Introduction

An oasis is a heterogeneous ecological landscape that maintains relative stability with significant microclimatic effects against a large-scale desert backdrop1, based on a small-scale range but with a sizable biological community. Oases are mainly found in the arid regions of China. As the distribution of water sources determines the distribution of oases, the linear form of water flow in the arid zone forms oases with a band distribution pattern, whereas springs, wells, and lakes in the shape of a point (surface) form oases with a scattered distribution2. For the inhabitants of arid regions, oases are vital, merging man-made and natural landscapes to support human activities and livelihoods3,4. Simultaneously, the unique topographical features of oases can effectively offset some extremes in the climate. Vegetation in oases helps prevent soil erosion and conserve soil and water. Therefore, the stability of oases is related to the survival of human beings and sustainable economic development in arid areas3,5.

As an important part of the ecological environment of the Tibetan Plateau, oases provide a valuable barrier to the ecologically fragile Tibetan Plateau region. In recent years, the irrational exploitation of farmland and arable land in arid zones, and the overutilization of water resources by humans have led to oases in arid zones encountering environmental problems, such as land desertification6,7, secondary salinization of the land8, and severe soil pollution by heavy metals. Oasis ecosystems in arid zones are extremely fragile and face ecological and environmental challenges such as drought, wind erosion, and soil poor fertility ensues9,10. The soil is the most important component of an ecosystem as it affects the cycles of mineral and organic matter, as well as the energy flow through the whole ecosystem. Further, heavy metals are hazardous to soils and human health due to their cumulative nature and difficulty in management and degradation11,12,13. Social and economic development of arid zones have cause ecological and environmental problems to become increasingly severe, and environmental carrying capacity is produced when the contradiction between the environment and economic development reaches a certain threshold level, thus reflecting the relationship between the environment and human economic development10. The ecological problems of oases in arid zones can be solved more effectively if existing and future environmental carrying capacity problems are identified. Therefore, identifying and predicting the environmental carrying capacity of oases in arid areas is paramount to the development of arid areas and the livelihoods of the people.

Because of the importance of oases and environmental problems, many scholars have conducted studies on oases in arid zones. Thus, for example, Wang et al. (2021) used hyperspectral remote sensing to estimate the content of the heavy metal Cr in soils of the Weigan River-Kucha River delta oasis and found that the Cr content of the cultivated soils showed a high spatial distribution14. Similarly, based on a study of the surface wind erosion characteristics of different land-use types in the Ulan Buh Desert Oasis, Xu et al. (2018) found that stubble land is an effective control measure against soil erosion caused by wind15. In turn, Wu et al. (2013) used the Tessier morphology continuous leaching method to study the morphology distribution and redistribution trends of heavy metals in oasis soils in arid zones under a single stress, and found that the effects of heavy metal contamination on soils and crops were long lasting16. Without considering various geological backdrops and soil types, most of these studies have focused on the content of specific elements or compounds in various land-use types to address the soil environmental capacity problem encountered by oases in arid zones. However, in each case, the study area was small, mostly one oasis rather than a cluster of oases, and mostly concentrated at low elevations. Conversely, it is necessary to select an arid-zone oasis complex at high altitudes and consider the influence of its geological background and soil types on the capacity of the soil environment to conduct the study.

Research on oases in the arid zones of the Tibetan Plateau is scarce. The Tibetan Plateau has always been known as the “Roof of the World”17, and has been influenced by a variety of factors, forming the world highest and youngest natural geographic units with a close combination of horizontal and vertical zonation18. The terrain is steep and varied, topography is complex, mountains differ significantly, and there is an abundance of various types of resources. Simultaneously, the Tibetan Plateau suffers from several environmental problems, such as melting glaciers, land sanding, and soil erosion19. Therefore, research on the environmental carrying capacity of oases in the arid region of the Tibetan Plateau can not only solve the long-lasting environmental problems of the oases in the Tibetan Plateau and the arid region but additionally, it can provide support and reference for research on the environmental capacity of the soils of the oasis cluster in the high-altitude arid region.

Based on foregoing discussion, in this study, the Delingha-Wulan oasis cluster was selected as the study area for the high-altitude arid zone oasis, and the environmental capacity of the soil in the Delingha-Wulan area was carefully discussed using geographic information system (GIS) analysis of space, the linear balance of materials model, the environmental composite index technique, and the enriched factor approach. The primary goals of this study were (1) To establish background soil values based on soil measurements in the Delingha-Wulan area; (2) Using a linear material balance model, the environmental capacity of heavy metals in the soils of the Delingha-Wulan area was determined, and this environmental capacity trend was forecast over the past 50 years; (3) Early warning of health risks and soil capacity risk assessment were accomplished through the application of the enrichment factor and environmental capacity index methodologies; (4) To put forward proposals designed to solve the ecological and environmental problems of oases in arid zones. The research findings summarized herein enhance our knowledge and understanding of the soil environmental capacity of arid zone oases in the Qinghai-Tibetan Plateau region. Furthermore, our data offer scientific support for the preservation of the environment, and serve as a source of information for future studies.

