Modeling variations in soil salinity in the oasis of Junggar Basin, China

Abstract

Soil salinization leads to a significant degradation for oasis land. Variations in soil salinity are controlled by geologic, geomorphic, climatic, and hydrologic factors that are scale dependent. Many factors characterize soil salinity and its variations. Empirical mode decomposition (EMD) and correlation analysis are usually applied to examine the variations of soil salinity at different scales. However, few researches have been conducted on the modeling of these variations among different scales that requires further development and refinement. This paper investigates the potential of assessing scale‐specific variations in soil salinity via EMD using 2 modeling approaches (random forest and linear models). The remotely sensed environmental factors including land surface temperature, evapotranspiration, Tropical Rainfall Measuring Mission precipitation, and digital elevation model products were used as inputs for the models. The Junggar Basin in Xinjiang Province of China was selected as study area because the oasis was quite typical in the whole country and even in mid‐Asia. Soil salinity data and environmental factors were first decomposed using the EMD algorithm. Then, the decomposed components of the remotely sensed environmental factors were evaluated, and the most important components of each factor were selected to model the salinity variations that were represented by the decomposed components of soil salinity. The salinity variations estimated from the environmental factors were favorably consistent with the decomposed components of the soil salinity data, with coefficients of determination (R2) ranging from 0.24–0.52 and 0.73–0.98 for the linear and random forest models, respectively. In addition, land surface temperature and salinity were coupled well at the 326‐ and 334‐km scale. Our results showed that reasonably accurate results can be obtained using the proposed approach.

Spatial Distribution Characteristics of Soil Salinity and Moisture and Its Influence on Agricultural Irrigation in the Ili River Valley, China

“…Therefore, when exploring the degree to which other factors influence the spatial variability of soil salinity and moisture, the interaction between factors needs to be studied further. Secondly, spatial variation of soil properties is scale specific, so the factors that affect soil properties at different scales are different [36,38]. Therefore, the relationship between spatial variability of soil salinity and moisture and topographic factors in large-scale regions should be further studied and considered in the future.…”

“…Additionally, there are some differences in the spatial variation of soil salinity and moisture in different scales [36,37]. Ma, et al [38] indicated that the variation of soil salinity is controlled by topographic, climatic, and hydrological factors at the scale. Ren, et al [39] explored the correlation between soil salinity with groundwater, topography, irrigation, and other factors with three scales.…”

Quantitative Estimation of Soil Salinization in an Arid Region of the Keriya Oasis Based on Multidimensional Modeling

“…Approximately 1.128 billion hectares of global lands were affected by soil salinization [2], and in China, salinized areas accounting for approximately 9 percent of the national land resources [3,4]. Major causes of soil salinization can be separated into two ways: one way from primitive soluble saline water, scarce precipitation, and intense evaporation and the other way from shallow groundwater levels, excessive agricultural activities, and flooding irrigation agriculture [5,6]. Quantitative analysis of salt-affected land is one of the effective methods to evaluate the extent of soil salinization, and there is a wide divergence in the embedding temporal and spatial dimensions.…”

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“…In the arid region, the spatial heterogeneity of soil was significant, which might result in the underestimation of SMC (Thevs et al 2015;Zhang et al 2017). Studies on the soil properties in arid areas have achieved similar results (Ding et al 2018;Ma et al 2018). In recent years, the uncertainties of the ELM method were reviewed by Liu and Lin (Lin et al 2015;Liu et al 2015), especially for the different activation functions and subsequent robustness.…”

“…SMC is the main factor that limits the growth of crops to an oasis in this region. Furthermore, increasing human activities in recent years have led to regional SMC imbalances and increased soil salinization within the oasis (Ma et al 2018;Wu et al 2015). During the implementation of sustainable soil management practices and precision agriculture, understanding the spatial distribution of SMC is essential for determining the regional drought situation and measuring water and salt transport in soils.…”