@phdthesis{Graeff2011,
  author    = {Gr{\"a}ff, Thomas},
  title     = {Soil moisture dynamics and soil moisture controlled runoff processes at different spatial scales : from observation to modelling},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-54470},
  school      = {Universit{\"a}t Potsdam},
  year      = {2011},
  abstract  = {Soil moisture is a key state variable that controls runoff formation, infiltration and partitioning of radiation into latent and sensible heat. However, the experimental characterisation of near surface soil moisture patterns and their controls on runoff formation remains a challenge. This subject was one aspect of the BMBF-funded OPAQUE project (operational discharge and flooding predictions in head catchments). As part of that project the focus of this dissertation is on: (1) testing the methodology and feasibility of the Spatial TDR technology in producing soil moisture profiles along TDR probes, including an inversion technique of the recorded signal in heterogeneous field soils, (2) the analysis of spatial variability and temporal dynamics of soil moisture at the field scale including field experiments and hydrological modelling, (3) the application of models of different complexity for understanding soil moisture dynamics and its importance for runoff generation as well as for improving the prediction of runoff volumes. To fulfil objective 1, several laboratory experiments were conducted to understand the influence of probe rod geometry and heterogeneities in the sampling volume under different wetness conditions. This includes a detailed analysis on how these error sources affect retrieval of soil moisture profiles in soils. Concerning objective 2 a sampling strategy of two TDR clusters installed in the head water of the Wilde Weißeritz catchment (Eastern Ore Mountains, Germany) was used to investigate how well "the catchment state" can be characterised by means of distributed soil moisture data observed at the field scale. A grassland site and a forested site both located on gentle slopes were instrumented with two Spatial TDR clusters that consist of up to 39 TDR probes. Process understanding was gained by modelling the interaction of evapotranspiration and soil moisture with the hydrological process model CATFLOW. A field scale irrigation experiment was carried out to investigate near subsurface processes at the hillslope scale. The interactions of soil moisture and runoff formation were analysed using discharge data from three nested catchments: the Becherbach with a size of 2 km², the Rehefeld catchment (17 km²) and the superordinate Ammelsdorf catchment (49 km²). Statistical analyses including observations of pre-event runoff, soil moisture and different rainfall characteristics were employed to predict stream flow volume. On the different scales a strong correlation between the average soil moisture and the runoff coefficients of rainfall-runoff events could be found, which almost explains equivalent variability as the pre-event runoff. Furthermore, there was a strong correlation between surface soil moisture and subsurface wetness with a hysteretic behaviour between runoff soil moisture. To fulfil objective 3 these findings were used in a generalised linear model (GLM) analysis which combines state variables describing the catchments antecedent wetness and variables describing the meteorological forcing in order to predict event runoff coefficients. GLM results were compared to simulations with the catchment model WaSiM ETH. Hereby were the model results of the GLMs always better than the simulations with WaSiM ETH. The GLM analysis indicated that the proposed sampling strategy of clustering TDR probes in typical functional units is a promising technique to explore soil moisture controls on runoff generation and can be an important link between the scales. Long term monitoring of such sites could yield valuable information for flood warning and forecasting by identifying critical soil moisture conditions for the former and providing a better representation of the initial moisture conditions for the latter.},
  language  = {en}
}
@phdthesis{Jagdhuber2012,
  author    = {Jagdhuber, Thomas},
  title     = {Soil parameter retrieval under vegetation cover using SAR polarimetry},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-60519},
  school      = {Universit{\"a}t Potsdam},
  year      = {2012},
  abstract  = {Soil conditions under vegetation cover and their spatial and temporal variations from point to catchment scale are crucial for understanding hydrological processes within the vadose zone, for managing irrigation and consequently maximizing yield by precision farming. Soil moisture and soil roughness are the key parameters that characterize the soil status. In order to monitor their spatial and temporal variability on large scales, remote sensing techniques are required. Therefore the determination of soil parameters under vegetation cover was approached in this thesis by means of (multi-angular) polarimetric SAR acquisitions at a longer wavelength (L-band, lambda=23cm). In this thesis, the penetration capabilities of L-band are combined with newly developed (multi-angular) polarimetric decomposition techniques to separate the different scattering contributions, which are occurring in vegetation and on ground. Subsequently the ground components are inverted to estimate the soil characteristics. The novel (multi-angular) polarimetric decomposition techniques for soil parameter retrieval are physically-based, computationally inexpensive and can be solved analytically without any a priori knowledge. Therefore they can be applied without test site calibration directly to agricultural areas. The developed algorithms are validated with fully polarimetric SAR data acquired by the airborne E-SAR sensor of the German Aerospace Center (DLR) for three different study areas in Germany. The achieved results reveal inversion rates up to 99\% for the soil moisture and soil roughness retrieval in agricultural areas. However, in forested areas the inversion rate drops significantly for most of the algorithms, because the inversion in forests is invalid for the applied scattering models at L-band. The validation against simultaneously acquired field measurements indicates an estimation accuracy (root mean square error) of 5-10vol.