scholarly journals An Improved Approach for Soil Moisture Estimation in Gully Fields of the Loess Plateau Using Sentinel-1A Radar Images

2019 ◽  
Vol 11 (3) ◽  
pp. 349 ◽  
Author(s):  
Shanchuan Guo ◽  
Xuyu Bai ◽  
Yu Chen ◽  
Shaoliang Zhang ◽  
Huping Hou ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Land Surface ◽  
Incidence Angle ◽  
Equation Model ◽  
The Loess Plateau ◽  
Radar Images ◽  
Angle Correction ◽  
Ecological Parameter ◽  
Moisture Estimation

As an essential ecological parameter, soil moisture is important for understanding the water exchange between the land surface and the atmosphere, especially in the Loess Plateau (China). Although Synthetic Aperture Radar (SAR) images can be used for soil moisture retrieval, it is still a challenge to mitigate the impacts of complex terrain over hilly areas. Therefore, the objective of this paper is to propose an improved approach for soil moisture estimation in gully fields based on the joint use of the Advanced Integral Equation Model (AIEM) and the Incidence Angle Correction Model (IACM) from Sentinel-1A observations. AIEM is utilized to build a simulation database of microwave backscattering coefficients from various radar parameters and surface parameters, which is the data basis for the retrieval modeling. IACM is proposed to correct the deviation between the local incidence angle at the scatterer and the radar viewing angle. The study area is located in the Loess Plateau of China, where the main land cover is mostly bare land and the terrain is complex. The Sentinel-1A SAR data in C-band with dual polarization acquired on October 19th, 2017 was adopted to extract the VV&VH polarimetric backscattering coefficients. The in situ measurements of soil moisture were collected on the same day of the SAR acquisition, for evaluating the accuracy of the SAR-derived soil moisture. The results showed that, firstly, the estimated soil moisture with volumetric content between 0% and 20% was in the majority. Subsequently, both the RMSE of estimation values (0.963%) and the standard deviation of absolute errors (0.957%) demonstrated a good accuracy of the improved approach. Moreover, the evaluation of IACM confirmed that the improved approach coupling IACM and AIEM was more efficient than employing AIEM solely. In conclusion, the proposed approach has a strong ability to estimate the soil moisture in the gully fields of the Loess Plateau from Sentinel-1A data.

Soil moisture variations in response to precipitation properties and plant communities on steep gully slope on the Loess Plateau

2021 ◽  
Vol 256 ◽  
pp. 107086
Author(s):  
Pingzong Zhu ◽  
Guanghui Zhang ◽  
Hongxiao Wang ◽  
Baojun Zhang ◽  
Yingna Liu
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Plant Communities ◽  
The Loess Plateau

scholarly journals Assimilation of SMOS brightness temperatures or soil moisture retrievals into a land surface model

2016 ◽  
Vol 20 (12) ◽  
pp. 4895-4911 ◽  
Author(s):  
Gabriëlle J. M. De Lannoy ◽  
Rolf H. Reichle
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Soil ◽  
Root Zone ◽  
Incidence Angle ◽  
Land Surface Model ◽  
Surface Model ◽  
Model Errors ◽  
Surface Soil Moisture ◽  
Brightness Temperatures

Abstract. Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40° incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval assimilation.

Stochastic soil moisture dynamic modelling: a case study in the Loess Plateau, China

2018 ◽  
Vol 109 (3-4) ◽  
pp. 437-444
Author(s):  
Cong WANG ◽  
Shuai WANG ◽  
Bojie FU ◽  
Lu ZHANG ◽  
Nan LU ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Loess Plateau ◽  
Hydrological Cycle ◽  
Dynamic Modelling ◽  
Vegetation Restoration ◽  
Balance Model ◽  
Rainfall Regime ◽  
The Loess Plateau ◽  
Dry Period

