Introduction

The middle reaches of the Yellow River are the main source of sediment for the Yellow River1. Strong soil erosion leads to regional soil and water sediment loss, soil resource destruction, ecological environment deterioration, soil fertility decline, and other related problems2,3. Therefore, the ecological protection and high-quality development of the Yellow River Basin are highly valued by the nation. In order to curb the serious soil erosion, China has adopted a series of treatment measures, such as returning farmland to forest and building terraces, and has effectively carried out soil and water conservation in the Yellow River Basin by using an integrated management model combining biological, engineering, and farming measures4. In October 2021, the Chinese government issued Outline of the Plan for Ecological Protection and High-Quality Development of the Yellow River Basin5, which highlighted the importance of attaining soil and water conservation in the Loess Plateau, continuously consolidating the results of returning farmland to forest or grassland and returning grazing land to grassland, and intensifying the comprehensive efforts to control soil erosion. The soil erosion control in the Yellow River Basin has entered a new stage6. Therefore, the quantitative assessment of the soil erosion control effect in the middle reaches of the Yellow River is an important reference for the development of new stage control measures.

There are various evaluation methods and indicator systems internationally used to assess the current status of soil erosion and its control effectiveness7,8. To reasonably evaluate the current status of soil erosion in research areas, scholars at home and abroad would select appropriate soil erosion models and calculate them by considering various influencing factors. Soil erosion models can be broadly classified into three categories: empirical statistical models, physical causal models, and distributed soil erosion models9. Among them, the typical representative of empirical models is the Universal Soil Loss Equation (USLE) proposed by Wischmeier and Smith10. Building on this, scholars have also established empirical models tailored to the characteristics of different regions. With the support of erosion models and erosion data, scholars have adopted more comprehensive methods to evaluate the effectiveness and measures of soil erosion control. Sutherland11 evaluated the effect of landslide erosion control by calculating the erosion rate and sediment yield. Jayanath and Gamini12 explored factors affecting erosion control from a socioeconomic perspective, highlighting that population, policy, and farmers’ income significantly impact erosion control in developing countries. Ferko et al.13 focused on erosion control measures in southern Mali, emphasizing the importance of reconstructing the baseline of erosion control and examining the erosion time period. Su et al.14 established an evaluation index system for small basin control degree, using hierarchical analysis from three perspectives: soil and water conservation, socioeconomic development, and ecological service functions. Along with the establishment of the soil erosion evaluation system, relevant indices have emerged for the quantitative assessment of soil erosion management, such as the soil tolerance loss15,16 and the soil erosion management degree17. Water and soil conservation technologies are becoming increasingly mature, with the factors affecting soil erosion being key elements in implementing control measures. Scholars have also quantitatively evaluated the effectiveness of different control scenarios. Wang Kai et al.18 used the Soil Erosion Potential Danger Index (SEPDI) to assess the magnitude of potential soil erosion hazards in areas with different slopes or land types. Jia Chen et al.19 evaluated the controlling effect of land use efficiency (LULC) on soil erosion in red soil hilly regions of southern China, finding that bare land had the highest runoff and soil loss, while cultivated land and grassland had the lowest runoff and soil loss. Ping Li et al.20 used a biogeochemical model to simulate natural vegetation dynamics and evaluate the control effect of regional vegetation restoration on soil loss. In addition to quantitative evaluations of various influencing factors for assessing control effectiveness, indicators for overall management effects on water and soil loss are gradually improving. For the level of soil erosion control in small basins, the term "soil erosion control degree" is usually used to characterize the level of soil erosion control13, which is expressed in the terminology of soil and water conservation (GB/T 20,465-2006)21 as "the ratio of the treated area to the eroded area in a small basin". The treated area in a small basin is the sum of the area where soil and water conservation measures are implemented, including the area of forested land, grassland, basic farmland, and intercepted ditches, etc. In some cases, the soil erosion control degree (SECD) may reach the maximum value of 1, yet soil erosion still occurs. Therefore, this index can only serve as an idealized measure in the soil erosion control process and does not accurately reflect the actual improvement achieved by control measures in specific areas. Based on this problem, some scholars22 proposed the concept of the soil erosion control degree (SECD) through the study of the soil erosion on the Loess Plateau, that is, "the ratio of the minimum possible soil erosion modulus to the current soil erosion modulus". Gao et al.23 carried out a study on the potential of soil erosion control in the Loess Plateau using the SECD. They assumed the suitable distribution areas for different soil and water conservation measures, where each region theoretically would complete all the control work and keeps the soil erosion modulus under a reasonable level. The amount of soil and water conservation measures under this circumstance is referred to as the capacity of soil and water conservation measures. The minimum possible soil erosion modulus is the one under this capacity of soil and water conservation measures. The suitable distribution areas of different land use modes in different regions had spatial variability, which requires a large amount of fieldwork data. At the same time, the basis of division needed to be adapted to local conditions, and the results of the division lacked a universal scientific basis. So, the minimum soil erosion modulus is difficult to determine and the promotion of which is hindered. In order to overcome this difficulty, this paper introduces the maximum possible soil erosion modulus to calculate the degree of soil erosion control. The maximum possible soil erosion modulus is considered as the soil erosion modulus assuming that both the supporting-practice factor (P) and the cover-management factor (C) reach their maximum values under a long time series. The calculation of the maximum probable soil erosion modulus does not require detailed soil and water conservation data to achieve an assessment of the extent of soil erosion control.

