Articles | Volume 25, issue 5
https://doi.org/10.5194/hess-25-2739-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-2739-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Advances in soil moisture retrieval from multispectral remote sensing using unoccupied aircraft systems and machine learning techniques
Earth System Science, Stanford University, Stanford, CA, USA
Anna Fryjoff-Hung
Center for Information Technology in the Interest of Society and the Banatao Institute, University of California, Merced, Merced, CA, USA
Andreas Anderson
Center for Information Technology in the Interest of Society and the Banatao Institute, University of California, Merced, Merced, CA, USA
Joshua H. Viers
Center for Information Technology in the Interest of Society and the Banatao Institute, University of California, Merced, Merced, CA, USA
Department of Civil and Environmental Engineering, University of California, Merced, Merced, CA, USA
Teamrat A. Ghezzehei
Center for Information Technology in the Interest of Society and the Banatao Institute, University of California, Merced, Merced, CA, USA
Life and Environmental Science, University of California, Merced, Merced, CA, USA
Related authors
Samuel N. Araya, Jeffrey P. Mitchell, Jan W. Hopmans, and Teamrat A. Ghezzehei
SOIL, 8, 177–198, https://doi.org/10.5194/soil-8-177-2022, https://doi.org/10.5194/soil-8-177-2022, 2022
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We studied the long-term effects of no-till (NT) and winter cover cropping (CC) practices on soil hydraulic properties. We measured soil water retention and conductivity and also conducted numerical simulations to compare soil water storage abilities under the different systems. Soils under NT and CC practices had improved soil structure. Conservation agriculture practices showed marginal improvement with respect to infiltration rates and water storage.
Samuel N. Araya, Marilyn L. Fogel, and Asmeret Asefaw Berhe
SOIL, 3, 31–44, https://doi.org/10.5194/soil-3-31-2017, https://doi.org/10.5194/soil-3-31-2017, 2017
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This research investigates how fires of different intensities affect soil organic matter properties. This study identifies critical temperature thresholds of significant soil organic matter changes. Findings from this study will contribute towards estimating the amount and rate of changes in soil carbon, nitrogen, and other essential soil properties that can be expected from fires of different intensities under anticipated climate change scenarios.
Samuel N. Araya, Mercer Meding, and Asmeret Asefaw Berhe
SOIL, 2, 351–366, https://doi.org/10.5194/soil-2-351-2016, https://doi.org/10.5194/soil-2-351-2016, 2016
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Using laboratory heating, we studied effects of fire intensity on important topsoil characteristics. This study identifies critical temperature thresholds for significant physical and chemical changes in soils that developed under different climate regimes. Findings from this study will contribute towards estimating the amount and rate of change in essential soil properties that can be expected from topsoil exposure to different intensity fires under anticipated climate change scenarios.
Toshiyuki Bandai and Teamrat A. Ghezzehei
Hydrol. Earth Syst. Sci., 26, 4469–4495, https://doi.org/10.5194/hess-26-4469-2022, https://doi.org/10.5194/hess-26-4469-2022, 2022
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Scientists use a physics-based equation to simulate water dynamics that influence hydrological and ecological phenomena. We present hybrid physics-informed neural networks (PINNs) to leverage the growing availability of soil moisture data and advances in machine learning. We showed that PINNs perform comparably to traditional methods and enable the estimation of rainfall rates from soil moisture. However, PINNs are challenging to train and significantly slower than traditional methods.
Samuel N. Araya, Jeffrey P. Mitchell, Jan W. Hopmans, and Teamrat A. Ghezzehei
SOIL, 8, 177–198, https://doi.org/10.5194/soil-8-177-2022, https://doi.org/10.5194/soil-8-177-2022, 2022
Short summary
Short summary
We studied the long-term effects of no-till (NT) and winter cover cropping (CC) practices on soil hydraulic properties. We measured soil water retention and conductivity and also conducted numerical simulations to compare soil water storage abilities under the different systems. Soils under NT and CC practices had improved soil structure. Conservation agriculture practices showed marginal improvement with respect to infiltration rates and water storage.
