Unveiling the Potential of Agricultural Soil Loss Mitigation in Poland: Assessing Conservation Management and Support Practices

Abstract

This study aims to evaluate soil erosion mitigation strategies in Poland’s agricultural landscapes by applying the Revised Soil Loss Equation (RUSLE) model to identify high-risk areas where excessive soil loss adversely affects agricultural sustainability and productivity. Scenario assessments were conducted to evaluate the effectiveness of specific conservation practices—contour farming, reduced tillage, and cover crops—by simulating changes in the C-factor (cover-management factor) and P-factor (support practices factor) within the RUSLE framework. The research revealed heightened soil erosion rates during the summer months, particularly in regions with steep slopes and loess formations. Analysis indicated that annual soil loss from arable lands in Poland totals approximately 4.65 Mt yr⁻¹ and that contour farming, reduced tillage, and cover crops could collectively reduce this amount by up to 47%, with the highest reduction observed during the summer period. These findings highlighted the urgent need for stakeholders to adopt sustainable land management strategies. By quantifying the impact of these management practices on soil erosion rates, the study provided insights into the effectiveness of soil conservation measures in reducing erosion risks within Poland’s agricultural landscapes. This study emphasizes the importance of adopting sustainable land management strategies to preserve soil integrity and maintain agricultural productivity in Poland.

1. Introduction

Soil serves as the foundation of terrestrial ecosystems and plays a significant role in maintaining agricultural viability [1]. Beyond its function as a physical foundation, soil serves as a nurturing environment for biodiversity, a crucial repository of vital nutrients, and an integral contributor to global biogeochemical processes [2]. It is crucial for agricultural production, providing the essential support system for crop growth and sustenance of agricultural ecosystems [3]. However, soil faces numerous threats, among which soil erosion by water stands as a significant concern [4,5]. Soil erosion by water, which is estimated to contribute to approximately 50% of erosion worldwide, poses notable risks to agricultural production and food safety, with far-reaching consequences for both farmers and consumers [6]. As soil erodes, it strips away the fertile topsoil layer, which is important for sustaining crop growth and productivity. The loss of topsoil diminishes soil fertility, reduces water-holding capacity, and impairs nutrient availability, thereby compromising the ability of agricultural lands to support healthy crop yields [7]. Beyond its immediate impact on soil loss and productivity, soil erosion can lead to a number of adverse consequences that compromise the resilience of agricultural systems and the integrity of surrounding ecosystems. Reduced water infiltration and storage, soil compaction, and degradation of soil structure are among the primary consequences of soil erosion, impairing the capacity of agricultural lands to support healthy crop growth and productivity [8,9,10]. Furthermore, soil erosion contributes to the loss of biodiversity, sedimentation of water bodies, increased pesticide and fertilizer runoff, and loss of arable land, exacerbating environmental degradation and threatening food security [11,12]. In addition, soil erosion accelerates land degradation, leading to increased susceptibility to extreme weather events such as floods and droughts, further exacerbating agricultural challenges [13].

Agricultural land management practices are instrumental in controlling soil erosion and mitigating its effects on agricultural productivity and environmental sustainability [14]. Through the implementation of appropriate soil conservation measures and sustainable land management techniques, farmers can effectively reduce erosion rates and preserve soil resources [15]. Conservation practices such as contour farming, terracing, no-till farming, and the use of cover crops help to minimize soil disturbance, enhance soil structure, and promote vegetation cover, thereby reducing the risk of erosion by water [16]. Furthermore, proper land use planning, erosion control structures, and adoption of precision agriculture technologies play crucial roles in preventing soil erosion and promoting soil conservation at the landscape scale. By integrating these agricultural and management practices into farming systems, farmers can mitigate soil erosion, protect soil fertility, and sustainably manage agricultural landscapes for long-term productivity and environmental resilience [17].

Evaluating soil erosion is essential for formulating effective strategies to protect soil health and minimize its negative consequences. However, direct field measurements of soil erosion face challenges due to their dynamic and complex nature, as well as spatial and temporal variability. Consequently, soil erosion models are widely used to predict erosion rates, patterns, and drivers across different landscapes [18,19]. These models utilize mathematical equations and empirical relationships based on factors like rainfall, soil properties, land use, and topography. The Revised Universal Soil Loss Equation (RUSLE) is a widely employed model for predicting water-driven soil erosion and is applicable at various scales [20]. In the RUSLE model, the impact of land management is commonly parametrized through the cover-management factor, which quantifies the effect of practices such as tillage, cover crops, and plant residues on reducing soil loss from agricultural lands. Another important factor in the RUSLE model is the support practices factor, which accounts for control practices that mitigate runoff erosion potential by altering drainage patterns, runoff concentration, velocity, and hydraulic forces exerted on the soil surface. This factor reflects the cumulative impact of conservation practices, such as contour farming, strip cropping, terracing, and subsurface drainage, on soil loss at specific sites by modifying surface runoff patterns and reducing runoff volume and velocity [21]. These two factors are frequently utilized in the literature to simulate the effects of agricultural and management practices in controlling soil erosion and mitigating its impacts on agricultural productivity and environmental sustainability [22].

In Poland, the risk of agricultural soil erosion is heightened by a combination of factors specific to the country’s agricultural landscape. Although awareness of soil conservation practices is increasing, their implementation remains limited, especially among small-scale farmers who constitute the majority of the agricultural sector. The prevalence of small-farm agriculture contributes to fragmented land management practices, hindering the widespread implementation of soil conservation measures. Moreover, monoculture cropping systems, common in many parts of Poland, further intensify erosion risks by leaving soil exposed and vulnerable to erosion events. Inadequate soil conservation practices, such as conventional tillage and limited use of cover crops, fail to mitigate erosion effectively, exacerbating soil loss. The country’s topography, characterized by undulating terrain and varying slopes, exacerbates erosion risks, especially in regions with steep slopes and poorly vegetated areas. Additionally, Poland’s climate pattern, characterized by seasonal variations and frequent heavy rainfall events, further intensifies erosion risks by increasing surface runoff and soil detachment. These challenges are not unique to Poland; similar issues are observed in other Central and Eastern European countries such as Slovakia, Romania, and Bulgaria, where fragmented land ownership and conventional tillage contribute to erosion risk [23,24,25]. Moreover, Poland lies within the European loess belt, which extends across several countries, including Germany, the Czech Republic, Slovakia, Austria, Hungary, Ukraine, and parts of France and Romania. Regions within this belt are especially prone to erosion due to the high erodibility of loess soils, particularly under intense rainfall and reduced vegetation cover.

