Assessment of Soil Loss Due to Wind Erosion and Dust Deposition: Implications for Sustainable Management in Arid Regions

Featured Application

A number of negative consequences, including reduced soil fertility, increased desertification, diminished agricultural productivity, and heightened air pollution, have been caused by soil erosion and dust deposition in the Al-Baha region; therefore, the methodologies and outcomes of this study provide practical guidance for measuring these effects on soil properties. This study emphasizes the development of sustainable management techniques that mitigate these adverse impacts, ensure compliance with international environmental standards, and support long-term ecological balance and agricultural sustainability. The results could be used to help land managers and policymakers develop efficient soil conservation measures in areas susceptible to wind erosion.

Abstract

Soil loss due to wind erosion and dust deposition has become a growing concern, particularly in arid regions like Al-Baha, Saudi Arabia. The aim of this study was to quantitatively assess soil loss and dust deposition using three different dust collection methods across 20 sites during the summer of 2022. The methods include Big Spring Number Eight (BSNE), which measures airborne dust particles using passive samplers; Surface Dust Collector (SDC), designed to collect dust settling on the ground surface; and Marble Dust Collector (MDCO), which utilizes marble-coated surfaces to trap and measure dust deposition. These methods collectively provide a comprehensive evaluation of dust dynamics in the study area. The objective was to evaluate the effects of wind erosion and dust deposition on soil properties, offering insights into the mechanisms of soil loss in arid environments. The study revealed significant variations in soil characteristics, including low organic matter content (<1%), high calcite (up to 19.62%), and increased salinity levels, with notable quantities of Cl⁻ (211.58 meq kg⁻¹) and Na^⁺ (165.98 meq kg⁻¹). July showed the highest dust deposition (0.0133 ton ha⁻¹), particularly at site S11, while soil loss was lowest at site S5. This research offers novel insights into the nonlinear relationship between soil loss and time, contributing to sustainable soil management strategies. By aligning with Saudi Arabia’s Vision 2030 and the Sustainable Development Goals (SDGs), the findings underscore the need to mitigate soil loss to enhance environmental sustainability, prevent desertification, and promote long-term resilience in arid regions.

1. Introduction

Soil, often described as the “skin of the Earth”, is a vital resource for sustaining life and supporting ecosystems worldwide [1]. However, it faces significant threats from wind erosion, a natural process that predominantly occurs under dry conditions with high wind velocities, especially on bare soils with limited plant biomass [2,3,4]. Over one-third of the Earth’s land surface has experienced wind erosion, resulting in environmental and socio-economic consequences such as reduced agricultural productivity, respiratory ailments, damage to infrastructure, and diminished water supplies [5,6,7,8,9]. Desertification and wind erosion, often culminating in dust storms, are particularly destructive in arid and semi-arid regions, including the Arabian Peninsula, where climatic and environmental factors drive their occurrence [10]. The movement of dust particles is influenced by a range of factors, including high wind velocities; low vegetation cover; dry soil conditions; and land mismanagement, such as overgrazing and deforestation. These factors exacerbate soil erosion and the detachment of particles, making them more susceptible to transport by wind [11]. Dust storms, which affect over 2 billion people globally and nearly 40% of the Earth’s land surface, transport approximately 2 billion tons of dust annually. This movement alters soil texture, nutrient availability, and atmospheric properties while posing severe threats to environmental and human health [12,13,14]. These processes degrade topsoil, reduce soil fertility, and contribute to the formation of sand dunes, blocking waterways, burying arable lands, and creating significant socio-economic challenges [15,16].

The challenges posed by wind erosion and dust deposition are intricately linked to several of the United Nations Sustainable Development Goals (SDGs) adopted in 2015, including preventing climate change (SDG 13), ensuring clean water and sanitation (SDG 6), encouraging sustainable agriculture (SDG 2), and maintaining life on land (SDG 15). Addressing these challenges contributes directly to global efforts aimed at promoting environmental sustainability and improving socio-economic well-being [17].

The Kingdom of Saudi Arabia (KSA), with its arid and semi-arid landscapes, extensive deserts, harsh summers, sparse vegetation, and low rainfall, faces significant environmental challenges due to wind erosion. This phenomenon impacts public health and soil productivity, particularly in rural and urban areas. The region’s low rainfall, minimal vegetative cover, and extreme weather conditions exacerbate the risk of wind erosion and soil loss, leading to the transportation of soil particles, loss of topsoil, nutrient depletion, the formation of sand dunes, and sedimentation in water bodies. These consequences hinder water storage capacity and agricultural productivity [18,19]. Additionally, intra-regional impacts include local environmental disturbances, ecosystem disruption, reduced visibility, traffic fatalities, land abandonment, and, in extreme cases, forced migration [11].

Managing wind erosion also is in line with Saudi Arabia’s Vision 2030, which aims to improve environmental sustainability, guarantee the economical use of natural resources, and lessen the negative consequences of climate change [20]. The Kingdom’s Vision 2030 places a strong emphasis on environmental stewardship and sustainable development. Saudi Arabia can enhance its long-term economic and environmental resilience by addressing wind erosion and its aftermath, protecting its natural landscapes, promoting sustainable farming methods, and enhancing public health. Furthermore, managing wind erosion and dust deposition is critical considering the current trend of climate change, as it can help to facilitate the restoration of degraded areas and the reduction of greenhouse gas emissions from agricultural soil [21,22].

Understanding and measuring wind erosion is essential for gaining insights into its mechanisms, assessing its environmental impact, predicting its occurrence, and evaluating conservation practices [4]. Quantifying soil loss due to wind erosion requires sophisticated methods that integrate field observations, remote-sensing data, and computational algorithms [4,23]. Techniques like the Revised Wind Erosion Equation (RWEQ) and remote-sensing technology allow researchers to assess erosion rates, sediment transport, and deposition patterns at various spatial and temporal scales [23,24,25]. Accurate quantitative estimation of soil loss is crucial for accurate land management decisions, prioritizing conservation efforts, and assessing erosion control measures [26].

Understanding the qualitative impacts of wind erosion is equally important. Wind erosion selectively removes finer soil particles, organic matter, and nutrients, altering soil properties and fertility [27]. This loss compromises soil quality by reducing its water-holding capacity, nutrient retention, and overall productivity [28]. Moreover, falling dust plays a pivotal role in transferring nutrients and contaminants across regions, shaping ecosystem dynamics and human health [29,30].

Recognizing the global significance of soil erosion and dust deposition, international organizations like the United Nations Convention to Combat Desertification (UNCCD) have established critical limits and standards to guide soil conservation efforts [31]. These standards set thresholds for soil erosion rates, soil organic carbon content, and air quality parameters to safeguard soil quality and ecosystem integrity [32]. Compliance with these internationally permissible critical limits is essential for maintaining sustainable land-use practices and mitigating the adverse effects of soil loss on ecosystems and human well-being.

Managing wind erosion of surface soils and the resulting dust generation in KSA drylands presents a significant challenge due to the complex interactions among various driving forces (e.g., economics and policy), pressures (e.g., weather, climate, fire, and land use), and ecosystem states (e.g., topography, vegetation, and soil conditions), which complicate effective mitigation efforts [27]. Effective mitigation of soil loss due to wind erosion and falling dust requires the implementation of several soil conservation strategies, such as afforestation, contour plowing, cover cropping, and windbreak establishment. These strategies stabilize soil surfaces, enhance soil structure, and promote vegetation cover [33,34]. Collaboration among policymakers, land managers, researchers, and local communities is crucial for addressing the root causes of erosion and fostering sustainable land management practices in KSA. The objective of this study was to evaluate soil loss resulting from wind erosion and dust deposition in the Al-Baha region of Saudi Arabia and explore its implications for sustainable soil management. By quantifying the extent of these processes and their impact on soil quality, the study aims to develop targeted strategies to mitigate soil loss. Additionally, the research seeks to link these findings with global environmental frameworks, providing actionable insights to enhance soil conservation efforts on a regional and global scale.

The novelty of this work lies in its comprehensive evaluation of the dual impact of wind erosion and dust deposition on soil quality, with a specific focus on sustainable land management practices. Additionally, this study contributes to the field by offering new insights into how these findings can support international compliance with environmental standards and guide global sustainable agriculture policies, an area that has not been extensively covered in previous studies. Specifically, the research offers new insights into mitigating the negative effects of soil loss, with practical implications for policy development and global sustainable agriculture initiatives.