Materials and methods

General description of the study area

The study area(Fig. 1) is located in the northeastern part of Chaidam, between 36°55’~38°22’N and 96°15’~98°15’E, under the jurisdiction of Haixi Mongol and the Tibetan Autonomous Prefecture. The study area covered two main regions: Delingha and Wulan. The Delingha region encompasses the town of Huaitoutala, the city of Delingha-Gahai, and the western part of Xuji Township; in turn, the Wulan region encompasses the county of Wulan, the town of Chaka, and the area of Chachaxiangka East. Although there are more soil types in the study area, most are calcareous brown soils. Given the saline and watered conditions of the soils, the most common land-use types are farming, agriculture, forestry, and animal husbandry. The study area is located in the Qin-Qilian-Kunlun stratigraphic region, which is further divided into four subregions from north to south: the Southern Qilian Mountains, the Northern Margin of Qaidam Basin, the Southern Margin of Qaidam Basin, and the Zongwulong-Zeku subregion. The stratigraphy in this area ranges from the Early Proterozoic to the Quaternary period, reflecting a complex geological history. Detailed stratigraphic information is shown in the geological map provided (Fig.S1).

Fig. 1
figure 1

Map of sampling points in the study area.

Full size image

Soil data collection and analysis

The 1:50,000 topographic and land-use maps of the second land survey were used as the base map for this study, the sampling points were arranged following the principle of combining grids and patches. For larger patches, sampling points were set in conjunction with the grid layout; each smaller patch was controlled by samples, while larger patches had an increased number of sampling points to ensure uniform spatial distribution of the samples. Additionally, based on actual conditions, the sampling points were placed in the most representative locations within the grid, considering the representativeness of the sampling points. A total of 1,517 soil samples were collected and the sampling depth was 0 cm to 20 cm according to the Specification of land quality geochemical assessment (DZ/T0295-2016). When collecting samples, a spade with a 21 cm blade was used to excavate a sampling pit to a depth of 21 cm. A soil column measuring 3 cm × 3 cm × 20 cm was cut from the vertical section, ensuring that the error did not exceed 1 cm. The samples were collected after removing weeds, gravel, and other foreign materials, placed into cloth bags labeled with sample numbers, and then sealed inside an additional layer of polyethylene plastic bags. The entire process required measures to prevent the surface soil from slipping. The field-collected samples were first anti-fouled and then air-dried with frequent kneading during the drying process to avoid gumming. After drying the sample with a gentle mallet and then fully passing through a 20-mesh nylon sieve, the material in the upper part of the sieve was discarded, while that in the lower part was mixed and placed into a paper bag. Samples (> 200 g) were sent to the laboratory for testing and analysis.

Currently, elements such as Cd, As, Pb, and Hg have been confirmed to pose serious threats to human health20. Additionally, these heavy metals are commonly found in the soil of the Qinghai-Tibet Plateau region, posing potential risks to the ecosystem, so six elements (As, Cd, Cu, Hg, Pb, and Zn) were selected as evaluation indices of soil environmental capacity. According to the analytical indices and sample characteristics involved in the soil analysis in this project, based on Chinese national standard methods and relevant industry standard analysis methods, combined with actual conditions, the appropriate measurement method is selected for the elements. Atomic Fluorescence Spectrometry (AFS) is an analytical technique used for determining the concentration of trace elements in samples, offering high sensitivity and selectivity. Therefore, AFS was employed to measure the elements As and Hg. Inductively Coupled Plasma Mass Spectrometry (ICP-MS) is a powerful analytical technique for trace element determination and isotope analysis; thus, ICP-MS was used to determine the elements Cd and Pb. Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES) measures the intensity of light emitted by excited atoms or ions in a plasma, with each element producing a unique set of emission lines that allows for the identification and quantification of various elements in a sample. ICP-AES provides high sensitivity, precision, and accuracy, and for the precise determination of the element Zn, we utilized Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). X-ray Fluorescence Spectrometry (XRF) is a non-destructive analytical technique used to ascertain the elemental composition of materials. Its working principle involves irradiating the sample with x-rays, causing the sample to emit secondary (or fluorescent) x-rays. The energy and intensity of these fluorescent x-rays are characteristic of the elements present in the sample. Therefore, the element Cu was determined using X-ray Fluorescence Spectrometry (XRF). The threshold concentrations for detection using these methodologies were 0.2, 0.02, 1, 0.0005, 2, and 1 µg/g for As, Cd, Cu, Hg, Pb, and Zn, respectively. For quality control, four national-level soil standards with different contents (GSS-4, GSS-8, GSS-9, and GSS-14) and four national-level soil active-state standards with different contents (GBW07412a, GBW07413a, GBW07414a, and GBW07460) were added to each batch of 50 soil samples in a coded manner. The logarithmic difference (ΔlgC) between the single determination value and the standard value for each element was calculated. The one-time pass rate for all elements was 100%. Accuracy using 12 inserts per 500 samples in soil samples (GSS17 to GSS28).