With the increasing attention to soil erosion, soil erosion control measures have achieved remarkable results. At the same time, it also means that it is difficult to provide a reference for further adjustment of soil erosion control measures by simply and roughly assessing the degree of soil erosion control. The SECD can be used as a grid unit to evaluate the degree of soil erosion control in the study basin. The value of SECD is between 0-1. The closer the SECD is to 1, the better the degree of soil erosion control. On the contrary, the closer the SECD is to 0, the worse the degree of soil erosion control, and the soil erosion control measures need to be further adjusted. Therefore, SECD provides an important reference value for the formulation and adjustment of soil erosion control measures.

Effective soil erosion management in the Yellow River Basin is the main content of ecological protection in the Yellow River Basin, as well as the basic guarantee of the high-quality development of the Yellow River. The Dali River Basin in the middle reaches of the Yellow River, as a key tributary of the concentrated coarse sand coming into the Yellow River Basin24, is taken as study area. The aim of this paper is (1) to analyze the spatial and temporal distribution characteristics of the soil erosion modulus in the basin from 2001 to 2020, (2) to calculate SECD of the Dali River Basin in 2020, quantitatively assess the level of soil erosion control in the basin, and (3) to analyze the control degree and its influencing factors such as the annual rainfall, land use type, slope, and so on. The results will provide a reference for the soil erosion management and ecological protection, and new ideas for assessing soil erosion management level.

Study area and datasets

Study area

The Dali River Basin is the second largest tributary of the Wu Ding River which is a tributary of the Yellow River. It is located between 37°30′-37°56′ N latitude and 109°14’-110°13′ E longitude, with a total length of 159.9 km, a basin area of 4761 km2, a height difference of 503.3 m, and a gradient of 3.16‰ (Fig. 1).

Fig. 1
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Location of the Dali River Basin. Figure 1 was using ArcGIS10.8 (https://soft.wxqilinz.cn/gis-jb61d/)software. Data source: Provincial-level administrative divisions in China (https://github.co-m/GaryBikini/ChinaAdminDivisonSHP); Vector data of China’s fifth-level water system (https://www.rserforum.com/).

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It flows southeast through Hengshan County, Zi Zhou County, and Sui De County and is injected into the Wu Ding River in the northeast of Sui De County. The Dali River Basin belongs to a typical continental monsoon climate, characterized by a dry spring, rainy summer, a large temperature differences between day and night in autumn, and a cold and dry winter. It contains fragmented terrain, sparse vegetation, serious soil erosion, and a ridge. The basin contains fragmented terrain, sparse vegetation, serious soil erosion, and ridges, as well as a hilly gully landform characterized by ravines and gullies crisscrossed by washes on the valley floor after long-term geological erosion25. There are two types of sediment in the Dali River Basin: bedload and suspended sediment. The high sand content is mainly concentrated in July and August, which is the main source of coarse sediment in the Yellow River Basin.

Data

The data required to calculate the soil erosion modulus and control degree of the Dali River Basin mainly include: monthly and annual rainfall data for the Dali River Basin from 1991 to 2020, with a spatial resolution of about 1 km, based on comprehensive scientific research on the Qinghai-Tibet Plateau26; soil data for the Dali River Basin obtained from the Harmonized World Soil Database (HWSD) with a spatial resolution of 30 m27; Digital Elevation Model (DEM) data from ASTGTM with a spatial resolution of 30 m28; maximum annual average NDVI values for the Dali River Basin from 1991 to 2020, obtained from the Google Earth Engine (GEE) platform with a spatial resolution of 30 m29; and annual land cover data for the Dali River Basin from 1991 to 2020, with a spatial resolution of 30 m, cropped by the Wuhan University research team30.

