Vegetation Cover as a Driver of Sedimentary Organic Matter in Small Water Reservoirs

Abstract

Understanding the impact of vegetation on organic matter content in sediments is essential for sustainable reservoir management and water quality protection. This study examined the relationship between land cover, erosion processes, and organic matter accumulation in the sediments of four small water reservoirs in the Republic of Serbia. Organic matter content was quantified and analyzed in relation to basin characteristics, including land-use composition, absolute and mean flow gradients, and sediment grain size distribution. Field sampling was conducted across the catchments of four small water reservoirs—Duboki potok, Resnik, Ljukovo, and Sot—with sediment samples collected from main tributaries and accumulation basins. A multi-method approach was employed, combining remote sensing for vegetation-cover assessment, granulometric analysis, organic matter evaluation via loss-on-ignition at 350 °C, and statistical correlation analysis to assess the influence of land use and hydrological gradients on sediment composition. The results revealed a strong correlation (R = 0.892) between forest cover and sedimentary organic matter content, confirming the significant role of vegetation in stabilizing sediments and promoting organic matter deposition. Reservoirs with higher forest and shrub cover (e.g., Sot and Duboki potok) exhibited greater organic matter accumulation (5.79–5.98%), while the agriculture-dominated Ljukovo catchment (76.85% agricultural land) recorded the lowest organic matter content (3.89%) due to increased sediment displacement and reduced erosion resistance. These findings underscore the critical role of vegetation in regulating sediment dynamics and enhancing organic matter retention in small water reservoirs. To mitigate excessive organic matter deposition and improve water quality, sustainable watershed management strategies—such as vegetation buffer strips, afforestation, and erosion control measures—are recommended.

1. Introduction

Vegetation plays a critical role in land conservation, particularly in reducing soil erosion and stabilizing sediments through root systems and canopy cover [1,2]. However, in the context of small water reservoirs, vegetation can also contribute to sediment accumulation, as plant residues from both terrestrial and aquatic vegetation become part of the deposited material [3]. As these organic materials decompose, they can release harmful compounds—such as phenols, nitrosamines, polycyclic aromatic hydrocarbons, and dioxins—that degrade water quality [4,5].

Sedimentation in small water reservoirs presents significant challenges for water resource management. It reduces storage capacity, disrupts flow regulation, increases maintenance costs, and lowers the efficiency of systems designed for irrigation, flood control, and water supply [6,7]. This problem is intensified by high organic matter content in sediments, which not only alters sediment texture and geomechanical properties [8] but also deteriorates water quality by promoting anoxic conditions and nutrient release [9,10]. Due to their relatively small volumes and sensitivity to environmental changes, small reservoirs often serve as effective indicators of broader watershed conditions [11].

For clarity, this study defines a “small water reservoir” as a human-made waterbody with a surface area of less than 50 hectares and a storage capacity typically below 1 million cubic meters, primarily used for irrigation, flood control, livestock, recreation, or local water supply. These systems are common in rural and semi-rural landscapes but are often underrepresented in hydrological and sedimentation research.

While organic carbon dynamics in large reservoirs and natural lakes have been widely studied, smaller systems have received limited attention—despite their growing importance in integrated watershed management. Organic carbon plays a key role in the global carbon cycle, transferring material from terrestrial ecosystems into aquatic systems, where it is either buried in sediments or released as CO₂ through decomposition [12,13,14]. The rate of this accumulation is controlled by catchment factors such as vegetation cover, land-use practices (e.g., deforestation and agriculture), and hydrological gradients [15,16,17,18].

Although small reservoirs are typically more environmentally compatible than large-scale impoundments—causing fewer disruptions to local climate and ecosystems [19,20]—they are especially vulnerable to sedimentation. High-energy tributaries and poor land management accelerate sediment delivery, diminishing reservoir lifespan and water quality [21,22].

Despite their importance, few studies have focused on how vegetation influences organic matter dynamics in the sediments of small water reservoirs [23,24]. Most research to date has emphasized sediment-yield modeling, erosion control, or nutrient cycling in larger systems [25,26]. This gap in knowledge limits our understanding of how vegetation structure and distribution influence sediment composition and organic retention in smaller-scale aquatic environments.

The present study addressed this research gap by analyzing four small water reservoirs in the Republic of Serbia. The study investigated how basin characteristics—including land cover, terrain slope, erosion potential, and sediment grain size—affect organic matter accumulation in sediments. By integrating remote sensing, field sampling, geostatistical modeling, and regression analysis, this research provides new insights into the interaction between vegetation, erosion processes, and sediment composition, contributing to the development of sustainable watershed and reservoir management strategies.

