Evaluating post-wildfire logging-slash cover treatment to reduce hillslope erosion after salvage logging using ground measurements and remote sensing

Continuing long and extensive wildfire seasons in the Western US emphasize the need for better understanding of wildfire impacts including post-fire management scenarios. Advancements in our understanding of post-fire hillslope erosion and watershed response such as flooding, sediment yield, and debris flows have recently received considerable attention. The potential impacts of removing dead trees, called salvage logging, has been studied, however the use of remotely sensed imagery after salvage logging to evaluate spatial patterns and recovery is novel. The 2015 North Star Fire provided an opportunity to evaluate hillslope erosion reduction using two field experiments and coincidental remotely sensed imagery over 3 years. Simulated rill experiments with four flow rates were used to quantify hillslope erosion on skidder trails with and without added logging slash compared with a burned-only control. Seven replicated hillslope silt fence plots with the same treatments were also evaluated for natural rainfall events. WorldView-2 satellite imagery was used to relate ground cover and erodible bare soil between the two experiments using multi-temporal Normalized Differenced Vegetation Index (NDVI) values. Results indicate that the skid trails produced significantly more sediment (0.70 g s⁻¹) than either the slash treated skid trail (0.34 g s⁻¹) or controls (0.04 g s⁻¹) with the simulated rill experiment. Similarly, under natural rainfall conditions sediment yield from hillslope silt fence plots was significantly greater for the skid trail (3.42 Mg ha⁻¹) than either the slash treated skid trail (0.18 Mg ha⁻¹) or controls (0 Mg ha⁻¹). An NDVI value of 0.32 on all plots over all years corresponded to a ground cover of about 60% which is an established threshold for erosion reduction. Significant relationships between NDVI, ground cover, and sediment values suggest that NDVI may help managers evaluate ground cover and erosion potential remotely after disturbances such as a wildfire or salvage logging.     

Applying Geography Course Projects to Issues in City Resilience and Global Connectivity

Globalization would appear to be a subject that easily could be addressed in geography classrooms, yet this is not always the case. In terms of pedagogy, many geographers are concerned whether the field has been adequately engaging various components of this topic (e.g., connectivity, core-periphery), especially in terms of making the subject matter relevant to students. This article presents the results of a recent course project situated at the intersection of city-level resilience to hazards and connectivity with the global economy, utilizing SWOT analysis. The student projects demonstrated that this comparatively simple analytical tool was a useful means for exploring and integrating key topics in globalization and urban-economic geography, while also facilitating a problem-based learning environment.     

Spatial Pair-Copula Modeling of Grade in Ore Bodies: A Case Study

A real-world mining application of pair-copulas is presented to model the spatial distribution of metal grade in an ore body. Inaccurate estimation of metal grade in an ore reserve can lead to failure of a mining project. Conventional kriged models are the most commonly used models for estimating grade and other spatial variables. However, kriged models use the variogram or covariance function, which produces a single average value to represent the spatial dependence for a given distance. Kriged models also assume linear spatial dependence. In the application, spatial pair-copulas are used to appropriately model the non-linear spatial dependence present in the data. The spatial pair-copula model is adopted over other copula-based spatial models since it is better able to capture complex spatial dependence structures. The performance of the pair-copula model is shown to be favorable compared to a conventional lognormal kriged model.     

High-resolution optical and infrared spectroscopic observations of Cir X-1

We present new optical and infrared (IR) observations of Cir X-1 taken near apastron. Both sets of spectra show asymmetric emission lines. Archival optical observations show that an asymmetric H α emission line has been in evidence for the past 20 years, although the shape of the line has changed significantly. We present an eccentric ( e ∼0.7–0.9) low-mass binary model, where the system consists of a neutron star orbiting around a (sub)giant companion star of 3–5 M_⊙. We suggest that the broad components of the emission lines arise in a high-velocity, optically thick flow near the neutron star, while the narrow components of the optical and the IR lines arise near the companion star and a heated ejecta shell surrounding the binary respectively. In this model, the velocity of the narrow component reflects the space velocity of the binary; the implied radial velocity (+430 km s⁻¹ after correcting for Galactic rotation) is the highest velocity known for an X-ray binary.     

MoisturEC: A New R Program for Moisture Content Estimation from Electrical Conductivity Data

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data‐analysis tools are needed to “translate” geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user‐friendly tools are required to fully capitalize on the potential of geophysical information for soil‐moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two‐ and three‐dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach.     

Deriving fragility functions from bilinearized capacity curves for earthquake scenario modelling using the conditional spectrum

The development of fragility curves to perform seismic scenario-based risk assessment requires a fully probabilistic procedure in order to account for uncertainties at each step of the computation. This is especially true when developing fragility curves conditional on an Intensity Measure that is directly available from a ground-motion prediction equation. In this study, we propose a new derivation method that uses realistic spectra instead of design spectral shapes or uniform hazard spectra and allows one to easily account for the features of the site-specific hazard that influences the fragility, without using non-linear dynamic analysis. The proposed method has been applied to typical school building types in the city of Basel (Switzerland) and the results have been compared to the standard practice in Europe. The results confirm that fragility curves are scenario dependent and are particularly sensitive to the magnitude of the earthquake scenario. The same background theory used for the derivation of the fragility curves has allowed an innovative method to be proposed for the conversion of fragility curves to a common IM (i.e. spectral acceleration or PGA). This conversion is the only way direct comparisons of fragility curves can be made and is useful when inter-period correlation cannot be used in scenario loss assessment. Moreover, such conversion is necessary to compare and verify newly developed curves against those from previous studies. Conversion to macroseismic intensity is also relevant for the comparison between mechanical-based and empirical fragility curves, in order to detect possible biases.