Evaluation of the Impact of Comprehensive Watershed Management on Carbon Sequestration Capacity of Soil and Water Conservation: A Case Study of the Luodi River Watershed in Changting County, Fujian Province

Abstract

Soil and water conservation measures have good carbon sinking capacity, and the comprehensive management of small watersheds involves plant measures, engineering measures and farming measures, which profoundly affect the capacity of the three major carbon pools of soil, vegetation and water bodies, making them an ideal place to carry out the monitoring and accounting of carbon sinks in soil and water conservation. The purpose of this paper is to monitor and evaluate the carbon sinks of soil and vegetation, to provide techniques and methods for the implementation of dynamic monitoring and evaluation of carbon sinks in soil and water conservation projects, and to provide theoretical and methodological support for the participation of soil and water conservation projects in carbon trading and the study of the formulation of relevant rules. In this study, field sampling and analysis, LiDAR, remote sensing and other related parameters were used to account for the carbon storage of vegetation carbon pools and soil carbon pools in the Luodi River sub-watershed, Changting County, Fujian Province, from 2001 to 2022, and to evaluate the carbon sink capacity of the various soil and water conservation management measures in the sub-watershed. The results show that after 21 years of comprehensive management, various soil and water conservation measures in the Luodi River sub-basin have significantly enhanced the role and capacity of carbon sinks, and the sub-basin’s carbon stock increased by 3.97 × 10⁴ t, with an average annual increase of 1.89 × 10³ t/a. From the perspective of the carbon pools, the carbon stocks of soil and vegetation increased by 73.73% and 346.41%, respectively, from 2001 to 2022. The total carbon sunk in the sub-watershed reached 2.90 × 10⁴ t, of which 1.57 × 10⁴ t was in soil carbon sinks and 1.34 × 10⁴ t was in vegetation carbon sinks. There were differences in the ability of various measures to enhance the increment of the carbon sink, among which the Castanea mollissima and the Fertilized Pinus massoniana Forest had the most obvious increase in carbon sunk, followed by the Mixed Needleleaf and Broadleaf Forest, the Nurture and Management Pinus massoniana Forest, and the Horizontal terraces Pinus massoniana Forest, and lastly, the Closed Management Forest and the Morella rubra. Various soil and water conservation measures have obvious effects of carbon retention, carbon sequestration and sink enhancement, while Castanea mollissima and Fertilized Pinus massoniana Forest and other forests that implement land preparation and afforestation with fertilization and nourishment measures have more significant increases in carbon sink capacity, which is an effective measure to improve the benefits of soil and water conservation and increase the amount of carbon sinks.

1. Introduction

With the continuous improvement of living standards of the population and the rapid development of the economy, global climate change has become the greatest threat facing mankind [1]. The excessive emission of greenhouse gases has increasingly intensified the global warming trend, causing extremely serious harm to the ecological environment and the global economy [2]. At present, all countries in the world are working together to control global warming, sustainable development has become an important trend in today’s society, and controlling carbon emissions has become a necessary condition for realising sustainable development [3]. Since the 1990s, scientists from various countries have carried out a lot of work on estimating regional-scale terrestrial carbon sinks, and have achieved a consensual conclusion: terrestrial ecosystems of the Northern Hemisphere are an important carbon sink, the size of which is basically able to offset the imbalance of the global carbon balance. With global changes in recent decades, terrestrial ecosystems have become an important sink for atmospheric carbon dioxide, effectively mitigating climate warming [4]. On average, terrestrial ecosystems absorb about 30 per cent of anthropogenic carbon dioxide emissions annually, and their carbon sink capacity is better than that of marine ecosystems. Therefore, in the context of global warming, carbon sinks in terrestrial ecosystems are seen as an important way to mitigate climate change [5]. Soil is the first major carbon reservoir in terrestrial ecosystems. The soil organic carbon pool is about twice as large as the vegetation carbon pool. Soil erosion caused by soil and water loss leads to the loss of carbon. According to statistics, 2.7 Pg (1 Pg = 10¹⁵ g) of soil organic carbon is lost each year worldwide due to soil erosion [6]. With surface spattering, surface erosion and gully erosion of bare soil, soil particles are moved and deposited, and severe soil erosion results in degradation of vegetation, elevation of river beds and pollution of water bodies, as well as directly leading to carbon mineralisation and carbon loss, decline in soil fertility and deterioration of ecosystems [7].

Soil and water conservation is the prevention and treatment of soil erosion caused by human activities and natural factors, controlling soil erosion by increasing surface vegetation cover, elevating the erosion datum, intercepting runoff sediment, etc., improving the regional ecological environment, and promoting the accumulation of the ecosystem’s carbon pool, which will generate huge carbon sink benefits [8]. Soil and water conservation carbon sinking is the process, activity or mechanism of converting the carbon fixed by physical objects of a soil and water conservation carbon sink, such as plant biomass, litter, soil organic matter and carbon in water bodies, into carbon dioxide equivalent, and absorbing carbon dioxide from the atmosphere through the implementation of soil and water conservation measures or projects and other activities in combination with carbon sink trading [9]. Soil and water conservation measures have a good carbon sink capacity, regulating surface runoff through sediment retention, soil conservation and plant cultivation, etc., and thus reduce carbon emissions caused by soil erosion, which is conducive to consolidating and increasing the capacity of the ecosystem’s carbon pool [10]. Comprehensive management of small watersheds involves plant measures, engineering measures, farming measures, etc., which profoundly affect the capacity of the three major carbon pools, namely soil, vegetation and water, and is an ideal place to carry out monitoring and accounting of carbon sinks in soil and water conservation [11].