Research methodology

Establishment of soil geochemical background values and risk reference values

Soil geochemical background values are background values for elements in environments with high anthropogenic impacts. Defined as the average of the arithmetic \(\:\overline{\text{X}}\) mean values of elemental contents in the topsoil samples in the study area after \(\:\overline{\text{X}}\)±3 S iterations to remove outliers. These mean values are the actual baseline concentrations in which each element is present in the soil and serve as a frame of reference for measuring future changes in environmental quality. Because oases have a significant impact on the life and development of arid regions, the establishment of soil background values for the Delight-Wulan region is necessary for studying and evaluating the degree of soil contamination under local conditions. Analysis of the data obtained on the contents of As, Cd, Cu, Hg, Pb, and Zn in the soils of the Delingha-Wulan area revealed that they conform to a normal distribution. Therefore, the background concentration values of the soil elements in the Delingha-Wulan area were calculated according to the above method.

Prior to studying the environmental capacity of soil, we must ascertain the corresponding risk reference-value. In this study, the median value (6.5 < pH ≤ 7.5) in the risk screening level of other categories in the Risk Control Regulation for Soil Pollution of Agricultural Land (GB15618-2018) is referred to as the risk reference value for the six elements As, Cd, Cu, Hg, Pb, and Zn. When a certain pollutant content in the soil is equal to or lower than the risk reference value, it poses a low risk for the soil ecosystem. The soil geochemical background and risk reference values are listed in Table 1.

Table 1 Background and reference values of heavy metals in the soils of the study area.
Full size table

Spatial analysis methods

Inverse Distance Weighting (IDW)21,22 is an interpolation method commonly used in spatial data analysis that assigns different weights based on the distance of the predicted point from the location of the interpolated point to obtain a weighted average. One advantage of this method is that it provides a high degree of accuracy. A linear, unbiased, and ideally estimated interpolation approach without data modification was used to assess the environmental capacity of soil heavy metals and the environmental composite index of soil heavy metals using the raw data of the regional variables:

$$Z(x_{0} ) = \mathop \sum \limits_{{i = 1}}^{n} \varphi _{i} \times Z(x_{i} )$$
(1)

where, Z(x0) = the linearly predicted amount, Z(xi) = the value observed, n represents the total number of measurements, i = the sample identifier, and φi = the ideal weight value for an unbiased forecast with the least amount of volatility.

Linear modeling of material balances

Static environmental capacity

The static capacity of a soil is its maximum capacity to withstand a certain heavy metal in a certain time and space without interference from external factors23. It describes the future capacity of a certain area of land to host productive human life24,25,26. The parameters of the mathematical model of the soil static environmental capacity are easy to obtain and calculate, and are frequently selected by researchers who wish to examine the soil environmental capacity of an area. The formula used is given below:

$$Q_{s} = M \times \left( {C_{i} - C_{b} } \right) \times 10^{{ - 6}}$$
(2)

where, Qs (kg/hm2) = the static soil capacity, M (2.25 × 106 kg/hm2) = the weight of the plowed soil per hectare, Ci (mg/kg) = the risk standard, and Cb (mg/kg) = the fundamental value of the pollutant in the soil.

(2) Remaining environmental capacity.

The soil residual capacity is the total amount of a certain pollutant that can be accommodated in the future26, and is calculated using the following formula:

$$Q_{i} = M \times \left( {C_{i} - C_{o} } \right) \times 10^{{ - 6}}$$
(3)

where, Qi (kg/hm2) represents the remaining soil capacity; Ci (mg/kg) = the risk value of the reference; and Co (mg/kg) = the observed concentration of the element in the soil.

Dynamic environmental capacity

When a heavy metal in the soil participates in an environmental cycle, its maximum tolerance to heavy metals in a given time and space is known as its dynamic environmental capacity24. The amount of any given heavy metal that the soil can hold in relation to soil environmental quality standards varies because heavy metals are in a state of dynamic equilibrium. In other words, the soil has a variable capacity. Therefore, considering these variations and presuming a linear model of material balance, a linear relationship between soil pollutant output and soil pollutant content was applied to derive the following, average, dynamic annual-capacity Eq. 11:

$$Q_{n} = \left[ {W_{n} - W_{o} \times K^{n} } \right] \times \frac{{1 - K}}{{K \times \left( {1 - K^{n} } \right)}} = M \times \left( {C_{i} - C_{o} \times K^{n} } \right) \times \frac{{1 - K}}{{K \times \left( {1 - K^{n} } \right)}} \times 10^{{ - 6}}$$
(4)

where, Wn = the total anticipated concentration (kg/hm2) of heavy metal elements in the topsoil layer of the soils in the area after a few years, and Wo = the total elemental content (kg/hm2) in the tillage layer at the beginning of the observation year. The link between the content of an element in the soil after one year of cultivation, the total amount of that element in the soil in the previous year, and the input of that element in the current year are represented by the residual rate, or K value. The average dynamic yearly capacity, Qn (kg/hm2·a) = the control year.