2. Materials and Methods

2.1. Description of the Study Area

The study was conducted in the Al-Baha region, located in the southwestern part of Saudi Arabia within the Sarawat Mountains (20°00′45″ N, 41°27′55″ E). The region covers approximately 11,000 km² and features varied topography, including the Tihama plains, highlands of the Sarawat Mountains, and the eastern mountains and plateaus. The Al-Baha region is bordered to the north and west by the administrative boundaries of the Makkah Al-Mukarramah region, and to the south and east by the administrative boundaries of the Asir region (Figure 1). These jurisdictional boundaries are provided to give readers a clear understanding of the study area’s geographic context and its administrative divisions, which influence land-use patterns, resource management, and the implementation of regional environmental policies.

Geologically, Al-Baha is part of the Arabian Shield, which is characterized by widespread igneous and metamorphic rocks. The Arabian Shield comprises a crystalline basement overlaid by basalts, forming the Precambrian continental crust [35]. The region’s predominant weathering conditions, influenced by the geological composition, include both mechanical and chemical weathering processes, which contribute to the development of the regolith. The availability of soil particles for erosion and wind transport is highly dependent on the lithological variability across the area, which influences the texture and stability of the soils in different locations. Figure 2 shows a geological map of the Al-Baha region as part of the KSA to provide a clearer representation of the geological domains and their extent within the study area.

The area’s vegetation is influenced by rainfall and elevation, with dense cover in the highlands and sparse vegetation in the eastern regions. The Tihama plains experience a hot, dry climate, with more moderate conditions in the highlands during summer and cooler temperatures in winter. The wind speed averages higher in summer, particularly in July, with predominant northwesterly winds.

The region’s climate is influenced by its elevation, with mean daily temperatures around 20 °C, and extremes ranging from 13 °C to 39 °C. According to the Köppen–Geiger climate classification, Al-Baha falls under the semi-arid climate (BSh) category, characterized by hot summers and mild winters. The area receives an average annual precipitation of approximately 100–250 mm, with most rainfall occurring during the spring and summer months, primarily due to orographic lifting caused by the surrounding mountains. These climatic conditions contribute to the vulnerability of the region to soil erosion and dust deposition, particularly during the dry season.

2.2. Collection of Dust and Soil Samples

The collection of dust sampling was conducted at 20 sites across the Al-Baha region (Figure 3), during the summer season in 2022, with nine sites in the Tihama plains, eight in the Sarawat highlands, and three in the eastern mountains. Dust samples were collected using three different methods (Figure 4): Big Spring Number Eight (BSNE) Dust Collectors, Surface Dust Collectors (SDCs), and Marble Dust Collectors (MDCOs).

Big Spring Number Eight (BSNE) Dust Collectors are designed to monitor wind erosion by capturing dust at various heights (25, 50, 75, and 100 cm) above the soil surface, providing a comprehensive understanding of vertical dust distribution in the atmosphere. Studies such as those by Goossens and Buck [36] have demonstrated the BSNE’s effectiveness in quantifying airborne dust and monitoring wind erosion patterns in arid environments. Surface Dust Collectors (SDCs) focus on capturing surface dust directly affected by wind erosion. Positioned close to the ground, they assess the immediate impact of wind-driven dust on the soil surface. Their reliability in estimating surface-level dust deposition has been validated in studies like those by Goossens and Buck [36]. Marble Dust Collectors (MDCOs) utilize a methodology based on Mamadou et al. [37]. These collectors target deposited dust (falling dust) using rectangular trays fitted with a marble filter, providing precise measurements of dust accumulation on the soil surface. Prior research highlights their utility in quantifying settled dust in areas with variable deposition rates [14,36,37].

In this study, 20 BSNE devices were installed at different locations across the study area to monitor wind erosion, and the SDC and MDCO devices were co-located at the same 20 sites to complement the data collection. The proximity of the different devices at each location was within 5–10 m, ensuring consistent comparative data across methodologies.

In addition, soil samples were collected from 40 locations, at a depth of 0–30 cm around the locations of the dust collectors (2 soil samples per site). The sampling locations were selected using a systematic sampling approach to ensure a representative distribution across the study area, with consideration for accessibility and potential environmental variations. The samples were packed in airtight bags for laboratory analysis. The study area was classified according to its topographic distributions, water flow, height from sea, and soil types. Soil loss was further quantified in relation to dust mass collected in dust collectors, and soil samples were analyzed for their physiochemical characteristics to determine the possible impact of wind erosion and dust deposition.

2.3. Climatic Conditions in the Study Area

Historical climatic data were collected for the study area over the past 20 years (2002–2022), as sourced from the National Center for Meteorology (NCM) in Saudi Arabia (https://ncm.gov.sa/ar/Pages/default.aspx, accessed on 10 November 2024). The collected data included air temperature, humidity, wind speed, precipitation, and solar radiation. The data were analyzed to obtain averages of the entire period, and the averages were compared to a comprehensive overview of climatic parameters across the different locations (S1 to S20) in the study area that were recorded during the months of June, July, and August 2022. The climatic data collected during the summer of 2022 were consistent with the average climatic parameters recorded over the past 20 years in the Al-Baha region. However, it is important to note that there may have been variations in these meteorological parameters over time that could influence the current conditions.

A detailed analysis of meteorological parameters revealed important variations that influence soil erosion and deposition. Most locations exhibited a noticeable increase in humidity from June to August. Wind speeds remained relatively consistent across most sites, averaging between 2.8 and 3.4 m s⁻¹, with a slight decline from June to August. This consistency in wind speed is critical for understanding the dynamics of soil erosion, as stable wind conditions can result in predictable patterns of dust deposition and soil loss. Precipitation varied significantly across the study sites. While some locations, such as S1, recorded low precipitation in June (0.7 mm) and July (0.1 mm), August experienced a marked increase (5.2 mm). This rise in precipitation during August plays a crucial role in soil moisture accumulation, potentially mitigating some of the effects of wind erosion during this period.

2.4. Characterization of Collected Dust and Soil Samples

All the collected soil samples were analyzed for their physiochemical characteristics. Initially, soil samples were air-dried, passed through sieve of 2 mm, and stored in airtight plastic containers. Soil pH, electrical conductivity (EC), and soluble cations and anions were analyzed in soil suspension at 1:2 (w/v ratio) by following the standard procedures [38]. EC and pH were analyzed by EC (YSI Model 35, YSI Inc., Yellow Springs, OH, USA) and pH (WTW-pH-523, WTW GmbH, Troistedt, Germany) meters, respectively. Soluble cations and anions were analyzed by titration, while sodium and potassium were determined by using a flame photometer (Model: AE-EP8501, A and E Lab (UK) Co., Ltd., London, UK). The Walkley and Black [39] method was followed to determine the content of organic matter of soil samples. Soil samples were analyzed by X-ray diffractometer (MAXima X XRD-7000, Shimadzu Corporation, Kyoto, Japan) to observe the mineralogical composition. The mineralogical composition of the dust samples was determined using X-ray diffractometer (MAXima X XRD-7000, Shimadzu, Kyoto, Japan). The dust samples were also weighed to assess the deposition over time.

2.5. Estimation of Wind Erosion and Dust Deposition

Wind erosion was evaluated by collecting soil drift samples using the BSNE device, which captures soil particles at different heights. The exponential equation was applied to calculate soil loss from dust traps (Q_salt) [40]. The exponential equation is presented as Y = c·e^dx, where Y is the amount of soil loss obtained through dust traps at each height (g cm⁻²). For each period of the study, the value of c·e^dx was integrated between a height of 0 and 0.2 m as follows:

$${\mathrm{Q}}_{\mathrm{salt}}={\int }_{0.0}^{0.2}c·e^{dx}$$

(1)

which can be solved mathematically as follows:

$${\mathrm{Q}}_{\mathrm{salt}. (\mathrm{g} {\mathrm{cm}}^{-1} \mathrm{width})=[{\displaystyle \frac{c}{d}}\mathrm{EXP} (0.2 \mathrm{d}) - 1)] 100}$$

(2)

where c and d are fitting parameters for the exponential equation.

Similarly, the exponential equation (Y = a·x^b), where a and b are the statistical recoil constants that will be used to calculate the amount transported by suspension (Q_suspension) through the mathematical integration of the exponential equation a·x^b between 0.2 and 2 m high, is as follows:

$${\mathrm{Q}}_{\mathrm{suspension}}={\int }_{0.2}^{2.0}a·x^b$$

(3)

which can be solved mathematically as follows:

$${\mathrm{Q}}_{\mathrm{s}\mathrm{u}\mathrm{s}\mathrm{p}\mathrm{e}\mathrm{n}\mathrm{s}\mathrm{i}\mathrm{o}\mathrm{n} \left({\mathrm{g} \mathrm{c}\mathrm{m}}^{-1} \mathrm{w}\mathrm{i}\mathrm{d}\mathrm{t}\mathrm{h}\right) = \left[\frac{a}{b+1}\right({2.0}^{\left(\mathrm{b}+1\right)} - {0.2}^{(\mathrm{b}+1)}\left)\right] 100}$$

(4)

The values of soil loss, Q, resulting from the integration of the previous equations will be in grams per cm of width, from which soil loss will be calculated in kg per meter of width and tons per hectare per year. Additional analysis included particle size distribution using dry sieving and estimating soil loss in kilograms per meter and tons per hectare per year using regression analysis.

