**1. Introduction**

Viticulture represents one of the most important agricultural activities worldwide, covering, at a global scale in 2018, 7.4 million ha [1]. In Europe, vineyards are mostly devoted to wine production, and, in 2016, they covered 3.3 million ha, and Italy, with 690.000 ha, was ranked third, after Spain and France [1]. The vineyard agro-ecosystem has relevant socio-economic impacts on the vine-growing regions, because of its interactions with the environment, landscape, the cultural and touristic features, and employment [2].

The vineyard agro-ecosystem needs to be carefully managed to preserve essential resources such as soil and water, and its overall socio-economic and environmental sustainability [3]. Since the last decade, a growing attention was paid to the impacts of agricultural activities on the ecosystem services, defined as "the direct and indirect contributions of ecosystems to human well-being" [4]. Such ecosystem services are negatively affected by soil degradation, namely soil compaction and soil erosion, offsite contamination, biodiversity reduction, and pressure on water resources [5–7]. Soil erosion and soil compaction were identified as two of the major threats that affect worldwide agricultural soils

by the Soil Thematic Strategy from the European Union [8,9] and the FAO Status of the World's Soil Resources [10].

Vineyard operations are highly mechanized, so the traffic of tractors and other machines (e.g., harvesters) necessarily occurs along fixed paths. Traffic is particularly intense from late spring to harvest and has a relevant effect on soil compaction, on soil hydraulic properties, and, consequently, on runoff and soil erosion at field scale [11–13]. The soil management that is adopted in vineyards' inter-rows, as well as in other permanent crops, such as fruit and olive orchards, affects the hydrological response of the soil, the ecosystem services, and the cultural, landscape, and aesthetic values. Several studies report cover crops (or grass cover) in the inter-rows as a soil management practice adopted to reduce runoff and soil erosion in vineyards, with differences in its effectiveness depending on local conditions [14–21]. The use of vegetation cover in vineyards also has a relevant effect in improving biodiversity [22], soil organic matter and physical properties [23], and water availability and trafficability [24]. The vineyard inter-row soil management has a fundamental impact on the water balance at field scale, due to its effects on evapotranspiration, runoff formation, and several hydrological characteristics of the soil, such as hydraulic conductivity, soil water content, soil water retention, and ground-water recharge [25–29]. Depending on the pedoclimatic context, when not properly managed, cover crops may affect grapevine yield because of the competition for water and nutrients [30–32]. For this reason, in semi-arid environments, the soil is usually maintained bare, while, in regions with a less-dry climate, different soil managements to improve soil quality and ecosystem services are adopted [33]. For example, in the framework of the 2007–2013, the local regional Rural Development Program the Piedmont region (NW Italy) set up and supported measures for soil erosion prevention and the maintenance of soil organic carbon (SOC) levels based on the grass covering on more than 13,000 ha of orchards and vineyards [34].

Wide use of machinery during vineyard plantation and management in modern viticulture affects soil and water conservation. Deep ploughing and, occasionally, land levelling are carried out with heavy machinery before plantation [35,36]. Multiple tractor passes on fixed paths in the inter-rows are required every year for operations such as mechanical weeding, chemical spreading, green and winter pruning, and harvesting [37]. The repeated tractor traffic in inter-rows causes soil compaction on most of the vineyard surface [37], and when operations are performed on wet soil conditions, the risk of soil compaction worsens [38]. Soil compaction increases soil resistance to roots' exploration, reduces yields [39,40], and negatively affects soil physical fertility and soil organic carbon stock, resulting in the reduction of soil porosity, water infiltration capacity, and increased runoff, with a decrease of storage and supply of water in the soil [11–13]. Scaling-up spatially the effects of soil compaction, the increase of surface runoff at field-scale impacts the peak discharge at the catchments scale, and thus could have a relevant role in increasing flood risk [40].

In the sloping vineyards of the Alto Monferrato region, previous studies showed the effectiveness of inter-rows' permanent grass cover in reducing runoff and soil erosion, with respect to soil management with tillage [12,16,20,41]. Such behavior is likely related to soil compaction induced by tractor traffic, which also influences soil water infiltration and retention. This study aimed to investigate the blended effects of soil management and tractor traffic on the spatial and temporal variability of soil compaction and both hydrological and erosional processes. Soil water content, rainfall, runoff, and soil erosion were continuously monitored for two years in coupled field-scale plots, with inter-rows managed with permanent grass cover and tillage, respectively. In addition, periodic surveys were carried out during the growing seasons, to measure temporal variations in soil compaction and field-saturated hydraulic conductivity after the implementation of tractor passages.