In the early 1980s, China began to carry out comprehensive management of small watersheds, and so far, it has formed a comprehensive soil erosion management model with Chinese characteristics based on small watersheds as a unit [12]. Liu Zhen [13] divided the development of comprehensive management of small watersheds in China into four stages: the exploration stage (1950s–1970s), the confirmation and pilot stage (1980s–early 1990s), the stage of economic benefits as the main development stage (1990s), and the stage of large-scale prevention and control (end of the 20th century to the present). He defined the governance methods and routes for the initial stage of small watershed governance, which began to sprout in China, and after the pilot projects in small watersheds had achieved results, they began to be promoted on a large scale. In the middle stage, due to the establishment and improvement of China’s economic system, a series of problems such as irrational project configuration, insignificant effects of measures, and low motivation of the masses appeared in the comprehensive management of small watersheds; by changing ideas and adjusting concepts, the comprehensive management of small watersheds was put back on the right track [14]. Later on, the state vigorously developed ecological construction, prompting the rapid development of comprehensive management of small watersheds. Research on comprehensive management of small watersheds has made great progress, paying more attention to both governance and development, ushering in a new process of economic development of small watersheds, and pushing the development of small watershed management to the market [15]. Since the concept of small watersheds was proposed based on source management, a large number of research results have appeared, mainly focusing on the construction of sediment transport models, ecology, landscape, hydrological monitoring, and the effect of comprehensive management [16]. The Soil and Water Resources Conservation Act (RCA), enacted in 1935, and the Watershed Protection and Flood Control Act, enacted in 1954, provide the legal basis for small watershed management in the United States, guiding the USDA in carrying out strategic natural resource planning and related small watershed management programmes, as well as establishing soil and water conservation demonstration and collaborative zones. Currently, the Natural Resources Conservation Service (NRCS) under the U.S. Department of Agriculture (USDA) is responsible for the implementation and management of small watershed governance and other related work. The first soil and water conservation district was established in the Brown Creek watershed in North Carolina, U.S.A. in August 1936, and since then, the traditional method of using soil and water conservation districts (or watersheds) as a unit, and assisting farmers to carry out soil and water conservation, has been formed [17]. In Europe, small watershed management has its origins in mountain remediation. In the first 30 years of the 20th century, a great deal of small watershed management work was carried out in Austria, Germany, Italy, Romania, Spain, Switzerland, Yugoslavia, etc. In 1902, Switzerland enacted a forest law, which not only gave a great impetus to the work of small watershed management, but also made the law the first one in the world to deal with the technology of small watershed management [18].

In previous studies, some scholars have explored the carbon sink function and mechanism of soil and water conservation [19], and the carbon sink role of relevant measures, especially plant measures [20,21]. However, there are few studies specifically on the comprehensive monitoring methods and accounting system of carbon sinking for soil and water conservation projects or small watershed comprehensive management [22]. Establishing a carbon sink monitoring and evaluation method for soil and water conservation projects is not only one of the prerequisites for the carbon sinks of soil and water conservation projects to enter the carbon trading market for trading or be used for voluntary emission reduction, but can also provide a scientific basis for the effective evaluation of the comprehensive management effect of the “community of life for mountains, rivers, forests, farmlands, lakes, and grasslands”, provide a transformation approach for “lucid waters and lush mountains are invaluable assets”, and is an important measure for the implementation of the carbon peak and carbon neutrality strategy.

In order to accurately calculate the carbon sink value of the soil and water conservation governance project, this paper takes the Luodi River small watershed in Changting County, Fujian Province, in the southern red soil hilly area, the leading area for high-quality development of soil and water conservation in China, as the object. After a comprehensive investigation of the soil and water loss governance situation since comprehensive management of the small watershed began, aiming at the two core carbon pools of soil and vegetation in the small watershed, an integrated monitoring method combining remote sensing, LiDAR and measured data is constructed, and the monitoring and evaluation of soil and vegetation carbon sinks are carried out. The aim is to provide techniques and methods for the implementation of dynamic monitoring and evaluation of the carbon sinks of the soil and water conservation project, and to provide theoretical and methodological support for the soil and water conservation project to participate in carbon emission rights trading and the research and formulation of relevant rules.

2. Materials and Methods

2.1. Study Area

The Luodi River small watershed is located in the south of Hetian Town, Changting County, Fujian Province, 26 km away from the county town, adjacent to Nanshan Town in the east, bordering Sanzhou Town in the south, and Cewu Town in the west, with a total area of 24.67 square kilometres. The altitude is 275~520 m, which is basin topography, high in the east and low in the west, narrow in the east-west direction, and the hills, low mountains and basin valleys below 500 m account for 76%, 19%, and 5%, respectively. The basin is located in the central subtropical monsoon climate zone, the average annual temperature is 18.8 °C, ≥10 °C active cumulative temperature is 5800 °C, and frost-free period is 270 days. The average annual rainfall is 1700 mm, with uneven rainfall distribution; April–June is the rainy season, with precipitation accounting for 51.8 per cent of the year; July–September is characterised by typhoons and torrential rains, with a multi-year average annual runoff depth of 1050 mm and a runoff coefficient of 0.6.