Recent research findings at the country level have revealed that within agricultural regions of Poland, the mean annual soil loss is quantified at 0.27 t ha⁻¹ yr⁻¹ [26]. Noteworthy is the peak monthly soil erosion rates, particularly evident during the summer season, with rates escalating to 0.08 t ha⁻¹ month, as documented on a country-wide scale [27]. However, localized areas exhibit considerably amplified erosion rates during August, with rates surpassing 2 t ha⁻¹ month⁻¹. The cumulative monthly soil loss from agricultural lands across Poland is estimated at approximately 4.87 Mt annually, with a substantial majority, comprising 68%, occurring within the summer months. Intense summer rainfall events, combined with reduced vegetation cover due to activities such as harvesting and post-harvest fallow, considerably increase soil vulnerability to erosion. Interestingly, the highest erosion rates do not coincide with the period of peak rainfall erosivity, as maximum vegetation cover during this time provides protection. Instead, erosion reaches its peak in August, following the harvest season. This disparity highlights the critical role of conservation agricultural practices (CAPs), particularly the temporary exposure of bare soil post-harvest, as a key factor contributing to elevated soil erosion rates. Multiple studies have consistently indicated that the utilization of conservation management practices in agricultural production in Poland is remarkably low [19,21]. This persistent underutilization of soil conservation measures constitutes a prominent contributing factor to the pervasive issue of soil loss and erosion across the country’s agricultural landscapes. Despite a growing body of scientific evidence highlighting the effectiveness of CAPs in mitigating erosion risks and preserving soil health, their integration into mainstream agricultural practices remains notably limited.

Numerous studies at the catchment scale have been conducted in Poland utilizing various modeling tools and methods to quantitatively assess soil erosion and identify critical areas. These studies typically employ models such as RUSLE [28,29] and SWAT [30], alongside pedological investigations [31] and direct plot measurements [32,33], to evaluate both historical and long-term changes in soil erosion rates. Geographically, much of this research focuses on the southern, mountainous regions of Poland, where the combination of erosive soils and prone topography leads to some of the highest erosion rates in the country. This study addresses gaps in current understanding and practice regarding soil erosion mitigation within Poland’s agricultural landscapes. Despite the well-documented impact of soil erosion on agricultural productivity and environmental sustainability, there is a significant lack of comprehensive assessments specifically evaluating the effectiveness of conservation management practices in Poland. Existing research has underscored the low adoption rates of soil conservation measures among farmers, highlighting the need for evidence-based strategies to promote their implementation and efficacy. Moreover, while previous studies have provided valuable insights into soil erosion dynamics and contributing factors within Poland, few have comprehensively evaluated the potential impact of targeted conservation interventions at both national and regional scales. This study directly addresses these limitations by (1) evaluating the maximum potential impact of three key conservation practices—reduced tillage, cover crops, and contour farming—and (2) applying the RUSLE model at a monthly temporal resolution to capture intra-annual variability in erosion intensity, and (3) conducting the analysis at a national scale across all arable lands in Poland.

Given this context, the main goal of this study is to assess the potential for soil erosion reduction in Poland’s agricultural areas through the application of conservation management and support practices. Specifically, the focus lies in assessing the effectiveness of implementing various management practices by simulating changes in the C-factor (cover-management factor) and P-factor (support practices factor) within the RUSLE framework. By quantifying the impact of these management practices on soil erosion rates, the study aims to provide insights into the maximum potential efficacy of soil conservation measures in mitigating erosion risks within Poland’s agricultural landscapes. To guide the analysis, this study addresses the following research questions: (1) What are the spatial and seasonal patterns of soil erosion risk across Poland’s arable lands at a monthly scale? (2) To what extent can conservation practices—specifically reduced tillage, cover crops, and contour farming—mitigate soil erosion when applied across these lands? (3) Which regions and time periods show the highest potential for soil loss reduction under a combined conservation scenario?

2. Materials and Methods

2.1. Research Area

Poland, with an area of 312,683 km², is situated in Central and Eastern Europe (Figure 1). The landscape is predominantly lowland with an average elevation of 173 m a.s.l. and the highest point reaching 2500 m a.s.l. [34]. The country’s soils exhibit significant diversity, generally characterized by low colloidal content and clay minerals, alongside medium to fast permeability. Granulometrically, gravel and sand make up the largest portion (46%), followed by clay (26%) and silt (8%), while the remainder includes soils from alluvial deposits, organogenic structures, and carbonate formations [35]. The country experiences a temperate climate. Precipitation levels vary across the country, with mountainous regions receiving over 1000 mm annually, while lowland areas receive between 400 and 500 mm, averaging 600 mm per year [36]. Rainfall distribution is also seasonal, with summer precipitation contributing approximately 63% and winter accounting for the remaining 37% [37]. Agriculture is the dominant land use, covering 63% of the total area, whereas forests account for 32%. The agricultural landscape is fragmented, consisting predominantly of small farms averaging 8.6 ha [38]. Notably, arable lands constitute 76% of agricultural areas. Despite the evident vulnerability of these lands, soil conservation practices have yet to achieve widespread adoption, with only marginal improvements observed in recent decades [39].