2.6. Sensitivity Analysis Using the Kriging Method and GIS

In the Al-Baha region, georeferenced data were gathered from 20 sites (S1 to S20). Wind speed, soil type, slope, surface roughness, and dust deposition rates (ton ha⁻¹) were among the variables. Spatial data on land-use practices; topographical features; and meteorological parameters, such as wind speed and precipitation, were combined with field data on wind erosion and dust deposition. We used Geographic Information Systems (GISs) and the Kriging interpolation method to evaluate the susceptibility of several sites in the Al-Baha region to wind erosion, wind surface disturbance, and dust deposition. We were able to map and examine spatial changes throughout the research region thanks to this methodology, which gave us insights into the environmental factors influencing soil stability.

Layered maps of the area were produced using GIS, showing the geographical distribution of dust deposition, wind surface disturbance, and wind erosion at each location. A complete spatial context was provided by each layer’s alignment with elevation, slope, and topographical-feature data. Digital Elevation Models (DEMs) obtained from satellite data were used to map topographical features like slope and elevation. This research assisted in identifying regions with steep slopes or high altitudes that are more vulnerable to wind erosion.

In unsampled areas, Kriging was used to forecast the sensitivity of wind erosion and dust deposition. This geostatistical method computes the spatial autocorrelation between neighboring points using known sample points (S1 to S20) to estimate values in surrounding areas. To carry out the Kriging analysis, several GIS modules were utilized, including ArcGIS Geostatistical Analyst. To determine which model best fits the data on the spatial distribution of dust and wind disturbances, we investigated a variety of models, including spherical and exponential ones. Cross-validation techniques were employed to validate the Kriging model and evaluate the precision of predicted values in comparison to observed values at sample points. Kriging produced continuous surfaces that showed different susceptibilities to dust deposition and wind erosion. These were plotted on maps to show the locations at high risk.

Based on the sites’ anticipated susceptibility to dust deposition and wind erosion, they were categorized into sensitivity zones. Elevated winds, little foliage cover, and steep inclines were used to identify high-sensitivity locations. High-, medium-, and low-sensitivity zones were clearly distributed spatially in the final sensitivity maps. This classification helps identify the most vulnerable locations and directs efforts toward sustainable land management and wind erosion reduction.

2.7. Statistical Analysis

Data analysis was performed using SPSS 2000 and STATGRAPHIC 2000 to determine correlations, regression relationships, and statistical constants. Variance analysis and spatial distribution assessments were conducted using satellite images and data from meteorological stations. The least significant difference (LSD) test at p < 0.05 was applied to evaluate significant differences among the different average values.

3. Results and Discussion

3.1. Variations in Climatic Conditions

A comprehensive overview of climatic parameters across different locations (S1 to S20) in the study area during the months of June, July, and August 2022 is presented in

Table 1. Climatic parameters across different locations (S1 to S20) during the months of June, July, and August, focusing on average humidity, wind speed, solar radiation, precipitation, and temperature.

Location	Height from Sea Level (m)	Average Humidity (g km−3)			Average Wind Speed (m s−1)			Average Solar Radiation (KJ M−2 day−1)			Average Precipitation (mm)			Temperature (°C)
		June	July	August	June	July	August	June	July	August	June	July	August	June	July	August
S1	170	3589	4382	5073	3.1	3.3	2.5	24,061	21,242	22,558	0.7	0.1	5.2	48.6	44.1	41.5
S2	350	3377	4289	5765	2.9	2.9	2.4	24,343	21,597	22,281	0.6	2.0	6.6	45.7	40.2	35.0
S3	1920	1327	2176	2018	2.9	2.8	2.4	23,642	21,615	22,504	0.4	1.6	7.1	39.7	35.8	29.7
S4	2060	1470	2017	1928	2.9	2.9	2.5	23,601	21,609	22,263	0.3	1.1	6.9	41.3	38.8	33.2
S5	1560	1640	2054	2205	3.0	3.0	2.7	23,692	21,955	22,630	0.3	1.0	6.8	45.7	44.9	37.3
S6	165	3791	4393	5424	3.1	3.1	2.7	24,429	21,747	22,942	0.6	1.1	5.7	47.4	43.3	42.0
S7	420	3090	3960	5267	2.9	3.1	2.6	24,419	22,397	22,844	0.6	1.3	6.4	42.7	37.3	33.5
S8	1950	1415	2384	2091	2.8	2.8	2.3	23,584	21,507	22,185	0.5	1.2	6.8	42.7	37.3	33.5
S9	2080	1479	1979	1744	2.9	2.9	2.3	23,495	21,321	22,277	0.4	1.2	6.8	44.7	42.7	36.3
S10	1760	1545	1978	1716	2.9	2.8	2.3	23,504	21,560	22,409	0.5	1.2	6.4	42.6	40.4	35.0
S11	115	4179	4759	4928	3.0	3.2	2.6	23,761	21,119	21,995	0.7	0.8	5.5	50.3	44.4	43.5
S12	770	2552	3699	3558	3.0	3.1	2.6	24,261	22,646	23,085	0.6	1.3	6.4	41.9	34.9	31.3
S13	1550	1762	2841	2558	3.0	3.1	2.6	23,879	21,944	22,420	0.6	1.4	6.3	43.5	36.6	33.5
S14	2050	1512	1793	1558	3.0	2.9	2.4	23,365	21,386	21,961	0.6	1.2	6.9	40.3	38.5	32.1
S15	1550	1763	1928	1769	3.2	3.2	2.6	23,541	21,529	22,402	0.5	1.1	7.1	47.9	46.5	41.7
S16	820	2489	3693	4341	3.0	3.1	2.6	23,833	21,903	22,448	0.7	1.1	6.8	42.4	37.2	33.2
S17	380	2761	4373	4723	2.9	3.1	2.6	24,189	22,246	22,679	0.7	1.2	6.6	43.2	36.7	34.0
S18	2085	1494	2405	2875	2.9	2.9	2.5	23,204	21,234	21,671	0.8	1.1	8.7	39.2	37.3	31.7
S19	1955	1517	2621	2164	2.9	2.9	2.5	23,271	21,269	21,760	0.9	1.1	8.9	40.2	39.2	32.8
S20	1320	2183	1963	1685	3.0	3.4	2.7	23,480	21,481	22,288	0.3	0.6	6.0	51.1	48.8	43.7

. Most locations show a noticeable increase in humidity from June to August. For example, at S1, humidity rises from 3589 g km⁻³ in June to 5073 g km⁻³ in August. Some locations, like S6 and S7, exhibit exceptionally high humidity levels, particularly in July and August, suggesting that these areas might be more prone to moisture retention or may have more vegetation or water bodies influencing local humidity.

Across the locations, wind speeds are relatively consistent, with most locations averaging between 2.8 and 3.4 s m⁻¹. There is a slight decline in wind speed from June to August at several locations, such as S1, where it drops from 3.1 s m⁻¹ in June to 2.5 s m⁻¹ in August. This stability in wind speed is important for understanding soil erosion dynamics, as consistent wind conditions can lead to predictable patterns of dust deposition and erosion. June generally has the highest solar radiation across most locations. For instance, S1 records 24,061 KJ M⁻¹ in June, decreasing to 21,242 KJ M⁻¹ in July. There is a gradual decline in solar radiation from June to July across almost all locations, which might be due to seasonal changes, such as increased cloud cover or the sun’s position during the summer months. The results of our study align with previous findings, such as those documented in [41]. Seasonal variables, such as increased cloud cover or the sun’s shifting position throughout the summer, which affects the intensity of solar energy reaching the surface, are probably to blame for this drop in solar radiation. The parallels between our findings and those reported in [41] support the validity of these trends and imply that the conclusions may be applied more broadly to areas with comparable climates. These insights are critical for agricultural and environmental planning that depends on seasonal patterns of solar radiation, as well as for improving solar energy harvesting.

Precipitation levels vary widely across the locations. Some locations, such as S1, experience very low precipitation in June (0.7 mm) and July (0.1 mm), followed by a significant increase in August (5.2 mm). Generally, August sees the highest levels of precipitation, with several locations recording more than 5 mm, indicating that this month is critical for moisture accumulation in the soil, which could mitigate some wind erosion effects. The data indicate a strong interplay between humidity, wind speed, solar radiation, and precipitation across the different locations. The increase in humidity and precipitation toward August might contribute to a reduction in dust emission and soil erosion. The steady wind speeds and high solar radiation in June are likely to exacerbate dust deposition, especially in drier and less vegetated areas. Understanding these trends is crucial for environmental management and for developing strategies to mitigate soil losses due to wind erosion in the context of climate change.

