@misc{BaroniZinkKumaretal.2017, author = {Baroni, Gabriele and Zink, Matthias and Kumar, Rohini and Samaniego, Luis and Attinger, Sabine}, title = {Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales}, series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe}, number = {545}, issn = {1866-8372}, doi = {10.25932/publishup-41917}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-419174}, pages = {20}, year = {2017}, abstract = {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.}, language = {en} } @article{BaroniZinkKumaretal.2017, author = {Baroni, Gabriele and Zink, Matthias and Kumar, Rohini and Samaniego, Luis and Attinger, Sabine}, title = {Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales}, series = {Hydrology and earth system sciences : HESS}, volume = {21}, journal = {Hydrology and earth system sciences : HESS}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1027-5606}, doi = {10.5194/hess-21-2301-2017}, pages = {2301 -- 2320}, year = {2017}, abstract = {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.}, language = {en} } @misc{DobkowitzWalzBaronietal.2020, author = {Dobkowitz, Sophia and Walz, Ariane and Baroni, Gabriele and P{\´e}rez-Marin, Aldrin M.}, title = {Cross-Scale Vulnerability Assessment for Smallholder Farming}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {978}, issn = {1866-8372}, doi = {10.25932/publishup-47470}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-474703}, pages = {26}, year = {2020}, abstract = {Climate change heavily impacts smallholder farming worldwide. Cross-scale vulnerability assessment has a high potential to identify nested measures for reducing vulnerability of smallholder farmers. Despite their high practical value, there are currently only limited examples of cross-scale assessments. The presented study aims at assessing the vulnerability of smallholder farmers in the Northeast of Brazil across three scales: regional, farm and field scale. In doing so, it builds on existing vulnerability indices and compares results between indices at the same scale and across scales. In total, six independent indices are tested, two at each scale. The calculated indices include social, economic and ecological indicators, based on municipal statistics, meteorological data, farm interviews and soil analyses. Subsequently, indices and overlapping indicators are normalized for intra- and cross-scale comparison. The results show considerable differences between indices across and within scales. They indicate different activities to reduce vulnerability of smallholder farmers. Major shortcomings arise from the conceptual differences between the indices. We therefore recommend the development of hierarchical indices, which are adapted to local conditions and contain more overlapping indicators for a better understanding of the nested vulnerabilities of smallholder farmers.}, language = {en} } @article{DobkowitzWalzBaronietal.2020, author = {Dobkowitz, Sophia and Walz, Ariane and Baroni, Gabriele and P{\´e}rez-Marin, Aldrin M.}, title = {Cross-Scale Vulnerability Assessment for Smallholder Farming}, series = {Sustainability}, volume = {12}, journal = {Sustainability}, number = {9}, publisher = {MDPI}, address = {Basel}, issn = {2071-1050}, doi = {10.3390/su12093787}, pages = {24}, year = {2020}, abstract = {Climate change heavily impacts smallholder farming worldwide. Cross-scale vulnerability assessment has a high potential to identify nested measures for reducing vulnerability of smallholder farmers. Despite their high practical value, there are currently only limited examples of cross-scale assessments. The presented study aims at assessing the vulnerability of smallholder farmers in the Northeast of Brazil across three scales: regional, farm and field scale. In doing so, it builds on existing vulnerability indices and compares results between indices at the same scale and across scales. In total, six independent indices are tested, two at each scale. The calculated indices include social, economic and ecological indicators, based on municipal statistics, meteorological data, farm interviews and soil analyses. Subsequently, indices and overlapping indicators are normalized for intra- and cross-scale comparison. The results show considerable differences between indices across and within scales. They indicate different activities to reduce vulnerability of smallholder farmers. Major shortcomings arise from the conceptual differences between the indices. We therefore recommend the development of hierarchical indices, which are adapted to local conditions and contain more overlapping indicators for a better understanding of the nested vulnerabilities of smallholder farmers.}, language = {en} } @article{KayatzBaroniHillieretal.2018, author = {Kayatz, Benjamin and Baroni, Gabriele and Hillier, Jon and L{\"u}dtke, Stefan and Heathcote, Richard and Malin, Daniella and van Tonder, Carl and Kuster, Benjamin and Freese, Dirk and H{\"u}ttl, Reinhard and Wattenbach, Martin}, title = {Cool farm tool water}, series = {Journal of cleaner production}, volume = {207}, journal = {Journal of cleaner production}, publisher = {Elsevier}, address = {Oxford}, issn = {0959-6526}, pages = {1163 -- 1179}, year = {2018}, abstract = {The agricultural sector accounts for 70\% of all water consumption and poses great pressure on ground water resources. Therefore, evaluating agricultural water consumption is highly important as it allows supply chain actors to identify practices which are associated with unsustainable water use, which risk depleting current water resources and impacting future production. However, these assessments are often not feasible for crop producers as data, models and experiments are required in order to conduct them. This work introduces a new on-line agricultural water use assessment tool that provides the water footprint and irrigation requirements at field scale based on an enhanced FAO56 approach combined with a global climate, crop and soil databases. This has been included in the Cool Farm Tool - an online tool which already provides metrics for greenhouse gas emissions and biodiversity impacts and therefore allows for a more holistic assessment of environmental sustainability in farming and agricultural supply chains. The model is tested against field scale and state level water footprint data providing good results. The tool provides a practical, reliable way to assess agricultural water use, and offers a means to engage growers and stakeholders in identifying efficient water management practices. (C) 2018 The Authors. Published by Elsevier Ltd.