multiple consecutive water run-on events with the same soil slab. Rodrigo-Comino et al. [28] found that soil erosion and surface runoff decreased drastically in abandoned olive and orange orchards, while abandoned vineyards showed no difference and abandoned almond orchards experienced higher surface runoff/erosion rates. Liang et al. [29] presented that vegetation restoration could reduce runoff by 68.0% to 97.4% and soil erosion by 98.0% to 99.9% compared to bare soil areas, with no significant difference in surface runoff and soil loss from areas with different types of vegetation during 11 erosive rains.
Time to runoff or time to runoff initiation is defined as the time between the beginning of a rainfall event and the beginning of runoff and is used to examine runoff generation and infiltration patterns as the basis for soil and water conservation measures. Time to runoff is affected by various factors, including rainfall intensity, soil texture, vegetation, soil moisture content, and land-use type. Time to runoff is prolonged in dry soils but decreases with increasing antecedent soil moisture content, where the probability of surface runoff generation under dry antecedent soil moisture conditions is lower than that under moderate or wet antecedent conditions [30].
Sandy soils are less fertile and, therefore, often abandoned in the Central European region. In our previous study [31], the impact of secondary succession during more than 40 years of lasting abandonment of agricultural fields with alkaline sandy soil on infiltration was estimated in Csólyospálos, Hungary, and we wanted to know if soil pH affects this impact. Therefore, the objective of this study was to find the impact of secondary succession during more than 30-year lasting abandonment of agricultural fields with acidic sandy soil on infiltration and surface runoff. The impact was characterized by the changes in SOC content, pH, water and ethanol sorptivity, hydraulic conductivity, water drop penetration time, repellency index, time to runoff, and surface runoff coefficient. The method of space-for-time substitution was used so that the fields abandoned at different times were treated as a homogeneous chronosequence [32]. We hypothesize that the vegetation induced SWR (characterized by WDPT and repellency index) and surface runoff (characterized by surface runoff coefficient and time to runoff) characteristics will increase, while infiltration (characterized by water sorptivity and hydraulic conductivity) will decrease in acidic sandy soil during the abandonment of agricultural fields.

2. Materials and Methods

2.1. Site Description

The experimental sites S1, S2, and S3 are located at Studienka village in the Borská nížina lowland (southwestern Slovakia) (Figure 1). The region has a temperate oceanic climate (Cfb) [33] with a mean annual temperature of 9 °C and means annual precipitation of 600 mm, which mainly occurs during the summer months. The soils of the Studienka sites are classified as Arenosol [34] and have a sandy texture [35]. The experimental sites were selected to include three different stages of secondary succession in relatively the same site conditions (climate, soil, and relief conditions). Plant nomenclature follows Marhold and Hindák [36].
Study site S1 (48°31′37″ N, 17°7′54″ E; 173 m a.s.l.) is arable land with flat relief. It is covered by synanthropic vegetation, which replaced the harvested crops. Its cover is 98% and is dominated by annual herbs, especially Conyza canadensis, Persicaria mitis, and Galinsoga parviflora, but some grasses (Agrostis stolonifera, Setaria pumila) and perennial herbs (Potentilla anserina, Trifolium repens) are also abundant (Figure 1a).
Study site S2 (48°31′41″ N, 17°7′49″ E; 180 m a.s.l.) is about 10-year-abandoned arable land with flat relief. It is covered by synanthropic vegetation. Its cover is 100% and is dominated by perennial grasses, especially Calamagrostis epigejos, Elytrigia repens, Poa angustifolia (Figure 1b).
Study site S3 (48°31′39″ N, 17°7′52″ E; 171 m a.s.l.) is about 30-year-abandoned arable land with scattered Scots pine (Pinus sylvestris) trees with flat relief. It is covered by synanthropic vegetation. Its cover is 98% and is dominated both by perennial grasses (Arrhenatherum elatius, Calamagrostis epigejos, Festuca rupicola, Poa angustifolia) and perennial herbs (Acetosa pratensis, Solidago canadensis) (Figure 1c).

2.2. Field Methods

All the field measurements were carried out on the surface of the studied soils during a hot and dry spell in September 2021. The volumetric water content, w (% vol), of the superficial (0–5 cm) soil layer was measured directly in the field using a soil moisture meter HH2 with soil moisture sensor SM200 (Delta-T Devices Ltd., Cambridge, UK).
Field water and ethanol infiltration measurements were performed with a minidisk infiltrometer [37] under a negative tension h0 = −2 cm. The cumulative infiltration I was calculated based on the Philip infiltration equation:
I = C1 t1/2 + C2 t + C3 t3/2 + … + Cm tm/2 + …
where C1, C2, C3, …, and Cm are coefficients, and t is time.
The sorptivity, S, was estimated from the first term of the Philip infiltration equation (I = C1 t1/2) during early-time infiltration of water and ethanol [38]:
S(−2 cm) = I/t0.5
Equation (2) was used to calculate both the water sorptivity (Sw) and ethanol sorptivity (Se) from the cumulative infiltration vs. time relationships taken from the minidisk infiltrometer measurements. It should be mentioned that the water sorptivity is a measure of both the SWR and soil pore size, while the ethanol sorptivity is a measure of soil pore size only.
The repellency index RI
RI = 1.95 Se/Sw
was estimated from the combination of all the ethanol and water sorptivities, i.e., m × n values of RI were calculated from m values of Sw and n values of Se [39]. The following classes of the RI were distinguished: wettable or non-water-repellent soil (RI < 1.95), slightly (RI = 1.95–10), strongly (RI = 10–50), severely (RI = 50–110), and extremely (RI > 110) water repellent soil [40].
The persistence of SWR was assessed by the WDPT test. It involves placing a 50 ± 5 μL water drop from a standard medicine dropper or pipette on the soil surface and recording the time of its complete penetration. A standard droplet release height of approximately 10 mm above the soil surface was used to minimize the cratering effect on the soil surface [41]. The WDPT test determines how long strong water repellency persists in the contact area of a water droplet [42]. The following classes of the persistence of SWR were distinguished: wettable or non-water-repellent soil (WDPT < 5 s), slightly (WDPT = 5–60 s), strongly (WDPT = 60–600 s), severely (WDPT = 600–3600 s), and extremely (WDPT > 3600 s) water repellent soil [43].
Field water infiltration measurements with the minidisk infiltrometer under a negative tension h0 = −2 cm were used to estimate the hydraulic conductivity k(h0). Zhang [44] proposed to use the first two terms of the Philip infiltration equation to fit the cumulative infiltration vs. time relationship and estimate the hydraulic conductivity k(h0) from the equation:
k(h0) = C2/A
where A is a dimensionless coefficient. Equation (4) was used to estimate the hydraulic conductivity k(−2 cm) in the present study, using the value of A = 1.73 corresponding to sandy soil and suction h0 = −2 cm as suggested by the Minidisk Infiltrometer User’s Manual [37].
Field water and ethanol infiltration measurements were performed in all 3 plots. Before the measurement, the plants were cut with scissors without disturbing the soil, biological crust, or vegetation roots.
The surface runoff measurements were done using a portable rainfall simulator [45], designed specifically for soil erosion studies. The runoff plot of the rainfall simulator covered an area of 0.0625 m2 and was surrounded by a metal frame so that all runoff water was collected at the lowest point. Distilled water was used for sprinkling, and raindrops with a weight of 0.106 g fell from an average height of 0.4 m onto the soil surface. At each study site (S1, S2, S3), the rainfall simulations were undertaken at three different plots. Before the rain simulations, herbs and grass were carefully scraped with a sharp-edged spatula just above the soil surface, without disturbing the roots of plants or biocrust. After vegetation removal, WDPT and volumetric water content were measured at three points near each runoff plot. After installing the metal frame, the slope of the runoff plot was measured with a digital inclinometer (GLM50C) placed on the frame. Three consecutive rains with a duration of 15 min were applied to the same plot with a break of approximately five minutes between the rains. A total of 27 rainfall simulations were conducted. The volume of runoff water was measured 9 and 15 min after the start of sprinkling. After the third rainfall simulation, volumetric water content was measured at three points inside the runoff plot.
Surface runoff at the study sites was evaluated using the surface runoff coefficient (Cr), defined as a fraction of rainfall that is transformed into direct overland flow [26], and the time to runoff (T), estimated as the time of arrival of the first drop of runoff water into the sample bottle.