2. Materials and Methods

2.1. Study Area

This research was conducted at four small water reservoirs in the Republic of Serbia, situated in Southeastern Europe (Figure 1). The selected reservoirs were Sot (near Šid), Ljukovo (near Inđija), and Resnik and Duboki potok (both located in the suburbs of Belgrade). These sites were chosen for their contrasting land cover characteristics: three of the reservoirs are situated in catchments with substantial forest cover, both within the basin and along the reservoir banks, while Ljukovo is located in a predominantly agricultural landscape, with minimal natural vegetation.

The characteristics of the reservoir catchments are summarized in

Table 1. Organic matter values represent mean percentages calculated from multiple sediment samples collected at different points within each reservoir.

Reservoir	Basin Area (km2)	Absolute Gradient of Flow (%)	Mean Basin Gradient (%)	Organic Matter in Sediment (%)	Mean Diameter of Sediment (mm)	Dominant Land Use	Vegetation Cover (%)	Geological Composition	Soil Type	No of Samples	Sampling Depth (cm)
Duboki potok	6.05	3.67	12.74	5.79	1.90–20.00	Mixed Forest	44.13	Sandstones, clays, marls	Haplic Cambisol	5	0–20
Resnik	4,00	6.67	7.18	5.98	0.02–0.08	Deciduous Forest	36.75	Gray-blue marl, iron clays, limestone, sand clays	Haplic Cambisol	6	0–25
Ljukovo	17.11	0.71	2.92	3.89	0.02–0.03	Agriculture	12.39	Sandy-clay siltstones, sandy siltstones	Carbonate chernozem	6	0–30
Sot	13.6	1.97	8.45	5.85	0.015–0.017	Mixed Land Use	54.62	Sands, sandy siltstones	Haplic Cambisol	5	0–22

Note: The median diameter of sediment (d50) is the particle diameter at 50% cumulative percentage on the granulometric composition curve.

and described in more detail below. Each reservoir differs in its hydrological, geological, and sedimentation features, making them well-suited for analyzing sediment transport, organic matter accumulation, and the influence of land use.

The Duboki potok Reservoir was formed in 1991. The lake has an area of about 0.08 km² and receives inflow from seven tributaries streams. Sediment control structures have been installed along these tributaries to minimize sedimentation in the main basin. The right side of the valley is densely covered with autochthonous vegetation, including Turkey oak, hornbeam, beech, linden, and wild cherry, while the left valley side experiences only minor erosion activity.

The geological substrate is dominated by sandstones, clays, and marls, which together account for approximately 85% of the terrain. The prevailing soil type is Haplic Cambisol, known for its moderate fertility and susceptibility to surface erosion under certain conditions.

The Resnik Reservoir, situated at the base of Mt. Avala, was constructed in 1980 to control flooding along the Topčiderska River. The reservoir has a surface area of approximately 0.084 km². The geological composition of the basin is primarily gray-blue marl and iron-rich clays (47%), accompanied by limestone and sandy clay formations (32%). The surrounding landscape is covered by deciduous forests, while areas prone to erosion contribute to sediment accumulation within the reservoir basin. The dominant soil type in the catchment is Haplic Cambisol, covering approximately 84% of the area.

Ljukovo Reservoir, built in 1973, has a surface area of 0.35 km² and is primarily used for irrigation and fish farming, with an annual fish yield of 3–5 tons. The dam is equipped with a water intake structure and a drainage system featuring a 450 mm pipeline, which enables complete drainage of the reservoir when needed. The geological structure consists of sandy-clay siltstone and sandy siltstone (58%), with sand deposits occurring along the main tributaries (42%). The dominant soil type in the catchment is carbonate chernozem (88%).

Sot Reservoir, created in 1979, has a surface area of 0.33 km² and is used for irrigation, livestock watering, sport fishing, and recreation. The surrounding terrain is hilly, with meadows and forests of oak, hornbeam, linden, and mixed deciduous–coniferous woodland. The dominant soil type is Haplic Cambisol (85%), characterized by a high clay content, which makes it susceptible to surface leaching and erosion during intense precipitation events. The underlying geological structure consists primarily of sands and sandy siltstones (77%).

