Multi-layer high-resolution soil moisture estimation using machine learning over the United States

L Karthikeyan, AK Mishra - Remote Sensing of Environment, 2021 - Elsevier
The lack of proper understanding of multi-layer soil moisture (SM) profile (signals) remains a
persistent challenge in sustainable agricultural water management and food security …

[HTML][HTML] A 1 km daily soil moisture dataset over China using in situ measurement and machine learning

Q Li, G Shi, W Shangguan, V Nourani… - Earth System …, 2022 - essd.copernicus.org
High-quality gridded soil moisture products are essential for many Earth system science
applications, while the recent reanalysis and remote sensing soil moisture data are often …

The influence of soil moisture on convective activity: a review

W Liu, Q Zhang, C Li, L Xu, W **ao - Theoretical and Applied Climatology, 2022 - Springer
Soil moisture (SM) influences the initiation and development of convective systems and
consequently the generation and development of precipitation through land–air interaction …

Improving Jakarta's katulampa barrage extreme water level prediction using satellite-based long short-term memory (LSTM) neural networks

H Kardhana, JR Valerian, FIW Rohmat, MSB Kusuma - Water, 2022 - mdpi.com
Jakarta, the capital region of Indonesia, is experiencing recurring floods, with the most
extensive recording loss as high as 350 million dollars. Katulampa Barrage's observation of …

Soil moisture influences on Sierra Nevada dead fuel moisture content and fire risks

E Rakhmatulina, S Stephens, S Thompson - Forest Ecology and …, 2021 - Elsevier
Dead fuel moisture influences the risk of fire ignition events, with implications for fire
hazards, risk mitigation, and the design of prescribed burning activities. Because direct fuel …

Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability

R Zhang, S Kim, A Sharma, V Lakshmi - Remote Sensing of Environment, 2021 - Elsevier
This study evaluates the relative strengths of three remotely sensed soil moisture (SM)
products to capture temporal variability at a global scale, the products being the Soil …

[HTML][HTML] On the relation between antecedent basin conditions and runoff coefficient for European floods

C Massari, V Pellet, Y Tramblay, WT Crow… - Journal of …, 2023 - Elsevier
The event runoff coefficient (ie the ratio between event runoff and precipitation that
originated the runoff) is a key factor for understanding basin response to precipitation …

Generation of global 1-km daily soil moisture product from 2000 to 2020 using ensemble learning

Y Zhang, S Liang, H Ma, T He, Q Wang… - Earth System …, 2023 - essd.copernicus.org
Motivated by the lack of long-term global soil moisture products with both high spatial and
temporal resolutions, a global 1-km daily spatiotemporally continuous soil moisture product …

Characterizing satellite soil moisture drydown: A bivariate filtering approach

J Sinha, A Sharma, L Marshall… - Water Resources …, 2024 - Wiley Online Library
Drying of soil impacts land energy and water balance, influences the sustainability of
vegetation growth, and modulates hydrological extremes including floods. While satellite soil …

A deep learning data fusion model using sentinel-1/2, SoilGrids, SMAP, and GLDAS for soil moisture retrieval

V Batchu, G Nearing, V Gulshan - Journal of …, 2023 - journals.ametsoc.org
We develop a deep learning–based convolutional-regression model that estimates the
volumetric soil moisture content in the top∼ 5 cm of soil. Input predictors include Sentinel-1 …