@phdthesis{Rasche2024, author = {Rasche, Daniel}, title = {Cosmic-ray neutron sensing for the estimation of soil moisture}, doi = {10.25932/publishup-63646}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-636465}, school = {Universit{\"a}t Potsdam}, pages = {xvi, 194}, year = {2024}, abstract = {Water stored in the unsaturated soil as soil moisture is a key component of the hydrological cycle influencing numerous hydrological processes including hydrometeorological extremes. Soil moisture influences flood generation processes and during droughts when precipitation is absent, it provides plant with transpirable water, thereby sustaining plant growth and survival in agriculture and natural ecosystems. Soil moisture stored in deeper soil layers e.g. below 100 cm is of particular importance for providing plant transpirable water during dry periods. Not being directly connected to the atmosphere and located outside soil layers with the highest root densities, water in these layers is less susceptible to be rapidly evaporated and transpired. Instead, it provides longer-term soil water storage increasing the drought tolerance of plants and ecosystems. Given the importance of soil moisture in the context of hydro-meteorological extremes in a warming climate, its monitoring is part of official national adaption strategies to a changing climate. Yet, soil moisture is highly variable in time and space which challenges its monitoring on spatio-temporal scales relevant for flood and drought risk modelling and forecasting. Introduced over a decade ago, Cosmic-Ray Neutron Sensing (CRNS) is a noninvasive geophysical method that allows for the estimation of soil moisture at relevant spatio-temporal scales of several hectares at a high, subdaily temporal resolution. CRNS relies on the detection of secondary neutrons above the soil surface which are produced from high-energy cosmic-ray particles in the atmosphere and the ground. Neutrons in a specific epithermal energy range are sensitive to the amount of hydrogen present in the surroundings of the CRNS neutron detector. Due to same mass as the hydrogen nucleus, neutrons lose kinetic energy upon collision and are subsequently absorbed when reaching low, thermal energies. A higher amount of hydrogen therefore leads to fewer neutrons being detected per unit time. Assuming that the largest amount of hydrogen is stored in most terrestrial ecosystems as soil moisture, changes of soil moisture can be estimated through an inverse relationship with observed neutron intensities. Although important scientific advancements have been made to improve the methodological framework of CRNS, several open challenges remain, of which some are addressed in the scope of this thesis. These include the influence of atmospheric variables such as air pressure and absolute air humidity, as well as, the impact of variations in incoming primary cosmic-ray intensity on observed epithermal and thermal neutron signals and their correction. Recently introduced advanced neutron-to-soil moisture transfer functions are expected to improve CRNS-derived soil moisture estimates, but potential improvements need to be investigated at study sites with differing environmental conditions. Sites with strongly heterogeneous, patchy soil moisture distributions challenge existing transfer functions and further research is required to assess the impact of, and correction of derived soil moisture estimates under heterogeneous site conditions. Despite its capability of measuring representative averages of soil moisture at the field scale, CRNS lacks an integration depth below the first few decimetres of the soil. Given the importance of soil moisture also in deeper soil layers, increasing the observational window of CRNS through modelling approaches or in situ measurements is of high importance for hydrological monitoring applications. By addressing these challenges, this thesis aids to closing knowledge gaps and finding answers to some of the open questions in CRNS research. Influences of different environmental variables are quantified, correction approaches are being tested and developed. Neutron-to-soil moisture transfer functions are evaluated and approaches to reduce effects of heterogeneous soil moisture distributions are presented. Lastly, soil moisture estimates from larger soil depths are derived from CRNS through modified, simple modelling approaches and in situ estimates by using CRNS as a downhole technique. Thereby, this thesis does not only illustrate the potential of new, yet undiscovered applications of CRNS in future but also opens a new field of CRNS research. Consequently, this thesis advances the methodological framework of CRNS for above-ground and downhole applications. Although the necessity of further research in order to fully exploit the potential of CRNS needs to be emphasised, this thesis contributes to current hydrological research and not least to advancing hydrological monitoring approaches being of utmost importance in context of intensifying hydro-meteorological extremes in a changing climate.