3.2. Extent of Dust Accumulation and Soil Loss

3.2.1. Extent of Dust Accumulation

Dust samples were collected using various dust collectors across different study areas at specific intervals during the summer season. The quantity of dust collected varied significantly based on the method and timing. The highest dust deposition was recorded using the Multi-Directional Collection Option (MDCO), followed by the Surface Dust Collector (SDC) and Big Spring Number Eight (BSNE).

Table 2. Average values of collection of dust by variable dust collector at variable time intervals.

Sites	Wind Erosion (ton ha−1)	Wind Surface (ton ha−1)	Dust Deposition (ton ha−1)
S1	0.00308 AB	0.00531 ABC	0.00949 B
S2	0.00268 BCD	0.00441 BCD	0.00803 BCDE
S3	0.00219 BCDE	0.00358 CD	0.00644 DE
S4	0.00205 CDE	0.00342 CD	0.00588 E
S5	0.00168 E	0.00314 D	0.00585 E
S6	0.00311 AB	0.00515 AB	0.00955 B
S7	0.00225 BCDE	0.00418 BCD	0.00803 BCDE
S8	0.00198 CDE	0.00333 CD	0.00617 DE
S9	0.00181 DE	0.00335 CD	0.00617 DE
S10	0.00178 DE	0.00343 CD	0.00602 E
S11	0.00363 A	0.00608 A	0.01327 A
S12	0.00272 AB	0.00444 BCD	0.00802 BCDE
S13	0.00262 BCD	0.00425 BCD	0.00764 BCDE
S14	0.00237 BCDE	0.00372 CD	0.00737 BCDE
S15	0.00231 BCDE	0.00363 CD	0.00706 CDE
S16	0.00272 ABC	0.00435 BCD	0.00838 BCD
S17	0.00290 ABC	0.00452 BC	0.00873 BC
S18	0.00224 BCDE	0.00367 CD	0.00733 BCDE
S19	0.00220 BCDE	0.00355 CD	0.00677 CDE
S20	0.00211 CDE	0.00369 CD	0.00739 BCDE

Different superscript letters indicate significant differences among different average values of study location (S) down the table according to the least significant difference (LSD) test at p < 0.05.

and Figure 5 show that the highest average dust quantity (0.0133 tons ha⁻¹) was collected from S11 using the BSNE, while the lowest was from S5 (0.0058 tons ha⁻¹). Dust deposits peaked between 10 and 30 July, likely due to increased wind activity and the geographical positioning of the sites. Areas with higher wind erosion, such as S11, exhibited greater dust accumulation due to their topographic and climatic conditions. These findings are comparable with the results reported by [42], where areas with higher wind erosion showed increased dust accumulation, likely due to the region’s topographic and climatic conditions.

This variation highlights the influence of the collection method on the efficiency of dust capture, with MDCO proving most effective due to its low micro-roughness and high particle capture rate. These findings align with the results of [14], where the MDCO method demonstrated superior efficiency in capturing dust particles due to its low micro-roughness and high particle capture rate. This supports the conclusion that the MDCO method is highly effective in regions with significant wind activity. The higher dust collection observed from the SDC compared to the BSNE can be attributed to the SDC’s larger dimensions and its proximity to the dust source. The differences in dust deposition were attributed to factors such as the source of dust; particle size; and topographical features, like slope and soil type. The proximity of the Surface Dust Collector (SDC) to the dust source played a significant role in the results. Sodic soils, known for their poor structure and high erosion susceptibility, showed higher dust accumulation. The SDC collected nearly twice as much dust as the BSNE, indicating its greater efficiency in capturing surface dust. The higher dust collection observed from the SDC compared to the BSNE also can be attributed to the SDC’s larger dimensions and its proximity to the dust source.

3.2.2. Soil Loss Analysis

The amount of soil loss followed the order of dust deposition > wind surface > wind erosion for all the studied sites (Figure 5 and Table 2). This could be due to the high velocity with which the wind blew over the surface of the land, depositing a large number of particles that had been eroded from the area. Significantly, the highest amount of soil loss due to wind erosion was recorded in S11, while the lowest was recorded in S5. The sequence of soil loss due to wind erosion across all sites is as follows: S11 > S6 > S1 > S17 > S12 > S2 > S16 > S13 > S14 > S15 > S7 > S18 > S19 > S3 > S20 > S4 > S8 > S9 > S10 > S5. The details of soil loss at each site are clearly illustrated in Figure 5 and Table 2 to give a better understanding. This distribution indicates that certain sites are more susceptible to erosion, which could be influenced by factors such as soil type, vegetation cover, and topographical features. Further analysis of these factors could provide valuable insights into the underlying causes of soil erosion in the Al-Baha region.

The findings of our study are consistent with previous research on wind erosion and its related effects. This pattern can be attributed to the high wind velocity across the surface of the land, which deposits a substantial number of eroded particles. Similar observations have been documented by Guo et al. [2], who highlighted how wind erosion in Northern China leads to significant soil degradation, exacerbated by strong winds that carry eroded soil particles over long distances. Moreover, research by Chappell and Baldock [21] also points to the substantial role that wind plays in redistributing soil and organic matter, especially in arid and semi-arid regions, further corroborating our findings on the role of wind velocity in enhancing dust deposition. Similarly, Rezaei et al. [3] studied the transport of microplastics by wind erosion in semi-arid agricultural soils, noting the powerful influence of wind on particle movement, which parallels our results showing dust deposition as a dominant factor in soil loss.

Similarly, in the S11 study site, a significantly higher amount of soil loss due to wind surface was recorded when compared to other study sites, with the lowest recorded in S5. The order of soil loss due to wind surface followed a similar pattern: S11 > S1 > S6 > S17 > S12 > S2 > S16 > S13 > S7 > S14 > S20 > S18 > S15 > S3 > S19 > S10 > S4 > S9 > S8 > S5. The concentration of soil loss due to dust deposition was also highest in S11 and lowest in S5. The dust deposited in the study sites followed the pattern of S11 > S6 > S1 > S17 > S16 > S7 > S2 > S12 > S13 > S20 > S14 > S18 > S15 > S19 > S3 > S8 = S9 > S10 > S4 > S5.

3.2.3. Temporal and Spatial Variation

The order of abundance in soil loss varied among study sites, with some sites demonstrating consistency in their patterns, while others exhibited significant differences based on the methods used (wind erosion, wind surface, and dust deposition). For the sites S1, S2, S3, S4, S5, S6, S8, S11, S15, S16, S17, S18, and S19, the highest soil loss was recorded on 20 July 2022, while the lowest was observed on 30 August 2022. In contrast, site S9 displayed a different trend: for wind erosion, the highest soil loss occurred on 10 July 2022, and the lowest on 30 August 2022. For wind surface, the highest and lowest amounts were recorded on 20 July 2022, and 30 August 2022, respectively. For dust deposition, the highest and lowest were also recorded on 10 July 2022, and 30 August 2022, respectively. This reorganization of the results allows for a clearer comparison across methods and sites.

This variability can be explained by the interplay of local environmental conditions, such as soil texture, topography, and vegetation cover, which affect the efficiency of each method in capturing soil movement. Uniform wind speeds, land-use practices, or soil composition likely had an impact on the processes causing soil loss at sites where patterns were consistent, whether through wind erosion, surface wind impacts, or dust deposition. These factors led to predictable results. On the other hand, locations exhibiting notable disparities could have been impacted by diverse microclimatic circumstances or anthropogenic actions that shaped the amount of soil lost, moved, or deposited. These variations highlight the value of employing a variety of techniques to gain a thorough understanding of wind-induced soil loss, since a single technique might not fully capture the scope of erosion processes at various sites. These observations align with studies such as those by Chi et al. [9] and Jarrah et al. [4], which highlight the complexity of wind erosion processes and how environmental factors and land-use changes influence soil loss patterns across regions.

In S12, S14, and S20, the highest and lowest soil loss for wind erosion and wind surface were recorded on 20 July 2022, and 30 August 2022, while for dust deposition, different dates were recorded: 20 July 2022, and 15 July 2022. In S9, the highest soil loss due to wind erosion and dust deposition occurred on 10 July 2022, and the lowest on 30 August 2022, while for wind surface, the highest loss occurred on 20 July 2022, and the lowest on 30 August 2022.