2.3. Laboratory Methods

Basic soil properties were determined on disturbed samples in the ISO Certified Laboratory of the Soil Science and Protection Research Institute in Bratislava. Particle size distribution was determined by sieving and sedimentation according to ISO 11277 [46], pH (KCl) and pH (H20) were measured according to ISO 10390 [47], SOC content was determined by oxidation with K2Cr2O7-H2SO4 and titration of non-reduced dichromate according to ISO 10694 [48], and carbonate content was determined from the volume of CO2 produced during the decomposition of carbonates with about 10% hydrochloric acid, according to ISO 10693 [49]. Soil samples were taken randomly within an area of 25 m2 from the surface (0–5 cm) layer at S1, S2, and S3 sites in September 2021.

2.4. Statistical Treatment

The statistical analysis to find differences between the characteristics estimated in different sites was performed with NCSS 12 Statistical Software [50], using single-factor ANOVA and Tukey’s Honestly Significant Difference (HSD) posthoc test (p < 0.05). The Tukey–Kramer method (also known as Tukey’s HSD (Honest Significant Difference) method) uses the Studentized Range distribution to compute the adjustment to cα. The Tukey–Kramer method achieves the exact alpha level (and simultaneous confidence level (1 – α)) if the group sample sizes are equal and is conservative if the sample sizes are unequal. The Tukey–Kramer test is one of the most powerful all-pairs testing procedures and is widely used.
The Tukey–Kramer adjusted critical value for tests and simultaneous confidence intervals is
cα = q1−α,k,v/√2
where q1−α,k,v is the (1 − α) quantile of the Studentized range distribution.
NCSS 12 was used also to determine an appropriate mathematical model (among pre-programmed 39 models), representing relationships between a dependent (WDPT and T) and a single independent variable (Cr) and to estimate the values of its parameters. Each dataset was fitted with all 39 models and the most appropriate model was selected according to the highest value of the coefficient of determination (R2), which is a statistical measure of how well the regression model fits the data. R2 may be defined either as a ratio or a percentage. Since we used the ratio form, its values ranged from zero to one. A value of R2 near zero indicates no linear relationship between the Y and the X’s, while a value near one indicates a perfect fit.

3. Results

Basic soil-physical and -chemical properties are presented in Table 1. Sand content increased and the content of small (silt and clay) particles decreased during the 30-year lasting abandonment of agricultural fields in Studienka. The pH(H2O) and pH(KCl) decreased monotonously during the 30-year lasting abandonment of agricultural fields in Studienka. In contrast, the increase in SOC was registered between 1 and 10 years and a slight decrease between 10 and 30 years of abandonment.
The hydrophysical and water repellency characteristics of soil properties of the top layer of acidic sandy soils from the sites S1, S2, and S3 are presented in Table 2 and Figure 2 and Figure 3. The measured values of the actual volumetric water content, w, were minimal at all sites due to the hot and rainless period. The hydrophysical characteristics k(−2 cm) and Sw(−2 cm) showed the same course, i.e., a decrease between 1 and 10 years followed by a slight increase between 10 and 30 years of abandonment of agricultural fields in Studienka. The water repellency characteristics WDPT and RI showed the opposite course, i.e., an increase between 1 and 10 years followed by a slight decrease between 10 and 30 years of abandonment of agricultural fields in Studienka. The ethanol sorptivity did not change significantly during abandonment similar to our previous study [43]. As the ethanol sorptivity depends mainly on soil pore size, the last finding could mean that the pore size of acidic sandy soils did not change during succession.
The results of surface runoff experiments are presented in Table 2 and Table 3. It was found that the 15-min sprinkling intensity, ir, set by the height of an aeration tube (8 cm), varied between 1.55 mm min−1 and 1.92 mm min−1 (Table 3), with an average value of 1.78 mm min−1. Despite high sprinkling intensities, no surface runoff was observed at S1 because the mean value of 15-min sprinkling intensity (ir = 0.0297 mm s−1) was smaller than the mean value of hydraulic conductivity (k = 0.104 mm s−1). At severely and extremely water repellent sites S2, resp. S3, surface runoff was detected during each simulation.
The surface runoff coefficient, Cr, showed an increase between 1 and 10 years followed by a decrease between 10 and 30 years of abandonment, i.e., a course similar to the WDPT dependence on the duration of field abandonment. The time to runoff, T, did not change significantly between 10 and 30 years of abandonment, and it was not measured after 1 year of abandonment because no runoff occurred. The Cr vs. T relationship is presented in Figure 4 and described by the exponential model Cr = e−0.041(T−16.88), R2 = 0.69.
The surface runoff coefficient, Cr, and time to runoff, T, in sandy soil in a sequence of three consecutive rain events conducted at sites S2 and S3 at Studienka village in the Borská nížina lowland (southwestern Slovakia) are presented in Figure 5. At site S2, the surface runoff coefficient increased during the second rain in comparison with the first rain, and then slightly decreased during the third rain. At site S3, the surface runoff coefficient slightly decreased during the consecutive rains (first rain > second rain > third rain). The time to runoff increased monotonously during the consecutive rains (first rain < second rain < third rain) at S2 and S3.

