TY - JOUR A1 - Guillemoteau, Julien A1 - Tronicke, Jens T1 - Non-standard electromagnetic induction sensor configurations: Evaluating sensitivities and applicability JF - Journal of applied geophysics N2 - For near surface geophysical surveys, small-fixed offset loop-loop electromagnetic induction (EMI) sensors are usually placed parallel to the ground surface (i.e., both loops are at the same height above ground). In this study, we evaluate the potential of making measurements with a system that is not parallel to the ground; i.e., by positioning the system at different inclinations with respect to ground surface. First, we present the Maxwell theory for inclined magnetic dipoles over a homogeneous half space. By analyzing the sensitivities of such configurations, we,show that varying the angle of the system would result in improved imaging capabilities. For example, we show that acquiring data with a vertical system allows detection of a conductive body with a better lateral resolution compared to data acquired using standard horizontal configurations. The synthetic responses are presented for a heterogeneous medium and compared to field data acquired in the historical Park Sanssouci in Potsdam, Germany. After presenting a detailed sensitivity analysis and synthetic examples of such ground conductivity measurements, we suggest a new strategy of acquisition that allows to better estimate the true distribution of electrical conductivity using instruments with a fixed, small offset between the loops. This strategy is evaluated using field data collected at a well-constrained test-site in Horstwalde (Germany). Here, the target buried utility pipes are best imaged using vertical system configurations demonstrating the potential of our approach for typical applications. (C) 2015 Elsevier B.V. Pill rights reserved. KW - Electromagnetics KW - EMI sensors KW - Loop-loop systems KW - Near surface geophysics KW - Civil engineering KW - Sensitivity analysis Y1 - 2015 U6 - https://doi.org/10.1016/j.jappgeo.2015.04.008 SN - 0926-9851 SN - 1879-1859 VL - 118 SP - 15 EP - 23 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Grimm, Volker A1 - Berger, Uta T1 - Robustness analysis: Deconstructing computational models for ecological theory and applications JF - Ecological modelling : international journal on ecological modelling and engineering and systems ecolog N2 - The design of computational models is path-dependent: the choices made in each step during model development constrain the choices that are available in the subsequent steps. The actual path of model development can be extremely different, even for the same system, because the path depends on the question addressed, the availability of data, and the consideration of specific expert knowledge, in addition to the experience, background, and modelling preferences of the modellers. Thus, insights from different models are practically impossible to integrate, which hinders the development of general theory. We therefore suggest augmenting the current culture of communicating models as working just fine with a culture of presenting analyses in which we try to break models, i.e., model mechanisms explaining certain observations break down. We refer to the systematic attempts to break a model as “robustness analysis” (RA). RA is the systematic deconstruction of a model by forcefully changing the model's parameters, structure, and representation of processes. We discuss the nature and elements of RA and provide brief examples. RA cannot be completely formalized into specific techniques and instead corresponds to detective work that is driven by general questions and specific hypotheses, with strong attention focused on unusual behaviours. Both individual modellers and ecological modelling in general will benefit from RA because RA helps with understanding models and identifying “robust theories”, which are general principles that are independent of the idiosyncrasies of specific models. Integrating the results of RAs from different models to address certain systems or questions will then provide a comprehensive overview of when certain mechanisms control system behaviour and when and why this control ceases. This approach can provide insights into the mechanisms that lead to regime shifts in actual ecological systems. KW - Sensitivity analysis KW - Ecological theory KW - Computational modelling KW - Robustness KW - Model analysis KW - Understanding Y1 - 2016 U6 - https://doi.org/10.1016/j.ecolmodel.2015.07.018 SN - 0304-3800 SN - 1872-7026 VL - 326 SP - 162 EP - 167 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Baroni, Gabriele A1 - Scheiffele, Lena A1 - Schrön, Martin A1 - Ingwersen, Joachim A1 - Oswald, Sascha T1 - Uncertainty, sensitivity and improvements in soil moisture estimation with cosmic-ray neutron sensing JF - Journal of hydrology N2 - Cosmic-ray neutron sensing (CRNS) is a promising proximal soil sensing technique to estimate soil moisture at intermediate scale and high temporal resolution. However, the signal shows complex and non-unique response to all hydrogen pools near the land surface, providing some challenges for soil moisture estimation in practical applications. Aims of the study were 1) to assess the