The watershed belongs to the granite erosion area with intense weathering. It is mainly mountain red soil with a thin soil layer, poor water and fertilizer retention, weak erosion resistance, and is extremely prone to soil and water loss. A remote sensing census in 1985 showed that the area of soil and water loss in the watershed was 12.46 km², and the rate of soil and water loss was as high as 50.5%. The vegetation was scarce with a coverage rate of less than 10%. The red soil was exposed and the area suffered from severe desiccation and heating.

Due to long-term anthropogenic disturbance, the original vegetation is mostly destroyed. After investigation, the vegetation in the area is mostly secondary Pinus massoniana, with a single species and simple structure; the understorey vegetation is mostly Dicranopteris pedata and Syzygium buxifolium; and the economic forests are mainly Castanea mollissima and Morella rubra.

Since 2001, the watershed has continuously implemented key soil and water conservation management, which has achieved good benefits, with the current soil and water conservation rate reaching 95.4 per cent. The land cover types in the small watershed that are combined with land use and management measures include Fertilised Pinus massoniana forests, Nurture and Management Pinus massoniana Forest, Horizontal terraces Pinus massoniana Forests, Mixed Needleleaf and Broadleaf Forests, Closed Management Forests, Castanea mollissima orchards and Morella rubra orchards, with an area of 62.36, 915.86, 359.00, 7.00, 429.44, 128.65, and 62.28 hm², respectively; the areas of untreated forest land and other land (including settlements, hardened roads, streams and farmland) were 7.06 and 651.28 hm², respectively (

Table 1. Soil and Water Conservation Measures Information in the Luo Di River Watershed.

Management Measures	Area (hm2)	Percent (%)
Fertilized Pinus massoniana Forest	62.36	2.38
Nurture and Management Pinus massoniana Forest	915.86	34.92
Horizontal terraces Pinus massoniana Forest	359	13.69
Mixed Needleleaf and Broadleaf Forest	7	0.27
Closed Management Forest	429.44	16.37
Castanea mollissima	128.65	4.90
Morella rubra	62.28	2.37
Baseline Scenario	7.06	0.27

).

Among them, according to Changting County Soil and Water Conservation Centre’s management records and visits and research, the area of Mixed Needleleaf and Broadleaf Forest is small and Pinus massoniana is the dominant species, so in order to accelerate succession and improve the quality of the forest, small saplings of Liquidambar formosana (diameter at breast height less than 2 cm) are planted in the forest and labelled as Mixed Needleleaf and Broadleaf Forest. Castanea mollissima orchards and Morella rubra orchards have a certain amount of organic fertiliser and a small amount of chemical fertiliser (digging holes for fertiliser) applied every year. During the project period, necessary soil and water conservation measures were carried out in the small watersheds, and no forest felling or thinning was carried out, except for planting trees for renewal in the Morella rubra orchard (Figure 1).

2.2. Small Watershed Carbon Pool Division and Baseline Scenario Determination

The Luodi River small watershed is divided into two carbon pools, the plant carbon pool and the soil carbon pool, according to its ecosystem structure and major land use types, and the dynamics of each pool is monitored and evaluated in accordance with the seven land cover types mentioned above. According to the principle of conservatism in carbon sink measurement, other land cover types (including settlements, hardened roads, streams and farmland, etc.) were not included in the monitoring and evaluation. Greenhouse gases emissions from fertiliser application were not included in this study [23].

The Luodi River small watershed began to undergo comprehensive management in early 2001, with most of the mountainous terrain being scattered “Old-man Pines” and Castanea mollissima and Morella rubra orchards taking shape. Because of the ex post facto monitoring, on the basis of the field survey, combined with the soil and water conservation management plan and implementation records of Changting County, it was determined that the baseline scenario would be a piece of untreated control land in the watershed, with scattered Pinus massoniana, with an area of 7.06 hm².

2.3. Technical Route for Monitoring and Evaluating Carbon Sink Capacity of a Small Watershed

The monitoring and evaluation of the carbon sink capacity of a small watershed mainly involve four key steps: data collection and preprocessing, field sampling and processing, vegetation and soil carbon stock modelling, and analysis of vegetation and soil carbon sink capacity. The technical route is illustrated in Figure 2.

2.4. Data Collection and Preprocessing

2.4.1. Field Plot Layout and Survey Sampling

Field plots were laid out using a systematic grid point method based on kilometre grids [24]. Adjustments were made near obstacles when necessary. A total of 34 plots were established, including 26 Pinus massoniana sample plots (including the Closed Management Forests, etc.), 5 Castanea mollissima sample plots, 2 Morella rubra sample plots (Figure 1), and 1 untreated forest land sample plot (baseline scenario). Each sample plot measures 20 m × 20 m.

The field survey was carried out in August 2022. During the survey, each tree was checked and the species and diameter at breast height (DBH) of individual trees were recorded in detail, as well as the age, degree of depression, planting method, forest condition and other stand factors of the sample plots. The DBH and tree species data were used for calculating individual tree carbon stocks, while other indicators were used for assessing and establishing remote sensing carbon stock models [25]. In each vegetation sample plot, 3 sampling points were evenly set up, soil sampling avoided fertiliser holes, and 0~20 cm soil samples were collected. The soil samples from the three sampling points were mixed thoroughly, and 200~300 g was taken from them by tetrad method and brought back to the laboratory, placed in a cool place to air-dry, picking off plant roots (≮ 2 mm) and gravels in the soil, and ground through a sieve of 0.150 mm to be measured. The volume weight of each soil layer was determined by the ring knife method, and soil organic carbon was determined by oxidative external heating with potassium dichromate.