4. Discussion

In the sites under extensive arable use, the topsoil containing thatch extracts and root mucilages is mixed with the subsoil, and, therefore, these water repellent compounds cannot induce the topsoil water repellency. After the abandonment of agricultural fields, the water repellent compounds accumulate in topsoil and the persistence and severity of water repellency increase over time as a result of an increase in SOC and a decrease in pH. This increase in SWR results in a decrease in infiltration and in an increase in runoff.
It was found in our study that the pH(H2O) decreased monotonously from 6.11 to 5.21 after the 30-year lasting abandonment of agricultural fields in Studienka. A similar decrease in pH values (from 5.3 to 4.7) was observed in sandy soil after almost 30-year lasting abandonment of agricultural fields at Stanisławów in Central Poland [19]. Wang et al. (2011) [51] also found that the pH of sandy loam soil decreased linearly with increasing time since abandonment. Acidification can be promoted by vegetation supplying raw humus [52].
The increase in SOC was registered between 1 and 10 years and a slight decrease between 10 and 30 years of abandonment. It could be due to weak organic fertilization of arable land at site S1 resulting in the low SOC value (SOC = 0.66%), as SOC = 1.80% was measured in acidic sandy soil planted with barley (Hordeum vulgare L.) in this region [43]. The increase in SOC obtained during the 30-year lasting abandonment of agricultural fields in Studienka is consistent with the findings of Hewelke [19] who found a slightly smaller increase in SOC between the site remaining under extensive arable use (0.89 ± 0.13%) and post-arable site in Central Poland abandoned for 30 years and covered by self-sown Scots pine (1.25 ± 0.19%). Gispert et al. [53] found a significantly higher increase in SOC between recently abandoned shallow loamy sand soil under vines (0.251 ± 0.025%) and sandy loam soil in grassland (3.624 ± 0.075%) in northeast Spain. It should be mentioned that the former vineyard was at an altitude of 65 m a.s.l. and the pasture at 260 m a.s.l. The SOC content in the top layer of acidic silt loam soil under grass cover in Hněvčeves, the Czech Republic, was 1.74% [54]. It seems that the higher clay and silt content can result in a better ability to accumulate organic matter.
The decrease in the volumetric water content, w, was registered between 1 and 10 years followed by its slight increase between 10 and 30 years of abandonment of agricultural fields in Studienka. This course could result from the field area size and the presence of trees and shrubs at the edges of abandoned fields. Sites S1 and S3 were substantially smaller than site S2 and surrounded by trees and shrubs at the edges, but there were no trees and shrubs on site S2. The presence of trees and shrubs could reduce wind speed and thus the evaporation of water from the soil [55].
The unusually high values of hydraulic conductivity, k(−2 cm), and water sorptivity, Sw(−2 cm) at site S1 could result from the higher value of volumetric water content at this site in comparison with that at sites S2 and S3. Moret-Fernández et al. [56] found that the Sw in sandy soil increased monotonously with an increase in w from 7 to 30%. The k increased significantly with an increase in w from 7 to 15%, followed by a negligible k increase with an increase in w from 15 to 30%. Hewelke et al. [57] found that the Sw in sandy soil increased with an increase in w from 5 to 20% and decreased with an increase in w from 20 to 35% at the forested and arable sites. They found a continual increase in Se with a decrease in w from 35 to 5% at the forested and arable sites. Lucas-Borja et al. [22] measured k = 0.0022 mm s−1 (about two times higher than mean k measured at S2 site) in slightly repellent clay loam soil at farmland abandoned about 15 years ago and now mainly covered by herbs and shrubs.
The decrease in water repellent (WDPT and RI) characteristics between 10 and 30 years of abandonment of agricultural fields in Studienka was also surprising to us because in our previous studies in this region, SWR at the grassland grew with age [31] and the Scots pine needles and root exudates made it even bigger [58,59]. Buczko et al. [60] found extremely (WDPT > 3600 s) water repellent sandy soil at the experimental 84-year-old Scots pine (Pinus sylvestris) stand Kahlenberg in Germany, and Hewelke [19] estimated the median of measured WDPT values equal to 17,700 s in sandy soil covered by self-sown Scots pine after almost 30-year lasting abandonment of agricultural fields in Central Poland. This extremely high WDPT value was explained by the significant decrease in moisture in the surface layer of the abandoned soil [13]. Hewelke et al. [57] found that RI increased from 5 to 230 with a decrease in w from 13 to 8% at the forested site, and RI increased from 5 to 15 with a decrease in w from 11 to 5% at the arable site. In our former study on abandoned fields with alkaline soil in Csólyospálos, Hungary, WDPT and RI showed an increase between 1 and 17 years followed by a slight decrease between 17 and 44 years of abandonment [31].
Median and mean of the runoff coefficients were 0.08 and 0.236 at S2 and 0.12 and 0.138 at S3, respectively. A substantially higher range of the values of runoff coefficients was estimated by Hlavčová et al. [61] in loamy soil with different plant cover. They found very low values of runoff coefficients with a median of 0.015 for the bare soil and no-tillage farming and the highest values of runoff coefficients with a median of 0.322 for the bare soil and the sowed winter crop with a high initial soil water content. On the other hand, Yu et al. [62] found very low values of runoff coefficients in loamy soil with different plant cover. Müller et al. [27] found a decrease in runoff coefficient during ten consecutive rain events, with Cr = 0.89 and 0.12 for events 1 and 10, respectively. Leitinger et al. [63] found a mean surface runoff coefficient of 0.01 on abandoned areas and 0.18 on pastures with sandy loam soil. Nunes et al. [64] estimated the mean surface runoff coefficient of 0.1574 for the agriculturally used plot with sandy loam soil, and 0.3306, 0.0480, and 0.0025 for the plots with sandy loam soil after 4–5, 15–20, and 30–40 years of abandonment, respectively. Cerdà et al. [65] determined the highest mean surface runoff coefficient of 0.772 in the agriculturally used plot with clay-loam soil, and 0.718, 0.51, 0.423, 0.323, 0.223, and 0.128 in the abandoned plots with clay-loam soil after 1, 2, 3, 5, 7, and 10 years of abandonment, respectively. The reported results of runoff experiments performed on wettable (or partially water-repellent) soils showed the opposite trend of the relationship between the surface runoff coefficient and the time since abandonment (lower values of Cr at the long-abandoned plots and higher values at the active/shortly abandoned plots) as in our study on water-repellent soils.
Median and mean of the time to runoff were 67 s and 144 s at S2 and 80 s and 154 s at S3, respectively. Similar median values of the time to runoff were estimated by Hlavčová et al. [61] in loamy soil with different plant cover. They found that the median of the time to runoff decreased with an increase in initial soil water content and ranged from 32 s for sowed winter crop (low soil water content) to 175 s for 15-cm-tall winter crop (high soil water content). Substantially higher values of the time to runoff were estimated by Bogunovic et al. [66] in clay soil in vegetable cropland, tilled olives, and grass-covered olive orchards. They found that the value of time to runoff parameter ranged from 180 to 300 s (mean 225.6 s) in vegetable cropland plots, from 420 to 1020 s (mean 652.5 s) in tilled olive orchard plots and from 660 to 1140 s (mean 840 s) in grass-covered olive orchard plots. Cerdà et al. [65] found that the time to a runoff ranged from 88.3 s in the agriculturally used plot to 917 s in a 10-year abandoned plot with clay-loam soil. Nunes et al. [64] estimated the median value of time to runoff of 16.37 min for the agriculturally used plot with sandy loam soil, and 9.55 min and 11.23 min for the plots with sandy loam soil after 4–5 and 15–20 years of abandonment, respectively. The trend of the time to runoff vs. time since abandonment relationship in the above-mentioned studies (higher values of the time to runoff at the sites abandoned a long time and lower values at the sites abandoned a short time or agriculturally used) is the opposite of this trend in our study in water-repellent soils.