2.2. RUSLE Model

This study utilized an adapted version of the RUSLE model, originally developed by Renard [20]. The model integrates five key factors: rainfall erosivity (R-factor), soil erodibility (K-factor), length and slope steepness (LS-factor), cover management (C-factor), and conservation practices (P-factor). The RUSLE framework estimates the average annual soil erosion rate using the following equation:

$$E=R\times K\times LS\times C\times P$$

(1)

where E-annual average soil loss (t ha⁻¹ yr⁻¹); R-rainfall erosivity factor (MJ mm ha⁻¹ h⁻¹ yr⁻¹); K-soil erodibility factor (t ha h ha⁻¹ MJ⁻¹ mm⁻¹); LS-slope length and slope steepness factor (-); C-cover-management factor (-), and P-conservation practices factor (-).

Equation (1) can be modified to determine the monthly soil erosion rates by adjusting the temporal resolution of dynamiC-factors R and C from yearly to monthly intervals:

$$E_{month}=R_{month}\times K\times LS\times C_{month}\times P$$

(2)

where E_month is the average monthly soil loss (t ha⁻¹ month⁻¹); R-rainfall erosivity factor (MJ mm ha⁻¹ h⁻¹ month⁻¹).

In this study, Equation (2) was used to compute the monthly efficiency of agricultural conservation measures based on soil erosion maps within arable lands across Poland at a spatial resolution of 50 m.

2.3. Research Factors

In this study, all RUSLE factors were derived from previously published research and subjected to comprehensive evaluation. These factors, which encompass various parameters such as rainfall erosivity (R-factor), soil erodibility (K-factor), slope length and steepness (LS-factor), cover-management practices (C-factor), and support practices (P-factor), were carefully determined to accurately assess soil erosion risks in the study area. By utilizing data from existing literature and incorporating evaluation procedures, the RUSLE factors employed in this study are robust and reliable, providing a solid foundation for analyzing soil erosion processes and informing soil conservation strategies. The methodological framework for this study is presented in Figure 2, while the RUSLE parameter values are illustrated in Figure 3, Figure 4 and Figure 5 and summarized in

Table 1. RUSLE factor values for Poland.

RUSLE Parameter	Range	Mean	Standard Deviation	Source
K-factor t (ha h ha−1 MJ−1 mm−1)	0.003–0.05	0.016	0.009	[26]
LS-factor (dimensionless)	0.04–163	0.47	1.42	[26]
P-factor (dimensionless)	0.55–1	0.9781	0.056	[21]
R-factor January (MJ mm ha−1 h−1 month−1) *	0–42	1.6	2.8	[40]
R-factor February	0–37	0.3	1.1	[40]
R-factor March	0–44	1.5	2.6	[40]
R-factor April	3–111	12.3	5.5	[40]
R-factor May	29–321	62.2	22.9	[40]
R-factor June	59–400	108.7	33.9	[40]
R-factor July	70–470	165.8	42.2	[40]
R-factor August	47–358	114.3	24.9	[40]
R-factor September	24–218	49.5	15.8	[40]
R-factor October	12–95	22.4	6.8	[40]
R-factor November	3–66	11.6	4.3	[40]
R-factor December	0–44	4.4	3.7	[40]
C-factor January (dimensionless)	0–1	0.17	0.09	[27]
C-factor February	0–1	0.22	0.09	[27]
C-factor March	0–1	0.24	0.07	[27]
C-factor April	0–1	0.14	0.07	[27]
C-factor May	0–1	0.03	0.02	[27]
C-factor June	0–1	0.01	0.01	[27]
C-factor July	0–1	0.06	0.05	[27]
C-factor August	0–1	0.11	0.08	[27]
C-factor September	0–1	0.12	0.09	[27]
C-factor October	0–1	0.12	0.06	[27]
C-factor November	0–1	0.13	0.06	[27]
C-factor December	0–1	0.16	0.08	[27]

* The P-factor values were calculated using datasets spanning the years 2008–2022.

.

The R-factor was obtained from the Global Rainfall Erosivity Database (GloREDa), following the methodology by Panagos et al. [40], which utilizes high-frequency rainfall data from over 250 Polish stations (2008–2022) and ensemble machine learning interpolation at 1 km resolution. The C-factor was computed using monthly NDVI values from Terra-Aqua satellite imagery (2003–2023), based on the methodology of Marcinkowski and Szporak-Wasilewska [27], applying the Van der Knijff et al. [41] exponential regression model tailored to European conditions.

The final erosion maps in this study were generated using ArcGIS software (ArcMap version 10.8.2), specifically utilizing the raster calculator function. This process involved an expression that multiplied all RUSLE factors: rainfall erosivity, soil erodibility, topographic factor, cover-management factor, and support practice factor. The resulting output maps, which detail soil erosion intensity, were produced with a high resolution of 50 m.

2.4. Agricultural Conservation Practices

2.4.1. Conservation Practices Assumptions

In the course of this study, an assumption was made to estimate the potential of soil erosion mitigation, specifically within arable lands across the country. This approach was selected after careful consideration of various agricultural areas, with a particular focus on arable lands. The decision to concentrate solely on arable lands stemmed from the recognition that, unlike grasslands, which typically remain unploughed, arable lands are subjected to intensive agricultural practices and represent the most vulnerable areas to soil erosion within the Polish agricultural landscape. By narrowing the scope to arable lands, the study sought to target the areas most susceptible to erosion and where soil conservation measures are likely to yield the greatest impact. Another assumption was made to estimate the maximum potential of soil erosion mitigation in arable lands spanning the entire geographical expanse of the country. This approach was adopted to provide a comprehensive assessment of the plausible range of soil erosion reduction achievable within the agricultural landscape. The rationale behind this assumption rests upon several key considerations. Firstly, by extrapolating the maximum potential of soil erosion reduction across all arable lands nationwide, the study aims to offer insights into the upper bounds of achievable mitigation outcomes, thereby facilitating informed decision-making and policy formulation at a broader scale. Additionally, the estimation of maximum potential serves as a theoretical benchmark against which the efficacy of implemented soil conservation measures can be evaluated, offering valuable insights into the practical limitations and opportunities for enhancing soil erosion control practices.

