Subjects: Geosciences >> Atmospheric Sciences submitted time 2023-03-13 Cooperative journals: 《干旱区研究》
Abstract： For maintaining crop yield in salt-affected dry agricultural settings, monitoring and analyzing spatiotemporal dynamics of soil salinity over broad areas is crucial yet challenging due to its high variability. The most popular techniques for evaluating spatial distribution patterns and temporal trends are classical statistical analysis and traditional geostatistical analysis, but they are not suitable for accurately capturing spatio-temporal trends of soil salinity due to irregular sampling time and inconsistent spatial position during sampling time. Spatiotemporal Kriging is an extension of spatial geostatistics to space- time geostatistics and may overcome this problem effectively because its model covariance/variance is a function of both space and time. However, its application in spatio-temporal modeling and prediction of regional soil salinity is still unclear. Based on 4582 soil salinity data of 0- 1.8 m soil profiles from 68 monitoring locations in the Longsheng study area of Hetao Irrigation District, Inner Mongolia, spatio- temporal variation characteristics of regional soil salinity using a spatio- temporal geostatistical method, and spatio- temporal Kriging interpolation accuracy was compared with traditional spatial Kriging interpolation. Furthermore, the ability of spatio- temporal Kriging to obtain regional soil salinity dynamics was verified using less than half of the original monitoring locations. The results showed that the spatial variation coefficient of soil salt in the study area ranged from 0.43 to 1.14, which was categorized as medium to strong variability. Regional averaged soil salinity dynamics had obvious seasonal variation characteristics, and the root zone (0-0.6 m) soil salinity accumulated in the crop growing season and desalted in the fallow season, while the deep soil salinity (0.6-1.8 m) was the opposite. The sum-metric model can fit the temporal and spatial experience semi- variance of soil salinity well, and the root mean square error (RMSE) between the predicted value and observed value of soil salinity in each layer was less than 0.21 dS·m-1, which was 0.02-0.09 dS·m-1 less than that of traditional spatial Kriging. The areas of different soil salinity determined by 32 sparse monitoring locations were in good agreement with those determined by all sampling sites, and the mean relative error between areas of different soil salinity for 0-0.6 m and 0.6-1.2 m were −13.20% and −8.35%, respectively. Similarly, the respective RMSE were 466.67 hm2 and 494.43 hm2 and the determination coefficient (R2) were 0.79 and 0.72, indicating that spatial distribution of soil salinity obtained by sparse monitoring locations is consistent with the results of all sampling locations. Spatio- temporal Kriging significantly improves the prediction accuracy of soil salinity compared with ordinary Kriging, since it uses more information on soil salinity in time and space. The accurate estimation of spatio-temporal dynamics of soil salinity in the data set of sparse monitoring points was realized, which can greatly improve the monitoring efficiency of the spatiotemporal pattern of soil salinity in the region.
Subjects: Geosciences >> Other Disciplines of Geosciences submitted time 2022-12-20 Cooperative journals: 《干旱区研究》
Abstract：
With the foundation of global climate change in recent years, droughts in various climatic areas in Inner Mongolia may bring unpredictable disaster risks to local agricultural production. The whole region was divided into five climatic areas, and monthly data was received from 46 meteorological stations from 1981 to 2012. Twenty meteorological stations from 2014 to 2020 were selected to calculate the different time scales of the standardized precipitation evapotranspiration index (SPEI) using precipitation and reference evapotranspiration from the Penman-Monteith method to reveal the drought characteristics and its dominant meteorological factors during the crop growing season (May-September) in Inner Mongolia. A monthly drought during the crop growing season was revealed. The high-incidence month and region of drought in the growing season in various climatic areas were identified by the SPEI of a 1-month scale, and a stepwise linear regression method was selected and verified to extract the dominant meteorological factors driving the drought in each month and the whole growing season in various climatic areas. Results indicated that the following: (1) from the interannual changes, the drought from 1998 to 2008 was more serious, and the drought in other years was less serious. (2) The largest drought area and degree appeared in May during the crop growing season. The probability of moderate drought in the moist and semi- humid area was 37% higher compared to the hyper- arid area, while the extreme drought probably occurred in the moist and semi-humid area and dry and semi-humid area. (3) Dominant meteorological factors driving the drought varied in the crop growth period of various climatic areas in Inner Mongolia. Precipitation and a minimum temperature were the main impact factors for a drought in the crop growing season. (4) Using limited meteorological data, the regression models in each climate region performance well can be used to estimate the monthly SPEI. The results provide a theoretical basis for scientific evaluation of drought characteristics in the spring maize growing season and formulates reasonable measures of response to the drought.
Subjects: Geosciences >> Geography submitted time 2021-06-13 Cooperative journals: 《干旱区研究》
Abstract：河套灌区杭锦后旗各质地盐渍土壤的水分入渗性能、温度及含盐量不同，使土壤改良效果存在差异。为研究“沙穴”种植番茄对不同土质的土壤水分、温度、盐分的迁移规律，通过在土柱中填装3种典型土质（砂壤土、粉壤土、黏壤土），同时布设沙穴，探索在滴灌条件下种植加工番茄以改良不同土壤质地的可行性。结果表明：沙穴种植对不同土质的水热盐迁移影响不同，沙穴种植能显著改善黏壤土土壤水分入渗性能，提高根系层土壤的湿润区面积及含水率，在深度20~40 cm相对增加了24.15%，但降低了砂壤土和粉壤土的保水性，土壤剖面含水率呈上干下湿的特点；沙穴种植可显著提高作物生长初期黏壤土的温度（P20 cm处，粉壤土和黏壤土的盐分淋洗效果显著（P<0.05），平均相对脱盐率达23.28%和56.29%。综合分析沙穴种植对不同土质盐渍土土壤水热盐迁移规律，得出在杭锦后旗3种典型盐渍土中，黏壤土是最适宜沙穴改良方式的土质。
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