5. Conclusions

The present study evidenced that the abandoned soils previously subjected to agriculture showed a decrease in pH, a significant increase in soil water repellency, and a decrease in infiltration. If these soils had low SOC due to poor management, SOC increased in the early stages of their abandonment. The small hydraulic conductivity of abandoned soils previously subjected to agriculture can cause serious problems in terms of surface runoff and soil erosion. To prevent soil water repellency and its consequences in abandoned sandy soils, an adequately high soil water content should be maintained, and mixed forest afforestation should be preferred to pine afforestation. This is extremely important in the context of climate change and the increasing frequency of prolonged dry periods.

Author Contributions

Conceptualization, Ľ.L. and P.Š.; methodology, Ľ.L., P.Š. and J.K.; validation, Ľ.L. and P.Š.; formal analysis, Ľ.L. and P.Š.; investigation, L.T., S.H., P.Š., J.K. and Ľ.L.; resources, Ľ.L.; data curation, L.T., S.H., P.Š., J.K. and Ľ.L.; writing—original draft preparation, L.T., P.Š., J.K. and Ľ.L.; writing—review and editing, L.T., P.Š., J.K. and Ľ.L.; visualization, Ľ.L. and P.Š.; supervision, P.Š.; project administration, P.Š.; funding acquisition, Ľ.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Slovak Scientific Grant Agency (VEGA) grant number 2/0020/20 and the European Regional Development Fund grant number 313011W112.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors thank the three reviewers and Academic Editor for their wise comments and suggestions. This work was supported by the Slovak Scientific Grant Agency (VEGA) project 2/0020/20 and the project “Sustainable smart farming systems taking into account the future challenges 313011W112”, co-financed by the European Regional Development Fund within the operational program Integrated infrastructure.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

RI = repellency index; SOC = soil organic carbon; SWR = soil water repellency; WDPT = water drop penetration time.