3.2.4. Implications of Dust Accumulation

Aeolian dust is of critical importance due to its impact on climate change, the environment, and ecosystems [43,44]. Dust storms and dust accumulation are major phenomena in arid regions, such as Saudi Arabia. Therefore, exploring the dust accumulation rates and fluxes is important to avoid its adverse impacts. Arid climate, atmospheric circulation, and human activities have been considered the major factors for dust emissions [45]. Dust storms and accumulation are significant concerns, impacting climate, environment, and ecosystem health. Our analysis of dust storms in Al-Baha demonstrated significant variation in dust accumulation across different sites and collection methods. The highest dust deposition was observed using the Marble Dust Collector (MDCO), followed by the Surface Dust Collector (SDC) and the Big Spring Number Eight (BSNE). In this study, soil loss related to wind erosion, wind surface erosion, and dust deposition followed a similar pattern. Notably, S11 exhibited the highest soil loss due to both wind erosion and dust deposition.

The term “wind erosion” refers to the process by which soil particles are detached and lifted away by wind, while “wind surface erosion” specifically refers to the loss of soil material that occurs at the surface level due to wind action. The order of soil loss due to these processes was generally highest at S11, followed by S6, S1, and S17. This pattern underscores the impact of high wind speeds and soil susceptibility to erosion on dust accumulation and soil degradation. This pattern is consistent with the findings of Wu et al. [46], where soil loss was also highest in areas with significant wind activity and susceptible soils. This highlights the combined influence of high wind speeds and soil vulnerability to erosion that contributes to increased dust accumulation and soil degradation, mirroring the observations reported in [46].

3.3. Chemical Properties of Dust and Soil Samples

Collected soil samples were further analyzed for their chemical properties and textural class, as shown in

Table 3. The physiochemical properties of the collected soil samples.

Site	pH	EC (dSm−1)	Cations and Anions (meq kg−1)							CaCO3 (%)	OM (%)	Textural Class
			K+	Na+	Ca2+	Mg2+	HCO3−	Cl−	SO42−
S1	7.55 bcd	10.67 a	1.85 c	165.98 a	19.68 b	3.70 cde	1.89 gh	211.56 a	8.17 cd	5.66 f	0.61 cdefg	LS
S2	7.65 abc	0.97 e	0.45 hijk	4.99 cde	21.62 b	3.44 cdef	3.00 c	6.67 ghi	5.17 ef	13.58 bc	0.85 ab	LS
S3	7.58 bc	4.44 c	1.07 e	20.42 cd	37.34 a	1.95 fg	2.56 e	63.25 cd	14.09 a	19.31 a	0.82 abc	SL
S4	7.38 d	1.10 e	0.85 f	7.21 cde	7.03 c	6.16 b	2.22 f	15.22 fg	4.25 ef	9.58 de	0.94 a	SL
S5	7.53 cd	0.99 e	2.06 b	2.54 e	6.76 c	8.39 a	2.03 fg	3.60 i	6.86 cde	13.39 bc	0.87 ab	SL
S6	7.65 abc	0.38 e	0.74 fg	2.33 e	4.32 c	1.31 g	1.88 gh	3.38 i	1.81 gh	5.55 f	0.74 abcde	SiL
S7	7.74 ab	0.64 e	0.28 klm	4.27 de	4.24 c	3.80 cd	2.19 f	14.50 gh	0.61 h	7.00 ef	0.59 dfgh	SL
S8	7.79 a	1.05 e	1.21 de	6.80 cde	4.94 c	6.23 b	2.78 d	25.81 ef	1.24 gh	17.71 a	0.71 bcde	SiL
S9	7.64 abc	0.23 e	0.37 ijkl	1.89 e	3.07 c	1.09 g	2.50 e	0.77 e	1.29 gh	5.70 f	0.72 bcde	SL
S10	7.65 abc	0.35 e	1.27 d	1.38 e	4.76 c	1.69 g	3.41 a	1.59 e	1.50 gh	11.05 cd	0.80 abcd	LS
S11	7.76 a	0.26 e	0.73 fg	1.88 e	3.25 c	0.84 g	1.81 h	2.86 e	0.82 h	6.06 ef	0.45 gh	SL
S12	7.63 abc	0.36 e	0.21 lm	2.45 e	5.54 c	1.71 g	2.84 cd	1.13 i	1.63 gh	7.47 ef	0.79 abcd	SiL
S13	7.68 abc	2.53 d	0.59 gh	18.57 cd	16.37 b	2.08 fg	2.05 fg	69.69 c	8.50 bc	19.62 a	0.43 gh	SiL
S14	7.66 abc	0.75 e	0.70 fg	5.44 cde	5.01 c	4.44 c	3.27 b	4.39 h	4.15 efg	13.61 bc	0.43 gh	LS
S15	7.68 abc	0.5 e	0.17 mn	2.74 e	4.00 c	1.91 fg	1.56 h	55.91 d	4.92 ef	14.71 b	0.83 ab	SiL
S16	7.74 ab	0.45 e	0.77 f	5.10 cde	5.22 c	1.43 g	2.19 f	3.39 i	2.89 fgh	6.71 ef	0.39 h	S
S17	7.68 abc	0.92 e	0.21 lm	8.69 cde	4.75 c	6.16 b	2.09 fg	26.28 e	0.37 h	12.33 bc	0.54 efgh	SL
S18	7.62 abc	7.78 b	2.28 a	96.66 b	20.11 b	7.78 a	1.91 gh	106.94 b	11.45 ab	11.36 bcd	0.49 fgh	SL
S19	7.76 ac	0.92 e	0.02 n	14.44 cde	5.94 c	2.21 efg	0.91 i	10.84 gh	5.29 de	6.98 ef	0.59 defgh	SL
S20	7.52 bcd	0.46 e	0.30 jklm	0.97 e	3.79 c	2.68 defg	2.94 cd	1.80 i	2.50 fgh	11.80 bcd	0.70 bcdef	SL
LSD	0.19	0.46	0.17	15.65	5.55	1.54	0.21	10.75	2.99	3.56	0.21	-

OM, organic matter; texture class (LS, loamy sand; SL, sandy loam; SiL, silt loam; S, sand). Different superscript letters indicate significant differences among different means across the study locations according to the least significant difference (LSD) test at p < 0.05.

. The findings confirm that the soil across the study areas is slightly alkaline, with a mean pH range of 7.38–7.79. This pH range is similar to the results discussed by Geilfus [47], who highlighted the influence of such alkaline conditions on metal dynamics and adsorption processes. These slightly alkaline soils can affect the availability and mobility of metals, making up an important factor in understanding soil chemistry and its implications for environmental sustainability. The mean pH values suggest that the soil across the study areas is slightly alkaline. This information is important, as it relates to the soil’s suitability for agricultural practices and its capacity to retain nutrients.

The highest pH was recorded at site S8 (7.79), followed by sites S11 (7.76) and S19 (7.76), while the lowest pH was observed at site S4 (7.38). The slightly alkaline pH range of 7.38–7.79 can influence metal dynamics and adsorption, which is crucial for understanding soil quality. Specifically, when soil pH is within this range, it can affect the availability and mobility of various metals, potentially leading to several risks. (1) Metal availability: An alkaline pH can lead to the immobilization of certain heavy metals, reducing their bioavailability to plants. However, it may also facilitate the release of other metals that are more soluble at higher pH levels, leading to potential toxicity, particularly at Sites S8 and S11, where the highest pH values were recorded. (2) Adsorption capacity: The pH affects the adsorption capacity of soil minerals for heavy metals. Changes in pH can alter the surface charge of soil particles, impacting the adsorption of metals and, consequently, their transport in the soil profile. Sites like S4, with a lower pH of 7.38, may experience more dynamic metal movement compared to higher-pH sites like S8 and S11. (3) Environmental contamination: Elevated levels of heavy metals in the soil can pose risks to plant growth and soil organisms, and the heavy metals can ultimately enter the food chain, affecting human health and the ecosystem. Sites with higher pH levels, such as S8 and S11, might face challenges related to metal toxicity, impacting plant growth, soil organisms, and the broader ecosystem. (4) Soil quality: The dynamics of metal adsorption can also influence overall soil quality, affecting fertility and productivity. High concentrations of certain metals can lead to soil loss, limiting agricultural output. Managing the pH and metal dynamics, particularly at sites with higher pH values, like S8 and S11, is essential for promoting sustainable land management practices that align with Saudi Arabia’s Vision 2030 and the Sustainable Development Goals (SDGs). Considering these factors, understanding the pH’s role in metal dynamics and adsorption is essential for assessing soil quality and implementing effective soil management practices.