Methodology

The USLE model is an empirical soil erosion prediction model developed in the U.S.A. for quantitatively predicting the average annual soil loss on agricultural or grassland slopes. It was introduced into China at the end of the 20th century, and Chinese scholars conducted extensive research on revising the calculation methods of USLE factors and applying the equations for soil erosion monitoring and prediction, which advanced the progress of soil erosion research in China. In this paper, the algorithms of each factor of the USLE model are determined according to the characteristics of the Dali River Basin, and the measured data of hydrological stations located in the Dali River Basin are used to verify the applicability of the USLE model to the Dali River Basin. As shown in Figs. 2 and 3, the trend lines of sand transport from Baijiachuan site and annual average soil erosion modulus of Dali River basin both exhibit peaks in 2013 and 2017. The sand transport at Baijiachuan out showed an increasing and then decreasing trend from 2008 to 2010; an increasing trend from 2011 to 2013; a decreasing trend from 2013 to 2015; and an increasing and then decreasing trend from 2015 to 2020, which is consistent with the trend of the annual average soil erosion modulus of the Dali River Basin from 2008 to 2020. This also fully demonstrates that the use of the USLE model to calculate the soil erosion control degree modulus is applicable to the Dali River Basin.

Fig. 2
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Measured data on sand transport in the Dali River Basin (Baijiachuan Hydrological Station).

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Fig. 3
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Changes in the annual average soil erosion modulus in the Dali River Basin from 2008 to 2020.

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Therefore, in this paper, the soil erosion model USLE is used to calculate the soil erosion modulus. Then the maximum possible soil erosion modulus is derived based on the vegetation cover factor as well as the soil and water conservation measures factor from 1991 to 2020. Finally, the degree of soil erosion control was calculated. The technical route is shown in Fig. 4:

Fig. 4
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Flowchart for the soil erosion control degree (SECD).

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USLE model

The universal soil loss equation (USLE) model widely used worldwide10. This paper selects it to calculate the soil erosion modulus, and the expression is:

$$A=R\cdot K\cdot L\cdot S\cdot C\cdot P$$

where A is the soil erosion modulus, \(\text{t}\cdot {\text{km}}^{-2}\cdot {\text{a}}^{-1}\); R is the rainfall–runoff erosivity factor; K is the soil erodibility factor; L is the slope length factor; S is the slope steepness factor; C is the cover-management factor; and P is the supporting-practice factor. The technology roadmap is shown in Fig. 4.

Rainfall–runoff erosivity factor(R)

The rainfall–runoff erosivity factor reflects the magnitude of the soil erosion dynamics caused by the rainfall. In this paper, Wischmeier’s empirical equation’s31 indigenization formula was chosen to calculate the rainfall–runoff erosivity factor. The expression is:

$$R=1.735\times {10}^{1.5\times log\sum_{i=1}^{12}\left(\frac{{p}_{i}^{2}}{p}\right)-0.8188}$$

where \({p}_{i}\) is the monthly precipitation, mm; and \(p\) is annual precipitation, mm. The rainfall–runoff erosivity factor was calculated year by year using the monthly rainfall raster data of the Dali River Basin from 2001 to 2020.

Soil erodibility factor(K)

The soil erodibility factor is an indicator used to evaluate the ease of soil separation, erosion, and transport by rainfall erosion forces. This factor can be derived from the sand, silt, and clay content of the surface layer of the soil profile. Wischmeier et al.32 established a relationship between the soil erodibility factor and soil properties, and measured the soil erodibility factor based on these properties. The expression is:

$$K=\{2.1*1{0}^{-4}*\left(12-a\right)*{\left[Soi{l}_{\text{c}}*\left(100-Soi{l}_{\text{s}}\right)\right]}^{1.14}+3.25*\left(b-2\right)+2.5*\left(c-3\right)\}/100$$

where \(Soi{l}_{\text{s}}\) and \(Soi{l}_{\text{c}}\) indicate the percentage content of clay and chalk in the soil, respectively. The soil structure class and infiltration class are determined according to the corresponding classes of soil organic matter content and clay grain content.

Slope length factor(L) and the slope steepness factor(S)

We extracted the slope steepness and slope length distribution maps based on the DEM of the topographic feature analysis. The slope length factor from the USLE was used to calculate the slope length factor33:

$$L=\left(\frac{\lambda }{22.1}\right)^{m}$$

where L is the slope length factor; λ is the slope length, m; m is the slope length index; and its value equation is:

$${\text{m}} = \left\{ {\begin{array}{*{20}l} {0.5} \hfill & {\theta < 1^\circ } \hfill \\ {0.3} \hfill & {1^\circ \le ~\theta \le 3^\circ } \hfill \\ {0.4} \hfill & {3^\circ \le \theta \le 5^\circ } \hfill \\ {0.5} \hfill & {\theta > 5^\circ } \hfill \\ \end{array} } \right.$$

The calculation of the slope steepness factor was considered by segmentation, i.e., McCool’s slope steepness factor equation34 for gentle slopes and Baoyuan Liu’s slope steepness factor equation35 for steep slopes were combined, and the expression is:

$${\text{S}} = \left\{ {\begin{array}{*{20}l} {10.8{\text{sin}}\theta + 0.03} \hfill & {\theta < 5{^\circ } } \hfill \\ {16.8{\text{sin}}\theta } \hfill & {5{^\circ } \le \theta < 10{^\circ } } \hfill \\ {21.91{\text{sin}}\theta } \hfill & {\theta \ge 10{^\circ } } \hfill \\ \end{array} } \right.$$

where S is the slope steepness factor, and θ is the slope.