#### **2. Materials and Methods**

#### *2.1. Study Site*

The study was carried out at the Tenuta Cannona Experimental Vine and Wine Centre of Agrion Foundation. It is located in the Alto Monferrato hilly area of Piedmont, North-West Italy, at an average elevation of 296 m above sea level (a.s.l.) (Figure 1). The study site lies on Pleistocenic fluvial terraces in the Tertiary Piedmont Basin, including highly altered gravel, sand, and silty-clay deposits, with red alteration products [42]. Soil has a clay-to-clay-loam texture, and it is classified as Typic Ustorthents, fine-loamy, mixed, calcareous, mesic [43], or Dystric Cambisols [44]. The climate is Csa (Hot-summer Mediterranean climate in the Köppen climate classification [45]). The average annual precipitation value recorded in the experimental site in the period 2000–2016 was 852 mm, ranging from a minimum of 539 mm (year 2007) to a maximum of 1336 mm (year 2002). The annual mean air temperature in the same period was 13 ◦C. Rainfall is mainly concentrated in October and November (about 40% of annual precipitation observed in autumn), when major runoff events usually occur [46], and, secondarily, in March. Summer, particularly July, is the driest season, with 12% of annual precipitation.

**Figure 1.** Location of the Tenuta Cannona Experimental Vine and Wine Centre of Agrion Foundation. Photos show the two soil managements.

The 2-years' experiment was carried out in two vineyard plots (1221 m2, 6 rows aligned along the slope, spaced 2.75 m, where the vines are spaced 1.0 m along the row), located on a hillslope with average 15% slope and SE aspect. The vineyard was planted in 1988 with Barbera grape variety and managed according to conventional farming for wine production. The soil of the two plots was managed with different techniques since 2000. Twice a year, in spring and autumn, either cultivation with chisel at a depth of about 0.25 m or mulching of the spontaneous grass cover was carried out, in the conventional tillage plot (CT, hereafter) and in the controlled grass (GC), respectively. Most of the farming operations in the vineyard were carried out using tracked or tyred tractors (Table 1), carrying or towing implements, with passage intensification from spring to the grape harvest time. The dates of tractor passages and field measurements are reported in Table 2, along with soil water content measured during surveys.


**Table 1.** Tractors' characteristics.

**Table 2.** Dates in bold indicate field measurements: values of soil water content (SWC, m<sup>3</sup> m<sup>−</sup>3) measured in the conventional tillage plot (CT) and in the controlled grass (GC) treatments in track (T) and no-track (NT) positions are indicated. Other dates indicate the passage of tractors in vineyard (the number of passages and if passages were tyred or tracked) and dates of execution of field operations (ripping and/or mulching).



**Table 2.** *Cont.*

#### *2.2. Measurements*

The experiment was conducted in the period November 2016–October 2018. Measurements were periodically carried out in the two plots, both in the track position (T), which is the portion of inter-row affected by the passage of tractor wheels or tracks, as this is where the compressive effects tend to concentrate [47], and in the middle of the inter-row, identified as the no-track position (NT), that is not affected by direct contact with tractor wheels or tracks. Thus, measurements were carried out in four positions: CT-T and CT-NT in the tilled plot, and GC-T and GC-NT in the grassed plot. Periodic measurements (Table 2) were carried out to obtain values of compaction, namely soil penetration resistance (PR), bulk density (BD), and the associated initial soil water content (SWC). They were performed monthly in the growing season (depending on weather conditions) and two times before and after winter passages. Infiltration tests were performed according to the simplified falling head (SFH) technique [48] to detect the temporal variability of the field-saturated soil hydraulic conductivity (Kfs) at the surface of the vineyard inter-rows. A weather station and a monitoring system measured and recorded rainfall, runoff, and soil loss in the experimental plots.

#### 2.2.1. Rainfall, Runoff, and Soil Water Content

From November 2016 to October 2018, rainfall and runoff related to 93 events were recorded for the two plots. Rainfall was recorded at 10 min intervals by a rain-gauge station, with 0.2 mm resolution, placed near the plots. Based on the records, RIST (Rainfall Intensity Summarization Tool) [49] was used to obtain the rainfall amount (P), event duration (D), rainfall maximum intensity at 15, 30, and 60 min time intervals (MAX15, MAX 30, and MAX60), rainfall energy (E) (based on the equation proposed by Brown and Foster [50]), and the event erosivity index (EI30) [51] for each precipitation event. Rainfall events were defined as the time between the initiation and cessation of rainfall with a lack of rainfall for at least 12 h, in order to separate long-lasting events. Isolated events with less than 1 mm of rainfall were omitted from the analysis, because they were not significant for runoff initiation or for soil moisture changes. Runoff generated by rainfall was collected separately for each plot. Each vineyard portion was hydraulically bounded, and runoff was collected at the extremity by a channel, connected with a sedimentation trap, and then a tipping bucket device measured the hourly volumes of runoff (RO) and the runoff rates (RC) in CT and GC. Runoff samples were collected to obtain sediment yield (SY) for erosive events. Furthermore, if sedimentation occurred in the channels and sediment trap, then sediment yield was collected and weighted (see Biddoccu et al. [46], for details). Soil moisture was monitored by indirect method [52] by capacitance/frequency domain sensors (ECH2O-5TM sensors, Decagon Devices Inc., Pullman, WA, USA), gravimetrically calibrated, and placed at 0.1, 0.2, and 0.3 m depth in each plot in NT and T positions. Soil water content was obtained every hour from the average of 1 min measurements and stored by a Decagon EM50 Datalogger.