2.2. Sediment Sampling and Laboratory Analysis

A comprehensive sediment sampling campaign was carried out at key tributary inflows and accumulation zones within each reservoir. Sampling locations were georeferenced using a Topcon GMS-2 manual GPS device to ensure accurate spatial positioning. Sediment samples were collected using a hand grab excavator, allowing access to deeper sediment layers (Figure 2). Sediment sampling was conducted at four reservoirs: Duboki potok, Resnik, Ljukovo, and Sot. A total of 22 sediment samples were collected across the four reservoirs, with 5–6 samples per reservoir. Samples were taken from the main tributaries, the center of the accumulation basins, and near the reservoir banks to capture variability in sediment deposition. Sampling was performed at depths ranging from 0 to 30 cm, using a hand grab excavator for the deeper layers (Figure 2), ensuring representation of both surface and subsurface sediments. GPS coordinates for each sampling point were recorded using a Topcon GMS-2 manual GPS device. All samples were collected in late spring to reflect hydrological conditions that influence sedimentation patterns.

In the laboratory of the Institute of Forestry (Pedological Laboratory), the following analyses were performed:

Sedimentary organic matter content was determined using the loss-on-ignition (LOI) method, by ashing the samples at 350 °C ± 25 °C, in accordance with SRPS EN 15169:2010. This temperature was chosen as it effectively oxidizes organic matter while minimizing the thermal decomposition of carbonates, which typically occurs at higher temperatures (e.g., above 400 °C) and can result in overestimation of organic content. The selected ashing temperature aligns with methodologies recommended in previous studies for accurate analysis of sedimentary organic matter [27]. For each sample, about 10 g of sediment (air-dried) was placed in a pre-weighed crucible and combusted in a muffle furnace for 6 h. The ashing duration was sufficient to ensure complete combustion of organic matter while avoiding excessive alteration of the mineral fraction. Following ashing, the residual mineral content was cooled in a desiccator and subsequently weighed to determine organic matter content based on mass loss.

2.3. Land Use and Erosion Analysis

To evaluate the impact of land use on sediment production, a combined remote sensing and orthophoto analysis was conducted. Vegetation maps were generated for all four reservoir catchments, with land cover types classified using satellite imagery and GIS-based vegetation indexing techniques.

To estimate sediment production from each basin, the erosion potential method (EPM) was applied [28]. This model integrates land-use type, terrain slope, and rainfall data to simulate sediment yield and transport dynamics across reservoir catchments.

The analysis considered several key parameters. In particular, basin gradients were analyzed, focusing on both the absolute flow gradient and the mean catchment slope, given their strong influence on sediment mobility and deposition processes. Additionally, the tensile (shear) force of the flow was calculated to assess hydrodynamic conditions and their contribution to erosion potential [28]. The tensile force of the flow refers to the shear stress exerted by flowing water on sediment particles, which influences sediment transport and erosion processes. It determines the ability of water to mobilize and transport sediments, impacting sedimentation rates in reservoirs.

The tensile force (shear stress, τ) is commonly expressed using the bed shear stress equation:

τ = ρgRS

(1)

where the following variables are used:

τ = shear stress (Pa);

ρ = density of water (kg m⁻³);

g = acceleration due to gravity (9.81 s⁻²);

R = hydraulic radius (m), defined as the cross-sectional area of flow divided by the wetted perimeter;

S = slope of the energy gradient (dimensionless).

The tensile force was calculated using measured hydraulic parameters of the reservoirs’ inflows and basin gradients. This equation helps in quantifying the erosive capacity of flowing water and its influence on sediment deposition.

Additionally, a correlation analysis was conducted to examine the relationships between land use, erosion processes, and sedimentary organic matter content, offering valuable insights into how these environmental factors interact within the studied reservoirs.

2.4. Geostatistical Modeling

To analyze the spatial variability of sediment transport and deposition processes, a grid-based geostatistical overlay method was applied to the catchment areas of the studied reservoirs. The study area was divided into a regular grid of geostatistical points, with each cell representing a defined spatial unit characterized by topographical, hydrological, and land-use attributes.

Source datasets:

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Elevation data were derived from a digital elevation model (DEM) obtained from the EU-DEM v1.1 dataset (resolution: 25–30 m), which was used to calculate slopes, basin gradients, and flow direction.

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Land cover data were obtained from the CORINE Land Cover (CLC) 2018 dataset, which provides standardized classifications (e.g., forest, agriculture, and urban) at a 100 m resolution across Europe.

Hydrological parameter derivation:

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Flow accumulation and drainage density were calculated using standard hydrological analysis tools in ArcGIS 10.x and QGIS (with GRASS plugin). Flow direction and flow accumulation layers were computed using the D8 algorithm on the DEM, which models the path of water across the terrain.