2.4.2. Management Factor and Support Practice Factor Scenario

The management factor serves as a crucial metric for assessing the impact of various CAPs, including tillage practices and cover crop utilization, on mitigating soil loss from agricultural lands. Adhering to the methodology elucidated by Panagos and Borrelli [19], original C-factor values were adjusted on a monthly basis to simulate the practical implementation of protective measures tailored to the specific agricultural conditions of Poland. Specifically, the typical agricultural management schedule in Poland was considered, with reduced tillage practices applied during the months of July and August, coinciding with the harvest period. Reduction values of 65% were adapted from Stone and Hilborn [42] to reflect the effectiveness of reduced tillage in minimizing soil loss. Subsequently, for the intervening months from September to April, a period typically marked by bare soil following harvest, cover crops were introduced as a protective measure. The 65% reduction coefficient for reduced tillage and the slope-based P-factor values are consistent with prior Polish applications of the RUSLE model. Specifically, these values have been used in studies such as [33,43]. In addition, these coefficients align with values reported in European-scale studies, such as [21], which explicitly included Poland and its agricultural soil conditions in their empirical datasets and modeling framework. Drawing from the findings of Panagos and Borrelli [19], reduction values of 20% were applied to account for the soil-conserving benefits attributed to cover crop implementation during this phase of agricultural management. The C-factor adjustment was implemented across all arable lands in Poland. Cover-management practices, such as tillage practices and cover crops, can be utilized across various agricultural landscapes and cropping systems, without stringent requirements based on specific geographic or environmental conditions. Unlike practices such as contour plowing, which necessitate considerations of slope gradients and topographical features, cover-management practices are more universally applicable and adaptable to diverse agricultural contexts.

The Support Practice Factor encompasses a range of measures aimed at managing runoff and erosion, including contour farming, terracing, strip cropping, and the installation of grass waterways. The P-factor quantifies the efficacy of these practices in mitigating soil loss from agricultural lands. In this study, the P-factor was utilized to simulate contour farming practices in Poland, with values sourced from Morgan [44] and varying according to slope gradients. The lowest P-factor values (0.6) were assigned to slopes ranging from 10% to 12%, while the highest values (0.95) were assigned to slopes exceeding 25%. Moreover, the C-factor adjustment was uniformly applied across all arable lands in Poland with slopes greater than 10%, adhering to recommendations by Panagos and Borrelli [21]. This adjustment targeted areas where no support practices were identified in the original P-factor map from the study by Panagos and Borrelli [21], as depicted in Figure 3.

2.4.3. Scenario Application

In this study, the agricultural management scenario incorporating combined adjustments to the C and P factors was calculated using the RUSLE model (Equation (2)), with computations conducted separately for each month. Erosion rates were determined, and maps with a resolution of 50 m were generated to depict the spatial distribution of erosion across the landscape. To assess the effectiveness of the management interventions, total and relative changes in erosion were quantified by comparing the scenario-derived erosion rates with those obtained from the original soil erosion rate maps provided by Marcinkowski and Szporak-Wasilewska [27]. Additionally, to enhance the clarity and applicability of the results for policymakers, findings were not only presented at the national level but also disaggregated to the voivodeship level. This multi-scale approach facilitated a comprehensive understanding of the spatial variability in erosion mitigation outcomes, enabling targeted policy interventions and management strategies tailored to the specific characteristics of each administrative region.

3. Results

3.1. Current Soil Erosion in Arable Lands

The examination of monthly soil erosion dynamics across arable lands in Poland unveiled notable spatio-temporal variances (Figure 6). Model outputs underscored heightened soil erosion levels during the summer period (July–September), followed by a marked reduction during the winter and spring months (December–March). The cumulative total annual soil loss, calculated as the aggregate of monthly soil erosion estimations, within arable lands of Poland was computed at 4.65 Mt. Remarkably, at the monthly scale, the lowest soil erosion magnitude was observed in February (10 kt), while the highest was recorded in August (1.45 Mt). Notably, the soil erosion magnitude in August was approximately 140 times greater than that of February (

Table 2. Monthly values of soil erosion (kt month⁻¹) at voivodeship level on arable lands in Poland.

Voivodeship	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Total	% of National Total	Ratio of Total Erosion and Total Arable Land Area (kt km−2)
Śląskie	5	3	14	21	9	6	48	61	34	18	15	7	242	5%	0.05
Opolskie	0	0	1	7	6	3	87	107	55	17	8	1	292	6%	0.05
Wielkopolskie	2	0	1	6	8	9	75	80	34	13	7	4	237	5%	0.01
Zachodniopomorskie	7	1	6	8	6	4	54	77	31	13	7	10	225	5%	0.02
Świętokrzyskie	0	0	0	23	20	9	80	106	58	28	13	1	338	7%	0.06
Kujawsko-pomorskie	0	0	0	7	11	7	65	84	35	14	8	3	233	5%	0.02
Podlaskie	0	0	0	8	8	4	15	28	16	9	6	2	96	2%	0.01
Dolnośląskie	7	1	9	24	14	8	135	169	74	35	18	9	504	11%	0.05
Podkarpackie	0	0	17	43	16	8	51	66	49	38	23	19	330	7%	0.05
Małopolskie	8	3	33	81	38	21	99	143	85	59	40	19	628	13%	0.09
Pomorskie	4	0	1	8	8	4	41	75	32	16	10	8	206	4%	0.03
Warmińsko-mazurskie	3	1	2	12	9	4	40	84	37	17	15	7	231	5%	0.02
Łódzkie	0	0	0	6	6	5	49	52	22	9	7	2	158	3%	0.02
Mazowieckie	0	0	0	8	10	7	42	55	27	11	7	2	169	4%	0.01
Lubelskie	0	0	0	39	35	9	143	239	137	57	22	8	689	15%	0.05
Lubuskie	1	0	1	2	2	3	24	23	9	4	2	2	74	2%	0.02
Total	37	10	86	302	207	108	1050	1449	734	358	208	102	4652	100%	0.03