The electrical conductivity (EC) of the soil samples varied widely, with a minimum value of 0.23 dS m⁻¹ and a maximum of 10.67 dS m⁻¹. This variation in EC suggests that soluble salts have accumulated, indicating severe soil salinization. Notably, sites such as S1, S3, and S18 exhibited high EC values, which reflect the accumulation of soluble salts. While the overall EC for most sites was within the normal range (below 2.00 dS m⁻¹), as reported by Smith and Doran [48], several sites exhibited EC values that exceeded this threshold. For example, sites S1 (10.67 dS m⁻¹), S3 (4.44 dS m⁻¹), S13 (2.53 dS m⁻¹), and S18 (7.78 dS m⁻¹) showed signs of mild-to-severe soil salinity, indicating compromised soil quality. These high EC levels are likely due to factors such as anthropogenic (human) activities and water flow, as noted by Smith and Doran [48]. Human activities such as intensive agriculture, industrial discharges, and urban development contribute significantly to soil salinization. Practices such as over-irrigation and the use of saline water for irrigation can lead to the accumulation of salts in the soil.

The EC values in these sites surpass the acceptable limit of 2 dS m⁻¹ for most soil types, suggesting potential adverse effects on soil quality and fertility (Table 3). The wide range of EC values indicates varying levels of salinization across the sites. We have discussed the implications of high EC levels on soil quality and crop productivity, particularly in sites such as S1, S3, and S18.

The concentrations of cations and anions have been examined to highlight their roles in soil fertility and potential environmental risks, particularly in relation to sodicity. The concentration of sodium (Na⁺) was particularly high in sites S1, S18, and S3, indicating high sodicity and poor soil structure in these areas. These findings align with the classification of many study sites as sodic soils, characterized by high concentrations of Na⁺ ions. The presence of high sodium levels further corroborates the issues of soil permeability and fertility in these areas. High sodium content is commonly linked to reduced soil permeability and fertility, a relationship also emphasized by Geilfus [47]. In soils with elevated sodium levels, such as those observed in this study, these effects can hinder water infiltration and root growth, ultimately compromising soil health and agricultural productivity.

Additionally, chloride (Cl⁻) concentrations showed significant variability across the sites, with S1 exhibiting the highest levels. This suggests severe contamination that could negatively impact soil quality and agricultural productivity.

3.4. Mineralogical Properties of Dust and Soil

The mineralogical composition of the collected soil and dust samples was analyzed using X-ray diffraction (XRD, MAXima_X XRD-7000, Shimadzu, Japan). The XRD analysis of the soil samples revealed that quartz (with peaks at 3.17 Å–3.34 Å) and calcite (with peaks at 1.34 Å–2.70 Å) were the dominant minerals present. This mineral composition suggests a strong influence of dust deposition on the soil surface, alongside natural weathering of rocks and surface soils in the vicinity of the study sites [49]. The accumulation of quartz and calcite can be attributed to these processes, with quartz serving as a key indicator of dust accumulation, as highlighted by Menéndez et al. [50]. These findings align with the notion that dust deposition plays a crucial role in shaping the mineralogical composition of soils in arid regions.

Similarly, the mineralogical analysis of the collected dust samples, also performed using XRD, confirmed that quartz and calcite were the most prevalent minerals. The XRD patterns, illustrated in Figure 6, displayed peaks at 3.33–3.71 Å for quartz and at 2.94 Å for calcite, further supporting the dominance of these minerals in the dust samples. The high concentration of quartz in both dust and soil samples aligns with the findings of Prakash et al. [49], emphasizing quartz as a reliable marker for dust deposition.

The presence of these minerals, particularly quartz, underscores the significant impact of dust deposition on soil mineralogy in the study area. This is consistent with the observed mineralogical patterns, where dust deposition, combined with natural weathering processes, has led to the accumulation of quartz and calcite in the soil. For instance, at site S11, which recorded the highest dust deposition, quartz levels were notably elevated, illustrating the direct relationship between dust accumulation and soil composition. Similarly, sites S6 and S9, which also experienced considerable dust deposition, displayed mineralogical patterns consistent with the accumulation of both quartz and calcite, driven by natural weathering processes. The findings from the XRD analysis provide clear evidence of the mineralogy alterations in the soil due to dust deposition, highlighting the interplay between dust accumulation and soil mineral composition.

3.5. Classification of Study Area

The study area exhibited significant elevation variation, which in turn affected the local climate and dust erosion patterns. The temperature ranges varied by site and height, with higher elevations generally experiencing cooler temperatures. The area’s topography included diverse slopes and soil types, such as leptosols, fulvisols, and calcisols, contributing to differing impacts of erosion and soil-formation processes. As indicated in Figure 2, the study area was thoroughly observed for its geological parameters. Site contours revealed an elevation range from a minimum of 300 m to a maximum of 2400 m. Figure 3 and Figure 7 show that the study area is uneven and has varied slopes, with degrees ranging from 0–5 m to 36–76 m. This variability in slope contributes to the complex dynamics of wind erosion, which is influenced by both elevation and slope. Soil-type data indicate leptosols as the dominant type of soils, followed by fulvisols and calcisols (Figure 7). Usually, such kinds of soils are distributed among mountains and desert areas with less soil formation. Such kinds of soils are prone to erosion depending on their topographic features and climate. These findings are similar to those reported by Silva et al. [51], who also observed that leptosols are prevalent in mountainous and desert areas, where limited soil formation increases their susceptibility to erosion. The occurrence of fulvisols and calcisols also indicates that soil in the study area is comparatively young, which indicates that these soils are likely to be affected by wind and water erosion and less influenced by weathering processes. Likewise, the occurrence of fulvisols and calcisols, which are indicative of relatively young soils, is comparable with the findings of Jones et al. [52], suggesting that such soils are more prone to erosion due to their limited weathering and low organic matter content.

3.6. Impacts of Falling Dust on Soil

Soil loss due to the falling dust for the studied sites is shown in Figure 8. Global warming and subsequent climate changes are contributing to consistent exposure of soil surface to many kinds of abiotic issues, such as wind erosion, dust storm, and water erosion, consequently resulting in soil deterioration and, in certain cases, complete soil loss. Soil loss is a common phenomenon resulting from wind erosion, dust storms, and dust emission that not only disturbs soil properties but also results in low soil fertility and, in some cases, the complete loss of arable land. These findings are consistent with previous studies that have reported significant nutrient loss, reduced soil organic carbon content, and overall poor soil fertility as consequences of dust storms and emissions [16,53,54].

Dust emission from dust storms not only affects soil biogeochemical properties but also impacts air quality due to airborne soil constituents. These findings are similar to those of previous studies [55], which also highlight the multifaceted effects of dust storms, emphasizing the necessity for effective management strategies to mitigate soil degradation while simultaneously protecting both soil and air quality. Addressing these interconnected issues is crucial for sustaining environmental health and ensuring the productivity of arable lands in affected regions.

Our findings showed that wind erosion and resultant soil emission and deposition severally deteriorated soil physiochemical properties (Table 3). Collected data from all studied sites regarding soil physiochemical properties indicated that dust deposited increased soil EC at a couple of sites, reaching a maximum of 10.67 and 7.78 dS m⁻¹ at sites S1 and S18, respectively, while no prominent effects were found on soil pH. Soluble cations were found in high quantities, especially Na⁺, which severally impacted soil properties and resulted in problems of soil sodicity in several sites. The highest contents of Na⁺ were found at S1 (165.98 meq kg⁻¹), S18 (96.96 meq kg⁻¹), and S3 (20.42 meq kg⁻¹), indicating a high accumulation of Na⁺ ions, ultimately resulting in poor soil structure and low infiltration [56]. The accumulation of Na⁺ ions through dust deposition could be due to anthropogenic activities within the vicinity of the studied areas and water flow and surface runoff. Similar to the higher accumulation of Na⁺, Cl⁻ ions were also found in higher concentrations at some studied sites. S1 was credited with the highest Cl⁻ accumulation (211.56 meq kg⁻¹), followed by S13 (69.96 meq kg⁻¹) and S3 (106.94 meq kg⁻¹).

These findings indicate severe contamination at these sites (S1, S3, and S13), likely attributed to local anthropogenic activities, leaching from natural sources, and dust deposition resulting from dust storms. Furthermore, the elevation data are relevant, as they highlight the topographical features that can affect water flow patterns, influencing runoff and the distribution of contaminants in the soil, while also impacting vegetation growth and public visibility in the affected areas. Overall, dust deposition contributes significantly to soil loss and environmental degradation in the studied regions, highlighting the need for effective management strategies to mitigate these impacts.