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Drainage density was calculated as the total length of streams (identified using a stream threshold on the flow accumulation raster) divided by the basin area.

GIS-based spatial modeling techniques included:

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Raster-based overlay analysis to combine slope, land use, and flow accumulation layers.

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Reclassification and weighting of individual raster layers based on erosion potential indices.

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Zonal statistics and map algebra to quantify erosion risk and identify critical sediment deposition zones.

The grid resolution was chosen based on the catchment size and data availability—primarily 50 m × 50 m for smaller basins and 100 m × 100 m for larger ones—to ensure a balance between spatial detail and computational efficiency.

This approach offers several benefits, including:

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Improved spatial precision in identifying sediment sources and transport pathways.

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Enhanced ability to conduct correlation analysis between land use, slope gradients, and sedimentation.

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Greater predictive capability for erosion modeling and long-term reservoir sedimentation forecasting.

The results from this geostatistical modeling were used to quantify erosion potential, delineate critical sedimentation zones, and better understand how land-use practices influence organic matter accumulation in reservoir sediments [29].

2.5. Linear Regression Model for Sediment and Vegetation Analysis

To evaluate the relationship between vegetation cover, land use, and sedimentary organic matter content, a multiple linear regression model was developed. The objective was to quantify the influence of forest and shrub cover on organic matter accumulation in sediments, while accounting for basin gradients, erosion potential, and land-use distribution.

The dataset used in the regression analysis was carefully constructed to capture the primary drivers of organic matter retention in reservoir sediments. It included the percentage of forest and shrub cover within each watershed, reflecting the extent of vegetation and its potential effect on sediment stabilization.

To assess erosion dynamics, the erosion coefficient (Z-value) was calculated using the erosion potential method (EPM) [27], offering insights into sediment displacement within each catchment. Additionally, both the absolute flow gradient and mean basin slope were included as key hydrological parameters, given their influence on sediment transport and deposition processes across the studied reservoirs [28].

All input variables were derived from a combination of field sampling, remote sensing, and geostatistical modeling. The dataset was compiled into a structured geospatial database, with all spatial layers standardized to ensure consistent resolution and alignment across reservoir catchments.

2.6. Regression Methodology

A multiple linear regression (MLR) model was used to evaluate the relationship between sedimentary organic matter content and key explanatory variables: forest and shrub cover, mean basin gradient, and erosion coefficient. Rather than relying solely on the four reservoir-level averages, the model incorporated data from all 22 sediment sampling points. For each sampling location, the contributing drainage area was delineated using hydrological flow direction analysis. The associated values for vegetation cover (%), average slope (%), and erosion coefficient (Z) were calculated based on the characteristics of the specific upstream sub-catchment.

This spatially detailed approach enabled the regression model to capture variability both within and across reservoir basins, thereby increasing the robustness and reliability of the statistical analysis. The model was validated using the coefficient of determination (R²) to assess explanatory power, and p-values to test statistical significance, with a threshold of p < 0.05 used to determine meaningful relationships.

The model was formulated as follows:

OM = β0 + β1 (FC) + β2 (EG) + β3 (Z) + ϵ

(2)

where the following variables are used:

OM = organic matter content in sediment (%);

FC = forest and shrub cover (%);

EG = mean basin gradient (%);

Z = erosion coefficient

β0 = intercept;

β1, β2, β3 = regression coefficients;

ϵ = error term.

This modeling framework provided a quantitative basis for identifying the dominant landscape and hydrological factors influencing sedimentary organic matter accumulation, forming the foundation for the results presented in the following section.

3. Results

The results provide a comprehensive assessment of sediment composition and organic matter content across the four studied reservoirs. Key environmental factors—including catchment morphology, land use, and hydrological gradients—were found to significantly influence sediment deposition and organic matter distribution.

The regression analysis revealed a strong correlation (R² = 0.892) between forest cover and sedimentary organic matter content, indicating that increased vegetation significantly enhanced organic matter retention in reservoir sediments. The erosion coefficient (Z) exhibited a negative correlation with organic matter, suggesting that higher erosion rates were associated with reduced organic accumulation. The basin gradient was found to play a secondary role, primarily influencing sediment transport and deposition dynamics.

These findings confirm that vegetation cover is the dominant factor governing organic matter accumulation in small water reservoirs. The results align with previous studies on the influence of land use and erosion processes on sediment dynamics in freshwater systems [29].

