Bioturbation and erosion rates along the soil-hillslope conveyor belt,part 2: Quantification using an analytical solution of the diffusion–advection equation

Particles on soil-mantled hillslopes are subject to downslope transport by erosion processes and vertical mixing by bioturbation. Both are key processes for understanding landscape evolution and soil formation, and affect the functioning of the critical zone. We show here how the depth–age information, derived from feldspar-based single grain post-infrared infrared stimulated luminescence (pIRIR), can be used to simultaneously quantify erosion and bioturbation processes along a hillslope. In this study, we propose, for the first time, an analytical solution for the diffusion–advection equation to calculate the diffusivity constant and erosion–deposition rates. We have fitted this model to age–depth data derived from 15 soil samples from four soil profiles along a catena located under natural grassland in the Santa Clotilde Critical Zone Observatory, in the south of Spain. A global sensitivity analysis was used to assess the relative importance of each model parameter in the output. Finally, the posterior probability density functions were calculated to evaluate the uncertainty in the model parameter estimates. The results show that the diffusivity constant at the surface varies from 11.4 to 81.9 mm² a^-1 for the hilltop and hill-base profile, respectively, and between 7.4 and 64.8 mm² a^-1 at 50 cm depth. The uncertainty in the estimation of the erosion–deposition rates was found to be too high to make a reliable estimate, probably because erosion–deposition processes are much slower than bioturbation processes in this environment. This is confirmed by a global sensitivity analysis that shows how the most important parameters controlling the age–depth structure in this environment are the diffusivity constant and regolith depth. Finally, we have found a good agreement between the soil reworking rates proposed by earlier studies, considering only particle age and depth, and the estimated diffusivity constants. The soil reworking rates are effective rates, corrected for the proportion of particles actually participating in the process. © 2019 John Wiley & Sons, Ltd.     

Uncertainty in quantitative analyses of topographic change: error propagation and the role of thresholding

Topographic surveys inevitably contain error, introducing uncertainty into estimates of volumetric or mean change based on the differencing of repeated surveys. In the geomorphic community, uncertainty has often been framed as a problem of separating out real change from apparent change due purely to error, and addressed by removing measured change considered indistinguishable from random noise from analyses (thresholding). Thresholding is important when quantifying gross changes (i.e. total erosion or total deposition), which are systematically biased by random errors in stable parts of a landscape. However, net change estimates are not substantially influenced by those same random errors, and the use of thresholds results in inherently biased, and potentially misleading, estimates of net change and uncertainty. More generally, thresholding is unrelated to the important process of propagating uncertainty in order to place uncertainty bounds around final estimates. Error propagation methods for uncorrelated, correlated, and systematic errors are presented. Those equations demonstrate that uncertainties in modern net change analyses, as well as in gross change analyses using reasonable thresholds, are likely to be dominated by low-magnitude but highly correlated or systematic errors, even after careful attempts to reduce those errors. In contrast, random errors with little to no correlation largely cancel to negligible levels when averaged or summed. Propagated uncertainty is then typically insensitive to the precision of individual measurements, and is instead defined by the relative mean error (accuracy) over the area of interest. Given that real-world mean elevation changes in many landscape settings are often similar in magnitude to potential mean errors in repeat topographic analyses, reducing highly correlated or systematic errors will be central to obtaining accurate change estimates, while placing uncertainty bounds around those results provides essential context for their interpretation. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.     

Spatially-explicit sensitivity and uncertainty analysis in a MCDA-based flood vulnerability model

This study presents a methodology for conducting sensitivity and uncertainty analysis of a GIS-based multi-criteria model used to assess flood vulnerability in a case study in Brazil. The paper explores the robustness of model outcomes against slight changes in criteria weights. One criterion was varied at-a-time, while others were fixed to their baseline values. An algorithm was developed using Python and a geospatial data abstraction library to automate the variation of weights, implement the ANP (analytic network process) tool, reclassify the raster results, compute the class switches, and generate an uncertainty surface. Results helped to identify highly vulnerable areas that are burdened by high uncertainty and to investigate which criteria contribute to this uncertainty. Overall, the criteria ‘houses with improper building material’ and ‘evacuation drills and training’ are the most sensitive ones, thus, requiring more accurate measurements. The sensitivity of these criteria is explained by their weights in the base run, their spatial distribution, and the spatial resolution. These findings can support decision makers to characterize, report, and mitigate uncertainty in vulnerability assessment. The case study results demonstrate that the developed approach is simple, flexible, transparent, and may be applied to other complex spatial problems.     

Analysis of positional uncertainty of road networks in volunteered geographic information with a statistically defined buffer-zone method

Volunteered geographic information (VGI) is crowdsourced information that can enrich and enhance research and applications based on geo-referenced data. However, the quality of VGI is of great concern, and positional accuracy is a fundamental basis for the VGI quality assurance. A buffer-zone method can be used for its assessment, but the buffer radius in this technique is subjectively specified; as result, different selections of the buffer radius lead to different positional accuracies. To solve this problem, a statistically defined buffer zone for the positional accuracy assessment in VGI is proposed in this study. To facilitate practical applications, we have also developed an iterative method to obtain a theoretically defined buffer zone. In addition to the positional accuracy assessment, we have derived a measure of positional quality, which comprises the assessment of positional accuracy and the level of confidence in such assessment determined with respect to a statistically defined buffer zone. To illustrate and substantiate the theoretical arguments, both numerical simulations and real-life experiments are performed using OpenStreetMap. The experimental results confirm the high significance of the proposed statistical approach to the buffer zone-based assessment of the positional uncertainty in VGI.     