}, language = {en} } @article{SchroenOswaldZachariasetal.2021, author = {Schr{\"o}n, Martin and Oswald, Sascha and Zacharias, Steffen and Kasner, Mandy and Dietrich, Peter and Attinger, Sabine}, title = {Neutrons on rails}, series = {Geophysical research letters : GRL / American Geophysical Union}, volume = {48}, journal = {Geophysical research letters : GRL / American Geophysical Union}, number = {24}, publisher = {Wiley}, address = {Hoboken, NJ}, issn = {0094-8276}, doi = {10.1029/2021GL093924}, pages = {10}, year = {2021}, abstract = {Large-scale measurements of the spatial distribution of water content in soils and snow are challenging for state-of-the-art hydrogeophysical methods. Cosmic-ray neutron sensing (CRNS) is a noninvasive technology that has the potential to bridge the scale gap between conventional in situ sensors and remote sensing products in both, horizontal and vertical domains. In this study, we explore the feasibility and potential of estimating water content in soils and snow with neutron detectors in moving trains. Theoretical considerations quantify the stochastic measurement uncertainty as a function of water content, altitude, resolution, and detector efficiency. Numerical experiments demonstrate that the sensitivity of measured water content is almost unperturbed by train materials. Finally, three distinct real-world experiments provide a proof of concept on short and long-range tracks. With our results a transregional observational soil moisture product becomes a realistic vision within the next years.}, language = {en} } @article{SchattanKoehliSchroenetal.2019, author = {Schattan, Paul and K{\"o}hli, Markus and Schr{\"o}n, Martin and Baroni, Gabriele and Oswald, Sascha}, title = {Sensing area-average snow water equivalent with cosmic-ray neutrons: the influence of fractional snow cover}, series = {Water resources research}, volume = {55}, journal = {Water resources research}, number = {12}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1029/2019WR025647}, pages = {10796 -- 10812}, year = {2019}, abstract = {Cosmic-ray neutron sensing (CRNS) is a promising non-invasive technique to estimate snow water equivalent (SWE) over large areas. In contrast to preliminary studies focusing on shallow snow conditions (SWE <130 mm), more recently the method was shown experimentally to be sensitive also to deeper snowpacks providing the basis for its use at mountain experimental sites. However, hysteretic neutron response has been observed for complex snow cover including patchy snow-free areas. In the present study we aimed to understand and support the experimental findings using a comprehensive neutron modeling approach. Several simulations have been set up in order to disentangle the effect on the signal of different land surface characteristics and to reproduce multiple observations during periods of snow melt and accumulation. To represent the actual land surface heterogeneity and the complex snow cover, the model used data from terrestrial laser scanning. The results show that the model was able to accurately reproduce the CRNS signal and particularly the hysteresis effect during accumulation and melting periods. Moreover, the sensor footprint was found to be anisotropic and affected by the spatial distribution of liquid water and snow as well as by the topography of the nearby mountains. Under fully snow-covered conditions the CRNS is able to accurately estimate SWE without prior knowledge about snow density profiles or other spatial anomalies. These results provide new insights into the characteristics of the detected neutron signal in complex terrain and support the use of CRNS for long-term snow monitoring in high elevated mountain environments.