Jing Yan and Teamrat Ghezzehei
Biogeosciences Discuss., https://doi.org/10.5194/bg-2022-52, https://doi.org/10.5194/bg-2022-52, 2022
Publication in BG not foreseen
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Although hydraulic redistribution (HR) is a well-documented phenomenon, whether it is a passive happy accident or actively controlled by roots is not well understood. Our modeling study suggests HR is long-range feedback between roots that inhabit heterogeneously resourced soil regions. When nutrients and organic matter are concentrated in shallow layers that experience frequent drying, root-exudation facilitated HR allows plants to mineralize and extract the otherwise inaccessible nutrients.
Daniel Rath, Nathaniel Bogie, Leonardo Deiss, Sanjai J. Parikh, Daoyuan Wang, Samantha Ying, Nicole Tautges, Asmeret Asefaw Berhe, Teamrat A. Ghezzehei, and Kate M. Scow
SOIL, 8, 59–83, https://doi.org/10.5194/soil-8-59-2022, https://doi.org/10.5194/soil-8-59-2022, 2022
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Storing C in subsoils can help mitigate climate change, but this requires a better understanding of subsoil C dynamics. We investigated changes in subsoil C storage under a combination of compost, cover crops (WCC), and mineral fertilizer and found that systems with compost + WCC had ~19 Mg/ha more C after 25 years. This increase was attributed to increased transport of soluble C and nutrients via WCC root pores and demonstrates the potential for subsoil C storage in tilled agricultural systems.
Jing Yan, Nathaniel A. Bogie, and Teamrat A. Ghezzehei
Biogeosciences, 17, 6377–6392, https://doi.org/10.5194/bg-17-6377-2020, https://doi.org/10.5194/bg-17-6377-2020, 2020
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An uneven supply of water and nutrients in soils often drives how plants behave. We observed that plants extract all their required nutrients from dry soil patches in sufficient quantity, provided adequate water is available elsewhere in the root zone. Roots in nutrient-rich dry patches facilitate the nutrient acquisition by extensive growth, water release, and modifying water retention in their immediate environment. The findings are valuable in managing nutrient losses in agricultural systems.
Teamrat A. Ghezzehei, Benjamin Sulman, Chelsea L. Arnold, Nathaniel A. Bogie, and Asmeret Asefaw Berhe
Biogeosciences, 16, 1187–1209, https://doi.org/10.5194/bg-16-1187-2019, https://doi.org/10.5194/bg-16-1187-2019, 2019
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Soil water is a medium from which microbes acquire resources and within which they are able to move. Occupancy and availability of water and oxygen gas in soils are mutually exclusive. In addition, as soil dries the remaining water is held with an increasing degree of adhesive energy, which restricts microbes' ability to extract resources from water. We introduce a mathematical model that describes these interacting effects and organic matter decomposition.
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
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This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
Roland Baatz, Pamela L. Sullivan, Li Li, Samantha R. Weintraub, Henry W. Loescher, Michael Mirtl, Peter M. Groffman, Diana H. Wall, Michael Young, Tim White, Hang Wen, Steffen Zacharias, Ingolf Kühn, Jianwu Tang, Jérôme Gaillardet, Isabelle Braud, Alejandro N. Flores, Praveen Kumar, Henry Lin, Teamrat Ghezzehei, Julia Jones, Henry L. Gholz, Harry Vereecken, and Kris Van Looy
Earth Syst. Dynam., 9, 593–609, https://doi.org/10.5194/esd-9-593-2018, https://doi.org/10.5194/esd-9-593-2018, 2018
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Focusing on the usage of integrated models and in situ Earth observatory networks, three challenges are identified to advance understanding of ESD, in particular to strengthen links between biotic and abiotic, and above- and below-ground processes. We propose developing a model platform for interdisciplinary usage, to formalize current network infrastructure based on complementarities and operational synergies, and to extend the reanalysis concept to the ecosystem and critical zone.