DEM提取坡度信息的不确定性分析

以陕西省671幅1∶50000比例尺,25m分辨率的DEM数据为信息源,分析DEM分辨率对提取坡度信息的不确定性影响。研究表明:平均坡度随DEM分辨率的减小呈显著递减型二次曲线变化,但当DEM分辨率减小到一定程度时,平均坡度将趋于稳定;并且,随DEM分辨率变化,坡度的不确定性呈现明显的空间结构性分布,DEM栅格单元内部地形的复杂性和变异性越大,坡度提取不确定性越大,如沟坡地坡度提取误差明显大于沟间地。因此,实际应用中要充分考虑研究区域DEM地形描述的尺度效应和不确定性问题,选择合适尺度的DEM提取坡度信息,保证提取结果的科学有效。     

长江中下游平原升金湖流域硝酸盐来源解析及其不确定性

考虑流域地理特征的空间分异,以升金湖流域人口/农业集约区大渡口(DDK)与森林子流域唐田河(TTH)为研究区,利用贝叶斯同位素混合模型分别解析这2个子流域硝酸盐来源的贡献率,并分析其不确定性. 研究表明:(1)地下水中,DDK?TTH硝酸盐均主要来源于粪便/污水,贡献率可达65%以上,粪便/污水通过土壤下渗导致地下水硝...     

Uncertainty analysis of strain modal parameters by Bayesian method using frequency response function

Structural strain modes are able to detect changes in local structural performance, but errors are inevitably intermixed in the measured data. In this paper, strain modal parameters are considered as random variables, and their uncertainty is analyzed by a Bayesian method based on the structural frequency response function (FRF). The estimates of strain modal parameters with maximal posterior probability are determined. Several independent measurements of the FRF of a four-story reinforced concrete frame structural model were performed in the laboratory. The ability to identify the stiffness change in a concrete column using the strain mode was verified. It is shown that the uncertainty of the natural frequency is very small. Compared with the displacement mode shape, the variations of strain mode shapes at each point are quite different. The damping ratios are more affected by the types of test systems. Except for the case where a high order strain mode does not identify local damage, the first order strain mode can provide an exact indication of the damage location.     

Temperature and Pressure Dependencies of Thermal Transport Properties of Rocks: Implications for Uncertainties in Thermal Lithosphere Models and new Laboratory Measurements of High-Grade Rocks in the Central Fennoscandian Shield

Measurements on thermal conductivity and diffusivity as functions of temperature (up to 1150 K) and pressure (up to 1000 MPa) are presented for Archaean and Proterozoic mafic high-grade rocks metamorphosed in middle and lower crustal pressures, and situated in eastern Finland, central Fennoscandian Shield. Decrease of 12–20% in conductivity and 40–55% in diffusivity was recorded between room temperature and 1150 K, which can be considered as typical of phonon conductivity. Radiative heat transfer effects were not detected in these samples. Pressure dependencies of the samples are weak if compared to crystalline rocks in general, but relatively typical for mafic rocks.The temperature and pressure dependencies of thermal transport properties (data from literature and the present study) were applied in an uncertainty analysis of lithospheric conductive thermal modellings with random (Monte Carlo) simulations using a 4-layer model representative of shield lithosphere. Model parameters were varied according to predetermined probability functions and standard deviations were calculated for lithospheric temperature and heat flow density after 1500 independent simulations. The results suggest that the variations (uncertainties) in calculated temperature and heat flow density values due to variations in the temperature and pressure dependencies of conductivity are minor in comparison to the effects produced by typical variations in the room temperature value of conductivity, heat production rate or lower boundary condition values.     

GIS质量控制中不确定度理论

阐述了ＧＩＳ质量控制中不确定度的概念和定义,交 分为随机的和综合的不确定度两类,分别给出了其估计方法,并指出在ＧＩＳ数据中如何估计系统方差和置信系数,是需要深入研究和解决的难题。     

Large-Eddy Simulation Of A Nocturnal Stratocumulus-Topped Marine Atmospheric Boundary Layer: An Uncertainty Analysis

A large-eddy simulation (LES) model has been used to study a nocturnalstratocumulus-topped marine atmospheric boundary layer. The main objectivesof our study have been first to investigate the statistical significance of LES-derived data products. Second, to test the sensitivity of our LES results with respect to the representation of subgrid-scale mixing and microphysical processes, and third to evaluate and to quantify the parametric uncertainty arising from the incomplete knowledge of the environmental parameters that are required to specify the initial and boundary conditions of a particular case study. Model simulations were compared with observations obtained in solid stratocumulus during the third flight of the first 'Lagrangian' experiment of the Atlantic Stratocumulus Transition Experiment (ASTEX). Based on these simulations the following conclusions could be drawn. Resolution(50 × 50 × 25 m³) and domain size (3.2 × 3.2 × 1.5 km³) of the LES calculations were adequate from a numerical point of view to represent the essential features of the stratocumulus-topped boundary layer. However, the ensemble runs performed in our study to investigate the statistical significance of LES-derived data products demonstrate that the area-time averaging procedure for the second-order moments produces only a low degree of statistical reliability in the model results. This illustratesthe necessity of having LES model results that are not only of adequate resolution but also of sufficiently large domain. The impact of different subgrid schemes was small, but the primary effects of drizzle were found to influence the boundary-layer structure in a climatologically significant way. The parametric uncertainty analysis revealed that the largest contribution to the variance of the LES-derived data products is due to theuncertainties in the cloud-top jump of total water mixing ratio and the net radiative forcing. The differences between the model and measurements for most of the simulated quantities were within the modelling uncertainties, but the calculated precipitation rate was found to differ significantly from that derived in the observations.