Articles | Volume 10, issue 1
https://doi.org/10.5194/essd-10-61-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-61-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
11 Jan 2018
| 11 Jan 2018
The Raam regional soil moisture monitoring network in the Netherlands
Harm-Jan F. Benninga
CORRESPONDING AUTHOR
Department of Water Resources, Faculty of Geo-Information Science and
Earth Observation, University of Twente, 7500 AE Enschede, the Netherlands
Coleen D. U. Carranza
Soil Physics and Land Management Group, Department of Environmental
Sciences, Wageningen University, 6700 AA Wageningen, the Netherlands
Michiel Pezij
Water Engineering and Management, Faculty of Engineering Technology,
University of Twente, 7500 AE Enschede, the Netherlands
Pim van Santen
Waterschap Aa en Maas, 5216 PP `s-Hertogenbosch, the Netherlands
Martine J. van der Ploeg
Soil Physics and Land Management Group, Department of Environmental
Sciences, Wageningen University, 6700 AA Wageningen, the Netherlands
Denie C. M. Augustijn
Water Engineering and Management, Faculty of Engineering Technology,
University of Twente, 7500 AE Enschede, the Netherlands
Rogier van der Velde
Department of Water Resources, Faculty of Geo-Information Science and
Earth Observation, University of Twente, 7500 AE Enschede, the Netherlands
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Cited
22 citations as recorded by crossref.
- Soil moisture content retrieval over meadows from Sentinel-1 and Sentinel-2 data using physically based scattering models H. Benninga et al. 10.1016/j.rse.2022.113191
- Estimating soil moisture condition of paddy fields by using optical remote sensing imagery R. Sholihah et al. 10.1088/1755-1315/1109/1/012067
- Root zone soil moisture estimation with Random Forest C. Carranza et al. 10.1016/j.jhydrol.2020.125840
- Sentinel-1 soil moisture content and its uncertainty over sparsely vegetated fields H. Benninga et al. 10.1016/j.hydroa.2020.100066
- Implementation of Two-Stream Emission Model for L-Band Retrievals on the Tibetan Plateau X. Wu 10.3390/rs14030494
- Towards Estimating Land Evaporation at Field Scales Using GLEAM B. Martens et al. 10.3390/rs10111720
- The Texas Soil Observation Network:A Comprehensive Soil Moisture Dataset for Remote Sensing and Land Surface Model Validation T. Caldwell et al. 10.2136/vzj2019.04.0034
- The role of pit-mound microrelief in the redistribution of rainwater in forest soils: a natural legacy facilitating groundwater recharge? D. Juřička et al. 10.1007/s10342-022-01439-7
- Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset P. Zhang et al. 10.5194/essd-13-3075-2021
- Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data M. Pezij et al. 10.1016/j.envsoft.2020.104756
- Modified monitoring system of soil temperature based on ARM M. Liu 10.1016/j.eti.2020.101346
- Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands R. van der Velde et al. 10.5194/hess-25-473-2021
- State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management M. Pezij et al. 10.1016/j.hydroa.2019.100040
- Anatomy of the 2018 agricultural drought in the Netherlands using in situ soil moisture and satellite vegetation indices J. Buitink et al. 10.5194/hess-24-6021-2020
- Application of multi-criteria decision-making methods to identification of soil moisture monitoring sites in an urban catchment in South Australia D. Ratnayake et al. 10.1016/j.wse.2022.09.003
- Monitoring agricultural field trafficability using Sentinel-1 C. Carranza et al. 10.1016/j.agwat.2019.105698
- Soil Moisture Measuring Techniques and Factors Affecting the Moisture Dynamics: A Comprehensive Review M. Rasheed et al. 10.3390/su141811538
- Initial Machine Learning Framework Development of Agriculture Cyber Physical Systems G. Airlangga & A. Liu 10.1088/1742-6596/1196/1/012065
- A signature‐based approach to quantify soil moisture dynamics under contrasting land‐uses R. Araki et al. 10.1002/hyp.14553
- Improving moisture content estimation from field resistivity measurements with subsurface structure information H. Chen & Q. Niu 10.1016/j.jhydrol.2022.128343
- Twelve years of profile soil moisture and temperature measurements in Twente, the Netherlands R. van der Velde et al. 10.5194/essd-15-1889-2023
- Machine Learning to Estimate Surface Soil Moisture from Remote Sensing Data H. Adab et al. 10.3390/w12113223
21 citations as recorded by crossref.
- Soil moisture content retrieval over meadows from Sentinel-1 and Sentinel-2 data using physically based scattering models H. Benninga et al. 10.1016/j.rse.2022.113191
- Estimating soil moisture condition of paddy fields by using optical remote sensing imagery R. Sholihah et al. 10.1088/1755-1315/1109/1/012067
- Root zone soil moisture estimation with Random Forest C. Carranza et al. 10.1016/j.jhydrol.2020.125840
- Sentinel-1 soil moisture content and its uncertainty over sparsely vegetated fields H. Benninga et al. 10.1016/j.hydroa.2020.100066
- Implementation of Two-Stream Emission Model for L-Band Retrievals on the Tibetan Plateau X. Wu 10.3390/rs14030494
- Towards Estimating Land Evaporation at Field Scales Using GLEAM B. Martens et al. 10.3390/rs10111720
- The Texas Soil Observation Network:A Comprehensive Soil Moisture Dataset for Remote Sensing and Land Surface Model Validation T. Caldwell et al. 10.2136/vzj2019.04.0034
- The role of pit-mound microrelief in the redistribution of rainwater in forest soils: a natural legacy facilitating groundwater recharge? D. Juřička et al. 10.1007/s10342-022-01439-7
- Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset P. Zhang et al. 10.5194/essd-13-3075-2021
- Applying transfer function-noise modelling to characterize soil moisture dynamics: a data-driven approach using remote sensing data M. Pezij et al. 10.1016/j.envsoft.2020.104756
- Modified monitoring system of soil temperature based on ARM M. Liu 10.1016/j.eti.2020.101346
- Validation of SMAP L2 passive-only soil moisture products using upscaled in situ measurements collected in Twente, the Netherlands R. van der Velde et al. 10.5194/hess-25-473-2021
- State updating of root zone soil moisture estimates of an unsaturated zone metamodel for operational water resources management M. Pezij et al. 10.1016/j.hydroa.2019.100040
- Anatomy of the 2018 agricultural drought in the Netherlands using in situ soil moisture and satellite vegetation indices J. Buitink et al. 10.5194/hess-24-6021-2020
- Application of multi-criteria decision-making methods to identification of soil moisture monitoring sites in an urban catchment in South Australia D. Ratnayake et al. 10.1016/j.wse.2022.09.003
- Monitoring agricultural field trafficability using Sentinel-1 C. Carranza et al. 10.1016/j.agwat.2019.105698
- Soil Moisture Measuring Techniques and Factors Affecting the Moisture Dynamics: A Comprehensive Review M. Rasheed et al. 10.3390/su141811538
- Initial Machine Learning Framework Development of Agriculture Cyber Physical Systems G. Airlangga & A. Liu 10.1088/1742-6596/1196/1/012065
- A signature‐based approach to quantify soil moisture dynamics under contrasting land‐uses R. Araki et al. 10.1002/hyp.14553
- Improving moisture content estimation from field resistivity measurements with subsurface structure information H. Chen & Q. Niu 10.1016/j.jhydrol.2022.128343
- Twelve years of profile soil moisture and temperature measurements in Twente, the Netherlands R. van der Velde et al. 10.5194/essd-15-1889-2023
1 citations as recorded by crossref.
Latest update: 19 Apr 2024
Short summary
Soil moisture is a central hydrological state variable. We set up a soil moisture and soil temperature profile monitoring network of 15 stations, distributed over the 495 km2 Raam region. The Raam catchment faces dry and wet periods, which both have implications for agricultural and regional water management. The measurements at 5 cm depth provide a reference for soil moisture retrievals from earth observations, while the measurements at deeper layers enable investigation of root zone processes.
Soil moisture is a central hydrological state variable. We set up a soil moisture and soil...
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