Interpreting effective hydrologic depth estimates derived from soil moisture remote sensing: A Bayesian non-linear modeling approach-Reference-Cited by-同舟云学术

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Interpreting effective hydrologic depth estimates derived from soil moisture remote sensing: A Bayesian non-linear modeling approach

Published:2024-01 Issue: Volume:908 Page:168067
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Kim Hyunglok,Crow Wade T.

Funder

Agricultural Research Service

U.S. Department of Agriculture

Oak Ridge Associated Universities

U.S. Department of Energy

Oak Ridge Institute for Science and Education

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference21 articles.

1. Hydrological storage length scales represented by remote sensing estimates of soil moisture and precipitation;Akbar;Water Resour. Res.,2018

2. Partitioning of historical precipitation into evaporation and runoff based on hydrologic dynamics identified with recent SMAP satellite measurements;Akbar;Water Resour. Res.,2020

3. Variational inference: a review for statisticians;Blei;J. Am. Stat. Assoc.,2017

4. Soil as a natural rain gauge: estimating global rainfall from satellite soil moisture data: using the soil as a natural raingauge;Brocca;J. Geophys. Res. Atmos.,2014

5. SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations;Brocca;Earth Syst. Sci. Data,2019

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Temporal Gap‐Filling of 12‐Hourly SMAP Soil Moisture Over the CONUS Using Water Balance Budgeting;Water Resources Research;2023-12

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