Moisture influencing factors on semi-fixed sand dunes in southeast edge of Tengger Desert

doi:10.7522/j.issn.1000-694X.2025.00227

Journal of Desert Research ›› 2025, Vol. 45 ›› Issue (5): 328-337.DOI: 10.7522/j.issn.1000-694X.2025.00227

Moisture influencing factors on semi-fixed sand dunes in southeast edge of Tengger Desert

Shurui Yang¹(), Tian Yang², Lu Zhang², Dinghai Zhang²(), Haidi Qi²

^1.Gansu Minqin Liangucheng National Nature Reserve Management and Protection Center，Minqin 733399，Gansu，China
^2.Center for Quantitative Biology，College of Science，Gansu Agricultural University，Lanzhou 730070，China

Received:2025-05-23 Revised:2025-07-23 Online:2025-09-20 Published:2025-09-27
Contact: Dinghai Zhang

Abstract

Abstract:

Soil moisture is a key driver of the sand fixation vegetation patterns and processes in arid sandy regions， exhibiting significant variability across different microtopography types in the sandy area. This study focuses on soil moisture in the semi-fixed dunes on the southeastern edge of the Tengger Desert， analyzing its distribution characteristics across four microtopographic types： windward slope， leeward slope， the top of dune， and the bottom of dune. A partial least squares structural equation model （PLS-SEM） was employed to determine the influence paths of topography， shrub， and herbaceous factors on soil moisture. Additionally， an interpretable machine learning model （SHAP） was used to identify the key factors influencing soil moisture among topographic and vegetation factors and elucidate their mechanisms. The results indicate that the surface soil moisture at the bottom of dune is highest， at 1.21%， while the mid- and deep-layer soil moisture on the leeward slope reaches 2.25% and 2.43%， respectively. As herbaceous coverage increases and slope direction changes， soil moisture at different depths first decreases and then increases. Surface soil moisture shows a trend of decrease followed by increase as height difference changes， with a threshold of 3 meters in elevation. The soil moisture in the middle and deep layers also exhibits a trend of increasing and then decreasing with the rise in biomass and shrub cover， with thresholds of 30 g and 40%， respectively.

Key words: Tengger Desert, semi-fixed dune, soil moisture, topography-vegetation factor, structural equation model, SHAP model

CLC Number:

Shurui Yang, Tian Yang, Lu Zhang, Dinghai Zhang, Haidi Qi. Moisture influencing factors on semi-fixed sand dunes in southeast edge of Tengger Desert[J]. Journal of Desert Research, 2025, 45(5): 328-337.

Figures/Tables 9

Fig.1 Schematic diagram of test sample plots

Fig.2 Distribution of soil moisture in surface， middle and deep layers on four microtopography types

Table 1 Average soil moisture content and coefficient of variation in surface， middle and deep layers of four microtopography types

微地貌	0~40 cm		40~200 cm		200~300 cm
微地貌	平均土壤水分/%	变异系数	平均土壤水分/%	变异系数	平均土壤水分/%	变异系数
背风坡	0.71	0.62	2.25	0.52	2.43	0.36
丘底	1.21	0.41	2.23	0.25	1.98	0.23
丘顶	0.81	0.87	1.57	0.46	2.01	0.27
迎风坡	0.33	0.57	0.86	0.41	1.09	0.51

Table 2 External model validity test

潜变量	克伦巴赫α系数	DG. rho系数	第一特征根	第二特征根
地形	0.89	0.92	2.58	0.53
灌木植被	0.61	0.84	1.43	0.56
草本植被	0.66	0.80	2.09	0.99
土壤水分	0.79	0.88	2.14	0.70

Fig.3 Effects of topography and vegetation factors on soil moisture based on PLS-SEM Model

Table 3 Model evaluation results of two machine learning models for surface， middle and deep soil moisture

评价指标	算法	表层	中层	深层
$R 2$	RF	0.84	0.70	0.83
$R 2$	XGBoost	0.68	0.61	0.59
MSE	RF	0.19	0.52	0.30
MSE	XGBoost	0.31	0.45	0.36
MAE	RF	0.34	0.50	0.35
MAE	XGBoost	0.28	0.58	0.41
MAPE/%	RF	5.25	13.5	5.47
MAPE/%	XGBoost	7.11	13.7	11.59

Table 3 Model evaluation results of two machine learning models for surface， middle and deep soil moisture

评价指标	算法	表层	中层	深层
$R 2$	RF	0.84	0.70	0.83
$R 2$	XGBoost	0.68	0.61	0.59
MSE	RF	0.19	0.52	0.30
MSE	XGBoost	0.31	0.45	0.36
MAE	RF	0.34	0.50	0.35
MAE	XGBoost	0.28	0.58	0.41
MAPE/%	RF	5.25	13.5	5.47
MAPE/%	XGBoost	7.11	13.7	11.59

Fig.4 SHAP interpretation map of surface， middle and deep soil moisture based on random forest model

Fig.5 Ranking of the importance of variables affecting soil moisture at different depths based on random forest models

Fig.6 SHAP feature dependence graph based on random forest

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Moisture influencing factors on semi-fixed sand dunes in southeast edge of Tengger Desert

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