). Strikingly, during the summer trimester (July–September), 69% of the total annual soil loss was observed. Spatially, the most pronounced erosion occurred in Lubelskie Voivodeship, with an annual estimate of 689 kt, whereas the least erosion was observed in Lubuskie Voivodeship, totaling 74 kt annually. Notably, a considerable portion of the overall soil erosion burden, accounting for nearly 40% (1.82 Mt annually), is concentrated within three voivodeships: Lubelskie, Małopolskie, and Dolnośląskie, despite their combined arable land area representing only 20% of Poland’s total. When examining the ratio of total soil erosion to total arable land, notably higher values, approximately 0.06 kt km⁻², are observed for voivodeships in southern Poland (Śląskie, Opolskie, Świętokrzyskie, Dolnośląskie, Małopolskie, Lubelskie) in contrast to central and northern regions, where the ratio is 0.02 kt km⁻².

3.2. Application of Agricultural Conservation Measures

In accordance with the recommendations provided by Panagos, Borrelli [21] regarding the specifications for contour plowing based on slope gradient, a threshold of 10% was established for Poland. Figure 7 illustrates the distribution of arable lands with slopes exceeding 10% alongside an updated map depicting the P-factor adjustments corresponding to areas with slopes greater than 10% on arable lands. The geospatial analysis conducted unveiled that within Poland, there exists an expanse of land totaling 10,855 km² where gradients exceed 10%, yet contour farming practices have not been applied. In response to this finding, adjustments to the P-factor were introduced for these particular plots, varying depending on the gradient of the slope. As delineated in

Table 3. Characteristics of agricultural conservation scenario application at voivodeship level.

Voivodeship	Area (km2)	Area of Arable Lands (km2)	Share of Arable Lands (%)	Area of P-Factor Change (km2)	Share of P-Factor Change on Arable Lands (%)
Śląskie	12,317	4557	37	480	10.5
Opolskie	9400	5429	58	225	4.1
Wielkopolskie	29,797	16,935	57	224	1.3
Zachodniopomorskie	22,896	9328	41	538	5.8
Świętokrzyskie	11,697	5589	48	284	5.1
Kujawsko-pomorskie	17,948	11,142	62	421	3.8
Podlaskie	20,054	8994	45	423	4.7
Dolnośląskie	19,936	10,232	51	1033	10.1
Podkarpackie	17,843	7253	41	1586	21.9
Małopolskie	15,166	7282	48	2694	37.0
Pomorskie	18,235	8158	45	840	10.3
Warmińsko-mazurskie	24,054	11,989	50	1368	11.4
Łódzkie	18,194	10,370	57	44	0.4
Mazowieckie	35,529	18,090	51	87	0.5
Lubelskie	25,004	13,913	56	488	3.5
Lubuskie	13,990	4440	32	120	2.7

, the Małopolskie voivodeship exhibited the highest proportion of P-factor alteration to simulate contour farming (37%), while the lowest percentage was observed in Łódzkie (0.4%). Generally, a greater proportion of P-factor adjustments were concentrated in the southern region of Poland, characterized by mountainous terrain, with comparably lower adjustments evident in the central plains. The average percentage of P-factor adjustments applied to arable lands throughout Poland was calculated at 8.2%. The country’s average P-factor was reduced by 0.03 from its original value derived from the map by Panagos, Borrelli [21], resulting in a current value of 0.94.

Uniform modifications to the cover-management factor were applied across all arable lands, encompassing a total area of 153,000 km² (refer to Figure 1). The updated maps illustrating C-factor adjustments, simulating the effects of cover crops and reduced tillage practices, are presented in Figure 8 for each month. On average, the annual C-factor value decreased by 31% (0.04) from its original pre-conservation measures value of 0.13 to the current value of 0.09. The most substantial reduction was observed in August, amounting to 0.07.

3.3. Efficiency of Soil Loss Reduction

The implementation of agricultural soil conservation measures on arable lands in Poland has resulted in a reduction in soil loss. Figure 9 and Figure 10 illustrate the spatial distribution of these reductions for each month. The highest reduction potential was observed during the summer months (July–September), with an average reduction rate reaching up to −0.06 t ha⁻¹ month⁻¹ in August, while the lowest reduction was recorded during winter (−0.0002 t ha⁻¹ month⁻¹ in February). According to the findings, the total potential reduction ranged from −3.3 kt month⁻¹ (February) to −970.2 kt month⁻¹ in August, resulting in an overall reduction of −2190 kt year⁻¹ (relative reduction by 47%). Analyzing the spatial distribution of reduction potential, the greatest reductions were observed in Lubelskie (322 kt month⁻¹), Małopolskie (268 kt month⁻¹), and Dolnośląskie (258 kt month⁻¹) voivodeships, while the lowest reductions were noted in Lubuskie (−37 kt month⁻¹), Podlaskie (−39 kt month⁻¹), Łódzkie, and Mazowieckie (−76 kt month⁻¹) (

Table 4. Absolute monthly reduction in soil erosion after application of agricultural conservation scenario at voivodeship level (kt month⁻¹).

