Articles | Volume 19, issue 9
https://doi.org/10.5194/hess-19-3845-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-3845-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale
Department of Agricultural, Food and Environmental Sciences, Hydraulic and Forestry Division, University of Perugia, Perugia, Italy
L. Brocca
Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Italy
L. F. Termite
Department of Agricultural, Food and Environmental Sciences, Hydraulic and Forestry Division, University of Perugia, Perugia, Italy
W. Wagner
Department of Geodesy and Geoinformation, Vienna University of Technology, 10 Gusshausstr. 27–29, Vienna, Austria
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Cited
16 citations as recorded by crossref.
- Practical thresholds to distinguish erosive and rill rainfall events F. Todisco et al. 10.1016/j.jhydrol.2019.124173
- Comparison of the Applicability of Different Soil Erosion Models to Predict Soil Erodibility Factor and Event Soil Losses on Loess Slopes in Hungary B. Keller et al. 10.3390/w13243517
- Modelling the dynamics of seal formation and pore clogging in the soil and its effect on infiltration using membrane fouling models F. Todisco et al. 10.1016/j.jhydrol.2023.129208
- Robust Assessment of an Operational Algorithm for the Retrieval of Soil Moisture From AMSR-E Data in Central Italy E. Santi et al. 10.1109/JSTARS.2016.2575361
- Evaluation of SMAP, SMOS-IC, FY3B, JAXA, and LPRM Soil Moisture Products over the Qinghai-Tibet Plateau and Its Surrounding Areas J. Liu et al. 10.3390/rs11070792
- Global analysis of support practices in USLE-based soil erosion modeling M. Xiong et al. 10.1177/0309133319832016
- A comparative evaluation of random roughness indices by rainfall simulator and photogrammetry A. Vinci et al. 10.1016/j.catena.2020.104468
- A Review of the Applications of ASCAT Soil Moisture Products L. Brocca et al. 10.1109/JSTARS.2017.2651140
- Soil Moisture for Hydrological Applications: Open Questions and New Opportunities L. Brocca et al. 10.3390/w9020140
- A Random Forest Machine Learning Approach for the Identification and Quantification of Erosive Events L. Vergni & F. Todisco 10.3390/w15122225
- Infiltration and bulk density dynamics with simulated rainfall sequences F. Todisco et al. 10.1016/j.catena.2022.106542
- Predicting soil loss in central and south Italy with a single USLE-MM model V. Bagarello et al. 10.1007/s11368-018-1953-z
- Setup and calibration of the rainfall simulator of the Masse experimental station for soil erosion studies L. Vergni et al. 10.1016/j.catena.2018.05.018
- A roadmap for high-resolution satellite soil moisture applications – confronting product characteristics with user requirements J. Peng et al. 10.1016/j.rse.2020.112162
- Surface soil moisture estimate from Sentinel-1 and Sentinel-2 data in agricultural fields in areas of high vulnerability to climate variations: the Marche region (Italy) case study B. Brunelli et al. 10.1007/s10668-023-03635-w
- Soil Loss Estimation Coupling a Modified USLE Model with a Runoff Correction Factor Based on Rainfall and Satellite Soil Moisture Data F. Todisco et al. 10.3390/w14132081
16 citations as recorded by crossref.
- Practical thresholds to distinguish erosive and rill rainfall events F. Todisco et al. 10.1016/j.jhydrol.2019.124173
- Comparison of the Applicability of Different Soil Erosion Models to Predict Soil Erodibility Factor and Event Soil Losses on Loess Slopes in Hungary B. Keller et al. 10.3390/w13243517
- Modelling the dynamics of seal formation and pore clogging in the soil and its effect on infiltration using membrane fouling models F. Todisco et al. 10.1016/j.jhydrol.2023.129208
- Robust Assessment of an Operational Algorithm for the Retrieval of Soil Moisture From AMSR-E Data in Central Italy E. Santi et al. 10.1109/JSTARS.2016.2575361
- Evaluation of SMAP, SMOS-IC, FY3B, JAXA, and LPRM Soil Moisture Products over the Qinghai-Tibet Plateau and Its Surrounding Areas J. Liu et al. 10.3390/rs11070792
- Global analysis of support practices in USLE-based soil erosion modeling M. Xiong et al. 10.1177/0309133319832016
- A comparative evaluation of random roughness indices by rainfall simulator and photogrammetry A. Vinci et al. 10.1016/j.catena.2020.104468
- A Review of the Applications of ASCAT Soil Moisture Products L. Brocca et al. 10.1109/JSTARS.2017.2651140
- Soil Moisture for Hydrological Applications: Open Questions and New Opportunities L. Brocca et al. 10.3390/w9020140
- A Random Forest Machine Learning Approach for the Identification and Quantification of Erosive Events L. Vergni & F. Todisco 10.3390/w15122225
- Infiltration and bulk density dynamics with simulated rainfall sequences F. Todisco et al. 10.1016/j.catena.2022.106542
- Predicting soil loss in central and south Italy with a single USLE-MM model V. Bagarello et al. 10.1007/s11368-018-1953-z
- Setup and calibration of the rainfall simulator of the Masse experimental station for soil erosion studies L. Vergni et al. 10.1016/j.catena.2018.05.018
- A roadmap for high-resolution satellite soil moisture applications – confronting product characteristics with user requirements J. Peng et al. 10.1016/j.rse.2020.112162
- Surface soil moisture estimate from Sentinel-1 and Sentinel-2 data in agricultural fields in areas of high vulnerability to climate variations: the Marche region (Italy) case study B. Brunelli et al. 10.1007/s10668-023-03635-w
- Soil Loss Estimation Coupling a Modified USLE Model with a Runoff Correction Factor Based on Rainfall and Satellite Soil Moisture Data F. Todisco et al. 10.3390/w14132081
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Latest update: 25 Dec 2024
Short summary
We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly...