Quantity and Quality of Surface and Subsurface Runoff from an Eroded Loess Slope Used for Agricultural Purposes

Article Quantity and Quality of Surface and Subsurface Runoff from an Eroded Loess Slope Used for Agricultural Purposes

Andrzej Mazur

Department of Environmental Engineering and Geodesy, University of Life Sciences in Lublin, Leszczy´nskiego7, 20-069 Lublin, Poland; [email protected]; Tel.: +48-081-532-0644

Received: 27 July 2018; Accepted: 20 August 2018; Published: 24 August 2018

Abstract: The purpose of the work was to determine the surface and subsurface water runoff and selected constituents of the matter contained and carried out from the eroded loess slope used as arable land. The research was carried out in 2008–2011 on the Lublin Upland. The quantity of water flowing out of the slope was measured and samples were collected in order to determine the concentration of the soil suspension of nitrogen and its forms as well as phosphorus and potassium. Soil tests were also carried out and the rainfall amount and intensity was monitored. The research results show that the amount of precipitation was significantly statistically correlated with the quantity of surface and subsurface water runoff and with the precipitation and surface runoff erosion indicator EI30 (correlations at the level of r = 0.75–0.78). In addition, the mass of eroded soil was strongly correlated with the erosion indicator of rain and surface runoff EI30 (r = 0.86). The annual soil losses were from 21.1 to 173.1 Mg ha−1. The concentration of chemical components dissolved in the surface and subsurface runoff water in most cases proved to be negatively statistically correlated with the amount of precipitation and indicator EI30. The correlation coefficients (r) were at levels from −0.32 to −0.52. The annual loss of nutrients caused by chemical erosion was: nitrogen 7.210–29.949 kg ha−1, phosphorus 0.846–5.279 kg ha−1 and potassium 7.065–21.660 kg ha−1. The highest intensity of water erosion was recorded in 2010, when root crops were grown in the field.

Keywords: water quality; non-point source pollution; soil erosion; surface and subsurface outﬂow; arable land; loess soil

1. Introduction The water erosion of soils, understood as a physical process consisting of the separation of the soil particles from the ground as a result of the impact of rain or flowing water and their transfer to sedimentation sites, has long been the subject of scientific research. The published results of studies on soil erosion clearly indicate that this is a destructive process, which transforms the relief and structure of soil profiles (sometimes leading to deeper layers or ravine erosion) [1–3]. It leads to the impoverishment of soils in humus compounds and nutrients for plants [4–6], the deterioration of the physicochemical properties of soils [7–10], and in the end, to lower productivity [11–13] and decreased crop yields [14– 16]. The nutrients that are washed out as a result of erosion processes enter the surface water, causing pollution and eutrophication [17–20]. Incorrectly used soil easily undergoes erosive degradation [21], and reconstructing its original state is difficult, sometimes even impossible, because soil-forming processes are very slow [22,23]. Soils developed from loess belong to the most fertile soils in the world [24], but they are characterized by potentially high susceptibility to water erosion [25]. Research on soil erosion carried out in the belt of loess uplands of Poland is concerned with many aspects, e.g., the assessment of erosion size, determination of the intensity and range of erosion, conducting

Water 2018, 10, 1132; doi:10.3390/w10091132 www.mdpi.com/journal/water Water 2018, 10, 1132 2 of 17 range of erosion, conducting agrotechnical operations, erosion protection, erosion control, spatial management, and erosion process modeling [26–30]. Studies within the slope environment that ragrotechnicalegard quantitative operations,–qualitative erosion surface protection, and subsurface erosion control, water spatial runoff management,along with constituents and erosion of processmatter aremodeling significantly [26–30 ].less Studies common within in the the scientific slope environment literature [ that31]. regardStudying quantitative–qualitative the above issues in the surface loess areasand subsurface of the Lublin water Upland, runoff along under with conditions constituents of a s oftrong matter threat are significantly of water erosion lesscommon and intensive in the agriculturalscientific literature economy, [31 ].will Studying contribute the to above better issues recognition in the loess of the areas functioning of the Lublin of fluvial Upland, transport, under allowingconditions for of athe strong introduction threat of water of rational erosion farming and intensive consistent agricultural with the economy, principles will of contribute sustainable to development.better recognition of the functioning of fluvial transport, allowing for the introduction of rational farmingThe consistent paper presents with the the principles empirical of results sustainable of research development. from 2008–2011, carried out in natural conditionsThe paper on the presents Lublin theUpland, empirical regarding results quantity of research and quality from 2008–2011, of surface carriedand subsurface out in natural water runoffconditions as well on as the selected Lublin components Upland, regarding of matter quantity in an area and of quality eroded of loess surface slope and used subsurface as arable waterland. runoff as well as selected components of matter in an area of eroded loess slope used as arable land. 2. Material and Methods 2. Material and Methods 2.1. Research Object 2.1. Research Object The research was carried out in the area of a small loess catchment on arable lands in Wielkopole The research was carried out in the area of a small loess catchment on arable lands in Wielkopole (Figure 1) (50°57′26″ N, 23°01′01″ E), located in the eastern part of the mesoregion Wyniosłość (Figure1) (50 ◦5702600 N, 23◦0100100 E), located in the eastern part of the mesoregion Wyniosło´sć Giełczewska (Lublin Upland) [32]. The catchment area is 188.5 ha, its length is 2550 m, and the Giełczewska (Lublin Upland) [32]. The catchment area is 188.5 ha, its length is 2550 m, and the maximum width reaches up to 850 m. In terms of the surface shape, it is a typical eroded catchment maximum width reaches up to 850 m. In terms of the surface shape, it is a typical eroded catchment of of the Lublin Upland, with soils made of loess, covering a thickness of a few to approximately a dozen the Lublin Upland, with soils made of loess, covering a thickness of a few to approximately a dozen meters of Cretaceous rocks that are well visible in the bottom of the soil profile in deep gorge gaps. meters of Cretaceous rocks that are well visible in the bottom of the soil profile in deep gorge gaps. The The highest point in the catchment is 280 m above sea level, and the lowest point is 205 m above sea highest point in the catchment is 280 m above sea level, and the lowest point is 205 m above sea level. level. Denivelations reach up to 35 m and the maximum inclinations on the slopes reach 35%. Over Denivelations reach up to 35 m and the maximum inclinations on the slopes reach 35%. Over 79% of 79% of the catchment area is used for agricultural purposes. The direction of the main valley runs the catchment area is used for agricultural purposes. The direction of the main valley runs from west from west to east [33]. to east [33].

FigFigureure 1. 1. RResearchesearch location location in in the the agricultural agricultural loess loess catchment catchment in Wielkopole Wielkopole..

