Gully erosion stands out as one of the worst aspects of farmland degradation, which induces the loss of arable soil and tractor operation. Most of the gully erosion studies focused on the influence of precipitation erosion, slope erosion, and the freeze–thaw cycle on soil characteristics. Few studies discussed the effect of snowmelt on gully development. In this paper, the gully development induced by snowmelt was observed in a typical gully in Hailun City, the center of the Mollisols area of northeast China. The results showed that, during the snow melting period of 2017, the soil loss induced by snow melting was 0.22 t at the gully head + 0 m, 14.27 t at the gully head + 77 m, and 7.63 t at the gully head + 239 m, while 98.1% of the sediment was from the gully erosion. The horizontal projected area of the observed gully increased by 56.96 m², and the gully head advanced 2.3 m during the snow melting period. About 92.2% of the total runoff occurred in the initial snow melting period. The discharge runoff and sediment concentration had a significant correlation with the air temperature above 0 °C, and the same relationship existed between the discharge runoff and sediment concentration in the initial and middle snowmelt stages. The results indicate that the gully development induced by snowmelt should not be ignored in the area.

There are four sizable black soil regions throughout the world, all of which are valuable natural resources. The black soil region in Northeast China is a major foundation for grain production. Serious risks of soil erosion do exist, and they have an immediate impact on both the country’s food security and future ecological security. Many soil and water conservation measures have been put in place to control soil erosion. However, how effective and suitable are these measures? Currently, systematic analyses and assessments are lacking. The objective of this study was to assess the effectiveness and suitability of soil and water conservation measures on hillslopes using the comprehensive index method and the Pressure–State–Response model. The categorization of effectiveness and suitability of these measures were similar for both methods: that is, very effective and suitable measures included no-tillage + straw mulch and ridge belt or contour ridge. The two methods validated one another. Thus, this categorization standard is useful for choosing the best soil and water conservation measures for different soil erosion regions.

Tillage has been reported to induce seasonal changes of organic carbon (C_micro) and nitrogen (N_micro) in the biomass of microorganisms. Soil microorganisms execute such ecosystem functions as it is an immediate sink of labile biophil elements; it is an agent of a conversion, catalysis and synthesis of humus substances; it transforms soil contaminants into nonhazardous wastes and it participates in soil aggregation and pedogenesis as a whole. However, the seasonal turnover of microorganisms on arable lands in temperate ecosystems has not been studied at a relevant level. Hence, we are aimed at studying the dynamics of such soil microbial biomass patterns as C_micro, N_micro, microbial index (MI = (C_micro/C_TOC)·100%) and CO₂-C emissions against the background of 9 years of tillage and 22 years of abandoned (Ab) and fallow (F) usage. Our study was conducted on a long-term experimental site on a Mollisol in Northeast China. The maximum C_micro and N_micro contents were recorded at the beginning of the growing season at the 0–10-cm layer and mid-July at the 20–40-cm layer, while the minimum content was during August–October. The C_micro content ranged from 577.79 to 381.79 mg⁻¹ kg⁻¹ using Ab in the spring to 229.53 to 272.86 mg⁻¹ kg⁻¹ in the autumn using CT (conventional tillage) and F in the 0–10- and 10–20-cm layers, respectively. The amplitude of N_micro content changes were several times lower as compared with the C_micro. The smallest quartile range (IQR_0.25–0.75) of such changes was shown when using the following treatments: no till (NT) and Ab in the 0–10-, NT and F in the 10–20- and CT in the 20–40-cm layer. The widest C_micro:N_micro ratio was recorded at F and CT in the 0–20- and CT and rotational tillage (Rot) in the 20–40-cm layer. The MI dynamics were similar to the trends of C_micro and N_micro and changed from 0.72 ± 0.168 to 2.00 ± 0.030%. The highest share of C_micro in C_TOC was at Ab (1.82 ± 1.85%) and NT (1.66 ± 1.52 %) in the 0–10-, Ab (1.23 ± 1.27%) and NT (1.29 ± 1.32%) in the 10–20- and Ab (1.19 ± 1.09%) and F (1.11 ± 1.077%) in the 20–40-cm layer, correspondingly. The Pearson’s correlation coefficient between C_micro and C_TOC increased from the upper 0–10- to the lower 20–40-cm layer; it was “strong” and “high” between C_micro and C_TOC. Different uses of Mollisol affected the amplitude of the C_micro and N_micro seasonal changes, but it did not change their trend. Our results suggest the key role of Ab and NT technologies in C_micro accumulation in the total organic carbon (TOC).