Table 1 summarizes the main characteristics of each reservoir’s catchment, such as total basin area, flow gradient, sediment grain size, and organic matter content. These data offer a comparative overview of how different catchment configurations affect sediment characteristics.

The accompanying figures and tables present detailed correlations between sediment properties, land cover types (e.g., forest vs. agricultural areas), and erosion indicators. Together, they illustrate how vegetation density and basin slope influence both the quantity and quality of sediment deposited in each reservoir. The following variables are used in these figures and tables:

J_ap.to—absolute gradient of the flow;

J_sr—mean gradient of the basin;

d_50%—mean diameter of the deposit, derived from granulometric composition curve, with percentage of 50%.

According to the statistical analysis, sediment production parameters in the basin were compared with characteristic gradient values and land-use types to evaluate their influence on deposit formation (Figure 3,

Table 2. Display of p-values.

Location	Correlation Coefficient (R)	p-Value
Resnik	0.885	<0.001
Duboki potok	0.892	<0.001
Sot	0.509	<1
Ljukovo	0.859	<0.01

).

The Ljukovo reservoir showed the lowest organic matter content in sediment (3.89%), and its catchment characteristics offer several explanations for this result. Located in a flat lowland area, Ljukovo has the lowest mean basin gradient and absolute flow gradient among the study sites. These gentle slopes limit water velocity and reduce the tensile (shear) force in tributaries, significantly restricting the transport of organic material into the reservoir.

Moreover, land use in the Ljukovo basin is dominated by intensive agriculture, with minimal natural vegetation along the reservoir banks. The absence of forested riparian zones limits the input of organic debris such as fallen leaves, branches, and woody material. Much of the organic matter produced in the basin is harvested and removed through agricultural practices, rather than being allowed to enter the fluvial system. As a result, organic matter tends to decompose near its place of origin, and very little reaches the sedimentation zone of the reservoir.

In contrast, the other three reservoirs—Duboki potok, Resnik, and Sot—all showed significantly higher organic matter content in sediment (5.79%, 5.98%, and 5.89%, respectively). These reservoirs are situated in catchments with greater vegetation cover, especially forests and shrubs, and steeper terrain gradients. These features promote more effective transport of plant-derived material into the reservoirs and facilitate sediment deposition.

A strong positive correlation was observed between forest and shrub cover in the catchment and organic matter content in sediments. This trend highlights the role of vegetation in stabilizing soils and contributing organic material, either through direct erosion of forest litter or wave-driven bank erosion in vegetated areas. Notably, forested banks adjacent to the reservoirs, especially on the left sides of Duboki potok, Resnik, and Sot, contributed visibly to organic input, unlike the bare banks of Ljukovo.

The Sot reservoir, however, presented an exception in the statistical correlations due to its high vegetation cover (>50%) but relatively modest flow gradient. This condition suggests that while substantial organic matter is produced within the basin, much of it remains within the terrestrial system or decomposes before being transported to the reservoir due to slower hydrological movement.

Additional local factors further explain the variation. For example, Ljukovo’s large water surface area and shallow depth create favorable conditions for the growth of aquatic vegetation such as algae and underwater grasses, which contribute to in-reservoir organic production. Furthermore, runoff from nearby agricultural lands enriched with nitrogen and phosphorus fertilizers stimulates this aquatic biomass growth, altering the reservoir’s organic dynamics.

Although the catchments differ significantly in size, gradient, and land use, grain size distribution of sediments was relatively uniform across most sites—except for Duboki potok, where sediment grain diameter ranged from 1.9 to 20 mm. This coarser texture was consistent with the catchment’s steep gradients and high erosion energy, which favors the transport of larger particles.

The analysis confirmed that vegetation cover, basin slope, and land-use type are the most influential factors governing organic matter retention in reservoir sediments. The combined effect of low gradients and agricultural dominance in Ljukovo strongly limits organic matter accumulation, whereas forested, sloped catchments promote both erosion and organic deposition into small reservoirs.

4. Discussion

Our study confirms established relationships by demonstrating that forest and shrub cover significantly enhance organic matter accumulation in sediments of small water reservoirs. This reinforces earlier findings by Areu-Rangel et al. [30], and Shen et al. [31]. The role of vegetation in sedimentary organic matter dynamics is well-documented in hydrological and ecological literature [32,33,34,35,36]. Yang et al. [37] noted vegetation’s role in reducing erosion and stabilizing sediments.