\% for the soil moisture (range of in situ values: 1-46vol.\%) and of 0.37-0.45cm for the soil roughness (range of in situ values: 0.5-4.0cm) within the catchment. Hence, a continuous monitoring of soil parameters with the obtained precision, excluding frozen and snow covered conditions, is possible. Especially future, fully polarimetric, space-borne, long wavelength SAR missions can profit distinctively from the developed polarimetric decomposition techniques for separation of ground and volume contributions as well as for soil parameter retrieval on large spatial scales.},
  language  = {en}
}
@phdthesis{RiveraVillarreyes2013,
  author    = {Rivera Villarreyes, Carlos Andres},
  title     = {Cosmic-ray neutron sensing for soil moisture measurements in cropped fields},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69748},
  school      = {Universit{\"a}t Potsdam},
  year      = {2013},
  abstract  = {This cumulative dissertation explored the use of the detection of natural background of fast neutrons, the so-called cosmic-ray neutron sensing (CRS) approach to measure field-scale soil moisture in cropped fields. Primary cosmic rays penetrate the top atmosphere and interact with atmospheric particles. Such interaction results on a cascade of high-energy neutrons, which continue traveling through the atmospheric column. Finally, neutrons penetrate the soil surface and a second cascade is produced with the so-called secondary cosmic-ray neutrons (fast neutrons). Partly, fast neutrons are absorbed by hydrogen (soil moisture). Remaining neutrons scatter back to the atmosphere, where its flux is inversely correlated to the soil moisture content, therefore allowing a non-invasive indirect measurement of soil moisture. The CRS methodology is mainly evaluated based on a field study carried out on a farmland in Potsdam (Brandenburg, Germany) along three crop seasons with corn, sunflower and winter rye; a bare soil period; and two winter periods. Also, field monitoring was carried out in the Schaefertal catchment (Harz, Germany) for long-term testing of CRS against ancillary data. In the first experimental site, the CRS method was calibrated and validated using different approaches of soil moisture measurements. In a period with corn, soil moisture measurement at the local scale was performed at near-surface only, and in subsequent periods (sunflower and winter rye) sensors were placed in three depths (5 cm, 20 cm and 40 cm). The direct transfer of CRS calibration parameters between two vegetation periods led to a large overestimation of soil moisture by the CRS. Part of this soil moisture overestimation was attributed to an underestimation of the CRS observation depth during the corn period ( 5-10 cm), which was later recalculated to values between 20-40 cm in other crop periods (sunflower and winter rye). According to results from these monitoring periods with different crops, vegetation played an important role on the CRS measurements. Water contained also in crop biomass, above and below ground, produces important neutron moderation. This effect was accounted for by a simple model for neutron corrections due to vegetation. It followed crop development and reduced overall CRS soil moisture error for periods of sunflower and winter rye. In Potsdam farmland also inversely-estimated soil hydraulic parameters were determined at the field scale, using CRS soil moisture from the sunflower period. A modelling framework coupling HYDRUS-1D and PEST was applied. Subsequently, field-scale soil hydraulic properties were compared against local scale soil properties (modelling and measurements). Successful results were obtained here, despite large difference in support volume. Simple modelling framework emphasizes future research directions with CRS soil moisture to parameterize field scale models. In Schaefertal catchment, CRS measurements were verified using precipitation and evapotranspiration data. At the monthly resolution, CRS soil water storage was well correlated to these two weather variables. Also clearly, water balance could not be closed due to missing information from other compartments such as groundwater, catchment discharge, etc. In the catchment, the snow influence to natural neutrons was also evaluated. As also observed in Potsdam farmland, CRS signal was strongly influenced by snow fall and snow accumulation. A simple strategy to measure snow was presented for Schaefertal case. Concluding remarks of this dissertation showed that (a) the cosmic-ray neutron sensing (CRS) has a strong potential to provide feasible measurement of mean soil moisture at the field scale in cropped fields; (b) CRS soil moisture is strongly influenced by other environmental water pools such as vegetation and snow, therefore these should be considered in analysis; (c) CRS water storage can be used for soil hydrology modelling for determination of soil hydraulic parameters; and (d) CRS approach has strong potential for long term monitoring of soil moisture and for addressing studies of water balance.},
  language  = {en}
}
@phdthesis{Hohenbrink2016,
  author    = {Hohenbrink, Tobias Ludwig},
  title     = {Turning a problem into a solution: heterogeneities in soil hydrology},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-101485},
  school      = {Universit{\"a}t Potsdam},
  pages     = {x, 123},