Snowmelt erosion and rainfall erosion are important components of soil erosion in Northeast China. Studying how snowmelt and rainfall affect runoff and sediment yield is essential to control soil erosion in this region. Based on the soil and water loss observation data in small watershed during snowmelt and rainfall periods, snowmelt and rainfall erosion processes were studied. The runoff–sediment relationship was analyzed. The results indicate that 13 snowmelt runoff events and 14 rainfall runoff events were recorded. During the snowmelt period, runoff depth (RD) and sediment yield (SY) exhibited a slow increase (early stage), rapid increase (middle stage), and then rapid decrease (late stage) trend. RD and SY in the middle stage were higher than those in the early and late stages. Moreover, during the rainfall period, soil erosion mainly occurred from July to August; during these two months, the rainfall and rainfall erosivity accounted for 66.0 and 91.1% of the total rainfall and rainfall erosivity, respectively; and the RD and SY in this period accounted for 88.4 and 89.8% of total amounts in the whole rainfall period, respectively. In addition, the contributions of snowmelt and rainfall to RD and SY were 18.6 and 81.4%, and 3.8 and 96.2%, respectively. Hysteresis analysis suggested that clockwise hysteresis loop was the dominant pattern, followed by eight-shaped anticlockwise loop, and complex anticlockwise loop.

Rainfall is a major contributor to water erosion of sloping cropland in Northeast China. Identifying how rainfall and slope gradient (S) influence runoff depth (RD) and sediment yield (SY) is crucial for preventing water erosion. Field measurements from runoff plots were collected from 2023 to 2024, and K-means clustering was applied to clarify the rainfall patterns. Response of RD and SY to the rainfall pattern and S were analysed. Key factors impacting RD and SY were explored. The results showed that three rainfall patterns were identified for 34 erosive rainfall events: A (41.2%, medium duration, medium rainfall intensity, and medium rainfall amount (RA)). B (50.0%, short duration, high rainfall intensity, and low RA) and C (5.4%, long duration, low rainfall intensity, high RA). Furthermore, the cumulative RD and SY increased with S for the same rainfall pattern. The cumulative RD and SY responded similarly to rainfall patterns for the same S. The contribution of the rainfall pattern to the cumulative RD and SY decreased in the order of C, A, and B. In addition, rainfall duration (D) and maximum 30-minute rainfall intensity were the key factors affecting RD and SY for rainfall pattern A, respectively. Rainfall erosivity (R) was the key factor affecting RD and SY for rainfall pattern B and C. R and RD were the dominant factors influencing the RD and SY for all rainfall events, respectively.

The small area of cultivated land in the Qingling Mountains of China is important for the survival of the local population. The soil quality in the area has declined dramatically in recent decades due to the exploitation of mineral resources and unreasonable land management. This study estimates the level and spatial distribution characteristic of soil quality using the minimum data set (MDS) and total data set (TDS) methods. We then verify the reliability of the result using the MDS method in the cultivated land around the tailing ponds in the Qinling Mountains of China. A total of 32 soil samples were collected in the cultivated land around the four tailing ponds and 15 indicators comprising the soil chemical, physical, and heavy metal properties were analyzed. The key indicators of soil quality were soil organic matter, total nitrogen, total phosphorus, \({\text{NH}}_{4}^{ + }\)-N, soil water content, and Zn. These indicators were screened by principal component analysis and the norm value method. The soil quality index (SQI) determined using the TDS method (0.29–0.52, 0.40 average) was lower compared to that of the MDS method (0.25–0.65, 0.42 average). The spatial distribution pattern of soil quality indicated a fluctuating trend for SQI, with values increasing with the distance from the tailing ponds. The 1 : 1 line was employed to test the accuracy of the MDS results, with a coefficient of certainty of 0.999 and a coefficient of relative deviation of 0.057. This proves the ability of the MDS method to assess the cultivated soil quality around the tailing ponds in the Qinling Mountains. The results indicate that to realize agricultural sustainability, effective soil quality improvement measures, (e.g., mulch cover, no-till farming, and organic fertilizers) should replace current traditional cropland management measures in the cultivated land around the tailing ponds of the Qinling Mountains.