2.2. Water Water Research Measurement ofof thethe surfacesurface and and subsurface subsurface runoff runoff were were carried carried out out in a in selected a selected production production field fieldthat isthat part is ofpart the of catchment the catchment and situated and situated on a slope on awith slope an with average an average inclination inclinati of abouton of 11% about and 11% NE ◦ andexhibition NE exhibition (azimuth (azimuth of 30 ). Theof 30°). selected The selected field is used field asis arableused as land, arable with land a longitudinal, with a longitudinal direction directionfor conducting for conducting agrotechnical agrotechnical procedures, procedures and cultivation, and cultivation typical typical for the for Lublin the Lublin Upland. Upland. The fieldThe fieldshape shape is similar is similar to a to square, a square with, with a side a side length length of of about about 90 90 m, m, and and its its lower lower partpart reachesreaches the edge of the valley gorge, which is located in the valley axis. In In 2008, spring barley was grown, in 2009 winter triticale, in 2010 sugar beets and in 2011 winter wheat. In In April April 2008, 2008, in in the lower part of the slope, a a catcher catcher for for the the surface surface and and subsurface subsurface runoff runoff to a to depth a depth of 0.75 of 0.75m was m installed. was installed. Made Made of sheet of metalsheet and metal structurally and structurally similar similarto a Gerlach to a Gerlachcatcher, catcher,it was hous it wased in housed the soil in outcrop. the soil In outcrop. the front In wall, the gapsfront with wall, a gaps width with of a 1 width m were of 1 left, m were in which left, in barriers which barrierscollecting collecting the outgoing the outgoing water watertogether together with Water 2018, 10, 1132 3 of 17 with impurities from the depth of 0 m (surface runoff) and 0.00–0.25 m, 0.25–0.50 m; 0.50–0.75 m (subsurfaceimpurities runoff), from the were depth mounted. of 0 The m (surface water was runoff) discharged and 0.00 through–0.25 PVC m, (polyvinyl0.25–0.50 m; chloride) 0.50–0.75 pipes m to(subsurface calibrated tanks,runoff) which, were constituted mounted. The the receivers water was of thedischarged outflowing through water PVC (Figure (polyvinyl2). In the chloride case of ) thepipes outflow to calibrated presence, tanks, its volume which was constitut measureded the and receivers taken in of 1 the liter outflowing water bathymeters water (Figure for laboratory 2). In the analysis,case of the after outflow the homogenization presence, its volume of the whole was measured volume. The and content taken in of 1 suspensions liter water inbathymet the collecteders for waterlaboratory samples analysis, was determined after the homogenization according to Brański[ of the whole34] by volume. means The of the content gravimetric of suspensions method, in and the thecollected nitrogen water (total, samples ammonium, was determined nitrate and nitrite),according phosphorus to Brański and [34] potassium by means were of the determined gravimetric by applyingmethod, theand photometric the nitrogen method (total, [ammonium,35]: nitrate and nitrite), phosphorus and potassium were determined by applying the photometric method [35]: • total nitrogen: WTW photometer model MPM 2010 (after oxidation of the test sample in  total nitrogen: WTW photometer model MPM 2010 (after oxidation of the test sample in thermo- thermo-reactor at the temperature 100 ◦C); reactor at the temperature 100 °C ); • ammonium and nitrite: WTW photometer model MPM 2010;  ammonium and nitrite: WTW photometer model MPM 2010; • nitrate, phosphorus, and potassium: Slandi photometer model LF 300.  nitrate, phosphorus, and potassium: Slandi photometer model LF 300. BasedBased on on the the concentration concentration of of components components and and the the size size of of runoff,runoff, thetheloads loadsof ofcomponents components transportedtransported in in the the water water were were determined. determined.

Figure 2. Schema of the catcher surface and subsurface runoff. Figure 2. Schema of the catcher surface and subsurface runoff.

2.3.2.3. Rainfall Rainfall Research Research InvestigationsInvestigations intointo thethe rainfall,rainfall, surface and and subsurface subsurface runoff runoff were were conducted conducted in in total total during during 27 27periods periods (5 (5each each in in 2008 2008 and and 2009, 2009, 7 7 each each in in 2010 and 1010 eacheach inin 2011)2011) (Table (Table1). 1). Atmospheric Atmospheric precipitationprecipitation was was recorded recorded using using a a daily daily recording recording pluviograph pluviograph and and a a Hellmann Hellmann rain rain gauge. gauge.

Table 1. Date of occurrence and amount of erosive precipitation.

2008 2009 2010 2011 Month Day Rainfall (mm) Day Rainfall(mm) Day Rainfall (mm) Day Rainfall (mm)

Apr ------11–12 21.2 2–4 22.2 May 19 18.2 14–18 31.2 2 33.2 18–20 26.3 6 19.1 - 1–3 -37.2 Jun - - 23 19.8 29–30 32.1 19–20 23.2 25 50.8 3–4 63.5 5 57.2 7 31.5 Jul 25 15.3 24 59.8 14–15 38.8 20–22 28.4 20 32.1 27–28 46.3 6–7 44.2 13–14 42.1 Aug - - - - 9 63.6 18 22.2 30 41.5 Sep 16–20 46.1 ------Water 2018, 10, 1132 4 of 17

Table 1. Date of occurrence and amount of erosive precipitation.

2008 2009 2010 2011 Month Day Rainfall (mm) Day Rainfall (mm) Day Rainfall (mm) Day Rainfall (mm) Apr ------11–12 21.2 2–4 22.2 May 19 18.2 14–18 31.2 2 33.2 18–20 26.3 6 19.1 1–3 -37.2 - Jun - - 23 19.8 32.1 19–20 23.2 29–30 25 50.8 3–4 63.5 5 57.2 7 31.5 Jul 25 15.3 24 59.8 14–15 38.8 20–22 28.4 20 32.1 27–28 46.3 6–7 44.2 13–14 42.1 Aug - - - - 9 63.6 18 22.2 30 41.5 Sep 16–20 46.1 ------

On the basis of pluviographs, the unit kinetic energy of precipitation was calculated according to the Equation (1) developed by Brown and Forester [36]:

n Ekin = ∑ 0.29[1 − 0.72 exp(−0.05Ii)]∆Pi (1) i=1

−1 where Ekin is the kinetic energy per area unit (MJ ha ); Ii is the intensity of precipitation in time with −1 a constant partial intensity i (mm h ); and ∆Pi is the sum of precipitation in time with a constant partial intensity i (mm). According to deﬁnition included in the USLE (Universal Soil Loss Equation) model, a single rainfall was assumed as a precipitation, if it was separated from the next one by more than 6 h. For all precipitations with partial intensity with the threshold values 1, 2, 3, and 4 mm h−1, the sum, kinetic energy and erosion indicator of rain and surface runoff EI30 was calculated as a product of the kinetic energy of precipitation and its maximum intensity within 30 min [37].

2.4. Soil Research Soil investigations were carried out in April 2008 (samples were collected during the installation of the runoff catcher). A description of the soil profile was made in the field on the basis of stratified diagnostic horizons according to the systematics developed by the Polish Society of Soil Science [38]. Soil samples were collected from the distinguished diagnostic horizons and subjected to determinations according to the recommended methods [39,40]:

• Granulometric composition, using the Bouyoucos areometric method modiﬁed by Casagrande and Prószy´nski; • Density of the solid phase of the soil, by means of the pycnometric method; • Soil bulk density, using gravimetry (after collecting the soil with an intact structure into metal cylinders); • Total porosity, using Formula (2):

ρ − ρ P = o 100 (%) (2) o ρ

where Po is the total porosity; ρ is the density of the solid phase; and ρo is the soil bulk density. • Water permeability coefﬁcient, using the Eijkelkamp device (after collecting the soil with an intact structure into metal cylinders). Water 2018, 10, 1132 5 of 17

On the basis of the obtained research results, the dependence of quality indicators of runoff water and losses of matter components on precipitation and runoff parameters was determined, based on the determination and r-Pearson correlation index, at a signiﬁcance level of α = 0.05.

3. Results and Discussion

3.1. Meteorological Conditions Climatic conditions, in particular the size and intensity of atmospheric precipitation, have a very signiﬁcant impact on the intensity of water erosion. The supply of atmospheric precipitation in the catchment in Wielkopole is shown in Table2. The average long-term 1987–2011 annual rainfall was 636.1 mm, of which more than half (around 64%) was summer rainfall. The lowest annual rainfall occurred in the winter months (January and February, with 31.5 and 30.2 mm), while the highest occurred in July (97.1 mm). During the research period, rainfall was higher than the average long-term rainfall by about 11% in 2008, 36% in 2010 and 38% in 2011. Only in the hydrological year 2008–2009, was precipitation lower by about 7.7% in relation to the average long-term rainfall. High precipitation, almost two or three times higher than the average monthly rainfall for many years, was recorded in September 2008, June 2009, August 2010 and July 2011, of which the latter had the highest precipitation recorded in the history of observation at this meteorological station, accounting for as much as 349% of the average monthly rainfall in July. The amount of rainfall was not evenly distributed over the year. The rainfall from the summer period during the study period constituted 64% in 2008, 72% in 2009 and 76% in 2010 and 2011. The obtained results for the precipitation distribution were similar to those recorded by Mazur et al. [33]. They found that the climate of the Lublin Upland is distinguished by an increasing continental characteristic in an easterly direction. This is evidenced by the high amplitudes of air temperatures, small sums of annual rainfall (500–600 mm) and the prevalence of summer precipitation, which often consists of short-term, sudden, and local downpours [33].

Table 2. Monthly and annual rainfall totals (mm) in the catchment in Wielkopole in the hydrological years 2008–2011 and average values from 1987–2011.

Month Sum (mm) Year Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct 2008 45.7 19.7 42.3 21.3 78.9 49.3 70.2 39.0 102.3 77.8 108.9 52.1 707.5 2009 26.6 24.0 25.2 20.0 56.4 12.0 61.5 143.4 72.3 28.3 35.3 82.0 587.0 2010 41.1 47.6 35.5 37.5 14.8 29.4 100.8 71.8 169.5 200.5 102.8 16.4 867.7 2011 42.0 36.7 23.8 23.4 14.7 70.4 83.0 86.4 339.0 109.0 16.2 30.7 875.3 Average long-term 39.8 34.0 31.5 30.2 39.8 50.9 61.1 74.4 97.1 73.1 65.2 39.0 636.1 1987–2011

3.2. Soil Properties On the basis of the stratification of the distinguished diagnostic horizons made in the soil outcrop, in this study area the soils developed from loess and are of the lessive type (Haplic Luvisols). These are medium-eroded soils with an Ap-B2t-BC-Cca structure profile (Ap—arable-humic horizon, B2t—illuvian horizon, BC—transitional horizon, Cca—bedrock horizon), in which the arable-humus level was developed from the B2t horizon. In their composition, no skeletal fractions were found, and the sand fraction constituted a small proportion (2.8–4.1%) (Table3). The dominant fraction in the granulometric composition was dust, constituting about 60% of the volume of the soil samples, of which fine dust constituted from 46.2% to 47.9%. The alluvial parts (<0.02 mm) also constituted a high percentage (about 34%), and the largest of these was a thick dusty loam. The granulometric composition of the studied soils was similar to those found elsewhere in the Lublin Upland [29,41]. Water 2018, 10, 1132 6 of 17

Table 3. Soil granulometric composition.

Percent of Fraction of Diameter in mm Sum of Floatable Horizon Depth (cm) 1–0.1 0.1–0.05 0.05–0.02 0.02–0.006 0.006–0.002 <0.002 Parts <0.02 Ap 0–24 4.1 15.2 46.5 17.2 10.8 6.2 34.2 Bt2 24–52 3.9 15.5 47.3 16.5 10 6.8 33.3 BC 52–70 2.7 17.1 46.2 16.3 9.6 8.1 34.0 Cca >70 2.8 15.8 47.9 17.4 8.2 7.9 33.5

An important feature of loess formations are their physical properties, which determine the water permeability, storage of water in the soil, as well as the occurrence of water runoff. The average specific soil density was 2.6 Mg m−3 and ranged from 2.59 to 2.67, being the lowest in the upper arable-humic Ap horizon and the highest at a depth of 25–35 cm (Table4). The bulk density was similar, and increased with depth. The highest overall porosity was found in the Ap horizon (45.9%), and the lowest (39%) in the subsurface layer at a depth of 25–35 cm. The examined soils, in terms of physical properties, turned out to be similar to those ones developed from loess in the Lublin Upland [41]. The results presented in Table4 clearly indicate a higher degree of compaction of the subsurface layer and the formation of a so-called plough pan. This unfavorable thickening of the solid phase below the range of the cultivation tools (plow, cultivator, etc.) clearly affects the water infiltration conditions, especially during intense precipitation. In the arable layer, the water permeability coefficient was 6.152 × 10−6 m s−1, while in the direct subsurface layer, it decreased three times to the value 2.132 × 10−6 m s−1. In deeper layers, it ranged from 3.256 to 3.869 × 10−6 m s−1.

Table 4. Selected physical properties of the studied soils.

Speciﬁc Density Bulk Density Total Porosity Water Permeability Horizon Depth (cm) (Mg m−3) (Mg m−3) (%) (×10−6 m s−1) Ap 0–25 2.59 1.40 45.9 6.152 Bt2 25–35 2.67 1.63 39.0 2.132 Bt2 35–52 2.65 1.60 39.6 3.256 BC 52–70 2.64 1.59 39.8 3.746 Cca >70 2.64 1.63 38.3 3.869

3.3. Water Outflow and Selected Matter Components Investigations of the quantity and quality of the surface runoff and water outflow were carried out for a wide range of rainfall totals, from 15.3 to 63.6 mm (Table5). The obtained test results were very diversified, as evidenced by the standard deviation values. Of all the recorded erosive precipitations, they occurred most frequently in July (33.3%) and June (22.2%). In May and August, their incidence was 18.5%, and in April and September 3.7% (Table1). Water 2018, 10, 1132 7 of 17

Table 5. Range, average and standard deviation values characterizing the precipitation as well as the quantity and quality of water outﬂow from the slope.

Year 2008 2009 2010 2011 Parameter Range Average/Standard Deviation 22.2–46.1 15.3–50.8 31.2–63.6 21.2–63.5 Rainfall (mm) 30.9/8.1 24.6/13.2 42.9/13.5 38.9/13.1 132.5–388.6 176.3–623.5 145.1–699.3 123.5–586.7 Kinetic energy per area unit (J ha−1) 235.6/111.4 310.5/169.3 376.1/199.7 315.1/164.4 11.5–145.6 53.4–324.5 23.5–450.2 8.9–396.1 Index EI30 (MJ mm ha−1 h−1) 49.6/50.7 115.3/104.9 197.1/162.8 134.7/113.1 Surface Runoff 2.8–8.9 3.4–12.3 3.2–18.2 1.2–11.2 Outﬂow (mm) 4.4/2.3 5.6/3.4 10.9/4.9 5.9/2.6 56.365–186.235 12.421–156.232 98.445–301.278 9.345–175.324 Soil suspension (g dm−3) 120.323/53.712 43.376/56.474 190.817/74.899 82.855/55.273 0.923–5.854 0.652–5.023 1.156–6.321 0.956–5.354 N-Ntot (mg dm−3) 3.088/2.043 2.655/1.641 3.721/2.080 2.147/1.593 0.501–2.524 0.354–2.498 0.654–4.224 0.551–3.195 N-NH (mg dm−3) 4 1.450/0.882 1.359/0.785 3.721/1.311 1.161/0.913 0.222–1.623 0.156–1.212 0.247–1.514 0.211–1.365 N-NO (mg dm−3) 3 0.856/0.620 0.658/0.409 0.858/0.405 0.543/0.407 0.102–1.315 0.118–0.956 0.113–0.921 0.098–0.786 N-NO (mg dm−3) 2 0.533/0.465 0.421/0.330 0.478/0.336 0.260/0.227 0.039–1.141 0.041–0.852 0.131–2.105 0.112–1.125 P (mg dm−3) 0.454/0.495 0.452/0.350 0.837/0.814 0.393/0.375 1.126–5.023 1.156–5.234 0.885–7.852 0.698–5.734 K (mg dm−3) 2.965/1.431 3.201/1.419 3.185/2.602 2.230/1.834 Subsurface Runoff 0.5–0.9 0.5–2.3 0.3–3.6 0.2–3.6 Outﬂow (mm) 0.7/0.2 1.0/0.6 1.4/1.3 1.2/0.9 1.213–3.245 1.456–23.455 1.245–51.235 1.021–24.254 Soil suspension (g dm−3) 2.216/0.905 6.474/8.524 20.208/19.292 10.560/8.809 1.345–8.542 1.561–8.245 1.982–8.256 1.132–8.563 N-Ntot (mg dm−3) 4.619/3.153 3.651/2.549 4.882/2.639 3.050/2.513 0.723–4.456 0.554–4.562 0.856–4.952 0.525–4.954 N-NH (mg dm−3) 4 2.380/1.617 1.948/1.433 2.651/1.66 1.584/1.466 0.308–2.394 0.214–2.280 0.512–2.312 0.242–2.212 N-NO (mg dm−3) 3 1.227/0.941 0.999/0.733 1.311/0.741 0.795/0.720 0.122–1.456 0.098–1.145 0.298–0.962 0.081–0.985 N-NO (mg dm−3) 2 0.795/0.561 0.410/0.402 0.582/0.284 0.795/0.307 0.045–1.325 0.071–1.008 0.312–2.563 0.123–1.262 P (mg dm−3) 0.513/0.544 0.523/0.397 1.081/0.884 0.466/0.440 1.156–6.256 1.521–5.214 1.324–8.234 1.023–7.234 K (mg dm−3) 3.461/1.935 3.407/1.283 3.729/2.602 3.126/2.510