  year      = {2016},
  abstract  = {It is commonly recognized that soil moisture exhibits spatial heterogeneities occurring in a wide range of scales. These heterogeneities are caused by different factors ranging from soil structure at the plot scale to land use at the landscape scale. There is an urgent need for effi-cient approaches to deal with soil moisture heterogeneity at large scales, where manage-ment decisions are usually made. The aim of this dissertation was to test innovative ap-proaches for making efficient use of standard soil hydrological data in order to assess seep-age rates and main controls on observed hydrological behavior, including the role of soil het-erogeneities. As a first step, the applicability of a simplified Buckingham-Darcy method to estimate deep seepage fluxes from point information of soil moisture dynamics was assessed. This was done in a numerical experiment considering a broad range of soil textures and textural het-erogeneities. The method performed well for most soil texture classes. However, in pure sand where seepage fluxes were dominated by heterogeneous flow fields it turned out to be not applicable, because it simply neglects the effect of water flow heterogeneity. In this study a need for new efficient approaches to handle heterogeneities in one-dimensional water flux models was identified. As a further step, an approach to turn the problem of soil moisture heterogeneity into a solu-tion was presented: Principal component analysis was applied to make use of the variability among soil moisture time series for analyzing apparently complex soil hydrological systems. It can be used for identifying the main controls on the hydrological behavior, quantifying their relevance, and describing their particular effects by functional averaged time series. The ap-proach was firstly tested with soil moisture time series simulated for different texture classes in homogeneous and heterogeneous model domains. Afterwards, it was applied to 57 mois-ture time series measured in a multifactorial long term field experiment in Northeast Germa-ny. The dimensionality of both data sets was rather low, because more than 85 \% of the total moisture variance could already be explained by the hydrological input signal and by signal transformation with soil depth. The perspective of signal transformation, i.e. analyzing how hydrological input signals (e.g., rainfall, snow melt) propagate through the vadose zone, turned out to be a valuable supplement to the common mass flux considerations. Neither different textures nor spatial heterogeneities affected the general kind of signal transfor-mation showing that complex spatial structures do not necessarily evoke a complex hydro-logical behavior. In case of the field measured data another 3.6\% of the total variance was unambiguously explained by different cropping systems. Additionally, it was shown that dif-ferent soil tillage practices did not affect the soil moisture dynamics at all. The presented approach does not require a priori assumptions about the nature of physical processes, and it is not restricted to specific scales. Thus, it opens various possibilities to in-corporate the key information from monitoring data sets into the modeling exercise and thereby reduce model uncertainties.},
  language  = {en}
}
@phdthesis{Schroen2016,
  author    = {Schr{\"o}n, Martin},
  title     = {Cosmic-ray neutron sensing and its applications to soil and land surface hydrology},
  publisher = {Verlag Dr. Hut GmbH},
  address   = {M{\"u}nchen},
  isbn      = {978-3-8439-3139-7},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-395433},
  school      = {Universit{\"a}t Potsdam},
  pages     = {223},
  year      = {2016},
  abstract  = {Water scarcity, adaption on climate change, and risk assessment of droughts and floods are critical topics for science and society these days. Monitoring and modeling of the hydrological cycle are a prerequisite to understand and predict the consequences for weather and agriculture. As soil water storage plays a key role for partitioning of water fluxes between the atmosphere, biosphere, and lithosphere, measurement techniques are required to estimate soil moisture states from small to large scales. The method of cosmic-ray neutron sensing (CRNS) promises to close the gap between point-scale and remote-sensing observations, as its footprint was reported to be 30 ha. However, the methodology is rather young and requires highly interdisciplinary research to understand and interpret the response of neutrons to soil moisture. In this work, the signal of nine detectors has been systematically compared, and correction approaches have been revised to account for meteorological and geomagnetic variations. Neutron transport simulations have been consulted to precisely characterize the sensitive footprint area, which turned out to be 6--18 ha, highly local, and temporally dynamic. These results have been experimentally confirmed by the significant influence of water bodies and dry roads. Furthermore, mobile measurements on agricultural fields and across different land use types were able to accurately capture the various soil moisture states. It has been further demonstrated that the corresponding spatial and temporal neutron data can be beneficial for mesoscale hydrological modeling. Finally, first tests with a gyrocopter have proven the concept of airborne neutron sensing, where increased footprints are able to overcome local effects. This dissertation not only bridges the gap between scales of soil moisture measurements. It also establishes a close connection between the two worlds of observers and modelers, and further aims to combine the disciplines of particle physics, geophysics, and soil hydrology to thoroughly explore the potential and limits of the CRNS method.},
  language  = {en}
}