The results in Figure 8, which shows the quantity of dust collected (ton ha⁻¹) at various dates and locations (S1 to S20), illustrate the impact of wind erosion and dust deposition. The temporal variation perspective reveals an increase in dust deposition at most sites, such as S1, S2, S6, and S11, from June 20 to July 10. This rise may be attributed to seasonal variations or specific meteorological conditions that enhance soil particle movement. The peak dust deposition occurred between July 10 and July 20, with S11 recording the highest value (0.00616 tons ha⁻¹) on July 20, likely due to intense wind events or localized soil disturbances. This peak is consistent across most locations, though its magnitude varies. By July 30, the dust deposition notably decreased, indicating slower wind speeds, soil surface stabilization, or vegetation growth that reduced wind erosion. By the end of August, dust levels were minimal at all locations, ranging from 0.00058 to 0.00060 ton ha⁻¹ at S4 and S19. Additionally, Figure 7 provides information on wind erosion patterns over time by displaying the amount of wind surface (ton ha⁻¹) at different periods and places (S1 to S20). From June 20 to July 20, the data indicate an overall rise in the amount of wind surface at most places. S11 grew from 0.00635 to 0.00951 ton ha⁻¹, while S1 climbed from 0.00579 to 0.00823 ton ha⁻¹.

Spatially, sites like S11, S6, and S1 consistently showed higher dust displacement throughout the study period, likely due to factors such as soil composition, land use, or exposure to dominant wind patterns, making these areas more susceptible to wind erosion. In contrast, areas like S5, S9, and S10 often have lower dust accumulation, possibly due to more vegetation cover, less exposed soil, or lower wind speeds.

This analysis correlates with Table 1, which presents climatic parameters, such as humidity, wind speed, solar radiation, and precipitation. Locations with higher humidity, like S6 and S7, and relatively consistent wind speeds, such as S1, S2, and S6, align with the observed patterns of dust deposition and erosion. Humidity increased across most locations from June to August, with sites like S1 rising from 3589 g km⁻³ in June to 5073 g km⁻³ in August, potentially affecting dust movement. Wind speeds show a slight decline from June to August, particularly at S1, where it drops from 3.1 s m⁻¹ to 2.5 s m⁻¹. This stability or decline in wind speeds may contribute to the predictable patterns of dust deposition and reduced erosion by late August. Because the soil is more susceptible to wind erosion, this time frame probably correlates to a peak in wind erosion activity. This could be because of greater winds or decreased soil moisture. Most areas exhibit a decline in wind surface values after 20 July. S11, for instance, drops from 0.00951 ton ha⁻¹ to 0.00401 ton ha⁻¹ on 15 August. Changes in weather, such as lower wind speeds or higher humidity, which aids in soil consolidation, may be the cause of this drop.

However, S11 consistently showed the highest wind surface values across all dates, peaking at 0.00951 ton ha⁻¹ on 20 July. Similarly, S1 also showed high values, peaking at 0.00823 ton ha⁻¹. These locations may be more prone to wind erosion due to factors like loose soil, as indicated by measured sandy loam and loamy sand textures in S11 and S1, respectively (Table 3). Other factors may include lack of vegetation, or direct exposure to prevailing winds. Locations like S5, S9, and S10 generally exhibit lower wind surface values. For example, S5 peaked at 0.00537 ton ha⁻¹ on 20 July, which is relatively lower than the peaks at S11 and S1. These areas might have characteristics that protect against wind erosion, such as denser vegetation or soil types less susceptible to wind transport.

The quantity of dust collected (ton ha⁻¹) in relation to dust deposition over a range of dates and locations (S1 to S20) is shown in Figure 8. In most places, there is a general rise in dust deposition from 20 June to 20 July. S11 rises from 0.00930 to 0.01776 ton ha⁻¹, and S1 rises from 0.00890 to 0.01347 ton ha⁻¹. According to this pattern, there may be higher dust deposition in the mid-summer (late June to July) because of stronger winds, drier weather, or agricultural practices that expose more soil to wind erosion. Numerous places exhibit a decrease in dust deposition after 20 July. For instance, on 20 July, S1 falls to 0.01347 ton ha⁻¹, and on 30 August, it is reduced to 0.00494 ton ha⁻¹. Reductions in wind speeds or increases in humidity, which lessen the ability of winds to carry and deposit dust, could be linked to this drop in weather patterns. With the greatest dust deposition values, S11 stands out; on 10 July, it peaked at 0.02056 ton ha⁻¹, indicating a substantial vulnerability to dust deposition in this location. Similar to S1, S6, and S16, these places likewise show significant levels of dust deposition, indicating that wind-blown dust accumulation is more common in these areas. When compared to the greater deposition zones, locations like S3, S4, and S5 typically exhibit lower dust deposition values. S5, for instance, peaks on 20 July at 0.00795 ton ha⁻¹, a considerable decrease from the highest values in S11 or S1. These areas might have protective factors, such as vegetation cover, soil type, or topography, that mitigate dust deposition.

3.7. Environmental Impact of Dust Storms and Wind Erosion

3.7.1. Key Observations of Wind Erosion and Dust Deposition in Al-Baha Region

Location S11 exhibited the highest dust deposition across the study period, peaking at 0.00616 ton ha⁻¹ on 20 July. This suggests significant susceptibility to wind erosion, likely due to a combination of strong winds and vulnerable soil conditions. The data indicate a seasonal trend with higher dust deposition in mid-July, possibly linked to specific weather patterns, like dry winds or temperature changes, that enhance soil erosion. The general decline in dust collection toward late August suggests natural soil stabilization, possible vegetation growth, or a reduction in wind speeds, a trend consistent across almost all locations.

Most locations reached their highest wind surface values around 20 July, indicating a period of intense wind erosion activity, possibly linked to specific seasonal weather patterns. However, significant spatial variability was observed in wind surface values, with locations like S11, S1, and S6 showing consistently higher values, highlighting the need for targeted wind erosion-control measures in these areas. A clear temporal pattern was observed where dust deposition increased in the mid-summer period (late June to mid-July) and decreased toward the end of August. This suggests that dust deposition is closely linked to seasonal weather patterns and wind activity. The decline in dust deposition toward late August across most locations, such as S1 (dropping to 0.00494 ton ha⁻¹), indicates a reduction in dust-transporting wind events, likely due to seasonal changes that reduce soil erosion and dust mobilization.

Furthermore, the S11 location also showed a particularly high peak in dust deposition (0.02056 ton ha⁻¹) on 10 July, possibly indicating a localized event or conditions that significantly increased dust transport and deposition. The high dust deposition observed in locations such as S11 may be influenced by specific land-use practices, such as agriculture, overgrazing, or construction activities that disturb the soil. These practices can leave soil surfaces more vulnerable to wind erosion. The topographical conditions, such as steep slopes or uneven terrain in these areas, may also contribute to higher dust mobilization by facilitating wind erosion. Additionally, intense weather conditions, like strong winds, prolonged dry spells, and high solar radiation, can exacerbate soil erosion and dust deposition, particularly during the mid-summer period, when these factors are most pronounced.

3.7.2. Sensitivity Analysis of Wind-Erosion and Dust-Deposition Impacts in Al-Baha

Figure 9 provides data on the sensitivity of various sites in the Al-Baha region to wind erosion, wind surface disturbance, and dust deposition, measured in tons per hectare (ton ha⁻¹). These measurements indicate the degree to which each site is affected by these processes, offering insights into environmental conditions across the region.

The most vulnerable location in terms of wind erosion (0.00363 ton ha⁻¹), wind surface disturbance (0.00608 ton ha⁻¹), and dust deposition (0.01327 ton ha⁻¹) is S11 (Nawan, Al-Makhwah Governorate). Given how frequently valleys catch and direct wind-borne particles, the existence of Wadi Nawan, a valley, may be a factor in the high dust accumulation. High sensitivity is observed in S6 (Al-Rumaydah Center, Qilwah Governorate), especially for wind erosion (0.00311 ton ha⁻¹) and dust deposition (0.00955 ton ha⁻¹). Wadi Douqa’s topography may have a role in dust collection and wind-driven soil erosion; a wind surface value of 0.00515 ton ha⁻¹ indicates a considerable amount of surface disturbance. S1 (Wadi Sial, west of Al-Hajra Governorate) shows significant susceptibility to dust deposition (0.00949 ton ha⁻¹) and wind surface disturbance (0.00531 ton ha⁻¹). The region’s geomorphology most certainly has a major influence on dust collection and accelerated soil erosion.

Nevertheless, of the locations under investigation, S5 (Ma’shouqa Center, Al-Qura Governorate) has the lowest values for wind erosion (0.00168 ton ha⁻¹), wind surface disturbance (0.00314 ton ha⁻¹), and dust deposition (0.00585 ton ha⁻¹). Due to either protective vegetation cover or less severe wind activity, this site is significantly less affected by wind-related soil-loss processes. Another site with minimal susceptibility to wind erosion (0.00181 ton ha⁻¹), wind surface disturbance (0.00335 ton ha⁻¹), and dust deposition (0.00617 ton ha⁻¹) is S9 (Al-Qura Governorate). Al-Qura Governorate’s environment seems to lessen the effect of wind on soil loss; this could be because of the region’s topography, vegetation, or certain climate conditions that slow down wind. S10 (Bayda, Al-Qura Governorate) exhibits values that are similarly low in each category: dust deposition (0.00602 ton ha⁻¹), wind erosion (0.00178 ton ha⁻¹), and wind surface disturbance (0.00343 ton ha⁻¹). The data’s resemblance to S9 indicates that the Al-Qura Governorate region has a rather stable environment with few soil disturbances caused by wind.

The overall difference in sensitivity among the locations emphasizes how localized environmental conditions play a significant role in determining dust deposition and wind erosion. Higher-sensitivity areas might need special attention when it comes to soil protection, especially those that are close to wadis. It is possible that the funneling effect of valleys, which can trap and concentrate dust particles, is the reason why sites like S11, S6, and S1 tend to display greater levels of wind erosion and dust deposition. On the other hand, the Al-Qura Governorate has several sites, including S5, S9, and S10, that continuously exhibit reduced susceptibility to wind erosion and dust deposition. These findings raise the possibility that the region benefits from naturally occurring protective elements like vegetation cover or slower wind speeds. These results are essential for creating site-specific plans that will improve environmental sustainability and lessen soil loss in the Al-Baha area.

3.7.3. Implications for Sustainable Development in Saudi Arabia

In Saudi Arabia, the effects of wind erosion and dust storms pose serious obstacles to sustainable growth, especially when considering the objectives and goals of the Vision 2030. Through processes such as salinization, higher electrical conductivity, and changes in the mineral makeup of the soil, these natural occurrences exacerbate soil deterioration. Such modifications have a negative impact on soil quality, vegetation development, agricultural production, ecosystem stability, and environmental sustainability. To address these problems, integrated management approaches are needed. The implemented management approaches must consider regional climate and topography and comply with both international sustainability goals, such as the Sustainable Development Goals (SDGs), and the commitment of KSA’s Vision 2030 to building a resilient and sustainable environment.

Given their greater rates of erosion, locations such as S11, S6, and S1 may benefit from targeted erosion-control methods, such as windbreaks, vegetation cover, and soil stabilization techniques, especially during mid-summer, when dust deposition peaks. In order to lessen the impact of wind erosion during high-risk seasons, it may be essential to establish seasonal monitoring and mitigation methods, as dust deposition peaks around mid-July. Effective erosion control will require adaptive management solutions that consider the unique conditions of each location and time of year, given the spatial and temporal variability of wind erosion and dust deposition.

The findings of this study emphasize the significant effects of dust storms and dust accumulation on the physiochemical characteristics of soil in Al-Baha. One frequent result of wind erosion is dust deposition, which greatly improves electrical conductivity and changes the mineral content of the soil, leading to a possible increase in the salinity of the soil. The presence of dust particles in the air can cause these changes to significantly impair vegetation growth, deteriorate soil quality, and harm air quality. These changes, as noted in our research, are comparable with the findings of [54], which also highlighted how airborne dust particles can significantly impair vegetation growth, deteriorate soil quality, and negatively affect air quality. This underscores the urgent need for effective management strategies to address the multifaceted impacts of dust storms in arid regions. Dust deposition, wind erosion, and surface runoff all work together to worsen soil loss; this is especially true in places with strong winds and soils characterized with light-textures, like most locations in Al-Baha (Table 3). Agricultural productivity is threatened by the deterioration of soil quality brought on by salinization and dust deposition, which undermines attempts to achieve food security (SDG 2). The increased salinity observed in several locations in Al-Baha and the subsequent expected decrease in soil quality are clear indicators of this degradation. In dry regions like KSA, managing soil- and dust-related concerns requires considering local meteorological and topographic characteristics due to the variability of dust deposition and its impacts across different sites. These findings are comparable with those of [43,45], which also noted similar patterns of increased salinity and soil quality degradation in arid regions. In dry areas like Saudi Arabia, effectively managing soil and dust-related concerns necessitates considering local meteorological and topographic characteristics, given the variability in dust deposition and its impacts across different sites.

To accomplish the goals specified in Vision 2030, the Kingdom of Saudi Arabia must address several obstacles. The preservation of natural resources and environmental sustainability are key components of Vision 2030. The study’s findings support the objectives of Vision 2030 to strengthen the Kingdom’s resistance to climate change through the promotion of sustainable land management techniques that lessen desertification and soil erosion. In particular, controlling dust storms and their effects on soil and air quality is crucial to fostering a healthier environment—an objective that is highly valued in Vision 2030. Furthermore, the variation in dust deposition and its consequences at various locations emphasizes the significance of tailored approaches that take topographical and meteorological variables into account. In dry regions like KSA, these tactics are crucial for handling difficulties connected to soil and dust. By tackling these issues, KSA can achieve the sustainability goals contained in Vision 2030 and fulfill its commitment to the global SDGs with great success. This study’s conclusions not only offer insightful information about how dust storms affect the ecosystem, but they also highlight the necessity of focused interventions that support more general development and sustainability objectives.

Implementing such interventions will be key to mitigating the adverse effects of wind erosion and dust deposition, thereby supporting Saudi Arabia’s long-term vision for a sustainable, resilient future.

4. Summary and Conclusions

This study offers valuable insights into the impacts of wind erosion and dust deposition on soil losses in the Al-Baha region of Saudi Arabia during the summer of 2022. The research employed multiple dust-collection techniques (BSNE, SDC, and MDCO) at 20 distinct sites, revealing significant findings regarding soil composition and dust accumulation.

The findings revealed that soil loss was primarily driven by dust deposition, followed by surface wind disturbance and wind erosion, with site S11 experiencing the highest levels of soil loss. In contrast, site S5 showed the least soil loss, likely due to better vegetation cover or inherent soil stability. Dust deposition peaked in July, particularly at site S11, which recorded the highest values of dust accumulation and wind surface disturbance. This site, along with S1 and S6, emerged as a high-risk area for soil loss, emphasizing the need for targeted soil conservation measures. The effectiveness of the MDCO technique in capturing significant quantities of dust further highlights its utility in studying wind erosion patterns, especially in arid environments.

The study also shed light on the soil’s physicochemical characteristics, with pH levels ranging from 7.38 to 7.79, indicating slightly alkaline conditions across all sites. Electrical conductivity (EC) varied significantly, with higher values at sites S1, S3, and S18, suggesting increased salinity and potential soil contamination. The presence of high concentrations of sodium (Na^⁺) and chloride (Cl⁻) ions, particularly at site S1, points to sodicity and poor soil fertility in some areas, further emphasizing the impact of wind erosion and dust deposition on soil chemistry. Additionally, the mineralogical composition, dominated by quartz and calcite, reflects the influence of dust deposition on soil mineralogy and the broader environmental degradation processes at play in the region.

This study identified clear seasonal variations, with peak dust deposition and wind erosion occurring in mid-July, followed by a significant decline by late August. This pattern, combined with the analysis of meteorological conditions, highlights the importance of understanding seasonal weather impacts on soil loss dynamics. The data suggest that mitigation strategies should be prioritized in high-risk areas, particularly at sites like S11, S1, and S6, where soil loss is most severe.

In comparison with other arid and semi-arid regions, the results are consistent with findings from North Africa and the Middle East, which report similar peaks in dust deposition during summer months and corresponding increases in soil salinity. Similar trends have been observed in regions prone to wind erosion and dust storms, where seasonal variations in dust deposition are linked to changes in soil quality, especially salinity and fertility. However, this study offers a novel contribution by integrating multiple dust collection methods, providing a more comprehensive understanding of the mechanisms driving soil loss and dust accumulation. The lack of extensive research specific to the Al-Baha region, particularly studies using multi-method approaches, further underscores the importance of this research in the investigation of sustainable soil management practices. By advancing our knowledge of the effects of dust storms and wind erosion on soil properties, the findings of this research can aid in the development of methods and policies meant to reduce soil erosion and improve environmental sustainability in the Al-Baha region.

When compared to studies from other arid regions, such as those conducted in the Sahara Desert and parts of the Arabian Peninsula, the results of this study align with global trends in wind erosion and dust deposition, reinforcing the need for region-specific soil conservation strategies. Considering Saudi Arabia’s Vision 2030 and global Sustainable Development Goals (SDGs), the findings of this study highlight the critical need for strategies that mitigate wind erosion and dust deposition, ensuring long-term environmental sustainability and resilience in arid regions.