Voivodeship	Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec	Total
Śląskie	−1.6	−1.1	−4.5	−6.4	−0.9	−0.5	−32.7	−41.3	−8.8	−5.0	−4.3	−2.2	−109
Opolskie	0.0	0.0	−0.3	−1.9	−0.5	−0.2	−58.9	−72.1	−14.5	−4.4	−2.0	−0.3	−155
Wielkopolskie	−0.4	0.0	−0.2	−1.3	−0.3	−0.3	−49.7	−52.6	−7.5	−2.8	−1.5	−0.8	−117
Zachodniopomorskie	−2.0	−0.2	−1.5	−2.1	−0.4	−0.3	−36.1	−51.3	−7.5	−3.4	−1.9	−2.6	−109
Świętokrzyskie	0.0	0.0	−0.1	−5.7	−0.9	−0.4	−52.7	−70.3	−13.5	−6.7	−3.3	−0.3	−154
Kujawsko-pomorskie	0.0	0.0	0.0	−1.7	−0.5	−0.3	−43.0	−55.9	−8.3	−3.3	−1.9	−0.8	−116
Podlaskie	0.0	0.0	0.0	−1.9	−0.3	−0.2	−10.0	−18.7	−3.7	−2.2	−1.4	−0.4	−39
Dolnośląskie	−2.4	−0.3	−3.1	−7.5	−1.4	−0.7	−91.2	−114.2	−19.7	−9.7	−5.4	−2.7	−258
Podkarpackie	−0.1	−0.1	−5.8	−14.0	−1.9	−1.0	−35.1	−45.2	−14.0	−11.7	−7.2	−6.4	−143
Małopolskie	−2.6	−1.0	−11.3	−25.1	−3.0	−2.1	−67.4	−96.7	−22.6	−17.2	−12.3	−6.2	−268
Pomorskie	−1.0	0.0	−0.2	−2.3	−0.8	−0.4	−27.7	−50.8	−8.5	−4.5	−2.9	−2.3	−101
Warmińsko-mazurskie	−0.8	−0.4	−0.6	−3.2	−0.7	−0.4	−26.9	−56.2	−9.4	−4.7	−4.1	−2.0	−109
Łódzkie	0.0	0.0	0.0	−1.3	−0.1	−0.1	−32.1	−34.1	−4.7	−1.9	−1.5	−0.3	−76
Mazowieckie	0.0	0.0	0.0	−1.8	−0.2	−0.2	−27.7	−36.3	−5.7	−2.4	−1.6	−0.4	−76
Lubelskie	0.0	0.0	0.0	−9.9	−2.0	−0.4	−95.3	−159.4	−33.5	−14.2	−5.5	−2.0	−322
Lubuskie	−0.4	−0.1	−0.3	−0.5	−0.1	−0.1	−15.8	−15.4	−2.2	−0.9	−0.4	−0.5	−37
Total	−11.3	−3.3	−27.9	−86.4	−14.1	−7.6	−702.4	−970.2	−184.2	−95.0	−57.4	−30.3	−2190

).

4. Discussion

Soil erosion is widely recognized as a critical environmental issue with far-reaching implications for agricultural productivity and ecosystem stability. In Poland, this challenge is particularly pressing, as numerous local studies have highlighted erosion-prone areas, quantified the extent of soil loss, and examined the effects of land use changes and conservation practices on mitigating erosion rates. For instance, Kijowska-Strugała and Bucała-Hrabia [43] analyzed the intensity of soil erosion in a mountainous agricultural catchment that transitioned from intensive use to reduced farming and increased forest cover using the RUSLE model. Their findings indicated a substantial decrease in soil erosion by 77% due to these changes. Similarly, Latocha and Szymanowski [45] investigated the effects of land use/cover changes and climate changes on soil erosion rates in the Sudetes Mountains over the last 150 years, employing the RUSLE model. They observed significant increases in forest and grassland areas at the expense of arable lands, resulting in a 76.2% reduction in soil erosion in the study area.

This study addresses a significant research gap by providing an analysis at the national scale for the entire territory of Poland and quantifying intra-annual soil erosion variations on a monthly basis. The analysis of monthly soil erosion dynamics across arable lands in Poland clarifies the complex interaction between temporal and spatial factors influencing erosion processes. Substantial disparities are evident across diverse regions of the country. Notably, regions like Lubelskie Voivodeship exhibit elevated erosion rates, highlighting the localized occurrence of erosion hotspots. Furthermore, a concentration of soil erosion within southern voivodeships, despite their relatively modest arable land extents, is observed. Generally, areas displaying heightened susceptibility to soil erosion are concentrated in specific geographical locales characterized by distinct environmental attributes and land management practices. In southern Poland, particularly mountainous regions, elevated soil erosion rates are attributable to steep slopes. The identification of hot spot areas in this specific region aligns with findings reported by other researchers conducting local, detailed studies [30,46]. These studies corroborate the zones of heightened erosion risk, reinforcing the need for targeted soil conservation measures. Such consensus among various studies underscores the reliability of the data and methodologies used, providing a robust basis for further research and policy planning to mitigate soil erosion effectively in these critical areas. The presence of loess formations in the southern and southeastern parts of the country also contributes to heightened susceptibility to soil erosion [47]. Conversely, regions in central and northern Poland, encompassing the central plain areas and northern coastal zones, frequently exhibit lower soil erosion rates, potentially owing to flatter terrain characteristics, thereby mitigating soil erosion risk. While the spatial distribution of soil erosion risk aligns with previous investigations [26,33,43], this study notably contributes novel insights by incorporating temporal dynamics, a pioneering endeavor in the field.

Soil erosion is most pronounced from July to September, driven by both high rainfall erosivity and agricultural activities. Intense summer rainfall, combined with reduced vegetation cover due to harvesting and post-harvest fallow, increases erosion risk [48]. Notably, the highest erosion rates occur in August rather than July, despite July having the greatest rainfall erosivity, as dense vegetation provides protection earlier in the season. This highlights the significant role of CAPs, particularly the temporary exposure of bare soil after harvest, in amplifying erosion [49]. Although winter exhibits high C-factor values due to low vegetation cover, erosion remains limited as rainfall erosivity is minimal during this period.