2.4.2. Extraction of Data on Various Management Measures for Vegetation Carbon Pools

① Plant Carbon Stock Calculation Model.

Adopting the carbon measurement model of forest stand biomass with its carbon content rate (

Table 2. Biomass Model Formula and Carbon Content Coefficients for Each Tree Species.

Tree Species	Biomass Calculation Formula	Carbon Content Rate	References
Pinus massoniana	WAboveground = 482.4744508D0.141 × V	0.4596	Xiang Jia et al. [26]
	V = 0.000219756D2.178
	WBelowground = WAboveground × 0.08154D0.28646
Castanea mollissima	WTrunk = 50.0544 × lnD − 80.049	0.4796	Isochronous Growth Equation of Dominant Tree Species (Groups) in Fujian Province [27]
	WBranches = 18.6683 × lnD − 30.5257
	WLeaves = 7.247 × lnD − 11.907
	WRoots = 14.698 × lnD − 22.963
Morella rubra	W = 0.010 (Dground Diameter)2.995	0.4796	Peng Jianjian et al. [28]

), the carbon stock of each sample tree was calculated through the diameter at breast height and tree species investigated in the sample plot, and the carbon stock of the sample plot was cumulatively obtained (

Table 3. Statistical Results of Field Survey.

Management Measures	Code	Sample Size	Average Breast Diameter (cm)
Fertilized Pinus massoniana Forest	FP	2	8.90
Nurture and Management Pinus massoniana Forest	MP	15	10.86
Horizontal terraces Pinus massoniana Forest	BP	6	10.08
Mixed Needleleaf and Broadleaf Forest	LP	—	—
Closed Management Forest	EF	3	10.32
Castanea mollissima	LC	5	19.18
Morella rubra	WB	2	4.64
Baseline Scenario	CK	1	7.30

).

② Remote Sensing Image Collection and Processing.

The study area is a hilly and mountainous area in the south, with simultaneous water and heat, and a complex subsurface, which makes it extremely difficult to obtain high-quality remote sensing data with simultaneous phases and no cloud cover. In order to ensure image consistency and data quality, and at the same time, no significant changes in ground cover and vegetation types occurred between the image acquisition time and the ground survey time, two images of GF-6 and Sentinel-2, both dated 15 February 2021, which were similar to the time of the field survey, were finally selected.

The Gram-Schmidt method was used to generate fused images with a spatial resolution of 2 m. The optimal segmentation scale was determined to be 150 using the multi-scale parameter evaluation tool ESP of the eCognition (V9.0) software, and the shapes and smoothness were set to 0.2 and 0.5, respectively. The preprocessed fused images were used for the classification of the surface cover types mentioned later.

③ Airborne LiDAR Data Collection and Processing.

In early October 2022, LiDAR (light detection and ranging) data for the entire Luodi River watershed was acquired through a helicopter equipped with a Riegl VUX-240 LiDAR scanner [29]. The manufacturer of the Riegl VUX—240 LiDAR scanner is Riegl Laser Measurement Systems GmbH. The company is located in Horn, Austria. The data were processed using LiDAR360 software (V7.0) to obtain a digital elevation model (DEM) with a spatial resolution of 1 m and a canopy height model (CHM).

2.5. Evaluation Method for Vegetation Carbon Pool Carbon Stock

2.5.1. Vegetation Type Classification

Based on the aforementioned processed images, commonly used spectral and textural variables were extracted and surface cover types were classified using the random forest classification method [30,31]. Combining the field survey data and research objectives, the surface cover was classified into Pinus massoniana forests (including Closed Management Forest, etc.), Castanea mollissima, Morella rubra, and other utilisation types (including settlements, hardened pavements, streams, and farmland), with an overall classification accuracy of 92.86% and a kappa coefficient of 0.91.

2.5.2. Modelling Vegetation Carbon Storage in 2022

A carbon storage estimation model was established by correlating vegetation carbon storage in plots with remote sensing variables.

① Extraction of Remote Sensing Variables.

Considering the plot size of 20 m × 20 m from field surveys, remote sensing variables were extracted using a 1 m resolution canopy height model (CHM). Within each 20 × 20 pixel area, maximum, mean, standard deviation, variance, and height percentiles (H_10, H₂₀^…H₉₈) of tree heights were extracted as remote sensing variables.

② Establishment of Regression Equations.

The field-surveyed carbon storage in plots was used as training samples along with the CHM variables extracted within the plot boundaries to establish stepwise regression equations. Initially, a stepwise regression equation was built using the entire set of plot carbon storage data to select overall variables. Then, based on management measures (prohibition, fertilization, nurturing, soil levelling, and baseline scenarios) and forest types (Pinus massoniana, Castanea mollissima, and Morella rubra), the training samples were divided into 8 groups, each with its own stepwise regression equation for variable selection.

③ Development of Carbon Storage Models.

Variables selected into the equations (overall variables: H₄₀, H_ME; stratified variables: height percentiles H₂₀, H₃₀, H₅₀, H₉₈, H_std) were used as variables for establishing the carbon storage models using a two-factor Bayesian stratified model. Model accuracy validation was conducted using leave-one-out cross-validation, with model validation accuracy exceeding 84%. Details of variables used in the forest carbon storage models and model accuracy are presented in

Table 4. Forest Carbon Storage Estimation Models and Accuracy Analysis.