The process whereby heavy metals accumulate in the soil is represented by this equation, and the change in soil heavy metal pollutants mainly depends on the residual K rate. The lingering rate of heavy metal pollutants in the soil is an indicator of the dynamic equilibrium of pollutants, which depends not only on the structure and function of the soil but is also closely related to the nature of the pollutants entering the soil environment. Based on the elemental background and risk reference values of the Delingha-Wulan area, a formula was used to determine the soil dynamic environmental capacity in the study area. According to previous research, heavy metals are not easily leached naturally in soils, and the residual migration rate is usually, approximately 90%27. As a result, K = 0.9, The calculations made use of the residual rates of various heavy metal components in the soil. Because the number of control years, n, should be set neither excessively small nor large, it is recommended that the soil dynamic environmental capacity in the Delingha-Wulan area be set at 20, 30, and 50 years, i.e., until 2044, 2054, and 2074, respectively.

Environmental capacity index

The capacity of the soil environment was evaluated using the composite index method. The individual environmental capacity index is the ratio of the soil remaining element I environmental capacity to its static environmental capacity. On the other hand, the combined environmental capacity index is the average of multiple individual environmental capacity indices28:

$$\:\text{P}\left(\text{i}\right)\text{=}\raisebox{1ex}{${\text{Q}}_{\text{i}}$}\!\left/\:\!\raisebox{-1ex}{${\text{Q}}_{\text{s}}$}\right.$$
(5)
$$\:\text{PI=}\frac{\text{1}}{\text{n}}{\sum\:}_{\text{i=1}}^{\text{n}}{\text{P}}_{\text{i}}$$
(6)

where, P(i) = the individual environmental capacity index of heavy metal i in the soil, n is the number of elements, and PI = the composite environmental capacity index. Table 2 displays the grading standards for the environmental capacity of heavy metals.

Table 2 Classification standards of PI on environmental capacity.
Full size table
Enrichment factors

The enrichment factor method is a method to quantitatively evaluate the degree of soil heavy metal contamination by analyzing the influence of human activities on the source of soil heavy metals to determine the enrichment status of heavy metals in the soil29:

$$\:\text{EF=}\frac{\raisebox{1ex}{${\text{C}}_{\text{i}}$}\!\left/\:\!\raisebox{-1ex}{${\text{B}}_{\text{i}}$}\right.}{\raisebox{1ex}{${\text{C}}_{\text{r}}$}\!\left/\:\!\raisebox{-1ex}{${\text{B}}_{\text{r}}$}\right.}$$
(7)

where, EF = the enrichment factor for heavy metals, Ci and Bi in Ci/Bi = the measured (mg/kg) and background (mg/kg) values of heavy metal i in the soil, respectively, and Cr and Br in Cr/Br = the measured (mg/kg) and background (mg/kg) values of the reference element in the soil, respectively. The coefficient of variation for potassium in this study was small (7.96%). Therefore, potassium was selected as the reference element for this study. Table 3 displays the enrichment grade categorization requirements based on the enrichment factors.

Table 3 Enrichment level classification criteria.
Full size table

Data analysis

Microsoft Excel 2019 was used for data processing and statistics of the elements. Sampling distribution locations were plotted based on ArcGIS 10.8, and inverse distance weight interpolation was used to map the relevant spatial distribution of environmental capacity. The data were tested for normality using SPSS 27 software to analyze significant differences, distributional characteristics, and the factors influencing environmental capacity under different geological backgrounds, land use, and soil types at a confidence level of 0.05; The Origin 2022 software was used to graph data relationships.

Results and discussion

Characterization of soil mineral elemental content

The characteristics of the six heavy metals in the 1517 soil samples obtained from the study area are shown in Table 4. The mean concentrations of As (12.46 ± 1.33 mg/kg), Cd (0.16 ± 0.02 mg/kg), Cu (24.46 ± 2.65 mg/kg), Hg (0.03 ± 0.01 mg/kg), Pb (23.18 ± 3.71 mg/kg), Zn (67.01 ± 4.47 mg/kg) and organic matter (16.00 mg/kg)respectively. None of these values exceeded the recommended value of 6.5 < pH ≤ 7.5 in the Risk Control Standard for Soil Pollution on Agricultural Land (GB15618-2018) for risk screening value of other categories. The mean values for Hg and Pb were 1.16 and 1.04 times higher, respectively, than the background levels in the soil environment, indicating a certain degree of topsoil layer enrichment with these two heavy metals. The coefficients of variation for As, Cd, Cu, Hg, and Zn were 0.24, 0.30, 0.30, 0.88, and 0.22, respectively, which indicate moderate variation, whereas that for Pb was 1.13, which indicates a strong variation, and suggests that Pb was highly discrete and not uniformly distributed in the study area. From the data, we concluded that the overall heavy metal content in the soils of the Delingha-Wulan area is not high because the vegetation in the oasis can absorb solidified heavy metals30,31 and anthropogenic disturbance is low.

