A multiscale deep learning model for soil moisture integrating satellite and in situ data

J Liu, F Rahmani, K Lawson… - Geophysical Research …, 2022 - Wiley Online Library
Deep learning (DL) models trained on hydrologic observations can perform extraordinarily
well, but they can inherit deficiencies of the training data, such as limited coverage of in situ …

Inter-comparison and integration of different soil moisture downscaling methods over the Qinghai-Tibet Plateau

Y Shangguan, X Min, Z Shi - Journal of Hydrology, 2023 - Elsevier
Soil moisture (SM) is a key state variable in the water, energy cycle between atmosphere
and land surface but existing passive microwave soil moisture products typically have …

Two-step fusion method for generating 1 km seamless multi-layer soil moisture with high accuracy in the Qinghai-Tibet plateau

S Huang, X Zhang, C Wang, N Chen - ISPRS Journal of Photogrammetry …, 2023 - Elsevier
Current remote sensing techniques fail to observe and generate large scale multi-layer soil
moisture (SM) due to the inherent features of the satellite sensors. The lack of …

[HTML][HTML] Improving global hydrological simulations through bias-correction and multi-model blending

A Chevuturi, M Tanguy, K Facer-Childs… - Journal of …, 2023 - Elsevier
There is an immediate need to develop accurate and reliable global hydrological forecasts
in light of the future vulnerability to hydrological hazards and water scarcity under a …

[HTML][HTML] Comprehensive quality assessment of satellite-and model-based soil moisture products against the COSMOS network in Germany

T Schmidt, M Schrön, Z Li, T Francke… - Remote Sensing of …, 2024 - Elsevier
Critical to the reliable application of gridded soil moisture products is a thorough assessment
of their quality at spatially compatible scales. While previous studies have attempted to …

A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture

M Jamei, M Ali, M Karbasi, E Sharma, M Jamei… - … Applications of Artificial …, 2023 - Elsevier
The objective of this study is to develop a novel multi-level pre-processing framework and
apply it for multi-step (one and seven days ahead) daily forecasting of Surface soil moisture …

Generating high-accuracy and cloud-free surface soil moisture at 1 km resolution by point-surface data fusion over the Southwestern US

S Huang, X Zhang, N Chen, H Ma, J Zeng, P Fu… - Agricultural and Forest …, 2022 - Elsevier
Surface soil moisture (SSM) is of great importance in understanding global climate change
and studies related to environmental and earth science. However, neither of current SSM …

[HTML][HTML] A hybrid triple collocation-deep learning approach for improving soil moisture estimation from satellite and model-based data

W Ming, X Ji, M Zhang, Y Li, C Liu, Y Wang, J Li - Remote Sensing, 2022 - mdpi.com
Satellite retrieval and land surface models have become the mainstream methods for
monitoring soil moisture (SM) over large regions; however, the uncertainty and coarse …

A global-scale intercomparison of Triple Collocation Analysis-and ground-based soil moisture time-variant errors derived from different rescaling techniques

K Wu, D Ryu, W Wagner, Z Hu - Remote Sensing of Environment, 2023 - Elsevier
Accurate specification of spatiotemporal errors of remotely sensed soil moisture (SM) data is
essential for a correct assessment of their utility and optimally integrating multiple SM …

[HTML][HTML] Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite …

E Pinnington, J Amezcua, E Cooper… - Hydrology and Earth …, 2021 - hess.copernicus.org
Pedotransfer functions are used to relate gridded databases of soil texture information to the
soil hydraulic and thermal parameters of land surface models. The parameters within these …