The effect of intermittent water application by surface point sources on the soil moisture dynamics and on deep percolation under the root zone

Abstract. Spatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport and vegetation productivity. Its characterization, offers an avenue to improve our understanding of complex land surface–atmosphere interactions. In this paper, soil moisture dynamics at soil surface (first centimeters) and root-zone (up to 1.5 m depth) are investigated at three spatial scales: local scale (field measurements), 8×8 km2 (hydrological model) and 25×25 km2 scale (ERS scatterometer) in a French watershed. This study points out the quality of surface and root-zone soil moisture data for SIM model and ERS scatterometer for a three year period. Surface soil moisture is highly variable because is more influenced by atmospheric conditions (rain, wind and solar radiation), and presents RMS errors up to 0.08 m3 m−3. On the other hand, root-zone moisture presents lower variability with small RMS errors (between 0.02 and 0.06 m3 m-3). These results will contribute to satellite and model verification of moisture, but also to better application of radar data for data assimilation in future.

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Investigating the effect of limited climatic data on evapotranspiration-based numerical modeling of soil moisture dynamics in the unsaturated root zone: a case study for potato crop

Modeling Earth Systems and Environment ◽

10.1007/s40808-020-00824-8 ◽

2020 ◽

Vol 6 (4) ◽

pp. 2433-2449 ◽

Cited By ~ 3

Author(s):

Navsal Kumar ◽

Vijay Shankar ◽

Arunava Poddar

Keyword(s):

Numerical Modeling ◽

Soil Moisture ◽

Root Zone ◽

Potato Crop ◽

Climatic Data ◽

Soil Moisture Dynamics ◽

Moisture Dynamics

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root zone water quality and soil moisture dynamics of biomass cropping systems and landscape positions

10.31274/etd-180810-190 ◽

2012 ◽

Author(s):

Wade Welsh

Keyword(s):

Water Quality ◽

Soil Moisture ◽

Root Zone ◽

Cropping Systems ◽

Soil Moisture Dynamics ◽

Moisture Dynamics ◽

Zone Water

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Persistence and memory timescales in root-zone soil moisture dynamics

Water Resources Research ◽

10.1002/2015wr017983 ◽

2016 ◽

Vol 52 (2) ◽

pp. 1427-1445 ◽

Cited By ~ 27

Author(s):

Khaled Ghannam ◽

Taro Nakai ◽

Athanasios Paschalis ◽

Christopher A. Oishi ◽

Ayumi Kotani ◽

...

Keyword(s):

Soil Moisture ◽

Root Zone ◽

Soil Moisture Dynamics ◽

Moisture Dynamics

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A dense network of cosmic-ray neutron sensors for soil moisture observation in a pre-alpine headwater catchment in Germany

10.5194/essd-2020-48 ◽

2020 ◽

Author(s):

Benjamin Fersch ◽

Till Francke ◽

Maik Heistermann ◽

Martin Schrön ◽

Veronika Döpper ◽

...

Keyword(s):

Soil Moisture ◽

Hydrological Modeling ◽

Root Zone ◽

Spatial Scales ◽

Cosmic Ray ◽

Dense Network ◽

Data Set ◽

Soil Moisture Dynamics ◽

Moisture Dynamics ◽

Headwater Catchment

Abstract. Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while well established sensors typically suffer from a small spatial support. With a sensor footprint up to several hectares, Cosmic-Ray Neutron Sensing (CRNS) is an emerging technology to address that challenge. So far, the CRNS method has typically been applied with single sensors or in sparse national scale networks. This study presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km2: the pre-alpine Rott headwater catchment in Southern Germany which is characterized by strong soil moisture gradients in a heterogeneous landscape with forests and grasslands. With substantially overlapping sensor footprints, that network was designed to study root zone soil moisture dynamics at the catchment-scale. The observations of the dense CRNS network were complemented by extensive measurements that allow to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from Unmanned Areal Systems (UAS), permanent and temporary wireless sensor networks, profile probes as well as comprehensive manual soil sampling. Since neutron counts are also affected by hydrogen pools other than soil moisture, vegetation biomass was monitored in forest and grassland patches, as well as meteorological variables; discharge and groundwater tables were recorded to support hydrological modeling experiments. As a result, we provide a unique and comprehensive dataset to several research communities: to those who investigate the retrieval of soil moisture from cosmic-ray neutron sensing, to those who study the variability of soil moisture at different spatio-temporal scales, and to those who intend to better understand the role of root-zone soil moisture dynamics in the context of catchment and groundwater hydrology, as well as land – atmosphere exchange processes. The data set is available through EUDAT, splitted into the two subsets https://doi.org/10.23728/b2share.85fe0f9dac0f48df9215c17e65d1f1e1 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.93ed99e486904d48a8a6a68083066198 (Fersch et al., 2020b).

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A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany

Earth System Science Data ◽

10.5194/essd-12-2289-2020 ◽

2020 ◽

Vol 12 (3) ◽

pp. 2289-2309

Author(s):

Benjamin Fersch ◽

Till Francke ◽

Maik Heistermann ◽

Martin Schrön ◽

Veronika Döpper ◽

...

