TY - GEN A1 - Schrön, Martin A1 - Köhli, Markus A1 - Scheiffele, Lena A1 - Iwema, Joost A1 - Bogena, Heye R. A1 - Lv, Ling A1 - Martini, Edoardo A1 - Baroni, Gabriele A1 - Rosolem, Rafael A1 - Weimar, Jannis A1 - Mai, Juliane A1 - Cuntz, Matthias A1 - Rebmann, Corinna A1 - Oswald, Sascha A1 - Dietrich, Peter A1 - Schmidt, Ulrich A1 - Zacharias, Steffen T1 - Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 636 KW - forested headwater catchment KW - moisture observing system KW - soil-water content KW - parameterization methods KW - scale KW - field KW - dynamics KW - observatories KW - networks Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419134 IS - 636 SP - 5009 EP - 5030 ER - TY - GEN A1 - Baroni, Gabriele A1 - Zink, Matthias A1 - Kumar, Rohini A1 - Samaniego, Luis A1 - Attinger, Sabine T1 - Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales T2 - Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe N2 - Soil properties show high heterogeneity at different spatial scales and their correct characterization remains a crucial challenge over large areas. The aim of the study is to quantify the impact of different types of uncertainties that arise from the unresolved soil spatial variability on simulated hydrological states and fluxes. Three perturbation methods are presented for the characterization of uncertainties in soil properties. The methods are applied on the soil map of the upper Neckar catchment (Germany), as an example. The uncertainties are propagated through the distributed mesoscale hydrological model (mHM) to assess the impact on the simulated states and fluxes. The model outputs are analysed by aggregating the results at different spatial and temporal scales. These results show that the impact of the different uncertainties introduced in the original soil map is equivalent when the simulated model outputs are analysed at the model grid resolution (i.e. 500 m). However, several differences are identified by aggregating states and fluxes at different spatial scales (by subcatchments of different sizes or coarsening the grid resolution). Streamflow is only sensitive to the perturbation of long spatial structures while distributed states and fluxes (e.g. soil moisture and groundwater recharge) are only sensitive to the local noise introduced to the original soil properties. A clear identification of the temporal and spatial scale for which finer-resolution soil information is (or is not) relevant is unlikely to be universal. However, the comparison of the impacts on the different hydrological components can be used to prioritize the model improvements in specific applications, either by collecting new measurements or by calibration and data assimilation approaches. In conclusion, the study underlines the importance of a correct characterization of uncertainty in soil properties. With that, soil maps with additional information regarding the unresolved soil spatial variability would provide strong support to hydrological modelling applications. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 545 KW - global sensitivity analysis KW - hydraulic conductivity KW - pedotransfer functions KW - parameter uncertainty KW - physical properties KW - solute transport KW - model KW - rainfall KW - Evapotranspiration KW - impact Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419174 SN - 1866-8372 IS - 545 ER -