However, this study provides new insights by quantifying these effects in small water reservoirs, a system type that remains underrepresented in sedimentation research. Specifically, we show that:

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Even modest increases in forest and shrub cover within a catchment lead to significantly higher organic matter content in reservoir sediments.

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Low-gradient agricultural basins, such as Ljukovo, experience reduced sediment and organic matter delivery due to laminar flow and low erosive force.

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The presence of vegetated reservoir banks contributes to organic input via wave erosion and litter fall, a dynamic often overlooked in studies focusing solely on catchment-wide vegetation.

Many papers [38,39,40,41,42,43] established that the composition of terrestrial organic matter can be altered through biodegradation during transportation from the terrestrial to the aquatic environment. Our study provides empirical evidence that hydrological gradients and soil erodibility, in combination with vegetation cover, regulate both the quantity and quality of sediment delivered to small reservoirs. This aligns with findings by Wu et al. [44] and Chmiel et al. [35], who observed that finer sediments in low-energy systems are primary carriers of organic carbon, and sediment grain size can greatly influence carbon retention.

4.1. Novel Contributions of This Study

This study offers several methodological and analytical innovations that advance the understanding of sedimentary organic matter dynamics in small water reservoirs:

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A sub-catchment scale regression model was applied using 22 sediment sampling points rather than general basin averages, enhancing spatial resolution.

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The study demonstrated that riparian vegetation along reservoir margins contributes significantly to organic input, independent of broader land cover patterns.

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The study applied geostatistical erosion modeling to small reservoir catchments, integrating land use, slope, and hydrological variables to predict sedimentary organic matter.

4.2. Limitations

Several limitations should be acknowledged:

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The study covered only four reservoir systems within a single geographic region (Republic of Serbia), limiting generalizability.

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Seasonal variation in organic matter input and decomposition was not explicitly captured, as all samples were collected in spring.

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The erosion coefficient (Z), while useful, may not fully represent dynamic erosion events (e.g., during storms) due to its static formulation.

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Grain size and organic content were assessed from shallow sediment layers (0–30 cm), which may not reflect long-term accumulation trends.

Future studies could expand the temporal resolution (e.g., seasonal sampling), include more diverse climatic zones, and apply high-frequency monitoring to better capture episodic events.

4.3. Wider Implications

The findings from this study have broader applicability beyond the Serbian context:

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In agriculturally dominated catchments globally—especially in Eastern Europe, Central Asia, and Latin America—similar sedimentation and organic matter trends are expected.

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Results support nature-based solutions such as riparian buffers and reforestation as low-cost, effective strategies for reservoir sediment management.

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The methodology used—especially the integration of remote sensing, sub-catchment modeling, and geospatial regression—is transferable to other regions aiming to optimize land-use planning and sediment control in small water bodies.

Furthermore, in regions facing climate-driven changes in precipitation and erosion, understanding sedimentary organic matter dynamics is crucial for adapting reservoir management strategies and enhancing carbon sequestration potential in aquatic sediments.

5. Conclusions

This study analyzed four small reservoirs in the Republic of Serbia to investigate the relationship between catchment characteristics—particularly vegetation cover, land use, and slope gradients—and the organic matter content in reservoir sediments.

The results revealed a strong positive correlation between forest and shrub cover in the catchments and organic matter accumulation in sediments. Reservoirs with higher vegetation cover and steeper basin gradients (e.g., Duboki potok, Resnik, and Sot) exhibited significantly higher organic matter content compared with Ljukovo, which had the flattest terrain and the least vegetation. These findings highlight the role of both topography and land use in influencing erosion processes, sediment transport, and organic matter retention.

The sedimentation patterns also varied with the geological composition of the basins, affecting grain size and sediment characteristics. While this study focused on reservoirs not used for potable water supply, the findings have broader implications for reservoir management and water quality protection. In reservoirs designed for water supply or sensitive ecological functions, attention must be paid to the accumulation of organic matter, as its decomposition can degrade water quality.

To reduce excessive sediment and organic matter input, watershed management strategies such as the implementation of biological (e.g., reforestation and vegetative buffer zones) and technical erosion control measures are recommended. These interventions can help regulate sediment transport, enhance carbon sequestration, and improve reservoir lifespan and function.

Finally, the modeling approach used in this study demonstrates potential for long-term monitoring of sedimentation dynamics in small reservoirs. However, expanding the dataset across more reservoirs and diverse geographic conditions is necessary to develop a regionally applicable sedimentation model, which could support broader watershed and reservoir management planning.