The value of the EI30 index in the summer half of particular hydrological years varied in a wide range from 8.9 to 450.2 MJ mm ha−1 h−1. Higher values occurred in wet years (2010 and 2011), when the annual rainfall sums exceeded the average sum of many years. The highest value of the EI30 index was recorded on 9.08, 2010 (450.2 MJ mm ha−1 h−1), and was caused by precipitation from one high intensity storm (63.6 mm), reaching a maximum of 229.3 mm h−1. Dependence between the erosion rate of precipitation and surface runoff EI30 and the sum of the rainfall is shown in Figure 3 (the trend line was best described by the quadratic equation). The erosive potential of the high precipitation expressed by the EI30 index does not necessarily depend on the sum of the rainfall (sometimes rainfall with high sums was characterized by a low index and vice versa). However, it should be emphasized that the EI30 indicator is significantly correlated with the sum of precipitation (r = 0.78) and the determinationWater 2018, 10, 1132 index was R2 = 0.68. A high dependence (determination index R2 = 0.54) between8 ofthe 17 EI30 index and the amount of precipitation was also confirmed by results obtained by Rejman [29]. In Szewrański’s research [42] one can note a high dependence between the amount of precipitation and EI30 index and the amount of precipitation was also confirmed by results obtained by Rejman [29]. theIn Szewrański’sresearch kinetic energy that determines [42] one can the note intensity a high dependenceof soil erosion. between The correlation the amount coefficient of precipitation between and thethe rain kinetic erosion energy index that (EI determines30) and the the rain intensity layer (P) of soil calculated erosion. by The and correlation Święchowicz coefficient [43] amounted between the to 0.51. rain erosion index (EI30) and the rain layer (P) calculated by and Swi˛echowicz[´ 43] amounted to 0.51.

500

400 y = 0.1073x2 – 0.8446x )

1 R² = 0.6814 –

h 300

1 –

200 index

30 100 EI

(MJ mm ha mm (MJ 0 0 10 20 30 40 50 60 70 Rainfall (mm)

Figure 3. Rainfall erosivity index EI30 in dependence on rainfall amount. Figure 3. Rainfall erosivity index EI30 in dependence on rainfall amount.

The surface water runoff level on the slope slope was was from from 1.2 1.2 to to 18.2 18.2 mm mm (Table (Table 55),), whichwhich constitutedconstituted fromfrom 5.7% to 28.8% of the precipitation causing the erosive event. event. In In total, higher outflows outflows were recorded in the wet years 2010 and 2011 (76.4 and 58.9 mm), which accounted for 8.8% and 6.7% of annual precipitation, respectively. respectively. In 2008 and 2009, the outflow outflow was 22.1 and 22.0 mm, or 3.1% and 4.8% of the annual rainfall rainfall,, respectively respectively.. The obtained research research results prove that a high amount of precipitation does does not not always always result result in high in high surface surface runoff runoff (Figure (Figure4a). The 4a). trend The line trend was best line described was best describedby the quadratic by the equation. quadratic However, equation. theHowever, obtained the correlation obtained coefficient correlation r= coefficient 0.75 (determination r = 0.75 2 (indexdetermination R = 0.58) index shows R2that = 0.58 the) shows height that of the the surface height runoffof the issurface highly runoff correlated is highly with correlated the amount with of theprecipitation. amount of precipitation. Research conducted Research by conducted Kim et al. by [18 Kim], Zhang et al. et[18], al. Zhang [20] and et al.Zmuda˙ [20] and [31 ]Żmuda prove that[31] provethe outflow that the rate outflow is also rate influenced is also influenced by a number by a of number other factors, of other for factors, example for precipitationexample precipitation intensity, intensity,vegetation vegetation cover and cover soil moisture. and soil moisture. However, However, it is mainly it is the mainly intensity the intensity of precipitation of precipitation that initiates that initiatesthe surface the runoff.surface If runoff. it is greater If it is than greater the soilthan infiltration, the soil infiltration, a layer of a water layer isof formed water is on formed the surface on the of surfacethe terrain, of the which terrain, begins which to run begins down to the run slope down due the to slope gravity due [43 to,44 gravity]. The subsurface [43,44]. The runoff subsurface during runoffthe research during period the research occurred period only occurred from the only confined from layer the confined up to 0.25 layer m. Itup ranged to 0.25 from m. It0.2 ranged to 3.6 from mm 0.2(Table to 53.6), whichmm (Table accounted 5), which for 0.9% accounted and 6.3% for of 0.9% the precipitation and 6.3% of causingthe precipitation the erosive causing event, respectively. the erosive event,As in therespectively. case of surface As in runoff, the case it wasof surface higher runoff in 2010, itand was 2011 higher (10.1 in and2010 12.4 and mm), 2011 accounting(10.1 and 12.4 for mm),1.2% andaccount 1.4%ing of thefor annual1.2% and precipitation, 1.4% of the respectively. annual precipitation, In 2008 and respectively. 2009, the subsurface In 2008 and runoff 2009, was the at subsurfacethe level of runoff 3.6 and was 4.3 at mm the (0.5% level and of 3.6 0.7% and of 4.3 annual mm (0.5% rainfall), and respectively. 0.7% of annual The rainfall) relationship, respectively between. Thethe heightrelationship of the between subsurface the runoffheight of and the the subsurface amount ofrunoff precipitation and the amoun causingt of this precipitation outflow is causing shown tinhis Figure outflow4b (theis shown trend in line Figure was 4 bestb (the described trend line by was the best quadratic described equation). by the quadratic The correlation equation) here. The is stronger r = 0.77 (determination index R2 = 0.63) than in the case of the surface runoff, but the amount of subsurface outflow cannot be inferred from the amount of rainfall. correlation here is stronger r = 0.77 (determination index R2 = 0.63) than in the case of the surface Water 2018, 10, 1132 9 of 17 runoff, but the amount of subsurface outflow cannot be inferred from the amount of rainfall.

20 y = 0.0011x2 + 0.1457x 4 y = 0.0006x2 + 0.0058x R² = 0.5811 15 3 R² = 0.627

10 2

(mm) (mm) 5

water (mm) (mm) water 1 0 Subsurface runoff runoff Subsurface of 0

Surface runoff runoff water of Surface 0 10 20 30 40 50 60 70 0 10 20 30 40 50 60 70 Rainfall (mm) Rainfall (mm)

(a) (b)

FFigureigure 4 4.. SurfaceSurface runoff runoff of ofwater water (a) and (a) andsubsurface subsurface runoff runoff of water of water(b) in dependence (b) in dependence on the rainfall on the amountrainfall. amount.