Model	Variables *	Modelling R2	Validation R2	RMSE	RMSEr
Two-Factor Stratified Bayesian	Overall: H40, HME	0.94	0.84	5.51 t/hm2	24.87%
	Stratification: H20, H30, H50, H98, Hstd

* Note: H_ME represents mean, H_std represents standard deviation; H₂₀, H₅₀, H₉₈ represent height percentiles.

.

The above process was implemented using the ‘brms’ package in R, which internally utilizes the Stan program for computations.

2.5.3. Modelling Vegetation Layer Carbon Storage from 2001 to 2022

Using the random forest method, a carbon stock model was constructed by extracting remote sensing variables such as vegetation cover products, topographic factors (elevation, slope, slope direction) and other remote sensing variables from remote sensing images in 2001, 2005, 2010, 2015 and 2022 as variables with the carbon stock of the sample plots in 2022. The model was applied to 2001/2005/2010/2015 and the spatial distribution of vegetation carbon stocks in 2001/2005/2010/2015 was obtained. The process was done by the random Forest package in the R (V4.4.1) program. In particular, the vegetation cover products for 2001, 2005, 2010, 2015, and 2022 were calculated using Landsat imagery based on the NDVI (normalised difference vegetation index) with a confidence interval of [5%, 95%] using the image element binary model [32,33,34].

2.6. Evaluation Method for Carbon Stock in Soil Carbon Pools and the Ability to Conserve Soil and Carbon

2.6.1. Baseline Scenario Carbon Density Setting

The Luodi River small watershed baseline scenario has minimal vegetation and exogenous carbon inputs, and the presence of soil erosion has resulted in lower carbon density. According to the principle of conservatism, it can be assumed that there is no change in soil carbon density from 2001 to 2022, and the measured carbon density in August 2022 will be used as a proxy for soil carbon density and organic carbon content before the implementation of the comprehensive management project (2001), with a soil organic carbon content of 5.00 g/kg and a carbon density of 11.35 t/hm².

2.6.2. Soil Carbon Storage Evaluation from 2001 to 2022

Based on the baseline scenario plots and sampling plots, the inverse distance weighting method is used to spatially interpolate soil carbon storage, obtaining the spatial distribution of soil carbon storage with a resolution of 20 m in 2022. The spatial distribution of soil carbon storage for the years 2005, 2010, and 2015 is calculated by progressively increasing the difference between the carbon storage in 2022 and 2001 on a yearly basis.

2.6.3. Evaluation of the Capacity of Various Management Measures to Conserve Soil and Carbon

Comprehensive management of small watersheds for soil and carbon conservation refers to the total amount of carbon consolidated and stored in the watershed by the soil conservation benefits of various management measures after the implementation of comprehensive management, which is mainly embodied in the organic carbon in the soil stored in the small watershed [35]. The calculation formula is as follows.

$$\begin{gathered} C_{S-sw}=\sum _{i=1}^n{y}_i\times \left(Q_{ti}\times {\omega }_{bs}\right)\times {10}^{-3} \\ =\sum _{i=1}^n{y}_i\times A_i\times \left(M_{bs}-M_{swi}\right)\times {\omega }_{bs}\times {10}^{-3} \end{gathered}$$

(1)

where C_S-sw is the total soil carbon conservation amount in the watershed (in tons of C); y_i is the operating years of comprehensive management (in years); Q_ti is the soil conservation amount of the ith conservation measure (reduction in soil erosion, in tons per year); ω_bs is the baseline scenario soil organic carbon content (in g/kg of C); A_i is the area of the ith conservation measure (in hectares); M_swi is the soil erosion modulus under the ith conservation measure (in tons/(km²·year)); M_bs is the baseline scenario soil erosion modulus (in tons/(km²·year)); n is the number of soil conservation measures.

After consulting relevant data (actual observation data of runoff subzones in the Youfang small watershed in Changting County from 2014 to 2021) and considering the integrated governance plan for the Luodi River small watershed, the estimated soil conservation quotas for various governance measures, including FP, MP, BP, LP, EF, LC, and WB, are 52.25 ± 11.84, 52.25 ± 11.84, 51.88 ± 11.87, 51.88 ± 11.87, 52.40 ± 11.81, 52.40 ± 11.81, and 52.19 ± 11.85 t/(hm²·a), respectively.

3. Results

3.1. Spatial Distribution of Carbon Density in the Watershed from 2001 to 2022

The spatial distribution of carbon density in the Luodi River watershed shows significant differences (Figure 3), mainly concentrated in the range of 25 to 35 t/hm². Areas with high carbon density (>65 t/hm²) are sporadically distributed, mainly in the Nurture and Management Pinus massoniana Forest and Castanea mollissima Forest. Regions with low carbon density (<20 t/hm²) are found in the southern part of the study area, mainly in the Morella rubra Forest.

The carbon density of vegetation carbon pools is concentrated in the range of 15 to 35 t/hm². Areas with high carbon density (>65 t/hm²) are sporadically distributed, primarily in the Nurture and Management Pinus massoniana Forest. Regions with low carbon density (<5 t/hm²) are located in the southern part of the study area, mainly in the Morella rubra Forest.