Cover-management factor(C)

The cover-management factor reflects the influence of the vegetation on the soil loss according to the different conditions of ground plant cover. When the ground is completely bare, the value of the cover-management factor is 1.0. If the ground is well-protected, the value of the cover-management factor is 0.001, and the values of the cover-management factor range from 0.001 to 1. The cover-management factor is related to the type of vegetation and the degree of cover.

This paper uses the method proposed by Vander Knijff36 for determining the cover-management factor using NDVI:

$$C=\text{exp}[-\alpha \times NDVI/(\beta -NDVI)]$$

where \(\alpha ,\beta\) represents the dimensionless factor, \(\alpha =1,\beta =2\).

Supporting-practice factor(P)

Soil and water conservation measures are an effective way to prevent soil erosion, and the supporting-practice factor values for different land use types are usually determined after field visits. The supporting-practice factor values generally range from 0 to 1. A value of 0 represents areas where no erosion occurs at all, while a value of 1 represents areas where no control measures are taken. Due to the large size of the study area and the difficulty of obtaining complete and accurate data on soil and water conservation practices, we adopted a method of assigning P values based on slope classification for cropland, following previous research on soil conservation factors in the middle reaches of the Yellow River37,38,39,40, as shown in Table 1. Based on the studies of scholars like Wang41 and Xu42, where forestland, grassland, and bare land were assigned a value of 1, and construction land and water bodies were assigned a value of 0.

Table 1 P-values for different slopes of cultivated land in the USLE model.
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Soil erosion control degree (SECD)

Identification of the maximum possible soil erosion modulus

The minimum possible soil erosion modulus is calculated based on the capacity of soil and water conservation measures. Suitable distribution areas for these measures are identified according to the ground requirements, and then the measures are deployed. After the measures are set up, a certain area theoretically completes all the treatment work and the soil erosion modulus is controlled at a reasonable level, and the amount of soil and water conservation measures in this case is called the capacity of soil and water conservation measures. Therefore, the minimum possible soil erosion modulus is the theoretical soil erosion modulus of completing all treatment work. This leads to the fact that the calculation of the minimum possible soil erosion modulus requires detailed data on soil and water conservation measures and the method is difficult to be generalized. Therefore, this paper proposes to use the maximum possible soil erosion modulus instead of the minimum possible soil erosion modulus to redefine the calculation of soil erosion control degree.

Soil erosion control is primarily influenced by human activities. The supporting-practice factor (P) and the cover-management factor (C) reflect these influences on the soil erosion modulus43. In this paper, the maximum possible soil erosion modulus represents the highest soil erosion modulus that could occur under the most severe conditions of human influence, assuming that both the supporting-practice factor (P) and the cover-management factor (C) reach their maximum values over a long time series.

According to the regulations of the World Meteorological Organization (WMO), a 30-year period is considered the standard timeframe for climate calculations. A timescale of 30 years is generally regarded as sufficient to provide a relatively complete climate cycle, encompassing alternating conditions such as drought and wet periods. Therefore, this study selects data from the Dali River Basin from 1991 to 2020 to calculate the maximum values of the cover-management factor (C) and supporting-practice factor (P), which are then used to compute the maximum potential soil erosion modulus. The 30-year timescale helps capture long-term trends and cyclical characteristics of the cover-management factor (C) and supporting-practice factor (P), making the calculated maximum values of these factors more representative.

Evaluation model of SECD

In this paper, SECD is defined as the ratio of the difference between the maximum possible soil erosion and the actual soil erosion modulus to the maximum possible soil erosion modulus. The expression is:

$${r=({T}_{M}-T}_{S})/{T}_{M}$$

where r is the soil erosion control degree and dimensionless; \({T}_{S}\) is the actual soil erosion modulus, \(t\cdot {km}^{-2}\cdot {a}^{-1}\); and \({T}_{M}\) is the maximum possible soil erosion modulus, \(t\cdot {km}^{-2}\cdot {a}^{-1}\).