Keyword(s):

Soil Moisture ◽

Hydrological Modeling ◽

Root Zone ◽

Spatial Scales ◽

Cosmic Ray ◽

Dense Network ◽

Data Set ◽

Soil Moisture Dynamics ◽

Moisture Dynamics ◽

Headwater Catchment

Abstract. Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while conventional sensors typically suffer from small spatial support. With a sensor footprint up to several hectares, cosmic-ray neutron sensing (CRNS) is a modern technology to address that challenge. So far, the CRNS method has typically been applied with single sensors or in sparse national-scale networks. This study presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km2: the pre-Alpine Rott headwater catchment in Southern Germany, which is characterized by strong soil moisture gradients in a heterogeneous landscape with forests and grasslands. With substantially overlapping sensor footprints, this network was designed to study root-zone soil moisture dynamics at the catchment scale. The observations of the dense CRNS network were complemented by extensive measurements that allow users to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from unmanned areal systems (UASs), permanent and temporary wireless sensor networks, profile probes, and comprehensive manual soil sampling. Since neutron counts are also affected by hydrogen pools other than soil moisture, vegetation biomass was monitored in forest and grassland patches, as well as meteorological variables; discharge and groundwater tables were recorded to support hydrological modeling experiments. As a result, we provide a unique and comprehensive data set to several research communities: to those who investigate the retrieval of soil moisture from cosmic-ray neutron sensing, to those who study the variability of soil moisture at different spatiotemporal scales, and to those who intend to better understand the role of root-zone soil moisture dynamics in the context of catchment and groundwater hydrology, as well as land–atmosphere exchange processes. The data set is available through the EUDAT Collaborative Data Infrastructure and is split into two subsets: https://doi.org/10.23728/b2share.282675586fb94f44ab2fd09da0856883 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.bd89f066c26a4507ad654e994153358b (Fersch et al., 2020b).

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Analysis of surface and root-zone soil moisture dynamics with ERS scatterometer and the hydrometeorological model SAFRAN-ISBA-MODCOU at Grand Morin watershed (France)

Hydrology and Earth System Sciences ◽

10.5194/hess-12-1415-2008 ◽

2008 ◽

Vol 12 (6) ◽

pp. 1415-1424 ◽

Cited By ~ 25

Author(s):

T. Paris Anguela ◽

M. Zribi ◽

S. Hasenauer ◽

F. Habets ◽

C. Loumagne

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Root Zone ◽

Spatial Scales ◽

Soil Surface ◽

Temporal Variations ◽

Model Verification ◽

Atmospheric Conditions ◽

Soil Moisture Dynamics ◽

Moisture Dynamics

Abstract. Spatial and temporal variations of soil moisture strongly affect flooding, erosion, solute transport and vegetation productivity. Its characterization, offers an avenue to improve our understanding of complex land surface-atmosphere interactions. In this paper, soil moisture dynamics at soil surface (first centimeters) and root-zone (up to 1.5 m depth) are investigated at three spatial scales: local scale (field measurements), 8×8 km2 (hydrological model) and 25×25 km2 scale (ERS scatterometer) in a French watershed. This study points out the quality of surface and root-zone soil moisture data for SIM model and ERS scatterometer for a three year period. Surface soil moisture is highly variable because is more influenced by atmospheric conditions (rain, wind and solar radiation), and presents RMSE up to 0.08 m3 m−3. On the other hand, root-zone moisture presents lower variability with small RMSE (between 0.02 and 0.06 m3 m−3). These results will contribute to satellite and model verification of moisture, but also to better application of radar data for data assimilation in future.

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A global analysis of soil moisture derived from satellite observations and a land surface model

Hydrology and Earth System Sciences ◽

10.5194/hess-16-833-2012 ◽

2012 ◽

Vol 16 (3) ◽

pp. 833-847 ◽

Cited By ~ 52

Author(s):

K. T. Rebel ◽

R. A. M. de Jeu ◽

P. Ciais ◽

N. Viovy ◽

S. L. Piao ◽

...

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Root Zone ◽

Global Analysis ◽

Soil Layer ◽

Land Surface Model ◽

Surface Model ◽

Rain Event ◽

Soil Moisture Dynamics ◽

Moisture Dynamics

Abstract. Soil moisture availability is important in regulating photosynthesis and controlling land surface-climate feedbacks at both the local and global scale. Recently, global remote-sensing datasets for soil moisture have become available. In this paper we assess the possibility of using remotely sensed soil moisture – AMSR-E (LPRM) – to similate soil moisture dynamics of the process-based vegetation model ORCHIDEE by evaluating the correspondence between these two products using both correlation and autocorrelation analyses. We find that the soil moisture product of AMSR-E (LPRM) and the simulated soil moisture in ORCHIDEE correlate well in space and time, in particular when considering the root zone soil moisture of ORCHIDEE. However, the root zone soil moisture in ORCHIDEE has on average a higher temporal autocorrelation relative to AMSR-E (LPRM) and in situ measurements. This may be due to the different vertical depth of the two products – AMSR-E (LPRM) at the 2–5 cm surface depth and ORCHIDEE at the root zone (max. 2 m) depth – to uncertainty in precipitation forcing in ORCHIDEE, and to the fact that the structure of ORCHIDEE consists of a single-layer deep soil, which does not allow simulation of the proper cascade of time scales that characterize soil drying after each rain event. We conclude that assimilating soil moisture, using AMSR-E (LPRM) in a land surface model like ORCHIDEE with an improved hydrological model of more than one soil layer, may significantly improve the soil moisture dynamics, which could lead to improved CO2 and energy flux predictions.

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