uncertainty of CRNS as a stand-alone approach to estimate volumetric soil moisture in cropped field 2) to identify the causes of this uncertainty 3) and possible improvements. Two experimental sites in Germany were equipped with a CRNS probe and point-scale soil moisture network. Additional monitoring activities were conducted during the crop growing season to characterize the soil-plant systems. This data is used to identify and quantify the different sources of uncertainty (factors). An uncertainty analysis, based on Monte Carlo approach, is applied to propagate these uncertainties to CRNS soil moisture estimations. In addition, a sensitivity analysis based on the Sobol’ method is performed to identify the most important factors explaining this uncertainty. Results show that CRNS soil moisture compares well to the soil moisture network when these point-scale values are weighted to account for the spatial sensitivity of the signal and other sources of hydrogen (lattice water and organic carbon) are added to the water content. However, the performance decreases when CRNS is considered as a stand-alone method to retrieve the actual (non-weighted) volumetric soil moisture. The support volume (penetration depth and radius) shows also a considerable uncertainty, especially in relatively dry soil moisture conditions. Four of the seven factors analyzed (the vertical soil moisture profile, bulk density, incoming neutron correction and the calibrated parameter N0) were found to play an important role. Among the possible improvements identified, a simple correction factor based on vertical point-scale soil moisture profiles shows to be a promising approach to account for the sensitivity of the CRNS signal to the upper soil layers. KW - Soil moisture KW - Cosmic-ray neutrons KW - Uncertainty analysis KW - Sensitivity analysis Y1 - 2018 U6 - https://doi.org/10.1016/j.jhydrol.2018.07.053 SN - 0022-1694 SN - 1879-2707 VL - 564 SP - 873 EP - 887 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Wang, Enli A1 - He, Di A1 - Wang, Jing A1 - Lilley, Julianne M. A1 - Christy, Brendan A1 - Hoffmann, Munir P. A1 - O'Leary, Garry A1 - Hatfield, Jerry L. A1 - Ledda, Luigi A1 - Deligios, Paola A. A1 - Grant, Brian A1 - Jing, Qi A1 - Nendel, Claas A1 - Kage, Henning A1 - Qian, Budong A1 - Rezaei, Ehsan Eyshi A1 - Smith, Ward A1 - Weymann, Wiebke A1 - Ewert, Frank T1 - How reliable are current crop models for simulating growth and seed yield of canola across global sites and under future climate change? JF - Climatic change N2 - To better understand how climate change might influence global canola production, scientists from six countries have completed the first inter-comparison of eight crop models for simulating growth and seed yield of canola, based on experimental data from six sites across five countries. A sensitivity analysis was conducted with a combination of five levels of atmospheric CO2 concentrations, seven temperature changes, five precipitation changes, together with five nitrogen application rates. Our results were in several aspects different from those of previous model inter-comparison studies for wheat, maize, rice, and potato crops. A partial model calibration only on phenology led to very poor simulation of aboveground biomass and seed yield of canola, even from the ensemble median or mean. A full calibration with additional data of leaf area index, biomass, and yield from one treatment at each site reduced simulation error of seed yield from 43.8 to 18.0%, but the uncertainty in simulation results remained large. Such calibration (with data from one treatment) was not able to constrain model parameters to reduce simulation uncertainty across the wide range of environments. Using a multi-model ensemble mean or median reduced the uncertainty of yield simulations, but the simulation error remained much larger than observation errors, indicating no guarantee that the ensemble mean/median would predict the correct responses. Using multi-model ensemble median, canola yield was projected to decline with rising temperature (2.5-5.7% per degrees C), but to increase with increasing CO2 concentration (4.6-8.3% per 100-ppm), rainfall (2.1-6.1% per 10% increase), and nitrogen rates (1.3-6.0% per 10% increase) depending on locations. Due to the large uncertainty, these results need to be treated with caution. We further discuss the need to collect new data to improve modelling of several key physiological processes of canola for increased confidence in future climate impact assessments. KW - AgMIP KW - Brassica napus L. KW - Model calibration KW - Model improvement; KW - Multimodel ensemble KW - Sensitivity analysis Y1 - 2022 U6 - https://doi.org/10.1007/s10584-022-03375-2 SN - 0165-0009 SN - 1573-1480 VL - 172 IS - 1-2 PB - Springer Nature CY - Dordrecht ER - TY - JOUR A1 - Tella, Timothy O. A1 - Winterleitner, Gerd A1 - Morsilli, Michele A1 - Mutti, Maria T1 - Testing sea-level and carbonate production effects on stratal architecture of a distally steepened carbonate ramp (Upper Miocene, Menorca) BT - a 3D forward modelling approach JF - Sedimentary geology : international journal of applied and regional sedimentology N2 - Although distally steepened carbonate ramps have been studied