The presented magnitude of soil erosion in Poland carries significant consequences for agricultural productivity and river systems, with distinct implications for the country’s economy and environment. In agriculture, soil erosion leads to the loss of valuable topsoil, which is critical for sustaining crop yields and maintaining soil fertility [50]. The financial impact on farmers includes reduced crop productivity. Research by Panagos, Standardi [51] underscores the substantial annual productivity loss stemming from soil erosion in Poland, estimated at 30 million EUR. Furthermore, soil erosion engenders the deterioration of river systems by depositing sediment into water bodies, leading to escalated sedimentation rates and compromised water quality. For instance, Madeyski and Michalec [52] documented considerable silting of reservoirs in Southern Poland, surpassing national averages. Agricultural areas were identified as the principal contributors to sediment erosion, resulting in diminished reservoir capacity owing to silting. In line with these findings, recent data presented by Panagos and Matthews [53] estimated the annual cost of sediment removal in Poland to be 58 million EUR. Moreover, soil erosion, characterized by amplification in surface runoff, poses a notable risk of phosphorus depletion from the soil, thereby exacerbating concerns regarding water eutrophication, notably in regions susceptible to erosion, such as Southern Poland. Research conducted by Smoroń [54] delved into the phenomenon of surface water eutrophication in loess uplands in Southern Poland, revealing heightened concentrations of total phosphorus attributed to water-induced soil erosion.

The findings of this study indicate variable erosion rates across Poland. To evaluate the sustainability of observed soil erosion rates, it is essential to consider natural soil formation rates, which provide a benchmark for tolerable soil loss and long-term soil health. The assessment of tolerable soil erosion requires a critical understanding of natural soil formation rates, which in Europe are estimated to range between 0.3 and 1.4 t ha⁻¹ yr⁻¹ under undisturbed conditions [55]. These rates encompass contributions from both mineral weathering and dust deposition and serve as benchmarks for sustainable soil loss. In the context of our study area, the observed mean erosion rate of 0.27 t ha⁻¹ yr⁻¹ falls within this range. However, localized variations in erosion rates, particularly in areas with steep slopes or intensive agricultural activity, likely exceed the upper limit of soil formation. This disparity indicates that current erosion rates in some locations may be unsustainable, potentially leading to long-term soil degradation. The absence of region-specific soil formation data for the study area limits a precise evaluation of erosion tolerability. Future research should prioritize the quantification of soil formation rates at finer spatial scales to better align conservation efforts with the natural regenerative capacity of soils. Until such data are available, adopting the precautionary principle by implementing erosion control measures across vulnerable areas remains essential to safeguarding soil health and ecosystem services.

The findings of this study offer a comprehensive overview of the extent of soil erosion under the current limited use of agricultural conservation measures. Building on this assessment, the next phase aimed to highlight the potential impact of conservation practices and the significant reduction in soil erosion that can be achieved within Poland’s unique climatic and topographical context. The application of the RUSLE model in assessing the efficiency of agricultural conservation measures for reducing soil erosion and loss has become a fundamental aspect of contemporary soil management research. RUSLE, a widely used empirical model, integrates various factors such as climate, soil characteristics, topography, land use, and management practices to estimate soil erosion rates across diverse landscapes [56]. This framework allowed the construction of scenario-based assessments that evaluate the impact of different conservation strategies on potential soil loss before implementation. Recent studies have increasingly employed RUSLE to explore the impacts of different conservation practices on soil erosion dynamics [57,58,59]. In this study, the implementation of conservation measures revealed a potential reduction in soil loss of up to 47%, decreasing from 4.6 Mt to 2.46 Mt annually. Local studies in Poland assessing the impact of various soil protection measures have demonstrated significant potential for reducing soil erosion [43,45]. For instance, some strategies, like reforestation of agricultural areas, have been shown to decrease soil erosion by up to 76%. This substantial reduction underscores the effectiveness of more extensive landscape changes in mitigating erosion. In contrast, the reduction level reported in this study was achieved through the adoption of less drastic yet impactful practices such as contour farming, reduced tillage, and the use of cover crops. These measures were specifically implemented in areas deemed most suitable, illustrating a targeted approach to soil conservation that aligns with the practical and ecological contexts of the regions studied. These particular conservation practices are considered highly feasible for farmers to implement as they align with the objectives of the Agri-Environmental Program (AEP) of the European Union (EU). The AEP aims to promote sustainable CAPs while ensuring environmental protection, with a specific focus on enhancing soil and water conservation measures across agricultural landscapes. Under the AEP, farmers are encouraged to adopt practices that mitigate soil erosion, enhance soil structure, and improve soil fertility. Financial incentives and support are provided to farmers who voluntarily participate in these initiatives, including direct payments and subsidies for implementing specific conservation practices.

Despite the presence of direct payments offered through the Agri-Environmental Program (AEP) in Poland, the adoption rate among farmers remains notably low. Eurostat data from 2013 indicates that only approximately 18% of agricultural land in Poland is currently enrolled in any of the agri-environmental measures. Furthermore, research conducted by Sadowski and Czubak [60] suggests that merely 60% of all beneficiaries of the AEP are engaged in the specific package focused on soil and water protection. This indicates that a mere 10% of agricultural lands in Poland are receiving financial support and implementing at least one of the key measures, which include cover crops, contour farming, or reduced tillage. Despite the current low uptake, there remains ample room for improvement in promoting and incentivizing the adoption of conservation measures under the Agri-Environmental Program in Poland. Efforts to raise awareness among farmers about the benefits of soil and water protection practices, such as enhanced soil fertility, reduced erosion, and improved water quality, could help increase participation rates. Providing comprehensive support and guidance to farmers on implementing these measures effectively, including technical assistance and access to resources, could facilitate their uptake. Several targeted actions could be considered to improve uptake. These include simplifying application procedures to reduce administrative burden, expanding locally available advisory services to provide tailored technical support, and adjusting payment levels to better reflect the true costs and effort involved in implementing conservation practices. Longer-term program commitments and greater stability in funding could also improve farmer confidence. Experiences from countries like Austria and Germany—where agri-environmental participation rates are significantly higher—demonstrate that programs combining accessible design, sufficient financial incentives, and strong institutional support can lead to more widespread adoption [61]. Adapting such elements to the Polish context could help unlock greater environmental benefits from the AEP.