\({T}_{M}\) is the modulus of soil erosion that is likely to reach its maximum in the study area as judged from the long time series, and \({T}_{s}\) stands for the actual soil erosion modulus, so \({{T}_{M}-T}_{S}\) represents the soil erosion modulus reduced by humans through the implementation of control measures. When soil erosion is better managed in the study area, the actual soil erosion modulus TS will be smaller, and thus the degree of control r will be larger, and vice versa. Meanwhile, the value of SECD should be between 0 and 1. It reflects the closeness to the ideal control state of the study area. The closer to 1, the higher the control degree of the study area, and the closer to 0, the lower the control degree, the farther from the ideal control state. SECD quantitatively assesses the effect of soil erosion control in the study area and provides an important basis for to further develop soil erosion control measures.

Analysis of the degree of soil erosion control

Soil and water conservation measures mainly include biological, engineering and farming measures. Vegetation is the most commonly used biological measure for soil and water conservation, but the selection and configuration of species in the process of vegetation reconstruction, and its distribution pattern is the key. That will affect the effect of erosion control, and is also the difficulty in formulating soil and water conservation measures. At the same time, the anti-erosion effect of water conservation measures also has spatial and temporal variability, and the prevention and control benefits of the same soil and water conservation measures are different in different soil conditions. Therefore, this paper analyzes and discusses the effects of vegetation cover, land use type, slope, and soil erodibility factors on soil erosion. The specific analysis methods are shown below.

First, the SECD and its influencing factors were reclassified. According to the natural breakpoint method, SECD and its influencing factors, such as vegetation coverage, slope and soil erosion factors, were reclassified. Table 2 lists the classification criteria. Finally, the soil erosion control degree and each influencing factor were superimposed for analysis.

Table 2 Classification criteria for soil erosion control and its influencing factors.
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Results and analysis

Spatial and temporal distribution of the actual soil erosion intensity in the Dali River Basin

The USLE model was used to calculate the soil erosion modules from 1991 to 2020, and we graded the soil erosion intensity of the Dali River Basin according to SL 190-2007 "Soil erosion classification and grading standard". As shown in Table 3, it is divided into 6 levels: slight, mild, moderate, intense, very intense, and extreme erosion. Then, we obtained the soil erosion intensity in the 1991 and 2020 distribution maps, as shown in Fig. 5.

Table 3 Classification criteria for the soil erosion intensity.
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Fig. 5
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Distribution of the soil erosion intensity in the Dali River Basin in 1991 (a), 2000 (b), 2010 (c) and 2020 (d). Figure 5 was using ArcGIS10.8 (https://soft.wxqilinz.cn/gis-jb61d/)software. It is mainly calculated from the data presented in the 2.2 Data section.

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The spatial and temporal distribution of soil erosion in the Dali River Basin was analyzed, as shown in Fig. 5, the overall soil erosion intensity in the Dali River Basin shows obvious regional differences, divided into relatively weak erosion in the northwest part of the Dali River and relatively strong erosion in the eastern and southwestern parts of the Dali River Basin. In 1991, the overall soil erosion intensity in the Dali River Basin was slight and light erosion, in which the intensity class with the largest proportion was slight erosion, accounting for 64.52%, i.e. 3115.15 km2; In 2000, the soil erosion intensity in the Dali River Basin increased overall, and the eastern erosion intensity increased to medium and strong erosion, and the intensity class with the largest area share was slight erosion, accounting for 63.96% , i.e.3088.17 km2;;In 2010, the western erosion in the Dali River Basin showed a significant increase, and the eastern erosion was controlled to medium strength erosion, similar to the situation in 2000. It indicates that the policy of returning farmland to forest implemented in China since 2000 has achieved better ecological benefits44 and the serious area of soil erosion in the Dali River Basin has been effectively controlled. In terms of spatial distribution, the intensity level that accounts for the largest proportion is slight erosion, accounting for 49.12%, or 2371.69 km2. Soil erosion intensity increased significantly in the eastern part of the Dali River Basin in 2020, with very strong erosion as well as intense erosion occurring in the eastern part of the Daly Creek as well as in the southwestern part of the Dali River Basin.