Water draining from the surface or deeply from the slope carries dissolved or suspended Water draining from the surface or deeply from the slope carries dissolved or suspended constituents of matter [45]. Under the research conditions, the concentration of soil suspension constituents of matter [45]. Under the research conditions, the concentration of soil suspension contained in the surface runoff water varied within a wide range from 8.354 to 301.278 g dm−3, while contained in the surface runoff water varied within a wide range from 8.354 to 301.278 g dm−3, the range in the subsurface runoff water was 1.021–51.235 g dm−3 (Table 5). The highest mean while the range in the subsurface runoff water was 1.021–51.235 g dm−3 (Table5). The highest mean concentration of soil suspension in the surface runoff water (190.817 g dm−3) and subsurface runoff concentration of soil suspension in the surface runoff water (190.817 g dm−3) and subsurface runoff water (20.208 g dm−3) was recorded in 2010, whereas the lowest recorded was 43.376 g dm−3 in 2009 water (20.208 g dm−3) was recorded in 2010, whereas the lowest recorded was 43.376 g dm−3 in 2009 (surface runoff) and 2.216 g dm−3 in 2008 (subsurface runoff). Such large differences could have been (surface runoff) and 2.216 g dm−3 in 2008 (subsurface runoff). Such large differences could have caused by crop rotation, as in 2010 sugar beets were grown and cereals were grown in other years. been caused by crop rotation, as in 2010 sugar beets were grown and cereals were grown in other Soil washing from the slope during individual erosive events varied within a wide range from 0.112 years. Soil washing from the slope during individual erosive events varied within a wide range from to 54.833 Mg ha−1 for the surface runoff and from 0.002 to 1.844 Mg ha−1 for the subsurface runoff. 0.112 to 54.833 Mg ha−1 for the surface runoff and from 0.002 to 1.844 Mg ha−1 for the subsurface Slightly higher values were found by Żmuda [31] while conducting research in the area of Wzgórza runoff. Slightly higher values were found by Zmuda˙ [31] while conducting research in the area of Trzebnickie, where in a sugar beet field, the maximum surface soil runoff during a single event was Wzgórza Trzebnickie, where in a sugar beet ﬁeld, the maximum surface soil runoff during a single determined to be 60.132 Mg ha−1. However, in the research carried out by Rejman [29] in the Lublin event was determined to be 60.132 Mg ha−1. However, in the research carried out by Rejman [29] Upland, this figure reached 20.640 Mg ha−1 (cultivation of root crops, such as sugar beet and potato). in the Lublin Upland, this ﬁgure reached 20.640 Mg ha−1 (cultivation of root crops, such as sugar Figure 5 presents the relationship between the soil surface runoff and the amount of precipitation beet and potato). Figure5 presents the relationship between the soil surface runoff and the amount causing the erosive event (Figure 5a) and the EI30 indicator (Figure 5b). They show that the soil of precipitation causing the erosive event (Figure5a) and the EI 30 indicator (Figure5b). They show reaction, both towards the level of precipitation and their potential erosion (expressed by the EI30 that the soil reaction, both towards the level of precipitation and their potential erosion (expressed index), is very diverse and it is not possible to draw conclusions regarding the size of the soil wash by the EI index), is very diverse and it is not possible to draw conclusions regarding the size of the on the basis30 of these indicators. However, the mass of the eroded soil proved to be strongly correlated soil wash on the basis of these indicators. However, the mass of the eroded soil proved to be strongly with the EI30 index r = 0.86 (determination index R2 = 0.73), while it was less correlated with the sum correlated with the EI index r = 0.86 (determination index R2 = 0.73), while it was less correlated of precipitation r = 0.6530 (determination index R2 = 0.35). The relationship between the rainfall and with the sum of precipitation r = 0.65 (determination index R2 = 0.35). The relationship between the mass eroded soil was the subject of research of many authors. Experiments in simulated conditions rainfall and mass eroded soil was the subject of research of many authors. Experiments in simulated [46] showed that an increasing rainfall intensity had a larger effect on the sediment yield than conditions [46] showed that an increasing rainfall intensity had a larger effect on the sediment yield increasing slope. Other laboratory research [47] suggested that the collected sediment yield and than increasing slope. Other laboratory research [47] suggested that the collected sediment yield eroded soil volume increased with rainfall duration and slope. In their research, Shen et al. [48] and eroded soil volume increased with rainfall duration and slope. In their research, Shen et al. [48] generated an equation describing the relationship between the rill erosion rate and rainfall intensity generated an equation describing the relationship between the rill erosion rate and rainfall intensity and slope gradient. The authors indicated that the impact of rainfall intensity on hillslope rill erosion wereand slope greater gradient. than those The authorsof the slope indicated gradient. that For the impactthe experimental of rainfall treatments, intensity on the hillslope mean rillheadward erosion wereerosion greater rates thanincreased those with of the an slope increase gradient. in either For rainfall the experimental intensity or treatments, slope gradient the.mean headward erosion rates increased with an increase in either rainfall intensity or slope gradient. Water 2018, 10, 1132 10 of 17

6060

)

) –

60 1 –

60 1 – – 5050 y y= 0=. 084x0.084x y y= 0=. 338x0.338x 5050 R²R² = 0=. 07307.7307 R²R² = 0=. 03483.3483 4040 4040 3030 3030 2020

Soil loss (Mg ha Soil (Mg loss 20 Soil loss (Mg ha Soil (Mg loss

20 ha Soil (Mg loss Soil loss (Mg ha Soil (Mg loss 10 1010 10 0 0 0 0 0 200 400 600 0 0 1010 2020 3030 4040 5050 6060 7070 0 200 400 600 EI index (MJ mm ha–1–1–h1–1) Rainfall (mm) EI3030index (MJ mm ha h ) Rainfall (mm)

(a()a ) (b()b ) Figure 5. Soil loss through surface runoff per unit area depending on the rainfall amount (a) and index FigFigureure 5. 5.SoilSoil loss loss through through surface surface runoff runoff per per unit unit area area depend dependinging on on the the rainfall rainfall amount amount (a) ( aand) and index index EIEI30 30(b ()b. ). EI30 (b).

TheThe s oilsoil losses losses through through the the subsurface subsurface runoff runoff were were more more strongly strongly correlated correlated (r ( r= =0.70 0.70) with) with the the The soil losses through the subsurface runoff were more strongly correlated (r = 0.70) with the amountamount of of precipitation precipitation cau causingsing the the erosive erosive event event (Figure (Figure 6 a),6a), than than in in the the case case of of soil soil loss loss during during amount of precipitation causing the erosive event (Figure6a), than in the case of soil loss during surfacesurface runoff runoff (Figure (Figure 5 a).5a). However, However, also also in in this this case, case, there there was was erosive erosive precipitation precipitation with with a alarge large surface runoff (Figure5a). However, also in this case, there was erosive precipitation with a large volumevolume of of water water, during, during which which the the soil soil losses losses were were relatively relatively small. small. An An even even stronger stronger correlation correlation (r ( r volume of water, during which the soil losses were relatively small. An even stronger correlation = =89 89) was) was obtained obtained between between the the soil soil losses losses in in the the subsurface subsurface runoff runoff and and the the erosivity erosivity indicator indicator of of the the (r = 89) was obtained between the soil losses in the subsurface runoff and the erosivity indicator of the precipitationprecipitation and and surface surface runoff runoff EI EI30 30(Figure (Figure 6 b).6b). In In both both cases, cases, the the trend trend lines lines were were best best described described by by precipitation and surface runoff EI (Figure6b). In both cases, the trend lines were best described by quadraticquadratic equations equations. . 30 quadratic equations.

2 2 2 y y= 0.0000= 0.00001x1x2 –2 0–.00008x.0008x

)

) 1

) 2 1

) 2 –

1 y = 0.0005x – 0.0148x –

1 y = 0.0005x – 0.0148x R² = 0.9476 – R² = 0.9476 – 1.5 1.51.5 R²R² = 0.6351= 0.6351 1.5 1 1 1 1

0.5 0.50.5

0.5 ha Soil (Mg loss

Soil loss (Mg ha Soil (Mg loss

Soil loss (Mg ha Soil (Mg loss Soil loss (Mg ha Soil (Mg loss 0 0 0 0 0 100 200 300 400 500 0 0 1010 2020 3030 4040 5050 6060 7070 0 100 200 300 400 500 -0.5 -0.5-0.5 -0.5 EI index (MJ mm ha–1–1–h1–1) RainfallRainfall (mm) (mm) EI3030index (MJ mm ha h )

(a()a ) (b()b )