In light of the escalating challenges induced by climate change, the adoption of conservation practices emerges as increasingly imperative for Poland’s agricultural sector. As climate change continues to exert environmental pressures, with more frequent extreme weather events and changes in precipitation patterns, protecting the resilience of agricultural landscapes becomes crucial. Multiple studies on climate change projections for Poland underscore the anticipated shifts in precipitation patterns, with a consensus indicating not only an overall increase in annual precipitation but also a notable elevation in precipitation levels during the winter season. This trend is forecasted to manifest as a reduction in snowfall and a concurrent rise in rainfall occurrences [62,63,64,65]. Such alterations in precipitation dynamics have the potential to significantly impact the existing erosion patterns in Poland, particularly during the winter months when erosion rates are traditionally at their lowest due to minimal rainfall erosivity indices and very low cover management factors. A shift towards higher rainfall erosivity values during the winter season could exacerbate soil erosion during this period, thereby accentuating the critical need for the implementation of conservation measures to mitigate erosion risks and preserve soil integrity.

The findings of this study have significant applications for soil conservation and agricultural sustainability in Poland. By identifying erosion hotspots and quantifying the potential impact of conservation management practices, this study provides valuable insights for policymakers and stakeholders. The results can inform the development of targeted strategies, such as contour farming, reduced tillage, and cover cropping, to address soil erosion in the most vulnerable regions. Additionally, the study supports the prioritization and expansion of agricultural-environmental programs by demonstrating the cumulative benefits of implementing multiple conservation practices. On a regional scale, the findings can guide the design of localized land management plans tailored to the specific topographic and climatic conditions of each area.

While the RUSLE model is a widely accepted tool for assessing water-driven soil erosion, its applicability is primarily limited to sheet and rill erosion on agricultural lands, particularly arable fields. The model does not account for gully erosion, mass movements, or sediment transport processes, nor is it well suited for non-agricultural land uses such as forests, wetlands, or urban areas [20]. In this study, the application was limited to arable lands precisely because they fall within RUSLE’s most appropriate use case. Additionally, the reliability of RUSLE output is influenced by the accuracy and spatial resolution of input data, including rainfall erosivity (R-factor), soil erodibility (K-factor), slope characteristics (LS-factor), and land use data (C- and P-factors) [66]. Although high-resolution national datasets were used wherever possible, inherent uncertainties in these inputs may affect local precision, particularly in areas with complex topography or heterogeneous soils. Another limitation of the RUSLE model is its empirical structure, which does not allow for mechanistic simulation of the physical processes driving erosion (e.g., runoff generation, sediment transport). As such, it does not support a detailed analysis of interactions between variables such as rainfall, slope, and vegetation cover. This study was limited to identifying spatial and temporal patterns of erosion risk and mitigation potential, not modeling underlying process dynamics.

One limitation of this study is that it does not incorporate external drivers such as climate change, dynamic land-use transitions, or the evolution of agri-environmental policy frameworks. The results are based on present-day climatic and land use conditions and assume uniform implementation of conservation measures, which may differ significantly in real-world scenarios. Future research could expand on this work by integrating climate projections (e.g., future rainfall erosivity trends), land use change scenarios, and policy adoption modeling to estimate more nuanced and temporally responsive soil erosion trajectories. Incorporating such dynamic factors would further enhance the utility of erosion modeling for long-term soil and agricultural planning.

The decision to employ a monthly temporal resolution in this study was driven by the need to capture the intra-annual variability of key factors influencing soil erosion, particularly rainfall erosivity and vegetation cover. Monthly modeling allows for a more detailed understanding of erosion dynamics, facilitating the identification of periods with heightened erosion risk and informing the timing of conservation interventions. However, this choice introduces certain limitations. Monthly data may still overlook short-term extreme events, such as intense storms, which can contribute disproportionately to annual soil loss. Additionally, the increased data requirements and computational complexity associated with monthly modeling can pose challenges. Despite these limitations, the benefits of enhanced temporal detail are considered to outweigh the drawbacks, providing more actionable insights for soil conservation strategies.

5. Conclusions

In conclusion, this study underscores the need for proactive measures to address the escalating risk of soil erosion in Poland’s agricultural landscape. Through detailed analysis and the use of the RUSLE model, the study identified erosion hotspots where soil loss rates significantly threaten agricultural productivity. By simulating changes in the C-factor and P-factor within the RUSLE framework, the research highlighted the potential effectiveness of implementing various management practices, including contour farming, reduced tillage, and cover crops, in mitigating erosion risks. The findings reveal that these conservation measures could lead to a substantial reduction in soil loss, particularly during peak erosion periods in summer. For instance, the analysis revealed that contour farming, reduced tillage, and cover crops could collectively reduce soil loss by up to 47% annually. This translates to a reduction from an initial estimate of 4.65 Mt of soil loss per year to approximately 2.46 Mt, indicating a significant mitigation effect. Moreover, the study emphasizes the importance of adopting sustainable land management strategies to preserve soil integrity and ensure long-term agricultural sustainability. The insights provided in this research serve as a valuable resource for policymakers and stakeholders in devising targeted interventions and promoting the adoption of soil conservation measures. Moving forward, concerted efforts are needed to raise awareness, provide incentives, and facilitate the implementation of sustainable practices to safeguard Poland’s agricultural productivity and environmental resilience against the detrimental impacts of soil erosion.