As shown in Fig. 6, the average annual soil erosion modulus of the Dali River Basin shows volatility rises. From 1991 to 2020, the minimum average annual soil erosion modulus appeared in 1991 (949.04 \(\text{t}\cdot {\text{km}}^{-2}\cdot {\text{a}}^{-1}\)), and the maximum average annual soil erosion modulus appeared in 2013 (5051.83 \(\text{t}\cdot {\text{km}}^{-2}\cdot {\text{a}}^{-1}\)). Between 1991 and 1995, the average annual soil erosion modulus in the Dali River Basin increased, reaching its peak in 1995. However, it decreased from 1995 to 2000. The average annual soil erosion modulus suddenly increased to 2844.24 \(\text{t}\cdot {\text{km}}^{-2}\cdot {\text{a}}^{-1}\) in 2001, and then decreased year by year from 2001 to 2005. The average annual soil erosion modulus increased year by year from 2005 to 2009. Compared with the previous two increases, the increase rate was relatively slow, and the average annual soil erosion modulus showed a short-term fluctuation from 2009 to 2011. After a slight increase in the average annual soil erosion modulus in 2012, the average annual soil erosion modulus increased sharply in 2013, reaching the maximum annual soil erosion modulus from 1991 to 2020. This is primarily due to the increased and uneven spatial and temporal distribution of rainfall in the Dali River Basin in 2013. Rainfall, especially erosive rainfall, is one of the important external driving forces of soil erosion, and its change is one of the important influencing factors leading to the change of soil erosion in basin45. The fluctuation of the average annual soil erosion modulus during 2010-2020 is more frequent than that in the previous 20 years.

Fig. 6
figure 6

Changes in annual average soil erosion modulus, cover-management factor, supporting-practice factor, and annual rainfall from 1991 to 2020 in the Dali River Basin.

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From Fig. 6, it can be seen that relative to the trend of C factor and P factor from 1991 to 2020, the trend of annual average rainfall in the Dali River basin is more similar to that of annual average soil erosion modulus in the Dali River basin from 1991 to 2020. This also proves that rainfall is an important influencing factor of soil erosion. The average annual values of C factor and P factor from 1991 to 2020 fluctuated between 0.7 and 1. And the trends of C factor and P factor are not similar. This also verifies that the C-factor and P-factor are independent variables in the calculation of soil erosion modulus, and they each reflect the influence of different factors on soil erosion.

Maximum possible soil erosion modulus of the Dali River Basin in 2020

As shown in Fig. 7, the average value of the maximum possible soil erosion modulus is 4404.69 \(\text{t}\cdot {\text{km}}^{-2}\cdot {\text{a}}^{-1}\), which is much higher compared to other years. This indicates that the natural environmental conditions of the Dali River basin make it more susceptible to erosion and require certain measures for management and control. The distribution of the maximum possible erosion intensity shows that the eastern part of the Dali River Basin generally has a spatial potential for very strong or intense erosion. Comparatively speaking, the northwestern part of the Dali River Basin has a lower potential for very strong or intense erosion, which provides a reference value for further adjustment of soil erosion management in the Dali River Basin in the future.

Fig. 7
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Distribution of maximum possible soil erosion classes in the Dali River Basin in 2020.

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Maximum probable soil erosion is dominated by mild as well as moderate erosion, with moderate erosion accounting for 30.75% of the Dali River Basin area. The percentage of the area with moderate or lower soil erosion intensity in the maximum possible soil erosion intensity class is 63.98%, which is more than 50% of the area.

SECD of Dali River Basin

Based on the SECD concept proposed in this paper, the distribution map of SECD in the Dali River Basin was calculated. Areas with SECD greater than 0.5 were grouped into one category, while areas with SECD less than 0.5 were further subdivided to better observe the distribution profiles of smaller regions. This resulted in five categories: 0–0.20, 0.20–0.25, 0.25–0.30, 0.30–0.50, and 0.50–1.00. The average SECD value for the Dali River Basin is 0.31, which is below 0.50. As shown in Table 4, 54.16% of the area falls into the SECD range of 0.20 to 0.30, indicating significant management potential and the need for further intervention. Figure 8 illustrates that areas with control degrees between 0.50 and 1.00 are concentrated in the eastern and southwestern parts of the Dali River Basin, while areas with control degrees below 0.50 are primarily in the northwestern part. Compared to the 2020 graded distribution of soil erosion intensity, the northwest part of the Dali River Basin has a lower soil erosion modulus, but the effectiveness of current management measures remains limited. This suggests that further adjustments to the management measures in the northwest part of the Dali River Basin are necessary to improve management effectiveness.

Table 4 The area proportion of various SECD level in the Dali River Basin in 2020.
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Fig. 8
figure 8

Distribution of SECD in the Dali River Basin in 2020.

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Variation of SECD under different influence factor

SECD under different slopes

The area statistics of SECD at all levels under different slopes are shown in Table 5. It shows that under different slopes, the SECD degree of most areas is concentrated in the range of 0.2-0.3. As the slope increases, the percentage of area with soil erosion control degree of 0 to 0.2 increases and then decreases; the percentage of area with soil erosion control degree of 0.2 to 0.3 and 0.3 to 0.5 shows an increasing trend; and the percentage of area with soil erosion control degree of 0.5 to 0.7 and 0.7 to 1.0 both show decreasing trends. Overall, with the increase of slope, the area percentage of the SECD with 0.2-0.5 gradually increases, while the percentage of the area with 0.5-1 gradually decreases. The area percentage with 0-0.2 is basically unchanged.