FigFigureure. 6. .6 S. oilSoil loss loss in in the the sub subsurfacesurface runoff runoff per per unit unit area area depend dependinging on on rainfall rainfall amount amount (a ()a and) and index index Figure 6. Soil loss in the subsurface runoff per unit area depending on rainfall amount (a) and index EIEI30 30(b ()b. ). EI30 (b). TheThe s urfacesurface washing washing of of soil soil from from the the slope slope during during the the four four years years of of research research was was 304 304.930.930 Mg Mg −1 haha−1.−1 The. The largest surfacelargest amount amount washing of of ofsoil soil soil (55.6% (55.6% from of the of the slopethe weight weight during of of the the the eroded four eroded years soil soil of over over research four four years) was years) 304.930 flowed flowed Mg away away ha . ininThe 2010 2010 largest (169 (169.458. amount458 Mg Mg ha ha of−1)−1 soil, )when, when (55.6% sugar sugar of beets the beets weight were were grown ofgrown the, erodedand, and almost almost soil overeight eight fourtimes times years) less less soil flowedsoil (21 (21.623. away623 Mg Mg in −1 haha2010−1)−1 ()Figure ( (169.458Figure 7 a)7a)Mg was was ha lost lost ),when when winter sugarwinter triticale beets triticale were was was grown,grown grown in and in 2009 2009 almost. During. During eight the the times subsurface subsurface less soil runoff (21.623runoff, the, Mgthe −1 massmassha of )of (Figurethe the eroded eroded7a) was soil soil lostduring during when the the winter four four-year triticale-year study study was period period grown was was in 6 2009. .6314.314 Mg During Mg ha ha−1.−1the The. The subsurface largest largest soil soil runoff, loss loss −1 (3(3the.674.674 massMg Mg ha ofha−1, the−1 which, which eroded accounts accounts soil during for for 58.2% 58.2% the of four-year of the the eroded eroded study soil soil periodmass mass for for was four four6.314 years) years) Mg was hawas recorded recorded. The largest in in 2010 2010 soil, , −1 whilewhileloss (the3.674 the smallest smallest Mg ha soil soil, which loss loss (0 accounts(0.085.085 Mg Mg for ha ha 58.2%−1)−1 )( Figure(Figure of the 7 b) eroded7b) occurred occurred soil massin in 2008 2008 for, fourwhen, when years) spring spring was barley barley recorded was was in −1 growngrown2010,. whileThe. The results theresults smallest obtained obtained soil from loss from (0.085field field tests Mg tests haregarding regarding) (Figure soil soil7b) loss loss occurred are are difficult difficult in 2008, to to whenrelate relate springto to other other barley results results was. . ThThgrown.isis is is due due The to to differences results differences obtained in in the the frominclination inclination field tests of of slopes slopes regarding and and soil soilsoil conditions, lossconditions, are difficult but but mainly mainly to relate due due toto to otherthe the erosive erosive results. naturenatureThis isof of due rainfall. rainfall. to differences Research Research inconducted conducted the inclination by by Gil Gil of [49,50 [ slopes49,50] clearly] andclearly soil shows shows conditions, that that even even but the mainlythe average average due ten toten- theyear-year erosive size size ofof soil soil loss loss can can differ differ by by up up to to 140% 140% for for cereal cereal crops crops and and 50% 50% for for potato potato cultivation. cultivation. Water 2018, 10, 1132 11 of 17 nature of rainfall. Research conducted by Gil [49,50] clearly shows that even the average ten-year size of soil loss can differ by up to 140% for cereal crops and 50% for potato cultivation.

180 4.0 )

160 )

1 – 140 – 3.0 120 100 2.0 80 60 40 1.0

20 ha Soil (Mg loss Soil loss (Mg ha (Mgloss Soil 0 0.0 2008 2009 2010 2011 2008 2009 2010 2011 Year Year

(a) (b)

Figure 7 7.. SoilSoil losses losses during during surface ( a)) and and subsu subsurfacerface ( b) runoff in 2008 2008–2011.–2011.

The chemistry of water flowing off the slope was very diverse in individual years and during The chemistry of water flowing off the slope was very diverse in individual years and during outflow periods (Table 5). The concentrations of total nitrogen in the surface runoff water varied from outflow periods (Table5). The concentrations of total nitrogen in the surface runoff water varied 0.652 to 6.321 mg dm−3 N-Ntot. The concentration of other nitrogen forms was at the level of: from 0.652 to 6.321 mg dm−3 N-Ntot. The concentration of other nitrogen forms was at the level of: ammonium 0.354–4.224 mg dm−3 N-NH4, nitrate 0.156–1.623 mg dm−3 N-NO3, nitrite 0.098–1.315 mg −3 −3 ammonium 0.354–4.224 mg dm N-NH4, nitrate 0.156–1.623 mg dm N-NO3, nitrite 0.098–1.315 mg dm−3 N-NO2. The concentration of phosphorus flowing away in the dissolved form was on the level dm−3 N-NO . The concentration of phosphorus flowing away in the dissolved form was on the level of 0.039–2.1052 mg dm−3 P, while for potassium this was 0.698–7.852 mg dm−3 K. It is worth noting that of 0.039–2.105 mg dm−3 P, while for potassium this was 0.698–7.852 mg dm−3 K. It is worth noting the average content of biogenic nutrients, such as phosphorus and ammonium nitrogen, exceeded that the average content of biogenic nutrients, such as phosphorus and ammonium nitrogen, exceeded the threshold values corresponding to a good surface water class (Table 6), contained in the the threshold values corresponding to a good surface water class (Table6), contained in the Regulation Regulation of the Minister of Environment of 9 November 2011, which set out the method of classificationof the Minister of ofuniform Environment state surface of 9 Novemberwater bodies 2011, and which environmental set out the quality method standards of classification for priority of substancesuniform state [51] surface. These waterexcesses bodies did not and occur environmental in the case qualityof nitrate standards nitrogen. for Almost priority all tested substances chemical [51]. indTheseicators excesses of water did notquality occur reached in the casethe highest of nitrate values nitrogen. in 2010. Almost This all applies tested both chemical to the indicators maximum of waterconcentrations quality reached and average the highest values. values in 2010. This applies both to the maximum concentrations and average values. Table 6. The threshold values of water quality indices. Table 6. The threshold values of water quality indices. Threshold Values Index I Quality Class II Quality Class Threshold Values NIndex-NH4 (mg dm−3) ≤0.78 ≤1.56 N-NO3 (mg dm−3) I Quality≤2.2 Class II≤5 Quality Class −3 P-PO4 (mg− dm3 ) ≤0.07 ≤0.10 N-NH4 (mg dm ) ≤0.78 ≤1.56 −3 N-NO3 (mg dm ) ≤2.2 ≤5 −3 Analysis of the concentrationP-PO4 (mg dm of )the chemical≤0.07 components in ≤ surface0.10 runoff water showed a negative significant dependence on the majority of the analyzed factors (Table 7). The relationship between the concentration of the chemical components and the amount of precipitation was best Analysis of the concentration of the chemical components in surface runoff water showed a described by linear equations, and the correlation coefficients (r) were at levels from −0.32 to −0.44, negative significant dependence on the majority of the analyzed factors (Table7). The relationship and the determination index (R2) ranged from 0.10 to 0.20. Correlations between the concentration of between the concentration of the chemical components and the amount of precipitation was best chemical constituents and the indicator of rain erosion and surface runoff EI30 were at a slightly higher described by linear equations, and the correlation coefficients (r) were at levels from −0.32 to −0.44, level. The correlation coefficients (r) fluctuated from −0.39 to −0.49, and the determination index (R2) and the determination index (R2) ranged from 0.10 to 0.20. Correlations between the concentration of ranged from 0.27 to 0.37. chemical constituents and the indicator of rain erosion and surface runoff EI30 were at a slightly higher level. The correlation coefficients (r) fluctuated from −0.39 to −0.49, and the determination index (R2) ranged from 0.27 to 0.37. Water 2018, 10, 1132 12 of 17 Table 7. Equation of the dependence of water quality indicators on the concentration of the surface