The carbon density of soil carbon pools in the 0~20 cm layer is concentrated between 10 and 30 t/hm². Areas with high carbon density (>30 t/hm²) are mainly distributed in the southeast corner and central-northern parts, primarily in the soil of Nurture and Management Pinus massoniana Forest and Castanea mollissima Forest. Regions with low carbon density (<10 t/hm²) are mainly located in the southern part, primarily in the soil of Morella rubra Forest.

From 2001 to 2022, there has been a noticeable overall increase in the spatial distribution of carbon density in the watershed. Compared to the baseline scenario, areas where soil and water conservation measures have been implemented show a faster growth rate in carbon density in the watershed.

3.2. Watershed Carbon Density and Carbon Pool Changes

By analysing and calculating the data collected through field surveys, remote sensing extraction and soil and water conservation experimental observations, the main data on soil carbon pool, vegetation carbon pool and the capacity of various management measures to conserve soil and carbon, etc., are finally obtained, as shown in

Table 5. Calculation Results of Carbon Sinking in the Luodi River Watershed.

Management Measures	Soil Carbon Density/(t·hm−2)
	Year 2001	Year 2005	Year 2010	Year 2015	Year 2022
FP	11.35	13.35	15.85	18.34	21.84
MP	11.35	13.01	15.10	17.18	20.09
BP	11.35	12.34	13.58	14.82	16.55
LP	11.35	12.89	14.82	16.75	19.45
EF	11.35	13.03	15.13	17.22	20.16
LC	11.35	13.05	15.16	17.28	20.25
WB	11.35	11.78	12.32	12.86	13.61
CK	11.35	11.35	11.35	11.35	11.35
	Vegetation Carbon Density/(t·hm−2)
	Year 2001	Year 2005	Year 2010	Year 2015	Year 2022
FP	1.58	4.48	8.11	11.73	16.81
MP	1.70	4.21	7.34	10.48	14.87
BP	3.62	6.08	9.16	12.24	16.55
LP	3.16	5.83	9.18	12.52	17.20
EF	4.04	5.19	6.64	8.08	10.10
LC	7.81	11.09	15.19	19.30	25.04
WB	6.73	7.93	9.43	10.93	5.88
CK	0.55	1.47	2.62	3.78	5.39

.

The Luodi River small watershed soil carbon density was 11.35 t/hm² in 2001, and the soil carbon density was 19.68 t/hm² in 2022, which was an improvement of 8.33 t/hm²; the vegetation carbon density was 3.33 t/hm² in 2001, and the value was 14.86 t/hm² in 2022, which was an improvement of 11.53 t/hm². Based on the carbon stock of various management measures, calculation of carbon stock found that the soil carbon pool was 2.27 × 10⁴ and 3.93 × 10⁴ t in 2001 and 2022, respectively; and the vegetation carbon pool was 0.66 × 10⁴ and 2.97 × 10⁴ t, respectively. The soil carbon pools were larger than the vegetation carbon pools during the same period, which indicated that the soil carbon pools contributed more to the small watershed carbon pool capacity.

From 2001 to 2022, the carbon stock in small watersheds increased from 2.93 × 10⁴ t to 6.90 × 10⁴ t, an increase of 3.97 × 10⁴ t (Figure 4). Among them, the soil carbon stock increased by 1.66 × 10⁴ t, with an average annual growth rate of 2.66%, accounting for 41.81% of the increase in carbon stock in small watersheds; and the vegetation carbon stock increased by 2.31 × 10⁴ t, with an average annual growth rate of 7.39%, accounting for 58.19% of the increase in carbon stock in small watersheds. The average annual growth rate of vegetation carbon stock is higher than that of soil, which plays an important role in enhancing the carbon pool of small watersheds.

Therefore, it can be concluded that during the 21 years of comprehensive management in the Luodi River watershed, the soil carbon density was higher than the vegetation carbon density. However, the increase in the vegetation carbon pool was greater than that of the soil carbon pool.

3.3. Changes in Carbon Sink Capacity in the Watershed

Compared with the period before the project implementation (2001), in 2005, the soil carbon density of various management measures in the Luodi River small watershed varied from 0.43 to 2.00 t/hm², and the vegetation carbon density varied from 1.15 to 3.28 t/hm²; in the Luodi River small watershed in 2010, the change of soil carbon density of various management measures ranged from 0.97 to 4.50 t/hm², and the change of vegetation carbon density ranged from 2.60 to 7.38 t/hm²; in the Luodi River small watershed in 2015, for various management measures, soil carbon density changed by 1.51~6.99 t/hm², and the change of vegetation carbon density was 4.04~11.49 t/hm²; and in 2022, the Luodi River small watershed soil carbon density of various management measures varied from 2.26 to 10.49 t/hm², and the vegetation carbon density varied from −0.85 to 17.23 t/hm².

Among them, Castanea mollissima and Fertilised Pinus massoniana Forests have the largest change in carbon density, with strong carbon sequestration capacity; in the calculation results of the Luodi River small watershed in 2022, the change in the carbon density of Morella rubra is negative, mainly due to the fact that the poplar was renewed around 2019. Since the carbon stock data of Morella rubra forest at the time of renewal could not be obtained, it could not reflect the real situation of the carbon sink of Morella rubra forest land. If the average value of the vegetation carbon density of other management measures in the small watershed was taken as the vegetation carbon density of Morella rubra forest land, that is, the vegetation carbon sink of this small plot was 821.71 t, and the soil carbon sink was 224.55 t, then the value of that carbon sink was 1046.26 t.