Samuel N. Araya, Marilyn L. Fogel, and Asmeret Asefaw Berhe
SOIL, 3, 31–44, https://doi.org/10.5194/soil-3-31-2017, https://doi.org/10.5194/soil-3-31-2017, 2017
Short summary
Short summary
This research investigates how fires of different intensities affect soil organic matter properties. This study identifies critical temperature thresholds of significant soil organic matter changes. Findings from this study will contribute towards estimating the amount and rate of changes in soil carbon, nitrogen, and other essential soil properties that can be expected from fires of different intensities under anticipated climate change scenarios.
Samuel N. Araya, Mercer Meding, and Asmeret Asefaw Berhe
SOIL, 2, 351–366, https://doi.org/10.5194/soil-2-351-2016, https://doi.org/10.5194/soil-2-351-2016, 2016
Short summary
Short summary
Using laboratory heating, we studied effects of fire intensity on important topsoil characteristics. This study identifies critical temperature thresholds for significant physical and chemical changes in soils that developed under different climate regimes. Findings from this study will contribute towards estimating the amount and rate of change in essential soil properties that can be expected from topsoil exposure to different intensity fires under anticipated climate change scenarios.
T. A. Ghezzehei, D. V. Sarkhot, and A. A. Berhe
Solid Earth, 5, 953–962, https://doi.org/10.5194/se-5-953-2014, https://doi.org/10.5194/se-5-953-2014, 2014
Related subject area
Subject: Vadose Zone Hydrology | Techniques and Approaches: Remote Sensing and GIS
A robust gap-filling approach for European Space Agency Climate Change Initiative (ESA CCI) soil moisture integrating satellite observations, model-driven knowledge, and spatiotemporal machine learning
Exploring the combined use of SMAP and Sentinel-1 data for downscaling soil moisture beyond the 1 km scale
An inverse dielectric mixing model at 50 MHz that considers soil organic carbon
Parameter optimisation for a better representation of drought by LSMs: inverse modelling vs. sequential data assimilation
Multi-decadal analysis of root-zone soil moisture applying the exponential filter across CONUS
Geomorphometric analysis of cave ceiling channels mapped with 3-D terrestrial laser scanning
Analysis of SMOS brightness temperature and vegetation optical depth data with coupled land surface and radiative transfer models in Southern Germany
Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals
Influence of cracking clays on satellite estimated and model simulated soil moisture
Kai Liu, Xueke Li, Shudong Wang, and Hongyan Zhang
Hydrol. Earth Syst. Sci., 27, 577–598, https://doi.org/10.5194/hess-27-577-2023, https://doi.org/10.5194/hess-27-577-2023, 2023
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Remote sensing has opened opportunities for mapping spatiotemporally continuous soil moisture, but it is hampered by data gaps. We propose a robust gap-filling approach to reconstruct daily satellite soil moisture. The merit of our approach is to integrate satellite observations, model-driven knowledge, and spatiotemporal machine learning. We also apply the developed approach to long-term datasets. Our study provides a potential avenue for hydrological applications.
Rena Meyer, Wenmin Zhang, Søren Julsgaard Kragh, Mie Andreasen, Karsten Høgh Jensen, Rasmus Fensholt, Simon Stisen, and Majken C. Looms
Hydrol. Earth Syst. Sci., 26, 3337–3357, https://doi.org/10.5194/hess-26-3337-2022, https://doi.org/10.5194/hess-26-3337-2022, 2022
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The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.
Chang-Hwan Park, Aaron Berg, Michael H. Cosh, Andreas Colliander, Andreas Behrendt, Hida Manns, Jinkyu Hong, Johan Lee, Runze Zhang, and Volker Wulfmeyer
Hydrol. Earth Syst. Sci., 25, 6407–6420, https://doi.org/10.5194/hess-25-6407-2021, https://doi.org/10.5194/hess-25-6407-2021, 2021
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In this study, we proposed an inversion of the dielectric mixing model for a 50 Hz soil sensor for agricultural organic soil. This model can reflect the variability of soil organic matter (SOM) in wilting point and porosity, which play a critical role in improving the accuracy of SM estimation, using a dielectric-based soil sensor. The results of statistical analyses demonstrated a higher performance of the new model than the factory setting probe algorithm.
