scholarly journals Impacts of Re-Vegetation on Surface Soil Moisture over the Chinese Loess Plateau Based on Remote Sensing Datasets

2016 ◽  
Vol 8 (2) ◽  
pp. 156 ◽  
Author(s):  
Qiao Jiao ◽  
Rui Li ◽  
Fei Wang ◽  
Xingmin Mu ◽  
Pengfei Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Loess Plateau ◽  
Surface Soil ◽  
Chinese Loess Plateau ◽  
Surface Soil Moisture ◽  
Chinese Loess ◽  
The Chinese Loess Plateau

scholarly journals Effects of micro-topography and vegetation type on soil moisture in a large gully on the Loess Plateau of China

2017 ◽  
Vol 49 (4) ◽  
pp. 1255-1270 ◽  
Author(s):  
Bowei Yu ◽  
Gaohuan Liu ◽  
Qingsheng Liu ◽  
Jiuliang Feng ◽  
Xiaoping Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Variability ◽  
Loess Plateau ◽  
Root Zone ◽  
Plane Surface ◽  
Vegetation Type ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
Micro Topography ◽  
The Chinese Loess Plateau

Abstract Large gullies occur globally and can be classified into four main micro-topographic types: ridges, plane surfaces, pipes and cliffs. Afforestation is an effective method of controlling land degradation worldwide. However, the combined effects of afforestation and micro-topography on the variability of soil moisture remain poorly understood. The primary objectives of this study were to determine whether afforestation affects the spatial pattern of the root-zone (0–100 cm) soil moisture and whether soil moisture dynamics differ among the micro-topographic types in gully areas of the Chinese Loess Plateau. The results showed that in the woodland regions, the spatial mean moisture values decreased by an average of 6.2% and the spatial variability increased, as indicated by the standard deviation (17.1%) and the coefficient of variation (22.2%). In general, different micro-topographic types exerted different influences on soil moisture behavior. The plane surface presented the largest average soil moisture values and the smallest spatial variability. The lowest soil moisture values were observed in the ridge, mainly due to the rapid drainage of these areas. Although pipe woodland region can concentrate surface runoff during and after rainfall, the larger trees growing in these areas can lead to increased soil moisture evapotranspiration.

Soil moisture response to rainfall on the Chinese Loess Plateau after a long-term vegetation rehabilitation

2018 ◽  
Vol 32 (12) ◽  
pp. 1738-1754 ◽  
Author(s):  
Zhao Jin ◽  
Li Guo ◽  
Henry Lin ◽  
Yunqiang Wang ◽  
Yunlong Yu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
The Chinese Loess Plateau

Changes in soil moisture and organic carbon under deep-rooted trees of different stand ages on the Chinese Loess Plateau

2022 ◽  
Vol 328 ◽  
pp. 107855
Author(s):  
Fan Yang ◽  
Mingbin Huang ◽  
Chenhui Li ◽  
Xiaofei Wu ◽  
Tianqi Guo ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Organic Carbon ◽  
Loess Plateau ◽  
Rooted Trees ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
The Chinese Loess Plateau

scholarly journals Soil Moisture Estimation for the Chinese Loess Plateau Using MODIS-derived ATI and TVDI

2020 ◽  
Vol 12 (18) ◽  
pp. 3040
Author(s):  
Lina Yuan ◽  
Long Li ◽  
Ting Zhang ◽  
Longqian Chen ◽  
Jianlin Zhao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Vegetation Index ◽  
Joint Model ◽  
Iteration Procedure ◽  
Chinese Loess Plateau ◽  
Vegetation Coverage ◽  
Chinese Loess ◽  
The Chinese Loess Plateau

Timely and effective estimation and monitoring of soil moisture (SM) provides not only an understanding of regional SM status for agricultural management or potential drought but also a basis for characterizing water and energy exchange. The apparent thermal inertia (ATI) and Temperature Vegetation Dryness Index (TVDI) are two widely used indices to reflect SM from remote sensing data. While the ATI-based model is routinely used to estimate the SM of bare soil and sparsely vegetated areas, the TVDI-based model is more suitable for areas with dense vegetation coverage. In this study, we present an iteration procedure that allows us to identify optimal Normalized Difference Vegetation Index (NDVI) thresholds for subregions and estimate their relative soil moisture (RSM) using three models (the ATI-based model, the TVDI-based model, and the ATI/TVDI joint model) from 1 January to 31 December 2017, in the Chinese Loess Plateau. The initial NDVI (NDVI0) was first introduced to obtain TVDI value and two other thresholds of NDVIATI and NDVITVDI were designed for dividing the whole area into three subregions (the ATI subregion, the TVDI subregion, and the ATI/TVDI subregion). The NDVI values corresponding to maximum R-values (correlation coefficient) between estimated RSM and in situ RSM measurements were chosen as optimal NDVI thresholds after performing as high as 48,620 iterations with 10 rounds of 10-fold cross-calibration and validation for each period. An RSM map of the whole study area was produced by merging the RSM of each of the three subregions. The spatiotemporal and comparative analysis further indicated that the ATI/TVDI joint model has higher applicability (accounting for 36/38 periods) and accuracy than the ATI-based and TVDI-based models. The highest average R-value between the estimated RSM and in situ RSM measurements was 0.73 ± 0.011 (RMSE—root mean square error, 3.43 ± 0.071% and MAE—mean absolute error, 0.05 ± 0.025) on the 137th day of 2017 (DOY—day of the year, 137). Although there is potential for improved mapping of RSM for the entire Chinese Loess Plateau, the iteration procedure of identifying optimal thresholds determination offers a promising method for achieving finer-resolution and robust RSM estimation in large heterogeneous areas.

