Source and Mobilization Mechanism of Iron, Manganese and Arsenic in Groundwater of Shuangliao City, Northeast China

Excessive levels of Fe, Mn and As are the main factors affecting groundwater quality in Songliao plain, northeast China. However, there are few studies on the source and mobilization mechanisms of Fe, Mn and As in the groundwater of Northeastern China. This study takes Shuangliao city in the middle of Songliao plain as an example, where the source and mobilization mechanisms of iron, manganese and arsenic in groundwater in the study area were analyzed by statistical methods and spatial analysis. The results show that the source of Fe and Mn in the groundwater of the platform is the iron and manganese nodules in the clay layer, while, in the river valley plain, it originates from the soil and the whole aquifer. The TDS, fluctuation in groundwater levels and the residence time are the important factors affecting the content of Fe and Mn in groundwater. The dissolution of iron and manganese minerals causes arsenic adsorbed on them to be released into groundwater. This study provides a basis for the rational utilization of groundwater and protection of people’s health in areas with high iron, manganese and arsenic contents.

The Estimation of Reservoir Temperature for Thermal Springs Using the Integrated Multicomponent Geothermometry Method at Changbai Mountain, Northeastern Songliao Basin, China

The Changbai Mountain volcanic region, eastern Songliao Plain, China, is considered a potential target development area for geothermal water exploitation. To assess the feasibility of geothermal development, we applied integrated multicomponent geothermometry (IMG) in the program GeoT to estimate the geothermal reservoir temperatures for four major thermal springs in this area. Numerical optimizations of Al and HCO3- concentrations, dilutions, and steam fractions were conducted to reconstruct the original deep fluid compositions by the IMG method. The results show that the geothermal reservoir temperatures of these springs range from 118 to 172°C in the Changbai Mountain volcanic region. In contrast to classic geothermometers, the IMG method can quantify processes affecting the fluid chemical composition and yield reasonable temperatures. The reservoir temperatures for the Julong and Jinjiang thermal springs are significantly greater than those for the Shibadaogou and Xianrenqiao thermal springs. Moreover, the geothermal deep circulation characteristics of the above springs are also investigated based on reservoir temperature estimates. The methods presented in this study could be applied to other geothermal fields under similar geothermal resource conditions.

Spatial distribution characteristics of phaeozem in Songliao Plain based on RS

Phaeozem is one kind of scarce resources on the earth. Due to the restrictions of natural factors and the influence of human activities over the years, phaeozem degradation has become increasingly serious. Based on images of the ASTER in 2006 and the ETM+ in 2000 in this paper, the phaeozem organic matter content which is greater than 2 ％ was obtained by using quantitative retrieval. Through the three-dimensional remote sensing image, terrain rendering and relevant information were analyzed. On the basis of the above, the spatial distribution characteristics of phaeozem in Songliao Plain were analyzed using DEM (digital elevation model) data. The results show that the total area of phaeozem in Songliao Plain is about 51360.15 km2, and the phaeozem organic matter content is gradually increasing along with the increasing latitude or longitude, and decreasing along with increasing slope. In addition, the soil organic matter content is lower in southern slopes than that in northern slopes.

Effect of Climate Change on Maize Yield in the Growing Season: A Case Study of the Songliao Plain Maize Belt

Based on the 1965–2017 climate data of 18 meteorological stations in the Songliao Plain maize belt, the Coupled Model Intercomparision Project (CMIP5) data, and the 1998–2017 maize yield data, the drought change characteristics in the study area were analyzed by using the standardized precipitation evapotranspiration index (SPEI) and the Mann–Kendall mutation test; furthermore, the relationship between meteorological factors, drought index, and maize climate yield was determined. Finally, the maize climate yields under 1.5 °C and 2.0 °C global warming scenarios were predicted. The results revealed that: (1) from 1965 to 2017, the study area experienced increasing temperature, decreasing precipitation, and intensifying drought trends; (2) the yield of the study area showed a downward trend from 1998 to 2017. Furthermore, the climate yield was negatively correlated with temperature, positively correlated with precipitation, and positively correlated with SPEI-1 and SPEI-3; and (3) under the 1.5 °C and the 2.0 °C global warming scenarios, the temperature and the precipitation increased in the maize growing season. Furthermore, under the studied global warming scenarios, the yield changes predicted by multiple regression were −7.7% and −15.9%, respectively, and the yield changes predicted by one-variable regression were −12.2% and −21.8%, respectively.