Carbon sink measurement is based on the premise of conservatism and objectivity, so in this study, the carbon sink of Morella rubra woodland was not included in the total regional carbon sink.

Carbon sink capacity is defined as the net increase in the carbon pool of a project scenario over time relative to the baseline scenario. Compared to the change in carbon density in the baseline scenario, the increase in carbon density of soil ranges from 2.26 to 10.49 t/hm² and the increase in carbon density of vegetation ranges from 1.22 to 12.39 t/hm² over the period 2001~2022.

Based on the increase in carbon density and the area of various management measures, it can be calculated that the carbon sink value of soil in the small watershed ranges from 56.68 to 8004.58 t, and that of vegetation ranges from 64.38 to 7629.08 t, among which the highest carbon storage is found in the nurturing and management of Pinus massoniana, which is mainly due to the fact that the area of nurturing and management of Pinus massoniana is much larger than the area of other management measures.

However, in terms of the increase in carbon density, Castanea mollissima and fertilised Pinus massoniana forests were elevated by 26.13 t/hm² and 25.72 t/hm², which were 1.19 times and 1.17 times higher than that of the nursed and cared Pinus massoniana (21.91 t/hm²).

The total carbon sink of the small watershed can be deduced from the carbon sinks of various management measures to be 2.90 × 10⁴ t (

Table 6. Changes in Carbon Sequestration Capacity of the Luodi River Small Watershed.

Year	Management Measures	Increment in Soil Carbon Density /(t·hm−2)	Increment in Vegetation Carbon Density/ (t·hm−2)	Soil Carbon Sequestration/(t, as C)	Vegetation Carbon Sequestration/(t, as C)	Total Carbon Sequestration/ (t, as C)
2005	FP	2.00	2.90	124.59	123.52	248.12
	MP	1.66	2.51	1524.68	1454.90	2979.58
	BP	0.99	2.46	355.58	553.89	909.48
	LP	1.54	2.67	10.80	12.28	23.07
	EF	1.68	1.15	720.64	100.61	821.26
	LC	1.70	3.28	105.58	147.10	252.68
	WB	0.43	1.20	55.38	36.02	91.40
	CK	0.00	0.92	0.00	0.00	0.00
	Total			2897.26	2428.33	5325.59
2010	FP	4.50	6.53	280.33	277.93	558.26
	MP	3.75	5.64	3430.53	3273.53	6704.06
	BP	2.23	5.54	800.07	1246.26	2046.32
	LP	3.47	6.02	24.29	27.62	51.91
	EF	3.78	2.60	1621.45	226.38	1847.83
	LC	3.81	7.38	237.56	330.98	568.54
	WB	0.97	2.70	124.61	81.05	205.66
	CK	0.00	2.07	0.00	0.00	0.00
	Total			6518.84	7892.07	14,410.91
2015	FP	6.99	10.15	436.07	431.71	867.78
	MP	5.83	8.78	5336.39	5083.00	10,419.38
	BP	3.47	8.62	1244.55	1935.03	3179.58
	LP	5.40	9.36	37.79	42.90	80.69
	EF	5.87	4.04	2522.25	347.85	2870.10
	LC	5.93	11.49	369.53	514.23	883.77
	WB	1.51	4.20	193.83	124.79	318.62
	CK	0.00	3.23	0.00	0.00	0.00
	Total			10,140.41	8479.51	18,619.92
2022	FP	10.49	15.23	654.11	647.87	1301.98
	MP	8.74	13.17	8004.58	7629.08	15,633.65
	BP	5.20	12.93	1866.82	2904.34	4771.16
	LP	8.10	14.04	56.68	64.38	121.06
	EF	8.81	6.06	3783.38	523.92	4307.30
	LC	8.90	17.23	1144.99	1593.98	2738.96
	WB	2.26	−0.85	140.76	0.00	140.76
	CK	0.00	4.84	0.00	0.00	0.00
	Total			15,651.31	13,363.57	29,014.88

), of which the soil carbon sink is 1.57 × 10⁴ t, and the vegetation carbon sink is 1.34 × 10⁴ t, which accounted for 53.74% and 46.26% of the total carbon sink, respectively. This indicates that the soil sink is an important part of the carbon sinking capacity of integrated small watershed management.

4. Discussion

In the Luodi River small watershed, integrated soil and water conservation management was implemented from 2001–2022. During this period, the contribution of the management measures to the increase in carbon stocks varied significantly depending on the size of the managed area, the type of measure, and other factors.

In this study, the area share of nursed and managed Pinus massoniana forests was the largest among all management measures (42.90%), and its area advantage made this measure outstanding in terms of soil and carbon conservation, carbon storage, carbon sink increment, and total carbon sinking. Its carbon conservation reached 222.23 t/a (in terms of C), carbon stock was 29,881.01 t, carbon sink increment reached 18,726.92 t, and carbon sunk totalled 15,633.65 t. In contrast, Mixed Needleleaf and Broadleaf Forest performed poorly in all indicators due to its small area.

Not only that, there are also significant differences in the distribution of carbon pools among different management measures. For example, the soil carbon pools in Castanea mollissima (LC) and Pinus massoniana (FP) forests were altered in terms of physical structure and nutrient status due to the implementation of integrated measures such as land preparation, afforestation and fertilisation, which enhanced the carbon sequestration capacity of the soil; as for the vegetation carbon pool, conservation measures, selection and allocation of tree species will affect the growth, community structure and photosynthetic efficiency of the vegetation, which in turn will affect the carbon fixation capacity of the vegetation.