}, 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} } @article{GhasemizadeBaroniAbbaspouretal.2017, author = {Ghasemizade, Mehdi and Baroni, Gabriele and Abbaspour, Karim and Schirmer, Mario}, title = {Combined analysis of time-varying sensitivity and identifiability indices to diagnose the response of a complex environmental model}, series = {Environmental modelling \& software with environment data news}, volume = {88}, journal = {Environmental modelling \& software with environment data news}, publisher = {Elsevier}, address = {Oxford}, issn = {1364-8152}, doi = {10.1016/j.envsoft.2016.10.011}, pages = {22 -- 34}, year = {2017}, abstract = {Sensitivity and identifiability analyses are common diagnostic tools to address over-parametrization in complex environmental models, but a combined application of the two analyses is rarely conducted. In this study, we performed a temporal global sensitivity analysis using the variance-based method of Sobol' and a temporal identifiability analysis of model parameters using the dynamic identifiability method (DYNIA). We discuss the relationship between the two analyses with a focus on parameter identification and output uncertainty reduction. The hydrological model HydroGeoSphere was used to simulate daily evapotranspiration, water content, and seepage at the lysimeter scale. We found that identifiability of a parameter does not necessarily reduce output uncertainty. It was also found that the information from the main and total effects (main Sobol' sensitivity indices) is required to allow uncertainty reduction in the model output. Overall, the study highlights the role of combined temporal diagnostic tools for improving our understanding of model behavior.}, language = {en} } @article{BaroniDrastigLichtenfeldetal.2019, author = {Baroni, Gabriele and Drastig, Katrin and Lichtenfeld, Anna-Ulrike and Jost, Leonie and Claas, Peter}, title = {Assessment of irrigation scheduling systems in Germany}, series = {Irrigation and drainage}, volume = {68}, journal = {Irrigation and drainage}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {1531-0353}, doi = {10.1002/ird.2337}, pages = {520 -- 530}, year = {2019}, abstract = {In Germany, the irrigation sector accounts for only 1\% of water use. In recent years, however, this sector has attracted more attention due to the occurrence of severe drought periods. Irrigation scheduling systems could support adaptation strategies but little is known about current providers, performance and users. In this study we aimed to depict the current situation of the existence and functioning of irrigation scheduling systems available in Germany. Six methods were identified and assessed based on direct interviews with end-users and a comparative analysis. The results showed a positive feedback from the users. However, the recommendations were rarely implemented, while only the seasonal irrigation requirement was considered to support actual water abstraction. These results were corroborated by the comparative analysis. Five of the six irrigation scheduling systems estimated the seasonal irrigation amount consistently, while wider differences were found by looking at the irrigation season and at the number of irrigations. Overall, it is found that irrigation support systems are valuable tools for supporting adaptation strategies to fast changes in agro-environmental conditions. However, specific assessments based on real measurements should be considered in order to improve the performance of the systems and provide more consistent support to end-users. (c) 2019 John Wiley \& Sons, Ltd.}, language = {en} } @article{BaroniFrancke2020, author = {Baroni, Gabriele and Francke, Till}, title = {An effective strategy for combining variance- and distribution-based global sensitivity analysis}, series = {Environmental modelling \& software with environment data news}, volume = {134}, journal = {Environmental modelling \& software with environment data news}, publisher = {Elsevier}, address = {Oxford}, issn = {1364-8152}, doi = {10.1016/j.envsoft.2020.104851}, pages = {14}, year = {2020}, abstract = {We present a new strategy for performing global sensitivity analysis capable to estimate main and interaction effects from a generic sampling design. The new strategy is based on a meaningful combination of varianceand distribution-based approaches. The strategy is tested on four analytic functions and on a hydrological model. Results show that the analysis is consistent with the state-of-the-art Saltelli/Jansen formula but to better quantify the interaction effect between the input factors when the output distribution is skewed. Moreover, the estimation of the sensitivity indices is much more robust requiring a smaller number of simulations runs. Specific settings and alternative methods that can be integrated in the new strategy are also discussed. Overall, the strategy is considered as a new simple and effective tool for performing global sensitivity analysis that can be easily integrated in any environmental modelling framework.}, language = {en} } @article{StevanatoBaroniOswaldetal.2022, author = {Stevanato, Luca and Baroni, Gabriele and Oswald, Sascha and Lunardon, Marcello and Mareš, Vratislav and Marinello, Francesco and Moretto, Sandra and Polo, Matteo and Sartori, Paolo and Schattan, Paul and R{\"u}hm, Werner}, title = {An alternative incoming correction for cosmic-ray neutron sensing observations using local muon measurement}, series = {Geophysical research letters}, volume = {49}, journal = {Geophysical research letters}, number = {6}, publisher = {American Geophysical Union}, address = {Washington}, issn = {0094-8276}, doi = {10.1029/2021GL095383}, pages = {9}, year = {2022}, abstract = {Measuring the variability of incoming neutrons locally would be usefull for the cosmic-ray neutron sensing (CRNS) method. As the measurement of high energy neutrons is not so easy, alternative particles can be considered for such purpose. Among them, muons are particles created from the same cascade of primary cosmic-ray fluxes that generate neutrons at the ground. In addition, they can be easily detected by small and relatively inexpensive detectors. For these reasons they could provide a suitable local alternative to incoming corrections based on remote neutron monitor data. The reported measurements demonstrated that muon detection system can detect incoming cosmic-ray variations locally. Furthermore the precision of this measurement technique is considered adequate for many CRNS applications.}, language = {en} }