Table 4 Statistics of heavy metal contents in the soils of the study area.
Full size table

Status of static environmental capacity

According to Eq. (2), the contents of the six heavy metals under analysis in the Delingha-Wulan area ranked in the following order: Zn > Pb > Cu > As > Hg > Cd, with content values of 412.2, 219.82, 170.32, 39.37, 5.35, and 0.31 kg/hm2, respectively. Additionally, high static environmental capacities and low risks were calculated for Zn, Pb, and Cu. According to the calculations and data review, the average content of these six elements in the Delingha-Wulan area was relatively similar to their background values, and the coefficient of variation was not high, indicating that these elements were mainly affected by natural factors in the soil, whereas anthropogenic factors had less influence on the measured contents. The static environmental capacity of As, Hg, and Cd was smaller and at higher risk, among which, particularly, the static environmental capacity of Cd was only 0.315 kg/hm2, suggesting that the Delingha-Wulan area may be at an ecological risk associated to Cd.

Distribution of remaining environmental capacity

The distribution of the remaining environmental capacity was obtained by interpolating the IDW in accordance with Eqs. (1) and (3), as shown in Fig. 2a, b. The distribution of the residual environmental capacity of the six elements within the study area is shown in Table 5. According to Fig. 2a, b, and Table 5, the mean remaining environmental capacity of As was 39.45 kg/hm2, where the maximum value occurred in mobile-wind sandy soils and the minimum value in calcareous brown soils. High values were mainly found in the Chachaxiangka East and Chaka Township districts, whereas low values were mainly found in the Xuji Township, Huaitou Tala, and Wulan Districts. In turn, the mean residual environmental capacity of Cd was 0.31 kg/hm2, with the maximum value occurring in mobile wind-sand soils and the minimum value in calcareous brown soils. High values were mainly concentrated in the Huaitou Tala and Chachaxiangka East districts, whereas low values were mainly concentrated in Xuji Township District, Wulan District, and Chaka Township District. Meanwhile, the mean residual environmental capacity of Cu was 169.96 kg/hm2, with the maximum value occurring in mobile windswept sandy soils and the minimum value in calcareous brown soils. High values were mainly observed in the Chachaxiangka East region, whereas low values were mainly observed in Xuji Township, Huaitou Tala, and Wulan. Most values for the remaining environmental capacity in the Chaka Township area were moderate. With respect to Hg, the corresponding mean residual environmental capacity was 5.34 kg/hm2, with the maximum value occurring in the mobile windswept sandy soils and the minimum in the light-brown calcareous soils. High values were mainly concentrated in the Xuji Township and Chachaxiangka East areas, whereas the low values were mainly concentrated in the Delingha-Gahai area. The remainder of the region had mostly intermediate values, with a few low and high values. Furthermore, the residual environmental capacity of Hg was unexpectedly evenly distributed across soil types. As for the mean residual environmental capacity of Pb, this was 217.85 kg/hm2, with the maximum value occurring in mobile wind-sand soils and the minimum value occurring in plowed and irrigated light brown calcareous soils. The low values in this case were mainly distributed in Delingha-Gahai, with a small portion of these low values present in the Chaka Township and Wulan areas; meanwhile, high values were mainly distributed in the Huaitou Tala, Chachaxiangka East, and Chaka Township areas; and most of the values in the Xuji Township area were intermediate. Lastly, the mean residual environmental capacity of Zn was 411.73 kg/hm2, with the maximum value occurring in mobile windswept sandy soils and the minimum in calcareous brown soils. The high values were mainly concentrated in the Chachaxiangka East and Chaka Township areas, although a few of them were recorded in the Huaitou Tara area; in turn, low values were mainly distributed in the Wulan and Huaitoutala areas, with a few of them present in the Chaka Township area, while most values in the Xuji Township area were intermediate. Simultaneously, we found that the low and high values of the remaining environmental capacity of the six elements were distributed in Delinghai-Gahai, and the distribution area of the low values was larger than that of the high values. Most brown calcareous soils are barren, watered, and saline, with little vegetation cover and strong wind erosion32. Thus, most calcareous brown soils showed the lowest values of residual environmental capacity for each of the heavy metals analyzed.

Table 5 Residual capacity in the soils of the study area.
Full size table
Fig. 2
figure 2

(a) Residual environmental capacity of the heavy metals (As, Cd, Cu) in the soils of the study area. (b) Residual environmental capacity of the heavy metals (Hg, Pb, Zn) in the soils of the study area.

