Synergies for Soil Moisture Retrieval Across Scales From Airborne Polarimetric SAR, Cosmic Ray Neutron Roving, and an In Situ Sensor Network

Fersch, Benjamin; Jagdhuber, Thomas; Schrön, Martin; Völksch, Ingo; Jäger, Marc

doi:10.1029/2018wr023337

Cited by 38 publications

(39 citation statements)

References 72 publications

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“…In 2015, the neutron transport model URANOS (Ultra Rapid Neutron‐Only Simulation) (Köhli et al, 2015, 2018) was developed to reduce the number of model assumptions and make easy‐to‐use neutron simulations available for the hydrological and soil science communities. Since then, the revised model results have been confirmed in many experimental studies (Heidbüchel et al, 2016; Schattan et al, 2018; Schrön et al, 2017, 2018a, 2018b; Fersch et al, 2018). The footprint is a function of air pressure, soil moisture, and air humidity and is also slightly affected by the vegetation cover (Köhli et al, 2015).…”

mentioning

confidence: 75%

Can Drip Irrigation be Scheduled with Cosmic‐Ray Neutron Sensing?

Schrön

Köhli

et al. 2019

Vadose Zone Journal

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Cosmic‐ray neutron sensing (CRNS) was used in a drip‐irrigated field. Soil water content was estimated from CRNS. Neutron transport was simulated for the drip‐irrigated field. CRNS has limitations for irrigation scheduling of drip‐irrigated fields. Irrigation is essential for maintaining food production in water‐scarce regions. The irrigation need depends on the water content of the soil, which we measured with the novel technique of cosmic‐ray neutron sensing (CRNS). The potential of the CRNS technique for drip irrigation scheduling was explored in this study for the Picassent site near Valencia, Spain. To support the experimental evidence, the neutron transport simulation URANOS was used to simulate the effect of drip irrigation on the neutron counts. The overall soil water content (SWC) in the CRNS footprint was characterized with a root mean square error <0.03 cm3/cm3, but the experimental dataset indicated methodological limitations to detect drip water input. Both experimental data and simulation results suggest that the large‐area neutron response to drip irrigation is insignificant in our specific case using a standard CRNS probe. Because of the small area of irrigated patches and short irrigation time, the limited SWC changes due to drip irrigation were not visible from the measured neutron intensity changes. Our study shows that CRNS modeling can be used to assess the suitability of the CRNS technique for certain applications. While the standard CRNS probe was not able to detect small‐scale drip irrigation patterns, the method might be applicable for larger irrigated areas, in drier regions, and for longer and more intense irrigation periods. Since statistical noise is the main limitation of the CRNS measurement, the capability of the instrument could be improved in future studies by larger and more efficient neutron detectors.

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mentioning

confidence: 75%

Can Drip Irrigation be Scheduled with Cosmic‐Ray Neutron Sensing?

Schrön

Köhli

et al. 2019

Vadose Zone Journal

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“…Observed and simulated soil moisture for the DE-Fen site are presented in Figure12. The gray ribbons depict the 25-75 percentiles of a wireless soil moisture sensor network that consists of 55 profiles with measurements at 5, 20, and 50 cm depth (SoilNet, further details are available in Kiese et al, 2018;Fersch et al, 2018). Obviously, simulations and observation show a considerable offset and also the temporal variations are much smoother for the model.…”

Section: Evapotranspiration and Soil Moisturementioning

confidence: 99%

High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

Fersch¹,

Senatore²,

Adler³

et al. 2019

Preprint

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Abstract. The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or largely bound to traditional disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. This study examines the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assesses the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the preAlpine Terrestrial Environmental Observatory (TERENO-preAlpine) for the Ammer (600 km2) and Rott (55 km2) river catchments in southern Germany, covering a five month period (Jun–Oct 2016). The sensitivity of 7 land surface parameters is tested using the Latin-Hypercube One-factor-At-a-Time (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent Parameter Estimation and Uncertainty Analysis software (PEST). The calibration of the offline WRF-Hydro gives Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro, both using the calibrated parameters from the offline model, shows nominal alterations for radiation and precipitation but considerable changes for moisture- and heat fluxes. By comparison with TERENO-preAlpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.

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“…In order to extract from the recorded backscattering signal, only the scattering component triggered by the moisture of the soil, decomposition methods are essential to invert soil moisture from the corresponding part of the signal. Polarimetry offers an exploitable observation space for the decomposition of RADAR measurements to invert for soil moisture [238][239][240].…”

Section: Active Microwave Sensors (Radar Scatterometers)mentioning

confidence: 99%

“…In the last couple of years, soil moisture measurements with cosmic-ray neutrons have been conducted using stationary sensors or car-borne sensors ("rovers"), which are, however, limited to accessible terrain [240,333,334]. Very recent developments by Schrön [335] pioneered the application of airborne neutron sensing.…”

Section: Airborne Geophysical Sensors Of Natural Radiation-gamma and mentioning

confidence: 99%

“…The proof of concept indicated a high potential of airborne neutron sensing, which could become a valuable addition -or even an alternative -to conventional remote-sensing methods. Moreover, cosmic-ray neutron data can also be used to ground-truth remote-sensing products [336,337], or in synergy with airborne PolSAR to correct the cosmic-ray soil moisture product for the influence of biomass [240]. [334]).…”

Section: Airborne Geophysical Sensors Of Natural Radiation-gamma and mentioning

confidence: 99%

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Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

Lausch

Baade

Bannehr³

et al. 2019

Remote Sensing

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In the face of rapid global change it is imperative to preserve geodiversity for the overall conservation of biodiversity. Geodiversity is important for understanding complex biogeochemical and physical processes and is directly and indirectly linked to biodiversity on all scales of ecosystem organization. Despite the great importance of geodiversity, there is a lack of suitable monitoring methods. Compared to conventional in-situ techniques, remote sensing (RS) techniques provide a pathway towards cost-effective, increasingly more available, comprehensive, and repeatable, as well as standardized monitoring of continuous geodiversity on the local to global scale. This paper gives an overview of the state-of-the-art approaches for monitoring soil characteristics and soil moisture with unmanned aerial vehicles (UAV) and air- and spaceborne remote sensing techniques. Initially, the definitions for geodiversity along with its five essential characteristics are provided, with an explanation for the latter. Then, the approaches of spectral traits (ST) and spectral trait variations (STV) to record geodiversity using RS are defined. LiDAR (light detection and ranging), thermal and microwave sensors, multispectral, and hyperspectral RS technologies to monitor soil characteristics and soil moisture are also presented. Furthermore, the paper discusses current and future satellite-borne sensors and missions as well as existing data products. Due to the prospects and limitations of the characteristics of different RS sensors, only specific geotraits and geodiversity characteristics can be recorded. The paper provides an overview of those geotraits.

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Synergies for Soil Moisture Retrieval Across Scales From Airborne Polarimetric SAR, Cosmic Ray Neutron Roving, and an In Situ Sensor Network

Cited by 38 publications

References 72 publications

Can Drip Irrigation be Scheduled with Cosmic‐Ray Neutron Sensing?

Can Drip Irrigation be Scheduled with Cosmic‐Ray Neutron Sensing?

High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

Linking Remote Sensing and Geodiversity and Their Traits Relevant to Biodiversity—Part I: Soil Characteristics

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