Table 5 The area proportion of various SECD level in different slope zones.
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SECD under different soil erodibility factors

From Table 6, it can be seen that in the case of soil erosion factor less than 0.1, the proportion of area occupied by each classification of soil erodibility factor decreases when the SECD is from 0 to 0.5. When the soil erosion factor is greater than 0.1, the proportion of area occupied by each classification of soil erodibility factor increases as SECD ranges from 0 to 0.5. This indicates that the soil erosion control measures in the Dali River Basin have received obvious feedback, but the soil erosion control effect is still not obvious for the areas where the local soil is prone to erosion, and further improvement is needed.

Table 6 The area proportion of various SECD in the different soil erodibility factor zones.
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SECD under different vegetation cover

As shown in Table 7, overlay analysis of SECD and vegetation cover can be concluded that in the case of less than 20% vegetation cover, the SECD is concentrated between 0-0.2; in the case of 40-80% vegetation cover, the SECD is concentrated between 0.2-0.3; in the case of more than 80% vegetation cover, the SECD is concentrated in the range of 0.3-0.5. In areas with high vegetation cover, SECD is still below 0.5, which indicates that vegetation cover is not the only factor affecting the degree of soil erosion control. The future soil erosion control work should comprehensively consider various influencing factors to adjust treatment measures.

Table 7 The area proportion of SECD in the different vegetation cover zones.
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SECD under different land use types

From Table 8, it can be seen that the SECDs in cultivated land, forest land, and grassland are concentrated between 0.7-1.0, 0.3-0.5, and 0.2-0.3, respectively, with relatively high SECD in cultivated land. This is mainly because cropland is more susceptible to soil erosion and receives more social attention, and the policy of returning cropland to forest has been enacted in recent years. The SECD of bare land is concentrated in the range of 0~0.2, which indicates the effect of management is not obvious and soil erosion is easy to occur in bare land. The further management measures are needed in bare land.

Table 8 The area proportion of SECD in the different land use types.
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Discussion

Spatial-temporal distribution of soil erosion modulus and SECD

As shown in Fig. 5, comparing the spatial distribution of soil erosion intensity classes in 1991, 2000, 2010 and 2020, it can be seen that there is a significant difference in soil erosion intensity classes, and the difference is gradually obvious. The area share of each soil erosion class can be derived from the soil erosion class distribution map for each year, as shown in Table 9. It can be seen that in 1991 and 2000, slight erosion dominated; in 2010, slight erosion and mild erosion dominated; and in 2020, slight erosion, mild erosion and moderate erosion dominated. From the perspective of time distribution, the difference in spatial distribution of soil erosion intensity in the Dali River basin is gradually obvious. In terms of spatial distribution, the soil erosion intensity in the eastern and southwestern part of the Dali River Basin is small, and the soil erosion intensity in the northwestern part of the Dali River Basin is large.

Table 9 Percentage of area in each soil erosion intensity class by year.
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From the spatial distribution of SECD, as shown in Figs. 5 and 8, the degree of soil erosion control is lower in the northwestern part of the Dali River Basin, while it is higher in the eastern part of the basin and along both sides of the Dali River. Based on the spatial distribution of soil erosion classes, erosion intensity is lower in the northwestern part of the basin and higher in the eastern and southwestern parts.

Methods for calculating the degree of soil erosion control

The Yellow River Basin is a crucial ecological security barrier and economic belt in China, playing a significant role in the strategic framework of economic and social development. Therefore, the middle reaches of the Yellow River have always been the focus of soil and water conservation work. Based on the boundary of coarse sand and sand transport modulus and other indicators, large-scale soil erosion control has been carried out continuously in accordance with the principle of "coarse first, then fine, phased treatment". In recent years, soil erosion control has achieved significant results46. The greatly reduced soil erosion area means that rough estimates of soil erosion control status no longer provide a better reference for adjusting soil erosion control measures, so the next soil erosion management can be transformed into a refined management. Combined with remote sensing images, we can not only estimate the increase or decrease of soil erosion area on a large scale, but can utilize the soil erosion control degree to assess the degree of soil erosion management of each pixel, so as to formulate more refined management measures.

The current calculation of soil erosion control degree includes two aspects of calculation, one is the calculation of the minimum possible soil erosion modulus, and the other is the calculation of the actual soil erosion modulus. Among these, the concept of the capacity of soil and water conservation measures is proposed in the calculation of the minimum possible soil erosion modulus. Determining the amount of soil and water conservation measures requires comprehensive consideration of various factors, such as the current state of land use, rainfall distribution, and climatic zoning, among others. The rules for the division of suitable zones for soil and water conservation measures in different regions are not generalizable, which leads to the low efficiency of the assessment of the degree of soil erosion control based on the minimum possible soil erosion modulus, and its applicability is not high.

