Regional temporal persistence of dried soil layer along south–north transect of the Loess Plateau, China

Jia, Xiaoxu; Shao, Mingan; Zhang, Chencheng; Zhao, Chunlei

doi:10.1016/j.jhydrol.2015.06.025

Cited by 76 publications

(68 citation statements)

References 45 publications

(76 reference statements)

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“…The SWC data for the 0‐to 1.0‐m soil layer were excluded in our analysis to avoid the seasonal SWC variation caused by rainfall during the sampling period and ensure that the data from the study sites were comparable. Therefore, the present study focused on analyzing SWS below 1.0‐m depth from the surface, consistent with other studies (Jia et al, ; Wang et al, ).…”

Section: Methodssupporting

confidence: 80%

Estimating regional losses of soil water due to the conversion of agricultural land to forest in China's Loess Plateau

et al. 2017

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Afforestation on the Chinese Loess Plateau (CLP) has been extensively implemented by the central government over the past decades to control soil erosion. The conversion of agricultural land to forest, however, has led to decreases in soil‐water storage (SWS), which may in turn limit tree growth and threaten the health of ecosystems in the region. This study estimated the regional patterns of losses of soil water (ΔSWS) following conversions across the CLP. Soil‐water content at 0–5.0 m was measured in 169 forests on the plateau, and the initial preafforestation SWS at each sample site was then estimated using stepwise regression. The mean ΔSWS in the 1.0‐ to 5.0‐m profile across the study area was 203.7 mm, with an estimated annual average ΔSWS rate of 16.2 mm/year. ΔSWS and its main contributing factors varied amongst 3 rainfall zones. ΔSWS generally increased with mean annual precipitation (MAP). ΔSWS depended primarily on tree age in the >550 mm MAP zone and on slope gradient and initial SWS in the <450 mm MAP zone. This result suggested that the vegetation might be more important than soil or topographic properties for estimating ΔSWS following the conversion of farmland in the wettest area of the CLP. Our study also suggests that MAP, tree age, slope gradient, and initial SWS have important effects on ΔSWS, which vary with rainfall. Understanding the regional hydrological effects of afforestation is necessary for the efficient management of soil‐water resources on the CLP and in other water‐limited regions.

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Section: Methodssupporting

confidence: 80%

Estimating regional losses of soil water due to the conversion of agricultural land to forest in China's Loess Plateau

et al. 2017

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“…Compared to the croplands, the coarser soils and thus higher hydraulic conductivity in the forestlands and grasslands (Table SI) are supposed to enhance water and solute leaching. However, severe dry soil layers were observed at shallow soil depths there in a recent study (Jia et al, ), which might largely limit the leaching of dissolved OC.…”

Section: Resultsmentioning

confidence: 90%

“…First, spatial variations in SWC increases with increasing soil depth along the plateau transect (Jia et al, ). Second, dry soil layer develops in the soil layers below 100‐cm soil depth under forestlands and grasslands due to deep root water uptake (Jia et al, ). The dry soil conditions in the deep soil layers are difficult to reclaim in the CLP study area due to limited precipitation, deep water table and high vegetation water demand, influencing organic matter flow from shallow soil to deep soil layers (Zhang et al, ; Wang et al, ).…”

Section: Resultsmentioning

confidence: 99%

A State‐Space Analysis of Soil Organic Carbon in China's Loess Plateau

et al. 2017

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An accurate estimation of soil organic carbon (SOC) is important for the evaluation and management of carbon (C) flux in terrestrial ecosystems. However, there is little work on the spatial variability of SOC in deep soils and its driving factors. Thus, the objective of the study was to derive the primary factors dominating the spatial distribution of SOC in different soil layers with the use of the autoregressive state‐space approach. The concentration of SOC was measured to the depth of 500 cm (n = 86) along a south–north transect of China's Loess Plateau. The mean SOC of the 500‐cm soil profile generally decreased from south to north following the decreasing rainfall gradient. Based on the investigated factors, the state‐space model was able to capture 90.3–99.9% of the spatial variability of SOC in the various soil layers. According to the coefficients in the optimal state‐space model for each soil layer, climatic factors such as precipitation and temperature had a dominant control over the spatial distribution of SOC at shallow depths. However, both climatic and edaphic (e.g. soil texture) factors, and to a small extent land use, influenced the spatial behavior of SOC at the 40–200 cm soil depth. For soil layers below 200 cm, the importance of land use was revealed, and the spatial characteristics of SOC were together driven by land use, climatic and edaphic factors. This is critical for the management of soil C flux in deep soils and the C stock and cycle in terrestrial ecosystems. Table SI. Basic properties of soils and climate and elevation under three land uses along the south–north transect on the Loess Plateau (mean ± standard deviation). Note that SWC is gravimetric soil water content. Copyright © 2016 John Wiley & Sons, Ltd.

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“…The typical Loess Plateau region is a spatial zone between the provinces of Shanxi, Shaanxi, Gansu, Ningxia, Henan and Inner Mongolia, where the loess is thickest (30-80 m) and most continuous with severe erosion and geomorphic landforms (Jia et al, 2015). It is located at an elevation of 200-300 m a.s.l.…”

Section: Description Of Study Areamentioning

confidence: 99%

Using pedotransfer functions to estimate soil hydraulic conductivity in the Loess Plateau of China

Zhao

Shao

Jia

et al. 2016

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Soil hydraulic conductivity (K s ) is a crucial soil physical property that not only influences soil hydrological processes, but also the planning for vegetation recovery, irrigation practice and drainage design. However, K s data are often lacking at large-scale soil database due to difficulties in direct measurement that is often labour intensive, time consuming and cost inefficient. The objective of this study was to compare the performance of different emerging methods [Multiple linear regression (MLR) and artificial neural network (ANN)] of K s prediction. The pedotransfer function (PTF) is one such method that is based on selected factors closely correlated with K s at regional scale. We collected disturbed and undisturbed soil samples in the 0-40 cm soil layer at 243 sites across the entire typical Loess Plateau of China (430,000 km 2 ) and then measured K s and the potentially related factors. The results showed that K s was normally distributed with moderate a spatial variation (CV = 67%). Correlation analysis indicated that bulk density (BD), saturated soil water content (SSWC), clay content (Clay), silt content (Silt) and latitude were closely correlated (p b 0.05) with K s . Although the accuracies of MLR and ANN were equal in terms of estimating K s , the stability of PTF developed via ANN was not as good as that of MLR. Thus PTF developed via MLR, which included BD, Silt and Clay, was considered as the best model for estimating K s . There is a need to closely monitor the stability and repeatability of PTF during comparison and determination of PTF.

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Regional temporal persistence of dried soil layer along south–north transect of the Loess Plateau, China

Cited by 76 publications

References 45 publications

Estimating regional losses of soil water due to the conversion of agricultural land to forest in China's Loess Plateau

Estimating regional losses of soil water due to the conversion of agricultural land to forest in China's Loess Plateau

A State‐Space Analysis of Soil Organic Carbon in China's Loess Plateau

Using pedotransfer functions to estimate soil hydraulic conductivity in the Loess Plateau of China

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