}, language = {en} } @phdthesis{Barbosa2020, author = {Barbosa, Lu{\´i}s Romero}, title = {Groundwater recharge in tropical wet regions via GIS-based and cosmic-ray neutron sensing}, doi = {10.25932/publishup-46064}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-460641}, school = {Universit{\"a}t Potsdam}, pages = {XXVI, 175}, year = {2020}, abstract = {Studies on the unsustainable use of groundwater resources are still considered incipient since it is frequently a poorly understood and managed, devalued and inadequately protected natural resource. Groundwater Recharge (GWR) is one of the most challenging elements to estimate since it can rarely be measured directly and cannot easily be derived from existing data. To overcome these limitations, many hydro(geo)logists have combined different approaches to estimate large-scale GWR, namely: remote sensing products, such as IMERG product; Water Budget Equation, also in combination with hydrological models, and; Geographic Information System (GIS), using estimation formulas. For intermediary-scale GWR estimation, there exist: Non-invasive Cosmic-Ray Neutron Sensing (CRNS); wireless networks from local soil probes; and soil hydrological models, such as HYDRUS. Accordingly, this PhD thesis aims, on the one hand, to demonstrate a GIS-based model coupling for estimating the GWR distribution on a large scale in tropical wet basins. On the other hand, it aims to use the time series from CRNS and invasive soil moisture probes to inversely calibrate the soil hydraulic properties, and based on this, estimating the intermediary-scale GWR using a soil hydrological model. For such purpose, two tropical wet basins located in a complex sedimentary aquifer in the coastal Northeast region of Brazil were selected. These are the Jo{\~a}o Pessoa Case Study Area and the Guara{\´i}ra Experimental Basin. Several satellite products in the first area were used as input to the GIS-based water budget equation model for estimating the water balance components and GWR in 2016 and 2017. In addition, the point-scale measurement and CRNS data were used in the second area to determine the soil hydraulic properties, and to estimate the GWR in the 2017-2018 and 2018-2019 hydrological years. The resulting values of GWR on large- and intermediary-scale were then compared and validated by the estimates obtained by groundwater table fluctuations. The GWR rates for IMERG- and rain-gauge-based scenarios showed similar coefficients between 68\% and 89\%, similar mean errors between 30\% and 34\%, and slightly-different bias between -13\% and 11\%. The results of GWR rates for soil probes and CRNS soil moisture scenarios ranged from -5.87 to -61.81 cm yr-1, which corresponds to 5\% and 38\% of the precipitation. The calculations of the mean GWR rates on large-scale, based on remote sensing data, and on intermediary-scale, based on CRNS data, held similar results for the Podzol soil type, namely 17.87\% and 17\% of the precipitation. It is then concluded that the proposed methodologies allowed for estimating realistically the GWR over the study areas, which can be a ground-breaking step towards improving the water management and decision-making in the Northeast of Brazil.}, language = {en} } @article{SchattanBaroniOswaldetal.2017, author = {Schattan, Paul and Baroni, Gabriele and Oswald, Sascha and Schoeber, Johannes and Fey, Christine and Kormann, Christoph and Huttenlau, Matthias and Achleitner, Stefan}, title = {Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing}, series = {Water resources research}, volume = {53}, journal = {Water resources research}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0043-1397}, doi = {10.1002/2016WR020234}, pages = {3615 -- 3634}, year = {2017}, abstract = {The characteristics of an aboveground cosmic-ray neutron sensor (CRNS) are evaluated for monitoring a mountain snowpack in the Austrian Alps from March 2014 to June 2016. Neutron counts were compared to continuous point-scale snow depth (SD) and snow-water-equivalent (SWE) measurements from an automatic weather station with a maximum SWE of 600 mm (April 2014). Several spatially distributed Terrestrial Laser Scanning (TLS)-based SD and SWE maps were additionally used. A strong nonlinear correlation is found for both SD and SWE. The representative footprint of the CRNS is in the range of 230-270 m. In contrast to previous studies suggesting signal saturation at around 100 mm of SWE, no complete signal saturation was observed. These results imply that CRNS could be transferred into an unprecedented method for continuous detection of spatially averaged SD and SWE for alpine snowpacks, though with sensitivity decreasing with increasing SWE. While initially different functions were found for accumulation and melting season conditions, this could be resolved by accounting for a limited measurement depth. This depth limit is in the range of 200 mm of SWE for dense snowpacks with high liquid water contents and associated snow density values around 450 kg m(-3) and above. In contrast to prior studies with shallow snowpacks, interannual transferability of the results is very high regardless of presnowfall soil moisture conditions. This underlines the unexpectedly high potential of CRNS to close the gap between point-scale measurements, hydrological models, and remote sensing of the cryosphere in alpine terrain.}, language = {en} }