Soil organic carbon (SOC) plays a critical role in carbon cycling and soil quality of agroecosystems. Understanding the factors influencing SOC and the main indicators for soil quality can help in better soil management and sustainable agriculture. In this study, we selected three upland fields (U1, U2 and U3) and three paddy fields (P1, P2 and P3) of saline-alkali agroecosystems to study the impacts of soil physico-chemical properties (soil pH, exchangeable sodium percentage, electrical conductivity and bulk density) and enzyme activities (soil amylase, invertase, catalase and polyphenol oxidase) on SOC dynamics. The soil pH and exchangeable sodium percentage (ESP) had profoundly negative effect on SOC. Soil amylase and invertase activities were significantly positively correlated with SOC in both upland and paddy fields. Catalase promoted the accumulation of paddy SOC and polyphenol oxidase led to the acceleration of decomposition of upland SOC. Additionally, we combined SOC contents, soil physico-chemical properties and soil enzyme activities together to obtain the main indicators of soil quality. The results suggested that, in upland sites, the main factors affecting the soil quality were soil pH, ESP and SOC. As for paddy sites, the main indicators of soil quality were soil pH, amylase and invertase. By comparing the soil quality indicators between upland and paddy fields, it was observed that the inhibiting effect of ESP on paddy soil quality was not as significant as on upland soil quality due to the irrigation practice of rice planting, which could reduce the degree of soil alkalization. Therefore, paddy development has been widely used to improve the saline-alkali land in western Jilin Province of China.

The southwest of Songnen Plain, Northeast China, has an arid climate and is a typical concentrated distribution area of saline-alkali soil. The terrain here is low-lying, with many small, shallow lakes that are vulnerable to climate change. This paper used Landsat satellite remote sensing images of this area from 1985 to 2015 to perform interpretation of lake water bodies, to classify the lakes according to their areas, and to analyze the spatial dynamic characteristics of lakes in different areas. During the 30 years from 1985 to 2015, the number of lakes in the study area decreased by 71, and the total lake area decreased by 266.85 km2. The decrease was more serious in the east and northeast, and the appearance and disappearance of lakes was drastic. The Mann–Kendall test method was used to analyze trends in meteorological factors (annual mean temperature, annual precipitation, and annual evaporation) in the study area and perform mutation tests. Through correlation analysis and multiple generalized linear model analysis, the response relationship between lake change and climate change was quantified. The results showed that the average temperature in the area is rising, and the annual precipitation and evaporation are declining. Temperature and precipitation mainly affected lakes of less than 1 km2, with a contribution rate of 31.2% and 39.4%, and evaporation had a certain correlation to the total lake area in the study area, with a contribution rate of 60.2%. Small lakes are susceptible to climatic factors, while large lakes, which are mostly used as water sources, may be influenced more by human factors. This is the problem and challenge to be uncovered in this article. This research will help to improve our understanding of lake evolution and climate change response in saline-alkali areas and provide scientific basis for research into lakes’ (reservoirs’) sustainable development and protection.

Simulating the hydrological process of a river basin helps to understand the evolution of water resources in the region and provides scientific guidance for water resources allocation policies between different river basins and water resources management within the river basin. This paper provides a scientific basis for the sustainable development of regional water resources and an accurate grasp of the future change trend of runoff by analyzing the hydrological process response of runoff in typical watersheds in Changbai Mountains, China, to climate change. The applicability of the HEC-HMS (The Hydrologic Engineering Center’s-Hydrologic Modeling System) hydrological model in the watershed is verified by calibrating and verifying the daily rainfall-runoff process in the watershed during the wet season from 2006 to 2017. The daily rainfall data of the two scenarios SSP2-4.5 and SSP5-8.5 under the BCC-CSM2-MR model in the 2021–2050 CMIP6 plan were downscaled and interpolated to in-basin stations to generate future daily precipitation series to predict runoff response to future climate change. The daily rainfall data of the two scenarios were downscaled and interpolated to the stations in the basin to generate future daily rainfall series to predict the runoff response under future climate changes. The average certainty coefficient of the HEC-HMS model for daily runoff simulation reached 0.705; the rainfall in the basin under the two climate scenarios of SSP2-4.5 and SSP5-8.5 in the next 30 years (2021–2050) will generally increase, and rainfall will be more evenly distributed in the future; the outlet flow of the basin will increase during the wet season (June–September) in the next 30 years, but it is lower than the historically measured value; the peak flow of the future will appear at most in August and September. The peak flow current time mostly appears in July and August. The time of peak occurrence has been delayed.

Western Jilin Province is one of the world's three major saline–alkali land distribution areas, and is also an important area of global climate change and carbon cycle research. Rhizosphere soil microorganisms and enzymes are the most active components in soil, which are closely related to soil carbon cycle and can reflect soil organic carbon (SOC) dynamics sensitively. Soil inorganic carbon (SIC) is the main existing form of soil carbon pool in arid saline–alkali land, and its quantity distribution affects the pattern of soil carbon accumulation and storage. Previous studies mostly focus on SOC, and pay little attention to SIC. Illumina Miseq high-throughput sequencing technology was used to reveal the changes of community structure in three maize fields (M1, M2 and M3) and three rice fields (R1, R2 and R3), which were affected by different levels of salinization during soil development. It is a new research topic of soil carbon cycle in saline–alkali soil region to investigate the effects of soil microorganisms and soil enzymes on the transformation of SOC and SIC in the rhizosphere. The results showed that the root—soil—microorganism interaction was changed by saline–alkali stress. The activities of catalase, invertase, amylase and β-glucosidase decreased with increasing salinity. At the phylum level, most bacterial abundance decreases with increasing salinity. However, the relative abundance of Proteobacteria and Firmicutes in maize field and Firmicutes, Proteobacteria and Nitrospirae in rice field increased sharply under saline–alkali stress. The results of redundancy analysis showed that the differences of rhizosphere soil between the three maize and three rice fields were mainly affected by ESP, pH and soil salt content. In saline–alkali soil region, β-glucosidase activity and amylase were significantly positively correlated with SOC content in maize fields, while catalase and β-glucosidase were significantly positively correlated with SOC content in rice fields. Actinobacteria, Bacteroidetes and Verrucomicrobia had significant positive effects on SOC content of maize and rice fields. Proteobacteria, Gemmatimonadetes and Nitrospirae were positively correlated with SIC content. These enzymes and microorganisms are beneficial to soil carbon sequestration in saline–alkali soils.

The Chagan Lake Catchment is located in the midwest of Songnen Plain, which is a typical high fluoride groundwater area. High fluoride water has an important impact on the economic development and ecosystem stability of Chagan Lake. In this study, the spatial distribution characteristics and influencing factors of fluorine in Chagan Lake Catchment are discussed by using hydrochemistry and mathematical statistical analysis. The groundwater in the study area was characterized as Na+-rich and Ca2+-poor, with a high pH value and high HCO3– content. The average concentration of F– was 3.02 mg/L, which was the highest in Qian’an County. The dissolution of fluorine-containing minerals and the desorption of F– in soil provided the source of F– in groundwater, while calcite and dolomite precipitation, cation exchange, and evaporation concentration provided favorable conditions for F– dissolving, migration, and enrichment in water. In addition, the concentration of F– in surface water was 4.56 mg/L, and the highest concentration was found in Hongzi Pool and Hua’ao Pool. The elevated concentrations of F– in both surface water and groundwater in the study were affected by human factors, such as rice planting and water conservancy project construction.