Spatiotemporal Distribution of Soil Moisture and Salinity in the Taklimakan Desert Highway Shelterbelt

Huang, Yuan; Wang, Yongdong; Zhao, Ying; Xu, Xinwen; Zhang, Jianguo; Li, Congjuan

doi:10.3390/w7084343

Cited by 19 publications

(18 citation statements)

References 40 publications

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“…Spatial dependence is computed as the ratio of nugget to sill. Strong spatial dependence is lower than 25%; a ratio greater than 75% indicates low spatial dependence and values between 25% and 75% moderate dependence [46]:…”

Section: Geostatistical Spatial Analysismentioning

confidence: 99%

Spatial Distribution of Soil Hydrological Properties in the Kilombero Floodplain, Tanzania

et al. 2017

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Analysis and interpretation of soil properties dynamics is a keystone in understanding the hydrologic responses and yield potential of floodplain wetlands. This study characterizes the distribution and spatial trends of selected soil physical properties in the Kilombero floodplain, Tanzania. A total of 76 composite soil samples were taken from 0 to 20 cm and 20 to 40 cm depth in a regular grid design across three hydrological zones, related to flooding intensity defined as fringe, middle, and riparian during the rainy season of 2015. The samples were analyzed for soil texture, bulk density, organic carbon, and saturated hydraulic conductivity. Seasonal soil moisture content was monitored at depths of 10, 20, 30, and 40 cm, using 17 frequency domain reflectometry profile probes type PR2, installed at each hydrological zone for 18 months (March 2015-August 2016). Data were subjected to classical statistical and geostatistical analyses. Results showed significant (p < 0.05) differences in bulk density, texture, soil organic carbon (SOC), and saturated hydraulic conductivity (K sat ) across the hydrological zones. Bulk density showed a clear increasing trend towards the fringe zone. Mean K sat was highest at the riparian zone (69.15 cm·d −1 ), and clay was higher in the riparian (20.3%) and middle (28.7%) zones, whereas fringe had the highest percentage of sand (33.7-35.9%). Geostatistical spatial results indicated that bulk density, silt, and SOC at 0-20 cm had intermediate dependence, whereas other soil properties at both depths had high spatial dependence. Soil moisture content showed a significant (p < 0.05) difference across the hydrological zones. The riparian zone retained the highest soil moisture content compared to the middle and fringe zone. The temporal soil moisture pattern corresponded to rainfall seasonality and at the riparian zone, soil moisture exhibited a convex shape of sloping curve, whereas a concave sloping curve for topsoil and for the middle zone at the subsoil was observed during the start of the dry season. Our results are seen to contribute to a better understanding of the spatial distribution of soil properties and as a reference for soil and water management planning in the floodplain.

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Section: Geostatistical Spatial Analysismentioning

confidence: 99%

Spatial Distribution of Soil Hydrological Properties in the Kilombero Floodplain, Tanzania

et al. 2017

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“…The soil moisture rates in Robinia pseudoacacia forest varied periodically with seasons, the soil moisture rate is lower in the dry season as precipitation is rare and high evaporation but higher in the rainy season [29,30]. In this study, samples were taken in dry season and the soil moisture decreased with soil depth in healthy Robinia pseudoacacia forest because of soil water loss by transpiration of trees, understory grasses and evaporation from the ground surface [31][32][33], while increase in severe dieback forest because of lower groundwater table (less than 2 m at our sampling period) the reason for this phenomenon was that all severe dieback Robinia pseudoacacia forests located near river (less than 100 m) and also distributed along river direction (Figure 1). Moisture could limit soil respiration when the soil was too wet [34].…”

Section: Discussionmentioning

confidence: 99%

Effects of Soil on Degradation of Robinia pseudoacacia Forests in the Yellow River Delta in China

Hong¹,

Claire²,

Z³

et al. 2016

Forest Res

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“…The GLM is a flexible generalisation of ordinary linear regression that allows for response variables that have error distribution models other than a normal distribution. The study results from Yuan Huang [42] show that soil moisture, EC and clay content were log-normally distributed, while organic carbon, sand and silt content were normally distributed. Therefore, the Logit Link Function was chosen to model the correlation between spectral data and soil salinity in this study.…”

Section: Spectral Modelling Of Soil Propertiesmentioning

confidence: 97%

A Case Study of the Forced Invariance Approach for Soil Salinity Estimation in Vegetation-Covered Terrain Using Airborne Hyperspectral Imagery

Liu

Buchroithner

2018

IJGI

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Soil spectroscopy is a promising technique for soil analysis, and has been successfully utilized in the laboratory. When it comes to space, the presence of vegetation significantly affects the performance of imaging spectroscopy or hyperspectral imaging on the retrieval of topsoil properties. The Forced Invariance Approach has been proven able to effectively suppress the vegetation contribution to the mixed image pixel. It takes advantage of scene statistics and requires no specific a priori knowledge of the referenced spectra. However, the approach is still mainly limited to lithological mapping. In this case study, the objective was to test the performance of the Forced Invariance Approach to improve the estimation accuracy of soil salinity for an agricultural area located in the semi-arid region of Northwest China using airborne hyperspectral data. The ground truth data was obtained from an eco-hydrological wireless sensing network. The relationship between Normalized Difference Vegetation Index (NDVI) and soil salinity is discussed. The results demonstrate that the Forced Invariance Approach is able to improve the retrieval accuracy of soil salinity at a depth of 10 cm, as indicated by a higher value for the coefficient of determination (R 2 ). Consequently, the vegetation suppression method has the potential to improve quantitative estimation of soil properties with multivariate statistical methods.

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Spatiotemporal Distribution of Soil Moisture and Salinity in the Taklimakan Desert Highway Shelterbelt

Abstract: Salinization and secondary salinization often appear after irrigation with saline water. The Taklimakan Desert Highway Shelterbelt has been irrigated with saline ground water for more than ten years; however, soil salinity in the shelterbelt has not been evaluated.

Cited by 19 publications

References 40 publications

Spatial Distribution of Soil Hydrological Properties in the Kilombero Floodplain, Tanzania

Spatial Distribution of Soil Hydrological Properties in the Kilombero Floodplain, Tanzania

Effects of Soil on Degradation of Robinia pseudoacacia Forests in the Yellow River Delta in China

A Case Study of the Forced Invariance Approach for Soil Salinity Estimation in Vegetation-Covered Terrain Using Airborne Hyperspectral Imagery

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