References

  1. Cerdà, A.; Rodrigo-Comino, J.; Novara, A.; Brevik, E.C.; Vaezi, A.R.; Pulido, M.; Giménez-Morera, A.; Keesstra, S.D. Long-term impact of rainfed agricultural land abandonment on soil erosion in the Western Mediterranean basin. Prog. Phys. Geogr. Earth Environ. 2018, 2, 202–219. [Google Scholar] [CrossRef]
  2. Csecserits, A.; Czucz, B.; Halassy, M.; Kröel-Dulay, G.; Rédei, T.; Szabó, R.; Szitár, K.; Török, K. Regeneration of sandy old-fields in the forest steppe region of Hungary. Plant Biosyst. 2011, 145, 715–729. [Google Scholar] [CrossRef]
  3. Lasanta, T.; Sánchez-Navarrete, P.; Medrano-Moreno, L.M.; Khorchani, M.; Nadal-Romero, E. Soil quality and soil organic carbon storage in abandoned agricultural lands: Effects of revegetation processes in a Mediterranean mid-mountain area. Land Degrad. Dev. 2020, 31, 2830–2845. [Google Scholar] [CrossRef]
  4. Apostolakis, A.; Panakoulia, S.; Nikolaidis, N.P.; Paranychianakis, N.V. Shifts in soil structure and soil organic matter in a chronosequence of set-aside fields. Soil Tillage Res. 2017, 174, 113–119. [Google Scholar] [CrossRef]
  5. Kozak, M.; Pudelko, R. Impact assessment of the long-term fallowed land on agricultural soils and the possibility of their return to agriculture. Agriculture 2021, 11, 148. [Google Scholar] [CrossRef]
  6. Fér, M.; Kodešová, R.; Hroníková, S.; Nikodem, A. The effect of 12-year ecological farming on the soil hydraulic properties and repellency index. Biologia 2020, 75, 799–807. [Google Scholar] [CrossRef]
  7. Novák, V.; Lichner, Ľ.; Zhang, B.; Kňava, K. The impact of heating on the hydraulic properties of soils sampled under different plant cover. Biologia 2009, 64, 483–486. [Google Scholar] [CrossRef]
  8. Bayad, M.; Chau, H.W.; Trolove, S.; Moir, J.; Condron, L.; Bouray, M. The relationship between soil moisture and soil water repellency persistence in hydrophobic soils. Water 2020, 12, 2322. [Google Scholar] [CrossRef]
  9. Leelamanie, D.A.L.; Nishiwaki, J. Water repellency in Japanese coniferous forest soils as affected by drying temperature and moisture. Biologia 2019, 74, 127–137. [Google Scholar] [CrossRef]
  10. Czachor, H.; Rajkai, K.; Lichner, L.; Jozefaciuk, G. Sample geometry affects water retention curve: Simulation and experimental proves. J. Hydrol. 2020, 588, 125131. [Google Scholar] [CrossRef]
  11. Benito, E.; Varela, E.; Rodríguez-Alleres, M. Persistence of water repellency in coarse-textured soils under various types of forests in NW Spain. J. Hydrol. Hydromech. 2019, 67, 129–134. [Google Scholar] [CrossRef] [Green Version]
  12. Diehl, D.; Bayer, J.V.; Woche, S.K.; Bryant, R.; Doerr, S.H.; Schaumann, G.E. Reaction of soil water repellency to artificially induced changes in soil pH. Geoderma 2010, 158, 375–384. [Google Scholar] [CrossRef]
  13. Mielnik, L.; Hewelke, E.; Weber, J.; Oktaba, L.; Jonczak, J.; Podlasiński, M. Changes in the soil hydrophobicity and structure of humic substances in sandy soil taken out of cultivation. Agric. Ecosyst. Environ. 2021, 319, 107554. [Google Scholar] [CrossRef]
  14. Lichner, Ľ.; Babejová, N.; Dekker, L.W. Effects of kaolinite and drying temperature on the persistence of soil water repellency induced by humic acids. Rostl. Výroba 2002, 48, 203–207. [Google Scholar] [CrossRef] [Green Version]
  15. Täumer, K.; Stoffregen, H.; Wessolek, G. Seasonal dynamics of preferential flow in a water repellent soil. Vadose Zone J. 2006, 5, 405–411. [Google Scholar] [CrossRef]
  16. Sepehrnia, N.; Hajabbasi, M.A.; Afyuni, M.; Lichner, Ľ. Soil water repellency changes with depth and relationship to physical properties within wettable and repellent soil profiles. J. Hydrol. Hydromech. 2017, 65, 99–104. [Google Scholar] [CrossRef] [Green Version]
  17. Turski, M.; Lipiec, J.; Chodorowski, J.; Sokołowska, Z.; Skic, K. Vertical distribution of soil water repellency in ortsteinic soils in relation to land use. Soil Tillage Res. 2022, 215, 105220. [Google Scholar] [CrossRef]
  18. Sándor, R.; Iovino, M.; Lichner, L.; Alagna, V.; Forster, D.; Fraser, M.; Kollár, J.; Šurda, P.; Nagy, V.; Szabó, A.; et al. Impact of climate, soil properties and grassland cover on soil water repellency. Geoderma 2021, 383, 114780. [Google Scholar] [CrossRef]
  19. Hewelke, E. Influence of abandoning agricultural land use on hydrophysical properties of sandy soil. Water 2019, 11, 525. [Google Scholar] [CrossRef] [Green Version]
  20. Long, Y.; Liu, J.L.; Huang, T.M. Impact of afforestation on soil hydraulic conductivity and repellency index based on microdisk infiltration experiment. Fresenius Environ. Bull. 2020, 29, 5855–5859. [Google Scholar]
  21. Zema, D.A.; Plaza-Alvarez, P.A.; Xu, X.Z.; Carra, B.G.; Lucas-Borja, M.E. Influence of forest stand age on soil water repellency and hydraulic conductivity in the Mediterranean environment. Sci. Total Environ. 2021, 753, 142006. [Google Scholar] [CrossRef] [PubMed]
  22. Lucas-Borja, M.E.; Zema, D.A.; Plaza-Álvarez, P.A.; Zupanc, V.; Baartman, J.; Sagra, J.; González-Romero, J.; Moya, D.; de las Heras, J. Effects of different land uses (abandoned farmland, intensive agriculture and forest) on soil hydrological properties in Southern Spain. Water 2019, 11, 503. [Google Scholar] [CrossRef] [Green Version]
  23. Shillito, R.M.; Berli, M.; Ghezzehei, T.A. Quantifying the effect of subcritical water repellency on sorptivity: A physically based model. Water Resour. Res. 2020, 56, e2020WR027942. [Google Scholar] [CrossRef]
  24. Lemmnitz, C.; Kuhnert, M.; Bens, O.; Güntner, A.; Merz, B.; Hüttl, R.F. Spatial and temporal variations of actual soil water repellency and their influence on surface runoff. Hydrol. Processes 2008, 22, 1976–1984. [Google Scholar] [CrossRef]
  25. Miyata, S.; Kosugi, K.; Nishi, Y.; Gomi, T.; Sidle, R.C.; Mizuyama, T. Spatial pattern of infiltration rate and its effect on hydrological processes in a small headwater catchment. Hydrol. Processes 2010, 24, 535–549. [Google Scholar] [CrossRef]