Full size image

The level of significance of the remaining environmental capacity of different elements within the research area under different geological backgrounds, land use types, soil types and organic matter content is shown in Table 6. The geologic background values caused highly significant effects on Pb, while soil type, land use type, geologic background and organic matter content caused highly significant effects on the remaining five elements. These findings suggest that the vast majority of elements in the Delingha-Wulan region are controlled by geologic sources and that most elements in the highland oasis are also controlled by soil type and land-use practices. Further, the geological background values in the study area had highly significant effects on Pb because of geological effects. Particularly, bedrock weathering constantly inputs heavy metals into the soil, which easily causes their accumulation33. By analyzing significance, we found that As was most affected by tillage and irrigation of light brown calcareous soils; Cd by light brown calcareous and brown calcareous soils, and Hg by light brown calcareous and tillage and irrigation in brown calcareous soils. Conversely, Cu and Zn were most affected by brown calcareous soils. Because brown calcareous soils constitute most of the soils in the research area, tillage and the use of fertilizers during tillage are related to the residual environmental capacity of the six elements. Additionally, our analysis revealed that Cd and Cu were most affected by heathlands, Hg was affected by shrublands, and Zn was affected by bare gravel. Indeed, Zn was affected by three types of land use: barren grassland, bare gravel land, and irrigated land. Wasteland can be used for development and as a backup resource for agriculture, forestry, and livestock production. Shrublands improve ecology, retain water, and stabilize soils. Therefore, the irrational exploitation of wastelands affects the environmental capacity of Cd and Cu, and exacerbates soil erosion and land desertification in plateau oases. Based on this study, we found that some of the stratigraphic attributes of the area where the shrub forest is located are Holocene swamp deposits, and there is more water flow in the areas of Xuji Township and Chachaxiangkadong, where high values of the average remaining environmental capacity of Hg are located.

Table 6 Significant effects of geological setting, land use type, soil type and organic matter content on the environmental carrying capacity of heavy metals.
Full size table

This finding indicates that Hg enters wetland aquatic environments via surface (subsurface) runoff and eventually accumulates in wetland sediments. In addition, the distribution and transport of Hg are affected by the flow and mixing in the water column34,35. Table 6 shows that the majority of heavy metal elements are also significantly influenced by the soil organic matter (SOM) content. SOM can affect the solubility, mobility, and bioavailability of heavy metals through adsorption and complexation36,37. Studies have indicated that the presence of SOM can reduce the activity of certain heavy metals, thereby decreasing their potential environmental hazards. For example, it is mentioned in the study that SOM can form stable complexes with heavy metals, thus reducing their migration ability in the soil38.

Dynamic environmental capacity forecasting

Because heavy metals are in a dynamic equilibrium in the soil, the dynamic environmental capacity of the soil must be considered while researching environmental capacity. Based on Eqs. (1) and (4), the dynamic environmental capacity of the six elements under study in the Delingha-Wulan area was predicted after 20, 30, and 50 years. These prediction results are shown in Fig. 3. As can be seen, the environmental capacity of the elements within the research domain decreased with time, suggesting that the soil in the Delingha-Wulan region has a limited ability to purify itself. Even in the absence of drastic anthropogenic disturbances, environmental capacity is reduced by the constant input of heavy metals due to bedrock weathering. Owing to the extremely high temperatures of the Tibetan Plateau and the gradual increase in rainfall in the Chaidam Basin, regional soil erosion can be exacerbated, affecting the migration and accumulation of heavy metals39. Concomitantly, the environmental capacities of various constituents vary significantly, as does the rate at which the environmental capacity is reduced. Specifically, the environmental capacities of the research area for elemental Hg and Pb declined at faster rates (11.6% and 11.1%, respectively), between 2024 and 2074. In turn, Cd will exhibit the lowest environmental capacity (0.08 kg/hm2) in 2074. This forecast indicates a high risk of Cd exposure and overloading of the environmental capacity. Because calcareous brown soils are the main cultivated soils of oases in the study area, the source of Cd is controlled by oasis agriculture in addition to the geological background. Similarly, Hg has an environmental capacity of 0.60 kg/hm2, indicating that it is also at risk, probably owing to the high rainfall in the Chaidam Basin, which increases wet deposition and affects the soil Hg content40. Because Hg is most influenced by calcareous brown soils, it is controlled by oasis agriculture, in addition to natural factors and geological background. Therefore, the study area requires special attention to ensure rational tillage. Overall, the environmental capacities of the different elements varied among the different soil types. Special attention should be paid particularly to the effects of natural factors on the soils in the Tibetan region. Owing to the unique ecological function of the soil itself, protection of the soil environment must include comprehensive and strengthened management, strict control of multiple sources, and prevention-oriented, comprehensive prevention and control methods11,41. According to data analysis and predictions, the reasons for a decrease in environmental capacity over the next 50 years, besides the continuous input of heavy metals due to bedrock weathering, are also influenced by oasis agriculture. If land is overdeveloped and utilized excessively in the future, along with intensified farming and mining activities, this will accelerate the rate at which environmental capacity decreases. Conversely, if policies such as returning farmland to forests and grasslands are implemented and land use is reduced, this will slow down the rate of decline. Additionally, the current trend in climate change is global warming, which will impact water resources and consequently influence agriculture and changes in environmental capacity. Therefore, owing to the special nature of oases in the arid zone of the Tibetan Plateau, it is necessary to comprehensively consider the effects of soil properties, vegetation cover, water circulation, as well as anthropogenic activities, and take targeted measures to prevent and control these activities to effectively avoid and manage heavy metal contamination, while protecting the ecological environment and solve environmental and ecological problems in oases in the arid zone of the Tibetan Plateau.

Fig. 3
figure 3

Dynamic environmental capacity in the soils in the study area.