ABSTRACTSoil moisture is a key factor in the ecohydrological cycle in water-limited ecosystems, and it integrates the effects of climate, soil, and vegetation. The water balance and the hydrological cycle are significantly important for vegetation restoration in water-limited regions, and these dynamics are still poorly understood. In this study, the soil moisture and water balance were modelled with the stochastic soil water balance model in the Loess Plateau, China. This model was verified by monitoring soil moisture data of black locust plantations in the Yangjuangou catchment in the Loess Plateau. The influences of a rainfall regime change on soil moisture and water balance were also explored. Three meteorological stations were selected (Yulin, Yan'an, and Luochuan) along the precipitation gradient to detect the effects of rainfall spatial variability on the soil moisture and water balance. The results showed that soil moisture tended to be more frequent at low levels with decreasing precipitation, and the ratio of evapotranspiration under stress in response to rainfall also changed from 74.0% in Yulin to 52.3% in Luochuan. In addition, the effects of a temporal change in rainfall regime on soil moisture and water balance were explored at Yan'an. The soil moisture probability density function moved to high soil moisture in the wet period compared to the dry period of Yan'an, and the evapotranspiration under stress increased from 59.5% to 72% from the wet period to the dry period. The results of this study prove the applicability of the stochastic model in the Loess Plateau and reveal its potential for guiding the vegetation restoration in the next stage.

scholarly journals Soil Moisture-Boundary Layer Feedbacks on the Loess Plateau in China Using Radiosonde Data with 1-D Atmospheric Boundary Layer Model

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1619
Author(s):  
Yingsai Ma ◽  
Xianhong Meng ◽  
Yinhuan Ao ◽  
Ye Yu ◽  
Guangwei Li ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Soil Moisture ◽  
Atmospheric Boundary Layer ◽  
Loess Plateau ◽  
Atmospheric Stability ◽  
Heat Fluxes ◽  
Radiosonde Data ◽  
Atmospheric Conditions ◽  
The Loess Plateau ◽  
The Impact

The Loess Plateau is one land-atmosphere coupling hotspot. Soil moisture has an influence on atmospheric boundary layer development under specific early-morning atmospheric thermodynamic structures. This paper investigates the sensitivity of atmospheric convection to soil moisture conditions over the Loess Plateau in China by using the convective triggering potential (CTP)—humidity index (HIlow) framework. The CTP indicates atmospheric stability and the HIlow indicates atmospheric humidity in the low-level atmosphere. By comparing the model outcomes with the observations, the one-dimensional model achieves realistic daily behavior of the radiation and surface heat fluxes and the mixed layer properties with appropriate modifications. New CTP-HIlow thresholds for soil moisture-atmosphere feedbacks are found in the Loess Plateau area. By applying the new thresholds with long-time scales sounding data, we conclude that negative feedback is dominant in the north and west portion of the Loess Plateau; positive feedback is predominant in the south and east portion. In general, this framework has predictive significance for the impact of soil moisture on precipitation. By using this new CTP-HIlow framework, we can determine under what atmospheric conditions soil moisture can affect the triggering of precipitation and under what atmospheric conditions soil moisture has no influence on the triggering of precipitation.

scholarly journals Earthworm Burrowing Activity and Its Effects on Soil Hydraulic Properties under Different Soil Moisture Conditions from the Loess Plateau, China

2020 ◽  
Vol 12 (21) ◽  
pp. 9303
Author(s):  
Shuhai Wen ◽  
Ming’an Shao ◽  
Jiao Wang
Keyword(s):  
Soil Moisture ◽  
Loess Plateau ◽  
Hydraulic Properties ◽  
Soil Depth ◽  
Soil Aggregates ◽  
Field Capacity ◽  
Soil Hydraulic Properties ◽  
The Loess Plateau ◽  
Burrowing Activity ◽  
Soil Hydraulic

Earthworm activity has become more important in the Loess Plateau, where hydrological processes are crucial for ecosystem sustainability. In this study, we conducted a laboratory microcosm experiment to determine the various burrowing activities of Eisenia fetida and their impact on the soil hydraulic properties in response to different levels of soil moisture (50%, 70%, 90% of field capacity) in two common soil types (loessial and Lou soil) obtained from the Loess Plateau. Burrowing activity of E. fetida increased with higher soil moisture and was greater in loessial than in Lou soil. Most burrowing activities occurred within the top 5 cm and decreased with increasing soil depth. Macropores and burrow branching, which are highly related to the earthworm burrowing, were more prevalent in wetter soil. Earthworms significantly altered the formation of large soil aggregates (AGL, diameter >2 mm) under different soil moistures and depths. Distinct earthworm burrowing activities, controlled by soil moisture, altered soil hydraulic properties. However, soil saturated hydraulic conductivity (Ks) showed little differences between different treatments due to the horizontal and high–branched burrows of E. fetida, although higher burrowing activities were found in wetter soil. Soil field capacity was highest in drier soil due to the less macropores and burrowing activities.

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