Martin Schrön

Footprint characteristics revised for field‐scale soil moisture monitoring with cosmic‐ray neutrons

Cosmic-ray neutron probes are widely used to monitor environmental water content near the surface. The method averages over tens of hectares and is unrivaled in serving representative data for agriculture and hydrological models at the hectometer scale. Recent experiments, however, indicate that the sensor response to environmental heterogeneity is not fully understood. Knowledge of the support volume is a prerequisite for the proper interpretation and validation of hydrogeophysical data. In a previous study, several physical simplifications have been introduced into a neutron transport model in order to derive the characteristics of the cosmic-ray probes footprint. We utilize a refined source and energy spectrum for cosmic-ray neutrons and simulate their response to a variety of environmental conditions. Results indicate that the method is particularly sensitive to soil moisture in the first tens of meters around the probe, whereas the radial weights are changing dynamically with ambient water. The footprint radius ranges from 130 to 240 m depending on air humidity, soil moisture and vegetation. The moisture-dependent penetration depth of 15 to 83 cm decreases exponentially with distance to the sensor. However, the footprint circle remains almost isotropic in complex terrain with nearby rivers, roads or hill slopes. Our findings suggest that a dynamically weighted average of point measurements is essential for accurate calibration and validation. The new insights will have important impact on signal interpretation, sensor installation, data interpolation from mobile surveys, and the choice of appropriate resolutions for data assimilation into hydrological models.

Modeling jet and outflow feedback during star cluster formation

Powerful jets and outflows are launched from the protostellar disks around newborn stars. These outflows carry enough mass and momentum to transform the structure of their parent molecular cloud and to potentially control star formation itself. Despite their importance, we have not been able to fully quantify the impact of jets and outflows during the formation of a star cluster. The main problem lies in limited computing power. We would have to resolve the magnetic jet-launching mechanism close to the protostar and at the same time follow the evolution of a parsec-size cloud for a million years. Current computer power and codes fall orders of magnitude short of achieving this. In order to overcome this problem, we implement a subgrid-scale (SGS) model for launching jets and outflows, which demonstrably converges and reproduces the mass, linear and angular momentum transfer, and the speed of real jets, with ~ 1000 times lower resolution than would be required without SGS model. We apply the new SGS model to turbulent, magnetized star cluster formation and show that jets and outflows (1) eject about 1/4 of their parent molecular clump in high-speed jets, quickly reaching distances of more than a parsec, (2) reduce the star formation rate by about a factor of two, and (3) lead to the formation of ~ 1.5 times as many stars compared to the no-outflow case. Most importantly, we find that jets and outflows reduce the average star mass by a factor of ~ 3 and may thus be essential for understanding the characteristic mass of the stellar initial mass function.

Multiscale and Multivariate Evaluation of Water Fluxes and States over European River Basins

AbstractAccurately predicting regional-scale water fluxes and states remains a challenging task in contemporary hydrology. Coping with this grand challenge requires, among other things, a model that makes reliable predictions across scales, locations, and variables other than those used for parameter estimation. In this study, the mesoscale hydrologic model (mHM) parameterized with the multiscale regionalization technique is comprehensively tested across 400 European river basins. The model fluxes and states, constrained using the observed streamflow, are evaluated against gridded evapotranspiration, soil moisture, and total water storage anomalies, as well as local-scale eddy covariance observations. This multiscale verification is carried out in a seamless manner at the native resolutions of available datasets, varying from 0.5 to 100 km. Results of cross-validation tests show that mHM is able to capture the streamflow dynamics adequately well across a wide range of climate and physiographical character...

COLLECTIVE OUTFLOW FROM A SMALL MULTIPLE STELLAR SYSTEM

The formation of high-mass stars is usually accompanied by powerful protostellar outflows. Such high-mass outflows are not simply scaled-up versions of their lower-mass counterparts, since observations suggest that the collimation degree degrades with stellar mass. Theoretically, the origins of massive outflows remain open to question because radiative feedback and fragmentation of the accretion flow around the most massive stars, with M > 15 M ☉, may impede the driving of magnetic disk winds. We here present a three-dimensional simulation of the early stages of core fragmentation and massive star formation that includes a subgrid-scale model for protostellar outflows. We find that stars that form in a common accretion flow tend to have aligned outflow axes, so that the individual jets of multiple stars can combine to form a collective outflow. We compare our simulation to observations with synthetic H2 and CO observations and find that the morphology and kinematics of such a collective outflow resembles some observed massive outflows, such as Cepheus A and DR 21. We finally compare physical quantities derived from simulated observations of our models to the actual values in the models to examine the reliability of standard methods for deriving physical quantities, demonstrating that those methods indeed recover the actual values to within a factor of two to three.

