Study On The Dynamic Changes Of Soil Salinity In Ili River Irregated Area

Ili River Valley rich in land resources, the development prospect is broad. Therefore, understanding of the regional structure of spatial variability of soil salinity, knowing the movement of soil salinity has become urgent problem in the process of exploitation salt land resources and achieving the goal of sustainable development. For Geostatistics is the theory of the regionalized variable, meet the requirements of the soil characteristics and has become important tool of studying the spatial variability of the soil features. Although in other regions, the use of semi-variance model parameters to describe the spatial variability of soil salinity is very common, but the variability of soil properties is the result of the interaction of many factors. How to use the semi-variogram parameters and reveal the relationship between the spatial variability of soil salinity and different environmental factors? The role of spatial variability, in terms of time, is the its structure stable or not ? and how does it change? Only with the organic combination of spatial and temporal changes, in that comprehensive study on spatial and temporal variability of soil salinity, can we truly understand the spatial and temporal variation structures of salt. This observation of the water and salt to locate information as the basic data source, the use of geostatistical methods and statistics, to explore the spatial structure of soil salinity, to summary soil water and salt movement , analysis of spatial and temporal changes in soil salinity and the surrounding environmental factors. The main contents include:(1) The use of the parameter of the functions of semi-variance theory—a spatial correlation (structural variance and the sill ratio) detected in the region of the spatial variability of soil salinity, depth and area functions. By analyzing the different stages in the soil salinity spatial structure with the six environmental factors and the correlation coefficient between them and found that environmental factors influence different role in different orders, the depth and area. When a high spatial correlation of environmental factors (such as elevation, soil texture) play a major role, a strong structural spatial distribution of soil salinity; the other hand, when a low spatial correlation of environmental factors (such as pH, soil moisture and groundwater ) play a major role, the soil salinity spatial distribution of structural weak.(2) The use of cokriging to improve the accuracy of estimates of soil salt concentration distribution. Chosen Cl~-content as the main variable, total salt content as a secondary variable, of ordinary kriging (OK) and cokriging (COK) statistical methods both to the solute in the soil the role of ions and estimate the interpolation accuracy. Study found that when the small number of sampling points, COK significantly lower than the root mean square error of OK, and the coordination variable correlation with the main variables determine the size of the prediction accuracy of COK.(3) The establishment of a soil salinity associated with environmental factors. In order to more accurately detect different order, the depth of the spatial variability of soil salinity, the six environmental factors and soil salt content was used for pairwise correlation analysis. In the first, second terrace of the value of the underlying soil salinity was significantly correlated with PH; the second phase to the surface salinity was correlated with elevation; the third terrace surface salinity was significantly correlated with soil moisture.(4)Reveals the dynamic laws of soil salinity. Salinity of soil and ground water depth in the high and low prevalence of the Buddha, such as correlation. Soil salinity generally increases with depth and soil salinity X-axis also increases from small to big, to a certain depth (the approximate distribution of the first terrace in the 1.10m; the second terrace 0.98m and 1.23 meters; the third terrace distributed in the 5.52m) at the highest salinity value, the increase of salt content with the depth of decline. Groundwater through the groundwater conductivity and the correlation between the groundwater and soil conductivity and the correlation between conductivity curve equation we predict that during the period 2010 to 2020 electrical conductivity and soil electrical conductivity of groundwater trends, the results show that the soil electrical conductivity did not change much, remained at 1.5 mS / cm or so, keeping in good condition.(5) Analyzed the temporal and spatial variation of soil salinity structures. Upper soil salinity in June, nugget factor (block all the sill) to 0, with a strong spatial correlation; lower the soil salinity has a moderate spatial correlation, which with its high degree of mineralization by affecting the groundwater. The distribution of soil salt content in general is the second terrace are larger. Lower than the upper level of a large spatial variability of soil salt content mostly ring-shaped distribution, spatial structure is strong; lower the mostly planar or block the distribution of more than a patchy areas of high value or low value area, spatial structure weak.