Full size image

Evaluation of integrated environmental capacity

Based on Eqs. (1) and (5), the individual and composite environmental capacity indices of the six research area elements were visualized for early warning (Figs. S2a and S2b, Fig. S3). In the Delingha-Wulan area, the average integrated environmental capacity-index value for soils was 0.995, indicating an intermediate environmental capacity and a mild accompanying health risk. The average capacity indices for As, Cd, Cu, Hg, Pb, and Zn in the study area were 1.002, 0.984, 0.998, 0.999, 0.991, and 0.999, respectively. Among these, As had a lower risk than the other elements. In contrast, Cd had a higher risk than any other element. However, the average capacity indices in the study area did not significantly differ among elements. We find that most of the low values of the elements are concentrated in the Xuji Township, Wulan, and Delingha-Gahai areas (Figs. S2a and S2b, Fig. S3). On the other hand, Cu and Zn showed large low-value distributions in all six regions. Previous studies showed that the study area spreads across four Class-III metallogenic zones distributed in similar locations to the low-value distribution zones of Cu and Zn. Therefore, the development of the minerals may lead to localized enrichment of Cu and Zn. Based on the information reviewed, rainfall has increased in the basin, and, because of the showering effect of rain, heavy metals in mines are transported to the external environment, leading to an increase in heavy metal content in the soil42,43,44.

The distribution of the individual environmental capacity indices of the six elements in different soil types in the study area is shown in Table 7, with some variations in the environmental capacity indices of the elements under study in various soil types. The mobile windswept soils had the highest environmental capacity index, with a mean value of 1.15, which may be attributed to the erosive and transporting effects of wind, resulting in the transport of elements to other locations before they begin to accumulate. Brown calcareous soils had the lowest environmental capacity, with a mean value of 0.94, presumably, because calcareous brown soils are the predominant cultivated soils in the study area, which have a reduced environmental capacity owing to the accumulation of elements because of irrational development and utilization of arable land, as well as the application of chemical fertilizers.

Table 7 The soil environmental capacity level in the study area.
Full size table

In addition, The stability of human activities and climatic conditions in the study area greatly enhances the reliability of the environmental capacity assessment. Minimal human disturbances, such as rotational grazing, ensure that land-use patterns remain consistent over time, reducing anthropogenic impacts on soil chemical profiles45. Similarly, the plateau’s climatic stability, characterized by minimal seasonal and annual variability, prevents large-scale sediment redistribution or geochemical shifts caused by extreme weather events46. Additionally, the comprehensive methodological framework employed in this study supports the reliability of the results. By combining geochemical background analysis, enrichment factor evaluation, and dynamic environmental capacity modeling, the assessment effectively isolates the influence of geological factors and soil characteristics. These approaches ensure that the observed trends are robust and reflective of the intrinsic properties of the Qinghai-Tibet Plateau, providing a reliable basis for understanding soil environmental capacity in arid plateau ecosystems. Based on the analysis of the data, we concluded that the decreasing trend in the environmental capacity of the four elements (Cd, Cu, Hg, and Zn) is not only related to natural factors and geological background, but to human activities in the oases of the study area as well. For example, the levels of Cu and Zn are affected by mineral development and agricultural practices, whereas those of Cd and Hg are only affected by agricultural practices. Therefore, agricultural farming has had the greatest impact on carrying capacity of the oases in the study area, and needs to be controlled.

Enrichment factor analysis

Based on Eq. (6), the enrichment factors of the six elements in the soils of the Delingha-Wulan area were calculated, (Fig. 4). The order of enrichment of the soil elements in the study area was Hg (1.15) > Pb (1.04) > As (1.01) > Cu (1.00) >.

Fig. 4
figure 4

Violin and box plots of enrichment factor of heavy metals.

.

Full size image

Zn (1.00) > Cd (0.51). Overall, the soil heavy metal elements in the Delingha-Wulan area were mildly enriched, except for Cd, which was not enriched in this area. Among the six elements, Hg enrichment was the most prominent, and with a large coefficient of variation. As shown in Table 6, Hg was significantly influenced by geological background, soil type, and land use type, indicating that the enrichment of Hg in the study area was most related to the geological background, with localized areas of high background. Light brown calcareous soils and tillage-irrigated brown calcareous soils were the major tillage soils in the study area, and Hg was highly influenced by light brown calcareous soil and tillage-irrigated brown calcareous soil, as well as the study area develops cultivation vigorously. Therefore, the higher application rates of fertilizer have led to Hg showing the greatest enrichment among the elements analyzed in the study area. According to Table 6, it can be concluded that Pb is significantly influenced solely by geological background, indicating the presence of localized high background areas for Pb. The survey study reveals that the geographical locations of these Pb-enriched areas are near townsites and mining lands, suggesting a close relationship between surface enrichment of Pb and mining activities. Conversely, the lack of enrichment of Cd indicates that the wasteland of the oasis in the arid zone has not been overexploited or irrationally utilized. Although human disturbances are generally minimal in plateau oases, activities such as farming, rotational grazing, and mining can lead to the enrichment of certain elements, potentially causing localized environmental impacts. Therefore, we need to reduce the application of chemical fertilizers, strengthen the rational development and utilization of barren grasslands and other land-use types, and return more farmland to forests and grasslands to improve the ecological restoration of the Tibetan Plateau region and reduce the escalation of soil erosion and desertification.