  26. Miyata, S.; Kosugi, K.; Gomi, T.; Onda, Y.; Mizuyama, T. Surface runoff as affected by soil water repellency in a Japanese cypress forest. Hydrol. Process. 2007, 21, 2365–2376. [Google Scholar] [CrossRef]
  27. Müller, K.; Mason, K.; Strozzi, A.G.; Simpson, R.; Komatsu, T.; Kawamoto, K.; Clothier, B. Runoff and nutrient loss from a water-repellent soil. Geoderma 2018, 322, 28–37. [Google Scholar] [CrossRef] [Green Version]
  28. Rodrigo-Comino, J.; Martinez-Hernandez, C.; Iserloh, T.; Cerda, A. Contrasted impact of land abandonment on soil erosion in Mediterranean agriculture fields. Pedosphere 2018, 28, 617–631. [Google Scholar] [CrossRef] [Green Version]
  29. Liang, Y.; Jiao, J.Y.; Tang, B.Z.; Cao, B.T.; Li, H. Response of runoff and soil erosion to erosive rainstorm events and vegetation restoration on abandoned slope farmland in the Loess Plateau region, China. J. Hydrol. 2020, 584, 124694. [Google Scholar] [CrossRef]
  30. Zhang, J.L.; Zhou, L.L.; Ma, R.M.; Jia, Y.F.; Yang, F.; Zhou, H.Y.; Cao, X.Y. Influence of soil moisture content and soil and water conservation measures on time to runoff initiation under different rainfall intensities. Catena 2019, 182, 104172. [Google Scholar] [CrossRef]
  31. Lichner, L.; Felde, V.J.M.N.L.; Büdel, B.; Leue, M.; Gerke, H.H.; Ehlerbrock, R.H.; Kollár, J.; Rodný, M.; Šurda, P.; Fodor, N.; et al. Effect of vegetation and its succession on water repellency in sandy soils. Ecohydrology 2018, 11, e1991. [Google Scholar] [CrossRef]
  32. Csecserits, A.; Rédei, T. Secondary succession on sandy old-fields in Hungary. Appl. Veg. Sci. 2001, 4, 63–74. [Google Scholar] [CrossRef]
  33. Kottek, M.; Grieser, J.; Beck, C.; Rudolf, B.; Rubel, F. World map of the Köppen-Geiger climate classification updated. Meteorol. Z. 2006, 15, 259–263. [Google Scholar] [CrossRef]
  34. FAO. World Reference Base for Soil Resources 2014. In World Soil Resources Reports; No. 106; FAO: Rome, Italy, 2014; p. 192. [Google Scholar]
  35. Ditzler, C.; Scheffe, K.; Monger, H.C. (Eds.) Soil Survey Manual. U.S. Department of Agriculture Handbook 18; Government Printing Office: Washington, DC, USA, 2017; p. 603. [Google Scholar]
  36. Marhold, K.; Hindák, F. (Eds.) Checklist of Non-Vascular and Vascular Plants of Slovakia; Veda: Bratislava, Slovakia, 1998; p. 687. (In Slovak) [Google Scholar]
  37. Decagon Devices Inc. Mini Disk Infiltrometer—User′s Manual, Version 10; Decagon Devices Inc.: Pullman, WA, USA, 2012. [Google Scholar]
  38. Clothier, B.E.; Vogeler, I.; Magesan, G.N. The breakdown of water repellency and solute transport through a hydrophobic soil. J. Hydrol. 2000, 231, 255–264. [Google Scholar] [CrossRef]
  39. Pekárová, P.; Pekár, J.; Lichner, L. A new method for estimating soil water repellency index. Biologia 2015, 70, 1450–1455. [Google Scholar] [CrossRef]
  40. Iovino, M.; Pekárová, P.; Hallett, P.D.; Pekár, J.; Lichner, Ľ.; Mataix-Solera, J.; Alagna, V.; Walsh, R.; Raffan, A.; Schacht, K.; et al. Extent and persistence of soil water repellency induced by pines in different geographic regions. J. Hydrol. Hydromech. 2018, 66, 360–368. [Google Scholar] [CrossRef] [Green Version]
  41. Tinebra, I.; Alagna, V.; Iovino, M.; Bagarello, V. Comparing different application procedures of the water drop penetration time test to assess soil water repellency in a fire affected Sicilian area. Catena 2019, 177, 41–48. [Google Scholar] [CrossRef]
  42. Dekker, L.W.; Ritsema, C.J.; Oostindie, K.; Moore, D.; Wesseling, J.A. Methods for determining soil water repellency on field-moist samples. Water Resour. Res. 2009, 45, W00D33. [Google Scholar] [CrossRef]
  43. Lichner, L.; Iovino, M.; Šurda, P.; Nagy, V.; Zvala, A.; Kollár, J.; Pecho, J.; Píš, V.; Sepehrnia, N.; Sándor, R. Impact of secondary succession in abandoned fields on some properties of acidic sandy soils. J. Hydrol. Hydromech. 2020, 68, 12–18. [Google Scholar] [CrossRef] [Green Version]
  44. Zhang, R. Determination of soil sorptivity and hydraulic conductivity from the disk infiltrometer. Soil Sci. Soc. Am. J. 1997, 61, 1024–1030. [Google Scholar] [CrossRef]
  45. Kamphorst, A. A small rainfall simulator for the determination of soil erodibility. Neth. J. Agric. Sci. 1987, 35, 407–415. [Google Scholar] [CrossRef]
  46. ISO 11277. Soil Quality. Determination of Particle Size Distribution in Mineral Soil Material. Method by Sieving and Sedimentation. International Organization of Standardization: Geneva, Switzerland, 2009. Available online: https://www.iso.org/standard/54151.html (accessed on 1 December 2021).
  47. ISO 10390. Soil Quality. Determination of pH. International Organization of Standardization: Geneva, Switzerland, 2005. Available online: https://www.iso.org/standard/40879.html (accessed on 1 December 2021).
  48. ISO 10694. Soil Quality. Determination of Organic and Total Carbon after Dry Combustion (Elementary Analysis). International Organization of Standardization: Geneva, Switzerland, 1995. Available online: https://www.iso.org/standard/18782.html (accessed on 1 December 2021).
  49. ISO 10693. Soil Quality. Determination of Carbonate Content. Volumetric Method. International Organization of Standardization: Geneva, Switzerland, 1995. Available online: https://www.iso.org/standard/18781.html (accessed on 1 December 2021).
  50. NCSS 12 Statistical Software; NCSS, LLC.: Kaysville, UT, USA, 2018. Available online: https://www.ncss.com/software/ncss/ (accessed on 10 October 2021).
  51. Wang, B.; Liu, G.B.; Xue, S.; Zhu, B.B. Changes in soil physico-chemical and microbiological properties during natural succession on abandoned farmland in the Loess Plateau. Environ. Earth Sci. 2011, 62, 915–925. [Google Scholar] [CrossRef]
  52. Kuntze, H.; Schwaar, J. Landeskulturelle Aspekte zur Boden- und Vegetationsentwicklung aufgelassenen Kulturlandes. (Cultivation aspects for soil and vegetation development on idle agricultural land). Z. Kult. Flurberein. 1972, 13, 131–136. (In German) [Google Scholar]