Therefore, this paper proposes using the maximum possible soil erosion modulus to calculate the degree of soil erosion control. Specifically, it suggests comparing the maximum possible soil erosion modulus with the current soil erosion modulus to determine the ratio, which reflects the soil management potential. Using this ratio to characterize the degree of soil management potential, to make up for the dams, terraces, and the appropriate distribution area of the forest land and the minimum possible soil erosion is difficult to determine the shortcomings, and make the degree of soil erosion control degree to characterize the degree of soil erosion management potential is more representative. At the same time, using the maximum possible soil erosion modulus to calculate the degree of soil erosion control improves the efficiency of the degree of soil erosion control assessment, providing an important reference for soil erosion management.

Compared to the calculation of the degree of soil erosion control by the minimum probable soil erosion modulus, which does not require detailed data on soil and water conservation measures, the determination of the maximum probable soil erosion modulus is easier, thus improving the efficiency of the assessment of the degree of soil erosion control. In addition, the suitable distribution areas of different land use types are spatially different47. There are various soil erosion control measures which are implemented in the different areas, so it is impossible to directly apply the suitable areas of one area to another area. Meantime, calculating SECD for large areas using the minimum probable soil erosion modulus is difficult, while the data required for calculating the maximum possible soil erosion modulus are easy to obtain and apply. Therefore, algorithm for calculating the SECD based on the maximum possible soil erosion modulus is more generalizable.

Conclusion

This paper, which focuses on the Dali River Basin, utilized Geographic Information System software (ArcGIS) and the Universal Soil Loss Equation (USLE) model to calculate soil erosion modulus and SECD. We analyzed the soil erosion management potential of the Dali River Basin in 2020 by examining changes in the spatial and temporal distribution of soil erosion intensity from 2001 to 2020 along with SECD data from 2020. The following conclusions were drawn:

  1. (1)

    There are significant regional differences in the spatial distribution of soil erosion intensity in the Dali River Basin, which have become increasingly apparent. As can be seen from Fig. 5, the soil erosion intensity is stronger in the eastern and southwestern parts of the Dali River Basin, and relatively smaller in the northwestern part of the Dali River Basin. Comparing the spatial distribution of soil erosion intensity levels in 1991, 2000, 2010 and 2020, it can be seen that regional differences in the spatial distribution of soil erosion intensity levels in the Dali River Basin are gradually obvious.

  2. (2)

    The average value of SECD in the Dali River Basin in 2020 was 0.31, and the spatial distribution of SECD was consistent with the spatial distribution of soil erosion intensity in the Dali River Basin. From the perspective of the spatial distribution of SECD, the overall soil erosion control potential in the Dali River Basin is greater. The areas with better soil erosion control are concentrated in the eastern and southwestern parts of the Dali River Basin. Combined with Fig. 5_d and Fig. 8, it can be seen that the areas with high soil erosion control in the Dali River Basin are mainly concentrated in the areas with strong soil erosion. Therefore, in the future, it is necessary to further adjust and increase soil erosion control measures to strengthen the management of the northwest part of the Dali River Basin.

  3. (3)

    Slope as well as soil erodibility factors in the Dali River Basin affect SECD to some extent. From Table 5, it is concluded that with the increase of slope, the proportion of area with SECD of 0.2-0.3 in each slope zone showed an increasing trend. Conversely, with the increase of slope, the area proportion of SECD with 0.5-0.7 in each slope zone showed a downward trend. From Table 6, it is concluded that with the increase of soil erodibility factor, the area proportion of SECD with 0-0.5 in each soil erodibility factor zone tended to decrease and then increase.

  4. (4)

    Vegetation cover in the Dali River Basin is not the only factor in managing soil erosion. According to the overlay analysis of SECD and vegetation cover in the Dali River basin, it can be concluded with the vegetation cover increases, the area proportion of SECD with 0-0.5 in each vegetation cover zone showed a downward trend. This suggests that increasing vegetation cover can improve soil erosion control to some extent. Combined with the land use type, the SECD of cultivated land was concentrated between 0.7-01, the SECD of forest land was concentrated between 0.3-0.5, and the SECD of grassland was concentrated between 0.2-0.3. On the whole, the SECD in areas with high vegetation cover is still below 0.5, that indicates that vegetation coverage is not the only factor affecting soil erosion control. The following soil erosion control work should comprehensively consider various influencing factors to adjust treatment measures.