Study limitations

The study of environmental capacity is critical for determining background and risk reference values for the soil environment. In this study, localized soil background values were established according to the actual situation in the Delingha-Wulan area, with a certain degree of accuracy. Additionally, the risk reference value for the six elements is 6.5 < pH ≤ 7.5 in the risk screening value of other categories in the Risk Controlling Regulation for Soil Pollution on Agricultural Land (GB15618-2018). However, due to the many unique environmental characteristics of the Qinghai-Tibet region, there may be some uncertainty in the risk reference values used. Unfortunately, there are few studies on the Qinghai-Tibet region, and there is a lack of harmonized local standards. In the future, more data and multiple analyses are needed to derive local standards suitable for the Qinghai-Tibet region. Second, this study calculated the soil dynamic capacity using the widely accepted K-value, 0.9. However, the differences in the residual rates of different elements in the soil may have led to uncertainties in the prediction of the dynamic capacity in this study. In the future, K values of the different elements should be calculated according to the actual situation of the soil weathering, land erosion, and leaching processes of heavy metals in the soils in the Qinghai-Tibet region. Thirdly, there are differences in the distribution of heavy metals and organic pollutants at different depths. For example, in the soil profile of the Suaeda salsa salt marsh in the Yellow River Delta, the highest concentrations of As and Cu were found at a depth of 20–40 cm, while the highest concentration of Cr was observed at a depth of 0–10 cm47. Sampling only within the 0–20 cm depth may lead to an underestimation or overestimation of the actual risk posed by contaminants, thereby affecting the accuracy of environmental capacity predictions.

Dynamic environmental capacity is an exponential function. Although widely cited, the calculations show that the reduction in environmental capacity decreases as time of control increases, meaning that the reduction in environmental capacity in the years 0–10 is greater than in the years 10–20, as determined by the formula. Therefore, this may lead to some bias in the prediction results, whereby, more research is needed to improve the dynamic environmental capacity formula suitable for the Qinghai-Tibet region. At the same time, because of the low sampling of mobile windswept soils, it was not possible to analyze the impact of wind transport on the environmental capacity of the elements more concretely and effectively. In addition, we need to consider the uptake and degradation of heavy metals in the soil by vegetation in highland oases.

Moreover, this study analyzed the environmental capacity of the Delingha-Wulan region by considering different geological backgrounds, land-use types, and soil types. Nonetheless, the environmental capacity of the soil reflects the features of the surrounding environment and its functional role, and the result is a range of values, which is a fundamental property of the soil. Many factors affect the capacity of the soil environment, including: soil type, type of land use, nature and type of pollutants, the specific environmental conditions of the soil, and the intensity of human activities.

Therefore, in the future, we need to identify additional factors influencing the environmental capacity of oases in arid zones and obtain more data to better determine the situation and factors influencing the environmental capacity of oases in arid zones.

Conclusions

This study focused the environmental capacity impact of heavy metals in oases in arid zones. Specifically, the Delingha-Wulan area was selected as the study area. The findings summarized herein showed that the geological background has a significant impact on the residual capacity of the six heavy metals analyzed. Further, the data showed that, in the Qinghai-Tibet region, most studied elements are controlled by geological sources and that, even in the absence of external interferences, the environmental capacity will continue to decrease; whereby, strengthening pollution prevention and control measures is vital for soil restoration and conservation. The predicted results of the dynamic environmental capacity were generally consistent with actual observations, further demonstrating the suitability of the Tibetan Plateau region for studying the factors influencing the environmental capacity of heavy metals in arid zone oases. From our analysis of the data, we concluded that most of the elements in the study area are significantly associated with the main tillage-soil brown calcareous soils and the unused grassland land-use type. These findings indicate that the decrease in the environmental capacity of the elements under study may result from excessive cultivation and irrational utilization by oasis people for production and living in the arid zone. In the Delingha-Wulan area, the average integrated environmental capacity index value for soils was 0.995, indicating an intermediate level of environmental capacity and a corresponding mild health risk. Our study emphasizes the soil environmental capacity of oases in the arid zone of the Qinghai-Tibetan Plateau region and the environmental and ecological problems of oases in the arid zone considering the research results. Furthermore, our study presents preliminary recommendations for the prevention and control of soil pollution and the reduction of soil erosion and land desertification. However, because of the lack of soil research in the Qinghai-Tibetan region, there is a need to explore other sources of heavy metals and the influence of soil-forming matrices and parent rocks to protect the ecological environment of the Qinghai-Tibetan Plateau region and solve the environmental and ecological problems of oases in arid zones under specific local conditions. The findings presented herein offer scientific support for environmental conservation and rational and effective utilization of resources in the oases of the Qinghai-Tibet and other arid zones, enrich the research content of soil environmental capacity in the Qinghai-Tibet Plateau region, and provide a foundation and theoretical basis for future research in the same field.