and subsurface runoff water depending on the amount of precipitation and indicator EI30. Table 7. Equation of the dependence of water quality indicators on the concentration of the surface Parameter Rainfall (mm) R2 r EI30—Index R2 r and subsurface runoff water depending on the amount of precipitation and indicator EI . Surface Runoff 30 N-Ntot Parameter Rainfally = −0.0486x (mm) + 4.5634 0.1264R2 −0.36r y = −0.98ln(x) EI —Index + 7.0755 0.3231R2 −0.41r (mg dm−3) 30 N-NH4 Surface Runoff y = −0.0246x + 2.3867 0.1032 −0.32 y = −0.503ln(x) + 3.69 0.2715 −0.39 N-Ntot(mg dm−3) −3 y = −0.0486x + 4.5634 0.1264 −0.36 y = −0.98ln(x) + 7.0755 0.3231 −0.41 (mg dmN-NO) 3 y = −0.0121x + 1.1377 0.1238 −0.35 y = −0.263ln(x) + 1.8474 0.3695 −0.40 N-NH −3 (mg4 dm ) y = −0.0246x + 2.3867 0.1032 −0.32 y = −0.503ln(x) + 3.69 0.2715 −0.39 (mg dm−3) N-NO2 N-NO y = −0.0103x + 0.7673 0.1768 −0.42 y = −0.182ln(x) + 1.1881 0.3464 −0.44 (mg3 dm−3) y = −0.0121x + 1.1377 0.1238 −0.35 y = −0.263ln(x) + 1.8474 0.3695 −0.40 (mg dm−3) N-NO P 2 y = −y 0.0103x= −0.015x + 0.7673+ 1.0676 0.17680.1382 −0.37−0.42 y = y − =0.275ln(x)−0.182ln(x) + 1.7231 + 1.1881 0.29220.3464 −0.47−0.44 (mg dm(mg− dm3) −3) P K − y = y− =0.015x −0.0622x + 1.0676 + 5.022 0.13820.1959 −0.44−0.37 y = y − =1.05ln(x)−0.275ln(x) + 7.3505 + 1.7231 0.35160.2922 −0.49−0.47 (mg dm(mg dm3) −3) K y = −0.0622x + 5.022 0.1959Subsurface− Runoff0.44 y = −1.05ln(x) + 7.3505 0.3516 −0.49 (mg dm−3) N-Ntot y = −0.0872x + 7.2027 0.1949 −0.39 y = −1.479ln(x) + 10.488 0.3717 −0.45 (mg dm−3) Subsurface Runoff N-NtotN-NH4 − y = −y 0.0872x= −0.048x + 7.2027+ 3.8796 0.19490.1789 −0.37−0.39 y = y − =0.816ln(x)−1.479ln(x) + 5.6974 + 10.488 0.34170.3717 −0.44−0.45 (mg dm(mg dm3) −3) N-NH N-4NO3 y = −0.048x + 3.8796 0.1789 −0.37 y = −0.816ln(x) + 5.6974 0.3417 −0.44 (mg dm−3) y = 0.0002x2 − 0.0391x + 2.2444 0.2102 −0.40 y = −0.435ln(x) + 2.974 0.3886 −0.47 (mg dm−3) N-NO3 2 N−-NO3 2 y = 0.0002x − 0.0391x + 2.2444 0.2102 −0.40 y = −0.435ln(x) + 2.974 0.3886 −0.47 (mg dm ) y = 0.0002x2 − 0.0258x + 1.2236 0.2286 −0.42 y = −0.24ln(x) + 1.5563 0.4352 −0.46 N-NO(mg dm−3) 2 y = 0.0002x2 − 0.0258x + 1.2236 0.2286 −0.42 y = −0.24ln(x) + 1.5563 0.4352 −0.46 (mg dm−P3) y = −0.0169x + 1.2804 0.1333 −0.32 y = 0.00001x2 − 0.0072x + 1.2016 0.2521 −0.42 (mgP dm−3) 2 −3 y = −0.0169x + 1.2804 0.1333 −0.32 y = 0.00001x − 0.0072x + 1.2016 0.2521 −0.42 (mg dm K) K y = −0.0751x + 6.215 0.2201 −0.41 y = −1.258ln(x) + 8.9784 0.4120 −0.52 (mg dm−3) y = −0.0751x + 6.215 0.2201 −0.41 y = −1.258ln(x) + 8.9784 0.4120 −0.52 (mg dm−3)

In the surface runoff, the total annual dissolved nutrients in the surface runoff water that flowed In the surface runoff, the total annual dissolved nutrients in the surface runoff water that flowed from the slope were as follows: from 5.762 to 23.448 kg ha−1 N-Ntot, 2.706–13.561 kg ha−1 N-NH4, from the slope were as follows: from 5.762 to 23.448 kg ha−1 N-Ntot, 2.706–13.561 kg ha−1 N-NH , 1.548–5.478 kg ha−1 N-NO3, 0.950–2.824 kg ha−1 N-NO2, 0.696–4.644 kg ha−1 P, and 5.937–19.216 kg ha4−1 −1 −1 −1 1.548–5.478K. Kim et al kg. [18] ha determinedN-NO3, 0.950–2.824 nutrient losses kg ha of NN-NO-Ntot2 ,5.63 0.696–4.644–13.97 kg kg ha ha−1 andP, P and 0.96 5.937–19.216–11.00 kg ha kg−1, −1 −1 hadependK.ing Kim on et the al. [location18] determined and method nutrient of us lossese. The of largest N-Ntot outflows 5.63–13.97 of all kg studied ha and nitrogen P 0.96–11.00 forms, kg as −1 hawell, as depending phosphorus on theand location potassium, and methodwere recorded of use. Thein 2010 largest (Figure outflows 8) and of each all studied outflow nitrogen was at forms,a level asclose well to as 50% phosphorus of the total and mass potassium, of eroded were matter recorded in the in four 2010-year (Figure study8) and period. each outflow was at a level close to 50% of the total mass of eroded matter in the four-year study period.

25 N-Nog

20 N-NH4 )

1 15 N-NO3 – 10 N-NO2

(kg ha (kg 5 P 0 K Loss of the ingredient the ofLoss 2008 2009 2010 2011 Year

Figure 8. Mass of eroded chemical components (surface runoff). Figure 8. Mass of eroded chemical components (surface runoff).

WhenWhen analyzinganalyzing the results obtained obtained regarding regarding the the chemistry chemistry of of the the water water draining draining from from the the 0– 0–0.250.25 m msubsurface subsurface layer layer (Table (Table 5), it5 ),was it wasconcluded concluded that the that concentration the concentration of the majority of the majority of the tested of thewater tested quality water indicators quality was indicators higher wasthan higherin surface than runoff in surface water. runoff This applie water.d to This the appliedmaximum to and the maximumthe average and values. the This average is likely values. the result This of is chemical likely the erosion, result ofi.e. chemical, infiltrating erosion, water wa i.e.,shing inﬁltrating out the waterchemical washing components out the naturally chemical contained components in the naturally soil or chemicals contained applied in the to soil the or surface chemicals (arable) applied layer toduring the surfaceplant production (arable) layer [31]. The during total plant nitrogen production concentrations [31]. Thevaried total from nitrogen 1.132 to concentrations 8.563 mg dm−3 −3 variedN-Ntot from. Concentration1.132 to 8.563s of mgother dm nitrogenN-Ntot. forms Concentrations were at the following of other level nitrogens: ammonium forms were 0.525 at–4. the954 Water 2018, 10, 1132 13 of 17