by numerous researchers, the processes that control the development of these carbonate systems, including tectonics, differential carbonate production along the ramp profile, or antecedent physiography of the slopes, are an ongoing discussion. We use a stratigraphic forward model to test different hypotheses to unravel controls over distally steepened ramp development, referenced to the well-known Upper Miocene Menorca carbonate ramp (Spain). Sensitivity tests show that distally steepened ramps develop under complex interaction among accommodation, carbonate production and sediment transport parameters. Ramp slope initiation is favoured by still stands and falls of sea-level, in a setting with high-frequency sea-level fluctuations with amplitude between 20 m and 40 m. Low-frequency and higher amplitude sea-level fluctuations of about 115 m tend to form models with no significant slope development. The impact of antecedent slope on the geometry of ramps is determined by the paleoslope inclination, with flat to subhorizontal paleosurfaces resulting in ramps that mirror the antecedent slope. In contrast, steeper paleosurfaces tend to result in ramps with well-defined slopes. Our models, therefore, show that the ramp profile becomes more influenced by the depth constraints on the carbonate sediment producers than by the geometry of the underlying topography as the inclination of the paleosurface increases. The presented models also show that seagrass-dominated shallow carbonate production tends to result in steep slopes due to the low-transport characteristic imposed by seagrass trapping. This steepness can, however, be altered by the introduction of high transport sediment grains from deeper carbonate producers, which fill the slopes and more distal sections of the ramp profile. KW - Forward model KW - Distally steepened ramp KW - Sea-level fluctuation; KW - Sensitivity analysis KW - Sediment transport KW - Carbonate production KW - Grain KW - association Y1 - 2022 U6 - https://doi.org/10.1016/j.sedgeo.2022.106267 SN - 0037-0738 SN - 1879-0968 VL - 441 PB - Elsevier CY - Amsterdam [u.a.] ER - TY - JOUR A1 - Gomez-Zapata, Juan Camilo A1 - Pittore, Massimiliano A1 - Cotton, Fabrice A1 - Lilienkamp, Henning A1 - Shinde, Simantini A1 - Aguirre, Paula A1 - Santa Maria, Hernan T1 - Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models JF - Bulletin of Earthquake Engineering N2 - In seismic risk assessment, the sources of uncertainty associated with building exposure modelling have not received as much attention as other components related to hazard and vulnerability. Conventional practices such as assuming absolute portfolio compositions (i.e., proportions per building class) from expert-based assumptions over aggregated data crudely disregard the contribution of uncertainty of the exposure upon earthquake loss models. In this work, we introduce the concept that the degree of knowledge of a building stock can be described within a Bayesian probabilistic approach that integrates both expert-based prior distributions and data collection on individual buildings. We investigate the impact of the epistemic uncertainty in the portfolio composition on scenario-based earthquake loss models through an exposure-oriented logic tree arrangement based on synthetic building portfolios. For illustrative purposes, we consider the residential building stock of Valparaiso (Chile) subjected to seismic ground-shaking from one subduction earthquake. We have found that building class reconnaissance, either from prior assumptions by desktop studies with aggregated data (top-down approach), or from building-by-building data collection (bottom-up approach), plays a fundamental role in the statistical modelling of exposure. To model the vulnerability of such a heterogeneous building stock, we require that their associated set of structural fragility functions handle multiple spectral periods. Thereby, we also discuss the relevance and specific uncertainty upon generating either uncorrelated or spatially cross-correlated ground motion fields within this framework. We successively show how various epistemic uncertainties embedded within these probabilistic exposure models are differently propagated throughout the computed direct financial losses. This work calls for further efforts to redesign desktop exposure studies, while also highlighting the importance of exposure data collection with standardized and iterative approaches. KW - Epistemic uncertainty KW - Sensitivity analysis KW - Scheme KW - Faceted taxonomy KW - Probabilistic exposure modelling KW - Earthquake scenario KW - Data collection KW - Earthquake loss modelling KW - Spatially cross-correlated ground motion KW - fields Y1 - 2022 U6 - https://doi.org/10.1007/s10518-021-01312-9 SN - 1570-761X SN - 1573-1456 N1 - Update notice Correction to: Epistemic uncertainty of probabilistic building exposure compositions in scenario-based earthquake loss models (Bulletin of Earthquake Engineering, (2022), 20, 5, (2401-2438), https://doi.org/10.1007/s10518-021-01312-9) Bulletin of Earthquake Engineering, Volume 20, Issue 5, Pages 2439, March 2022, https://doi.org/10.1007/s10518-022-01340-z VL - 20 IS - 5 SP - 2401 EP - 2438 PB - Springer CY - Dordrecht ER -