#### 2.2.2. Soil Compaction Measurements

Soil compaction was evaluated with two different methods: bulk density (BD) and penetration resistance (PR). The use of two separate methods was meant to offer a robust experimental setup, capable of internal corroboration and multiple detection capacity, where the effects that may elude one method are captured by the other [46,53].

For each of the four positions, 5 PR profiles and 9 BD were yielded, with a total number of 20 PR and 36 BD for each recurrent measurement. Measurements were repeated 10 times in Year 1 (200 PR and 360 soil cores), and 8 times in Year 2 (160 penetration resistance profiles and 288 soil cores). Dates of field sampling, along with soil water content measured in the same day, and dates of tractor passages in each plot are reported in Table 2. For reference values, the survey farther from tractor passages (20/2/2017) was chosen for the GC plot, whereas values recorded on 17/5/2018 were selected for the CT plot, that were obtained just after the tillage without tractor passages. The standard Proctor compaction test [54] was performed on soil samples taken in the two treatments for both years.

#### (1) Penetration resistance (PR)

Soil penetration resistance was measured using a dynamic penetrometer, built according to the design of Herrick and Jones [55]. The cone used for the tests had an ASAE-standard 30◦ cone angle (3.22 cm<sup>2</sup> base area). The penetrometer was placed vertically, with the cone tip inserted into the soil. The mass of the slide hammer was 2 kg, falling from a height of 0.3 or 0.4 m. The number of hits necessary to reach the penetration depths of 3.5 – 7.0 – 10.5 – 14.0 – 17.5 – 21.0 – 24.5 – 28.0 cm was recorded manually to evaluate changes in penetration resistance values down the soil profile. At each survey, 5 repetitions were performed in the T and NT positions, both in the GC and in the CT plot. The PR was then estimated as the work done by the soil to stop the movement of the penetrometer, divided by the cone travelled distance [55] according to the following equation:

$$R\_{\ $} = \frac{W\_{\$ }}{P\_d} \tag{1}$$

where *Rs* is soil resistance (N), *Ws* is work done by the soil (J), and *Pd* is cone travel distance through the soil (m).

The work done by the soil was calculated as the change in the kinetic energy of the penetrometer, according to Equation (2) [56]. As the penetrometer was driven into the soil by the hammer, the kinetic energy of the hammer was transferred to the penetrometer cone. Therefore, the work done by the soil was equal to the kinetic energy (KE) transferred to the cone from the penetrometer when the hammer contacted the strike plate, which was calculated as follows:

$$KE = \mathcal{W}\_s = \frac{1}{2}mv^2\tag{2}$$

where *v* is hammer velocity (m s<sup>−</sup>1) and *m* is hammer mass (2 kg).

In turn, velocity (*v*) was calculated as:

$$v = \sqrt{v\_0^2 + 2a(x)}\tag{3}$$

where *x* is falling height (0.3 m), *a* is gravity acceleration (9.81 m s<sup>−</sup>2), and *v*<sup>0</sup> is initial velocity (assumed as null).

The previous calculations assume that all of the hammer's kinetic energy was transferred to the cone.

Finally, average PR was estimated for each depth interval of soil travelled by a given number of hammer strikes as:

$$R\_s = \frac{a \cdot m \cdot x \cdot n}{A \cdot P\_d} \tag{4}$$

where *m* is hammer mass (2 kg), *n* is number of strikes, and *Pd* is penetration depth (m).

PR is directly correlated with BD and shows an inverse relationship with SWC, but those relationships are not linear over a wide range of values of BD and SWC. Several studies suggest to operate cone penetrometer measurements at water contents close to a standardized matric potential to obtain comparable results [57]. To allow comparison of measurements taken at different SWC conditions, Busscher [58] introduced the practice of normalizing PR readings to a common SWC value. According to the procedure illustrated by Vaz et al. [59], the measured data were used to parameterize the exponential function proposed by Jakobsen and Dexter [60]:

$$PR = \exp(a + b \cdot BD + c \cdot SWC) \tag{5}$$

that expresses PR as function of SWC and BD. The PR mean values for 10-cm depth intervals were associated to corresponding BD and SWC values measured during each survey. Each of the four datasets obtained in different treatments and positions during the study period was used to obtain the best fitting equations, minimizing root mean square error. Then PR data for the 10 cm depth intervals were normalized using a common SWCcorr value that was set at 0.300 m<sup>3</sup> m<sup>−</sup>3.

(2) BD (and SWC)

BD is a dynamic soil property that varies according to its structure, which can be altered by flora and microorganisms, by agricultural practices, by trampling, or by heavy vehicle traffic, but also by the impact of precipitation. To determinate BD and SWC, core samples (V = 100 cm3) were collected in the T and NT position both in the GC and in the CT plot, at the depth of 0–0.10, 0.10–0.20, and 0.20–0.30 m. Then, samples were weighed before and after oven-drying at 105 ◦C for 48 h. SWC was determined by gravimetric method from each sample. Three samples were collected at each position and depth; thus, BD and SWC were calculated as the average of values obtained from the three repetitions.