Hélène Dewaele, Simon Munier, Clément Albergel, Carole Planque, Nabil Laanaia, Dominique Carrer, and Jean-Christophe Calvet
Hydrol. Earth Syst. Sci., 21, 4861–4878, https://doi.org/10.5194/hess-21-4861-2017, https://doi.org/10.5194/hess-21-4861-2017, 2017
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Soil maximum available water content (MaxAWC) is a key parameter in land surface models. Being difficult to measure, this parameter is usually unavailable. A 15-year time series of satellite-derived observations of leaf area index (LAI) is used to retrieve MaxAWC for rainfed straw cereals over France. Disaggregated LAI is sequentially assimilated into the ISBA LSM. MaxAWC is estimated minimising LAI analyses increments. Annual maximum LAI observations correlate with the MaxAWC estimates.
Kenneth J. Tobin, Roberto Torres, Wade T. Crow, and Marvin E. Bennett
Hydrol. Earth Syst. Sci., 21, 4403–4417, https://doi.org/10.5194/hess-21-4403-2017, https://doi.org/10.5194/hess-21-4403-2017, 2017
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This study applied the exponential filter to produce an estimate of root-zone soil moisture at 20 to 25 cm depths. Four types of microwave, surface satellite soil moisture were used. The study focused on the continental United States, and in situ data were used from the International Soil Moisture Network for comparison. This study spans almost two decades (1997 to 2014). Root mean square error was close to 0.04, which is the baseline value for accuracy designated for many satellite missions.
Michal Gallay, Zdenko Hochmuth, Ján Kaňuk, and Jaroslav Hofierka
Hydrol. Earth Syst. Sci., 20, 1827–1849, https://doi.org/10.5194/hess-20-1827-2016, https://doi.org/10.5194/hess-20-1827-2016, 2016
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This paper presents a novel approach that provides evidence of
environmental conditions during the formation of a cave inferred from
measuring the geometry of the cave surface. We focused on winding
channels with associated cave landforms carved high up in the cave
ceiling inaccessible to direct inspection by speleologists. This was
possible by coupling 3-D laser scanning of the cave and analyzing the
cave morphology by the tools used in 3-D computer graphics and digital
terrain analysis.
F. Schlenz, J. T. dall'Amico, W. Mauser, and A. Loew
Hydrol. Earth Syst. Sci., 16, 3517–3533, https://doi.org/10.5194/hess-16-3517-2012, https://doi.org/10.5194/hess-16-3517-2012, 2012
Y. Y. Liu, R. M. Parinussa, W. A. Dorigo, R. A. M. De Jeu, W. Wagner, A. I. J. M. van Dijk, M. F. McCabe, and J. P. Evans
Hydrol. Earth Syst. Sci., 15, 425–436, https://doi.org/10.5194/hess-15-425-2011, https://doi.org/10.5194/hess-15-425-2011, 2011
Y. Y. Liu, J. P. Evans, M. F. McCabe, R. A. M. de Jeu, A. I. J. M. van Dijk, and H. Su
Hydrol. Earth Syst. Sci., 14, 979–990, https://doi.org/10.5194/hess-14-979-2010, https://doi.org/10.5194/hess-14-979-2010, 2010
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Short summary
We took aerial photos of a grassland area using an unoccupied aerial vehicle and used the images to estimate soil moisture via machine learning. We were able to estimate soil moisture with high accuracy. Furthermore, by analyzing the machine learning models we developed, we learned how different factors drive the distribution of moisture across the landscape. Among the factors, rainfall, evapotranspiration, and topography were most important in controlling surface soil moisture distribution.
We took aerial photos of a grassland area using an unoccupied aerial vehicle and used the images...