scholarly journals Modeling Soil Moisture from Multisource Data by Stepwise Multilinear Regression: An Application to the Chinese Loess Plateau

2021 ◽  
Vol 10 (4) ◽  
pp. 233
Author(s):  
Lina Yuan ◽  
Long Li ◽  
Ting Zhang ◽  
Longqian Chen ◽  
Weiqiang Liu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Chinese Loess Plateau ◽  
P Value ◽  
Significant Finding ◽  
Multilinear Regression ◽  
Dummy Variables ◽  
Chinese Loess ◽  
Spatial Coverage ◽  
The Chinese Loess Plateau

This study aims to integrate multisource data to model the relative soil moisture (RSM) over the Chinese Loess Plateau in 2017 by stepwise multilinear regression (SMLR) in order to improve the spatial coverage of our previously published RSM. First, 34 candidate variables (12 quantitative and 22 dummy variables) from the Moderate Resolution Imaging Spectroradiometer (MODIS) and topographic, soil properties, and meteorological data were preprocessed. Then, SMLR was applied to variables without multicollinearity to select statistically significant (p-value < 0.05) variables. After the accuracy assessment, monthly, seasonal, and annual spatial patterns of RSM were mapped at 500 m resolution and evaluated. The results indicate that there was a high potential of SMLR to model RSM with the desired accuracy (best fit of the model with Pearson’s r = 0.969, root mean square error = 0.761%, and mean absolute error = 0.576%) over the Chinese Loess Plateau. The variables of elevation (0–500 m and 2000–2500 m), precipitation, soil texture of loam, and nighttime land surface temperature can continuously be used in the regression models for all seasons. Including dummy variables improved the model fit both in calibration and validation. Moreover, the SMLR-modeled RSM achieved better spatial coverage than that of the reference RSM for almost all periods. This is a significant finding as the SMLR method supports the use of multisource data to complement and/or replace coarse resolution satellite imagery in the estimation of RSM.

scholarly journals Dependence of the cyclization of branched tetraethers (CBT) on soil moisture in the Chinese Loess Plateau and the adjacent areas: implications for palaeorainfall reconstructions

2014 ◽  
Vol 11 (6) ◽  
pp. 10015-10043 ◽  
Author(s):  
H. Wang ◽  
W. Liu ◽  
C. L. Zhang
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Total Sample ◽  
Chinese Loess Plateau ◽  
Mean Annual Precipitation ◽  
Chinese Loess ◽  
Thermal Changes ◽  
Sample Set ◽  
Semi Arid ◽  
The Chinese Loess Plateau

Abstract. Branched glycerol dialkyl glycerol tetraethers (bGDGTs) have been show promising for continental paleotemperature studies in loess-paleosol sequences (LPSs). Thus far, however, little is known about the effect of soil moisture on their distributions on the Chinese Loess Plateau (CLP). In this study, the relationships between environmental variables and the cyclization of bGDGTs (the so called CBT index) were investigated in a comprehensive set of surface soils in the CLP and its adjacent arid/semi-arid areas. We find that CBT correlates best with soil water content (SWC) or mean annual precipitation (MAP) for the total sample set. Particularly for the CLP soils, there is a significant positive relationship between CBT and MAP (CBT = −0.0021 · MAP + 1.7, n = 37, R2 = 0.87; MAP range: 210–680 mm). This indicates that CBT is mainly controlled by soil moisture in the alkalescent soils (pH > 7) in arid/semi-arid regions, where it is not sensitive to soil pH. Therefore, we suggest that CBT can potentially be used as a palaeorainfall proxy on the CLP. According to the preliminary CBT–MAP relationship for modern CLP soils, palaeorainfall history was reconstructed from three LPSs (Yuanbao, Lantian, and Mangshan) with published bGDGT data spanning the past 70 ka. The CBT-derived MAP records of the three sites consistently show precession-driven variations resembling the speleothem δ18O monsoon record, and are also in general accord with the fluctuations of the respective magnetic susceptibility (MS) record, supporting CBT as a reasonable proxy for palaeorainfall reconstruction in LPS studies. Moreover, the comparison of CBT-derived MAP and bGDGT-derived temperature may enable us to further assess the relative timing and magnitude of hydrological and thermal changes on the CLP, independent of chronology.

Soil moisture mapping over the Chinese Loess Plateau using ENVISAT/ASAR data

2009 ◽  
Vol 43 (7) ◽  
pp. 1111-1117 ◽  
Author(s):  
Tangtang Zhang ◽  
Jun Wen ◽  
Zhongbo Su ◽  
Rogier van der Velde ◽  
Joris Timmermans ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
Envisat Asar ◽  
The Chinese Loess Plateau

Effects of rainwater harvesting system on soil moisture in rain-fed orchards on the Chinese Loess Plateau

2021 ◽  
Vol 243 ◽  
pp. 106496
Author(s):  
Wenbin Ding ◽  
Fei Wang ◽  
Yunyun Dong ◽  
Kai Jin ◽  
Chenyu Cong ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Rainwater Harvesting ◽  
Chinese Loess Plateau ◽  
Chinese Loess ◽  
The Chinese Loess Plateau
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