  53. Gispert, M.; Pardini, G.; Emran, M.; Doni, S.; Masciandaro, G. Seasonal evolution of soil organic matter, glomalin and enzymes and potential for C storage after land abandonment and renaturalization processes in soils of NE Spain. Catena 2018, 162, 402–413. [Google Scholar] [CrossRef]
  54. Kodešová, R.; Jirků, V.; Kodeš, V.; Mühlhanselová, M.; Nikodem, A.; Žigová, A. Soil structure and soil hydraulic properties of Haplic Luvisol used as arable land and grassland. Soil Tillage Res. 2011, 111, 154–161. [Google Scholar] [CrossRef]
  55. Davarzani, H.; Smits, K.; Tolene, R.M.; Illangasekare, T. Study of the effect of wind speed on evaporation from soil through integrated modeling of the atmospheric boundary layer and shallow subsurface. Water Resour. Res. 2014, 50, 661–680. [Google Scholar] [CrossRef] [Green Version]
  56. Moret-Fernández, D.; Latorre, B.; Giner, M.L.; Ramos, J.; Alados, C.L.; Castellano, C.; López, M.V.; Jimenez, J.J.; Pueyo, Y. Estimation of the soil hydraulic properties from the transient infiltration curve measured on soils affected by water repellency. Catena 2019, 178, 298–306. [Google Scholar] [CrossRef]
  57. Hewelke, E.; Gozdowski, D.; Korc, M.; Małuszyńska, I.; Górska, E.B.; Sas, W.; Mielnik, L. Influence of soil moisture on hydrophobicity and water sorptivity of sandy soil no longer under agricultural use. Catena 2022, 208, 105780. [Google Scholar] [CrossRef]
  58. Lichner, Ľ.; Holko, L.; Zhukova, N.; Schacht, K.; Rajkai, K.; Fodor, N.; Sándor, R. Plants and biological soil crust influence the hydrophysical parameters and water flow in an aeolian sandy soil. J. Hydrol. Hydromech. 2012, 60, 309–318. [Google Scholar] [CrossRef] [Green Version]
  59. Šurda, P.; Lichner, Ľ.; Kollár, J.; Zvala, A.; Igaz, D. Evaluation of soil properties in variously aged Scots pine plantations established on sandy soil. J. Hydrol. Hydromech. 2021, 69, 347–355. [Google Scholar] [CrossRef]
  60. Buczko, U.; Bens, O.; Hüttl, R.F. Variability of soil water repellency in sandy forest soils with different stand structure under Scots pine (Pinus sylvestris) and beech (Fagus sylvatica). Geoderma 2005, 126, 317–336. [Google Scholar] [CrossRef]
  61. Hlavčová, K.; Danáčová, M.; Kohnová, S.; Szolgay, J.; Valent, P.; Výleta, R. Estimating the effectiveness of crop management on reducing flood risk and sediment transport on hilly agricultural land—A Myjava case study, Slovakia. Catena 2019, 172, 678–690. [Google Scholar] [CrossRef]
  62. Yu, Y.; Wei, W.; Chen, L.D.; Feng, T.J.; Daryanto, S. Quantifying the effects of precipitation, vegetation, and land preparation. techniques on runoff and soil erosion in a Loess watershed of China. Sci. Total Environ. 2019, 652, 755–764. [Google Scholar] [CrossRef] [PubMed]
  63. Leitinger, G.; Tasser, E.; Newesely, C.; Obojes, N.; Tappeiner, U. Seasonal dynamics of surface runoff in mountain grassland ecosystems differing in land use. J. Hydrol. 2010, 385, 95–104. [Google Scholar] [CrossRef]
  64. Nunes, A.N.; Coelho, C.O.A.; de Almeida, A.C.; Figueiredo, A. Soil erosion and hydrological response to land abandonment in a central inland area of Portugal. Land Degrad. 2010, 21, 260–273. [Google Scholar] [CrossRef]
  65. Cerdà, A.; Ackermann, O.; Terol, E.; Rodrigo-Comino, J. Impact of farmland abandonment on water resources and soil conservation in citrus plantations in eastern Spain. Water 2019, 11, 824. [Google Scholar] [CrossRef] [Green Version]
  66. Bogunovic, I.; Telak, L.J.; Pereira, P.; Filipovic, V.; Filipovic, L.; Percin, A.; Durdevic, B.; Birkás, M.; Dekemati, I.; Comino, J.R. Land management impacts on soil properties and initial soil erosion processes in olives and vegetable crops. J. Hydrol. Hydromech. 2020, 68, 328–337. [Google Scholar] [CrossRef]
Agriculture 12 00168 g001 550
Figure 1. Location and areal view of the studied area with experimental sites S1 (a), S2 (b), and S3 (c) located at Studienka village in the Borská nížina lowland (southwestern Slovakia).
Figure 1. Location and areal view of the studied area with experimental sites S1 (a), S2 (b), and S3 (c) located at Studienka village in the Borská nížina lowland (southwestern Slovakia).
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Figure 2. Relationships between hydraulic conductivity, k(−2 cm), water sorptivity, Sw(−2 cm), ethanol sorptivity, Se(−2 cm), and repellency index, RI, estimated in the top layer of acidic sandy soils, and duration of field abandonment at experimental sites S1, S2, and S3 located at Studienka village in the Borská nížina lowland (southwestern Slovakia). Note that both vertical axes have a logarithmic scale.
Figure 2. Relationships between hydraulic conductivity, k(−2 cm), water sorptivity, Sw(−2 cm), ethanol sorptivity, Se(−2 cm), and repellency index, RI, estimated in the top layer of acidic sandy soils, and duration of field abandonment at experimental sites S1, S2, and S3 located at Studienka village in the Borská nížina lowland (southwestern Slovakia). Note that both vertical axes have a logarithmic scale.
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Figure 3. Relationships between soil organic carbon (SOC) content, pH (H2O), water drop penetration time, WDPT, time to runoff, T, and surface runoff coefficient, Cr, estimated in the top layer of acidic sandy soils, and duration of field abandonment at experimental sites S1, S2, and S3 located at Studienka village in the Borská nížina lowland (southwestern Slovakia). Note that both vertical axes have a logarithmic scale.
Figure 3. Relationships between soil organic carbon (SOC) content, pH (H2O), water drop penetration time, WDPT, time to runoff, T, and surface runoff coefficient, Cr, estimated in the top layer of acidic sandy soils, and duration of field abandonment at experimental sites S1, S2, and S3 located at Studienka village in the Borská nížina lowland (southwestern Slovakia). Note that both vertical axes have a logarithmic scale.