The spatial distribution of carbon stocks in small watersheds is closely related to the distribution of soil and water conservation measures. In terms of vegetation, the high carbon density areas are mainly Pinus massoniana woodlands; in terms of soil, the high carbon density areas were mainly Castanea mollissima woodland and nurturing and caring Pinus massoniana woodland, while the low carbon density areas of both were mainly Morella rubra woodland. This spatial distribution pattern not only reflects the differences in carbon sink capacity under different land use types and governance measures, but is also closely related to factors such as topography and soil texture. For example, areas with high altitude and steep slopes may have relatively low carbon stocks in vegetation and soils due to the high risk of soil erosion, while carbon stocks are relatively high in areas with flatter terrain, fertile soils and proper management measures.

Among the seven management measures, the soils of Castanea mollissima forest (LC) and fertilised Pinus massoniana forest (FP) showed stronger carbon sequestration capacity and higher carbon sequestration efficiency, with carbon densities elevated by 26.13 t/hm² and 25.72 t/hm², respectively, with an increase of 199.01% and 136.41%, respectively. This remarkable enhancement of carbon sequestration capacity is, on the one hand, attributed to the fact that fertilisation provides sufficient nutrients to the soil, promotes plant growth and photosynthesis, and increases the absorption and fixation of atmospheric carbon dioxide by the plants; on the other hand, reasonable forest management measures also help to optimise the structure of the forest stand, and improve the productivity and carbon sink capacity of the forest stand. In addition, the deep-rooted nature of Castanea mollissima forests and the broad adaptability of Pinus massoniana forests give them a unique advantage in absorbing and storing carbon in the soil.

The basic function of soil and water conservation and management measures to preserve soil and hold water is of great significance to carbon sequestration and the enhancement of carbon sink incrementation. During the period 2001~2022, the carbon stock of small watersheds increased by 3.97 × 10⁴ t, of which vegetation carbon stock contributes 58.02% and soil carbon stock contributes 41.98%. Compared with the baseline scenario, the carbon sinking generated by the small watershed is 2.90 × 10⁴ t, of which the contribution of soil and vegetation is 53.74% and 46.26%, respectively. It can be seen that the integrated soil and water erosion management significantly enhanced the carbon stock of vegetation and soil carbon pools, and played a significant role in carbon accumulation. Soil sinks become an important carbon sink and carbon stock component in small watersheds with serious soil erosion.

However, current governance measures still have certain limitations and room for development. For example, although some of the governance measures have achieved significant carbon sinking effects in the short term, their sustainability and stability in the long term still need to be further studied and verified; the synergistic mechanism between different governance measures is not yet completely clear, and in-depth exploration is needed to achieve a more optimal governance scheme. In addition, the potential impacts of climate change and land use change on the carbon sink capacity of small watersheds need to be further assessed and quantified [36,37].

5. Conclusions

Through the monitoring of carbon stock changes in soil carbon pools and vegetation carbon pools in the Luodi River small watershed, this study analyses and evaluates comprehensively and in depth the carbon sink benefits of integrated soil and water erosion management.

The Luodi River small watershed was used as an object in this study, and the carbon sinks generated in the small watershed under 21 years of continuous integrated management from 2001 to 2022 were evaluated by using scientifically sound methods of baseline selection, carbon layer delineation, field monitoring and carbon stock modelling. The results of the study show that the carbon stock of small watersheds has increased significantly under the continuous soil and water conservation management measures. The results not only provide a scientific basis for the ecological construction and sustainable development of small watersheds, but also provide an important reference for other similar soil and water conservation carbon sink projects in terms of the selection of technical methods, data monitoring and analyses, and model construction and application.

From 2001 to 2022, the Luodi River small watershed has significantly increased its carbon stock through the continuous implementation of various soil and water conservation measures. The Luodi River small watershed in Changting County has a large carbon sink capacity influenced by soil and water conservation management measures, and there are also spatial differences in carbon density within the small watershed, with high carbon density areas distributed sporadically and low carbon density areas located in the southern part of the study area. This spatial distribution pattern provides a direction for further optimising the layout and implementation of soil and water conservation management measures.

A scientific and reasonable mix of management measures is the key to enhancing the carbon sink capacity of small watersheds. In the future, in the soil and water conservation and sink enhancement action, on the one hand, the proportion of Castanea mollissima forests (LC) and fertilised Pinus massoniana forests (FP) and other measures with higher carbon sequestration capacity and sink efficiency can be appropriately expanded; on the other hand, in the process of optimising vegetation measures, measures such as engineering land preparation and reasonable application of organic fertilizer can be scientifically implemented to further consolidate the role of carbon sinks in small watersheds and enhance the capacity of small watersheds to increase sinking capacity. In addition, in-depth investigation of the synergistic mechanism between different management measures and the influence of climate change and land use change on the carbon sink capacity of small watersheds is of great significance to achieve the sustainable development of small watershed ecosystems and maximise their carbon sinking function.

Continuously improving and developing the monitoring and assessment system for carbon sinks in soil and water conservation in small watersheds will help to quantify more accurately the carbon sink benefits of soil and water conservation measures, and provide strong support for the formulation of scientific and reasonable ecological protection policies and carbon trading market rules. It will also promote the practical transformation of the concept of “green mountains are golden mountains”, and contribute to the realisation of the global carbon peak and carbon neutrality goal.