Computationally inexpensive identification of noninformative model parameters by sequential screening

Environmental models tend to require increasing computational time and resources as physical process descriptions are improved or new descriptions are incorporated. Many-query applications such as sensitivity analysis or model calibration usually require a large number of model evaluations leading to high computational demand. This often limits the feasibility of rigorous analyses. Here we present a fully automated sequential screening method that selects only informative parameters for a given model output. The method requires a number of model evaluations that is approximately 10 times the number of model parameters. It was tested using the mesoscale hydrologic model mHM in three hydrologically unique European river catchments. It identified around 20 informative parameters out of 52, with different informative parameters in each catchment. The screening method was evaluated with subsequent analyses using all 52 as well as only the informative parameters. Subsequent Sobols global sensitivity analysis led to almost identical results yet required 40% fewer model evaluations after screening. mHM was calibrated with all and with only informative parameters in the three catchments. Model performances for daily discharge were equally high in both cases with Nash-Sutcliffe efficiencies above 0.82. Calibration using only the informative parameters needed just one third of the number of model evaluations. The universality of the sequential screening method was demonstrated using several general test functions from the literature. We therefore recommend the use of the computationally inexpensive sequential screening method prior to rigorous analyses on complex environmental models.

The SCALEX Campaign: Scale-Crossing Land Surface and Boundary Layer Processes in the TERENO-preAlpine Observatory

AbstractScaleX is a collaborative measurement campaign, collocated with a long-term environmental observatory of the German Terrestrial Environmental Observatories (TERENO) network in the mountainous terrain of the Bavarian Prealps, Germany. The aims of both TERENO and ScaleX include the measurement and modeling of land surface–atmosphere interactions of energy, water, and greenhouse gases. ScaleX is motivated by the recognition that long-term intensive observational research over years or decades must be based on well-proven, mostly automated measurement systems, concentrated in a small number of locations. In contrast, short-term intensive campaigns offer the opportunity to assess spatial distributions and gradients by concentrated instrument deployments, and by mobile sensors (ground and/or airborne) to obtain transects and three-dimensional patterns of atmospheric, surface, or soil variables and processes. Moreover, intensive campaigns are ideal proving grounds for innovative instruments, methods, and...

Cosmic‐ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads

Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic-Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture non-invasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of local structures and roads. We employed neutron transport simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that the presence of roads introduces a bias in the CRNS estimation of field soil moisture compared to non-road scenarios. However, this effect becomes insignificant at distances beyond a few meters from the road. Measurements from the road could overestimate the field value by up to 40 % depending on road material, width, and the surrounding field water content. The bias could be successfully removed with an analytical correction function that accounts for these parameters. Additionally, an empirical approach is proposed that can be used on-the-fly without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between road-effect corrected measurements and field soil moisture observations. However, if knowledge about the road characteristics is missing, any measurements on the road could substantially reduce the accuracy of this method. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture.

Response functions for detectors in cosmic ray neutron sensing

Cosmic-Ray Neutron Sensing (CRNS) is a novel technique for determining environmental water content by measuring albedo neutrons in the epithermal to fast energy range with moderated neutron detectors. We have investigated the response function of stationary and mobile neutron detectors typically used for environmental research in order to improve the model accuracy for neutron transport studies. Monte Carlo simulations have been performed in order to analyze the detection probability in terms of energy-dependent response and angular sensitivity for different variants of CRNS detectors and converter gases. Our results reveal the sensor’s response to neutron energies from 0.1 eV to 106 eV and highest sensitivity to vertical fluxes. The detector efficiency shows good agreement with reference data from the structurally similar Bonner Spheres. The relative probability of neutrons contributing to the overall integrated signal is especially important in regions with non-uniform albedo fluxes, such as complex terrain or heterogeneous distribution of hydrogen pools.