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Figure 4. The relationships of surface runoff coefficient, Cr, vs. time to runoff, T, in sandy soil at experimental sites S2 and S3 at Studienka village in the Borská nížina lowland (southwestern Slovakia). (Black line—regression curve, red area—the upper and lower boundaries of a prediction interval at a specific value of T, black dots—measured values).
Figure 4. The relationships of surface runoff coefficient, Cr, vs. time to runoff, T, in sandy soil at experimental sites S2 and S3 at Studienka village in the Borská nížina lowland (southwestern Slovakia). (Black line—regression curve, red area—the upper and lower boundaries of a prediction interval at a specific value of T, black dots—measured values).
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Figure 5. The surface runoff coefficient, Cr (a) and time to runoff, T (b) in sandy soil in a sequence of three consecutive rain events conducted at sites S2 and S3 at Studienka village in the Borská nížina lowland (southwestern Slovakia).
Figure 5. The surface runoff coefficient, Cr (a) and time to runoff, T (b) in sandy soil in a sequence of three consecutive rain events conducted at sites S2 and S3 at Studienka village in the Borská nížina lowland (southwestern Slovakia).
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Table
Table 1. Physical and chemical properties of the top (0–5 cm) soils taken from the experimental sites S1, S2, and S3. The results are presented in the form: arithmetic mean ± standard deviation. (SOC—soil organic carbon).
Table 1. Physical and chemical properties of the top (0–5 cm) soils taken from the experimental sites S1, S2, and S3. The results are presented in the form: arithmetic mean ± standard deviation. (SOC—soil organic carbon).
AttributeS1S2S3
Sand (%)91.936 ± 0.54495.377 ± 0.14094.503 ± 0.030
Silt (%)2.407 ± 0.4271.568 ± 0.0641.525 ± 0.051
Clay (%)5.657 ± 0.1173.055 ± 0.0763.972 ± 0.021
CaCO3 (%)<0.05<0.05<0.05
SOC (%)0.66 a ± 0.011.30 c ± 0.021.12 b ± 0.01
pH(H2O)6.11 a ± 0.015.90 b ± 0.015.21 c ± 0.01
pH(KCl)5.63 a ± 0.015.07 b ± 0.014.12 c ± 0.01
Properties denoted with different letters are significantly different on significance level 0.05.
Table
Table 2. Statistical characteristics of soil properties (namely the volumetric water content, w, hydraulic conductivity, k(−2 cm), water sorptivity, Sw(−2 cm), ethanol sorptivity, Se(−2 cm), water drop penetration time, WDPT, and repellency index, RI) of the top layer of acidic sandy soils from the sites S1, S2, and S3. (SD—standard deviation; N—number of replicates).
Table 2. Statistical characteristics of soil properties (namely the volumetric water content, w, hydraulic conductivity, k(−2 cm), water sorptivity, Sw(−2 cm), ethanol sorptivity, Se(−2 cm), water drop penetration time, WDPT, and repellency index, RI) of the top layer of acidic sandy soils from the sites S1, S2, and S3. (SD—standard deviation; N—number of replicates).
SiteAttributeMinimumMaximumMedianMeanSDN
S1w (% vol.)02.80.80.83 a0.7733
k (mm s−1)0.0460.2210.0970.104 a0.0568
Sw (mm s−1/2)1.0302.3511.4631.487 a0.4048
Se (mm s−1/2)2.4412.7272.5852.584 a0.1433
WDPT (s)1833.2 a1.933
RI (−)2.0255.1633.4543.583 a0.83724
Cr (−)0000 a09
T (s)n.d.n.d.n.d.n.d.n.d.0
S2w (% vol.)0000 b033
k (mm s−1)0.000010.0040.0010.001 b0.0018
Sw (mm s−1/2)0.0070.0180.010.011 b0.0038
Se (mm s−1/2)2.0552.1192.1092.094 a0.0343
WDPT (s)1156672020242625 c134133
RI (−)222.6590.3406.0416.3 c114.224
Cr (−)0.010.720.080.236 b0.2859
T (s)3052567144 a1659
S3w (% vol.)00.800.06 b0.1833
k (mm s−1)0.000030.0060.0010.002 b0.0038
Sw (mm s−1/2)0.0130.0320.020.020 b0.0068
Se (mm s−1/2)1.4241.9281.8981.750 a0.2833
WDPT (s)4039757101083 b105333
RI (−)86.8289.2177.6182.6 b55.524
Cr (−)0.010.300.120.138 a,b0.1119
T (s)5747880154 a1389
Properties denoted with different letters are significantly different on significance level 0.05.
Table
Table 3. Parameters of rainfall simulations (15-min sprinkling intensity, ir, 15-min rainfall total, Hr) and the volumetric water content, w, at the plots before the experiments and the slope of the runoff plots. N is the number of replicates of measurement at each study site.
Table 3. Parameters of rainfall simulations (15-min sprinkling intensity, ir, 15-min rainfall total, Hr) and the volumetric water content, w, at the plots before the experiments and the slope of the runoff plots. N is the number of replicates of measurement at each study site.
SiteAttributeMinimumMaximumMedianMeanSDN
S1ir (mm min−1)1.681.871.791.78 a0.0699
Hr (mm)25.228.126.926.67 a1.059
w (% vol)1.53.12.32.4 a0.499
slope (°)15161615.67 a0.583
S2ir (mm min−1)1.551.781.741.7 a0.0769
Hr (mm)23.226.7226.0825.60 a1.149
w (% vol)1.12.51.61.7 a0.459
slope (°)12161614.67 a2.313
S3ir (mm min−1)1.701.921.771.79 a0.0859
Hr (mm)25.4428.826.6026.79 a1.28 9
w (% vol)0.14.22.52.2 a1.429
slope (°)12141313.00 a1.003
Properties denoted with different letters are significantly different on significance level 0.05.
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Toková, L.; Hološ, S.; Šurda, P.; Kollár, J.; Lichner, Ľ. Impact of Duration of Land Abandonment on Infiltration and Surface Runoff in Acidic Sandy Soil. Agriculture 2022, 12, 168. https://doi.org/10.3390/agriculture12020168

AMA Style

Toková L, Hološ S, Šurda P, Kollár J, Lichner Ľ. Impact of Duration of Land Abandonment on Infiltration and Surface Runoff in Acidic Sandy Soil. Agriculture. 2022; 12(2):168. https://doi.org/10.3390/agriculture12020168

Chicago/Turabian Style

Toková, Lucia, Slavomír Hološ, Peter Šurda, Jozef Kollár, and Ľubomír Lichner. 2022. "Impact of Duration of Land Abandonment on Infiltration and Surface Runoff in Acidic Sandy Soil" Agriculture 12, no. 2: 168. https://doi.org/10.3390/agriculture12020168

APA Style

Toková, L., Hološ, S., Šurda, P., Kollár, J., & Lichner, Ľ. (2022). Impact of Duration of Land Abandonment on Infiltration and Surface Runoff in Acidic Sandy Soil. Agriculture, 12(2), 168. https://doi.org/10.3390/agriculture12020168

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