−3 −3 −3 −3 −3 followingmg dm N levels:-NH4, ammoniumnitrate 0.2140.525–4.954–2.394 mg mg dm dm N-NON-NH3, nitrite4, nitrate 0.081 0.214–2.394–1.456 mg mgdm dm N-NON-NO2. The3, −3 −3 nitriteconcentration 0.081–1.456 of phosphorus mg dm N-NO flowing2. The away concentration in the dissolved of phosphorus form was flowing0.045–2. away563 mg in dm the dissolved P, while formpotassi wasum 0.045–2.563was 1.023–8 mg.234 dm mg− 3dmP,−3 while K. Analysis potassium of the was concentration1.023–8.234 of mg the dm chemical−3 K. Analysis components of the in concentrationthe subsurface of runoff the chemical water show componentsed a negative in the subsurface correlation runoff with waterthe analyzed showed factors a negative (Table correlation 7), and withthesethe relationships analyzed factors were stronger (Table7), than and thesefor the relationships surface runoff were water. stronger The than relationship for the surface between runoff the water.concentration The relationship of chemical betweencomponents the and concentration the amount of of chemical precipitation components was best anddescribed the amount by linear of precipitationand quadratic was equations, best described but the correlation by linear and coefficients quadratic (r) equations, were at level buts from the correlation −0.32 to −0.42, coefficients and the (r)determin were atation levels index from (R−2) 0.32ranged to − from0.42, 0.18 and theto 0.23. determination Correlations index between (R2) rangedthe concentration from 0.18 to of 0.23. the Correlationschemical components between theandconcentration the erosion rate of of the the chemical rain and components surface runoff and EI the30 were erosion present rate ofat theslightly rain andhigher surface level runoffs (the correlation EI30 were present coefficient at slightly r ranged higher from levels −0.42 (the to − correlation0.52), and coefficientthe determination r ranged index from −R20.42 ranged to − from0.52), 0.25 and to the 0.44. determination index R2 ranged from 0.25 to 0.44. During the the outflow outflow of of subsurface subsurface water, water, the theannual annual dissolved dissolved form formss of the of nutrients the nutrients were: −1 −1 −1 4 −1 −1 3 −1 −1 were:1.447–3 1.447–3.500.500 kg ha N kg-N hatot, 0.746N-Ntot,–1.811 0.746–1.811kg ha N-NH kg, 0 ha.377–0N-NH.902 kg4, ha 0.377–0.902 N-NO , 0. kg251 ha–0.442N-NO kg ha3, 2 −1 −1 −1−1 −1 0.251–0.442N-NO , 0.149 kg–0 ha.635 N-NOkg ha 2 ,P, 0.149–0.635 1.128–2.645 kg kg ha ha P, K. 1.128–2.645 As in the kgcase ha of surfaceK. As in outflow, the case the of surfacelargest outflow,outflows theof all largest nitrogen outflows forms of tested all nitrogen were recorded forms tested in 2010 were (Figure recorded 9) and in 2010each (Figureoutflow9) was and at each the outflowlevel of 37 was–38% at theof the level total of mass 37–38% of eroded of the totalcomponent mass ofs in eroded the four components-year study in period. the four-year Phosphorous study period.outflow Phosphorousin 2010 accounted outflow for approximately in 2010 accounted 47.8% for of approximately the sum of the47.8% eroded of component the sum ofs theof the eroded four componentsyears. The highest of the fourpotassium years. Theoutflow highest was potassium recorded outflowin 2011 was(33.7%), recorded although in 2011 in 2010 (33.7%), this although outflow inwas 2010 ver thisy similar outflow and was represented very similar 31.2% and of represented the four-year 31.2% total. of the four-year total.

4.000 3.500

3.000 N-Nog

) 1 – 2.500 N-NH4 2.000 N-NO3 (kg ha (kg 1.500 1.000 N-NO2

Loss of the ingredient of the Loss 0.500 P 0.000 K 2008 2009 2010 2011 Year

Figure 9. Mass of eroded chemical components (subsurface runoff). Figure 9. Mass of eroded chemical components (subsurface runoff).

Our research showed a high dependence between the EI index and the mass of eroded soil Our research showed a high dependence between the EI30 30index and the mass of eroded soil (R2 2 2 (R= 0.73).= 0.73). Also, Also, the thevalue value of ofthe the determi determinationnation coefficient coefficient (R (R2 = =0.62) 0.62) was was increased increased by by Rejman Rejman [29]. [29]. Swi˛echowicz[´ 43] determined that with an increase of the EI index, soil loss on bare fallow land Święchowicz [43] determined that with an increase of the EI3030 index, soil loss on bare fallow land −1 increases.increases. However,However, the the total total surface surface and and subsurface subsurface annual annual outflows outflows of nitrogen of nitrogen7.210–29.949 7.210–29 kg.949 ha kg, −1 −1 phosphorusha−1, phosphorus 0.846–5.279 0.846–5 kg.279 ha kg and ha−1potassium and potassium 7.065–21.660 7.065–21 kg.660 ha kg, were ha−1, higherwere higher than those than found those −1 –1 −1 infound the in literature the literature (4.5–20 (4 kg.5–20 ha kg haN-Ntot,−1 N-N 0.5tot, kg0.5 hakg haP,–1 2–17P, 2–17 kg kg ha ha−K)1 K) [ 31[31,52,53,52,53].]. TheThe obtainedobtained results are difficultdifficult to explicitlyexplicitly relate to those of erosive research conducted on other objects due to the complexity of the problem. The intensity of erosive processes in a given place is determined by many local factors, e.g. e.g.,, precipitation erosivity, soil erosion, land relief, vegetation cover, cover, land use, etc. [1818,54,54–56]. These factors, when interrelated, can intensify or reduce thethe soilsoil erosion.erosion. 4. Conclusions 4. Conclusions The research carried out on a loess slope in the catchment area in Wielkopole in the Lublin Upland, The research carried out on a loess slope in the catchment area in Wielkopole in the Lublin regarding the outflow of surface and subsurface water and selected components of matter, found that Upland, regarding the outflow of surface and subsurface water and selected components of matter, this area is highly affected by erosion, and the outgoing water is loaded with a high concentration of found that this area is highly affected by erosion, and the outgoing water is loaded with a high pollutants. This is the result of strong denuding processes. The possibility of erosive phenomena is concentration of pollutants. This is the result of strong denuding processes. The possibility of erosive phenomena is favored by the formation of a plough pan, which impedes the infiltration of water and intensifies the surface and subsurface runoff. The intensity and occurrence of meteorological events Water 2018, 10, 1132 14 of 17 favored by the formation of a plough pan, which impedes the infiltration of water and intensifies the surface and subsurface runoff. The intensity and occurrence of meteorological events significantly affect the size of water and soil outflow. Surface and subsurface drainage was highly correlated with the amount of precipitation with r = 0.75 and 0.77, respectively. High correlation (r = 0.78) was found between the erosivity index of the precipitation, the runoff EI30, and the sum of precipitation. Also, the mass of eroded soil was strongly correlated with the indicator EI30 (r = 0.86), while less correlated with the sum of rainfall (r = 0.65). The largest soil outflows occurred in 2010 when individual erosion events mobilized up to 60 Mg ha−1 of soil material on the slope and over 170 Mg ha−1 in total over one year. In addition to the atmospheric conditions, crop rotation, which included sugar beet crops, could have contributed to such large losses of soil and nutrients. Root plants poorly protected the soil against water erosion. In the remaining years of the study, soil losses were three to eight times smaller, which could partly be the result of cereal cultivation. The cultivation of root crops is associated with the use of mechanical care treatments that loosen the topsoil. In addition, root crops cover the soil poorly, especially in the early stages of development. This promotes soil erosion due to surface flushing. However, no mechanical care is carried out in the production of cereals. In addition, cereals (especially winter) are well-rooted, and the number of plants per unit area is high. As a result, the soil is more effectively protected against water erosion. The chemistry of the outgoing water fluctuated over a wide range, and the concentrations of biogenic components, such as phosphorus and ammonium nitrogen, exceeded the threshold values for good surface water. In the surface-draining water, the maximum concentrations were: −3 −3 −3 −3 6.321 mg dm N-Ntot, 4.224 mg dm N-NH4, 1.623 mg dm N-NO3, 1.315 mg dm N-NO2. The maximum phosphorus concentration was 2.105 mg dm−3 P, while the potassium level was 7.852 mg dm−3 K. In the subsurface runoff water, the concentrations of the analyzed indicators were −3 −3 −3 higher and were as follows: 8.563 mg dm N-Ntot, 4.954 mg dm N-NH4, 2.394 mg dm N-NO3, −3 −3 −3 1.456 mg dm N-NO2, 2.563 mg dm P, 8.234 mg dm K. The concentration of chemical components in the surface and subsurface runoff water in most cases proved to be negatively statistically correlated with the amount of precipitation and the indicator EI30. The correlation coefficients (r) were at levels from −0.32 to −0.52, and the determination index (R2) ranged from 0.10 to 0.44. The largest loss of nutrients caused by chemical erosion occurred in 2010 and amounted to 29.949 kg ha−1 of nitrogen; 5.279 kg ha−1 of phosphorus; and 21.660 kg ha−1 of potassium. The agricultural use of severe water erosion threatened loess areas in case of the poor selection of rotating crops (especially root crops) may result in large amounts of biogenic components and soil suspension in the water, causing the pollution and eutrophication of the aquatic environment.

Conﬂicts of Interest: The author declares no conﬂict of interest.

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